The Association of Human Leukocyte Antigen(HLA)

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2009-01-01 The Association of Human Leukocyte Antigen(HLA) Alleles and Type 2 Diabetes Mellitus (T2DM) among Mexican Americans (MA) Kantibhai Motiram Patel University of Texas at El Paso, [email protected]

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THE ASSOCIATION OF THE HUMAN LEUKOCYTE ANTIGEN (HLA) ALLELES

AND TYPE 2 DIABETES MELLITUS (T2DM) AMONG MEXICAN AMERICANS (MA)

KANTIBHAI MOTIRAM PATEL

Interdisciplinary Health Sciences

APPROVED:

______Nelda C. Martinez, Ph.D., RN, Chair

______Delfina C. Dominguez, MT (ASCP), Ph.D.

______Jianying Zhang, M.D., M.PH., Ph.D.

______Robert L. Anders, Dr.PH, APRN, CS, CNAA

______Zuber D. Mulla, Ph.D.

______Patricia D. Witherspoon, Ph.D. Dean of the Graduate School

Dedication

To my wonderful family:

I dedicate this dissertation to my wonderful family who stood by me and supported me

unconditionally throughout this process.

THE ASSOCIATION OF THE HUMAN LEUKOCYTE ANTIGEN ALLELES AND

TYPE 2 DIABETES MELLITUS AMONG MEXICAN AMERICANS

KANTIBHAI MOTIRAM PATEL, M.Ed., CHS (ABHI), I (ASCP)

DISSERTATION

Presented to the Faculty of Graduate School of

The University of Texas at El Paso

in partial fulfillment

of the requirements

for the degree of

DOCTOR OF PHILOSOPHY

Interdisciplinary Health Sciences

THE UNIVERSITY OF TEXAS AT EL PASO

December 2009

Acknowledgements

First of all, I would like to thank Dr. Nelda C. Martinez, my mentor, who advised and guided me throughout my research and completion of my dissertation. Her assistance with the organization and editing of my proposal was of immense help.

Second, I would like to thank all my present committee members: Dr. Delfina C. Dominguez, Dr. Jianying Zhang, Dr. Robert L. Anders, and Dr. Zuber D. Mulla, and past committee members: Dr. Judith A. Pester of Sierra Medical Center, Dr. Rodrigo X. Armijos, Dr. Mary-Margaret Weigel, and Dr. Amitava Biswas of the University of Texas at El Paso, TX. Their advice in data analysis, organizing my proposal, and their time to review my proposal was of great help.

I wish to express my special thanks to: Dr. Ruta Radvany, Northwestern University Medical School, Chicago, IL, Dr. Subba Dhanwada, Mercy Medical Center, Des Moines, IA, Dr. Steven Geier, Laboratories at Bonfils, Denver, CO, Dr. Lakshmi Gaur, Puget Sound Blood Center, Seattle, WA, Kevin Harrell and Haik Muradyan from One Lambda, Inc., Canoga Park, CA, and Dr. Harry Wilson, Dr. Hector Diaz-Luna, and Dr. Fernando Raudales, Sierra Providence Health Network, El Paso, TX, and Ms. Linda Sigmund of United Blood Services, El Paso, TX, for their encouragement and technical contribution.

I thank my Transplant Immunology Laboratory staff at Sierra Medical Center: Margarita Pena, Delores C. Gonzalez, and Everick Austin for their excellent technical assistance.

I would like to thank to Ms. Lee Ann Paradise for her excellent editing work on my dissertation.

I would also like to thank my wife, Sharda Patel, daughter, Kaushal Patel, and son, Devesh Patel. The tremendous support and understanding they extended had great impact on the pursuit of this project.

Last, but not least, I am grateful to the senior management team from Las Palmas Medical Center Mr. Hank Hernandez, CEO, Mr. Don Karl, COO, Mrs. Caryn Iverson, Assistant CNO, and Ms. Leonor Chavez, Administrative Director, for their assistance. I appreciate their willingness to allow me to proceed with my dissertation proposal, and to pursue basic genetics studies related to diabetes and other disease research.

There are so many that have directly or indirectly helped me in this research project; I’m grateful for their invaluable suggestions in shaping up and completion of my dissertation, “The Association of the Human Leukocyte Antigen (HLA) alleles and Type 2 Diabetes Mellitus (T2DM) among Mexican Americans (MA)” funded by the College of Health Sciences, the Graduate Enhancement Funds, and for their award of the funding for conference attendance.

Abstract

The epidemic of type 2 diabetes mellitus (T2DM) is ranked as a major public health priority across the United States and especially in the El Paso, Texas region. The risk for the development of T2DM is greater in minority groups, particularly among Mexican Americans (MA) who comprise approximately 78% of El Paso’s population. The growing incidence of T2DM in this group is typically attributed to increase in weight (obesity). The incidence of diabetes may also be influenced by genetic factors that are unique to this group.

Several earlier studies have identified genetic markers for type 1 diabetes mellitus (T1DM). These markers, which reside in the major histocompatibility complex (MHC), are known as the human leukocyte antigens (HLA). These are divided into Class I (HLA-A, B, C loci) and Class II (HLA-DR and DQ loci) antigens. Although some antigens are purported to be protective, other antigens are indicated for possible susceptibility with T2DM, particularly among MA. This includes the association of Class II alleles and T2DM in this ethnic population. However, there are only a few studies that have explored the association of HLA and T2DM among MAs. Given the limited study and information available, genetic markers for susceptibility and protective effects for MA with and without T2DM would be merited. This study is guided by the following research questions: (1) What is the relationship between HLA Class I (HLA-A, B, C loci) antigens and T2DM among MA?; (2) What is the relationship between HLA Class II (HLA-DR and DQ loci) antigens and T2DM among MA?; and (3) What is the relationship between specific HLA Class II (HLA-DRB1*, DQA1*, DQB1* loci) alleles and T2DM among MA?

The genetic testing proposed for this study has the potential to significantly advance our understanding of the genetic basis of T2DM. This is especially important for advancing our knowledge as it relates to MA people. Early detection of individuals with susceptibility or protective factors for T2DM will likely allow for (1) protection or delay of the onset of diabetes through known preventive strategies; (2) earlier treatment of the disease; and/or (3) prevention of chronic diabetes complications for those individuals.

Methodology of this case-controlled study was divided into two parts: Part I of the study consisted of 110 cases (with T2DM), 196 controls #1 (without T2DM and without family history of T2DM), and 24 controls #2 (with family history and without T2DM). These groups were analyzed by serological and whenever possible confirmed by SSP-DNA methods. Sierra Medical Center Transplant Immunology Laboratory was instrumental for collection of HLA data. Part I focused on data analysis for HLA-A, B, C, DR, and DQ antigens in association with T2DM.

Part II of the study involved 57 frozen samples derived from a previous study conducted at The University of Texas at El Paso. Additional testing and analysis included 22 frozen blood samples that were derived from Sierra Medical Center, El Paso, Texas.

The HLA-DNA alleles testing were performed at Las Palmas Medical Center using Genomic DNA extracted from human leukocytes. Extracted DNA was used for identifying HLA DRB1*, DQA1*, DQB1* alleles. The process involved a reverse sequence-specific oligogonucleotide probes (rSSO) methodology. The testing employed in the study utilized

LABType, Luminex technology that discriminates between the different alleles. Following a polymerase chain reaction (PCR) process, the amplified DNA product was biotinylated, which allows it to detect using R-Phycoerythrin-conjugated Strepavidin (SAPE).

The data was analyzed using PROC LOGISTIC in the SAS Statistical Software. Logistic regression was used to calculate crude and adjusted odds ratio (OR), chi-square, and p-value with the binary outcome for T2DM.

The results of the SAS analysis showed statistically significant protective and susceptible association with controls and T2DM. HLA-A3 and B35 antigens showed protective association with T2DM and control #1 (without T2DM and without history of T2DM) with crude OR and adjusted age and sex OR. The susceptible association demonstrated with T2DM and control # 1 was associated with HLA-B44, B49, B50, and C5 antigens with crude OR and/or adjusted age and sex OR. The T2DM and controls #2 (without T2DM and with family history of T2DM) indicated protective association with HLA-A2 and A25 antigens for crude OR and not with adjusted (age/sex) OR. The HLA-A28, B56, B57, and DQ1 antigens showed protective association with adjusted (age and sex) OR and not with crude OR. All these associations showed a confounding factor with age and sex with case-control #1 and case-control #2. The case-control of study HLA allelic markers analysis did not show a statistically significant protective or susceptible association with T2DM, perhaps due to a smaller sample size.

