Molecular Genetic Studies of Psoriasis in Pakistani Population
By Saeeda Munir
Department of Biochemistry Faculty of Biological Sciences Quaid-i-Azam University Islamabad, Pakistan 2015
Molecular Genetic Studies of Psoriasis in Pakistani population
A thesis submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy
In
Biochemistry/Molecular Biology
By
Saeeda Munir
Department of Biochemistry Faculty of Biological Sciences Quaid-i-Azam University Islamabad, Pakistan
Dedicated
To
My beloved Parents
Mr. and Mrs. Muhammad Munir Malik
Whose best wishes, prayers and guidance at every
step made me achieve such a success in life
2015 Table of Contents
Acknowledgements……………………………………………………………………………………………………………. i
List of Figures…………………………………………………………………………………………………………………….iii
List of Tables...... iv
List of Abbreviations...... vi
Abstract ...... ix
Chapter 1
Introduction ...... 1
Epidemiology ...... 1
The Skin ...... 2
The Psoriasis Skin ...... 3
Clinical Features ...... 4
Types of Psoriasis ...... 6
Type I Psoriasis...... 6
Type II Psoriasis ...... 6
Triggering Factors ...... 6
Diagnosis ...... 7
Treatment ...... 7
Topical Therapy...... 7
Phototherapy ...... 8
Systemic Treatments ...... 8
Biological Agents ...... 9
Psoriasis as an Autoimmune Disease ...... 9
Psoriasis Immunology ...... 10
Genetics of Psoriasis ...... 12
Family and Twin Studies ...... 13
Inheritance Models ...... 13
Identified Psoriasis Susceptibility Locus (PSORS) ...... 14
Genetic Approaches to find associated genes in monogenic or complex disease…………………..33
Positional cloning…………………………………………………………………………………………………………………..33
Candidate gene approach………………………………………………………………………………………………………35
Aims of the Study ...... 37
Chapter 2
Materials and Methods ...... 40
Study Subjects...... 40
Extraction of Genomic DNA from Venous Blood Samples ...... 43
DNA Quantification ...... 44
HLA Typing ...... 44
Polymerase Chain Reaction with Sequence Specific Primers for HLA Class and Class II Typing 46
Agarose Gel Electrophoresis for HLA ...... 46
Meta-Analysis ...... 48
Genotyping of ACE I/D Polymorphism ...... 48
SNP Genotyping ...... 50
KASP Genotyping ...... 50
KASP genotyping Assay ...... 52
Statistical Analysis ...... 54
Chapter 3
Role of HLA allelic and haplotype polymorphism ...... 56
Introduction ...... 56
HLA Association with Psoriasis ...... 58
Results ...... 65
Association Analysis of HLA Class I and Class II Alleles...... 65
Haplotype Analysis of HLA Class I and Class II Alleles ...... 67
Meta-Analysis of HLA Class I and Class II Alleles ...... 67
Discussion ...... 81
HLA Class I And Class II Association with Psoriasis in Cases and Controls:...... 81
Association of HLA Class I and Class II Alleles with Type I and II Psoriasis ...... 82
Haplotype Analysis of HLA Class I and Class II Alleles ...... 84
Meta-Analysis of HLA Class I and Class II Alleles ...... 85
Chapter 4
ACE gene polymorphism study ...... 88
Introduction ...... 88
Results ...... 90
Discussion ...... 94
Chapter 5
Exploring the candidate and GWAS SNPs for association ...... 101
Introduction ...... 101
Selected genes for the Study ...... 102
Aims and Objectives of the Study: ...... 120
Results ...... 123
Discussion ...... 132
Chapter 6
Conclusion ...... 141
References...... 145
Appendix ...... 194
ACKNOWLEDGEMENTS
All praise for Almighty Allah (SWT) the most compassionate, the most beneficent and ever merciful, who gives me the power to do, the sight to observe and mind to think and judge. Peace and blessings of Almighty Allah (SWT) be upon His Prophet Hazrat Muhammad (P.B.U.H) who exhorted his followers to seek knowledge from cradle to grave.
I feel a deep sense of gratitude and indeptness to my dignified supervisor, Dr. Kehkashan Mazhar, PSO at Institute of Biomedical and Genetic Engineering (IB&GE).for her kind supervision, useful suggestions, consistent encouragement, friendly behavior and dynamic supervision which enabled me to complete this task successfully.
I would like to show my cordial gratitude to my respected co-supervisor Prof. Dr. Wasim Ahmad Professor, Department of Biochemistry, Quaid-i-Azam University, Islamabad who took me as her Ph.D. student, provided me an opportunity to work under his supervision and guided me at every step of my research.
I am highly obliged to Prof. Dr. Bushra Mirza, Chairperson, Department of Biochemistry, Quaid-i-Azam University, Islamabad, for her co-operation in providing me all possible facilities in this course of study.
I would like to thank Dr. Muhammad Ismail Director General IB&GE, for his kind suggestions and for providing me every facility during my research.
I am deeply obliged and thankful to Prof.Asa Torinsson Naluai (University of Gothenburg, Sweden) because of his kind and considerate suggestions during my IRSIP program.
Special thanks to Higher Education Commission, Pakistan for funding me by giving IRSIP scholarship.
I owe many thanks and appreciation to Dr. Sadia Rehman (PSO), Ms. Nusrat Saba (SSO), Dr. Saima siddiqui (SSO), Ms. Attiya Rubab and Sumera sajjad and other lab fellows at Institute of Biomedical and Genetic Engineering (IB&GE), Islamabad for their kind, caring attitude, valuable suggestions and encouragement throughout the study, they have made available their support in a number of ways to carry out the research work smoothly which would not have been possible without their support and guidance.
Heartfelt thanks are also extended to everyone in Biochemistry office specially Tariq Mehmood, Fayaz khan and Muhammad saeed for their cooperation and help in official documentation.
It would not have been possible to write this manuscript without help of my husband Mr. Asim Naseer and my children Ameena Asim and Mustafa. I am thankful to them for their help, entertainment and care they provided me.
Heartfelt gratitude for my beloved parents who always stood by me whenever I needed them and whose uninterrupted support in various aspects of my life and studies, kept me going with grace and honor under the shades of their prayers. I am grateful to my sisters Fatima, Khadija, Mariam, Rabeea. I am highly obliged to my brother Abdul Rehman whose inspiration and good wishes have always accompanied me.
May Almighty Allah shower His blessings and prosperity on all those who assisted me in any way during this research work.
Saeeda Munir
Abstract
Psoriasis is a chronic immune mediated skin disease characterized by inflammation and scaly lesions. It is regarded as a multifactorial disease due to involvement of both genetic and environmental factors in its pathogenesis. Though the major genetic factor for psoriasis susceptibility is believed to be the HLA locus on chromosome 6, but there is variation in reported loci and alleles for disease association. Other susceptibility loci have been identified through candidate gene approach and genome-wide linkage investigations. Current study was aimed to explore the genetic etiology of psoriasis in a
Pakistani population by genotyping allelic polymorphisms in the major genetic determinant and also to analyze single-nucleotide polymorphisms (SNPs) in previously reported candidate genes as well as other genome-wide associated markers.
Considering the importance of HLA in psoriasis pathogenesis, HLA class I and II alleles were genotyped in psoriasis patients and controls. Previously reported strong associations with HLA-B*57 and Cw*0602 were confirmed in the present study. Novel associations with HLA-A*3201, B*40, Cw*15 and DRB1*03 alleles previously not reported in any other population were also found. Haplotype and meta-analyses also confirmed previous findings along with some novel associations.
In second part of this study we analyzed ACE gene with variable reports of association in different populations. ACE I/D polymorphism was determined in patient and control groups and the data analyzed on the basis of psoriasis types, as well as gender. We observed significant association of the disease with genotype II and with allele I in both types of psoriasis. However, when analyzed on the basis of gender the association was
observed only in male patients and was absent in female psoriasis patients This study asserts the role of ACE in normal skin homeostasis.
In another comprehensive study, fifty seven single-nucleotide polymorphisms (SNPs) from 43 loci were genotyped. Our results showed genome wide significant association of the MHC region as well as nominally significant associations at ten other loci (p<0.05) in the studied Pakistani population including LCE3B, REL, IL13/IL4, TNIP1, IL12B,
TRAF3IP2, ZC3H12C, NOS2 and RNF114 from GWAS and PRR9 from a previous candidate gene study. The results indicate similar genetic risk factors and molecular mechanisms behind disease pathogenesis in Pakistani psoriasis patients as in other populations. Difference in results with some previous studies may be due to racial/geographical difference, genetic heterogeneity and multifactorial etiology of psoriasis.
The study gives a comprehensive overview of psoriasis genetics in Pakistani patients.
Association of multiple disease variants with susceptibility to psoriasis reflects the genetic heterogeneity of the disease. Moreover, some novel findings in Pakistani psoriasis patients along with some deviations from the reported studies depict that multiple genetic factors along with environmental triggers play their role in disease presentation and progression. These novelties may be population specific but the overall genetics of psoriasis is not different from the reported studies. Defining the genetic factors that are involved in pathogenesis of psoriasis in Pakistani population will help in better understanding of the underlying disease pathways. Further genotyping and expression studies are required to identify disease susceptibility genes and the underlying
network of molecular mechanisms. This will increase our understanding of disease etiology and will lead to ultimate benefit for patients. Introduction
1. Introduction
Psoriasis is a common, chronic and inflammatory skin disorder affecting approximately
1-3% of general population (Henseler, 1998; Kurd and Gelfand, 2009). Most common form of this disease is psoriasis vulgaris which is clinically characterized by well-defined red and scaly plaques on scalp, elbows and knees (Lomholt, 1963). Psoriatic scaly lesions are characterized by abnormal differentiation and hyper proliferation of keratinocytes.
Other cellular changes include inflammation due to increased infiltration of leukocytes and also poorly adherent stratum corneum that results in characteristic scales or flakes of the lesions (Krueger and Ellis, 2005). Psoriasis impairs quality of life, may often lead to hospitalization and can be fatal in rare instances. There is no curative treatment available for psoriasis; therapies used are mostly laborious and ineffective in a large number of patients with chances of some side effects.
1.1. Epidemiology
Psoriasis shows worldwide occurrence but its prevalence varies with ethnicity and geographical location. Low prevalence (0-0.3%) has been reported among Aboriginal
Australians, Asians, West Africans and native American Indians (Lomholt, 1963; Farber and Nall, 1974; Green, 1984; Yip, 1984; Krueger and Duvic, 1994; Leder and Farber,
1997; Gladman et al., 2005). Highest prevalence (5-10% of the population) has been reported in Europe including Norway and northernmost regions of Russia (Bhalerao and
Bowcock, 1998). Australia, Northern Europe, Scandinavia and United States have reported prevalence of 2-3%. Psoriasis occurs equally among both sexes (Lomholt, 1964) although women tend to develop psoriasis at an earlier age than men (Henseler, 1998). In Introduction
Pakistan no population based studies have been conducted to assess the prevalence of psoriasis, there is only sparse data from small hospital-based studies (Ejaz et al., 2013).
1.2. The Skin
Skin is the largest organ of human body, adult human carries approximately 3.6 kilograms (8 pounds) and 22 square feet (2 square meters) of skin. It forms a protective barrier over the body and helps in maintaining internal body environment. It also guards the body against external threats such as infections with microorganisms and mechanical injury. It also helps in regulating body temperature. Skin is composed of two primary layers: the epidermis and the dermis.
Epidermis forms the outermost layer of the skin and is mainly composed of keratinocytes that constitute about 95% of the epidermis. It is also composed of three specialized cells- the Merkel cells having sensory touch function (Moll et al., 2005), the Langerhans’ cells that play a role in immune function and the melanocytes responsible for skin pigment
(melanin) formation (Hunter et al., 1989; Bjerke, 2002). Keratinocytes generate antimicrobial proteins, polysaccharides, cytokines and cytokeratins and also take part in immune defense (Barker et al., 1991). Epidermis has five basic layers: Stratum corneum,
Stratum lucidum, Stratum granulosum, Stratum spinosum and Stratum basale (Candi et al., 2005). Keratinocytes are formed in the epidermal basement cell layer: startum basale and move towards the skin surface by new keratinocytes that grow from underneath and it roughly takes up to a month. During this procedure the nucleus is lost and the keratinocyte dies. Keratinocytes from the stratum corneum eventually shed from the skin surface. Introduction
Dermis is the skin layer present beneath the epidermis and consists of elastic tissue, collagen and thin arterial capillaries that carry oxygen and nutrition to the skin (Hunter et al., 1989). The dermis cushions the body from stress by providing elasticity and tensile strength to the skin through an extracellular matrix that is composed of microfibrils, elastic fibers and collagen fibrils embedded in proteoglycans (Breitkreutz et al.,
2009).The base layer of skin is the subcutaneous tissue, a fatty layer made up of looser tissues. It works as a fat storage and also serves the function of insulation for the body.
1.2.1. The Psoriasis Skin
Psoriatic lesion is characterized by red inflammatory and silvery scaly plaques. The redness is due to increased growth and dilation of superficial blood vessels leading to increased blood circulation and hence the redness of lesions (Braveman and Sibley,
1982). Scaling is formed by impaired differentiation and hyperproliferation of epidermal keratinocytes. The epidermal cell cycle in psoriatic skin is eight times shorter and the dividing cell population is two times greater than in normal skin (Weinstein et al., 1985).
A psoriatic keratinocyte lasts for only a few days while normal skin keratinocyte usually lives for 4-6 weeks (Liu et al., 2007). This short cell cycle results in incomplete keratinocyte differentiation with aberrantly retained intact nuclei (parakeratosis) and the release of few of the extracellular lipids that normally help in their binding (Bowcock and
Krueger, 2005). There is also inflammation in the epidermis. Lesions are rich in activated
CD4+ and CD8+ T cells that release proinflammatory cytokines and are typically distributed symmetrically on the scalp, elbows, knees and lumbosacral area (Christophers and Mrowietz, 1995; Ghoreschi et al., 2003).
1.3. Clinical Features Introduction
Psoriasis is an inflammatory disease in which the duration, degree, and morphological variants can differ significantly both between patients and within the same individual.
There are several clinical subtypes of psoriasis. Psoriasis vulgaris or chronic plaque psoriasis is the most common phenotype, accounting for 80-90% of cases (Lomholt,
1963). The shape and size of the plaques may differ to a great extent and they usually appear on the scalp, knees, elbows and lower back. Guttate psoriasis, originated from the
Greek word “gutta” which means droplet, characterized by the sudden onset of small drop like lesions, 1-10 mm in diameter. It appears rapidly often after a streptococcal throat infection and is seen mostly in children or adolescents (Telfer et al., 1992; Mallon et al., 2000) and the lesions are usually distributed over the trunk and proximal limbs.
Guttate psoriasis may often develop into chronic plaque form and patients with psoriasis vulgaris may also present with guttate flares (Martin et al., 1996; Naldi et al., 2001).
Inverse psoriasis is another type with non-scaling lesions, located in the groin and axillary regions, this form often coexists with chronic plaque psoriasis. Erythrodermic psoriasis, involves more than 90 percent of the skin surface. Pustular psoriasis can be of two types, palmoplantar psoriasis (PPP) that is localized on palms and soles; or generalized, with white, sterile pustules surrounded by red skin (Farber and Nall, 1993).
In addition, psoriasis can be associated with seronegative spondylo-arthropathy referred to as psoriatic arthritis (PsA) present in 5 to 20% of psoriatic patients with affected skin
(Lavaroni et al., 1994). Psoriasis of the nails is seen in 40-45 % of psoriasis patients
(Gladman et al., 1986). Psoriatic nail disease is often associated with PsA. Common characteristics of different subtypes are given in Table 1.1.
Table 1.1: Clinical characteristics of different phenotypes of Psoriasis. Introduction
Psoriasis Phenotypes Clinical Characteristics Most common form; shape and size of plaques vary; usually Plaque psoriasis located on scalp and extensor surfaces; scaling is typically absent Common in children and adults, often followed by streptococcal Guttate psoriasis throat infection; skin lesions are small and usually widely located on the upper trunk and extremities
Occurs as erythema e.g. in groin and axillary regions; scaling is Inverse psoriasis absent
Can cover almost the entire cutaneous surface of the body; can Erythrodermic be accompanied by systemic metabolic disturbances e.g. hypo- psoriasis albunemia
Sterile pustules in erythematous and scaly skin; localized or Pustular psoriasis generalized; also called palmar/plantar psoriasis
Joint damage; usually in the hands and feet but occasionally in Psoriatic Arthritis large joints
Thickened, yellowish finger or toe nails that may separate from Nail psoriasis the nail bed Introduction
1.4. Types of Psoriasis
Two clinical types of psoriasis have been described, based on the age of onset and familial clustering.
1.4.1. Type I Psoriasis
Type I psoriasis is the early onset type that begins before the age of 40. Majority of type I psoriatic patients have a positive family history; they tend to develop more severe disease and is reported to be associated with human leukocyte antigen-Cw6 (Henseler and
Christophers, 1985).
1.4.2. Type II Psoriasis
Type II psoriasis has a later onset that develops after the age of 40. This type is more sporadic, has minor hereditary association and is usually milder (Henseler and
Christophers, 1985; Swanbeck et al., 1995).
Of these two types, type I is more common world wide where the disease onset occurs before age 40 in 75% of all psoriasis patients (Gladman et al., 2005).
1.5. Triggering Factors
Psoriasis is a multifactorial disease and interaction of multiple genetic components and environmental factors are important in the disease pathogenesis (Elder et al., 2001).
Psoriasis can be triggered by several different environmental factors. Koebner phenomenon (skin trauma), throat infection with streptococci, acute viral infections and local skin infections with staphylococcus aureus or Candida albicans can trigger or worsen psoriasis (Koebner, 1872; Lindegard 1986; Telfer et al., 1992; Rosenberg et al.,
1994; Naldi et al., 2001). HIV infection has also been shown to aggravate psoriasis
(Mallon et al., 1998). Psoriasis can also be triggered by drugs such as lithium, beta- blockers, anti malarials and also after withdrawal of steroid treatment (Abel et al., 1986). Introduction
Smoking, Stress and alcohol are common environmental factors that can induce psoriasis
(Ockenfels, 2003). UV light has been shown to exacerbate psoriasis (Ros and Eklund,
1987) although controlled UV light also has a clear beneficial effect in majority of the cases and is often used as a treatment modality (Krueger and Ellis, 1995).
1.6. Diagnosis
Diagnosis of psoriasis is usually based on the clinical presentation on the skin characterized by silvery and scaly patches usually localized on elbow, knees and back. In rare cases, a small sample of skin, called a biopsy, is suggested to determine the exact type of psoriasis and to rule out other skin disorders, such as lichen planus, lichen simplex, seborrhoeic dermatitis, and pityriasis rosea. In case of psoriatic arthritis, which is sometimes a complication of psoriasis, blood tests are carried out to exclude other conditions such as rheumatoid arthritis and X-rays of the affected joints may be taken.
1.7. Treatment
Currently there is no cure for psoriasis. The objective of psoriasis treatment is lowering of symptoms of the disease to a manageable level with minimal toxicity. Three types of therapies, alone or in combination can be used: topical agents, appropriate wavelengths of
UV radiation and systemic medications.
1.7.1. Topical Therapy
Topical treatments are most widely used in psoriasis and most common are the Vitamin
D3 analogues and corticosteroids (Van de Kerkhof et al., 2000). These tend to slow down the epidermal proliferation and decrease the accumulation of inflammatory cells. Side effects with the use of corticosteroids are skin atrophy and also systemic effects such as iatrogenic Cushing’s syndrome and hypothalamic-pituitary adrenal axis suppression Introduction
(Bruner et al., 2003).Vitamin D3 derivatives lack the risks associated with corticosteroids but have slow onset of action and cause skin irritation in about 20-25 % of users. Other therapeutically active topical agents licensed for psoriasis include coal tar, dithranol and tazarotene (a retinoid).
1.7.2. Phototherapy
When topical therapy is inadequate the treatment is usually combined with phototherapy.
The most common forms of phototherapy are ultraviolet B (UVB) and Psoralen plus ultraviolet A (PUVA). The mechanism of action is the production of photoproducts that inhibit epidermal proliferation and induce DNA damage, especially T cells and keratinocytes are susceptible to UVB and PUVA induced apoptosis (Krutmann, 1998).
Both treatments have proven extremely effective for psoriasis but premature ageing of the skin, erythema and increased risk of skin cancers are the associated side effects (Mckenna and Stern, 1995).
1.7.3. Systemic Treatments
Systemic treatment is used in patients with moderate to severe psoriasis as well as in those unresponsive to other therapies. The two most common systemic drugs are methotrexate and acitretin. Methotrexate is a folic acid antagonist that interferes with purine synthesis and inhibits DNA synthesis and cell replication. It also has a specific T cell-suppressive activity. It is teratogenic and can cause severe side effects such as liver fibrosis and bone marrow suppression. Acitretin normalize the keratinocyte differentiation and proliferation by binding to retinoid receptors, there by altering gene transcription. It is also teratogenic and can cause mucocutaneous side effects resembling hypervitaminosis A, hyperlipidemia, osteoporosis and skeletal abnormalities. Introduction
1.7.4. Biological Agents
In severe psoriasis biological therapies have been approved as treatment choice recently during the past 3 years. Biological agents are proteins or antibodies that target specific molecules that are important in psoriasis pathogenesis. There are two groups of biological agents, T-cell agents, including Alefacept and Efalizumab, and TNFα inhibitors, including Etanercept, Infliximab and Adalimumab. They have been well tolerated in clinical practice but the main issue is their long-term chronic immunosuppression which may facilitate infection and increase the risk of cancer.
1.8. Psoriasis as an Autoimmune Disease
Autoimmune diseases are characterized by the presence of autoantibodies and/or autoreactive T cells to a specific antigen within a target organ (Eisenberg, 2003).
Psoriasis is considered to be a T lymphocyte-mediated autoimmune disease, although no epidermal autoantigens have been identified (Horrocks et al., 1997). The fact that supports this classification stems from the positive effects of immunosuppressing drugs in clinical studies (Bowcock and Krueger, 2005). The identification of clonal populations of T cells within intact skin lesions (Prinz et al., 1999; Vollmer et al., 2001) and studies of human skin xenografts in mice (Nickoloff, 2000) strongly support immune-mediated pathogenesis.
1.8.1. Psoriasis Immunology
Like many other autoimmune/inflammatory diseases, psoriasis is driven and maintained by multiple components of the immune system, which consist of an innate and an adaptive part. The innate system responds first to an infection and is mediated by macrophages, neutrophils, mast cells, dendritic cells, natural killer cells, eosinophils and Introduction basophils. They recognize and respond to pathogens in a non-specific manner. This system is present from birth but has no memory and hence does not confer long-lasting protective immunity to the host. Adaptive immunity is in contrast, a highly specialized system. It recognizes non-self-antigens and eliminates specific pathogens or pathogen infected cells, develop an immunologic memory and is mainly mediated by B and T lymphocytes.
Psoriasis is considered to be a T cell mediated disease (Ortonne, 1999). There is a mixture of innate immune cells, T cells and pro-inflammatory cytokines and chemokines in fully developed psoriatic skin lesions. B lymphocytes are the major cells involved in the formation of antibodies. There are two main types of T cells, helper T cells and cytotoxic T cells (Gaspari, 2006).
Pathogenesis of psoriasis is initiated when an antigen-presenting cell (APC) from the epidermis or dermis captures an antigen and becomes activated. No specific antigen for psoriasis has been identified yet, however, different antigens have been suggested, including self-polypeptides for instance heterogeneous nuclear ribonucleoprotein-A1
(hnRNP-A1) (Jones et al., 2004) and keratin 13 (K13) (Sigmundsdottir et al., 1997).
Other antigens that have been suggested are microbial agents, such as retrovirus (HIV)
(Mahoney et al., 1991), Streptococcal M protein (Sigmundsdottir et al., 1997), human papillomavirus (Favre et al., 1998) and microbial super antigens (a group of bacterial and viral proteins characterized by their capacity to stimulate a large number of T cells simultaneously (Baker et al., 1993; Rosenberg et al., 1994; Valdimarsson et al., 1995). A molecular mimicry hypothesis exists in which bacterial antigens and skin determinants Introduction have similar epitopes, causing the immune system to cross-react and induce an immune reaction to the self-peptide, creating an autoantigen (Christen and Von Herrath, 2004).
Activated APCs move to the peripheral lymph nodes where they activate immature CD4
(cluster of differentiation 4) or CD8 T (cluster of differentiation 8) cells. Activation includes presentation of the antigen to T cell receptor (TCR) on the T cell (MHC class I present the intracellular antigens and MHC class II present the extracellular antigens on the APC). T cell activation increases with increased synthesis of cell surface counter receptors (i.e., CD86, CD80, CD40, LFA-3 and CD54) in a maturation process. As T cell activation occurs, two distinct lines of differentiation are possible. T helper 1 (Th1) cells develop under the influence of IL-12 and IFN-γ, take part in cell-mediated immunity and are responsible for controlling intracellular pathogens such as viruses. They secrete type
1 cytokines, including IL-2, TNF-α and IFN-γ (Austin et al., 1999; Bonifati et al., 1999;
Nishibu et al., 1999). T helper 2 (Th2) cells develop under the influence of IL-4, IL-6 and
IL-10. They help B cells and are thus important for antibody-mediated immunity required to control extracellular pathogens such as bacteria. Th2 cells secrete type 2 cytokines including IL-4, IL-6, IL-10, and IL-11.
Psoriasis is considered to be a type I disease, characterized by type 1 cytokines and a predominance of CD4 T cells in the dermis and CD8 cells in the epidermis (Uyemura et al., 1993; Schlaak et al., 1994). These are released at the site of inflammation in the skin, aided by the activated T cell expressing a new surface protein known as cutaneous lymphocyte-associated antigen (CLA). CLA helps T cell to bind to endothelium in the cutaneous post capillary venules by interacting with E-selectin and P-selectin which are over-expressed on cutaneous micro vessels during inflammation (Picker et al., 1991; Introduction
Fuhlbrigge et al., 1997). T cells can finally enter the skin after binding to ICAM-1 and
VCAM-1 on the blood vessels with LFA-1 and VLA-4 integrins (Lee and Cooper, 2006).
The released cytokines from the migrating epidermal lymphocytes disrupt the basement membrane and desmosome connections between adjacent keratinocytes. The overall result is increased proliferation of keratinocytes manifested by elongation of rete ridges, loss of granular layer, parakeratosis and endothelial hyper proliferation (Krueger, 2003;
Lebwohl, 2003).
1.9. Genetics of Psoriasis
Several epidemiological and genetic reports based on family and twin studies provide strong evidence that genetic component is present in psoriasis pathogenesis but segregation of psoriasis in most pedigrees does not obey simple Mendelian laws. Further support for the genetic basis of psoriasis has come from linkage analyses where several susceptibility loci for psoriasis have emerged, and also from the HLA association studies. Introduction
1.9.1. Family and Twin Studies
Inheritance of psoriasis was observed for the first time by Willan (Willan, 1801). After that in a classical epidemiological study of the Faroe Islands, Lomholt observed that incidence of psoriasis was greater amongst first-and second-degree relatives of psoriatic patients than unaffected control subjects (Lomholt, 1963). Later studies in other populations confirmed this finding and estimated that there is approximately 24 to 28% lifetime risk of developing psoriasis in the first degree relatives (Farber and Nall, 1974;
Melski and Stern, 1981; Brandrup, 1984; Swanbeck et al., 1994, 1997).
Studies of twins have also indicated a strong genetic predisposition to psoriasis.
Monozygotic (MZ) twins have identical genomes while dizygotic (DZ) twins share only half of their genomes. MZ twins have a concordance rate of 35-72% compared with the
14-23% concordance rate of DZ twins further supporting the genetic background of psoriasis (Farber and Nall, 1974; Brandrup et al., 1982; Duffy et al., 1993). Heritability for psoriasis, h2 (the proportion of phenotypic variation of a trait attributable to genetic variability), has been estimated at between 60% and 90%, highest among all the multifactorial genetic disorders (Elder et al., 2001). These observations show that genetic factors are involved in development of psoriasis; however concordance rate in MZ twins never reaches 100% which implicates that environmental factors play some role in triggering psoriasis.
1.9.2. Inheritance Models
Several models for inheritance of psoriasis have been proposed. Some of the first studies suggested a dominant mode of inheritance with incomplete penetrance (Abele et al.,
1963). Researchers have been trying to fit psoriasis into a mode of inheritance using Introduction
Mendelian models e.g. autosomal dominant with incomplete penetrance and recessive mode of inheritance (Nair et al., 1995). Other suggestions include genetic heterogeneity, where one or more different genetic factors cause the same phenotype, and multifactorial inheritance, where a combination of genetic factors and external triggers influence the onset and development of the disease (Lomholt, 1963; Burch and Rowell, 1965; Nair et al., 1995). Currently the common belief is that psoriasis follows a multifactorial mode of inheritance (Henseler, 1998; Barker, 2001; Elder et al., 2001; Bowcock and Barker,
2003).
1.9.3. Identified Psoriasis Susceptibility Locus (PSORS)
Genetic contribution to psoriasis has been extensively described and at least 20 different psoriasis susceptibility loci have been identified (Bowcock and Cookson, 2004). Nine of these regions have yielded strong enough results to be designated as psoriasis susceptibility loci (PSORS1-9). Additional loci on 2p, 4q13, 4q21, 6q, 7, 8q24, 11p13,
14q31-32, 15q, 18p11 and 20p have also been indicated (Nair et al., 1997; Trembath et al., 1997; Bhalerao and Bowcock, 1998; Samuelsson et al., 1999; Veal et al., 2001
Asumalahti et al., 2003; Karason et al., 2003).