Table of Contents

Page

Acknowledgements……………………………………………………………………… iv

Abstract………………………………………………………………………………….. v

Table of Contents ………………………………………………………………………. vii

List of Tables ……………………………………………………………………………. xiv

List of Figures…………………………………………………………………………… xviii

Introduction …………………………………………………………………………….. 1

Diabetes Mellitus (DM) and Prevalence Forms……………………………….. 3

The Human Leukocytes Antigen (HLA) Complex……………………………. 5

HLA Class I and Class II Antigen and Allele Nomenclature…………………. 10

Summary…………………………………………………………………………. 11

Background and Significance……………………………………………………………. 13

Purpose of the Study……………………………………………………………... 14

Research Questions………………………………………………………………. 14

Theoretical Framework Model of Genes-environment Interaction in T2DM... 14

Theoretical Framework Model of HLA Antigen/Allele Association in T2DM...16

Limitations………………………………………………………………………… 18

Summary…………………………………………………………………………... 18

Review of Related Literature…………………………………………………………….. 19

HLA Class I (HLA-A, -B, -C Locus) Antigen Association………………………19

HLA Class II (HLA-DR, -DQ Locus) Antigen Association……………………. 21

HLA-DRB1*, DQA1*, DQB1* Allele Association……………………………… 24

vii

Summary………………………………………………………………………….. 25

Preliminary Study………………………………………………………………………… 27

Crude OR Calculation……………………………………………………………. 28

Results and Analysis ……………………………………………………………... 28

Research Design and Methods…………………………………………………………... 32

Part I………………………………………………………………………………. 32

Research Question #1…………………………………………………………….. 33

Research Design…………………………………………………………... 33

Sample Size and Power…………………………………………………… 33

Protection of Human Subject–IRB……………………………………… 35

Inclusion/Exclusion Criteria for Acceptance…………………………… 35

Research Methodology…………………………………………………… 36

Limitations………………………………………………………………… 37

Statistical Analysis………………………………………………………... 37

Case-Control Group-A…………………………………………… 38

Case-Control Group-B…………………………………………… 39

Research Question #2…………………………………………………………….. 39

Research Design…………………………………………………………... 39

Protection of Human Subject–IRB……………………………………… 40

Inclusion/Exclusion Criteria for Acceptance……………………………. 40

Research Methodology…………………………………………………….40

Limitations………………………………………………………………… 42

Statistical Analysis……………………………………………………….. 42

viii

Case-Control Group-A…………………………………………… 43

Case-Control Group-B…………………………………………… 43

Part II ……………………………………………………………………………... 44

Research Question #3…………………………………………………………….. 44

Research Design (Set #1)………………………………………………… 44

Protection of Human Subject–IRB (Set #1)……………………………. 45

Inclusion/Exclusion Criteria for Acceptance (Set #1)………………….. 55

Research Design (Set #2)………………………………………………… 46

Protection of Human Subject–IRB (Set #2)…………………………… 46

Inclusion/Exclusion Criteria for Acceptance (Set #2)………………….. 47

Research Methodology…………………………………………………… 48

DNA Extraction Procedure…..………………………………….. 49

LABType (rSSO) Class II Allele Typing Procedure…………... 50

Limitations………………………………………………………………… 53

Statistical Analysis……………………………………………………….. 54

Summary………………………………………………………………….. 55

Results…………………………………………………………………………………….. 56

Research Question #1……………………………………………………………. 56

Cases-Controls Group A (Case-Control #1)……………………...... 57

SAS Analysis of Class I Antigens (Case-Control #1)………………….. 65

Results of Class I Antigens (Case-Control #1)…………………………. 65

Cases-Controls Group B (Case-Control #2)…………………………… 67

SAS Analysis of Class I Antigens (Case-Control #2)………………….. 74

Results of Class I Antigens (Case-Control #2)…………………………. 74

Research Question #2……………………………………………………………… 76

Cases-Controls Group A (Case-Control #1)…………………………… 76

SAS Analysis of Class II Antigens (Case-Control #1)…………………. 80

Results of Class II Antigens (Case-Control #1)………………………… 80

Cases-Controls Group B (Case-Control #2)…………………………… 81

SAS Analysis of Class II Antigens (Case-Control #2)…………………. 85

Results of Class II Antigens (Case-Control #2)………………………… 85

Research Question #3……………………………………………………………… 86

Cases-Controls (Set #1 and #2)………………………………………….. 87

SAS Analysis of Class II Alleles (Case-Control Set #1 and #2)…………93

Results of Class II Alleles (Case-Control Set #1 and #2)……………………….. 93

Discussions…………………………………………………………………………………95

HLA Class I (HLA-A, B and C locus) antigens (Case-Control #1, Group A)… 95

HLA Class I (HLA-A, B and C locus) antigens (Case-Control #2, Group B)… 96

HLA Class II (HLA-DR, and DQ locus) antigens (Case-Control #1, Group A).97

HLA Class II (HLA-DR, and DQ locus) antigens (Case-Control #2, Group B).97

HLA Class II (HLA-DRB1*, DQA1* and DQB1* locus) alleles (Case-Control, Set #1

and #2)……………………………………………………………………… 98

Limitations, Problems, and Future Study………………………………………………. 104

Summary and Conclusions………………………………………………………………. 107

Summary………………………………………………………………………….. 107

Conclusions………………………………………………………………………... 109

List of References…………………………………………………………………………. 110

Abbreviations……………………………………………………………………………... 123

Title of Appendix…………………………………………………………………………. 125

Appendix A……………………………………………………………………………… 125

Demographic Data and HLA Class I Antigens……………………………………… 125

Appendix B………………………………………………………………………………. 126

Demographic Data and HLA Class II Antigens……………………………………… 126

Appendix C……………………………………………………………………………… 127

HLA Class I Antigen Nomenclature……………………………………………...127

Appendix D……………………………………………………………………………… 127

HLA Class II Antigen Nomenclature…………………………………………… 127

Appendix E……………………………………………………………………………… 128

HLA Class II (DRB1) Allele Nomenclature…………………………………….. 128

HLA Class II (DQA1) Allele Nomenclature…………………………………….. 130

HLA Class II (DQB1) Allele Nomenclature…………………………………….. 130

Appendix F………………………………………………………………………………. 131

HLA Class I Antigens – Controls #1 (1-7)……………………………………… 131

HLA Class I Antigens – Controls #2…………………………………………… 137

HLA Class I Antigens – Cases (1-4)…………………………………………… 138

Appendix G………………………………………………………………………………. 142

HLA Class II Antigens – Controls #1 (1-7)……………………………………… 142

HLA Class II Antigens – Controls #2…………………………………………… 148

HLA Class II Antigens – Cases (1-4)……..……………………………………... 149

Appendix H ……………………………………………………………………………... 153

HLA Class II alleles – Case-Control (Set #1)…………….…………………….. 153

HLA Class II alleles – Case-Control (Set #2)………………….……………….. 155

Appendix I……………………………………………………………………………… 156

Sierra Providence Health Network IRB Approval…………………………….. 156

Appendix J………………………………………………………………………………. 157

Sierra Providence Health Network IRB Renewal ………………………………157

Appendix K……………………………………………………………………………… 158

University of Texas at El Paso IRB Approval for SPHN………………………. 158

Appendix L………………………………………………………………………………. 159

University of Texas at El Paso IRB Renewal for SPHN- (1 of 2)……………… 159

University of Texas at El Paso IRB Renewal for SPHN- (2 of 2)……………… 160

Appendix M ……………………………………………………………………………... 161

University of Texas at El Paso IRB Approval for Apo-E Pilot Study…………. 161

Appendix N………………………………………………………………………………. 162

Approval Letter to Use Samples and Demographic Information of Apo-E Study... 162

Appendix O……………………………………………………………………………… 163

Las Palmas Medical Center IRB Approval for rSSO Testing…………………. 163

Appendix P………………………………………………………………………………. 164

Las Palmas Medical Center IRB Renewal for rSSO Testing………………….. 164

Appendix Q……………………………………………………………………………… 165

University of Texas at El Paso IRB Approval for Dissertation………………... 165

Appendix R……………………………………………………………………………… 166

xii

NIH Web-based Training Course Protection Human Research Participants…166

A Biographic Sketch……………………………………………………………………… 167

Curriculum Vita…………………………………………………………………………... 169

xiii

List of Tables

Table 1 Family history affects the risk of diabetes………………………………………5

Table 2 Demographic data of the Case (T2DM)-Control (without T2DM and without

Family History of T2DM)…………………………………………………………27

Table 3 Crude odds ratio (OR) is estimated by 2×2 table ……………………………... 27

Table 4 SPSS Analysis of HLA-A Locus antigens……………………………………… 28

Table 5 SPSS Analysis of HLA-B Locus antigens……………………………………… 29

Table 6 SPSS Analysis of HLA-C Locus antigens……………………………………… 29

Table 7 SPSS Analysis of HLA-DR Locus antigens……………………………………. 30

Table 8 SPSS Analysis of HLA-DQ Locus antigens……………………………………. 30

Table 9 Clinical features of Case (T2DM)-Control (without T2DM and without family

history of T2DM) - Questions #1 and #2……………………….………………... 32

Table 10 Required sample size for Case-Control of the susceptible with T2DM…….. 33

Table 11 Required sample size for Case-Control of the protective without T2DM….. 34

Table 12 Clinical features of the Case-Control (Question #3)………………………… 46

Table 13 Amplification mixture for three reactions……………………………………. 52

Table 14 Clinical features of the Case (T2DM)-Control #1 (without T2DM and without

family history of T2DM) - Question #1…………………………………………... 57

Table 15 Demographic data of the Case (T2DM)-Control #1 (without T2DM and without

family history of T2DM) - Question #1………………………………………...... 57

Table 16 SAS Analysis of HLA-A locus antigens Case (T2DM)-Control #1 (without T2DM

and without family history of T2DM) 1 of 2……………………………………... 59

xiv

Table 16 SAS Analysis of HLA-A locus antigens Case (T2DM)-Control #1 (without T2DM

and without family history of T2DM) 2 of 2………………….………...... 60

Table 17 SAS Analysis of HLA-B locus antigens Case (T2DM)-Control #1 (without T2DM

and without family history of T2DM) 1 of 3…………………………...... 61

Table 17 SAS Analysis of HLA-B locus antigens Case (T2DM)-Control #1(without T2DM

and without family history of T2DM) 2 of 3………………..…………………… 62

Table 17 SAS Analysis of HLA-B locus antigens Case (T2DM)-Control #1(without T2DM

and without family history of T2DM) 2 of 3………………..…………………… 63

Table 18 SAS Analysis of HLA-C locus antigens Case (T2DM)-Control #1 (without T2DM

and without family history of T2DM)…………………………………………… 64

Table 19 Clinical features of the Case (T2DM)-Control #2 (without T2DM and with family

history of T2DM)…………………………………...... 67

Table 20 Demographic data of the Case (T2DM)-Control #2 (without T2DM and with

family history of T2DM)……………………………...... 67

Table 21 SAS Analysis of HLA-A locus antigens Case (T2DM)-Control #2 (without T2DM

and with family history of T2DM) 1 of 2………………………………………... 69

Table 21 SAS Analysis of HLA-A locus antigens Case (T2DM)-Control #2 (without T2DM

and with family history of T2DM) 2 of 2……………………..…………………. 70

Table 22 SAS Analysis of HLA-B locus antigens Case (T2DM)-Control #2 (without T2DM

and with family history of T2DM) 1 of 2………………………………………... 71

Table 22 SAS Analysis of HLA-B locus antigens Case (T2DM)-Control #2 (without T2DM

and with family history of T2DM) 2 of 2………………………………………... 72

Table 23 SAS Analysis of HLA-C locus antigens Case (T2DM)-Control #2 (without T2DM

and with family history of T2DM)…………………………………………………73

Table 24 Clinical features of the Case (T2DM)-Control #1 (without T2DM and without

family history of T2DM) - Question #2………………………………………..... 76

Table 25 Demographic data of the Case (T2DM)-Control #1 (without T2DM and without

family history of T2DM) - Question #2…………………………………………..77

Table 26 SAS Analysis of HLA-DR locus antigens Case (T2DM)-Control #1 (without

T2DM and without family history of T2DM)……………………………...... 78

Table 27 SAS Analysis of HLA-DQ locus antigens Case (T2DM)-Control #1(without

T2DM and without family history of T2DM) ……….………………………….. 79

Table 28 Clinical features of the Case-Control #2 (without T2DM and with family history