PSORS1
The PSORS1 (psoriasis susceptibility 1) locus at 6p21.3 is the major susceptibility locus for psoriasis and is the most consistently replicated of all loci. It is estimated that this locus accounts for 30% to 50% of the genetic predisposition to psoriasis (Trembath et al.,
1997) and is located within the MHC. In linkage studies of different populations, significant linkage to the PSORS1 locus has been reported (Nair et al., 1997; Trembath et al., 1997; Burden et al., 1998; Samuelsson et al., 1999; Lee et al., 2000; Veal et al., Introduction
2001). Best-known genes in the MHC region are the subsets that encode cell-surface antigen-presenting proteins, HLA. Strong association of HLA-Cw6 with psoriasis was reported as early as over 26 years ago (Tiilikainen et al., 1980). This association is particularly strong in patients with a young age at onset (Henseler and Christopher,
1985). However, proof of this association is still lacking due to the extensive linkage disequilibrium (LD) across the class I region, resulting in the existence of particularly strong extended haplotypes. It is thus unclear whether this allele is the predisposing psoriasis gene or simply a marker in strong LD with the true disease gene (Jenisch et al.,
1999; Nair et al., 2000; Veal et al., 2002; Gudjonsson et al., 2004).
The PSORS1 locus was further refined by association analyses with densely spaced markers across the MHC region (Balendran et al., 1999; Oka et al., 1999; Nair et al.,
2000). Based on these studies, the psoriasis susceptibility gene in PSORS1 locates most likely in a region of approximately 200 kb telomeric to HLA-C. Eight genes have been identified in this region: HLA-C, TCF19 (SCI), OTF3 (POU5FI), HCR (Pg8), CDSN,
SEEK1, SPR1, and STG (Zhou and Chaplin, 1993; Krishnan et al., 1995; Guillaudeux et al., 1998; Oka et al., 1999; Holm et al., 2003; Chang et al., 2003a), shown in Figure. 1.
Introduction
Figure 1: Map of the PSORS1 locus, with different PSORS1 regions refined in different studies (Bowcock and Barker, 2003). Introduction
HCR
HCR (alpha-helix coiled-coil rod homologue, Pg8) was first predicted by Guillaudeux and later verified and renamed by Oka (Guillaudeux et al., 1998, Oka et al., 1999). It has structural homologies to laminin, myosin, plectin and trichohyalin genes. HCR is highly polymorphic with 12 SNPs, two of these showed association with psoriasis (Asumalahti et al., 2000). HCR mRNA was expressed in psoriatic skin making HCR an appealing candidate gene (Asumalahti et al., 2000).
CDSN
CDSN (corneodesmosin) is another putative candidate gene for psoriasis. It is expressed at the late stages of keratinocyte differentiation in cornified squamous epithelia (Zhou and Chaplin, 1993). It is also expressed differently in psoriatic skin and in normal skin
(Allen et al., 2001). Significant association was observed with three non-synonymous
CDSN SNPs (CDSN-619, -1240, -1243, collectively termed CDSN*5) and psoriasis in a
TDT (transmission disequilibrium test) analysis (Allen et al., 1999). The CDSN association with psoriasis has been confirmed, but in tight LD with HLA-Cw*0602
(Jenisch et al., 1998). Other genes in the region have proved to be less tempting candidate genes for psoriasis.
OTF3
OTF3 (octamer-binding transcription factor 3) is a POU transcription factor important in embryogenesis and thus major changes in this gene would probably be lethal (Niwa et al.,
2000). The beta-allele of OTF3 has been shown to be associated with psoriasis, but in strong LD with the HLA-Cw*0602 allele (Gonzalez et al., 2000).
TCF19 Introduction
TCF19 (transcription factor 19) have an important function in cell regulation (Ku et al.,
1991). It is involved in the transcription of genes required for the later stages of cell cycle progression (Ku et al., 1991). No disease-specific variants have been found in this gene
(Nair et al., 2000).
SPR1
SPR1 (small Proline-Rich Protein 1) has four amino acid changing SNPs, but in a
Chinese population no difference was observed between patients vs controls and HLA-
Cw*0602 remained the major risk allele (Chang et al., 2003a). In Swedish patients, one of the four SNPs showed association but this was Cw*0602 dependent (Holm et al.,
2003).
SEEK1
In SEEK1 (specific expression in epidermal keratinocyte 1), five SNPs were shown to be associated with psoriasis in Swedish patients, two of which even showed Cw*0602 independent association. These SNPs were located, however, in the second exon of
SEEK1, which seems to be un-translated (Holm et al., 2003). Both SPR1 and SEEK1 are expressed in skin.
STG
STG (serotonin transporter gene) still remains a poorly characterized gene. Studies using large number of patients that carry only portion of the ancestral PSORS1 risk haplotype have shown that the location of PSORS1 is closer to the HLA-C/HLA-B region, excluding
CDSN and HCR (Helms et al., 2005; Nair et al., 2006). However, since the penetrance of the strongest associated allele at this locus, HLA-Cw*0602 (Nair et al., 2006) is only Introduction about 10% it is apparent that other genetic variants or environmental factors are important for disease pathogenesis (Elder et al., 2001; Bowcock and Cookson, 2004).
Other PSORS Loci
Several genome-wide scans have been performed in order to find new loci for psoriasis susceptibility. These linkage studies have identified multiple loci in different populations
(Table 1.2). Introduction
Table 1.2: Summary of Psoriasis Susceptibility Loci by Genome Wide Linkage Scans. Locus Location Genes Funtions References HLA C: Antigen presentation; TCF19: role in transcription of genes required for later stages of Trembath et al., 1997; cell cycle progression; OTF3: Critical for early HLA-C, TCF19 (SCI), Nair et al., 1997; embryogenesis; HCR: keratinocyte OTF3 (POU5FI), HCR Jenisch et al., 1998; PSORS1 6p21.3 differentiation; CDSN: maintain epidermal (Pg8), CDSN, SEEK1, Enlund et al., 1999; barrier integrity; SEEK1: role in immune SPR1, and STG Samuelsson et al., system; SPR1: involved in microtubule 1999; Oka et al., 1999 polymerization; STG: required for glutamate receptor function
SLC9A3R1(solute- SLC9A3R1: interacts with and regulates various carrier family 9 isoform proteins, NAT9: participates in the detoxification Tomfohrde et al., 1994; 3 regulator 1) and NAT9 of a plethora of hydrazine and arylamine drugs; Nair et al., 1997; PSORS2 17q24-25 (N-acetyl transferase 9), RAPTOR encodes a component of a signaling Enlund et al., 1999; RAPTOR (Regulatory pathway that regulates cell growth in response Samuelsson et al., 1999 Associated Protein of to environmental stimuli MTOR, Complex 1)
IRF2 competitively inhibits the IRF1-mediated PSORS3 4q34 IRF2 transcriptional activation of interferons alpha Matthews et al., 1996 and beta epidermal Play an important role in terminal differentiation Bhalerao and Bowcock, PSORS4 1q21 differentiation complex of the human epidermis 1998 (EDC) genes
Table 1.2 Continued…….
Introduction
Locus Location Genes Funtions References Cation/chloride cotransporter that may play a Samuelsson et al., PSORS5 3q21 SLC12A8 role in the control of keratinocyte proliferation 1999, Veal et al., 2001 Transcription factor involved in regulating gene PSORS6 19p13 JunB activity following the primary growth factor Lee et al., 2000 response Involved in cell growth regulation, in the regulation of mitogenic signals and control of PSORS7 1p35-p34 EPS15 cell proliferation and in the internalization of Veal et al., 2001 ligand-inducible receptors of the receptor tyrosine kinase (RTK) Plays a role in the immune response to NOD2 (nucleotide- intracellular bacterial lipopolysaccharides (LPS) binding oligomerization Nair et al., 1997, PSORS8 16q12-q13 by recognizing the muramyl dipeptide (MDP) domain containing 2) Karason et al., 2003 derived from them and activating the NFKB /CARD15 protein. PSORS9 4q31 IL-15 Stimulates the proliferation of T-lymphocytes. Yan et al., 2007 PSORS10 18p11 Asumalahti et al., 2003
Introduction
PSORS2, 17q25
This locus, on chromosome 17q25, was the first non-MHC locus found to confer susceptibility to psoriasis (Tomfohrde et al., 1994). Linkage at this locus has also been confirmed by several other groups (Matthews et al., 1996; Nair et al., 1997; Enlund et al.,
1999). There are two distinct loci within PSORS2. One locus includes the solute-carrier family 9 isoform 3 regulator 1 (SLC9A3R1) and N-acetyl transferase 9 (NAT9) genes, both of which encode proteins that play a role in negatively regulating immune cell activation. A common haplotype that carries SLC9A3R1 and NAT9 is associated with susceptibility to psoriasis (Helms et al., 2003). One psoriasis-associated allele from this five-marker haplotype leads to loss of a putative site for the runt related transcription factor (RUNX) family of transcription factors. RUNX1 sites have been associated with various autoimmune diseases that show its important role in tolerance. The second, more distal locus within PSORS2 encodes regulatory associated protein of mammalian target of rapamycin (RAPTOR). RAPTOR is a serine/threonine protein kinase that regulates cell growth and proliferation in response to environmental stimuli such as growth factors, mitogens or cytokines. It is a target for immunosuppressive drugs. Intronic SNPs have been shown to be associated with psoriasis and are therefore likely to be regulatory
(Helms et al., 2003).
PSORS3, 4q34
A genome wide scan was performed in six of the 17 q unlinked multiplex Irish families and found evidence of linkage to 4q34 (Matthews et al., 1996). The maximum total pairwise LOD score obtained with the microsatellite marker D4S1535 at theta = 0.08 was
3.03 (Matthews et al., 1996). IRF2 (Interferon regulatory factor 2) gene is located within Introduction this locus. Association of IRF2 with type 1 psoriasis was detected for two markers in the
IRF2 (Foerster et al., 2004).
PSORS4, 1q21
In Italian families, the genome-wide scan and fine mapping showed evidence for linkage at chromosome 1q21 (Capon et al., 1999; Capon et al., 2001). D1S305 marker gave the highest two-point LOD score (3.75, θ= 0.05). The same region had been identified with families from the USA (Bhalerao and Bowcock, 1998). PSORS4 resides within the region of epidermal differentiation complex, a cluster of at least 20 genes expressed during epithelial differentiation. Fine mapping of this region localized the susceptibility gene to the genomic interval spanned by D1S2346 and 140J1D (Capon et al., 2001).
Further refinement of this locus revealed a 100 kb region containing only the loricrine
(LOR) gene. The gene was ruled out as a candidate gene for the PSORS4 locus as no association could be detected (Giardina et al., 2004). Later studies have also reported involvement of other genes within this region, e.g. S100A8, S100A9, PGLYRP3 and
PGLYRP4 (Zenz et al., 2005; Sun et al., 2006).
PSORS5, 3q21
Two genome-wide scans in Swedish families suggested linkage at 3q21 (Enlund et al.,
1999, Samuelsson et al., 1999). The locus was narrwed to a 250-kb interval by TDT analysis (Hewett et al., 2002). SLC12A8 is present in this region which is a member of the solute carrier 12 family. An association was found with a five-marker haplotype of this gene (Hewett et al., 2002). Association with SLC12A8 has also been confirmed in a
German study (Huffmeier et al., 2005), however no association was detected in US families (Bowcock and Baker, 2003). Introduction
PSORS6, 19p13
A new susceptibility locus on chromosome 19p13 was identified by linkage analysis of
32 German extended families (Lee et al., 2000). An association scan of this region revealed both a protective and a susceptibility locus (Hensen et al., 2003). JunB, a gene within PSORS6, has been reported to show decreased expression in epidermal keratinocytes in psoriatic lesions (Zenz et al., 2005). It has also been shown that 100% of
JunB/c-Jun double-mutant mice have a psoriasis-like phenotype (Zenz et al., 2005).
PSORS7, 1p35-34
In a genome wide linkage analysis of families from Britian a novel locus at 1p35-p34 was identified (Veal et al., 2001). EPS15 that encodes an intracellular substrate for the EGF receptor is located in the defined region and is over expressed in psoriatic epidermis
(Veal et al., 2001).
PSORS8, 16q12-q13
In a genome wide scan suggestive linkage was found on chromosome 16p (Nair et al.,
1997). This linkage was also indicated in a subsequent analysis of affected sibling pairs by the International Psoriasis Genetics Consortium, especially when analyzing only those families carrying either of two psoriasis-associated MHC haplotypes. This locus contains
NOD2/CARD15 gene. This locus has later been identified when searching for a genetic locus for psoriatic arthritis and paternal transmission has been shown from this region
(Karason et al., 2003).
PSORS9, 4q31
In a genome-wide scan in the Chinese Han population a new psoriasis locus was identified at 4q 31 (Yan et al., 2007). This region was also recorded in a meta-analysis Introduction using the results of six genome-wide studies (Sagoo et al., 2004). IL-15 has been identified as a strong candidate gene for psoriasis in this region and significant association was identified at the 3’-untranslated region (UTR) of the IL-15 gene. It was also shown that the identified risk haplotype is associated with increased IL-15 activity
(Zhang et al., 2007).
PSORS10, 18p11
In a genome wide scan and fine mapping of 9 Finnish families with psoriasis, a locus for psoriasis susceptibility was identified on chromosome 18p11.23 (nonparametric multipoint linkage analysis score of 3.58 between markers D18S63 and D18S967
(Asumalahti et al., 2003).
Introduction
Table 1.3: Reported Genetic Contributors of Adaptive, Innate Immunity and Skin Barrier Pathways in Psoriasis. Gene/Locus Description Locus Expression Functions References Population
Macrophages, Maturation Of IL-23R IL-23 receptor subunit 1p31.3 Cargill et al., 2007 Caucasian dendritic cells T cells
runt-related transcription regulate T-cell RUNX3 1p36.11 Tsoi et al., 2012 Caucasian factor 3 function Receptor for Lymph, IL-28RA IL-29 receptor subunit 1p36.11 IL-28A, IL- Strange et al., 2010, Caucasian lymph node 28B, and IL-29 Facilitates the solute carrier family 45, uptake of SLC45A1, Tumor necrosis factor Brain, T cells, glucose, role in 1P36.23 Tsoi et al., 2012 Caucasian TNFRSF9 receptor superfamily heart. generation of member 9 memory CD8+ T-cells. Epithelia and LCE3B and Late cornified envelope Barrier de Cid et al., 2009; Caucasian, 1q21.3 lesional PS LCE3C 3B and 3C function skin Chen et al., 2009 Chinese skin Member of heart, ovary, EDC(epidermal Singaporean PRR9 Proline rich region 9 1q21.3 colon and Chen et al., 2009 differentiation Chinese testis complex) Blood, Transcription v-rel reticulo intestine, factor, member REL endotheliosis viral 2p13 Strange et al., 2010 Caucasian larynx, lymph of the REL/NF- oncogene homolog node, thyroid κB family Table 1.3 Continued …
Gene/Locus Description Locus Expression Functions References Population Introduction
catalyzes the UDP-GlcNAc: beta Gal initiation and beta-1,3-N-acetyl elongation of B3GNT2 2p15 Ubiquitous Tsoi et al., 2012 Caucasian glucosaminyl transferase poly-N-acetyl 2 lactosamine chains Cation/chloride cotransporter, Solute carrier family 12, Generally Huffmeier et al., SLC12A8 3q21 involved in Caucasian member 8 expressed 2005 keratinocyte differentiation Peptide Endoplasmic reticulum Generally Zhang et al., 2009; Caucasian, ERAP1 5q15 trimming of amino peptidase 1 expressed Sun et al., 2010 Chinese antigens Modulate humoral Nair et al., 2009; Caucasian IL-4, IL-13 IL-4, 13 5q31.1 Th2 cells immune Sun et al., 2010 Chinese response NK, Maturation Of Tsunemi et al.,2002, Caucasian, IL-12B IL-12/23, subunit p40 5q31.1-33.1 monocyte, T cells Nair et al., 2009, Chinese dendritic cells Ubiquitously, Regulation of Nair et al., 2009, TNAIP3-interacting lymphocytes, Caucasian TNIP1 5q32-33.1 NF-κB Strange et al., 2010, protein 1 and skeletal Chinese signaling Sun et al., 2010 muscle Table 1.3 Continued …
Gene/Locus Description Locus Expression Functions References Population Pituitary tumor Generally control mitosis, PTTG1 5q35.1 Sun et al., 2010 Chinese transforming gene expressed DNA repair, Introduction
and gene regulation Important pro inflammatory Li et al., 2002 TNF-α Tumor necrosis factor-α 6p21 Immune cells cytokine Caucasian
involved in psoriasis Epidermis, Component of Caucasian, CDSN Corneodesmosin 6p21 upregulated in the cornified Guerrin et al., 2001; Chinese psoriasis envelope Involves in the docking of Exocyst Complex Lymphoid exocytic EXOC2 6p25.3 Tsoi et al., 2012 Caucasian Component 2 cells vesicles to the plasma membrane involved in TRAF3-interacting Generally regulation of TRAF3IP2 6q21 Strange et al., 2010 Caucasian protein 2 expressed adaptive immunity
Human leukocyte Nucleated Antigen Trembath et al., Caucasian, HLA 6p21.33 antigen cells presentation 1997 Chinese
Table 1.3 Continued …
Gene/Locus Description Locus Expression Functions References Population Epithelia and NF-κB Tumor necrosis factor- Strange et al., 2010, TNFAIP3 6q23.3 lymphoid signaling Caucasian α-induced protein 3/A20 Sun et al., 2010 tissues inhibition Introduction
T-Cell Activation Rho Generally T cell TAGAP GTPase Activating 6q25.3 Tsoi et al., 2012 Caucasian expressed activation Protein IFN-α Engulfment And Cell Widely induction by ELMO1 7p14.1-14.2 Tsoi et al., 2012 Caucasian Motility expressed, plasmacytoid dendritic cells Antimicrobial DEFB β-Defensins 8p23.1 Epithelium & chemotactic Hollox et al., 2008 Caucasian cluster functions skin and CUB and Sushi multiple Tumor CSMD1(WG) 8p23.2 epithelial Sun et al., 2010 Chinese domains 1 repressor gene cells Present in nterferon- DEAD (Asp-Glu-Ala- vascular mediated DDX58 Asp) Box Polypeptide 9p21.1 smooth cells Tsoi et al., 2012 Caucasian antiviral 58 (at protein responses level) Regulates colon, testis, KLF4 Kruppel-Like Factor 4 9p31.2 signaling Tsoi et al., 2012 Caucasian lung and skin pathways prostate, regulates Zinc Finger, MIZ-Type ZMIZ1 10q22.3 spleen and transcription Tsoi et al., 2012 Caucasian Containing 1 testis. factors Table 1.3 Continued …
Gene/Locus Description Locus Expression Functions References Population
Widely Intracellular Ellinghaus et al., PRDX5 Per oxiredoxin 5 11q13 Caucasian expressed redox signaling 2012 Zinc Finger CCCH-Type Widely May function ZC3H12C 11q22.3 Tsoi et al., 2012 Caucasian Containing 12C expressed as RNase Introduction
V-Ets Avian Chemokine & Erythroblastosis Virus lymphoid ETS1 11q24.3 Cytokine genes Tsoi et al., 2012 Caucasian E26 Oncogene Homolog cells. expression 1 IL-23, Signal transducer Regulation of Monocytes & Nair et al., 2009; IL-23A/STAT2 and activator of 12q13.2 T-cell Caucasian dendritic cells Strange et al., 2010; transcription 2 activation EGFR brain, heart, (epidermal ATXN2 Ataxin 2 12q24.12 liver, muscle growth factor Liu et al., 2008 Caucasian and, pancreas receptor) trafficking Involved in Gap junction protein β2, GJB2 13q11-q12 Skin gap junction Sun et al., 2010 Chinese connexin 26 formation NF of kappa light Ellinghaus et al., polypeptide gene Generally Inhibiting NF- NFKBIA 14q13.2 2010; Strange et al., Caucasian enhancer in B cells expressed κB signaling 2010 inhibitor, alpha Epithelia, F-box and leucine-rich activates NF- FBXL19 16p11.2 lymph & Stuart et al., 2010 Caucasian repeat protein 19 κB brain Table 1.3 Continued …
Gene/Locus Description Locus Expression Functions References Population Cytokine Suppressor Of Cytokine Widely SOCS1 16p13.13 signal Tsoi et al., 2012 Caucasian Signaling 1 expressed transduction Nitric oxide synthase 2, Immune Immune NOS2 17q11.1 Stuart et al., 2010 Caucasian inducible system defense Introduction
Dissociation of Polymerase I and Widely the ternary PTRF, 17q21.2 Tsoi et al., 2012 Caucasian transcript Release Factor expressed transcription complex. Controls blood Angiotensin I Ubiquitously pressure and Weger et al., 2007; Caucasian, ACE 17q23 Converting Enzyme expressed electrolyte Chang et al., 2007 Chinese balance. activates NF- epithelial Caspase Recruitment κB signaling, tissues, CARD14 Domain Family, 17q25.3 protects cells Tsoi et al., 2012 Caucasian placenta and Member 14 against leukocytes apoptosis STARD6: transport of STARD6: (StAR- STARD6: lipids, POLI: Related Lipid Transfer Kidney, liver; hyper-mutation STARD6, POLI 18q21.2 Tsoi et al., 2012 Caucasian Domain Containing 6); POLI: of POLI: (Polymerase Iota) Ubiquitous. immunoglobuli n genes and in DNA repair
Table 1.3 Continued …
Gene/Locus Description Locus Expression Functions References Population Skin, vascular Serpin peptidase Serine tissue, SERPINB8 inhibitor clade B 18q21.3 proteinase Sun et al., 2010 Chinese connective member 8 inhibitor tissue, Introduction
Regulatory function, Generally ZNF816A(WG) Zinc-finger protein 816A 19q13.41 belongs to Sun et al., 2010 Chinese expressed same family as ZNF313 ILF3 regulates gene ILF3 (Interleukin ILF3: expression and Enhancer Binding Factor Ubiquitous, stabilize 3); CARM1 CARM1: in ILF3, CARM1 19p13.2 mRNAs,CAR Tsoi et al., 2012 Caucasian (Coactivator-Associated prostate M1 is a Arginine adenocarcino transcriptional Methyltransferase 1) mas coactivator of NF-κB associates with cytoplasmic Generally TYK2 Tyrosine kinase 2 19p13.2 domains of Strange et al., 2010, Caucasian expressed cytokine receptors A disintegrin and Metalloproteas metalloproteases Mesenchymal e, linked to Caucasian, ADAM33 20p13 Li et al., 2009 metallopeptidase domain cells angiogenesis & Chinese 33 remodeling Introduction
1.10. Genetic Approaches to find associated genes in monogenic or complex disease
Psoriasis is a complex disorder with multiple genes involved in its pathogenesis.
Although genetic factors are the cause of many complex diseases, they are much more difficult to identify than the genetic factors in Mendelian diseases because of the genetic heterogeneity they display. A Mendelian trait is controlled by a single locus and exhibits a simple Mendelian inheritance pattern. There are five basic Mendelian pedigree patterns, i.e. autosomal dominant, autosomal recessive, X-linked dominant, X-linked recessive and
Y-linked. However, non mendelian characteristics may be dependent on two, three or many genetic loci, with greater or smaller contributions from environmental factors also.
The fact that each contributing locus is neither necessary nor sufficient for a specific phenotype causes a weak relationship between the genotype and the disease phenotype.
There are two commonly used techniques used for identifying genetic risk factors for complex disorders such as psoriasis, i.e. positional cloning and candidate gene approach.
1.10.1. Positional cloning
Linkage analysis
The positional cloning of a disease gene can be divided into two steps; the first involves the localization of the chromosomal region on which the disease gene is located and the second involves identifying the correct gene within this region and finding the correct disease-causing mutation. Linkage analysis is the statistical tool used in the first step.
Genetic linkage is the tendency of alleles that are located close together on a chromosome to be inherited together during meiosis. It is based on the recombination phenomenon of homologous chromosomes during meiosis. Thus, linkage analysis exploits the phenomenon of recombination to localize disease genes in the genome relative to the known position of genetic markers. Microsatellites are the genetic markers that have been Introduction most widely used for linkage analysis. Linkage analysis requires a large collection of families with multiple affected individuals and can be divided into parametric (or model- based) and nonparametric (or model-free) methods.
Parametric linkage analysis
In parametric linkage analysis the mode of inheritance must be specified in addition to other genetic parameters, such as penetrance, disease-allele frequency, phenocopy and mutation rates. The unit for parametric linkage is the LOD score, which is a function of the recombination fraction θ. Two loci are linked if the recombination fraction is less than
0.5 and higher the LOD score, the greater the evidence of linkage. A score of 3 has traditionally been regarded as significant evidence of linkage (Chotai, 1984). This is equivalent to p=0.0001.
Non-parametric linkage analysis (NPL)
In the case of multifactorial diseases, for which several genes and environmental factors contribute to disease risk, there is no clear mode of inheritance. The advantage of a NPL analysis is that it does not require any specification of a genetic disease model. It is also more robust than parametric linkage analysis when the disease model is unknown, but it is less powerful than a correctly specified parametric linkage analysis.
Linkage Disequilibrium
LD is a condition in which alleles at two loci or genes are found together in a population at a greater frequency than that predicted simply by the product of their individual allele frequencies. When an interesting chromosomal region has been defined by linkage analysis, the next step is to finally identify the correct disease-causing gene, this is usually achieved by association analysis which relies on the phenomenon of LD. Alleles Introduction at markers near disease-causing genes tend to be in LD in the affected individuals since there is a lack of ancestral recombination events between them. This is particularly the case in isolated, homogeneous populations, in which it can be assumed that most affected individuals carry the same mutation. A set of alleles of closely linked loci on a chromosome that tend to be inherited together is commonly referred to as a haplotype. A haplotype is more informative than a single SNP which is why haplotype analysis is used in fine-mapping studies to obtain greater power. Using haplotype analysis, the disease mutation can be localized between two predicted historical crossover points.
1.10.2. Candidate gene approach
The candidate gene approach directly tests the effects of genetic variants within candidate genes identified by for example the knowledge of the gene functions, the position of the gene within a DNA region linked to the disease or identified through animal studies. This approach involves assessing the association between particular alleles within the candidate gene and the disease itself. An advantage of these studies is that they do not require large families with both affected and unaffected members, but can also be performed with unrelated cases and control subjects. Furthermore, candidate gene studies are better suited for detecting genes underlying common and more complex diseases where the risk associated with any given candidate gene is relatively small.
Genome-wide association (GWA) studies
In genetic epidemiology, a genome-wide association study (GWAS), also known as whole genome association study (WGAS) is an examination of many common genetic variants in different individuals to see if any variant is associated with a trait. GWASs typically focus on associations between single-nucleotide polymorphisms (SNPs) and Introduction traits like major diseases. The most common approach of GWAS is the case-control setup which compares two large groups of individuals, one healthy control group and one case group affected by a disease. All individuals in each group are genotyped for the majority of common known SNPs. The exact number of SNPs depends on the genotyping technology, but are typically one million or more and for each of these SNPs it is then investigated if the allele frequency is significantly altered between the case and the control group (Clarke et al., 2011). In such setups, the fundamental unit for reporting effect sizes is the odds ratio. The odds ratio is the ratio of two odds, which in the context of GWA studies are the odds of disease for individuals having a specific allele and the odds of disease for individuals who do not have that same allele. When the allele frequency in the case group is much higher than in the control group, the odds ratio will be higher than 1, and vice versa for lower allele frequency. Additionally, a P-value for the significance of the odds ratio is typically calculated using a simple chi-squared test.
Finding odds ratios that are significantly different from 1 is the objective of the GWA study because this shows that a SNP is associated with disease (Clarke et al., 2011).
Large-scale association studies have identified 26 loci that are associated with psoriasis
(de Cid et al., 2009; Nair et al., 2009; Zhang et al., 2009; Ellinghaus et al., 2010;
Ellinghaus et al., 2012; Strange et al., 2010; Stuart et al., 2010; Sun et al., 2010), 21 of which show association in individuals of European ancestry. Recently, in order to gain further insight into the genetic architecture of psoriasis, a meta-analysis of 3 genome- wide association studies (GWAS) and 2 independent data sets genotyped on the
Immunochip, including 10,588 cases and 22,806 controls was conducted that identified
15 new susceptibility loci, increasing the number to 36 that are associated with psoriasis Introduction in European individuals (Tsoi et al., 2012). The list of these reported loci from different association studies is shown in Table 1.3
Current study was performed with unrelated cases and control subjects. Since there is no comprehensive study carried out to investigate the genetics of psoriasis in the region therefore the best approach to identify the genetic risk factors in Pakistani psoriasis samples is the candidate gene approach. We used this approach to assess the association between particular alleles within the candidate genes and the disease. Different genes are reported to be associated with psoriasis in different populations and the most consistently reported locus is HLA. Reported candidate genes were selected to determine their association with the disease to comprehend the genetics of psoriasis in Pakistani population.
1.11. Aims of the Study
Psoriasis is a heterogenous disease, showing variation in presentation and associated factors. Association of genetic factors gives varied results in different populations. Most of the studies carried out are on White population of European origin, whereas some studies are also carried out on Chinese, Japenese, Korean and Indian populations. The reported studies have identified different disease variants, a few were population specific and some of them were common in all the populations. Identified genetic variants involve genomic regions potentially related to skin barrier function, IL-23 signaling, NF-κB and
IFN signaling, and IL-17 cell responses. To date, however, specific susceptibility genes have yet to be identified.