of T2DM) - Question #2 ………………………………….……………………….81

Table 29 Demographic data of the Case (T2DM)-Control #2 (without T2DM and with

family history of T2DM) - Question #2…………..………………………………82

Table 30 SAS Analysis of HLA-DR locus antigens Case (T2DM)-Control #2 (without

T2DM and with family history of T2DM)………………………………………. 83

Table 31 SAS Analysis of HLA-DQ locus antigens Case (T2DM)-Control #2 (without

T2DM and with family history of T2DM)………………………….…………… 84

Table 32 Clinical features of the Case (T2DM)-Control (without T2DM and without family

history of T2DM) - Question #3………………………………………………….. 87

Table 33 Demographic data of the Case (T2DM)-Control (without T2DM and without

family history of T2DM) - Question #3………………………………………...... 87

xvi

Table 34 SAS Analysis of HLA-DRB1 locus alleles Case (T2DM)-Control (without T2DM

and without family history of T2DM) 1 of 2……………………………………..89

Table 34 SAS Analysis of HLA-DRB1 locus alleles Case (T2DM)-Control (without T2DM

and without family history of T2DM) 2 of 2……………………………………. 90

Table 35 SAS Analysis of HLA-DQA1 locus alleles Case (T2DM)-Control (without T2DM

and without family history of T2DM)…………………………………………... 91

Table 36 SAS Analysis of HLA-DRB1 locus alleles Case (T2DM)-Control (without T2DM

and without family history of T2DM)……...... 92

xvii

List of Figures

Figure 1 HLA gene complex on human chromosome 6…………………………………6

Figure 2 Structure of MHC Class I……………………………………………………… 7

Figure 3 Structure of MHC Class II…………………………………………………….. 7

Figure 4 Inheritances of HLA antigens…………………………………………………. 8

Figure 5 Inheritance of HLA haplotypes……………………………………………….. 9

Figure 6 HLA antigen and allele nomenclature………………………………………... 10

Figure 7 Gene and environmental interaction in T2DM………………………………. 16

Figure 8 HLA antigens and alleles relationship with T2DM among MA…………….. 17

Figure 9 Summary of DNA extraction………………………………………………….. 50

Figure 10 Summary of LAB type rSSO HLA allele typing…………………………..…51

Figure 11 LAB type rSSO procedure……………………………………………………. 53

xviii

Introduction

Diabetes now affects nearly 24 million people in the United States (Centers for Disease

Control and Prevention (CDC), 2007). This reflects about 8% of the U.S. population. After adjusting for the population age difference between groups, Native Americans and Alaska Natives

(16.5 %) had the highest rate of diagnosed diabetes across race groups, followed by African

Americans and Hispanic Americans (11.8%), CDC, 2007). For Hispanic Americans, the highest prevalence is found among Mexican Americans (MA), (11.9%), followed by Puerto Ricans

(10.4%) and Cubans (8.2%). Asian and white Americans reflect the lowest prevalence rates for diabetes, 7.5% and 6.6%, respectively (CDC, 2007). According to the American Diabetes

Association (ADA), in 2007 the annual direct and indirect costs of diabetes care in the United

States were estimated to be 290 billion dollars (CDC, 2007).

Diabetes is the leading cause of death among those living along the U.S.-Mexico border

Pam American Health Organization, 2007). In particular, type 2 diabetes mellitus (T2DM) is increasing throughout the U.S.-Mexico border region along with risk factors for this disease

(obesity and sedentary lifestyle). Some 1.1 million U.S.-Mexico border residents 18 years of age and over suffer from T2DM and 836,000 are pre-diabetic. Nearly 22 % of those with T2DM are unaware they have the disease (Pan American Health Organization, 2007).

The etiology of type 1 diabetes mellitus (T1DM) and T2DM are the results of autoimmune, genetic, and environmental factors (ADA, 2005; CDC, 2007). Both the American

Diabetes Association (ADA) and CDC have cited T2DM as a major public health problem in the

United States, especially among MA. The prevention, early diagnosis, and treatment of the people with T2DM and its associated complications are ranked as major health priorities in the United

States, especially among MA (ADA, 2005). MA makes up approximately 78% of the population in the El Paso County (Martinez & Bader, 2007).

The data from the Hispanic Health and Nutrition Examination survey showed an increased prevalence of T2DM in the Hispanic population compared to non-Hispanic whites

(Talamantes, Lindeman, & Mouton, 2008). According to the Texas Diabetes Council (TDC), diabetes affects 1.3 million adult Texans and another 418,134 adults are believed to be undiagnosed. Although it is the sixth leading cause of death in all populations in Texas, among

Hispanics, it is fourth leading cause of death (TDC, 2008).

Although many studies have explored the etiology of T2DM among MA, overall there is very little understanding about the genetic risk for diabetes, particularly related to the inheritance of susceptible gene(s) from parents. Areas of genetic susceptibility come from human leukocyte antigens (HLA, also referred to as the major histocompatibility complex or MHC) Class I (HLA-

A, HLA-B, and HLA-C locus) and Class II (HLA-DR and HLA-DQ locus) antigens and Class II

(HLA-DRB1*, DQA1*, and DQB1* locus) alleles. These HLA genetic markers are known for their role in susceptibility for T2DM and are thought to be the central focus for disease association in this study (Perez-Luque et al., 2003; Haiyan et al., 2005; Almiwi et al., 2006;

Rudert & Trucco, 2007).

A history of T2DM in a first-degree relative doubles the risk of diabetes, suggesting that

T2DM has a genetic basis (Elbein, 1997). The risk of T2DM among family members varies by relationship. Inherited defects of both insulin sensitivity and β-cell function contribute to T2DM susceptibility (Kalsilamdrof & Tentolouris, 2003).

The risk for the development of T2DM is increased when compared to the general population in certain minority groups, including MA living in the El Paso region. This may be

partially due to the lifestyle of the family. The growing incidence of diabetes in these groups may be related to an increase in body mass index (BMI) or obesity. However, the degree of susceptibility for diabetes development in persons of Mexican descent is also influenced by genetic and environmental factors that are unique to these groups (Schulz et al., 2006; Weintrob,

2001).

Diabetes Mellitus (DM) and Prevalence Forms

The term diabetes refers to a group of diseases that affect the way the body uses blood glucose, commonly known as blood sugar. Glucose is vital to a person’s health because it is the main source of energy for the cells that make up your muscles and tissues. Essentially, glucose provides the body’s main source of fuel. The medical term mellitus is a Latin word meaning

“honey sweet,” referring to excess sugar in your blood and urine (Collazo-Clavell, 2008).

Types of DM: People often think diabetes is one disease. But glucose can accumulate in the blood for various reasons, resulting in different types of diabetes. The most common forms are

T1DM and T2DM. The gestational diabetes and pre-diabetes are not common types of diabetes.

T1DM is a less common form of diabetes compared to T2DM. Individuals with T1DM are unable to produce insulin and are given a diagnosis of insulin-dependent diabetes. As this type of diabetes affects younger individuals, the common name of juvenile diabetes is more often used.

T1DM is an autoimmune disease, which means that a person’s immune system is the source of trouble. Similar to how it attacks invading viruses or bacteria, the body’s infection-fighting system attacks the pancreas β-cells, which produce insulin. Researchers are not certain what causes a person’s immune system to fight its own body or “self,” but they believe certain factors such as genetics, exposure to certain viruses and diet may be involved. Only 5% to 10% of

diabetics have T1DM; the disease occurs almost equally among males and females (Collazo-

Clavell, 2008).

Diabetes ketoacidosis (DKA) predominantly in T1DM and is a dangerous condition that can be fatal if untreated and occurs when there is a failure to produce insulin over a period of time. Without sufficient insulin, the muscle cells become so starved for energy that the body takes emergency measures and breaks down fat. As your body transforms the fat into energy, it produces blood acids known as ketones. A buildup of ketones in the blood is called ketoacidosis.

DKA is more common in people with T1DM.

T2DM is the most prevalent form of the diabetes. Individuals with this form of diabetes can produce insulin, but their body either fails to produce enough insulin or their cells are insulin resistant. Excess fat, particularly in the abdomen, combined with lack of exercise have been identified as key factors in the development of T2DM. Approximately 90% to 95% of people over the age of 20, who have diabetes, have T2DM. Like T1DM, T2DM is also called by other names: non-insulin-dependent diabetes and adult-onset diabetes. The people with T2DM most often do not need insulin shots (Collazo-Clavell, 2008).

Gestational DM usually occurs during the second trimester of pregnancy, disappears immediately after pregnancy, and is usually T2DM. Approximately 5% to 10% of women will develop gestational diabetes during pregnancy.

Pre-DM is a condition that occurs when a person’s cells become resistant to insulin and the pancreas does not produce what is required. Blood glucose levels will increase above normal range, but not high enough to be diagnosed as a T2DM. There are 57 million Americans who have pre-DM. Table 1 lists the estimated risks of developing T1DM and T2DM associated with family history.

Table 1 Family history affects the risk of diabetes (Collazo-Clavell, 2008)

T1DM T2DM

Relative with Estimated risk Relative with Estimated risk diabetes diabetes

Mother 1% to 5 % Mother 5% to 20% Father 5% to 15% Father 5% to 20% Both parents 0% to 25% Both parents 25% to 50% Brother or sister 5% to 10 % Brother or sister 25% to 50 % Identical twin 25% to 50% Identical twin 60% to 75%

The Human Leukocytes Antigen (HLA) Complex

The HLA complex is a cluster of linked genes located on the short arm of chromosome 6

(Figure 1). This genetic complex comprises the MHC of humans (Rodey, 2000). HLA gene products are glycoprotein molecules found on cell surface membranes. Antigens described as

Class I are found on the surface of platelets and of most nucleated cells of the body, including lymphocytes, granulocytes, monocytes, and constituents of solid tissues. Class II antigens have more restricted distribution, being present at all times on B lymphocytes and cells of monocyte/macrophage lineage and on activated T lymphocytes and other cells after suitable stimulation (American Association of Blood Banks, 2008). The HLA antigens have long been known for their important role in controlling interactions between the different lymphocyte subpopulations that are responsible for generating immune response (SchieβI, 1986).

The genes of the MHC demonstrate more polymorphism than any other genetic system

(i.e., several alleles exist at each locus). An allele is an alternate form of a gene occupying the same locus on a particular chromosome. Nevertheless, for each locus a person has only one allele per chromosome and, therefore, encodes no more than two HLA antigens per locus. The antigens at each HLA locus are codominant (i.e., each is expressed independently). If both antigens at a locus are the same, the person is said to be “homozygous” (Tradif et al., 1993; Rodney, 2000).

Figure 1 HLA gene complex on human chromosome 6 (Source: Geier’s presentation, 2005)

Although this study focuses on two Classes of antigens and alleles, overall the HLA gene complex is actually comprised of three major regions: the Class I (HLA- A, HLA-B, and HLA-C loci); Class II (HLA-DR and HLA-DQ loci); and the Class III region (C4, C2, factor B, 21- hydroxylase, tumor necrosis factors (TNF), and heat shock protein HSP70). For this study, the

Class I region encodes genes for heavy chains of classical transplantation that includes HLA-A,

HLA-B, and HLA-C locus antigens. The Class II region encodes genes for alpha (α) and beta (β) chains for three types of expressed Class II antigens (HLA- DR, HLA- DQ, and HLA-DP). The

MHC consists of over 42 related loci (Geier, 2005).

Class I MHC

B C A

1 2 1 2 1 2 NH NH NH2 2 2

3 m 3 m 3 2m 2 2

Lipid Bilayer

COOH COOH COOH

(Geier, 2005)

Figure 2 Structure of MHC Class I (Source: Geier’s presentation, 2005)

In Figure 2, the structure of the Class I (HLA-A, B, and C locus) regions are shown. The structure of Class I consists of two polypeptide chains, a heavy chain of molecular weight 45,000, and a light chain of 12,000; these two are non-covalently linked. The heavy chain is encoded by

HLA genes (Chromosome 6p21.3) and carries serologically detectable determinants (α1, α2, and

α3). The light chain is composed of β2-microglobulin, encoded by the invariant β2-microglobulin gene on chromosome 15 (15q22).

Class II MHC

HLA-DP HLA-DQ HLA-DR

B2 A2 B1 A1 B2 A2 B1 A1 B1 B2 B3 A

NH2 NH2 NH2 NH2 NH2 NH2 NH2 NH2

1 1 1 1 1 1 1 1

2 2 2 2 2 2 2 2

Lipid Bilayer

COOHCOOH COOH COOH COOH COOH COOHCOOH

(Geier, 2005)

Figure 3 Structure of MHC Class II (Source: Geier’s presentation, 2005)

Figure 3 demonstrates the structure of the Class II (HLA-DR, HLA-DQ, and HLA-DP locus) regions. The structure of Class II is comprised of a light chain (molecular weight of 28,000) and a heavy chain (molecular weight 33,000); both chains are non-covalently bound. The determinants on these molecules are α1, α2, and β1, β2.

The recombination within the MHC is approximately 2% (Rodney, 2000). Normally a

complete set of HLA antigens is inherited from each parent as a unit or haplotype. Children who

inherit the same haplotypes from both parents are termed HLA-identical; those who inherit the

same haplotype from one parent, but a different haplotype from the other are known as haplo-

identical.

Linkage disequilibrium (LD) is the tendency for two alleles to be present on the same

chromosome or haplotype (positive LD) or not to segregate together (negative LD). As a result,

specific alleles at two different loci are found together more or less than expected by chance. The

situation may exist for more than two alleles.

The HLA genes demonstrate classical Mendelian inheritance (i.e., each individual may

inherit one of four possible combinations of paternal and maternal haplotypes). The probability of

genotypic HLA identity of any two siblings is 25%.

Inheritance of HLA antigens

Paternal A1 A2 A3 A9 Maternal Chromosomes Chromosomes B8 B12 B7 B5 HLA phenotype: X HLA phenotype: A1, A2, B8, B12, A3, A9, B5, B7, DR3 DR7 DR2 DR1 DR3, DR7 DR1, DR2

Offspring A1 A3 Haplotype 1: A1, B8, DR3 HLA phenotype: B8 B7 A1, A3, B7, B8, Haplotype 2: DR2, DR3 DR3 DR2 A3, B7, DR2

Figure 4 Inheritances of HLA antigens (Source: Shanahan, 2008)

Figure 4 demonstrate family segregation analysis where the antigens A1, B8, DR3 are

inherited from the father and antigens A3, B7, DR2 are inherited from the mother. The offspring

phenotype is A1, A3; B7, B8; DR2, DR3.

Figure 5 Inheritances of HLA haplotypes (Source: SchieβI’s HLA Typing, 1986)

Figure 5 demonstrates family segregation analysis where the haplotypes a/b are inherited from the father and haplotypes C/D are inherited from the mother. Child 1 and Child 3 share one haplotype, whereas Child 2 and Child 4 share a different one.

The HLA and disease association studies are the two major types of investigations to

determine the contributing antigens or genes that link to disease susceptibility or protective effects

(or any other phenotype). Although linkage studies can only use family data, association studies

can be family or population based.

Identification of susceptibility (risk) and protective markers allows use in immunogenetics

profiling, risk assessment, and therapeutic decisions. The present study is aimed at assessing such

specific factors. Further, the study will aid in refining already known along with constantly

emerging associations in the light of expanded knowledge of the HLA genetics.

HLA Class I and Class II Antigens and Alleles Nomenclature

The extreme polymorphism of the HLA system derives from the existence of multiple antigens or alleles at several loci. It is estimated that more than 100 million different phenotypes can result from all combinations of antigens or alleles in the HLA system. The extended haplotypes of an individual are nearly unique.

Figure 6 HLA antigens and alleles nomenclature interpretation (Source: Heard & Hensel’s ASHI Laboratory Procedure Manual, 2000)

Figure 6 demonstrates HLA antigens or alleles are designated by a letter following the

number that denotes the HLA series for Class I (HLA-A3, HLA-B7, and C1), Class II (HLA-

DR1, DQ5) antigens and Class II ( DRB1*0301, DQA1*0201, and DQB1*0201) alleles. Figure 7

shows the HLA Class I and Class II antigens and alleles nomenclature interpretation: For Class I

(HLA-A, HLA-B, or C locus) antigens, the letter indicates the locus, the first and second number

indicates the antigen (Example: A1, 11; B8, 57; C6, 12). For Class I (HLA-A*, HLA-B*, and

HLA-C*) alleles, the letter indicates the locus, the star indicates typing performed by DNA, the

first and second numbers indicate genes and the third and fourth indicate alleles; the fifth, sixth,

and seventh indicate intronic transitional change and the eighth letter indicates the low responder

(Example A*0101/*1101; B*0801/*5701; C*0601/*1201) alleles.

For Class II (HLA-DR and DQ locus) antigens, the letter indicates the locus, the first and

second number indicates the antigen (Example: DR 1, 4; DQ5, 8). For Class II (DRB1*, DQA1*,

and DQB1*) alleles, the first two letters indicate the locus, the third letter and forth number

indicate chain, the star indicates the typing performed by DNA, the first two numbers indicate

genes, the third and fourth numbers indicate alleles, the fifth indicates sequential difference

without protein change, and the sixth letter N indicates null alleles that do not express on the cell

surface antigen (Example: DRB1*0101/ *0401; DQA1*0501/*0302; DQB1*0501/*0302) alleles.

This study will involve HLA Class I (HLA-A, HLA-B, and HLA-C locus), Class II (HLA-

DR and HLA- DQ) antigens, and Class II (HLA-DRB1*, HLA-DQA1*, and HLA- DQB1* locus)

alleles. The antigens are comprised of HLA- A, HLA-B, HLA-C, HLA-DR, and HLA-DQ locus.

The HLA-A locus consists of 25 antigens, HLA-B locus consists of 53 antigens, HLA-C locus

consists of 10 antigens, HLA-DR locus consists of 19 antigens, and HLA-DQ locus consists of

nine antigens. The alleles are comprised of HLA-DRB1*, HLA-DQA1*, and HLA-DQB1* locus.

HLA-DRB1* locus consists of 490 alleles, HLA-DQA1* locus consists of 26 alleles, and HLA-

DQB1* locus consists of 69 alleles. The nomenclatures for Class I and Class II antigens are

provided in the Appendix C and D. The Class II (HLA-DRB1*, DQA1*, and DQB1*) alleles are

provided in the Appendices E.

Their association with T2DM was reported by Perez-Luque in 2003; DRB1*0701 and

DQB1*0201 alleles appear to have a protective effect against the development of T2DM in

Mexican Mestizos (Central Mexico), whereas DRB1*1101 and DQB1*0201 alleles are risk factors for T2DM in the Lebanese ethnic group as reported by Almawi in 2006.

Summary

The nomenclature of the HLA, the nature of the study, and the study plan are described in

detail. The research plan is explained, including the types of antigens and alleles studied (Class I

and Class II antigens and Class II alleles). The fundamental principles that govern the scope of the study are introduced, which sets the stage for a more thorough discussion of the research methods in the upcoming chapters.

Background and Significance

T2DM is a major cause of morbidity and mortality in the predominant segment of the

Mexican-American population located in the El Paso region. The study to identify genetic markers will open up a new avenue for our understanding of this metabolic disorder among this high-risk population group. Early detection of genetically susceptible individuals for T2DM will benefit from diabetes prevention and treatment, particularly considering the high risk for neurological and vascular complications of the disease. The economic value of such early diagnosis will be that of lessening the amount of health care funds expended and the well being of these individuals being significantly enhanced.

This study is expected to identify specific markers that are associated with HLA Class

I (HLA-A, HLA-B, and HLA-C locus), HLA Class II (HAL-DR and DQ locus) antigens, and

HLA Class II (HLA-DRB1*, HLA-DQA1* and DQB1* locus) alleles among MAs with T2DM, thus, identifying the possible genetic factors, which may serve as either the risk of susceptibility to diabetes, or, a protective factor for MA.

This study can provide information for early interventions with a focus on specific lifestyle interventions that may either prevent or slow the progression of this disabling disease.

Overall, this study will serve to enhance the quality of care and ultimately the quality of life for

MAs with T2DM by limiting or reducing the morbidity and mortality associated with the disease.

Such early diagnosis will have a major impact on health care. It not only aides in improvement of individual well-being by prevention strategies, but also lessens the economic burden of individuals and the health care system.

Purpose of this Study

The purpose of this study is to explore the relationship between HLA Class I and HLA

Class II HLA antigens and alleles and T2DM among MA.

Research Questions

The following are the research questions for this study of the relationship between HLA Class I and HLA Class II antigens and alleles with and without T2DM among MA.

Research Question #1: What is the relationship between HLA Class I (HLA-A, B, C loci) antigens and T2DM among MA?

Research Questions #2: What is the relationship between HLA Class II (HLA-DR and DQ loci) antigens and T2DM among MA?

Research Questions #3: What is the relationship between specific HLA Class II (HLA-DRB1*04,

DQA1*03, DQB1*03, and unknown Class II alleles) alleles and T2DM among MA?

Theoretical Framework Model of Genes-environment Interaction in T2DM

T2DM is often considered a polygenic disorder because multiple genes located on different chromosomes are associated with this condition. This is complicated by numerous environmental factors that also contribute to the disorder in genetically predisposed persons. Only a minority of causes of T2DM are by a single gene defect, such as maturity onset diabetes of the young, syndrome of insulin resistance (insulin receptor defect), maternally inherited diabetes, and the mitochondrial gene defect (Radha, Vimaleswaran, Deepa, & Mohan, 2003).