Pakistan is a country of diverse ethnic groups residing in various regions of the country.
Since the genetics of psoriasis is widely unexplored in the region therefore the aim of Introduction present study is to comprehensively investigate the genetic factors causing psoriasis in this population. Therefore following goals are focused upon:
A. Identification of psoriasis susceptibility genes in Pakistani population
HLA association study
Genotyping of ACE I/D polymorphism
Genotyping of genome wide significant markers
B. Investigation of polymorphisms in major psoriasis genes with different
manifestations of the disease.
Analysis of the disease association with respect to age of onset, clinical
phenotype and gender.
Psoriasis is a multifactorial disease and many disease areas are still unexplained, contributions from researches from different populations will help in the comprehension of genetics of psoriasis. Genotyping of disease associated markers will enable us to determine the major and minor genetic contributors of psoriasis. It will also help to confirm the previous findings and/or show some novel associations with psoriasis in this region, which will ultimately help in disease understanding. Genes and environment play a key role in psoriasis pathogenesis and knowledge of the genetic factors that cause the disease will lead to an understanding of its variable age at onset, its waxing and waning and the variability of body surface involvement. Role of the environmental triggers though a complex phenomenon, may also be understood once the altered pathways are elucidated.
It is anticipated that determination of genetic factors will not only give a better understanding of the disease but will also augment the comprehension of disease Introduction etiology. It should also provide a useful tool in risk assessment and prediction of the clinical outcome in Psoriatic patients, hopefully offering new means of therapeutic intervention. This would ultimately lead to better ways of disease management. Materials and Methods
2. Materials and Methods
This is a case control population based study, conducted by following ethical guide lines of the Helinski-II Declaration and also formal approval from the ethical committee of the
Institute of Biomedical and Genetic Engineering, Islamabad was obtained. Written consent from each participant was obtained before sample collection. Consent form is attached as appendix I.
2.1. Study Subjects
A total of 906 blood samples from 533 psoriasis cases and 373 normal healthy controls were recruited for the present study. Cases of psoriasis were selected for sample collection from the outpatient clinics of Rawalpindi. Both patients and controls belonged to various castes and tribes from northern Punjab and Khyber Pakhtunkhwa, they were from a similar ethnic background and mostly belonged to Punjabi and pathan ethnic groups. Psoriasis diagnosis was established as part of routine clinical care by dermatologists. Detailed clinical information was obtained from all patients, including age, gender, age at disease onset, family history of psoriasis and clinical manifestations.
Patients were considered to have type I psoriasis if disease onset was less than or equal to
40 years (< 40 years), and type II if age at onset was greater than 40 years (> 40 years).
Patients were considered to have familial or sporadic psoriasis on the basis if they had one or more first- or second-degree relatives affected or not.
The control group consisted of unrelated healthy individuals and was selected from general population. For HLA, the study was planned for 326 patients and 277 controls, for
ACE, the study included 486 patients and 571 controls whereas for SNP the study recruited 533 patients and 373 controls. Prior data indicated that the probability of Materials and Methods exposure among controls is 0.03. If the true odds ratio for disease in exposed subjects relative to unexposed subjects is 0.03, we will be able to reject the null hypothesis that this odds ratio equals 1 with probability (power) .834 for HLA, .969 for ACE and .943 for
SNP. The Type I error probability associated with the test of this null hypothesis is 0.05.
We will use an uncorrected chi-squared statistic to evaluate this null hypothesis (Dupont and Plummer, 1990).).
Demographic characteristics of patient and control group each for HLA, ACE and SNP study are listed in Tables 2.1, 2.2 and 2.3 respectively. Acid citrate dextrose (ACD) tubes were used to collect blood samples and stored at 4°C until processed. Patients and normal healthy controls were selected on the basis of criteria set in the questionnaire (appendix
II) with all the required information collected at the sample collection time.
Table 2.1: Characteristics of the group used for HLA study.
Parameter Psoriatic Subjects (n=326) Controls (277)
Gender ratio M/F 237/89 123/154
Mean age ± SD (years) 39±16.17 24±0.90
Mean onset age ± SD (years) 32±14.40 -
Type I/II 247/79 -
Familiar occurrence +/− 99/227 -
SD= Standard deviation.
Materials and Methods
Table 2.2: Characteristics of the group for ACE association study.
Parameter Psoriatic subjects (n=486) Controls (571)
Gender ratio M/F 322/164 316/255
Mean age ± SD (years) 37.6±15.83 37.6 ± 17.70
Mean onset age ± SD (years) 29.9±14.59 -
Type I/II 383/103 -
Familiar occurrence +/− 164/322 (34%+) -
SD= Standard deviation.
Table 2.3: Characteristics of the study group for SNP genotyping.
Parameters Psoriatic subjects (n=533) Controls (373)
Gender ratio M/F 358/175 195/178
Mean age ± SD (years) 37±16 26±14
Mean onset age ± SD (years) 29.9±15 -
Type I/Type II 417/116 -
Familial occurrence +/− 163/373 -
SD= Standard deviation. Materials and Methods
2.2. Extraction of Genomic DNA from Venous Blood Samples
Genomic DNA was extracted from blood samples using standard Phenol-Choloform method (Sambrook and Russel, 2001). About 4 to 5ml venous blood was drawn in Acid
Citrate Dextrose (ACD) vacutainers by means of sterile syringes. Samples were stored at
4°C before the extraction of genomic DNA. For DNA extraction, 15 ml cell lysis buffer
(155 mM Ammonium Chloride, 0.1 mM EDTA, 10 mM Potassium Bicarbonate) was added in a 50 ml tube along with blood sample. These samples were placed on ice for 30 minutes and were centrifuged at 1200 rpm for 10 minutes for complete lysis of RBCs in the samples. The supernatant was discarded and the above procedure was repeated with fresh cell lysis buffer. The WBC pellet obtained was resuspended in 4.75 ml of STE buffer (100 mM Sodium chloride, 50 mM Tris, 1 mM EDTA). To this mixture 250µL of
10% SDS was added drop-wise to lyse WBCs and 10 µL of proteinase K (20 mg/ml) was added to denature proteins. The tubes were then incubated in water bath at 55°C overnight.
After overnight digestion with proteinase K, equal quantity of equilibrated phenol (pH
8.0) chloroform and Isoamylalcohol (24:1) mixture (1:1) was added. After shaking for 10 minutes, tubes were placed on ice for ten minutes. These tubes were then centrifuged for thirty minutes at 3200 rpm. In the extracted aqueous layer 5 ml ice cold isopropanol along with 600 µl 10 M ammonium acetate was added and inverted a few times until DNA was visible in the form of white threads. The tubes were placed at -20°C overnight. These tubes were centrifuged at 3200 rpm for 50 minutes. DNA settled down in the form of pellet. The DNA pellet was washed with 5 mL of ice cold 70% ethanol. The pellet was Materials and Methods resuspended in 10 mM Tris HCl. Stocks of DNA were stored at -20°C. All the above mentioned centrifugations were carried out at 4°C.
2.3. DNA Quantification
DNA stocks were quantified by absorbance measurement at 260nm in Ultravtec spectrophotometer. A 1:50 dilution of DNA (6 µL DNA in 294 µL deionized H2O) was prepared in a glass tube and absorbance was measured at 260nm and 280nm respectively.
Stock DNA concentration was calculated by using the following standard formula for double stranded DNA:
Absorbance measured at 260nm × Dilution Factor (50) × Correction Factor (50) =
DNA Concentration µg/ ml
2.4. HLA Typing
HLA class I and II alleles were screened in DNA samples of the patients and controls by means of sequence specific primers (PCR-SSP). Primer mixes for HLA class I alleles (A,
B and C) and HLA class II alleles (DRB1, DRB3, DRB4, DRB5 and DQB1) were made according to the HLA photo typing method (Bunce et al., 1995). Primer mixes, 10x PCR buffer, and TDMH reagents were made in bulk and kept at -20°C for storage purpose. All reagents were prepared in autoclaved deionized water. The 10x PCR buffer contained
670 mM Tris base pH 8.8, 66 mM ammonium sulphate and one percent tween 20. TDMH contained 2.6x PCR buffer, 460 μM dNTPS and 6.25 mM MgCl2. TDMH was freshly prepared according to requirement and stored at 4°C in 5 ml falcon tubes. HLA alleles genotyped are listed in Table 2.4.
Materials and Methods
Table 2.4: HLA Class I (A, B and C) and Class II (DRB, DRB3, DRB4, DRB5 and DQB1 alleles used for HLA Typing (Olerup et al., 1993; Bunce et al., 1995). Materials and Methods
2.4.1 Polymerase Chain Reaction with Sequence Specific Primers for HLA Class I and Class II Typing
Polymerase chain reaction with sequence specific primers (PCR-SSP) was optimized and carried out for each patient and control sample (Bunce et al., 1995). A final volume of 13
μL was used for PCR in 96 well plates. Class I and II primer mixes (5 μL) were aliquoted in to labeled plates using the multichannel dispenser. Master mixes containing 5 μL of
TDMH, 0.187 units of Taq polymerase, 0.1 ng of DNA sample per reaction were prepared and 8.0 μL dispensed in 96 well plates using a multi dispensing channel. Each primer mix was subsequently added to the wells of a 96 well plate. The plates were properly sealed with the sealing films. PCR was performed using cycling conditions of 1 min denaturation at 96 °C followed by 5 cycles of 25 sec at 96°C, 45 sec at 70 °C and 72
°C for 45 sec. It was followed by additional 21 cycles of 96 °C for 25 sec, 65°C for 50 sec and 72 °C for 45 second 4 cycles of 25 sec at 96 °C, 55 °C for one min and 72 °C for
2 mins and final extension cycle for 10 min at 72 °C.
2.4.2 Agarose Gel Electrophoresis for HLA
The amplimers were separated on 2.0% (w/v) agarose gel, prepared in 0.5x Tris-Acetate-
EDTA, (TAE) buffer. A 5.0 μL volume of ethidium bromide (5 μg/ml) was added to the gel mixture in order to visualize DNA bands under UV light. For electrophoresis PCR product was mixed with loading dye (5 μL of 6x orange G) and loaded onto the wells.
Electrophoresis was performed for about one hour at 120 volts until the dye migrated at least 3 cm. DNA ladder of 100 bp was used as standard marker to identify alleles according to size. The gels were photographed under UV light. Appropriate product size amplified for various alleles was determined for the haplotypes (Figure 2.1). Materials and Methods
100 bp ladder
756 bp internal control
Figure 2.1: 2% (w/v) Agarose Gel Electrophoresis showing results of HLA class I and II typing. “A” represents control band, “B” represents allele specific band.
Haplotype: 100 bp ladder HLA-A; A*0301-02, A*1101-02 HLA-B; B*5101-05, B*52011-12 HLA-C; Cw*1202 HLA-DRB; DRB1* 13, DRB3* 0101 HLA-DQB1; DQB1* 0604-09 756 bp internal control
Materials and Methods
2.4.3. Meta-Analysis
Electronic databases like Med line and PubMed were searched up to July 2013 for all genetic studies involving HLA-A*01, A*3201, B*37, B*51, B*57, Cw*0602, Cw*15,
DRB1*03, DRB1*0701, DQB1*02 and HLA DQB1*03032 typing in psoriasis vulgaris patients in different studies all over the world. We searched Pubmed database
(www.ncbi.nlm.nih.gov/pubmed) to retrieve papers linking psoriasis risk and HLA alleles. The search terms were ‘psoriasis’ and ‘human leukocyte antigen’ or ‘HLA’ or
‘HL-A’. Studies selected in the meta-analysis were all case control studies and meta- analysis was done using Comprehensive Meta-analysis version 2 Biostat, Englewood, NJ,
2004. The associations of HLA-A*01, A*3201, B*37, B*51, B*57, Cw*0602, Cw*15,
DRB1*03, DRB1*0701, DQB1*02 and HLA DQB1*03032 with psoriasis vulgaris were estimated for each study by odds ratio (OR) and 95 percent confidence interval (CI). In forest plots each square represents the OR point estimate and its size is proportional to the weight of the study. The diamond shape represents the overall summary estimate, with confidence interval given by its width. The random effect model was preferred because it enables the modeling differences between studies by incorporating a heterogeneity parameter (Takkouche et al., 1999).
2.5. Genotyping of ACE I/D Polymorphism
Angiotensin-converting enzyme Alu I/D polymorphism in intron 16 was studied using primer sequences given in Table 2.5. PCR conditions were optimized and 15 μL volume was used for each PCR reaction, containing 1 μM of each primer, 1x PCR buffer, 0.45
μM MgCl2, 200 μM dNTPS, 1 U Taq polymerase (Fermentas EU) and 30 ng DNA. PCR cycling parameters were1 cycle at 94 °C for three min, followed by 35 cycles of 94 °C Materials and Methods for 45 sec, 58 °C for one min, and 72 °C for 45 sec and a final 1 cycle at 72 °C for 10 min (Batzer et al., 1996).
Amplimers were separated on two percent agarose gels and after staining with ethidum bromide the gels were visualized under UV transilluminator. Alleles having the insertion were denoted as "I" alleles and "D" alleles were the ones lacking this repetitive element.
In the absence of the 287 bp insertion the PCR method resulted in a 190 bp product (D allele) and in the presence of insertion it produced a 490 bp product (I-allele; Figure 2.2).
Both size bands (490 and 190 bp) were present in heterozygous samples. DNA ladder of
100 bp was used as standard (Figure 2.2).
Table 2.5: Primer Sequences of ACE I/D Polymorphism. Forward 5'– CTGGAGACCACTCCCATCCTTTCT-3'
Reverse 5'-GATGTGGCCATCACATTCGTCAGAT-3'
Figure 2.2: 2.0% (w/v) Agarose Gel Electrophoresis Showing Results of ACE I/D PCR Products. “A” represents 490bp band (I allele) and “B” represents 190 bp band (D allele).
2.6. SNP Genotyping Materials and Methods
All genes reported for psoriasis were retrieved from NCBI, the ones strongly associated with psoriasis and reported in genome wide association studies in other populations were selected. A few genes from candidate gene studies were also selected. In all 57 SNPs in
42 different genes were selected for genotyping. KASP genotyping method was used to analyze all the SNPs.
2.6.1. KASP Genotyping
KASP (KBioscience Competitive Allele‐Specific PCR genotyping system) is a homogeneous, fluorescent, endpoint‐genotyping technology. In order to genotype the
DNA sample, KASP reagents (KBioSciences, UK) were used. KASP genotyping system uses a combination of two molecular techniques: allele specific polymerase chain reaction (PCR) and fluorescence resonance energy transfer (FRET). A KASP assay includes: a) two allele-specific primers; one specific for each allele; b) one common primer; and c) two FRET cassettes, each including a quenched 6-FAM- or 6-HEX- labelled oligo-nucleotide. Each allele specific primer has a SNP specific base complementary to the target DNA template and one of the SNP alleles. Attached to each
SNP allele specific oligo is a unique 5’ tail with sequence homology to universal secondary oligos labeled with either a FAM or HEX fluorophore. Fluorescence from the secondary oligo is initially suppressed by bound quencher molecules. During the first round PCR, only the correct allele specific primer binds and its 5’ tail is incorporated into the PCR product. In the second round PCR, the reverse primer generates a sequence complementary to the 5’ tail of the allele specific sequence. This allows for the secondary fluorophore labeled oligo to bind and become incorporated into the PCR product during the third round PCR. Incorporation of the fluorophore labeled oligo into the PCR product Materials and Methods releases it from its quencher allowing it to fluoresce. As PCR continues, generation of signal increases. After completion of PCR the fluorescent signal can be read and a genotype determined (Figure 2.3). A heterozygous genotype at a SNP would cause both fluorophores to be detected, whereas if only one or the other fluorophphore is seen, the genotype call is homozygous (Robinson and Holme, 2011). Since each allele-specific primer is associated to one of the two dyes, homozygous genotypes are expected to be plotted at the maximum end of either the x- or y-axis. Heterozygous genotypes, in theory, should have an equal fluorescence signal from each dye, therefore a cluster roughly in between the other two homozygous groups should be observed.
Figure 2.3: Schematic drawing of the KASP method (Kompetitive Allele Specific PCR) http://en.wikipedia.org/wiki/Kompetitive_Allele_Specific_PCR_(KASP). Materials and Methods
2.6.2. KASP genotyping Assay
KASP genotyping Assays were performed on 384 well plates. DNA samples were aliquoted on a 384 well PCR plate and dried down by placing at 55°C incubator overnight; non-template controls (NTCs) were also included on each plate. PCR conditions were optimized and in a final 5 μL genotyping reaction volume 2 μL genomic
DNA (5ng/μL), 2.5 μL 2X KASP Master Mix and 0.07 μL KASP Primer Mix were used.
KASP 2x Master Mix contained the FRET reporting system (FAM, HEX) and PCR reagents. KASP Primer Mixes, unique for each SNP, contained two allele-specific primers and one common primer. Both mixes were obtained from LGC
Genomics/KBioscience (Beverly, MA). Master mixes were dispensed robotically in the plates by using Biomek FX (Beckman Coulter). The plates were properly sealed with the sealing films using heat-based plate sealer. PCR was performed using cycling conditions of 15 mins denaturation at 94°C followed by 10 cycles of 20 sec at 94°C and 60 sec at
55°C. It was followed by additional 26 cycles of 94°C for 20 sec and 55°C for 60 sec.
Plates were thermo cycled for further 3 cycles of 94°C for 20 sec and 57°C for 60 sec to obtain clearly distinguished genotyping clusters. After the completion of PCR run, plates were read by ABI 7900 HT (Life Technologies). Alleles were discriminated based on fluorescence readings. Allele discrimination plots (ADPs) were confirmed and were read by visual inspection of fluorescence data. Alleles were recorded as X (FAM) or Y (VIC) as shown in Figure 2.4. Materials and Methods
Figure 2.4: The result of SNP (rs1295685) assay using the KASP genotyping chemistry. Non template controls (NTC), Homozygous and heterozygous clusters are shown in each graph.
Materials and Methods
2.7. Statistical Analysis
Analysis of variance was calculated by Statistical Package for Social Sciences (SPSS) to estimate significant variation between HLA class I and II allelic frequencies and five- locus haplotypes in psoriasis patients and controls (Voelki and Gerber, 1999).
Calculations were also performed separately for three-locus and two-locus haplotypes for
HLA class I and II respectively. For a particular locus where only one allele was found, the sample was considered to be homozygous.
Hardy-Weinberg equilibrium (HWE), maximum likelihood estimate of allele and five- locus haplotype frequencies for the HLA class I and class II loci was calculated by
Arlequin (An Integrated Software for Population Genetics Data Analysis) Version 3.0 software 33. Linkage disequilibrium and its significance were calculated as described
(Imanishi et al., 1991).
Statistical significance of the allelic associations was assessed using P values. As multiple comparisons were made, Bonferroni’s correction was applied multiplying the obtained P values by the number of alleles considered at each locus (Pcor). The level of significance was set at Pcor <0.05.
For ACE I/D polymorphism allele and genotype frequencies were calculated by scoring the specific allele size bands. Calculations for odds ratio (OR) and 95 % confidence interval (CI) were estimated by means of an online calculator for Odds Ratios (http: // www.hutchon.net/ConfidOR.htm, Bland and Altman, 2000). The OR significance was calculated by using the 2 x 2 chi-square contingency test with Yates' correction for continuity (http://vassarstats.net/odds2x2.html). In case of SNPs, after the genotypes were determined from the allelic discrimination plot, the R software was used to compile Materials and Methods the data. All quality control steps and statistical analyses were performed using the
PLINK (v1.07) software (Purcell et al., 2007). SNPs with less than 90% success rate were excluded from the study. Allele and genotype frequencies were calculated and tested for Hardy–Weinberg (HW) Equilibrium to check the goodness of fit with one degree of freedom. Linkage disequilibrium values for SNPs present in the same locus/gene and for the genes present on the same chromosome were calculated and haplotype analysis was carried out in case of linkage using Arlequin ver 3.11 software
(Excoffier et al., 2005). Role of HLA allelic and haplotype polymorphism
3. Role of HLA allelic and haplotype polymorphism
3.1. Introduction
The human leukocyte antigen (HLA) system is the name of major histocompatibility complex (MHC) in humans. The Major Histocompatibility Complex (MHC) region is present on human chromosome 6 between 6p21.31 and 6p21.32 and spans about 4 million base pairs. It consists of more than 200 genes, over 40 of which encode for leukocyte antigens that are involved in the immune response. HLA genes are grouped into three classes: class I, class II and class III (Fig 3.1).
The major HLA class I genes (HLA-A, HLA-B and HLA-C) are expressed by most somatic cells. The class II genes are grouped into the main classes of HLA-DM,-DO, -DP,
-DQ and -DR, and further into two families, A or B, based on the antibody chain (α or β).
The class II genes are normally expressed only by immune cells (B cells, activated T cells, macrophages, dendritic cells, and thymic epithelial cells), but in the presence of γ interferon other cell types can also express them (Margulies, 1999; Klein and Sato,
2000a).
The class I and II MHC molecules are cell surface receptors that recognize and bind antigen fragments and after processing, present them to the T cells to initiate an immune response. The cytosolic proteins (defective or worn-out proteins of the cell or viral proteins) are presented by HLA class I molecules and extracellular proteins (self or foreign) are presented by class II molecules. As a result HLA-peptide complexes are formed that interact with T cell receptors or CD4-CD8 co-receptors of the T cells. The
MHC molecules can either protect or activate natural killing of the target cell by serving as elements for signal transduction for natural killer (NK) cells (Margulies 1999; Klein Role of HLA allelic and haplotype polymorphism and Sato, 2000a). HLA class III molecules encode components of the complement system.
Figure 3.1: A Simplified Map of the HLA Region on Chromosome 6.
MHC region is highly polymorphic that allows binding and presentation of a large number of different antigens. In addition to foreign pathogens, HLA molecules have an important role in self-recognition by the immune system. Any cell displaying some other
HLA type is recognized as “non-self” resulting in rejection of the tissue bearing those cells. MHC also plays a causative role in many autoimmune diseases but the exact mechanism is unclear. In some autoimmune diseases certain HLA alleles or haplotypes are significantly more common in patients compared to controls, for example DR4 in rheumatoid arthritis, HLA-B27 in ankylosing spondylitis, DQB1*0302 in insulin Role of HLA allelic and haplotype polymorphism dependent diabetes mellitus and DR3 in celiac disease. Psoriasis is the only disease known to be associated with HLA-C gene (Margulies 1999; Klein and Sato 2000b). MHC region is composed of blocks within which recombination appears to be very rare and tight linkage disequilibrium exists between the alleles, forming extended conserved haplotypes (Marshall et al., 1993).
3.2. HLA Association with Psoriasis
Numerous HLA alleles at the HLA-A, -B, -C, -DRB1, -DQA1, and –DQB1 loci have been reported to be associated with psoriasis. Among these HLA-A*01, A*02, B*13, B*17,
B*39, B*57, Cw*0602, Cw*07, DRB1*0701 and DQA1*0201 (Bedi et al., 1979;
Malaviya et al., 1984; Nakagawa et al., 1989; Pitchappan et al., 1989; Ikaheimo et al.,
1996; Rani et al., 1998; Kim et al., 2000) have been reported to be significantly associated. HLA class I alleles Cw*0602 and B*57 have been most consistently reported worldwide (Elder et al., 1994). Early reports on association between psoriasis and the
HLA antigens were obtained by serologic typing during 1970s before any genome wide linkage studies were performed (Tervaert and Esseveld, 1970; Russel et al., 1972; White et al., 1972). A significant increase of the HLA-class I alleles –B13 (A13) and –B17
(W17) in psoriasis patients were observed as compared to controls (27.3% and 22.7% in psoriasis patients and 3.4% and 9% in controls, respectively) in 44 Caucasian patients and 89 controls (Russell et al., 1972).
Later on, in subsequent studies HLA-B13 (A13) and -B17 (W17) alleles were also shown to be associated with psoriasis (White et al., 1972; Tiilikainen et al., 1980). In a study reported on Finnish population samples, 45.9% of patients were HLA-Cw*0602 carriers compared with 7.4% of controls (Tiilikainen et al., 1980). Studies with serological typing Role of HLA allelic and haplotype polymorphism method were less sensitive for HLA-C (Bunce et al., 1996), by using more specific DNA- based genotyping methods, the allele HLA-Cw*0602 has been shown to be the strongest and most consistently reported HLA associated allele for psoriasis. Later studies in White population of British origin and Swedish population showed significant increase in frequency of the HLA-Cw*0602 allele in patients compared to the controls (Enerback et al., 1997; Mallon et al., 1997).
At the protein level amino acid change from alanine to threonine at position 73 of the
HLA-C was reported to be associated with psoriasis (Asahina et al., 1991; Ikaheimo et al., 1994). This change was seen in the HLA-Cw*0602 allele, but it was not exclusive to
Cw*0602. The HLA-Cw*04, -Cw*07, -Cw*12, -Cw*1503 and -Cw*17 alleles also have
Ala 73 in their coding regions (Kostyu et al., 1997; Mallon et al., 1997). In a study reported in White population of British origin, Ala 73 was present at high frequencies in both psoriasis patients (88.5%) and the control group (84.3%) and showed a significant association with type I psoriasis male patients only (Mallon et al., 1997). The authors concluded that the HLA-Cw*0602 allele was most likely playing the main role and not
Ala 73 (Mallon et al., 1997). In Japanese population, the HLA-Cw*11 allele was reported to be significantly more frequent in patients than in controls (57% vs. 9%), but HLA-
Cw*0602 and -Cw*07 alleles also showed an increased risk (Nakagawa et al., 1989).
The association of HLA-Cw*0602 allele was higher in early onset psoriasis patients
(Tiilikainen et al., 1980; Henseler and Christophers, 1985; Enerbäck et al., 1997; Mallon et al., 1997). Based on the consistent report of association with HLA-Cw*0602, psoriasis patients were categorized into type I and type II (Henseler and Christophers, 1985). HLA- Role of HLA allelic and haplotype polymorphism
Cw*0602 positive and negative patients exhibit different clinical features and the disease is more severe in patients positive for HLA-Cw*0602 allele. Guedjonsson et al., 2002).
In addition to HLA class I, HLA class II alleles have also been reported to be associated with psoriasis. HLA-DRB1*0701 and HLA-DRB1*1401 alleles were present at a higher frequency in patients as compared to controls in a Taiwanese population (Jee et al.,
1998). In a Caucasian population, besides HLA-Cw*0602, -B*13 and -B*57 alleles,
DRB1*0701, DQA1*0201 and DQB1*0303 alleles were over-represented in type I psoriasis patients (Schmitt-Egenolf et al., 1993; Ikaheimo et al., 1996). Furthermore, an extended haplotype, EH57.1, containing Cw*0602-B*57-DRB1*0701-DQA1*0201-
DQB1*0303 was significantly more frequent in type I psoriasis patients than in controls
(P=0.00021). In type I psoriasis patients, individuals that carry the class I alleles of the haplotype “EH57.1” (HLA-Cw*0602 and B*57) but lack the class II alleles
(DRB1*0701, DQA1*0201, and DQB1*03032) were significantly more common than in the control group (12% vs. 2%; P=0.0060). By contrast, individuals carrying only the class II alleles of the haplotype and missing the class I alleles were not at risk. Analysis of the ancestral haplotype has shown that the class I end of the haplotype appears to be the actual psoriasis susceptibility region while the class II association is due to linkage disequilibrium between the alleles (Schmitt-Egenolf et al., 1996). It was also reported that the class I haplotype of EH57.1 was selectively retained among affected individuals and that the HLA-Cw*0602 allele was the strongest predictor of psoriasis risk. However, the HLA-Cw*0602 allele itself was unlikely to be the direct determinant of psoriasis susceptibility but rather was in tight linkage disequilibrium with it (Jenisch et al., 1998).