According to Radha, Vimaleswaran, Deepa, and Mohan’s (2003) theoretical framework model, the genes and environment do play a very important role in the development of T2DM in that the natural history of T2DM begins at birth when glucose homeostasis is normal, but

individuals are at risk for T2DM at some later time because of genetic polymorphisms

(diabetogenic genes). According to the model, T2DM shows a clear familial aggregation, but it does not segregate in a classical Mendelian fashion. T2DM is polygenic with different combinations of gene defects. Insulin biosynthesis, insulin secretion, and insulin action are shown to be affected by genetic and environmental factors. The task of identifying any single genetic susceptibility factor for T2DM is complicated by the complex interactions between genes and environmental factors (Figure 7). The maintenance of normal glucose homeostasis depends on a precisely balanced and dynamic interaction between sensitivity to insulin (especially in muscle and liver) and insulin secretion. The molecular circuitry that maintains glucose homeostasis depends on the result of several combined gene defects, or from the simultaneous action of several susceptible alleles, or combinations of frequent variants at several loci.

Environmental factors can probably aggravate the genetic predisposition leading to β-cell failure (Kahn, 2001). The exact mechanism of β-cell failure however remains controversial and it may be that it is regulated at the gene level (Kahn, 2001; Deffronzo, Bonadonna, & Ferrannini,

1992). It is generally accepted that insulin resistance (IR) precedes the failure of insulin secretion, which exacerbates this by imposing an increased secretory burden on the β-cells (Ferrannini,

1998). However, minor abnormalities in β-cell function have been demonstrated early in the course of T2DM, and even the first degree relatives of individuals with T2DM have a possible basis for an inherited component for β-cell failure (Kalsilamdrof & Tentolouris, 2003). In Pima

Indians, the progression from normal Impaired Glucose Tolerance (IGT) and finally to T2DM was accompanied by progressive decline in β-cell secretory capacity (Weyer, Bogardus, Mott, &

Pratley, 1999).

Genetic factors Genetic factors Genes influencing Genes influencing  cell Mass Obesity  cell Development Insulin Action  cell Function

 cell Immunogenicity Insulin Type 2 Insulin Secretory Resistance Defect DM Environmental factors Obesity Environmental Age factors Pregnancy Perinatal malnutrition Sedentary Lifestyle Diabetic mother Diabetogenic Drugs

Figure 7 Gene and environment interaction in T2DM (Source: Radha, Vimaleswaran, Deepa, & Mohan, 2003)

Insulin resistance and diminished insulin secretion increased genetic predisposition in the

Hispanic/Latino population: Metabolic syndrome abnormalities may cause abnormalities in β- cell function, leading to impaired glucose tolerance and eventually development of T2DM.

Theoretical Framework Model of HLA Antigens and Alleles Association in T2DM

The genes of the HLA region, MHC of humans, control a variety of functions involved in the immune response and influence susceptibility to over 40 diseases (Tiwari & Terasaki, 1985).

Theoretical studies in the development of models to determine the modes of inheritance of the

HLA-associated diseases have led to a better understanding of the model of inheritance patterns in type 1 diabetes, rheumatoid arthritis, multiple sclerosis, ankylosing spondylitis, hemochromatosis, celiac disease, and others. It is now clear that many of the HLA-associated diseases involve heterogeneity in their HLA components, as well as non-HLA genetic factors (Tiwari & Terasaki,

1985). In this model, I will explore the relationship between the HLA Class I and Class II antigens, as well as alleles with and without T2DM among the Mexican-American population.

To explore the relationship between HLA Class I and

HLA class II HLA antigens, alleles, and T2DM among

MA.

What is the What is the What is the relationship relationship relationship

between HLA between HLA between HLA

Class I (A, B, and Class II (DR and Class II (DRB1*,

C locus) antigens DQ locus) DQA1* and

and T2DM antigens and DQB1* locus)

among MA? T2DM among alleles and

MA? T2DM among

MA?

Figure 8 HLA antigens and alleles relationship with T2DM among MA

The HLA antigens’ and alleles’ relationship with T2DM among MA model is outlined in Figure

8. This study is divided into three research questions:

Research Question #1: What is the relationship between HLA Class I (A, B, and C locus) antigens and T2DM among MA?

Research Question #2: What is the relationship between HLA Class II (DR and DQ locus) antigens and T2DM among MA?

Research Question #3: What is the relationship between HLA Class II (DRB1*, DQA1*, and

DQB1* locus) alleles and T2DM among MA?

Limitations

The limitation of this study consists of the subjects included in the kidney transplant program at the Sierra Medical Center as kidney transplant recipients with T2DM; kidney transplant living donors; kidney transplant disease donors, or volunteer donors for quality control purposes. Other limitations of the study may be that it addresses only the MA ethnic group and selected demographic variables, such as age and sex, are employed.

Summary

The nomenclature of the HLA, the nature of the study and study plan are described in detail. The research plan, the types of antigens and alleles studied (Class I and Class II antigens and Class II alleles), is detailed introducing the fundamental principles that govern the scope of the study. Research plan description with the emphasis of the study plan outcomes are detailed, which sets the stage for more thorough discussion of the research methods in the coming chapters.

Review of Related Literature

The review of related literature will cover an outline of the association of the HLA-A,

HLA-B, HLA-C, HLA-DR, and HLA-DQ locus antigens with T1DM and T2DM among MA, other ethnic groups, and how this differs from MA without T1DM and T2DM. Statistical analysis of the preliminary data and odds ratio (OR) were performed from randomly selected cases (10) and controls (12) from Sierra Medical Center Transplant Immunology Laboratory patient and donor files of MA. I examined the association of the HLA-DRB1*, HLADQA1*, and

HLADQB1* alleles among MA with T2DM.

HLA Class I (HLA-A, HLA-B, and HLA-C locus) Antigen Association

The HLA Class I molecules are necessary for activation of a subset of (CD 8+) T cells.

The Class II region genes encode molecules that present peptide antigens to other T-cell subsets

(CD4+). Thus, the MHC molecules are critical in immune cell interactions. The tri-molecular complex between MHC molecules, peptides, and the T-cell antigen receptor on T lymphocytes is most probably central to the understanding of the associations between various HLA molecules and different autoimmune diseases. It seems likely they are due to the binding of certain organ- specific auto-antigenic peptides to the HLA molecules in question and subsequent presentation to auto-reactive T lymphocytes, which have escaped deletion (Garcia, Degano, & Stanfield, 1996).

The first evidence of MHC associations with diseases came from the observation of Lilly

(1964) that the susceptibility of mice to develop leukemia upon infection with Friend’s virus was controlled by the H-2 system. This finding was strengthened by the discovery of McDevitt (1969) that specific immune responses are controlled by the MHC changing the emphasis from malignant to autoimmune diseases.

The first convincing association between HLA and specific diseases was reported in the early 1970s for celiac disease (Falchuk, Rogentine, & Strober, 1972), psoriasis (Russell, Schultes,

& Kuban, 1972), and ankylosing spondylitis (Brewerton et al., 1973). Subsequently, a whole series of mostly autoimmune diseases, such as multiple sclerosis, insulin-dependent diabetes (type

1 diabetes), and rheumatoid arthritis were found to be associated with various HLA Class I alleles

(Schlosstein, Terasaki, Blustone, & Pearson, 1973). These observations provided strong support that polymorphic genetic factors are involved in the pathogenesis of these disorders. They also established HLA markers as powerful tools in unraveling the genetics of the conditions. It soon became clear that the HLA susceptibility to type 1 diabetes was positively associated with Class I antigens, HLA-B8 and B15, and negatively associated with HLA-B7. Moreover, it appeared that

HLA-B8/15 heterozygosity was associated with a higher risk than other genotypes. This suggested the existence of two different susceptibility factors that interact in those carrying both antigens (Thomsen & Bodmer, 1977).

Another important advancement in understanding the genetics of HLA-associated disorders was the realization that HLA-associated genes in patients are identical to those present in healthy individuals, thus the associations are not due to rare mutations (Svejgaard, Platz,

Nielsen, & Thomsen, 1975). It has also become clear that not all individuals carrying a disease- associated factor develop the condition in question. This may be attributed to the existence of as yet unknown HLA genes, which must then be in linkage disequilibrium with the genes now known to be associated to the fact that very few of the HLA-associated diseases are classical genetic diseases. The diseases are not inherited as such; it is the susceptibility that is inherited with HLA factors as genetic markers (Tiwari & Terasaki, 1985; Lechler & Warrens, 2000).

T2DM associated with HLA-A2 antigen was reported in a southern African black tribe, Xhosa

(Briggs, Jackson, Du-Toit, & Botha, 1980). The relationship between HLA-A2 and T2DM was also reported in the Pima Indians of the southwestern United States (Williams et al., 1981). The patients with gestational diabetes (GD) had an increased frequency of HLA-A33. The patient with GD who subsequently developed T2DM had significantly higher frequency of HLA-B41 than healthy controls (Perez-Luque et al., 2003).

Thus the research question of this dissertation proposal is to determine the Class I (HLA-

A, HLA-B, and HLA-C loci) antigen association with T2DM among El Paso’s Mexican-

American population.

HLA Class II (HLA-DR and DQ Locus) Antigen Association

Although association of diabetes with MHC Class I was extensively explored in the late

60s and early 70s, several investigators began to focus on Class II alleles, as MHC Class II polymorphism began to unravel in late 70s and early 80s. Several association patterns emerged, albeit a majority of them addressed T1DM.

The unraveling of the genetics of a disease is not complete until the mechanism behind the association becomes clarified. Some disease association has also been shown with HLA Class II alleles (Jersild et al., 1973). The mere existence of these HLA Class II alleles’ associations provides evidence, but not proof, that immune mechanisms are involved in the pathogenesis

(Lechler & Warrens, 2000). This evidence is strengthened by the recent characterization of the structure and biological function of MHC factors as antigen-presenting molecules. The discovery of the MHC restriction phenomenon (Todd, Bell, & McDevitt, 1987) was a very important step in that process because it made clear that the T lymphocytes only react with antigens bound to MHC molecules.

T1DM and HLA-B and DR antigen association has been reported (Terasaki, 1980); however, there are few HLA associations with T2DM. The situation across ethnic groups is different. In a population of Northern European ancestry, a parental history of T2DM increases the risk of T1DM in siblings, which suggests a genetic interaction between T1DM and T2DM.