HLA association studies in different populations are summarized in Table 3.1. The aim of Role of HLA allelic and haplotype polymorphism the study was to genotype HLA alleles to see whether same alleles and haplotypes are involved in psoriasis susceptibility in Pakistani population as reported in other populations. A meta-analysis was also carried out to analyze the HLA allelic associations reported previously and to correlate with our findings. Role of HLA allelic and haplotype polymorphism
Table 3.1: Published Associations Between Psoriasis And Human Leukocyte Antigens (HLA). S.No. Associated Alleles or Loci Methods Populations References 1 A1, B13,B17 Scottish Gunn et al., 1979 Serological HLA 2 A1, B13, B17, Cw6, DRw6, DR7 Japanese Ozawa et al., 1981 typing Serological HLA 3 B17, Cw6, DR7 Caucasian Marcusson et al., 1981 typing Serological HLA 4 DR7 Caucasian Tiwari et al.,1982 typing Serological HLA 5 B13, B17, B37, Cw6, DR7 - Woodrow et al., 1985 typing Serological HLA 6 Bw57, DR7 South Indian Pitchappan et al., 1989 typing A2-Cw11-Bw46-C2C-BFS-C4A4-C4B2- Serological HLA 7 Japanese Nakagawa et al., 1991 DRW8 haplotype typing DRB1*0701/2-DQA1*0201-DQB1*0303 HLA allele typing 8 - Schmitt-Egenolf et al., 1993 extended haplotype (genotyping) 9 HLA-A*17, B*13, B*27 Irish O'Donnell et al., 1983 Cw6-B57-DRB1*0701-DQA1*0201- 10 HLA allele typing Caucasian Schmitt-Egenolf et al., 1996 DQB1*0303 haplotype A2,B13,Cw6,DR7, DQA1*0201 and Serological and 11 Caucasian, Finnish Ikaheimo et al., 1996 A1,B17,Cw6,DR7,DQA1*0201 haplotypes HLA allele typing
12 DRB1*1502, DQB1*0601 HLA allele typing Japanese Saeki et al., 1998
13 DRB1*0701, DRB1*1401 HLA allele typing Taiwanese Jee et al., 1998
Table 3.1 Continued… Role of HLA allelic and haplotype polymorphism
S.No. Associated Alleles or Loci Methods Populations References A2, B46, B57, DQB1*0303 Serological and 14 A1-B57-DRB1*0701-DQA1*0201- HLA allele typing Thai Vejbaesya et al., 1998 DQB1*0303 (AH57.1) haplotype
A2-B46-DRB1*0901-DQA1*0301- DQB1*0303 (AH46.1)haplotype A1, A30, B13, B37, Cw*0602,
15 DRB1*07, DRB1*10, DQA1*02, DQB1*02, Serological and DPB1*1701 Korean HLA allele typing Kim et al., 2000
A30-B13-Cw*0602-DRB1*10-DQA1*01- DQB1*05 haplotype A1-B37-Cw*0602-DRB1*07-DQA1*02- DQB1*02-DPB1*1701 haplotype 16 B13, B17, Cw*0602, DR7 HLA allele typing Croatian Kastelan et al., 2000 Serological HLA 17 A30, Cw3, Cw6, DR7, DR14, DQ8, DQ9 Turkish Kundakci et al., 2002 typing A*0207-B*4601-Cw*01-DRB1*09- DQB1*0303 haplotype A*01-B*57-Cw*0602-DRB1*07-DQB1*0303 18 HLA allele typing North-eastern Thai Choonhakarn et al., 2002 A*30-B*13-Cw*0602-DRB1*07-DQB1*02 A*0207, A*30, Cw*01, DRB1*1401 Table 3.1 Continued…
Role of HLA allelic and haplotype polymorphism
S.No. Associated Alleles or Loci Methods Populations References
19 HLA-A26,B13, B27,HLA Cw*0304, Cw*0602 HLA allele typing Chinese Han Zhang et al., 2003 20 DQA1*0104, DQA1*0201 HLA allele typing Chinese Han Zhang et al., 2004 DRB3*02, DRB1*0102 21 HLA allele typing Brazilian Cardoso et al., 2005 DRB1*0102/DQB1*05,DRB1*0701/DQB1*03 HLA-B13,39,57, HLA Cw*06,Cw*12, 22 HLA allele typing Brazilian Biral et al., 2006 HLA-B*13,Cw*06 HLA-B*57, Cw*06 and PCR-SSP HLA-B*39, Cw*12 haplotypes HLA-A*30,A*68,B*7,B*13,B*57,Cw6, HLA allele typing 23 Turkish Atasoy et al., 2006 DRB1*07 PCR-SSP 24 DRB1 subregion Association study Japanese Mabuchi et al., 2007 HLA-A*30 and A*68, B*7, B*13, B*57, Cw6, HLA allele typing 25 Turkish Atasoy et al., 2006 and DRB1*07 PCR-SSP 26 DRB1 subregion Association study Japanese Mabuchi et al., 2007 Serological and 27 B52, A68, DR13, DRw52 and DQ2. Omani Al- Mamari et al., 2009 class I, II typing Serological HLA 28 HLA-A2,A28, B8, B5, B12, B15, B17, B44 Western India Umapathy et al., 2011 typing HLA allele typing 29 HLA-Cw 06,HLA-DRB1*01, 07, DQB1 02 Solvak Shawkatová et al., 2012 PCR-SSP Role of HLA allelic, genotype and haplotype polymorphism
3.3. Results
3.3.1. Association Analysis of HLA Class I and Class II Alleles
Statistically significant HLA class I and class II allelic frequencies observed in 326 patients with psoriasis and in the control group are highlighted in Table 3.2. Bonferroni correction test was applied on all the alleles and P corrected value (Pc = <0.05) was considered significant at each locus. Distribution of HLA class I and class II alleles among 326 patients and controls showed a significant increase in frequencies of HLA-A*3201 (OR-4.58,
Pc=0.03), B*37 (OR-3.67, Pc = <0.0001), B*57 (OR-4.65, Pc=<0.0001), Cw*0602 (OR-
3.21, Pc=<0.0001), DRB1*0701(OR-2.0, Pc=<0.0001) and DQB1*03032 (OR-6.82,
Pc=<0.0001) in patients, while the frequencies of B*40 (OR-0.52, Pc=0.03), B*51 (OR-0.55,
Pc=0.03), Cw*15, (OR-0.44, Pc=<0.0001), DRB1*03 (OR-0.57, Pc=0.006) and
DQB1*02(OR-0.59, Pc=0.002) were significantly decreased in psoriasis patients.
Furthermore, on subdividing 326 psoriasis samples into type I and type II groups the result showed that after applying Bonferroni correction test the frequencies of HLA-A*01 (OR-
1.69, Pc=0.02), B*37 (OR-4.42, Pc=<0.0001), B*57 (OR-5.2, Pc=<0.0001), Cw*0602 (OR-
3.80, Pc=<0.0001), DRB1*0701 (OR-2.08, Pc=<0.0001), DRB1*1001 (OR-2.36, Pc=0.01) and DQB1*03032 (OR-6.82, Pc=<0.0001) were significantly increased in 247 type I patients, while a significant decrease was seen in the frequencies of A*3201 (OR-4.9,
Pc=0.03), B*51 (OR-0.51, Pc=0.03), Cw*0702 (OR-0.58, Pc=0.05), Cw*15 (OR-0.43,
Pc=<0.0001), DRB1*03 (OR-0.53, Pc=0.004) and DQB1*02 (OR-0.57, Pc=0.002) alleles in patients as compared to controls. The results of the analysis are presented in Table 3.3.
In type II patients group (n=79) HLA-B*15 (OR-2.92, Pc=0.03), B*57 (OR-3.06, Pc=0.03),
DRB1*1302 (OR-3.69, Pc=0.01), and DQB1*03032 (OR-6.82, Pc=<0.0001) showed Role of HLA allelic, genotype and haplotype polymorphism significantly increased allele frequency in patients after applying the Bonferroni correction test, the results are shown in Table 3.4.
Since the major phenotype for the disease is psoriasis vulgaris and studies had been reported where analysis had been performed only with psoriasis vulgaris samples (plaque psoriasis) therefore, the data was also analyzed considering psoriasis vulgaris samples (n=270). Results of the analysis are shown in Table 3.5, the alleles were considered as significant when P corrected value was <0.05. The result showed a significant increase in the frequencies of
HLA-A*01 (OR-1.69, Pc=0.02), HLA-A*3201 (OR-5.01, Pc=0.02), HLA-B*37 (OR-3.61,
Pc=0.001), HLA-B*57 (OR-5.56, Pc=<0.0001), HLA-Cw*0602 (OR-3.74, Pc=<0.0001),
DRB1*0701 (OR-2.26, Pc=<0.0001) and DQB1*03032 (OR-7.85, Pc=<0.0001) in patients, while the frequencies of HLA-B*51 (OR-0.38, Pc=0.0002), HLA-Cw*15, (OR-0.37,
Pc=<0.0001), DRB1*03 (OR-0.53, Pc=0.003) and DQB1*02 (OR-0.59, Pc=0.004) alleles were significantly decreased in psoriasis patients.
The 270 psoriasis vulgaris samples were again subdivided into type I and type II groups. In type I group (n= 207) the result showed that the frequencies of HLA-A*01 (OR-1.82,
Pc=0.003), HLA-A*3201 (OR-5.17, Pc=0.017), HLA-B*37 (OR-1.06, Pc=<0.0001), HLA-
B*57 (OR-6.27, Pc=<0.0001), HLA-Cw*0602 (OR-4.38, Pc=<0.0001), DRB1*0701 (OR-
2.34, Pc=<0.0001), DRB1*1001(OR-2.34, Pc=0.03), and DQB1*03032 (OR-7.94,
Pc=<0.0001) were significantly increased in patients, while a significant decrease was seen in the frequencies of HLA-B*51 (OR-0.34, Pc=<0.0001), HLA-Cw*15 (OR-0.39,
Pc=<0.0001), DRB1*03 (OR-0.52, Pc=0.007) and DQB1*02 (OR-0.59, Pc=0.01) alleles in patients as compared to controls after applying the Bonferroni correction test as presented in
Table 3.6. Role of HLA allelic, genotype and haplotype polymorphism
In type II patient group (n=63) HLA-B*15 (OR-3.52, Pc=0.003), HLA-B*57 (OR-3.43,
Pc=0.006), DRB1*1302 (OR-4.72, Pc=0.001), and DQB1*03032 (OR-7.57, Pc=<0.0001)
showed increased allelic frequency in patients after applying the Bonferroni correction test,
the results are shown in Table 3.7.
3.3.2. Haplotype Analysis of HLA Class I and Class II Alleles
The five locus haplotype for HLA loci A, B, C, DRB and DQB1 were made by Arlequin.
Overall 401 haplotypes were generated in cases and 383 haplotypes in the controls.
Haplotypes showing frequencies greater than 2.0% in each group are shown in Table 3.8.
HLA class I and class II haplotypes were also analyzed separately and three locus haplotypes
and two locus haplotypes are shown in Tables 3.9 and 3.10 respectively.
3.3.3. Meta-Analysis of HLA Class I and Class II Alleles
A meta-analysis for significant alleles was performed using studies reported in different
populations including the present study. The results of HLA class I alleles HLA-A*01,
A*3201, B*37, B*51, B*57, Cw*0602, Cw*15 and HLA class II alleles DRB1*03,
DRB1*0701, DQB1*02 and DQB1*03032 are given in Tables 3.12 and 3.13 while
interpretation by forest plots for the most significant alleles are shown in Figures 3.2-3.5. In
the forest plots each square represents the OR point estimate and the diamond shape
represents the overall summary estimate, with confidence interval given by its width.
Analysis for all the alleles was carried out using data from the available studies and the
results are summarized in Table 3.11. Role of HLA allelic, genotype and haplotype polymorphism
Table 3.2: Frequency Distribution of HLA Alleles in Controls and Patients. Controls Patients S.No. Allele F Sig. OR 95 % CI Pc 277 326 1 A*01 0.162455 0.230061 8.64 0.003 1.541 1.152-2.059 0.051 2 A*03 0.117329 0.069018 7.92 0.005 0.568 0.381-0.846 0.085 3 A*3201 0.00722 0.032209 9.27 0.002 4.576 1.561-13.412 0.034 4 A*33 0.064982 0.038344 4.44 0.035 0.574 0.340-0.968 0.595 5 B*07 0.057762 0.027607 6.88 0.009 0.463 0.257-0.835 0.261 6 B*18 0.025271 0.009202 4.75 0.029 0.358 0.137-0.939 0.841 7 B*37 0.021661 0.075153 18.1 <0.0001 3.67 1.932-6.973 <0.0001 8 B*40 0.119134 0.065951 10.4 0.001 0.522 0.349-0.781 0.029 9 B*51 0.140794 0.082822 10.4 0.001 0.551 0.382-0.796 0.029 10 B*57 0.037906 0.154908 46.8 <0.0001 4.652 2.865-7.556 <0.0001 11 Cw*0602 0.124549 0.308282 63.7 <0.0001 3.215 2.374-4.354 <0.0001 12 Cw*0702 0.169675 0.115031 7.46 0.006 0.636 0.459-.882 0.096 13 Cw*14 0.043321 0.021472 4.7 0.03 0.485 0.248-0.946 0.48 14 Cw*15 0.146209 0.070552 18.4 <0.0001 0.443 0.303-0.649 <0.0001 15 DRB1*03 0.191336 0.118098 12.6 0.0004 0.566 0.412-0.778 0.006 16 DRB1*0701 0.095668 0.174847 15.9 <0.0001 2.003 1.415-2.836 <0.0001 17 DRB1*1001 0.037906 0.072086 6.6 0.01 1.972 1.164-3.341 0.14 18 DRB1*11 0.106498 0.065951 6.38 0.012 0.592 0.393-0.893 0.168 19 DRB1*1302 0.021661 0.047546 6.86 0.009 2.464 1.227-4.950 0.126 20 DQB1*02 0.263538 0.177914 14.1 0.0002 0.594 0.451-0.782 0.002 21 DQB1*0301/0304 0.120939 0.082822 4.83 0.028 0.656 0.450-0.958 0.308 22 DQB1*03032 0.018051 0.101227 38.2 <0.0001 6.82 3.366-13.819 <0.0001 23 DQB1*04 0.005415 0.018405 4.12 0.043 3.444 0.967-12.266 0.473 24 DQB1*05 0.203971 0.260736 5.39 0.02 1.376 1.050-1.804 0.22 25 DQB1*0602 0.039711 0.016871 5.14 0.024 0.436 0.208-0.912 0.264 26 DQB1*0604-9 0.023466 0.044479 4.759 0.029 2.102 1.062-4.160 0.319 HLA= Human leukocyte antigen, F = Fisher exact test, CI = Confidence interval, OR = Odds ratio, Pc= P corrected. Role of HLA allelic, genotype and haplotype polymorphism
Table 3.3: Frequency Distribution of HLA Alleles in Controls and Type I Psoriasis Patients. Controls Patients S.No. Allele F Sig. OR 95 % CI Pc 277 247 1 A*01 0.162455 0.246964 11.7 0.001 1.691 1.247-2.293 0.017 2 A*03 0.117329 0.064777 8.13 0.004 0.53 0.341-0.826 0.068 3 A*3201 0.064982 0.034413 9.91 0.002 4.9 1.638-14.664 0.034 4 B*07 0.057762 0.024291 7.31 0.007 0.406 0.207-0.798 0.203 5 B*37 0.021661 0.089069 24 <0.0001 4.416 2.305-8.463 <0.0001 6 B*40 0.119134 0.066802 8.41 0.004 0.529 0.342-0.819 0.116 7 B*51 0.140794 0.076923 10.9 0.001 0.509 0.338-0.765 0.029 8 B*57 0.037906 0.17004 53 <0.0001 5.2 3.169-8.532 <0.0001 9 Cw*0602 0.124549 0.346154 79.9 <0.0001 3.795 2.772-5.197 <0.0001 10 Cw*0702 0.169675 0.105263 9.1 0.003 0.576 0.400-0.828 0.048 11 Cw*14 0.043321 0.022267 3.59 0.058 0.503 0.244-1.038 0.928 12 Cw*15 0.146209 0.068826 16.2 <0.0001 0.432 0.283-0.657 <0.0001 13 DRB1*03 0.191336 0.111336 13 0.0003 0.53 0.373-0.752 0.004 14 DRB1*0701 0.095668 0.180162 16.1 <0.0001 2.077 1.443-2.991 <0.0001 15 DRB1*1001 0.037906 0.08502 10.3 0.001 2.358 1.376-4.041 0.014 16 DRB1*11 0.106498 0.07085 4.07 0.044 0.64 0.413-0.990 0.616 17 DRB1*1302 0.021661 0.040486 3.88 0.049 2.083 0.988-4.392 0.686 18 DQB1*02 0.263538 0.172065 13.8 0.0002 0.57 0.422-0.770 0.002 19 DQB1*03032 0.018051 0.101215 36.7 <0.0001 6.819 3.317-14.019 <0.0001 20 DQB1*0602 0.039711 0.016194 4.59 0.032 0.418 0.183-0.952 0.352 DQB1*0604- 21 0.023466 0.044534 4.36 0.037 2.105 1.031-4.300 0.407 9 HLA= Human leukocyte antigen, F = Fisher exact test, CI = Confidence interval, OR = Odds ratio, Pc= P corrected. Role of HLA allelic, genotype and haplotype polymorphism
Table 3.4: Frequency Distribution of HLA Alleles in Controls and Type II Psoriasis Patients. Controls Patients S.No. Allele F Sig. OR 95 % CI Pc 277 79 1 A*11 0.144404 0.227848 6.32 0.012 1.748 1.125-2.717 0.204 2 A*24 0.129964 0.063291 5.39 0.021 0.452 0.228-0.899 0.357 3 B*15 0.039711 0.107595 11.1 0.001 2.916 1.508-5.639 0.029 4 B*18 0.025271 4.09 0.044 1.293 1.242-1.346 1.276 5 B*40 0.119134 0.063291 4.03 0.045 0.5 0.251-0.996 1.305 1.106- 6 B*4901 0.001805 0.018987 6.54 0.011 10.703 0.319 103.619 7 B*57 0.037906 0.107595 12 0.001 3.06 1.572-5.955 0.029 8 Cw*0602 0.124549 0.189873 5.57 0.019 1.745 1.093-2.784 0.304 9 Cw*15 0.146209 0.075949 5.37 0.021 0.48 0.255-0.905 0.336 10 DRB1*0701 0.095668 0.158228 4.95 0.026 1.777 1.064-2.966 0.364 11 DRB1*11 0.106498 0.050633 4.52 0.034 0.447 0.209-0.957 0.476 12 DRB1*1302 0.021661 0.06962 10.3 0.001 3.694 1.570-8.689 0.014 13 DQB1*0301/0304 0.120939 0.056962 5.32 0.022 0.439 0.214-0.902 0.242 14 DQB1*03032 0.018051 0.101266 27.2 <0.0001 6.823 2.954-15.762 <0.0001 15 DQB1*04 0.005415 0.031646 7.67 0.006 6.002 1.419-25.397 0.066 16 DQB1*05 0.203971 0.303797 7.05 0.008 1.703 1.145-2.533 0.088 HLA= Human leukocyte antigen, F = Fisher exact test, CI = Confidence interval, OR = Odds ratio, Pc= P corrected. Role of HLA allelic, genotype and haplotype polymorphism
Table 3.5: Frequency Distribution of HLA Alleles in Controls and Plaque Psoriasis Patients. Controls Patients S.No. Allele F Sig. OR 95 % CI Pc 277 270 1 A*01 0.16246 0.2463 11.952 0.001 1.685 1.250-2.271 0.017 2 A*03 0.11733 0.06852 7.902 0.005 0.547 0.357-0.838 0.085 3 A*24 0.12996 0.09074 4.286 0.039 0.668 0.455-0.981 0.663 4 A*26 0.07762 0.04444 5.25 0.022 0.553 0.331-0.924 0.374 5 A*3201 0.00722 0.03519 10.47 0.001 5.014 1.695-14.838 0.017 6 B*07 0.05776 0.02963 4.424 0.036 0.53 0.291-0.967 1.044 7 B*37 0.02166 0.07407 16.818 <0.0001 3.613 1.874-6.966 0.001 8 B*40 0.11913 0.06482 9.696 0.002 0.512 0.334-0.786 0.058 9 B*4901 0.00181 0.01296 4.702 0.03 7.263 0.891-59.229 0.87 10 B*51 0.14079 0.05926 20.44 <0.0001 0.384 0.250-0.591 0.0002 11 B*56 0.00722 3.92 0.048 1.982 1.869-2.102 1.392 12 B*57 0.03791 0.17963 60.11 <0.0001 5.557 3.411-9.056 <0.0001 13 Cw*01 0.03971 0.01852 4.335 0.038 0.456 0.214-0.973 0.608 14 Cw*0602 0.12455 0.34074 79.985 <0.0001 3.735 2.740-5.092 <0.0001 15 Cw*0702 0.16968 0.11296 7.267 0.007 0.623 0.441-0.881 0.112 16 Cw*14 0.04332 0.01482 7.868 0.005 0.332 0.148-0.746 0.08 17 Cw*15 0.14621 0.05741 22.744 <0.0001 0.368 0.240-0.564 <0.0001 18 Cw*16 0.02708 0.01111 4.849 0.028 0.336 0.121-0.931 0.448 19 DRB1*03 0.19134 0.10926 13.821 0.0002 0.528 0.375-0.744 0.003 20 DRB1*0701 0.09567 0.19259 21.268 <0.0001 2.255 1.581-3.215 <0.0001 21 DRB1*1001 0.03791 0.07407 6.824 0.009 2.03 1.181-3.492 0.126 22 DRB1*11 0.1065 0.06296 6.692 0.01 0.564 0.363-0.875 0.14 23 DRB1*1302 0.02166 0.04815 6.728 0.01 2.497 1.221-5.105 0.14 24 DQB1*02 0.26354 0.17593 12.727 0.0004 0.593 0.444-0.793 0.004 25 DQB1*03032 0.01805 0.11482 45.521 <0.0001 7.854 3.862-15.973 <0.0001 26 DQB1*5 0.20397 0.25926 4.714 0.03 1.366 1.030-1.812 0.33 27 DQB1*0604-9 0.02347 0.0463 5.093 0.024 2.193 1.090-4.410 0.264 HLA= Human leukocyte antigen, F = Fisher exact test, CI = Confidence interval, OR = Odds ratio, Pc= P corrected. Role of HLA allelic, genotype and haplotype polymorphism
Table 3.6: Frequency Distribution of HLA Alleles in Controls and Type I Plaque Psoriasis Patients. Controls Patients S.No. Allele F Sig. OR 95 % CI Pc 277 207 1 A*01 0.16246 0.26087 14.283 0.0002 1.82 1.358-2.493 0.003 2 A*03 0.11733 0.06522 7.857 0.005 0.513 0.319-0.825 0.085 3 A*26 0.07762 0.04348 4.69 0.031 0.54 0.307-0.951 0.527 4 A*3201 0.00722 0.03623 10.454 0.001 5.169 1.703-15.692 0.017 5 B*07 0.05776 0.02657 4.534 0.033 0.487 0.248-0.957 0.957 6 B*37 0.02166 0.08454 20.671 <0.0001 1.059 0.725-1.547 <0.0001 7 B*40 0.11913 0.06763 7.206 0.007 0.536 0.338-0.851 0.203 8 B*51 0.14079 0.05314 20.018 <0.0001 0.342 0.209-0.560 <0.0001 9 B*57 0.03791 0.19807 68.3 <0.0001 6.269 3.808-10.321 <0.0001 10 Cw*01 0.03971 0.01691 4.249 0.04 0.416 0.176-0.983 0.64 11 Cw*0602 0.12455 0.37923 96.375 <0.0001 4.383 3.176-6.050 <0.0001 12 Cw*0702 0.16968 0.10387 8.503 0.004 0.567 0.386-0.834 0.064 13 Cw*14 0.04332 0.01449 6.588 0.01 0.325 0.132-0.802 0.16 14 Cw*15 0.14621 0.06039 17.025 <0.0001 0.391 0.247-0.621 <0.0001 15 Cw*16 0.02708 0.00725 5.122 0.024 0.262 0.075-0.912 0.384 16 DRB1*03 0.19134 0.10628 12.423 0.0005 0.515 0.354-0.750 0.007 17 DRB1*0701 0.09567 0.19807 21.11 <0.0001 2.335 1.609-3.388 <0.0001 18 DRB1*1001 0.03791 0.08454 9.528 0.002 2.344 1.343-4.090 0.028 19 DRB1*11 0.1065 0.06522 5.003 0.026 0.585 0.364-0.941 0.364 20 DQB1*02 0.26354 0.17391 11.198 0.001 0.587 0.429-0.805 0.011 21 DQB1*03032 0.01805 0.11594 44.356 <0.0001 7.942 3.850-16.384 <0.0001 HLA= Human leukocyte antigen, F = Fischer exact test, CI = Confidence interval, OR = Odds ratio, Pc= P corrected. Role of HLA allelic, genotype and haplotype polymorphism
Table 3.7: Frequency Distribution of HLA Alleles in Controls and Type II Plaque Psoriasis Patients. Controls Patients S.No. Allele F Sig. OR 95 % CI Pc 277 63 1 A*11 0.1444 0.24603 7.829 0.005 1.933 1.209-3.092 0.085 2 A*24 0.12996 0.06349 4.385 0.037 0.454 0.213-0.968 0.629 3 A*3201 0.00722 0.03175 5.337 0.021 4.508 1.112-18.276 0.357 4 B*15 0.03971 0.12698 15.105 0.0001 3.517 1.789-6.914 0.003 5 B*40 0.11913 0.05556 4.345 0.037 0.435 0.195-0.972 1.073 6 B*4901 0.00181 0.02381 8.582 0.004 13.488 1.391-130.762 0.116 7 B*57 0.03791 0.11905 13.712 0.0002 3.43 1.714-6.862 0.006 8 Cw*0303 0.00903 0.03175 4.07 0.044 3.6 0.953-13.603 0.704 9 Cw*0602 0.12455 0.21429 8.458 0.004 2.042 1.250-3.336 0.064 10 Cw*15 0.14621 0.04762 9.036 0.003 0.292 0.124-0.685 0.048 11 DRB1*0701 0.09567 0.1746 6.562 0.011 2 1.165-3.432 0.154 12 DRB1*1302 0.02166 0.0873 15.206 0.0001 4.722 1.999-11.154 0.001 13 DQB1*02 0.26354 0.18254 3.915 0.048 0.613 0.375-1.000 0.528 14 DQB1*03032 0.01805 0.11111 29.409 <0.0001 7.569 3.198-17.919 <0.0001 15 DQB1*04 0.00542 0.02381 3.983 0.046 4.48 0.893-22.460 0.506 16 DQB1*05 0.20397 0.29365 4.822 0.028 1.622 1.050-2.508 0.308
17 DQB1*0604-9 0.02347 0.05556 4.357 0.037 2.657 1.024-6.891 0.407 HLA= Human leukocyte antigen, F = Fisher exact test, CI = Confidence interval, OR = Odds ratio, Pc= P corrected. Role of HLA allelic, genotype and haplotype polymorphism
Table 3.8: Five-Locus Haplotype Frequencies (HLA Class I and II) in Psoriasis Patients and Controls. Patients Controls Analysis of Odds ratio A-B-C-DRB1- (326) (277) variance DQB HF LD (x HF LD (x F-test p- Pc (95% CI) p-value (%) 100) (%) 100) value value 01 1516/1517 1.2 1.2 0.4 0.4 2.733 0.099 3.46(0.73-16.43) 0.088 26.4 0701 1302 0604-9 01 37 0602 1001 2.3 2.3 0.7 0.7 4.825 0.028 3.29(1.08-10.04) 0.022 6.6 05 01 57 0602 0701 <0.00 0.000 4.5 4.5 0.4 0.4 21.179 13.94(3.30-58.86) 0.0000006 03032 01 18
02 08 0702 03 02 0.9 0.9 1.1 1.1 0.094 0.759 0.85(0.29-2.44) 0.482 144.6
02 40 15 15 0601 0.9 0.9 1.9 1.9 2.447 0.118 0.45(0.17-1.24) 0.092 27.6
02 52 12 15 0601 1.2 1.2 0.9 0.9 0.595 0.441 1.54(0.51-4.66) 0.301 90.3
11 15 04 15 05 2.1 2.1 0.0 0.0 12.137 0.001 0.00016 0.048
11 57 0602 0701 1.7 1.7 0.0 0.0 10.37 0.001 0.001 0.3 03032
26 08 0702 03 02 2.3 2.3 3.9 3.9 2.812 0.094 0.56(0.28-1.1) 0.063 18.9
30 13 0602 0701 1.4 1.4 0.9 0.9 0.595 0.441 1.54(0.51-4.66) 0.309 92.7 02
33 58 0302/0304 0.9 0.9 1.4 1.4 0.715 0.398 0.63(0.22-1.84) 0.28 84 03 02
HLA= Human leukocyte antigen, F = Fisher exact test, CI = Confidence interval, OR = Odds ratio, P c = P corrected, HF: Haplotype frequency; LD: Linkage disequilibrium. Only haplotypes with frequency greater than 2% in either patients or controls are shown. Role of HLA allelic, genotype and haplotype polymorphism
Table 3.9: Three-Locus Haplotype Frequencies (HLA Class I) in Psoriasis Patients and Controls. Patients Controls Analysis of Odds ratio (326) (277) variance A-B-C LD LD F-test Pc HF HF (x (x value p-value (95% CI) p-value (%) (%) 100) 100) 01 07 0702 0.3 0.3 1.4 1.2 2.097 0.148 0.421(0.126-1.407) 0.124 24.8 01 1516/1517 1.5 1.5 1.0 1.0 0.496 0.464 1.423(0.514-3.939) 0.337 0701 67.4 01 35 04 0.8 0.3 1.4 1.1 0.228 0.633 1.232(0.523-2.904) 0.399 79.8 01 37 0602 4.6 4.1 1.2 1.1 13.601 0.0002 4.166(1.828-9.493) <0.0001 0.04 01 52 12 0.9 0.8 1.7 1.6 0.057 0.811 1.107(0.481-2.544) 0.491 98.2 <0.000 01 57 0602 9.3 8.2 2.3 2.2 26.846 <0.0001 4.198(2.327-7.573) <0.0001 1 02 08 0702 1.0 0.9 0.9 0.6 0.215 0.643 1.278(0.452-3.614) 0.422 84.4 02 35 04 1.3 0.9 0.4 0.0 0.979 0.323 1.590(0.630-4.013) 0.224 44.8 02 40 0302/0304 1.1 1.0 0.2 0.1 2.053 0.152 2.995(0.620-14.478) 0.136 27.2 02 40 15 2.0 1.9 3.2 3.0 2.391 0.122 0.573(0.280-1.171) 0.086 17.2 02 5001 0602 1.3 1.2 1.2 1.1 0.031 0.86 1.094(0.405-2.956) 0.533 106.6 02 51 15 0.7 0.6 1.3 1.0 1.287 0.257 0.527(0.172-1.622) 0.196 39.2 02 52 12 1.2 1.1 1.1 1.0 0.016 0.9 0.943(0.381-2.338) 1 200 10.369(1.344- 02 57 0602 0.8 0.1 0.2 0.1 7.777 0.005 0.004 79.995) 0.8 03 07 0702 0.8 0.7 1.4 1.3 1.92 0.166 0.468(0.156-1.405) 0.132 26.4 03 08 0702 0.1 0.1 1.5 1.3 7.922 0.005 0.093(0.012-0.737) 0.005 1 03 35 04 1.7 1.5 2.0 1.8 0.667 0.414 0.714(0.317-1.607) 0.27 54 03 52 12 1.1 1.1 0.8 0.7 0.295 0.587 1.364(0.444-4.194) 0.399 79.8 11 15 04 2.1 2.0 1.1 1.0 2.08 0.149 2.004(0.765-5.251) 0.111 22.2 11 35 04 3.3 2.9 3.3 3.0 0.055 0.815 1.076(0.583-1.986) 0.47 94 11 40 15 0.0 -0.1 1.9 1.6 13.186 0.0003 1.021(1.008-1.032) <0.0001 0.06 11 52 12 1.5 1.4 1.5 1.4 0.701 0.403 1.426(0.619-3.284) 0.266 53.2 11 57 0602 2.7 1.8 1.5 1.4 19.314 <0.0001 0.966(0.952-0.980) 0 0 24 35 04 1.3 1.1 1.3 1.1 0.114 0.736 1.171(0.468-2.933) 0.461 92.2 24 35 1203 1.0 1.0 0.9 0.8 0.089 0.766 1.192(0.376-3.776) 0.5 100 24 51 14 0.2 0.2 1.6 1.5 7.955 0.005 0.152(0.034-0.688) 0.005 1 24 57 0602 0.6 0.2 0.3 0.2 4.189 0.041 4.299(0.938-19.704) 0.036 7.2 26 08 0702 2.8 2.7 4.4 4.2 2.675 0.102 0.601(0.324-1.113) 0.07 14 30 13 0602 1.6 1.5 1.3 1.2 0.365 0.546 1.341(0.516-3.483) 0.36 72 HLA= Human leukocyte antigen, F = Fisher exact test, CI = Confidence interval, OR = Odds ratio, Pc = P corrected, HF: Haplotype frequency; LD: Linkage disequilibrium. Only haplotypes with frequency greater than 2% in either patients or controls are shown. Role of HLA allelic, genotype and haplotype polymorphism
Table 3.10: Two-Locus Haplotype Frequencies (HLA Class II) in Psoriasis Patients and Controls. Patients Controls Analysis of Odds ratio (326) (277) variance DRB1, LD DQB1 HF HF LD (x F-test (x P-value (95% CI) P-value Pc (%) (%) 100) value 100) 01 05 2.4 1.6 4.5 3.6 3.871 0.049 0.532(0.281-1.008) 0.036 2.16 03 02 10.9 8.8 17.2 12.2 10.203 0.001 0.525(0.366-0.753) 0.0003 0.018 03 0301 0.6 -0.4 0.4 -1.9 0.749 0.387 0.604(0.191-1.913) 0.282 16.92 03 0603 0.2 -1.2 0.3 -2.1 5.619 0.018 0.120(0.015-0.979) 0.02 1.2 04 02 0.2 -0.7 1.1 -0.8 6.853 0.009 0.167(0.037-0.767) 0.009 0.54 04 0301 0.3 -0.1 1.3 0.4 3.707 0.054 0.240(0.050-1.162) 0.055 3.3 04 0302 3.4 3.2 3.6 3.3 0.049 0.824 0.932(0.503-1.727) 0.473 28.38 0701 02 6.7 3.6 6.0 3.5 0.002 0.962 1.011(0.643-1.590) 0.528 31.68 <0.000 0701 03032 8.9 7.1 1.6 1.4 30.903 5.913(2.902-12.048) <0.0001 1 <0.0001 0701 0601 0.3 -2.1 0.2 -1.2 1.408 0.236 1.884(0.651-5.456) 0.176 10.56 08 04 1.7 1.6 0.2 0.0 6.929 0.009 9.490(1.221-73.736) 0.007 0.42 1001 05 6.9 5.0 3.6 2.8 6.388 0.012 1.979(1.154-3.395) 0.008 0.48 1001 0601 0.2 -0.8 0.0 -0.6 6.871 0.009 1.860(1.765-1.961) 0.007 0.42 11 02 0.0 -1.2 0.9 -1.9 10.749 0.001 2.196(2.064-2.337) 0.001 0.06 11 0301 6.0 5.4 7.9 6.6 1.796 0.18 0.737(0.472-1.153) 0.11 6.6 11 05 0.5 -1.3 0.4 -1.8 1.152 0.283 0.590(0.223-1.561) 0.203 12.18 11 0601 0.0 -0.9 0.7 -0.9 9.537 0.002 2.194(2.062-2.334) 0.002 0.12 12 0301 0.5 0.4 1.4 1.2 3.211 0.073 0.315(0.083-1.195) 0.068 4.08 13 05 0.3 -1.9 0.0 -1.6 6.871 0.009 1.860(1.765-1.961) 0.007 0.42 13 0603 8.0 7.0 7.2 6.2 0.242 0.623 1.114(0.725-1.710) 0.352 21.12 1302 0604-9 3.2 3.0 1.4 1.3 4.036 0.045 2.271(0.998-5.169) 0.033 1.98 14 05 6.3 4.5 5.4 4.2 0.412 0.521 1.172(0.722-1.904) 0.303 18.18 15 0301 0.2 -1.8 0.4 -2.8 11.367 0.001 0.119(0.027-0.524) 0.001 0.06 15 03032 0.2 -2.2 0.0 -0.4 12.137 0.001 1.868(1.772-1.970) <0.0001 0.06 15 05 7.8 1.5 3.6 -1.3 13.969 0.0002 2.607(1.548-4.392) <0.0001 0.012 15 0601 13.0 9.7 12.9 9.4 0 0.983 1.004(0.717-1.405) 0.527 31.62 15 0602 1.2 0.8 3.7 2.7 8.432 0.004 0.315(0.139-0.718) 0.003 0.18 15 0603 1.5 -1.2 3.1 0.0 0.125 0.723 0.891(0.471-1.687) 0.423 25.38 16 05 1.1 0.8 1.4 1.0 0.334 0.563 0.741(0.267-2.056) 0.374 22.44 HLA= Human leukocyte antigen, F = Fischer exact test, CI = Confidence interval, OR = Odds ratio, Pc= P corrected, HF: Haplotype frequency; LD: Linkage disequilibrium. Only haplotypes with frequency greater than 2% in either patients or controls are shown.
Role of HLA allelic, genotype and haplotype polymorphism
Table 3.11: Meta Analysis of HLA Class I and II Alleles from Available studies. S. Alleles Studied Population Sample size No. White population of British origin, Korean and 1 A*01 404 patients and 925 Ct Pakistani population White population of British origin and Pakistani 2 A*3201 320 patients and 827 population White population of British origin, Korean, Croatian 3 B*37 512 patients and 1064 Ct and Pakistani population White population of British origin, Korean and 4 B*51 404 patients and 925 Ct Pakistani population White population of British origin, Korean, Turkish, 5 B*57 567patients and 1429 Ct Omani, Indian and Pakistani population White population of British origin, Korean, 6 Cw*0602 Croatian, Turkish, Omani, Slovak and Pakistani 785 patients and 1562 Ct population 7 Cw*15 Slovak and Pakistani population 417 patients and 471 Ct White population of British origin, Korean, Slovak 8 DRB1*03 551patients and 1119 Ct and Pakistani population White population of British origin, Croatian, 9 DRB1*0701 701 patients and 1464 Ct Turkish, Omani, Slovak and Pakistani population 10 DQB1*02 Korean, Omani, Slovak and Pakistani population 555 patients and 669 Ct
11 DQB1*03032 Korean, Slovak and Pakistani population 501 patients and 569 Ct
Role of HLA allelic, genotype and haplotype polymorphism
Meta Analysis
Model HLA-A*3201 Statistics for each study Odds ratio and 95% CI Odds Lower Upper ratio limit limit Z-Value p-Value This study 5.014 1.695 14.835 2.913 0.004 woodrow 1985 0.320 0.043 2.385 -1.112 0.266 Fixed 2.694 1.037 6.997 2.035 0.042 Random 1.450 0.099 21.224 0.271 0.786
0.01 0.1 1 10 100
Favours A Favours B
Meta AnalysisFigure 3.2: Forest plot of HLA-A*3201 and psoriasis vulgaris in overall studies.
Meta Analysis
Model HLA-B*57 Statistics for each study Odds ratio and 95% CI Odds Lower Upper ratio limit limit p-Value Z-Value This study 5.557 3.410 9.055 0.000 6.885 Woodrow 1985 7.573 4.014 14.288 0.000 6.250 Kim 2000 6.139 0.703 53.623 0.101 1.641 Aasoy 2006 20.000 6.643 60.215 0.000 5.327 Al-Mamari 2009 1.412 0.304 6.556 0.660 0.440 Umapathy 2011 7.996 3.740 17.095 0.000 5.362 Fixed 6.732 4.896 9.255 0.000 11.741 Random 6.884 4.283 11.063 0.000 7.968 0.01 0.1 1 10 100
Favours A Favours B
Meta AnalysisFigure 3.3: Forest plot of HLA-B*57 and psoriasis vulgaris in overall studies. Role of HLA allelic, genotype and haplotype polymorphism
Meta Analysis
Model HLA-Cw*0602 Statistics for each study Odds ratio and 95% CI Odds Lower Upper ratio limit limit p-Value Z-Value This study 3.735 2.740 5.092 0.000 8.335 Woodrow 1985 8.381 3.947 17.796 0.000 5.534 Kim 2000 36.000 14.928 86.819 0.000 7.979 Kastelan 2000 21.010 9.660 45.696 0.000 7.681 Atasoy 2006 21.111 9.104 48.953 0.000 7.107 Al-Mamari 2009 2.019 0.907 4.495 0.085 1.721 Shawkatová 2013 3.850 2.176 6.813 0.000 4.629 Fixed 5.658 4.552 7.031 0.000 15.628 Random 8.414 4.079 17.355 0.000 5.766 0.01 0.1 1 10 100
Favours A Favours B
Meta AnalysisFigure 3.4: Forest plot of HLA-Cw*0602 and psoriasis vulgaris in overall studies.
Meta Analysis
Model HLA-DRB1*0701 Statistics for each study Odds ratio and 95% CI Odds Lower Upper ratio limit limit p-Value Z-Value This study 2.255 1.581 3.216 0.000 4.491 Woodrow 1985 3.962 2.046 7.673 0.000 4.083 Kastelan 2000 3.833 2.144 6.853 0.000 4.533 Atasoy 2006 10.154 4.308 23.933 0.000 5.299 Al-Mamari 2009 0.578 0.198 1.688 0.316 -1.003 Shawkatová 2013 2.560 1.745 3.755 0.000 4.810 Fixed 2.772 2.242 3.426 0.000 9.423 Random 2.946 1.828 4.747 0.000 4.438 0.01 0.1 1 10 100
Favours A Favours B
Meta AnalysisFigure 3.5: Forest plot of HLA-DRB1*0701 and psoriasis vulgaris in overall studies.
Table 3.12: Summary of Meta-Analysis Results of Case-Control Studies of HLA Class I Alleles. Role of HLA allelic, genotype and haplotype polymorphism
Total Odds Ratio (95%CI) Model Z-value p-value Studies HLA-A*01 Fixed 3 1.906(1.467-2.475) 4.832 0 Random 2.806(1.266-6.221) 2.54 0.011 HLA-A*3201 Fixed 2 2.694(1.037-6.997) 2.035 0.042 Random 1.450(0.099-21.224) 0.271 0.786 HLA-B*37 Fixed 4 5.774(3.460-9.635) 6.711 0 Random 7.653(3.146-18.620) 4.487 0 HLA-B*51 Fixed 3 0.377(0.258-0.552) -5.016 0 Random 0.377(0.258-0.552) -5.016 0 HLA-B*57 Fixed 6 6.732(4.896-9.255) 11.741 0 Random 6.884(4.283-11.063) 7.968 0 HLA-Cw*0602
7 Fixed 5.658(4.552-7.031) 15.628 0 Random 8.414(4.079-17.355) 5.766 0 HLA-Cw*15 Fixed 2 0.396(0.263-0.597) -4.42 0 Random 0.454(0.208-0.993) -1.977 0.048 Table 3.13: Summary of Meta-Analysis Results of Case-Control Studies of HLA Class II Alleles. Total Odds Ratio (95%CI) Model Z-value p-value Studies HLA-DRB1*03 Fixed 4 0.556(0.421-0.735) -4.123 0 Random 0.549(0.365-0.826) -2.877 0.004 HLA-A*0701 Fixed 6 2.772(2.242-3.426) 9.423 0 Random 2.946(1.828-4.747) 4.438 0 HLA-DQB1*02
4 Fixed 0.837(0.688-1.019) -1.776 0.076 Random 0.943(0.530-1.677) -0.199 0.842 HLA-B*03032
3 Fixed 1.289(0.836-1.987) 1.15 0.25 Random 1.290(0.164-10.120) 0.242 0.809 3.4. Discussion Role of HLA allelic, genotype and haplotype polymorphism
Human leukocyte antigen region on chromosome 6p21 is known to carry the most important genetic factors for psoriasis susceptibility. The critical segment appears to be a 300-kb interval at the centromeric end of the chromosome, named PSORS1 (Nair et al., 2000).
Association of psoriasis with various alleles of the MHC genes has been known for over three decades and presently there are numerous association studies with these alleles.
Association of both HLA class I and class II antigens (e.g. HLA-B13, B17, DR7) with psoriasis were initially reported by serologic methods in 1970s (Russel et al., 1972).
Molecular genotyping was introduced in later years and subsequently many independent groups have proved HLA allele -Cw*0602 to confer the major and most consistent risk factor
(Asahina et al., 1991; Elder et al., 1994; Pasic et al., 2009). Other HLA alleles reported to be associated include A1, A2, A30, B13, B17 (B57, 58), B37, B39, B46, Cw6, Cw7, Cw9,
Cw11 and DR7. These associations however differ between patients of different racial and ethnic backgrounds (Tiwari et al., 1982; Elder et al., 1994; Ikaheimo et al., 1996; Henseler,
1997).
In this study 94 HLA class I and II alleles were genotyped in psoriasis patients and controls.
Of these alleles 62 were from HLA class I locus and 32 from HLA class II locus. Significant association was observed with 26 HLA alleles (14 alleles from class I locus and 12 alleles from class II locus). This study highlights the importance of HLA region in the psoriasis pathogenesis in Pakistani population also.
3.4.1. HLA Class I and class II association with Psoriasis in cases and controls:
We observed strong positive association of HLA-A*3201, B*37, B*40, B*51, B*57,
Cw*0602, Cw*15, DRB1*03, DRB1*0701, DQB1*02, and DQB1*03032 alleles with psoriasis after applying bonferroni correction. Alleles HLA-B*40, B*51, Cw*15, DRB1*03 Role of HLA allelic, genotype and haplotype polymorphism and DQB1*02 showed protection with the disease. When we analyzed only plaque samples
(n= 270) out of these 326 samples we found the same allelic associations except for HLA-
B*40 which was marginally associated with plaque psoriasis (Pc=0.058) and HLA-A*01 which showed marginal association in all samples (n=326) showed strong association in plaque samples (Pc=0.017).
3.4.2. Association of HLA Class I and Class II Alleles with Type I and II Psoriasis
Two types of psoriasis can be classified based on the age of onset. Type I psoriasis is the early onset type that begins before the age of 40 and type II psoriasis has a later onset and develops after the age of 40 (Henseler and Christophers, 1985).When we compared type I and type II psoriasis samples; HLA-A*01, A*3201, B*37, B*51, Cw*0602, DRB1*03,
DRB1*0701 and DQB1*02 alleles showed highly significant associations only in type I samples whereas HLA-B*57 and DQB1*03032 alleles were significant both in type I and type II samples. Strong association has been established between HLA-Cw*0602 and type I psoriasis in other studies and our results support these facts (Henseler and Christophers,
1985; Mallon et al., 1997). HLA-DRB1*07, B*13 and B*57 were reported to be present more frequently in early onset psoriasis patients (Henseler, 1997). Schmitt-Egenolf et al., 1996 found an association between the HLA-DR7 antigen and type I but not type II psoriasis. They also observed that B*57 and Cw*0602 antigens conferred a significantly higher relative risk of developing type I psoriasis.
The association unique to type II samples were HLA-B*15 and DRB1*1302. Association with HLA-A*3201, B*40, Cw*15 and DRB1*03 with psoriasis has not been reported previously. HLA-A*3201 was observed to be positively associated with the disease whereas rest of the alleles were shown to confer protection against the disease. Several alleles Role of HLA allelic, genotype and haplotype polymorphism reported to be associated with psoriasis in other populations did not reach significance level
(p < 0.05 after applying Bonferroni correction) in our psoriasis samples. HLA-A*02 and
B*13 alleles most frequently reported to be associated in Caucasian and other ethnic groups
(Russell et al., 1972; Henseler and Christophers, 1985; Schmitt-Egenolf et al., 1993;
O’Donnell et al., 1993; Gonzaga et al., 1996; Kim et al., 2000; Choonhakarn et al., 2002;
Zhang et al., 2003) were not associated in this study. It reflects the previously observed population variation of disease association.
We observed a strong positive association of psoriasis with HLA-Cw*0602, also reported in white population of European descent as well as in several other ethnically different groups.
HLA-Cw*0602 allele has been reported to be associated with type I psoriasis and the present study also confirms the same association. It is emphasized that the presence of Cw*0602 is sufficient to indicate a clinically significant risk of psoriasis (Ikaheimo et al., 1996).
Association with HLA-Cw*07 allele has been reported in Japanese population (Roitberg-
Tambur et al., 1994; Asahina et al., 1996). In this study allele Cw*0702 gave a border line significance (Pcor = 0.048) value in an overall analysis with type I samples (Table 3.3).
Association of psoriasis with HLA-A*01, B*37, B*51, B*57, Cw*0602, DRB1*0701,
DQB1*02, and DQB1*03032 has been reported in Caucasian population (Schmitt-Egenolf et al., 1993; Gonzaga et al., 1996; Schmitt-Egenolf et al., 1996; Shawkatová et al., 2013).
Association with DRB1*1001 allele has been reported in the Korean population (Kim et al.,
2000); where the reported association was both with psoriasis vulgaris and type I PV samples but not with type 2 samples. In our study the association with DRB1*1001 was also observed with type I samples only (Table 3.3 and 3.6).
3.4.3. Haplotype Analysis of HLA Class I and Class II Alleles Role of HLA allelic, genotype and haplotype polymorphism
Five locus haplotypes for the HLA loci A, B, C, DRB and DQB1 were generated by
Arlequin. Haplotypes with frequencies more than 2% in each group were considered for analysis as shown in Table 3.8. The haplotype HLA-A*01-B*57-Cw*0602-DRB1*0701-
DQB1*03032 showed high significance (P = 0.0000006) which is consistent with previous reported studies. In German, Italian and Thai populations, the extended haplotype (EH) HLA-
Cw*06-B*57-DRB1*0701-DQA1*0201- DQB1*0303 named according to the B allele EH-
57.1, was reported to be highly over-represented in patients with psoriasis (Schmitt-Egenolf
1996; Choonhakarn et al., 2002). Another similar predisposing haplotype, HLA-C*0602-
B57-DRB1*0701-DQA1*0201-DQB1*0201 (EH-57.2), was observed in Croatian patients
(Kastelan et al., 2003) but it was not present in our samples. Another haplotype that had significant p-value (P = 0.022) in our samples was HLA*01-B*37-Cw*0602-DRB1*1001-
DQB1*05, this haplotype is reported as risk haplotype in Korean psoriasis samples (Kim et al., 2000).
Two other haplotypes that were significant in our samples were HLA-A*11-B*15-Cw*04-
DRB1*15-DQB1*05 (P=0.00016) and HLA-A*11-B*57-Cw*0602-DRB1*0701-
DQB1*03032 (P=0.001). These were novel risk haplotypes not reported previously in any other population. The haplotype HLA-A*30-B*13-Cw*0602-DRB1*0701-DQB1*02 reported as a risk haplotype in North eastern Thai population (Choonhakarn et al., 2002) was also noted at a frequency of more than 2% but was not significant in the studied samples.
Bonferroni correction was applied and the only haplotype that showed significance was the ancestral haplotype (EH 57.1). The results reflect that many of the associated alleles tend to vary among patients of different racial and ethnic backgrounds. Deviation from Hardy
Weinberg equilibrium was observed for different loci both in patients and controls. Although Role of HLA allelic, genotype and haplotype polymorphism the samples were from unrelated individuals the deviation could be the result of inbreeding following many generations of consanguineous marriages in Pakistan. The other reason could be due to multi alleleic nature of the locus (Ohta, 1998; Sommer, 2005). The deviation from the equilibrium did not affect the strongest associations observed for different HLA alleles and haplotypes that are observed in other populations that reflect the true HLA associations rather than mere chance in our population.
Haplotype analysis was also performed separately with class I (three loci) and class II (two loci) and the results are shown in Tables 3.9 and 3.10 respectively. As expected, a strong association was seen with haplotype HLA-A*01-B*57-Cw*0602 which is the class I side of the extended haplotype EH57.1. Similarly for class II strong association was observed with
DRB1*0701-DQB1*03032 which is the class II side of EH57.1. Both these haplotypes showed significant variation between the two groups and the alleles were in strong linkage disequilibrium.
3.4.4. Meta-Analysis of HLA Class I and Class II Alleles
A significant association (p<0.00) between the HLA-B*37, B*51, B*57, Cw*0602 and psoriasis vulgaris was observed in overall analysis considering both fixed and random models and the meta analysis of these alleles including our study proves the importance of significance of these results in comparison with other world populations. As evident from the forest plot, present study is in conformity with previously reported studies on world populations showing a similar trend of association of these alleles with risk of psoriasis vulgaris.
Alleles HLA-A*01, Cw*15 and DRB1*03 showed significant association while considering fixed model (p<0.00) and with the random model gave p values of 0.011, 0.048 and 0.004 Role of HLA allelic, genotype and haplotype polymorphism respectively. Results of analysis for these three alleles are in conformity with the different population studies and therefore verify the significance of association with psoriasis vulgaris.
In case of HLA-DRB1*0701 significant association (p<0.00) was observed in over all analysis considering both fixed and random models. Out of 6 studies of White population of
British origin, Croatian, Turkish, Oman, Slovak and Pakistani populations (701 patients and
1464 controls) all the studies verify the association except one study from Oman as can be seen from the forest plot of all the studies (Figure 3.5).
In case of HLA-A*3201 marginal association was found with the fixed model (p= 0.042) while no association was found with the random model (p= 0.786) (Table 3.12). HLA-
A*3201 allele is not reported to be associated with psoriasis vulgaris in any other study and the forest plot for this allele verifies as data available from only one study deviate from our study (Figure 3.2). However, we did find association in our population in the present study and it is possible that this association is population specific.
In case of HLA-DQB1*02 and DQB1*03032 no significant associations was found in combined analysis with either of the models (Table 3.12 and 3.13). If we look at the forest plot of HLA-DQB1*02 the studies from Omani and Slovak populations follow the same whereas Korean study deviates from our study. In case of DQB1*03032 we used two studies one from Korean and the other from Slovak populations in addition to our study (501 patients and 569 controls), both the studies deviate from our study and is shown in the forest plot.
In conclusion, HLA allelic association with psoriasis samples confirmed the previous consistently strong associations with HLA-B*57 and Cw*0602. We also observed novel association with HLA-A*3201, B*40, Cw*15 and DRB1*03 as they are not reported in any other population. In the haplotype analysis, we observed strong association with haplotype Role of HLA allelic, genotype and haplotype polymorphism
EH-57.1, consistently reported to be associated with psoriasis in other populations also. In addition novel haplotype associations were also observed in along with some positive and negative haplotype associations reported previously in other ethnic groups. In meta analysis most of the associated alleles follow the same trend reported in other populations except for
DRB1*0701 for which the study from Oman and in case of DQB1*02 the Korean study deviates from present study. Whereas, meta-analysis for A*3201 and DQB1*03032 alleles deviate from the reported studies. ACE gene polymorphism study
4. ACE gene polymorphism study
4.1. Introduction
Angiotensin-converting enzyme (ACE), a zinc metallopeptidase is the key enzyme of rennin angiotension system (RAS) and is also called Kininase II. It is found on the surface of endothelial cells and exists as two isoforms, a somatic form (sACE, 150–180 kDa) and a smaller protein (gACE, 90–110 kDa) found exclusively in adult testes. This gene encodes an enzyme involved in catalyzing the conversion of angiotensin I into a physiologically active peptide angiotensin II. Angiotensin II is a potent vasopressor and aldosterone-stimulating peptide that controls blood pressure and fluid-electrolyte balance.
It is also involved in the degradation of circulating bradykinin and the haemoregulatory peptide, N-acetyl SDKP (Corvol et al., 1995).
ACE gene is localized on chromosome 17q23.10 (Crisan and Carr, 2000) (Fig. 4.1), and comprises of 26 exons and two promoters, and has clearly arisen by gene duplication
(Hubert et al, 1991). It was cloned in 1988 (Soubrier et al., 1988). ACE gene polymorphism study
Figure 4.1: Molecular Location of ACE gene on chromosome 17. (http://www.genecards.org/)
Expression and activity of ACE in blood depends upon an insertion and deletion polymorphism (Koh et al., 2003; Riget et al., 1990). A common genetic variant in the
ACE gene was described as deletion or absence (D allele) and insertion or presence (I allele) of 287 base pairs Alu repeat sequence (dbSNP rs4646994) in intron 16 of the gene
(Rigat et al., 1990). When the level of serum ACE was compared among the three genotype classes (II, DD and ID) it was found that deletion polymorphism has got the highest serum ACE level whereas intermediate levels were observed in heterozygotes i.e. in ID (Rigat et al., 1990). Genetic association studies have a correlation of this polymorphism with health, sports and also with the genesis and maintenance of various diseases. Polymorphisms in ACE gene may also predict the response to psoriasis therapy
(Huskic et al., 2007). ACE I/D polymorphism not only affects different disease prognosis but can also modify treatments given to patients. The main objective of this part of study ACE gene polymorphism study was to find out association of ACE I/D polymorphism with the disease in Pakistani patients.
4.2. Results
In the present study it was found that homozygous insertion (II) is associated with risk of psoriasis in the study population. It has shown OR=2.59, 95% CI=1.85-3.61 and p value
= <0.001 indicating a strong association of homozygous insertion with the disease. The heterozygous insertion (ID) gives protective association with OR=0.63, 95%CI=0.50-
0.81 and p value=0.00023. The genotype results for ACE I/D polymorphism are shown in
Table 4.1. No association was seen with homozygous deletion (DD). When the alleles were analyzed separately the results showed that ACE insertion allele was associated with susceptibility to psoriasis in the studied Pakistani population. It showed OR=1.36, 95%
CI=1.15-1.62 and p value=0.00044. These results have shown that I allele is associated with psoriasis risk in our population. The deletion allele was showing association with protection having OR=0.73, 95%CI=0.62-0.87 and p=0.00044 as shown in Table 4.1
When the polymorphism was further analyzed on the basis of age of onset and family history the association with II genotype was observed as shown in table 4.2. However when analyzed on the basis of gender it was found that II genotype and I allele frequency were significantly higher in male patients whereas no association was observed with female psoriasis patients (Tables 4.3 and 4.4). There were 322 psoriasis male patients and
316 male controls. Genotypic frequency of II was found significantly high with OR =
3.40, 95% CI=2.18-5.31 and p = <.0001 in male patients. ID genotypes was associated with protection of disease with OR = 0.58, 95% CI=0.43-0.79 and p = 0.00075 (Table
4.3). I allele was significantly higher in male patients as compared to the controls with ACE gene polymorphism study
OR = 1.53, 95% CI=1.23-1.91 and p= <.0.00015. Female psoriasis patients (n=164) and female controls (n=255) were also compared for this polymorphism. There was no significant difference between the two groups for the three genotypes or the two alleles
(Table 4.4). ACE gene polymorphism study
Table 4.1: Angiotensin-Converting Enzyme (ACE) Allele and Genotype in Psoriasis Cases and Controls.