There is also evidence that the HLA-DR4 antigen is associated with type 2 diabetes and transmission of the HLA-DR4 antigen from a T2DM parent to T1DM offspring (Rich, French,

Sprafka, Clements, & Goetz, 1993). The possible genetic interaction between T1DM and T2DM and an increased frequency of DR4 or DQ8 has been shown in T2DM with impaired β-cell function and increased need for insulin therapy (Li, Isomaa, Taskinen, Groop, & Tuomi, 2000; Li,

Linholm, Almgen, Gustafson, Forsblom, Groop, et al., 2005).

The patients with gestational diabetes (GD) had an increased frequency of HLA-DR2 and

DR9. The patient with GD who subsequently developed T2DM had significantly higher frequency of DR2 and lower frequency of DR1 and DR6 than healthy controls (Perez-Luque et al., 2003).

The proliferative retinopathy with T2DM patients showed an increase of HLA-DR7 and less frequency of HLA-DR11 compared with controls (Quiroz-Mercado et al., 2002). In another study in Turkey, the patients with non-proliferative retinopathy had higher frequency of HLA-

DR4 and DQ8 than those with proliferative retinopathy with T2DM. The HLA-DR7 frequency was associated more with proliferative retinopathy than non-proliferative retinopathy cases with

T2DM (Brinci, Brinci, Abidinoglu, Durupinar, & Oge, 2002).

Limited information is available regarding the presence of immunological markers and

HLA susceptibility genes for autoimmune pancreatic β-cell destruction in obese African

Americans with a history of diabetic ketoacidosis (DKA). Limited and conflicting information is

available regarding the prevalence of HLA susceptibility genes in African Americans with hyperglycemic crises. Winter et al. (1987) reported that the frequency of HLA-DR3 and HLA-

DR4 antigens was not increased in 12 African-American youths with diabetes. In contrast, Banerji et al. (1994) reported an increased frequency of HLA-DR3 or HLA-DR4 (65%) versus control subjects (30%) in 21 African-American patients with DKA. In a larger survey, no statistically significant HLA differences were found in the overall genotype distribution between the obese

DKA, the obese hyperglycemia, and the lean DKA groups. Nevertheless, a strong association was found between anti-glutamic acid decarboxylase (GAD) antibodies and the HLA DQB1*0201 allele suggesting that the HLA genotype provides a fertile background for the penetration of the autoantibody phenotype, particularly in the lean DKA group (Umpierrez et al., 1999). In the same study it was also shown that the DQB1*0602 allele, described as protective for type 1 diabetes in childhood-onset Caucasian studies, was present at normal frequency in DKA patient groups and was negatively associated with GAD antibodies. However, when ketosis prone-diabetic patients were grouped based on the presence of auto antibodies and β-cell function as opposed to lean and obese status, co-inheritance of certain HLA allotypes specifically, one or more alleles associated with β-cell autoimmunity, such as DQB1*02 allele, was not evident (Maldnado et al., 2008).

The genomic studies could transform into applications of predicting and preventing

T1DM, because approximately 89% of newly diagnosed patients carry the high-risk susceptibility haplotypes (HLA-DQ8, DQ2) and the remaining 11% develop T1DM due to interaction of genes and environmental factors (Balasubramanyam, Rema, & Mohan, 2006; Sanjeevi, Kanungo,

Shtauvere, Samal, & Tripathi, 1999).

HLA-DRB1*, DQA1* and DQB1* Allele Association

The HLA Class II alleles associated with T2DM is less clear. Few studies examined the prevalence of HLA Class II alleles and a possible role for HLA Class II in T2DM with autoimmune disease in adults, genetic interaction between T1DM and T2DM in families, and its association with Class II alleles with T2DM. It has been previously reported that the HLA Class II alleles, DRB1*0701/DQA1*0201/DQB1*0201 and DRB1*0403/DQA1*0301/DQB1*0302 haplotypes appear to be protective alleles against T2DM among Mexican Mestizos from central

Mexico (Perez-Luque, Alaez, Malacara, Garay, Fajardo, Nava, et al., 2003). Also reported is that

HLA Class II alleles, DRB1*040101, DRB1*070101, DRB1*150101, DQB1*0302,

DQB1*050101, and DQB1*060101, cause susceptibility with type 2 diabetes and DRB1* 110101 and DRB1*160101 alleles are associated with being protective in a Bahraini ethnic group (Motala et al., 2005). There is another study where the DRB1*110101/DQB1*0201 haplotype was a risk factor for type 2 diabetes in a Lebanese ethnic group (Almawi et al., 2006).

There are studies that found T2DM patients with end stage renal disease (ESRD) with increased frequencies of DRB1*1502, DQB1*0501, whereas the DRB1*0407 allele has been found to offer protection in the Mexican-Mestizos population (Perez-Luque et al., 2003).

Julio Granados and his group reported HLA Class II typing to distinguish between T1DM and T2DM based on the observation frequency of HLA-DRB1*08 alleles (Rodriguez-Ventura,

Yamamoto-Furusho, Coyote, Dorantes, Ruiz-Morales, Vargas-Alarcon, et al., 2007). They found an increase in children with type 2 diabetes when compared with patients with T1D associated with DRB1*03 and *04 alleles (Rudert & Trucco, 2007).

Summary

A review of the MHC, Class I region antigens, Class II region antigens, and Class II alleles and their role in detection of genetically associated disease conditions was presented in the previous section. General features of the MHC were reviewed; specifically the antigens coded by that complex as they relate to those with autoimmune diabetes mellitus and T2DM, a disease most prevalent in the Mexican-American population of the El Paso, Texas region. In summary, various

HLA alleles show association with diabetes and its complications; from a bulk of studies dating back to the late 70s until recently, it is very clear that HLA-DR4-DQ8 (DRB1*04-DQA1*0301-

DQB1*0302) and DR3-DQ2 (DRB1*0301- DQA1*0501-DQB1*0201) have been shown to be significantly associated with insulin-dependent diabetes mellitus (IDDM). These associations seem to transcend ethnic and racial barriers. Within the HLA gene complex, the polymorphic

MHC Class II gene HLA-DQ is most tightly linked to IDDM. A hierarchy of genetic associations among HLA-DQ alleles has been suggested in which HLA-DQA1*0301/DQB1* 0302 is the predominant HLA Class II allele associated with susceptibility in T1DM (IDDM) and HLA-

DQA1*0102/DQB1*0602 is the predominant HLA Class II allele associated with protection, even in individuals that carry HLA-DQA1*0301/DQB1*0302. Other HLA-DQ genotypes, such as HLA-DQA1*0301/DQB1*0301 and HLA-DQA1*0102/DQB1*0604, are not associated with

IDDM, even though they are structurally very similar to the susceptible allele, HLA-

DQA1*0301/DQB1*0302, and the protective allele, HLA-DQA1*0102/DQB1*0602, respectively. Furthermore, a single amino acid change seems to affect the function so drastically that protection is reversed to susceptibility. For example, HLA-DQA1*0102-DQB1*0602 is associated with protection against T1DM. A similar allele, HLA-DQA1*0102-DQB1*0604, contributes to T1DM susceptibility in certain populations with only a difference of seven amino

acids from the allele HLA-DQA1*0102- DQB1*0602. However, from the review of the literature, no such concrete evidence is available for T2DM and HLA association. However, studies have shown that type 2 diabetes could present itself in more than one form, thus affecting the clinical diagnosis of the disease.

Preliminary Study

Preliminary of the HLA antigens data analysis was performed using SPSS software version 15 for Windows that calculated Mantel Haenszel OR calculated for HLA- A, HLA-B,

HLA-C, HLA- DR, and HLA-DQ. This OR provided information regarding HLA associated with

T2DM among MA. This study consisted of the serology HLA typing and unclear antigens confirmed by Sequence Specific Primers (SSP) of ten randomly selected cases with T2DM and 12 controls without T2DM obtained from Sierra Medical Center’s Transplant Immunology archive files (Appendix: I to M. IRB approval from Sierra Providence Health Network and University of

Texas at El Paso). The summary of the demographic data is as follows:

Table 2 Demographic data of the Case (T2DM)-Control (without T2DM and without family history of T2DM)

Case (T2DM) Control (without T2DM and (n=10) without family history of T2DM) (n=12) Age Mean 56 50 Age SD 9.5 7.5 Male 5 (50%) 7 (58.3%) Female 5 (50%) 5 (41.7%) Race (MA) 100% 100%

Table 3 Crude OR is estimated by 2×2 table

Antigen T2DM (+) T2DM (-) Total DQ (+) 4 (a) 6 (b) 10 DQ (-) 1 (c) 11 (d) 12 Total 5 17 22

In Table 3, the crude OR for T2DM is estimated by obtaining a cross product ratio (ad/bc) 2×2 table and the calculation is shown in the following formula.

Crude OR Calculation

ad 4X11 44 OR = --- = ------= ---- = 7.3 bc 1X6 6

Results and Analysis

The summary of the case’s and control’s HLA typing data in Table 2 shows the mean age

of the cases to be 56 and the mean age of the controls to be 50 (male, 50% of the cases, and

58.3% of the controls; female = 50% of the cases, and 41.7% of the controls). These results were

obtained using SPSS v.15.0 software. The differences in frequency in the case and control groups

were tested using the chi-square test. The OR was calculated using Mantel Haenszel OR of HLA

A, B, C, DR, and DQ antigens. Typing was performed using serology technique and unclear

blank antigens were tested using PCR-SSP DNA methodology. As previously stated, a total of 10

cases and 12 controls were used for analysis. The detailed analysis of all subjects and HLA loci

are listed in Tables 4-8.