Genotype Psoriasis Patients Controls Chi- OR(95%CI) p-value n=486 n=571 square
II 118(24%) 63(11%) 32.46 2.59 (1.85-3.61) <0.001 ID 239 (49%) 345(60%) 13.42 0.63 (0.50-0.81) 0.00023 DD 129(27%) 163(29%) 0.53 0.91 (0.69-1.19) 0.467 Allele I 475(49%) 471(41%) 12.35 1.36 (1.15-1.62) 0.00044 D 497(51%) 671(59%) 12.35 0.73 (0.62-0.87) 0.00044
Table 4.2: Angiotensin-Converting Enzyme (ACE) Genotype and Allele Frequencies with Respect to Age of Onset and Family History in the Psoriasis Group Age of onset Family history Genotype Onset < 40 years Onset > 40 years Positive (164) Negative (322) (382) (104) P- n(%) P-value n(%) P-value n(%) n(%) P-value value II 89(23%) <.0001 29(28%) <.0001 32(19%) 0.004 86(27%) <.0001
ID 188(49%) 0.00064 51(49%) 0.03 88(54%) 0.12 151(47%) <.0001
DD 105(28%) 0.718 24(23%) 0.252 44(27%) 0.663 85(26%) 0.492
Allele
I 366(48%) 0.004 109(52%) 0.0028 152(46%) 0.0997 323(50%) 0.00027
D 398(52%) 0.004 99(48%) 0.0028 176(54%) 0.0997 321(50%) 0.00027
ACE gene polymorphism study
Table 4.3: ACE Insertion/Deletion Polymorphism in Male Psoriasis Patients and Male Controls. Psoriasis Male Controls Chi- Genotype Patients OR(95%CI) p-value n=316 square n=322 II 87(27%) 31(10%) 31.33 3.40(2.18-5.31) <.0001 ID 157(49%) 196(62%) 11.36 0.58(0.43-0.79) 0.00075
DD 78(24%) 89(28%) 1.28 0.82(0.57-1.16) 0.258 Allele I 331(51%) 258(41%) 14.35 1.53(1.23-1.91) 0.00015 D 313(49%) 374(59%) 14.35 0.65(0.52-0.81) 0.00015
Table 4.4: ACE Insertion/Deletion Polymorphism in Female Psoriasis Patients and Female Controls. Psoriasis Female Controls Genotype patients Chi-square OR(95%CI) p-value n=255 n=164 II 31(19%) 32(13%) 3.15 1.62(0.952.78) 0.076 ID 82(50%) 149(58%) 2.87 0.711(0.48-1.06) 0.09 DD 51(31%) 74(29%) 0.21 1.10(0.72-1.69) 0.647 Allele I 144(44%) 213(42%) 0.37 1.09(0.82-1.44) 0.54 D 184(56%) 29758%) 0.37 0.92(0.691.21) 0.54
ACE gene polymorphism study
4.3. Discussion
Angiotensin Converting Enzyme (ACE) is the major regulator of Rennin Angiotensin
System/Rennin Angiotensin Aldosterone System (RAS/RAAS). ACE is expressed in a wide range of tissues including skin, endothelial and immune cells (Smallridge et al.,
1986, Petrov et al., 2000, Noveral et al., 1987). Significant role of ACE has been observed in normal cutaneous homeostasis and wound healing. It has been observed that the human skin contains the complete rennin Angiotensin system (RAS) which plays an important role in normal cutaneous homeostasis (Steckelings et al., 2004; Huskic et al.,
2008). It is believed that ACE may be involved in survival of skin fibroblasts, melanocytes, endothelial cells and Keratinocytes (Scholzen et al., 2003; Morihara et al.,
2006).
ACE is involved in cutaneous homeostasis as it converts Angiotensin I into Angiotensin
II, inactivates bradykinin via the kallikrein–kininogen system and plays a major role in the rennin–angiotensin system (RAS). It is suggested that inhibition of bradykinin degradation by ACE inhibitors alters the kinin–kallikrein arachidonic acid system that leads to increased concentrations of kinins and related inflammatory metabolites in the skin which might contribute to inflammatory skin lesions in psoriasis. Almost half of the patients with psoriasis have elevated serum ACE activity (Ryder et al., 1985).
ACE I/D polymorphism is one of the most studied Alu polymorphism in intron 16 which is considered as a functional marker to study various disease etiologies. Angiotensin
Converting Enzyme Insertion/Deletion (ACE I/D) polymorphism have widely been studied in various diseases including Cardiovascular, Renal, Hypertension, Alzheimer’s,
Cancer, Parkinson’s and various Auto inflammatory and Autoimmune diseases (Cambien ACE gene polymorphism study et al., 1992; Schunkert et al., 1994; Kario et al.,1996; Hohenfellner et al., 2001; Nawaz and Hasnain, 2009). Investigations of ACE I/D polymorphism regarding the possible role of this enzyme in the pathogenesis of skin diseases are very rare (Huskic et al., 2008).
Raff and co-workers reported an increase of serum ACE levels in patients with psoriasis for the first time (Raff et al., 1981) and this was confirmed in other studies also (Ryder et al., 1985; Kavala et a., 2005). Present study is based on the investigation of association of
ACE I/D polymorphism with psoriasis. In this study psoriasis patient population was in
Hardy Weinberg equilibrium (p= 0.725) as patients did not belong to each other but controls were not found consistent with this equilibrium (p= 0) as the samples were collected from the same area so this may be the reason for the deviation of controls from
Hardy Weinberg equilibrium, and also because of trend of consanguineous marriages in
Pakistani population as polymorphic gene pool or sufficient heterogeneity is not resulted in case of successive cousin marriages. Present study revealed the significant association of II genotype and I allele with susceptibility to Psoriasis.
Although many studies have investigated association between ACE gene polymorphisms and susceptibility to psoriasis, the results are still controversial. Relationship between the angiotensin-converting enzyme (ACE) insertion/deletion (I/D) polymorphism and psoriasis has previously been studied in Caucasians and in Asians. In Asian population II genotype was reported to be associated with psoriasis (Chang et al., 2007, Al-Awadhi et al., 2007, Yang et al., 2014) except for one study from china (Liu et al., 2007) in which no association was observed with ACE I/D polymorphism and psoriasis. Chang et al., reported that I allele may be a risk factor for development of psoriasis in Chinese
Taiwanese population. In another study reported in Chinese Population no significant ACE gene polymorphism study differences were seen in the distribution of ACE gene polymorphisms between psoriasis patients and controls (Liu et al., 2007). In another study reported in Chinese population
ACE II genotype frequency (odds ratio (OR) = 1.32, P = 0.01) and I allele frequency (OR
= 1.25, P = 0.01) in psoriasis patients was significantly higher as compared to control group. Also the D allele frequency in patients was significantly lower (OR = 0.80, P =
0.01) than that in the control group. When stratified by family history, DD genotype frequency was marginally significantly lower in patients with a positive family history of psoriasis than in those with negative family history (OR = 0.47, P = 0.04). When stratified by onset of the disease, type and severity of psoriasis, no statistically significant result was observed (Yang et al., 2014). Al-Awadhi et al., in 2007 studied ACE I/D polymorphism in 51 Kuwaiti patients with psoriatic arthritis and 100 controls and observed that II genotype may confer susceptibility to the development of late-onset psoriatic arthritis.
The association studies between the angiotensin-converting enzyme (ACE) insertion/deletion (I/D) polymorphism and psoriasis in Caucasian Population have yielded inconsistent results. A study in Czech Republic population with 200 patients and
208 controls did not find significant differences in the distribution of ACE gene polymorphisms between psoriasis patients and controls (Vasku et al., 1999). Ozkur et al., in 2004 studied this association in 86 Turkish patients with psoriasis and 154 controls and showed that ACE I/D polymorphism was not associated with age of onset, types or gender. However, I allele frequency was significantly higher in patients with a positive family history of psoriasis than in those with no family history (48% vs. 32%; P =0.03).
Furthermore, I allele was found significantly more frequent in type I psoriasis patients ACE gene polymorphism study
(onset < 40 years and positive family history) than in type II psoriasis patients (onset >/=
40 years, no family history) (48% vs. 27%; P = 0.04). Similar results were found in a study reported in Egyptian Population (Nagui et al., 2012). Weger et al., studied this polymorphism in Austrian psoriasis patients (207 patients and 182 controls) and found that the II genotype may affect susceptibility to early-onset psoriasis in a White Austrian population, however in another study reported in Greece Population ID genotype and D allele were more common in early-onset psoriasis (Veletza et al., 2008). In a large study reported in Spanish Population (268 cases and 272 controls), no significant association was seen with ACE gene and psoriasis patients (Coto-Segura et al., 2009).
Two meta-analysis studies have been published reporting the association of psoriasis with
ACE gene. In one meta-analysis comprising eight studies the results indicated that I/I genotype was associated with risk of psoriasis whereas I/D genotype may decrease the risk of psoriasis in Asian, but not in white populations (Liu et al., 2013). In the second meta- analysis comprising five studies on psoriasis the study showed significant associations of the DD+ID genotype with psoriasis. Ethnicity-specific meta-analysis of the D allele showed no association with psoriasis in Europeans (Song et al., 2013).
Our result showed that genotype II and allele I frequencies were significantly higher in
Pakistani psoriasis patients as compared to the control group. These findings were supported by several previous studies on Asian and Caucasian population. However there are few differences as we did not find any remarkable difference in association with age at onset and also with family history of psoriasis as reported in the literature (Ozkur et al.,
2004, Nagui et al., 2012, Ozkur et al., 2004, Nagui et al., 2012). The samples were also compared on the basis of gender, analysis of this comparison showed genotype II and ACE gene polymorphism study allele I to be significantly high in male psoriasis patients compared to healthy male controls. When female patients were compared with female controls no association was found. This inconsistency of the results in case of gender can be attributed to the fact that number of female patients was relatively smaller than the male patients.
In the present study it was concluded that II gene polymorphism is a risk factor for psoriasis in Pakistani population. I-allele of the ACE gene has been shown to be associated with lower ACE activity and kinin degradation (Murphey et al., 2000). For this reason, we speculate that changes in ACE activity due to I/D polymorphism, leading to reduced ACE levels in plasma may increase bradykinin levels to trigger an alternative pathway that would cause inflammation in Psoriasis patients There are reports concerning the induction and/or exacerbation of psoriasis by ACE inhibitors which have been attributed to the ACE inhibitor-induced augmentation of kinin levels in skin (Coulter et al., 1993, Wolf et al., 1990). It has previously been observed that the average ACE activity level is comparatively very less in individuals with homozygous genotype II
(Rigat et al., 1990; Mizuiri et al., 2001). It may be thought that the Psoriasis patients with genotype II might have increased bradykinin which as a result might have triggered an inflammatory response leading to development of Psoriasis (Giardina et al., 2007; Lu et al., 2013). As ACE is involved in the survival of melanocytes along with other cells so the possible role of bradykinin can be suggested for hypomelanotic condition as a result of destruction of the melanocytes by inducing autoimmunity in Psoriasis
ACE plays a crucial role in blood pressure regulation and electrolyte balance by hydrolyzing angiotensin I into angiotensin II. Among other effects Ang II increases both the generation of reactive oxygen species (ROS) and the synthesis of cytokines such as ACE gene polymorphism study interleukin-6 (IL-6) and interleukin- 8 (IL-8), thus exerting proinflammatory effects
(Kranzhofer et al., 1999, Takahashi et al., 2000). ACE inactivates bradykinin which promotes vasodilation by enhanced formation of nitric oxide (NO), increases vascular permeability and stimulates the synthesis of proinflammatory cytokines such as IL-6 and
IL-8. All of the mentioned effects play a major role in the development of psoriasis
(Hayashi et al., 2000, Tschöpe et al., 2002, Nickoloff et al., 2004). In addition, ACE degrades substance P (SP), a member of the tachykinin family of neuropeptides. SP increases both vasodilation and vascular permeability, upregulates the expression of intercellular adhesion molecule-1 (ICAM-1) on human dermal microvascular endothelial cells, stimulates the proliferation of human T lymphocytes and enhances the expression of proinflammatory cytokines. All these functions have been shown to contribute to the development of psoriatic lesions (Quinlan et al., 1998, Kanda et al., 2002, Scholzen et al., 2004).
Moreover, both Ang II and bradykinin have already been shown to increase the expression of endothelin-1 (ET-1). ET-1 is a 21-amino acid peptide which is synthesized by different cell types including monocytes and endothelial cells. Besides its effects on vasoregulation, ET-1 acts as a mitogen for keratinocytes and mediates proinflammatory pathways by both the synthesis of cytokines such as IL-6 and monocyte chemoattractant protein -1 (MCP-1) and the activation of nuclear factor kappa beta (NFkB). Increased plasma ET-1 concentrations have already been found among psoriatic patients. In addition, overexpression of ET-1, both at the protein and mRNA levels, has been demonstrated in psoriatic lesions compared to the normal skin (Yildiz et al., 1997,
Browatzki et al., 2000, Wilson et al., 2001) Thus, it appears that ACE on the one hand ACE gene polymorphism study promotes inflammation but on the other hand, inhibits it by degradation of bradykinin and substance P.
Association of ACE I/D polymorphism in psoriasis patients have not been studied before in Pakistani population and the present study is the first such attempt to investigate this association. In the present study it was concluded that II gene polymorphism is a risk factor for psoriasis in Pakistani population. Difference in results with some previous studies may be due to racial/geographical difference, number of male and female patients under study, genetic heterogeneity and multifactorial etiology of psoriasis. Exploring the candidate and GWAS SNPs for association
5. Exploring the candidate and GWAS SNPs for association
5.1. Introduction
Psoriasis is a complex mutifactorial autoimmune disease caused due the combined effect of various genes and environmental triggers. It has been suggested that an abnormally regulated cutaneous immune response marked by helper T cell 1 (TH1) and 17 (TH17) activation and tumor necrosis factor (TNF)-α dependence are involved in the pathogenesis of psoriasis (Nestle et al., 2009; Elder et al., 2010). Genetic basis of the disease is established by a large number of families and population based studies, and has convincingly demonstrated a complex mode of inheritance for psoriasis (Capon et al.,
2012). Currently there are 41 significant (p < 5x 10-8) genome-wide susceptibility loci established for psoriasis including the HLA region on chromosome 6, therefore major genetic determinant remains within the MHC region. Association of psoriasis with HLA-
C gene has been reported both in Caucasian and Chinese Populations (Capon et al., 2008;
Liu et al., 2008; Tsoi et al., 2012; Ellinghaus et al., 2010; Nair et al., 2009; Zhang et al.,
2009) and also reported in Pakistani Population (Shaiq et al., 2013).
A vast majority of the identified susceptibility loci harbor genes within the active immune and inflammatory pathways, confirming the interaction between genetic susceptibility and immune responses in psoriasis. Several of these loci overlap with other autoimmune diseases (for example, celiac disease, Crohn’s disease and ankylosing spondylitis), particularly the genes that are involved in TH17 differentiation and IL17 responsiveness for example, IL23R, IL12B, IL23A and TRAF3IP2 (Cotsapas et al., 2011).
Various ethnic groups and geographical locations have shown variation in genetic susceptibility for psoriasis. One association study published previously identified 30 Exploring the candidate and GWAS SNPs for association markers in 24 known psoriasis susceptibility loci in a Pakistani population (Shaiq et al.,
2013). Several other smaller studies from India have reported association of psoriasis with MHC genes (Pitchappan et al., 1989; Rani et al., 1998; Gandhi et al., 2011;
Umapathy et al., 2011) whereas little is known about the genetic basis of psoriasis in
South Asian populations. In this study, we comprehensively tested a population from
Pakistan in order to determine association with psoriasis susceptibility loci known from
GWAS (Liu et al., 2008; Capon et al., 2008; Nair et al., 2009; Zhang et al., 2009; Strange et al., 2010; Ellinghaus et al., 2010; Stuart et al., 2010; Yang et al., 2013) and autoimmunity chip (Tsoi et al., 2012) as well as some candidate gene studies (Hüffmeier et al., 2005; Chen et al., 2009; Lu et al., 2013a).
Large-scale genome wide association studies have identified different loci that are associated with psoriasis (de Cid et al., 2009; Nair et al., 2009; Zhang et al., 2009;
Ellinghaus et al., 2010; Ellinghaus et al., 2012; Strange et al., 2010; Stuart et al., 2010;
Sun et al., 2010; Tsoi et al., 2012). All of these genome wide studies involved thousands of cases and controls. One of the recent genome wide study including 10,588 cases and
22,806 controls has identified 15 new psoriasis susceptibility loci (Tsoi et al., 2012).
Significantly associated markers were selected from all these studies to investigate their association with Pakistani psoriasis samples.
5.2. Selected genes for the Study
SLC45A1, TNFRSF9
SLC45A1 (solute carrier family 45, member 1) encodes a solute carrier protein that mediates the uptake of glucose (Amler et al., 2000). The TNFRSF9 (Tumor Necrosis
Factor Receptor Superfamily, Member 9) gene encodes a co-stimulatory molecule that Exploring the candidate and GWAS SNPs for association has a role in generating memory CD8+ T-cells. It can also induce proliferation in peripheral monocytes, enhance T cell apoptosis induced by TCR/CD3 triggered activation, and regulate CD28 co-stimulation to promote Th1 cell responses (Schwarz et al., 1993). Both SLC45A1 and TNFRSF9 are novel genes reported to be associated with psoriasis in a recent study (Tsoi et al., 2012). Both genes lie within 500kb region of SNP rs11121129.
IL28RA
IL28RA (Interleukin 28 receptor, alpha subunit) is a subunit for the interleukin-28 receptor. The protein encoded by IL28RA belongs to the class II cytokine receptor family.
This protein forms a receptor complex with interleukin 10 receptor beta (IL10RB) and the receptor complex has been shown to interact with three closely related cytokines, including IL28A, IL28B, and IL29. The expression of all three cytokines can be induced by viral infections (Kotenko et al., 2003). It is involved in negative regulation of cell proliferation, mucosal immune response, cytokine and chemokine mediated signaling pathway, regulation of defense response by the host against virus (Dumoutier et al.,
2004). IL28RA was first identified as a psoriasis susceptibility locus in genome wide association studies (Strange et al., 2010). Later on IL28RA association was also reported in Chinese population (Yang et al., 2013).
RUNX3
RUNX3 encodes a member of the Runt domain–containing family of transcription factors and has an essential role in T-cell biology particularly in the generation of CD8+ T cells in thymus (Woolf et al., 2003). RUNX3 is located on chromosome 1(1p36.11). The runt- domain family of transcription factors is involved in several diseases and acts on target Exploring the candidate and GWAS SNPs for association genes in a variety of tissues (Otto et al., 2003). Three members, RUNX1, RUNX2 and
RUNX3, can be expressed in the same cell but their binding to the consensus sequence is dependent on their relative levels and their affinity for the adaptor CBFβ (core binding factor β), with which all of the three can form heterodimers (Backstorm et al., 2001).
RUNX3 also has a role in promoting TH1 differentiation through binding to T-bet
(Djuretic et al., 2007). Association of RUNX3 with psoriasis has been published recently
(Tsoi et al., 2012).
IL23 and IL12
IL23 and IL12 are pro-inflammatory cytokines considered to play a key role in driving autoimmunity (Abraham et al., 2009).Three genes involved in IL23 signaling (IL23A,
IL23R, IL12B), have been reported to be associated with psoriasis (Nair et al., 2009) including IL12B (encoding the p40 subunit of IL23 and IL12), IL23A (encoding the p19 subunit of IL23), and IL23R (encoding a subunit of the IL23 receptor). The IL12 and IL23 receptors share the common IL12rRβ1 subunit, which binds to IL12Rβ2 to form the IL12 receptor and to the product of the IL23R gene to form the IL23 receptor (Nair et al.,
2009). IL12, IL23A and IL23R were identified as psoriasis-susceptibility genetic factors in candidate gene and genome-wide association studies of Europeans (Cargill et al.,
2007; Nair et al., 2009) and in Chinese (Zhang et al., 2009; Liu et al., 2008). IL12B,
IL23R are involved in IL23/Th17 signaling and play a critical role in the principal signaling mechanism for a wide array of cytokines and growth factors (Bettelli et al.,
2007). These genes have been reported to contribute to psoriasis susceptibility independent of each other, and subsequent studies have confirmed association with both Exploring the candidate and GWAS SNPs for association genes, which have an additive but not an interactive effect on each other (Nair et al.,
2009).
LCE3B/LCE
As psoriasis displays abnormal epidermal differentiation, the genes in the epidermal differentiation complex (EDC) are biologically plausible candidates for psoriasis susceptibility. LCE (late cornified envelope) gene family is located in the epidermal differentiation complex. The LCE cluster encoding stratum corneum proteins has a wide range of expression in various epithelia that respond to different environmental conditions (Jackson et al., 2005). Deletion of LCE was first identified as being significantly associated with psoriasis in individuals of western European descent (de Cid et al., 2009). This finding was replicated in a study of psoriasis patients in Germany
(Huffmeier et al., 2010) although another study by one of the same authors found that the deletion did not contribute to psoriatic arthritis (Huffmeier et al., 2010). A study of
Spanish subjects reported no association of allele and genotype frequencies with patients versus controls, but did confirm that homozygous LCE3C_3B-del (deletion of LCE3C and LCE3B) is a risk factor for developing psoriasis without psoriatic arthritis (Coto et al., 2010). Recently, a meta-analysis confirmed an association between LCE3C_LCE3B deletion and psoriasis in several ethnic groups and detected its interaction with HLA-Cw6
(Riveira-Munoz et al., 2011). In addition, single-nucleotide polymorphisms (SNPs) in the vicinity of the deletion were shown to be associated with psoriasis in an independent
Chinese population study (Zhang et al., 2009).The importance of this gene in pathogenesis of psoriasis can be judged by the fact that after HLA, the second most strongly associated locus in Caucasian population is LCE3B/LCE (Tsoi et al., 2012). Exploring the candidate and GWAS SNPs for association
Several other genes within the EDC were also shown to be associated with psoriasis.
These include IVL (Involucrin) and genes in a region within a 120 kb region of EDC 200 kb distal from IVL. This region includes SPRR2F, SPRR2G, SPRR2C, PRR9and LELP1 genes (Chen et al., 2009).
REL
REL (v-relreticuloendotheliosis viral oncogene homolog) encodes c-Rel, a transcription factor that is a member of the Rel/NFKB family. It also includes RELA, RELB, NFKB1 and NFKB2 and is highly important in the innate immune system (Ellinghaus et al.,
2012). These proteins are related through a highly conserved N-terminal region termed the 'Rel domain,' which is responsible for DNA binding, dimerization, nuclear localization and binding to the NFKB inhibitor (Belguise and Sonenshein, 2007). NF-κB plays a central role in the mediation of inflammation and the immune response
(Vallabhapurapu et al., 2009). Association of psoriasis has already been reported in the
Caucasian population for the REL locus (Strange et al., 2010; Tsoi et al., 2012).
B3GNT2
B3GNT2 is a member of the β-1,3-N-acetylglucosaminyl transferase family. It catalyzes the initiation and elongation of poly-N-acetyl lactosamine chains (Shiraishi et al., 2001).
Its deficiency has been shown to result in hyper activation of lymphocytes (Togayachi et al., 2010). It has been identified as a new susceptibility locus for psoriasis (Tsoi et al.,
2012).
IFIH1, KCNH7
The human IFIH1-GCA-KCNH7 locus is located on chromosome 2q24-3 and encodes for a key protein in the type 1 interferon (IFN) pathway. IFIH1 (Interferon Induced with Exploring the candidate and GWAS SNPs for association
Helicase C Domain 1) is an interferon-induced putative RNA helicase. The known biological function of IFIH1 supports a role for this gene in psoriasis. It affects cell differentiation, growth and cell death (Kang et al., 2002) and has been implicated in the recognition of RNA viruses (Kato et al., 2006). Virus infection may be one of the environment factors that trigger and/or exacerbate psoriasis, and human endogenous retroviruses have been detected in psoriatic skins (Fry and Baker, 2007). In addition,
IFIH1expression is increased in epidermal cells and tissues from psoriatic plaques compared to normal controls (Prens et al., 2008). The IFIH1 gene has also been implicated as a susceptibility gene in other autoimmune diseases, such as type I diabetes
(Smyth et al., 2006) or Graves' disease (Sutherland et al., 2007).
KCNH7 (Potassium voltage-gated channel subfamily H member 7) is a protein encoded by the KCNH7 gene. Voltage-gated potassium (Kv) channels perform diverse functions that include regulating epithelial electrolyte transport, smooth muscle contraction, neurotransmitter release, heart rate, insulin secretion, neuronal excitability, and cell volume (Akhavan et al., 2005). Both genes map within region of SNP rs17716942.
Association of these genes with psoriasis has been reported in the literature (Strange et al., 2010).
SLC12A8
SLC12A8 (Solute carrier family 12, member 8) is a cation/chloride co-transporter that play a role in the control of keratinocyte proliferation. An association was found with a five-marker haplotype of this gene (Hewett et al., 2002). Association with SLC12A8 has also been confirmed in a German study (Huffmeier et al., 2005), however no association was detected in families of North American origin (Bowcock and Baker, 2003). Exploring the candidate and GWAS SNPs for association
ERAP1
ERAP1 (endoplasmic reticulum aminopeptidase 1) has an important role in MHC class I peptide processing in the endoplasmic reticulum and has also been shown to be involved in shedding of pro-inflammatory cytokine receptors and has a potential involvement in the pathogenesis of psoriasis (Haroon and Inman, 2010). At present, the functional consequences of ERAP1 polymorphisms in psoriasis are unknown. ERAP1 has several functions. It may act as a “molecular ruler” clipping peptides for optimal HLA class I binding and presentation (Chang et al., 2005). The peptide-trimming function suggests a biological interaction with HLA and has been believed to be causative for most of the effect in psoriasis. The association of ERAP1 in psoriasis was reported in genome wide association study (Strange et al., 2010) and also in candidate gene studies (Bergboer et al., 2012, Lysell et al., 2013).
IL13/IL4
IL13 and IL4 genes are located within 12.5 kb of each other on human chromosome
5q31.1. Both are products of Th2 cells that play a multiple role in allergic reactions and in the immune response to extracellular pathogens. IL13 and IL4 exhibit a 30% of sequence similarity and have a similar structure. IL13 induces its effects through a multi- subunit receptor that includes the alpha chain of the IL4 receptor (IL4Rα) and at least one of two known IL13-specific binding chains (Wynn et al., 2003). Most of the biological effects of IL13 like those of IL4 are linked to a single transcription factor, signal transducer and activator of transcription 6 (STAT6). Both IL13 and IL4 are expressed at high levels in atopic dermatitis but only at very low levels in psoriasis (Griffiths et al.,
2007). Altered expression of the two IL13 receptor chains, IL4Rα and IL13α1, has been Exploring the candidate and GWAS SNPs for association observed in the skin of psoriasis patients (Cancino Diaz et al., 2002). Thus, IL13 represents a reasonable biological candidate gene for the development of psoriasis and
IL4 treatment has led to significant clinical improvement of psoriasis (Ghoreschi et al.,
2003). Association of IL13/4 with psoriasis has been reported in different studies (Nair et al., 2009; Strange et al.,2010; Sun et al.,2010).
TNIP1
TNIP1 encodes the TNFAIP3-interacting protein 1 (Fukushi et al., 1999). Both TNIP1 and TNFAIP3 (TNF-α induced protein 3) genes have been shown to be associated with psoriasis in GWAS studies (Nair et al., 2009), a finding that was later confirmed strongly in Caucasian (Strange et al., 2010) and suggestively in Chinese (Sun et al., 2010) populations. TNIP1and TNFAIP3 are important genes of the NFκB pathway and their gene products work downstream of TNF-α to negatively regulate NFκB. TNFAIP3 encodes A20, a TNF-α-inducible zinc finger protein that temporally limits immune responses by inhibiting NFκB activation and terminating NFκB mediated responses (Lee et al., 2000). Symptoms of psoriasis induced in a mouse model by administration of IL23 are improved by blocking of TNF-α (Chan et al., 2006), and in a different mouse model a region of mouse chromosome 10 encompassing Tnfaip3 promotes psoriasis in a TNF-α dependent manner (Wang et al., 2008). Both anti-IL12/IL23 p40 and anti-TNF-α monoclonal antibodies provide highly effective therapies for many psoriasis patients
(Krueger et al., 2007).
EXOC2
EXOC2 (Exocyst Complex Component 2) encodes a component of the multiprotein complex that facilitates the docking of exocytic vesicles to the plasma membrane Exploring the candidate and GWAS SNPs for association
(Grindstaff et al., 1998). At least eight components of the exocyst complex including this protein interact with the actin cytoskeletal remodeling and vesicle transport machinery
(Murthy et al., 2003). Association of EXOC2 with psoriasis has been published recently
(Tsoi et al., 2012).
HLA-C
The major genetic determinant of psoriasis is believed to be located within the MHC region. The MHC, and in particular, the HLA-C of HLA class I region, is the only region that has been shown to be consistently associated with psoriasis. HLA associations in psoriasis have been recognized for over 35 years (Russell et al., 1972). In addition to
Cw*0602, B*57 has also been reported worldwide (Elder et al., 1994).
Role of HLA-C as a major disease gene is consistent with current concepts of psoriasis immunopathogenesis. The most noticeable clinical features of psoriasis are epidermal hyperplasia and increased cutaneous blood flow and several lines of evidence show that these changes are generated and maintained by infiltrating immunocytes. HLA-C presents peptide antigens to CD8+T cells that comprise at least 80% of the T cells in lesional psoriatic epidermis (Gudjonsson et al., 2004). HLA-C also regulates the activity of natural killer cells by interacting with killer immunoglobulin-like receptors (KIR)
(Parham, 2005). Interestingly, variation in KIR genes has been associated with psoriasis
(Suzuki et al., 2004) and psoriatic arthritis (Martin et al., 2002).
TRAF3IP2
TRAF3IP2 (TNF receptor-associated factor 3 Interacting Protein 2) encodes TRAF3 interacting protein 2 that is involved in IL17 signaling which then interacts with members of the Rel/NF-κB transcription factor family (Ellinghaus et al., 2010). Exploring the candidate and GWAS SNPs for association
TRAF3IP2 gene product is required for IL17-mediated T-cell immune responses. The
TRAF3IP2 protein activates either NF-κB or Jun kinase by interacting with tumor necrosis factor receptor-associated factor (TRAF) proteins (Qian et al., 2007). Thus it is speculated that a dysregulation of TRAF3IP2 in psoriasis might have a major impact on
IL17 signaling and hence, on the activation of NFκB pathways leading to the up- regulation of pro-inflammatory factors (Ellinghaus et al., 2010). TRAF3IP2 has been reported to be associated in Caucasian Population (Strange et al., 2010; Ellinghaus et al.,
2010; Tsoi et al., 2010). In a recent study in Pakistani psoriasis patients this association has also been replicated (Shaiq et al., 2013).
TAGAP
TAGAP (T-Cell Activation Rho-GTPase Activating Protein) encodes a Rho-GTPase- activating protein that is involved in T-cell activation. TAGAP is a member of the Rho-
GTPase protein family, which release GTP from GTP-bound Rho, thereby acting as a molecular switch. The gene is expressed in activated T cells and appears to be important for modulating cytoskeletal changes (Chang and Hsiao, 2005). It has been found to be co- regulated with IL2 and is expected to play a role in T-cell activation (Chang et al., 2005).
Alterations in this gene may be associated with several diseases, including rheumatoid arthritis, celiac disease, Crohn’s disease, and multiple sclerosis (Raychaudhuri et al.,
2009; Festen et al., 2011; Patsopoulos et al., 2011). Association of this gene with psoriasis has recently been reported in Caucasian population (Tsoi et al., 2012).
ELMO1
ELMO1 (Engulfment and Cell Motility 1) encodes a member of the engulfment and cell motility protein family, which binds to DOCK2 (dedicator of cytokinesis 1) and is Exploring the candidate and GWAS SNPs for association important for Toll-like receptor (TLR7 and TLR9)-mediated interferon (IFN)-α induction by plasmacytoid dendritic cells (Gotoh et al., 2010) and plasmacytoid dendritic cell migration (Ippagunta et al., 2011). DOCK2 also has a role in antigen uptake and presentation and lymphocyte trafficking (Ippagunta et al., 2011). Association of this gene with psoriasis has recently been reported in Caucasian population (Tsoi et al., 2012).
DDX58
DDX58 DEAD (Asp-Glu-Ala-Asp) Box Polypeptide 58 encodes the RIG-I innate antiviral receptor that recognizes cytosolic double-stranded RNA (Loo and Gale, 2011) and regulates the immune response. It is induced by IFN-γ (Cui et al., 2004) and regulates the production of type I and II IFN (Negishi et al., 2008). Association of this gene with psoriasis has recently been reported in Caucasian population (Tsoi et al., 2012).
KLF4
KLF4 encodes a Kruppel-like transcription factor, which is required for the establishment of skin barrier function (Patel et al., 2006) and regulates key signaling pathways related to macrophage activation (Feinberg et al., 2005). The KLF4 protein also binds to the promoter of IL17A and positively regulates its expression. Association of this gene with psoriasis has recently been reported in Caucasian population (Tsoi et al., 2012).
ZMIZ1
ZMIZ1 (Zinc Finger, MIZ-Type Containing 1) encodes PIAS (protein inhibitor of activated STAT) like protein that interacts with Smad4 to regulate Smad3 transcription and modulate transforming growth factor-β signaling (Li et al., 2006). Association of this gene with psoriasis has recently been reported in Caucasian population (Ellinghaus et al.,
2012; Tsoi et al., 2012). Exploring the candidate and GWAS SNPs for association
PRDX5
PRDX5 encodes Peroxiredoxin-5, which belongs to the peroxiredoxin family of antioxidant enzymes that reduce hydrogen peroxide and alkyl hydroperoxides and might play a protective role during inflammatory processes (Ellinghaus et al., 2012). It has been reported as a psoriasis susceptible gene in a Caucasian population (Ellinghaus et al.,
2012; Tsoi et al., 2012).
ZC3H12C
ZC3H12C (zinc finger CCCH-type containing 12C) is a Zinc-finger protein regulating macrophage activation (Liang et al., 2008). It is a newly identified disease susceptibility region for psoriasis in a Caucasian population (Tsoi et al., 2012).
ETS1
ETS1 (V-Ets Avian Erythroblastosis Virus E26 Oncogene Homolog 1) encodes a transcription factor activated downstream of the Ras–mitogen-activated protein kinase
(MAPK) pathway and is involved in the homeostasis of squamous epithelia (Nagarajan et al., 2010). It is involved in CD8 T-cell differentiation and acts, in part, by promoting
RUNX3 expression (Zamisch et al., 2009). It is also a negative regulator of TH17 differentiation (Moisan et al., 2007). Association of this gene with psoriasis has recently been reported in Caucasian population (Tsoi et al., 2012).
RPS26
RPS26 (Ribosomal protein S26) encodes a ribosomal protein subunit whose expression is under cis-acting genetic control in the liver (Schadt et al., 2008). RPS26 was shown to be over-expressed in lesional psoriatic skin (Stuart et al., 2010). It lies in a region that has Exploring the candidate and GWAS SNPs for association been associated with susceptibility to type I diabetes (Todd et al., 2007). Association of this gene has been reported with psoriasis (Stuart et al., 2010).
ATXN2
ATXN2 (Ataxin 2) is involved in epidermal growth factor receptor trafficking (EGFR) and acts as negative regulator of endocytic EGFR internalization at the plasma membrane. In an association study of cardiovascular and metabolic disease genes with psoriasis, ATXN2 gene has been shown to be associated with psoriasis (Lu et al., 2013).
STAT2
STAT2 (Signal Transducer and Activator of Transcription 2) encodes a protein that is a member of the STAT protein family. It acts as signal transducer and activator of transcription that mediates signaling by type I IFNs (IFN-alpha and IFN-beta). It takes part in the activation of transcription of interferon stimulated genes which drive the cell in an antiviral state (Li et al., 1997). Association of this gene with psoriasis has been reported in Caucasian population (Tsoi et al., 2012).
NFKBIA, PSMA6
Nuclear Factor of Kappa Light Polypeptide Gene Enhancer in B-Cells Inhibitor, Alpha () and Proteasome (Prosome, Macropain) subunit, Alpha Type, 6 (PSMA6) genes map in the vicinity of SNP rs12586317. PSMA6 is over-expressed in psoriatic lesions (Stuart et al., 2010). NFKBIA and PSMA6 are both candidate genes for psoriasis susceptibility, as
NFKBIA encodes IκB-α, an inhibitor of NF-κB signaling, and PSMA6 encodes a proteosomal subunit involved in MHC Class I antigen processing. Both were shown to be associated with psoriasis at a genome-wide significant level (Stuart et al., 2010) which was further replicated in other studies (Strange et al., 2010, Tsoi et al., 2012). Exploring the candidate and GWAS SNPs for association
PRM3, SOCS1
SOCS1 (Suppressor of cytokine signaling 1) is a member of the suppressor of cytokine signaling family of proteins and prevents signaling events downstream of IFN-γ
(Sakamoto et al., 1998). It regulates TH17 differentiation by maintaining STAT3 transcriptional activity (Tanaka et al., 2008) and interacts with TYK2 in cytokine signaling (Piganis et al., 2011). SOCS1 is identified as a novel psoriasis susceptibility locus (Tsoi et al., 2012) and maps in a region of SNP rs367569 in the vicinity of PRM3
(Protamine 3).
FBXL19
FBXL19 (F-Box and Leucine-Rich Repeat Protein 19) is a member of F-box protein family. It has zinc finger, plant homology domain, and leucine-rich repeats in addition to the F-box (Jin et al., 2004). It is structurally related to FBXL11, an F-box family member that inhibit nuclear factor kappa (NF-κB) light chain enhancer of activated B cells activity by lysine demethylation (Lu et al., 2010). It lacks jumonji C domains required for demethylase activity so it activates NF-κB by negatively inhibiting demethylase activity.
FBXL19 has shown to be associated with psoriasis in genome wide association analysis studies in Caucasian population (Stuart et al., 2010). Role of FBXL19 in activation of
NF-κB further highlights the importance of NF-κB signaling pathway in psoriasis given that TNIP1, TNFAIP3 and NFKBIA regulate the same pathway and have been involved in psoriasis susceptibility (Nair et al., 2009).
UBBP4
UBBP4 (Ubiquitin B Pseudogene 4), an important paralog of this gene is UBB. UBB encodes ubiquitin that has a major role in targeting cellular proteins for degradation. It is Exploring the candidate and GWAS SNPs for association also involved in gene expression regulation, in chromatin structure maintenance and the stress response (Komander D, 2009). It has been identified as psoriasis susceptibility gene in a genome wide association analysis studies in Caucasians (Stuart et al., 2010).
NOS2
The NOS2 gene encodes iNOS (inducible nitric oxide synthase), expressed by a subset of
TNF-α (tumor necrosis factor-α) producing inflammatory dendritic cells (DC) that are significantly expanded in psoriatic lesions (Zaba et al., 2009). Increased expression of
NOS2 mRNA was found in lesional psoriatic skin by microarray analysis (Stuart et al.,
2010). NOS2 produces nitric oxides (NO) that act as a messenger molecule and have diverse functions in the body. NO mediates tumoricidal and bactericidal actions in macrophages and also has nitrosylase activity.
IL23 has been identified as psoriasis susceptibility gene (Nair et al., 2009). It acts on DC to promote the survival and expansion of pathogenic T-cells in psoriasis (Elder et al.,
2010) and inflammatory DC in psoriatic lesions express NOS2 (Stuart et al., 2010). NOS2 was first reported to be associated with psoriasis at genome wide significant level in
Caucasian population (Stuart et al., 2010) that was replicated afterwards in Pakistani population (Shaiq et al., 2013).
PTRF
PTRF (Polymerase I and Transcript Release Factor) encodes a protein that enables the dissociation of the ternary transcription complex. This protein regulates rRNA transcription by promoting the dissociation of transcription complexes and the reinitiate ion of polymerase I on nascent rRNA transcripts (Jansa et al., 1998). This protein also localizes to caveolae at the plasma membrane and is thought to play a critical role in the Exploring the candidate and GWAS SNPs for association formation of caveolae and the stabilization of caveolins (Aboulaich et al., 2004). This protein is also thought to modify lipid metabolism and insulin-regulated gene expression
(Aboulaich et al., 2006). Association with PTRF and psoriasis has been recently shown in a region that is in the vicinity of SNP rs963986 (Tsoi et al., 2012).
CARD14
CARD14 (Caspase Recruitment Domain Family, Member 14) encodes a member of the family of caspase recruitment domain–containing scaffold proteins, known as CARD- and membrane-associated guanylate kinase–like domain–containing protein (CARMA).
CARD14 (also known as CARMA2) is primarily expressed in epithelial tissues and mediates recruitment and activation of the NF-κB pathway (Blonska and Lin, 2011).
Association of CARD SNP rs11652075 with psoriasis has been reported (Tsoi et al.,
2012) and a further fifteen additional rare missense variants in CARD14 have also been reported in literature (Jordan et al., 2012).
POL1, STARD6
POL1 (Polymerase DNA Directed Iota) encodes an error-prone DNA polymerase which contributes to the hypermutation of immunoglobulin genes (Faili et al., 2002). STARD6
(START (StAR-Related Lipid Transfer) Domain Containing protein 6), is involved in the intracellular transport of sterols or other lipids (Rodriguez et al., 2005). Association has been reported for this region containing both these genes in the vicinity of SNP rs545979
(Tsoi et al., 2012).
TYK2
TYK2 (Tyrosine Kinase 2) gene encodes a member of the tyrosine kinase specifically, the
Janus kinases (JAKs) protein families. Genes that participate in NF-κB and IL17- Exploring the candidate and GWAS SNPs for association mediated signaling are found to be associated with psoriasis including TRAF3IP2,
NFKBIA and REL. TYK2 is also involved in NF-κB and IL17-mediated signaling and is shown to be associated with psoriasis (Nair et al., 2009) that was afterwards confirmed by another study (Tsoi et al., 2012). TYK2 encodes a kinase promoting IL17 transcription via STAT3 phosphorylation (Oyamada et al., 2009). TYK2 has shown to confer risk in multiple autoimmune diseases, namely Type I diabetes and Systemic lupus erythematosus (Wallace et al., 2010).
TYK2 also regulates type I and type III interferon (IFN) signaling (Zhou et al., 2007), proposing that innate IFN-activating pathways may contribute to psoriasis pathogenesis.
This is consistent with the finding that disease-associated SNPs lie in the vicinity of
IL28RA, which encodes a type III IFN receptor subunit (Kotenko et al., 2003).
ILF3, CARM1
ILF3 (Interleukin Enhancer Binding Factor 3) encodes a double-stranded RNA-binding protein that complexes with double-stranded RNAs, mRNAs and small noncoding RNAs to regulate gene expression and stabilize mRNA. It is a subunit of the nuclear factor of activated T cells (NFAT), a transcription factor required for IL2 expression in T cells.
CARM1 (Co-activator Associated Arginine Methyl transferase 1) encodes a transcriptional co-activator of NF-κB and functions as a promoter-specific regulator of
NF-κB recruitment to chromatin. Association has been reported for this region containing both these genes in the vicinity of SNP rs892085 (Tsoi et al., 2012).
SDC4
SDC4 (Syndecan 4) which encodes syndecan-4, a cell-surface heparin sulfate proteoglycan that inhibits T-cell activation (Chung et al., 2009). It has been reported that Exploring the candidate and GWAS SNPs for association expression of SDC4 mRNA was markedly reduced in lesional psoriatic skin compared to both normal and uninvolved skin (Stuart et al., 2010). Association has been reported with
SNP rs1008953 that resides 3.7 kb upstream of SDC4 (Stuart et al., 2010).
RNF114
Ring Finger Protein 114 (RNF114 )was identified as novel psoriasis susceptibility locus in a GWAS (Capon et al., 2008) and the result was subsequently replicated in further studies (Nair et al., 2009; Strange et al., 2010; Staurt et al., 2010; Tsoi et al., 2012).
Although the function of RNF114 is unknown, bioinformatic analyses indicate that the gene encodes a protein with an N-terminal RING domain, followed by three zinc fingers and an ubiquitin interaction motif (UIM; Giannini et al., 2008). It was reported earlier that RNF114 is a positive regulator of innate immune pathway and it contribute to psoriasis susceptibility by up-regulating the production of type I IFN through the RIG-
I/MDA5 pathway which is a key early mediator of epithelial inflammation (Nestle et al.,
2005). There are reports of psoriasis exacerbation following IFNα treatment of hepatitis
(Downs et al., 2000; Ketikoglou et al., 2005).
UBE2L3
UBE2L3 (Ubiquitin-Conjugating Enzyme E2L 3) encodes a protein involved in ubiquitination, a process in which abnormal or short-lived proteins are modified with ubiquitin to mark them for degradation. The protein encoded by UBE2L3 is involved in the ubiquitination of p53, c-Fos, and the NF-kB precursor p105 (Moynihan et al., 1998).
Additionally, the protein encoded by UBE2L3 has been shown in vitro to be involved in natural killer cell cytotoxic function which is an important part of the innate immune Exploring the candidate and GWAS SNPs for association response (Fortier and Kornbluth, 2006). Association with psoriasis has also been reported with this gene (Tsoi et al., 2012).
5.2.2. Aims and Objectives of the Study:
SNPs were selected from both the genome wide association and candidate gene studies with majority of SNPs from the genome wide association studies already reported in different populations. A few of SNPs were also selected from reported candidate gene studies. The aim of our study was to genotype these SNPs to get an overall picture of association in Pakistani psoriasis samples. There was already a reported association study from Pakistani psoriasis patients, it was interesting to see the association results in these psoriasis samples. This was a comprehensive study in Pakistani psoriasis samples as 57
SNPs were selected from 42 loci (Table 5.1).
The results obtained would help in obtaining the genetic profile of psoriasis in Pakistani population. It will in turn aid in understanding the disease mechanism and pathogenesis and once an underlying pathway of the disease is unveiled it will also help in therapeutics and ultimate benefit to the psoriasis sufferers.
Exploring the candidate and GWAS SNPs for association
Table 5.1: Single Nucleotide Polymorphisms (SNPs) Genotyped in Psoriasis Patients.
SNPs Nearby genes FirstAuthor Chr Position (Mb) RA rs11121129 SLC45A1,TNFRSF9 Tsoi et al., 2012 1 8.27 A rs7552167 IL28RA Tsoi et al., 2012 1 24.52 G rs7536201 RUNX3 Tsoi et al., 2012 1 25.29 C rs2201841 IL23R Nair et al., 2009 1 67.69 G rs9988642 IL23R Tsoi et al., 2012 1 67.73 T rs6677595 LCE3B/LCE3C Tsoi et al., 2012 1 152.59 T rs10788861 Upstream of PRR9 Chen et al., 2009 1 153.19 C rs4845342 Upstream of PRR9 Chen et al., 2009 1 153.21 C rs10888541 Upstream of PRR9 Chen et al., 2009 1 153.21 A rs62149416 REL Tsoi et al., 2012 2 61.08 T rs702873 REL Strange et al., 2010 2 61.08 G rs10865331 B3GNT2 Tsoi et al., 2012 2 62.55 A rs17716942 (IFIH1)KCNH7 Tsoi et al., 2012 2 163.26 T rs2228674 HEG1/SLC12A8 Hüffmeier et al., 2005 3 124.77 NA rs27524 ERAP1 Strange et al., 2010 5 96.1 A rs1295685 IL13/IL4 Tsoi et al., 2012 5 132 G rs2233278 TNIP1 Tsoi et al., 2012 5 150.47 C rs17728338 TNIP1 Nair et al., 2009 5 150.48 A rs3213094 IL12B Zhang et al., 2009 5 158.75 A rs2546890 IL12B Ellinghaus et al., 2010 5 158.76 A rs12188300 IL12B Tsoi et al., 2012 5 158.83 T rs9504361 EXOC2 Tsoi et al., 2012 6 0.58 A rs1265181 HLA-C Zhang et al., 2009 6 31.16 G rs12191877 HLA-C Nair et al., 2009 6 31.25 T rs4406273 HLA-C Tsoi et al., 2012 6 31.27 A rs3134792 HLA-C Capon et al., 2008 6 31.31 A rs2395029 HLA-C Liu et al., 2008 6 31.43 C rs240993 TRAF3IP2 Strange et al., 2010 6 111.67 A rs458017 TRAF3IP2 Strange et al., 2010 6 111.7 G rs33980500 TRAF3IP2 Tsoi et al., 2012 6 111.91 T rs610604 TNFAIP3 Nair et al., 2009 6 138.2 G rs2451258 TAGAP Tsoi et al., 2012 6 159.51 C rs2700987 ELMO1 Tsoi et al., 2012 7 37.39 A rs11795343 DDX58 Tsoi et al., 2012 9 32.52 T rs10979182 KLF4 Tsoi et al., 2012 9 110.82 A rs1250546 ZMIZ1 Ellinghaus et al., 2010 10 81.03 G Table 5.1 Continued …
Exploring the candidate and GWAS SNPs for association
SNPs Nearby genes FirstAuthor Chr Position (Mb) RA rs645078 PRDX5 Tsoi et al., 2012 11 64.14 A rs4561177 ZC3H12C Tsoi et al., 2012 11 109.96 A rs12580100 RPS26 Stuart et al., 2010 12 56.44 A rs2066819 STAT2 , IL23A Tsoi et al., 2012 12 56.75 C rs653178 ATXN2 Lu et al., 2008 12 112.01 T rs12586317 NFKBIA,PSMA6 Stuart et al., 2010 14 35.68 T rs8016947 NFKBIA Tsoi et al., 2012 14 35.83 G rs367569 PRM3,SOCS1 Tsoi et al., 2012 16 11.37 C rs12445568 FBXL19 Tsoi et al., 2012 16 31 C rs1975974 UBBP4 Stuart et al., 2010 17 21.71 G rs4795067 NOS2 Stuart et al., 2010 17 26.11 G rs963986 PTRF Tsoi et al., 2012 17 40.56 C rs11652075 CARD14 Tsoi et al., 2012 17 78.18 C rs545979 POL1,STARD6 Tsoi et al., 2012 18 51.82 T rs34536443 TYK2 Tsoi et al., 2012 19 10.46 G rs12720356 TYK2 Strange et al., 2010 19 10.47 A rs892085 ILF3,CARM1 Tsoi et al., 2012 19 10.82 A rs1008953 SDC4 Stuart et al., 2010 20 43.98 C rs1056198 RNF114 Tsoi et al., 2012 20 48.56 C rs4821124 UBE2L3 Tsoi et al., 2012 22 21.98 C
Exploring the candidate and GWAS SNPs for association
5.3. Results
Results of the genetic association analysis for psoriasis susceptibility for the 42 loci tested are summarized in Table 5.1 and 5.2. For each locus, the best known associated markers were tested. Fifty four SNPs (thirty nine) were selected from GWAS and three
SNPs (three loci) were selected from candidate gene studies. Genotypic frequencies for patients and controls were in HW Equilibrium except for rs2233278 & rs17728388 which showed linkage disequilibrium (r2=0.8). One SNP was excluded due to a call rate below
90% (rs2066819). The overall analysis was performed on all samples as well as on samples adjusted for age of onset.
The strongest association was shown to be with HLA-C locus at the MHC region for early onset psoriasis group. From the 5 SNPs genotyped for the MHC region, rs1265181 was overall most significant (OR = 3.38, p = 2.97 × 10-18) as well as specifically for type I group. Apart from MHC, nominally significant overall allelic associations were observed at ten other loci including LCE3B, PRR9, REL, IL13/IL4, TNIP1, IL12B, TRAF3IP2,
ZC3H12C, NOS2 and RNF114. The Odds ratio and p values for the significant loci were :
LCE3B (rs6677595, OR = 1.54, p = 3.01× 10-4), PRR9 (rs10788861, OR = 1.30, p =
0.02), REL (rs62149416, OR = 1.42, p = 0.03), IL13/IL4 (rs1295685, OR = 1.5, p = 4.41
× 10-4)TNIP1 (rs2233278, OR = 1.56, p = 7.44 × 10-3) IL12B (rs3213094, OR = 0.75, p =
0.009)TRAF3IP2 (rs33980500, OR = 2.05, p = 7.03 × 10-4) ZC3H12C (rs4561177, OR =
1.35, p = 0.007)NOS2 (rs4795067, OR = 1.31, p = 0.01) RNF114 (rs1056198, OR = 1.37, p = 0.003) represented in Tables 5.1 and 5.2.
When comparing the allelic association between type I and type II psoriasis, four loci were significantly different between the two groups. These included MHC, ELMO1, Exploring the candidate and GWAS SNPs for association
TNIP1 and RUNX3.In the MHC region, we genotyped 5 SNPs rs1265181, rs12191877, rs4406273, rs3134792 and rs2395029 and all of these SNPs showed strong association for type I samples. In type II samples association was observed with 4 SNPs but it was not as strong as was observed for type I samples e.g., with SNP rs1265181 in type I samples the odds ratios and p values were 4.06, 9.32× 0-23 respectively compared to the values of 1.61 and 0.04 respectively in type II samples (Table 5.1).
Other than MHC the most strongly associated gene in our study for type II psoriasis was the TNIP1, which has previously been reported as a psoriasis susceptibility gene in the
Caucasian population (Nair et al., 2009; Tsoi et al., 2012). We genotyped two SNPs in
TNIP1 (rs17728338 and rs2233278) and found association with both SNPs in all samples
(OR = 1.56 for both and p = 8.21 × 10-3, 7.44 × 10-3 for rs17728338 and rs2233278 respectively). However, when analyzed according to age of onset, the effect observed with type II samples was much stronger than in type I samples: (OR = 2.34, 2.19 and p =
1.61 × 10-4, 5.37 × 10-4) with both the SNPs respectively in type II samples as compared to type I samples (OR = 1.36, 1.4 and p = 0.09, 0.06, Table 5.1).
Another locus that showed different association results between the two types was
ELMO1. Association was observed in type I samples only with the SNP rs2700987 (OR
= 0.79, and p = 0.04) as compared to type II samples (OR = 1.23, and p = 0.26, Table
5.1). The RUNX3 gene was not significant in overall samples, neither was it significant in type I and II samples separately. However the association between the two groups was significantly different (p = 0.017). In the TYK2 marginal association was observed (p =
0.049) only in type II samples (Table 5.1). Exploring the candidate and GWAS SNPs for association
Bonferroni correction was applied for all the SNPs that were analyzed and it was observed that the SNPs that still showed significance were those that are present in
LCE3B, IL13/IL4, TNIP1, MHC and TRAF3IP2. All of the associated SNPs except IL12B
(rs3213094), were associated to the same risk variant as in the previous studies. In addition most SNPs which were not significant still had an OR in the same allelic direction, including some IL12B SNPs (rs2546890 and rs12188300) detected previously in the European population (Ellinghaus et al., 2010). A total of nine SNPs (rs11121129, rs7552167, rs2201841, rs3213094, rs2451258, rs2700987, rs10979182, rs12586317, rs8016947) out of the total 57 SNPs displayed an OR in the opposite allelic direction and only three loci totally lacked any SNP within a 95 % confidence interval of the odds ratio in the same allelic direction as previously reported (Table 5.1). The functions of associated genes are given in Table 5.3. Exploring the candidate and GWAS SNPs for association
Table 5.2: Results from the association analysis and comparisons with previous GWAS significant findings (p < 5 × 10 -8). GWAS results: This study: RA OR RA OR OR First Position Nearby R/NR OR OR 95% P Type P Type I SNP Chr RA freq or freq P All Type P Type I Type Author (Mb) genes allele All CI All II ≠Type II CT beta CT I II SLC45A1, rs11121129 Tsoi 1 8.27 A 0.29 1.13 G/A 0.69 0.87 0.7-1.09a 0.23 0.88 0.3 0.82 0.3 0.8 TNFRSF9 rs7552167 Tsoi 1 24.52 IL28RA G 0.86 1.21 A/G 0.07 0.76 0.52-1.11a 0.15 0.77 0.2 0.69 0.19 0.82 rs7536201 Tsoi 1 25.29 RUNX3 C 0.49 1.13 C/T 0.7 1.08 0.83-1.39 0.56 0.95 0.73 1.51 0.06 0.017 rs2201841 Nair 1 67.69 IL23R G 0.3 1.13 G/A 0.54 1.03 0.85-1.26 0.74 1.01 0.91 1.05 0.77 0.55 rs9988642 Tsoi 1 67.73 IL23R T 0.93 1.52 C/T 0.03 0.81 0.46-1.45a 0.47 0.78 0.42 0.79 0.59 0.7 LCE3B/ rs6677595 Tsoi 1 152.59 T 0.64 1.26 T/C 0.57 1.54 1.22-1.95 3.01E-04 1.67 6.87E-05 1.27 0.2 0.08 LCE3C rs62149416 Tsoi 2 61.08 REL T 0.64 1.17 T/C 0.87 1.42 1.03-1.97 0.03 1.56 0.01 1.19 0.5 0.16 rs702873 Strange 2 61.08 REL G 0.56 1.12 G/A 0.73 1.12 0.89-1.41 0.33 1.16 0.23 1.05 0.78 0.4 rs10865331 Tsoi 2 62.55 B3GNT2 A 0.37 1.12 A/G 0.43 1.02 0.84-1.25 0.82 1.03 0.79 1.03 0.85 0.9 rs17716942 Tsoi 2 163.26 KCNH7 T 0.86 1.27 T/C 0.92 1.28 0.85-1.92 0.23 1.31 0.22 1..29 0.44 0.77 rs27524 Strange 5 96.1 ERAP1 A 0.36 1.13 A/G 0.4 1.09 0.89-1.33 0.41 1.06 0.62 1.25 0.17 0.4 rs1295685 Tsoi 5 132 IL13/IL4 G 0.8 1.18 G/A 0.66 1.5 1.2-1.88 4.41E-04 1.45 2.47E-03 1.55 0.02 0.46 rs2233278 Tsoi 5 150.47 TNIP1 C 0.06 1.59 C/G 0.09 1.56 1.12-2.15 7.44E-03 1.4 0.06 2.19 5.37E-04 0.06 rs17728338 Nair 5 150.48 TNIP1 A 0.05 1.59 A/G 0.09 1.56 1.12-2.17 8.21E-03 1.36 0.09 2.34 1.61E-04 0.019 rs3213094 Zhang 5 158.75 IL12B A 0.45 1.28 G/A 0.67 0.75 0.61-0.93a 0.009C 0.75 0.01C 0.7 0.046C 0.95 rs2546890 Ellinghaus 5 158.76 IL12B A 0.56 1.54 A/G 0.6 1.2 0.98-1.46a 0.08 1.15 0.2 1.42 0.04 0.32 rs12188300 Tsoi 5 158.83 IL12B T 0.1 1.58 T/A 0.03 1.4 0.8-2.45 0.24 1.41 0.25 1.41 0.42 0.95 rs9504361 Tsoi 6 0.58 EXOC2 A 0.55 1.12 A/G 0.57 1.19 0.96-1.47 0.1 1.23 0.07 1.11 0.53 0.42 Table 5.2 continued...