Table 4 SPSS Analysis of HLA-A locus antigens

Case (n=10) Control (n=12) Fisher Exact Mantel- (Chi-Square) Haenszel Antigens Frequencies Frequencies P-value OR A1 1 (10%) 2 (17%) 0.56 0.56 A2 2 (20%) 4 (33%) 0.41 0.53 A3 3 (30%) 1 (8%) 0.25 4.0 A11 1 (10%) 0 (0%) 0.46 N/A A23 0 (0%) 2 (17%) 0.28 N/A A24 4 (40%) 6 (50%) 0.46 0.71 A25 1 (10%) 2 (17%) 0.56 0.56 A31 2 (20%) 2 (17%) 0.64 1.18 A32 1 (10%) 0 (0%) 0.46 N/A A33 2 (20%) 0 (0%) 0.21 N/A A68 2 (20%) 3 (25%) 0.57 0.75

Table 5 SPSS Analysis of HLA-B locus antigens

Case (n=10) Control (n=12) Fisher Exact Mantel- (Chi-Square) Haenszel Antigens Frequencies Frequencies P-value OR B7 3 (30%) 1 (8%) 0.23 4.20 B8 1 (10%) 1 (8%) 0.70 1.23 B14 0 (0%) 1 (8%) 0.55 N/A B35 3 (30%) 4 (33%) 0.62 0.90 B37 0 (0%) 1 (8%) 0.55 N/A B38 0 (0%) 2 (17%) 0.30 N/A B39 3 (30%) 2 (17%) 0.40 2.00 B44 2 (20%) 0 (0%) 0.20 N/A B47 0 (0%) 1 (8%) 0.55 N/A B48 0 (0%) 3 (25%) 0.16 N/A B49 1 (10%) 0 (0%) 0.45 N/A B51 1 (10%) 2 (17%) 0.58 0.58 B61 2 (20%) 4 (33%) 0.44 0.56 B62 1 (10%) 0 (0%) 0.45 N/A B65 1 (10% 0 (0%) 0.45 N/A

Table 6 SPSS Analysis of HLA-C locus antigens

Case (n=10) Control (n=12) Fisher Exact Mantel- (Chi-Square) Haenszel

Antigens Frequencies Frequencies P-value OR C2 1 (10%) 0 (0%) 0.44 N/A C3 1 (10%) 4 (33%) 0.25 0.27 C4 1 (10%) 4 (33%) 0.25 0.27 C5 2 (20%) 0 (0%) 0.19 N/A C6 0 (0%) 1 (8%) 0.56 N/A C7 6 (60%) 4 (33%) 0.21 2.50 C8 1 (10%) 5 (42%) 0.15 0.20 C9 1 (10%) 1 (8%) 0.70 1.29

Table 7 SPSS Analysis of HLA-DR locus antigens

Case (n=10) Control (n=12) Fisher Exact Mantel- Haenszel (Chi-Square) Antigens Frequencies Frequencies P-value OR DR1 2 (20%) 1 (8.3%) 0.45 2.44 DR4 1 (10%) 4 (30%) 0.22 0.25 DR7 0 (0%) 1 (8.3%) 0.54 N/A DR8 4 (40%) 6 (50%) 0.46 0.53 DR9 1 (10%) 1 (8.3%) 0.72 1.22 DR10 0 (0%) 1 (8.3%) 0.54 N/A DR11 2 (20%) 1 (8.3%) 0.45 2.44 DR13 3 (30%) 3 (25%) 0.60 1.18 DR14 3 (30%) 3 (25%) 0.60 1.18 DR15 3 (30%) 1 (8.3%) 0.25 3.88 DR17 1 (10%) 1 (8.3%) 0.72 1.16

Table 8 SPSS Analysis of HLA-DQ locus antigens

Case (n=10) Control (n=12) Fisher Exact Mantel-Haenszel (Chi-Square) Antigens Frequencies Frequencies P-value OR DQ1 1 (10%) 2 (17%) 0.55 0.55 DQ2 3 (30%) 2 (17%) 0.43 1.85 DQ3 0 (0%) 2 (17%) 0.28 N/A DQ4 3 (30%) 7 (58%) 0.20 0.40 DQ5 2 (20%) 2 (17%) 0.64 1.17 DQ6 4 (40%) 1 (8%) 0.13 5.50 DQ7 5 (50%) 4 (33%) 0.41 1.58 DQ8 1 (10%) 2 (17%) 0.55 0.55 DQ9 1 (10%) 1 (8%) 0.72 1.16

The OR of the Class I HLA-A locus antigens ranges from 0.25-3.88 and p-value ranges from 0.21-0.64. The OR of the HLA-B locus antigen ranges from 0.56-4.2 and p-values were from 0.16-0.7. The OR of the HLA-C locus antigen ranges from 0.20-2.5 and p-value were from

0.15-0.7. Analysis of the Class II HLA-DR locus antigens yielded OR from 0.25-3.88 and p- values range from 0.22-0.72, whereas the OR for the HLA-DQ locus antigens ranged from 0.55-

5.5 and p-values were from 0.13-0.72. The crude OR and adjusted OR for HLA-DQ6 antigens

were 7.3 and 5.5, respectively; p-value was 0.13. The overall sample size (N= 10 cases and 12 controls) was too small to find a statistically significant OR risk at α = 0.05 p-value and power (1-

β) = 80% in two-sided hypothesis testing (Gordis, 2004). The results from this preliminary study provided information to support initial efforts to further explore the association of HLA antigens and alleles with T2DM among MA.

Research Design and Methods

Methodology of this case-controlled study was divided into two parts:

Part I of study involved historical serological HLA data derived from the Sierra Medical

Center, Transplant Immunology Laboratory. Part I focused on data analysis for HLA-A, B, C,

DR, and DQ antigens in association with T2DM. The data was analyzed using PROC LOGISTIC in the SAS software version 9.1 for Windows. Logistic regression was used to calculate crude and adjusted ORs for the association between HLA antigens, alleles and the binary outcome of

T2DM. The ORs were reported along with chi-square p-values.

Part II of the study involved 57 frozen samples for HLA DRB1*, DQA1*, and DQB1* alleles typing and was derived from a previous study conducted at The University of Texas at El

Paso. Additionally, 22 frozen samples were used HLA DRB1*, DQA1*, and DQB1* alleles typing and were derived from the Sierra Medical Center, El Paso, Texas.

Part I

The specific research design and methods are described in their sections. The clinical features of the two research questions cases and controls are listed in Table 9.

Table 9 Clinical features of the Case-Control (Questions #1 and 2)

Patients Group I Group II Group III (or) Case (T2DM) Control #1 (without Control #2 (without Controls T2DMand without T2DM with family (n=110) family history of history of T2DM) T2DM) (n=196) (n=24) Age Groups Frequencies (%) Frequencies (%) Frequencies (%) 21-30 0 (0%) 0 (0%) 10(41.5%) 31-40 1 (1%) 12 (6%) 5 (21%) 41-50 29 (26%) 116 (59%) 6 (25%) 51-60 47 (43%) 54 (27.5%) 3 (12.5%) 61-70 30 (27%) 13 (7%) 0 (0%) 71-80 3 (3%) 1 (0.5%) 0 (0%)

Research Question #1: What is the relationship between HLA Class I (HLA-A, HLA-B, and

HLA-C locus) antigens and T2DM among MA?

Research Design

The case-control as proposed consisted of HLA Class I typing data Group I: the HLA

Class I typing data with 110 MA with T2DM (cases). Group II: the control group #1 the HLA

Class I typing data with 196 MA without T2DM and without family history of T2DM. Group III:

the control group #2 the HLA Class I typing data with 24 MA without T2DM and with family

history of T2DM. The HLA Class I data were selected based on inclusion and exclusion criteria

for case and control. This study’s HLA Class I data was derived from the Sierra Medical Center,

Transplant Immunology Laboratory, El Paso, Texas with Institutional Review Board Approval

(Appendix I to M: IRB Net ID #84647-1).

Sample Size and Power

Table 10 Required sample size for an unmatched case-controlled study of the susceptible association with T2DM; assuming an equal number of cases and controls (1:1 ratio); a significance level of 0.05; power of 80%; and two-tailed testing (Source: CDC Epi Info 3.5.1)

Sample size calculation is for all three research questions:

least extreme OR case-controlled sample size n (per group) to be detected po = 20% po = 23% po = 25% po = 30% 1.5 562 514 490 446 2.0 186 172 165 153 2.5 105 97 94 88 3.0 72 68 65 62 3.5 55 52 51 48 4.0 45 43 42 40 4.5 38 36 36 35 5.0 33 32 31 31 5.5 30 29 28 28 6.0 27 26 26 26

Po = the proportion of exposure among controls.

Table 10 represents the sample size was calculated for susceptible antigens/alleles

required for a case-controlled study with varying expected rates of exposure among controls, po, α

= 0.05 and β = 0.20 (power=80%). These sample sizes are required for varying expected rates of

exposure among controls as well as varying least extreme OR to be detected. These sample sizes

are the minimum estimate of the desired sample sizes, because they do not take into account

possible confounding and/or effect modification (interaction).

Table 11 Required sample size for an unmatched case-controlled study of the protective association without T2DM; assuming an equal number of cases and controls (1:1 ratio); a significance level of 0.05; power of 80%; and two-tailed testing (Source: CDC Epi Info 3.5.1).

Sample size calculation is for all three research questions:

least extreme OR case-controlled sample size n (per group) to be detected po = 20% po = 23% po = 25% po = 30% 0.01 45 38 35 28 0.02 46 40 36 29 0.05 51 44 40 33 0.1 60 52 48 39 0.15 71 62 57 47 0.2 85 74 68 57 0.25 101 88 82 69 0.3 122 107 99 84 0.35 148 130 120 102 0.4 181 159 148 127 0.45 224 198 184 159 0.5 282 250 233 201 0.55 361 321 300 260 0.6 475 423 395 344

Po = the proportion of exposure among controls.

Table 11 represents the sample size was calculated for protective antigens/alleles required

for a case-controlled study with varying expected rates of exposure among controls, po, α = 0.05

and β = 0.20 (power=80%). These sample sizes are required for varying expected rates of

exposure among controls as well as varying least extreme OR to be detected. These sample sizes

are the minimum estimate of the desired sample sizes, because they do not take into account possible confounding and/or effect modification (interaction).

Protection of Human Subjects – IRB

Research question #1 of the study involved the HLA Class I antigens typing data collected from 1992 to 2007. This data set came from the archived database of Sierra Medical Center

Transplant Immunology Laboratory with Institutional Review Board Approval (see Appendix I to

M: IRB Net ID #84647-1). All HLA Class I antigen samples were kept secure during the study and will be secured for a period of 5 years after the study. Sample data subject names were not available or linked with sample data identification throughout the study.

Inclusion/Exclusion Criteria for acceptance

The HLA Class I typing antigens’ data were selected based on the inclusion and exclusion criteria described as follows:

Inclusion

(1) Age: 21 to 80 years; (2) BMI: <39; (3) Mexican origin or Mexican descendent with

both parents of Mexican origin/descent; (4) male or female; and (5) with T2DM

Exclusion

(1) Age: <21 and or >80 years; (2) active malignancy or infection; (3) active hepatitis

B or C; (4) ongoing substance abuse; (5) intractable cardiac disease; (6) intractable

vascular disease; (7) intractable pulmonary disease; (8) acute MI within 6 months; (9)

morbid obesity; (10) HIV/AIDS; (11) chronic gastrointestinal disease; (12) life

expectancy less than 3 years; and/or (13) active psychosis.

Research Methodology

Viable T cells were incubated with a complement-binding antibody. The expression of T cells (antigen) will be recognized by the specific antibody; the Fab (antigen-binding fragment) portion of the antibody binds to the antigen forming antigen-antibody complex. After these complexes have formed, rabbit complement is added. The C1q and Ca++ form the complement that will bind to the Fc (crystallizable fragment) portion of the antibody. One IgM antibody is required to bind one molecule of C1q or two IgG antibodies are required to bind one molecule of

C1q that was bound with antigen-antibody complexes to initiate the complement cascade that leads to cell lysis. The T cells were alive in a negative reaction; whereas a positive reaction was comprised of dead T cells (One Lambda, Inc. HLA Class I antigens, Product Insert, 2004).