Exploring the candidate and GWAS SNPs for association
GWAS results: This study: RA OR RA OR OR First Position Nearby R/NR OR OR 95% P Type P Type I SNP Chr RA freq or freq P All Type P Type I Type Author (Mb) genes allele All CI All II ≠Type II CT beta CT I II 22.6 rs1265181 Zhang 6 31.16 HLA-C G NR G/C 0.11 3.38 2.55-4.5a 2.97E-18 4.06 9.32E-23 1.61 0.04 2.88E-06 2 rs12191877 Nair 6 31.25 HLA-C T 0.15 2.64 T/C 0.17 3 2.04-3.31 2.58E-15 3.06 4.38E-19 1.5 0.04 2.14E-05 rs4406273 Tsoi 6 31.27 HLA-C A 0.09 4.32 A/G 0.13 3.42 2.5-4.69 1.84E-15 4.1 6.84E-19 1.92 0.006 5.70E-05 rs3134792 Capon 6 31.31 HLA-C A NR NR A/C 0.86 1.43 1.05-1.94 0.02 1.53 0.013 1.08 0.74 0.29 rs2395029 Liu 6 31.43 HLA-C C 0.03 4.1 C/A 0.05 3.05 1.92-4.83 7.82E-07 3.38 1.10E-07 2.05 0.03 0.08 rs240993 Strange 6 111.67 TRAF3IP2 A 0.25 1.25 A/G 0.35 1.09 0.89-1.34 0.39 1.12 0.32 0.97 0.85 0.59 TRAF3IP rs458017 Strange 6 111.7 G 0.06 1.37 G/A 0.05 1.72 1.13-2.63 0.01 1.67 0.02 1.74 0.08 0.65 2 TRAF3IP rs33980500 Tsoi 6 111.91 T 0.07 1.52 T/C 0.05 2.05 1.34-3.12 7.03E-04 2.06 0.001 1.79 0.06 0.94 2 rs610604 Nair 6 138.2 TNFAIP3 G 0.32 1.19 G/T 0.3 1.16 0.94-1.45 0.17 1.13 0.29 1.3 0.14 0.51 rs2451258 Tsoi 6 159.51 TAGAP C 0.35 1.12 T/C 0.72 0.91 0.72-1.15 0.43 0.91 0.47 0.95 0.79 0.98 0.68-1.06 rs2700987 Tsoi 7 37.39 ELMO1 A 0.56 1.11 C/A 0.31 0.85 0.15 0.79 0.04C 1.23 0.26 0.038 a rs11795343 Tsoi 9 32.52 DDX58 T 0.6 1.11 T/C 0.74 1.13 0.9-1.43 0.3 1.16 0.24 1.09 0.67 0.55 rs10979182 Tsoi 9 110.82 KLF4 A 0.59 1.12 G/A 0.64 0.97 0.78-1.2 0.8 0.96 0.72 1.01 0.96 0.73 rs1250546 Ellinghaus 10 81.03 ZMIZ1 G NR 1.16 G/A 0.43 1.01 0.82-1.24 0.91 1.02 0.88 1.03 0.87 0.88 rs645078 Tsoi 11 64.14 PRDX5 A 0.61 1.09 A/C 0.64 1.17 0.95-1.45 0.15 1.18 0.16 1.23 0.23 0.89 rs4561177 Tsoi 11 109.96 ZC3H12C A 0.58 1.14 A/G 0.64 1.35 1.08-1.67 0.007 1.28 0.03 1.58 0.01 0.22 rs3802826 Tsoi 11 128.41 ETS1 A 0.48 1.12 A/G 0.42 1.03 0.84-1.26 0.76 1.06 0.58 1.01 0.97 0.42 rs12580100 Stuart 12 56.44 RPS26 A 0.9 1.17 A/G 0.69 1.03 0.83-1.28 0.78 1.01 0.95 1.09 0.62 0.57 Table 5.2 continued...
Exploring the candidate and GWAS SNPs for association
GWAS results: This study: RA OR RA OR OR First Position( Nearby R/NR OR OR 95% P Type I SNP Chr RA freq or freq P All Type P Type I Type P Type II Author Mb) genes allele All CI All ≠Type II CT beta CT I II STAT2, rs2066819 Tsoi 12 56.75 C 0.93 1.39 NA* NA NA NA NA NA NA NA NA NA IL23A rs12586317 Stuart 14 35.68 NFKBIA T 0.75 1.15 C/T 0.18 0.94 0.72-1.22 0.65 0.95 0.73 0.9 0.6 0.82 rs8016947 Tsoi 14 35.83 NFKBIA G 0.56 1.16 T/G 0.79 0.93 0.72-1.19 0.53 0.87 0.31 1.05 0.82 0.22 PRM3,SOC rs367569 Tsoi 16 11.37 C 0.71 1.13 C/T 0.66 1.11 0.9-1.38 0.33 1.14 0.28 1.1 0.6 0.61 S1 rs12445568 Tsoi 16 31 FBXL19 C 0.37 1.16 C/T 0.61 1.1 0.9-1.35 0.34 1.15 0.2 1.01 0.95 0.28
rs1975974 Stuart 17 21.71 UBBP4 G 0.23 1.17 G/A 0.28 1 0.9-1.4 0.3 1.13 0.3 1.08 0.67 0.84
rs4795067 Stuart 17 26.11 NOS2 G 0.35 1.19 G/A 0.39 1 1.06-1.61 0.01 1.27 0.03 1.49 0.02 0.47 rs963986 Tsoi 17 40.56 PTRF C 0.15 1.15 G/C 0.76 0.93 0.74-1.19 0.58 1.01 0.95 0.7 0.09 0.09 rs11652075 Tsoi 17 78.18 CARD14 C 0.5 1.11 C/T 0.66 1.08 0.87-1.34 0.48 1.14 0.27 0.88 0.47 0.19 POL1,STA rs545979 Tsoi 18 51.82 T 0.29 1.12 T/C 0.27 1.07 0.86-1.34 0.55 1.1 0.45 1.07 0.7 0.58 RD6 rs34536443 Tsoi 19 10.46 TYK2 G 0.95 1.88 G/C 0.98 1.58 0.69-3.61 0.27 1.3 0.54 ∞b 0.049 0.22 rs12720356 Strange 19 10.47 TYK2 A 0.9 1.4 A/C 0.99 1.43 0.41-4.98 0.57 1.37 0.64 1.5 0.71 0.84 ILF3,CAR rs892085 Tsoi 19 10.82 A 0.56 1.17 A/G 0.61 1.02 0.82-1.26 0.86 0.98 0.84 1.28 0.16 0.28 M1
rs1008953 Stuart 20 43.98 SDC4 C 0.79 1.14 C/T 0.8 1.13 0.88-1.45 0.34 1.08 0.57 1.3 0.22 0.35
rs1056198 Tsoi 20 48.56 RNF114 C 0.57 1.16 C/T 0.42 1.37 1.12-1.69 0.003 1.36 0.006 1.49 0.02 0.88
rs4821124 Tsoi 22 21.98 UBE2L3 C 0.19 1.13 C/T 0.23 1.13 0.9-1.42 0.29 1.13 0.32 1.12 0.55 0.98 RA freq= Risk allele frequency. R/NR allele = Risk/Non-Risk allele, OR = allelic Odds Ratio. CT = control. NR = Not Reported. NA = excluded due to low call rate. a = Our 95% confidence interval of the OR does not cover GWAS OR (For rs1265181 the reported OR is extremely high.) b = minor allele frequency 0 in affected individuals. c = Significant association in the opposite direction compared with GWAS. Genes with p-values below 0.05 are marked in italic bold. Exploring the candidate and GWAS SNPs for association
Table 5.3 Results from the association analysis and comparisons with previous candidate gene studies. Previous Studies This study: P- P- Position R/NR RA freq P- value value Nearby SNP Chr Author RA P-value OR (Mb) allele (controls) value Type Type genes I II Upstreamof rs10788861 1 153.19 Chen C 0.002 C/A 0.65 1.3 0.02 0.05 0.06 PRR9 1.0 Upstreamof rs4845342 1 153.21 Chen C 0.04 A/C 0.32 0.52 0.32 0.24 8 PRR9 1.1 Upstreamof rs10888541 1 153.21 Chen A 0.03 G/A 0.33 0.15 0.41 0.08 7 PRR9 1.1 HEG1/SLC1 rs2228674 3 124.77 Hüffmeier NA 0.048 G/A 0.16 0.46 0.61 0.42 1 2A8 1.2 rs653178 12 112.01 Lu T 2.08E-04 T/C 0.86 0.18 0.17 0.15 ATXN2 3 RA = Risk allele. RA freq = Risk allele frequency in our stud, R/NR allele = Risk/Non-Risk allele, OR = allelic Odds Ratio. NA = not available Exploring the candidate and GWAS SNPs for association
Table 5.4: The function of genes associated with psoriasis in Pakistani Population. Gene or Biological Description Chr Expression Putative Function References Locus pathway LCE3B Barrier Late cornified envelope Epithelia and de Cid et and function 1q21.3 Barrier function skin 3B and 3C lesional PS skin al.,2009 LCE3C skin
Barrier Skin, highly PRR9 function upstream of PRR9 1q21.3 upregulated in Barrier function skin Chen et al., 2009 skin psoriasis Runt-Related RUNX3 1p36.11 Regulate T-cell function Tsoi et al., 2012 Transcription Factor 31
Blood, intestine, Transcription factor, Innate v-relreticuloendotheliosis Strange et REL 2p13 larynx, lymph node, member of the REL/NF-κB immunity viral oncogene homolog al.,2010 thyroid, trachea family
Modulate humoral immune Adaptive IL-13/4 IL-13/4 5q31.1 Th2 cells response mediated by Th2 Sun et al., 2010 immunity cells Ubiquitous, induced Innate TNAIP3-interacting Regulation of NF-κB Nair et al.,2009; TNIP1 5q32-33 in psoriasis involved immun protein signaling Sun et al., 2010; skin Table 5.4 continued …
Gene or Biological Description Chr Expression Putative Function References Locus pathway Exploring the candidate and GWAS SNPs for association
Th1, Th0, NK, monocyte, DC, and Tsunemi et al., Adaptive 5q31.1- IL-12B IL-12/23, subunit p40 B-cell lines, induced Maturation T cells 2002; replicated immunity q33.1 in psoriasis involved many times skin Trembath et al., Adaptive Presenting antigens to HLA-C MHC gene 6p21.33 All nucleated cells 1997; replicated immunity immune cells many times Generally expressed, Signaling adaptor involved Ellinghaus et Adaptive TRAF3-interacting TRAF3IP2 6q21 induced in psoriasis in regulation of adaptive al.,2010; Strange immunity protein 2 involved skin immunity et al., 2010 macrophage activation, Innate zinc finger CCCH-type anti-inflammatory ZC3H12C 11q22.3 Tsoi et al.,2012, immunity containing 12C function, inhibits vascular inflammation Immune system, catalyzes the production of Innate Stuart et al., NOS2 Nitric oxide synthase 2 17q11.1 cardiovascular nitric oxide for immune immunity 2010 system defense against pathogens Generally expressed, Capon et al., ZNF313/R Adaptive Ubiquitination, regulation Ring-finger protein 114 20q13.14 strongest in skin, T- 2008; Strange et NF114 immunity of immune responses lymphocytes, DCs al., 2010 Exploring the candidate and GWAS SNPs for association
5.4. Discussion
Psoriasis is a complex disorder and multiple genes are involved in its pathogenesis, however the major genetic determinant is located within the MHC region. In compliance with previous studies (Tsoi et al., 2012; Lu et al., 2013), present data showed MHC as the most strongly associated locus for psoriasis, with rs1265181 being the most significant disease marker showing even higher significance with type I patients. The association of psoriasis with the MHC region has previously been reported in Pakistani population (Shaiq et al., 2013).
We also confirmed association at ten other loci in addition to HLA. Nine of these loci were reported to be associated in Europeans, whereas, PRR9 locus was reported in Singaporean
Chinese population (Chen et al., 2009) and the IL12B locus in both Europeans and Chinese populations (Liu et al., 2008; Zhang et al., 2009; Nair et al., 2009; Strange et al., 2010;
Ellinghaus et al., 2010; Hüffmeier et al., 2010; Tsoi et al., 2012).
In compliance with previous studies (Zhang et al., 2009; De Cid et al., 2009), the second most strongly associated locus in our study was LCE3B/LCE3C (p = 3.01 × 10-4, OR = 1.54). It also showed a possible difference between the two types of patients (p=0.08, Table 5.2).
LCE3B/LCE3C belong to the EDC complex, and a previous candidate gene study using high- density SNP genotyping within the 2 Mb EDC region in Singaporean Chinese psoriasis patients provided evidence for type I disease association within IVL vicinity (Chen et al., 2009). The study also found association at the PRR9 locus (Chen et al., 2009). We selected three SNPs
(rs10788861, rs4845342 and rs10888541) from PRR9 region, one out of our three selected SNPs
(rs1078886) that lies upstream PRR9 gene showed marginal association in both types of patients in this study. This finding is quite interesting as it replicates the association reported in the Exploring the candidate and GWAS SNPs for association
Singaporean Chinese population. Psoriasis displays abnormal epidermal differentiation and the genes in the EDC are biologically probable candidates for psoriasis susceptibility as the products encoded by the genes in this region take part in the differentiation of the epidermis. We observed association with SNPs selected from two genes in the EDC complex that shows the importance of this region in psoriasis pathogenesis. When Bonferroni correction was applied, significance was seen only with LCE locus but not with PRR9. Previous Pakistani study failed to show association at this locus (Shaiq et al., 2013).
IL-23 pathway has been shown to be involved in the pathogenesis of psoriasis by association studies. IL12B gene was identified for the first time as psoriasis susceptibility gene in a large scale association study (Cargill et al., 2007). In a subsequent study association was also identified with psoriasis and IL-23 receptor (IL23R) gene (Nair et al., 2009). Association of these loci has been confirmed in candidate and genome-wide association studies of Chinese (Zhang et al., 2009; Liu et al., 2008) and Europeans (Capon et al., 2007; Smith et al., 2008; Nair et al.,
2009; Huffmeier et al., 2009; Bowes et al., 2010) both in psoriasis and psoriatic arthritis. IL12B encodes the p40 subunit common to both IL-12 and IL-23, and was the first locus associated with psoriasis risk independent of MHC involvement (Cargill et al., 2007).
We genotyped three SNPs (rs3213094, rs2546890 and rs12188300) in IL12B, and two SNPs
(rs2201841 and rs9988642) in IL23R. No association was observed with IL23R and marginal association was observed with rs3213094 and rs2546890 for IL12B in both type I and type II psoriasis groups. However, the association with rs3213094 appears to be in the opposite direction compared to the Chinese population from the GWAS (Zhang et al., 2009) where the minor allele was reported to be the risk allele while this study reports major allele to be over Exploring the candidate and GWAS SNPs for association
represented in the patients. In an earlier study reported from the Pakistani population (Shaiq et al., 2013) no significant association was found with either IL23R or IL12B although different markers were used for IL12B and a common SNP for IL23R. IL12B and IL23R are involved in
IL23/Th17 signaling and play a critical role in the principal signaling mechanism for a wide array of cytokines and growth factors (Bettelli et al., 2007). These genes have reported to contribute to psoriasis susceptibility independent of each other, and subsequent studies have confirmed association with both genes which have an additive rather than interactive effect
(Smith et al., 2008; Nair et al., 2008).
We also found significant associations for REL, TNIP1 and TRAF3IP2 with psoriasis in our samples. In the previous study from Pakistani population marginal association with REL and significant association with TRAF3IP2 has been reported and no association was seen with the
TNIP1 (Shaiq et al., 2013). All three genes have been reported to be significantly associated in
Caucasian population (Nair et al., 2009; Strange et al., 2010 and Tsoi et al., 2012). These genes are involved in the signaling factor pathway for the transcription factor NF-κB which is highly important in the innate immune system. We genotyped two SNPs of REL rs62149416 and rs702873) and observed nominal overall significant association only with rs62149416 (p = 0.03,
OR = 1.42) and only in type I sample. In the previous Pakistani study borderline association was seen with rs702873 (p =0.05, OR = 1.26) (Shaiq et al., 2013).The two SNPs rs62149416 and rs702873 were in moderate LD with each other with r2 = 0.756.
TNIP1 (TNFAIP3 interacting protein 1) gene products work downstream of TNF-α to negatively regulate NF-κB. In this study we genotyped two SNPs (rs17728338 and rs2233278) and found association with both the SNPs only in type II samples, whereas in a separate study reported Exploring the candidate and GWAS SNPs for association
from the Pakistani population, no association was reported for the TNIP1 with the marker rs17728338 (Shaiq et al., 2013). TRAF3IP2 encodes TRAF3 interacting protein 2 that is involved in IL-17 signaling which interacts with members of the Rel/NF-κB transcription factor family (Ellinghaus et al., 2010). We genotyped three SNPs (rs33980500, rs458017 and rs240993) in the TRAF31P2 gene and found association with rs33980500 in type I samples. The same association was also seen in previous study from Pakistani population, we also found association with rs458017 not genotyped previously in Pakistani population. Thus, it is speculated that a dysregulation of TRAF3IP2 in psoriasis might have a major impact on IL-17 signaling and, hence on the activation of NFκB pathways, leading to the up regulation of pro- inflammatory factors (Ellinghaus et al., 2010).
Association with IL13 was reported in the previous Pakistani study (Shaiq et al., 2013). Both
SNPs from the IL13 region, rs1295685 genotyped in our samples and rs20541 previously reported are in absolute LD with each other with r2=1. Altered expression of the two IL-13 receptor chains has been observed in the skin of psoriasis patients (Cancino Diaz et al., 2002).
Thus, IL13 represents a reasonable biological candidate gene for the development of psoriasis and IL-4 treatment has led to significant clinical improvement of psoriasis (Ghoreschi et al.,
2003). Association of IL13/4 with psoriasis has been reported in different studies (Chang et al.,2008; Nair et al., 2009; Strange et al., 2010; Sun et al., 2010).
Significant association was also observed with NOS2 gene, reported to be associated with psoriasis at genome wide significant level (Stuart et al., 2010)). The NOS2 gene encodes iNOS
(inducible nitric oxide synthase), which is expressed by a CD11c-positive, CD1c-negative TNFα producing inflammatory dendritic cells in psoriatic lesions (Zaba et al., 2009). We genotyped Exploring the candidate and GWAS SNPs for association
one SNP (rs4795067) in the NOS2 gene and obtained a significant association that is confirmatory to previous study from Pakistani population (Shaiq et al., 2013).
A marginal association with ELMO1 in only type I samples was observed, a recently identified locus in Caucasian population (Tsoi et al., 2012). This locus was significantly different between type I and type II psoriasis. Also, this locus was among the three loci where the odds ratio was not within the 95% confidence interval of previous GWAS findings, and showed association with type I patients in the opposite allelic direction (Table 5.1).
Other loci that showed nominal association in the present study include RNF114 and ZC3H12C.
RNF114 (ZNF313) was identified as a novel psoriasis susceptibility locus in the GWAS (Capon et al., 2008) and results were subsequently replicated in other studies (Nair et al., 2009; Strange et al., 2010; Staurt et al., 2010; Tsoi et al., 2012). We genotyped a single SNP (rs1056198) from
RNF114, and obtained a nominal significance in all three types of patient groups. Similar results were obtained for ZC3H12C, which codes for Zinc-finger protein regulating macrophage activation. It was also identified as disease susceptibility region for psoriasis in a Caucasian population (Tsoi et al., 2012).
Observed associations in the current study are of interest for several reasons. Firstly, when patients were classified into two groups based on the age of onset as described by Henseler and
Christopher (Henseler and Christophers, 1985) several differences were observed. MHC showed the largest difference with type I patients. Associations with LCE3B/LCE3C and REL, were stronger in type I group also, however the difference was not statistically significant. Given the fact that type II group was smaller than type I, a strong effect in type II group could still be observed for TNIP1 and TYK2. In addition PRR9 association was reported for the first time in Exploring the candidate and GWAS SNPs for association
Pakistani psoriasis patients. Also, we indirectly confirmed association with IL13 previously reported in another Pakistani study (Shaiq et al., 2013).
We observed nominally significant association with IL12 (rs3213094) and it was also in absolute
LD with previously genotyped SNPs rs2082412 and rs3212227 in the Pakistani samples (Shaiq et al., 2013). However, no association was reported to any of these SNPs. Similarly, we also observed nominally significant association with RNF114 that was not associated previously in the Pakistani samples although both SNPs, rs1056198 genotyped in our samples, and rs495337 previously reported, are in absolute LD with each other (r2=1).
An integrated model has been proposed for psoriasis in which skin barrier function genes and immune system genes play their role in disease pathogenesis (Bergboer et al., 2011). In genetically predisposed individuals e.g heterozygous or homozygous for LCE3C_LCE3B-del, minor injury and exposure to antigens could lead to enhanced inflammatory responses and insufficient or delayed skin barrier repair (de Cid et al., 2009; Bergboer et al., 2011). It results in the activation of innate immune responses such as NFκB signaling and secretion of cytokines, chemokines and β-defensins. The low-grade inflammation triggered by keratinocyte activation will attract T cells and dendritic cells to the skin that could result in the activation of adaptive immune system. Current study supports evidence for an integrated model that combines skin barrier functions (LCE3B/LCE3C and PRR9 genes), innate-immune system (e.g., REL, TNIP1,
ZC3H12C and NOS2 genes) and adaptive immune system (e.g., IL13, IL12B, HLA-C, TRAF3IP2 and RNF114) involvement. Subsequent immune response characterized by secretion of Th1 and
Th17 cytokines will in turn cause keratinocytes activation resulting in a vicious cycle and chronicity of inflammation (Fig 5.1). Our results showed that skin barrier function genes and the Exploring the candidate and GWAS SNPs for association
immune system genes both work in an integrated fashion to present psoriasis in our population as described for the Caucasian population.
Figure 5.1: Tentative model of psoriasis based on genetic and cell biological data. (Bergboer et al., 2011).
The proposed model of psoriasis presented in Figure 5.1, could contribute to prevention and therapy of psoriasis. The vicious circle can be interrupted at any point, using the appropriate medication. T-cell-directed therapies will suppress secretion of Th1 and Th17 cytokines, resulting in a decrease of keratinocyte activation. Anti-TNF therapy will act on secreted or membrane-bound TNF, either from keratinocytes or from immunocytes. Retinoids suppress Exploring the candidate and GWAS SNPs for association
cytokine-induced keratinocyte activation and will decrease defensin and cytokine secretion.
Vitamin D3 derivatives will inhibit keratinocyte proliferation and thereby normalize epidermal differentiation, promoting skin barrier restoration. Various other successful antipsoriatic therapies such as corticosteroids, dithranol, and methotrexate may act on many points in the vicious circle, as they are found to be immunosuppressive but can also affect keratinocyte proliferation and differentiation.
This is the first study showing a nominal significance of association at the LCE3B, PRR9,
TNIP1, IL12B, ZC3H12C and RNF114 in Pakistani Population. Another study has been published from Pakistan (Shaiq et al., 2013) with 30 markers from 24 known psoriasis suspceptibility loci. We replicated the associations with HLA-C (MHC), IL13, TRAF31P2, REL and NOS2 genes previously observed in Pakistani psoriasis samples. Our study is the largest study as previous study included 351 cases whereas in the present study 57 markers in 533 cases were genotyped. We also analysed the psoriasis samples on the basis of age of onset. Overall picture of our results showed that similar molecular mechanisms and genetic risk factors are involved in disease pathogenesis in Pakistani psoriasis patients as in other populations. We replicated the association with known strongest markers in other populations especially
Caucasians e.g., HLA, LCE3B, TNIP1 and IL12B. The other Pakistani study failed to replicate
TNIP1 and IL12B gene associations, but in the present study the large sample size and further subclassification of our data gives a more reliable picture of the genetics of psoriasis in Pakistani population. Since, of all the 57 markers analyzed in this study only nine SNPs displayed odds ratio in the opposite allelic direction, and only three markers failed to reach the same odds ratios in this study within a 95% confidence interval as in the original GWAS findings, therefore, we Exploring the candidate and GWAS SNPs for association
have no reason to believe that the Pakistani psoriasis patients are particularly different from other investigated populations. However, two GWAS SNPs, which were nominally significant in our study, were associated in the opposite allelic direction, where the reported GWAS risk allele was the protective allele in our study. Perhaps these could either be true population differences or just random chance events. Type I and type II psoriasis difference was most notable for MHC,
LCE3B and REL in type I and for TNIP1 and RUNX3 in type II psoriasis. Further studies using large samples drawn from diverse ethnic populations will be required to provide a more comprehensive understanding of the global genetics of psoriasis. Conclusion
6. Conclusion
Psoriasis is a common skin disease occurring worldwide. Susceptibility to psoriasis has a strong genetic component with additional triggering factors playing an important role in disease presentation. It is not a life threatening disease but affects the quality of life in general and can strongly influence a patient's self-image, self-esteem and sense of well-being. Psoriasis patients suffer impaired quality of life similar to or worse than patients with other chronic diseases such as ischemic heart disease and diabetes (Finlay and Kelly, 1987).
Since the genetic component is highly variable among different populations of the world depending on the geographical location and ethnic origin, the current study was aimed to determine the genetics of psoriasis in Pakistani population in a perusal to better understand disease pathogenesis. A comprehensive investigation was carried out by genotyping significantly associated loci reported in other populations. It may be noted that the male patients are over represented in each of the association study. The reason for higher number of male patients is that the females mostly avoid visiting the clinics in our conservative society unless the disease becomes life threatning. However the power calculated for an independent case control study was high enough to reject the null hypothesis.
HLA is the most well established genetic marker for psoriasis susceptibility. In our study, HLA allelic association with psoriasis samples confirmed the previous consistently reported associations with HLA-B*57 and Cw*0602 (Elder et al., 1994). In addition novel associations not reported in any other population, were observed with HLA-A*3201, B*40, Cw*15 and
DRB1*03. In the haplotype analysis, EH-57.1 haplotype showed strong association which is also consistent with previous reports in other populations. Some positive and negative novel Conclusion
haplotype associations were also observed along with some associations that are reported previously in other ethnic groups. In meta-analysis most of the associated alleles follow the same trend reported in other populations but some alleles showed deviation from the reported studies.
Variations from the reported studies reflect the population specific variations of disease association.
Association studies of ACE I/D polymorphism with psoriasis in Caucasian and Asian populations have yielded inconsistent results in previous studies. In this study genotyping of I/D polymorphism with respect to psoriasis association of II genotype as well as I allele gave same results as reported previously in some of the Caucasian (Ozkur et al., 2004; Nagui et al., 2012;
Weger et al., 2007) and Chinese population studies (Chang et al., 2007; Al-Awadhi et al., 2007;
Yang et al., 2014). The results reported here also differ from some other studies reported in the two populations (Vasku et al., 1999; Veletza et al., 2008; Coto-Segura et al., 2009, Liu et al.,
2007).
Current study also included investigation of association for fifty seven single-nucleotide polymorphisms (SNPs) from 42 loci. Genotyping results showed genome wide significant association of the MHC region, as well as nominally significant associations at ten other loci
(p<0.05) in the investigated Pakistani population. These loci included LCE3B, REL, IL13/IL4,
TNIP1, IL12B, TRAF3IP2, ZC3H12C, NOS2 and RNF114 from GWAS and PRR9 reported from a previous candidate gene study.
The overall picture of results showed that similar molecular mechanisms and genetic risk factors are involved in disease pathogenesis in Pakistani psoriasis patients as in other populations. We presented the first study showing a nominal significance of association at the LCE3B, PRR9, Conclusion
TNIP1, IL12B, ZC3H12C, ACE and RNF114 in Pakistani population. Genotyping analysis revealed that besides HLA the most strongly associated loci viz LCE and IL12B were found to be strongly associated in the studied population which is also similarly reported in white population of European origin. This observation was different from previous study on Pakistani psoriasis patients (Shaiq et al., 2013). Results of the current study may reflect a better picture of association as the results have shown similarity with results for the white population of European origin. Various population based studies have shown a close evolutionary relationship of
Pakistani population with the whites of European origin. (Mansoor et al., 2008).
For HLA, we replicated the strong associations that were observed in whites of European origin.
A previous study from Pakistan on the HLA polymorphism in six ethnic groups suggested an influence from white European and Oriental populations (Mohyuddin et al., 2002). These reports support the findings of our study and thus reinforce the validity of true HLA associations in
Pakistani population.
In ACE gene study, we found the associations that confirm some of the previous studies on white population of European origin and also contradict some studies on similar populations.
Genotyping analysis with SNPs revealed that the top 3 strongly associated loci reported in caucasian population have also shown association in our samples. This also gives a true representation of Pakistani psoriasis samples in contrast to a previous study
Pakistani population is diverse with different ethnic groups residing in different parts. The samples in our study belonged to various castes and tribes from Northern Punjab and Khyber
Pakhtunkhwa and were mostly of Punjabi and Pathan in their ethnic origins. The study in this thesis provided a reasonable number of samples from the local area with limitation of samples Conclusion
from rest of the Pakistani ethnic groups such as Sindhi and Brahui from the Southern regions.
We assume that the study cohort is a representative of Pakistani population in general as the overall genetics of the population is closely related to the whites of European origin and therefore represent the genetics of psoriasis in the region.
The main aim of molecular genetics research is to identify genes involved in human diseases, which ultimately leads to a better comprehension of disease etiology and also its management.
Such studies are more straight forward for diseases with simple Mendelian inheritance pattern, but in case of complex diseases the identification of the genetic component and its role in disease pathogenesis is difficult to determine. It is mainly because in complex diseases several genes with overlapping effects, epigenetics and the environment collectively lead to a specific phenotype. Psoriasis is genetically and phenotypically a very heterogeneous disease. Several variants of environmental factors, disease history, antigens, super-antigens, and genetic susceptibility are involved in its pathogenesis. A number of effective treatments have been developed for its management but a cure for this common enigmatic disease is still lacking.
Moreover, patients may experience significant side effects from currently available management modalities. Identification of the psoriasis specific genes will help in revealing the contributing biological pathways in pathogenesis of the disease that will help in understanding disease nature and will ultimately help in developing better therapy. References
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