The HLA-PCR-SSP-DNA technique is based on the principle that completely matched oligonucleotide primers are more efficiently used in amplifying target sequence than a mismatched oligonucleotide primer by recombinant Taq polymerase. Primer pairs are designed to have perfect matches only with a single allele or group of alleles. Under strictly controlled PCR conditions, perfectly matched primer pairs result in the amplification of target sequences (a positive result), whereas mismatched primer pairs do not result in amplification (a negative result). After the PCR process, the amplified DNA fragments are separated by agarose gel electrophoresis and visualized by staining with ethidium bromide and exposure to ultraviolet light

(One Lambda, Inc., Micro-SSP HLA DNA Class II Typing, Product Insert, 2004).

The HLA Class I (HLA-A, HLA-B, and HLA-C locus) typing were performed using serology technique (Dynal Biotech Inc. Dynalbeads HLA Cell Prep I, Product Insert, 2004; One

Lambda, Inc. Terasaki HLA Tissue Typing Trays, HLA Class I antigens, Product Insert, 2004) and unclear antigens were confirmed by a low resolution Micro-SSP HLA-DNA typing technique

(Gentra Puregene DNA Isolation System Kit Product Insert, 2002; One Lambda, Inc., Micro-SSP

HLA DNA Typing Tray of Class I HLA Alleles, Product Insert, 2004). The HLA typing of recipients, living related donors, deceased donors, and volunteer donors has been performed for the kidney transplant.

Limitations

The limitation of this study consists of the HLA Class I typing data from the kidney transplant program at Sierra Medical Center as kidney transplant recipients; kidney transplant living donors; kidney transplant disease donors, or volunteer donors for quality control purposes.

Also the serology typing method optimum typing yields are dependent on the proper expression of the target antigen on the surface of the cell. (The list of Class I antigens that are identified in the study are provided in greater detail in Appendix C)

Statistical Analysis

Logistic regression was used to calculate crude and adjusted OR for diabetes, the binary outcome. The data were analyzed using PROC LOGISTIC in the SAS software version 9.1 for

Windows (Allison, 2001). The dichotomous outcome was T2DM. The three main exposure variables of interest were the susceptible (HLA- A, HLA-B, or HLA-C locus) antigens and protective (HLA- A, HLA-B, or HLA-C locus) antigens. It was hypothesized that the presence of susceptible (HLA- A, HLA-B, or HLA-C locus) antigens would increase the risk of developing

T2DM, whereas protective (HLA- A, HLA-B, or HLA-C locus) antigens would reduce the risk.

0.20; Mickey and Greenland (1989) showed that by using Monte Carlo simulations, this type of significance testing method can perform acceptably in selecting confounders if the significance level is set much higher than conventional levels (for example, 0.20 or greater). The method employed agrees with the change-in-estimate method, which is popular among epidemiologists, as long as the alpha is 0.20 or higher (Mickey & Greenland, 1989; Greenland, 1989). The change-in-estimate method does not rely on p-values, but rather on the change in the OR associated with the exposure of interest as one or more variables are added to the model

(Greenland, 1989). Crude and adjusted ORs (Gordis, 2004; Epi Info, 2007) were reported along with 95% confidence intervals for the population ORs (see shell table). The HLA Class I antigens

ORs will be considered to be statistically significant at the 0.05-level if the confidence interval excludes the null value of 1.

Case-Control Group A

This is a case-controlled HLA Class I typing of 306 cases [of which 110 have T2DM and

196 do not have T2DM (control without family history of T2DM)]. Assuming a 50% difference

(Perez-Luque, Malacara, Olivo-Diaz, Alaez, Debaz, & Vazquez-Garcia, et al., 2000; Perez-

Luque, Alaez, Malacara, Garay, Fajardo, Nava, et al., 2003; Patel, Preliminary Study, 2007) in

T2DM and a 25% difference in control related T2DM patients (46% T2DM patients, 23% control unrelated to T2DM) exists between T2DM subjects and control subjects, the minimum sample size (n=136) would allow an 80% chance of detecting a difference at the usual level of statistical significance (P ≤ 0.05). The sample size, power, and OR calculation were derived from Epi Info statistical analysis software (sample size calculation, see table #10 and #11).

Case-Control Group B

This is a case-controlled HLA Class I typing of 134 cases, of which 110 have T2DM and

24 do not have T2DM (control family with history of T2DM). Assuming a 50% difference

(Perez-Luque, Malacara, Olivo-Diaz, Alaez, Debaz, & Vazquez-Garcia, et al., 2000; Perez-

Luque, Alaez, Malacara, Garay, Fajardo, Nava, et al., 2003; Patel, Preliminary Study, 2007) in

T2DM and a 25% difference in control related T2DM patients (46% T2DM patients 34.5% control related to T2DM) exists between T2DM sample typing data and control sample typing data, the minimum sample size (n=136) would allow an 80% chance of detecting a difference at the usual level of statistical significance (P ≤ 0.05). The sample size, power, and the OR calculation were derived from Epi Info statistical analysis software (sample size calculation, see table #10 and #11).

Research Question #2: What is the relationship between HLA Class II (HLA-DR and HLA-DQ locus) antigens and T2DM among MA?

Research Design

The case-control as proposed consisted of HLA Class II typing data Group I: the HLA

Class II typing data with 110 MA with T2DM (cases). Group II: the control group #1 the HLA

Class II typing data with 196 MA without T2DM and without family history of T2DM. Group III: the control group #2 the HLA Class II typing data with 24 MA without T2DM and with family history of T2DM. The HLA Class II data was selected based on inclusion and exclusion criteria for case and control. The study’s HLA Class II data were derived from the Sierra Medical Center,

Transplant Immunology Laboratory, El Paso, Texas, with Institutional Review Board Approval

(see Appendix I to M: IRB Net ID #84647-1).

Protection of Human Subjects – IRB

Research question #2 of the study involved the HLA Class II antigens typing data collected from 1992 to 2007. This data set was derived from the archived database of the Sierra

Medical Center Transplant Immunology Laboratory with Institutional Review Board Approval

(see Appendix I to M: IRB Net ID #84647-1). All of the samples’ HLA Class II antigen data identification was kept secure during the study and will be kept secure after the completion of the study for 5 years. Sample data subject names were not available or linked with sample data identification throughout the study.

Inclusion/Exclusion Criteria for Acceptance

HLA Class II typing antigens’ data selected were based on the inclusion and exclusion criteria described as follows:

Inclusion:

(1) Age: 21 to 80 years; (2) BMI: <39; (3) Mexican origin or Mexican descendent with

both parents of Mexican origin/descent; (4) male or female; and (5) With T2DM.

Exclusion:

(1) Age: <21 and or >80 years; (2) active malignancy or infection; (3) active hepatitis B or

C; (4) ongoing substance abuse; (5) intractable cardiac disease; (6) intractable vascular

disease; (7) intractable pulmonary disease; (8) acute MI within 6 months; (9) morbid

obesity; (10) HIV/AIDS; (11) chronic Gastrointestinal disease; (12) life expectancy less

than 3 years; and (13) active psychosis.

Research Methodology

Viable B cells were incubated with complement-binding antibody. The expression of B cells (antigen) will be recognized by a specific antibody, the Fab (antigen-binding fragment)

portion of the antibody binds to the antigen forming antigen-antibody complex. After these complexes have formed, rabbit complement is added. The C1q and Ca++ form the complement bind to the Fc (crystallizable fragment) portion of the antibody. One IgM antibody is required to bind one molecule of C1q or two IgG antibodies are required to bind one molecule of C1q that was bound with antigen-antibody complexes initiates the complement cascade that leads to cell lysis. The B cells were alive in a negative reaction; whereas a positive reaction was comprised of the dead B cells (One Lambda, Inc. HLA Class II antigens, Product Insert, 2004).

(One Lambda, Inc., Micro-SSP HLA DNA Class II Typing, Product Insert, 2004).

The HLA Class II (HLA-DR and HLA-DQ locus) typing were performed using a serology technique (Dynal Biotech Inc. Dynalbeads HLA Cell Prep II, Product Insert, 2004; One Lambda,

Inc. Terasaki HLA Tissue Typing Trays, HLA Class II antigens, Product Insert, 2004) and confirmed by a low resolution HLA-PCR-SSP-DNA technique (Gentra Puregene DNA Isolation

System Kit Product Insert, 2002; One Lambda, Inc., Micro-SSP HLA DNA Typing Tray of Class

II HLA Alleles, Product Insert, 2004). The typing of recipients, living related donors, deceased donors, and volunteer donors has been performed for the kidney transplant.

Limitations

The limitation of this study consists of the HLA Class II typing data from the kidney transplant program at the Sierra Medical Center as kidney transplant recipients; kidney transplant living donors; kidney transplant disease donors, or volunteer donors for quality control purposes.

Also, the serology typing method optimum typing yields are dependent on proper expression of the target antigen on the surface of the cell. (The list of Class II antigens that are identified in the study is provided in greater detail in the Appendix K).

Statistical Analysis

Logistic regression was used to calculate crude and adjusted OR for T2DM, the binary outcome. The data were analyzed using PROC LOGISTIC in the SAS software version 9.1 for

Windows (Allison, 2001). The dichotomous outcome is T2DM. The three main exposure variables of interest are the susceptible (HLA- DR and HLA-DQ locus) antigens and protective

(HLA- DR and HLA-DQ locus) antigens. It was hypothesized that the presence of susceptible

(HLA- DR and HLA-DQ locus) antigens will increase the risk of developing T2DM, whereas protective (HLA- DR and HLA-DQ locus) antigens will reduce the risk.

The following variables were considered potential confounders of the association under study: age (a continuous variable), sex (a categorical), and family history of diabetes. The exposure variable of interest, the term composed of the two HLA Class II antigens was forced into the model, while the significance level for potential confounders that remained in the model was 0.20. Mickey and Greenland (1989) have shown by using Monte Carlo simulations that this type of significance testing method can perform acceptably in selecting confounders if the significance level is set much higher than conventional levels (for example, 0.20 or greater). The method that was employed generally agreed with the change-in-estimate method, which is

popular among epidemiologists, as long as the alpha is 0.20 or higher (Mickey & Greenland,

1989; Greenland, 1989). The change-in-estimate method does not rely on p-values, but rather on the change in the OR associated with the exposure of interest as one or more variables are added to the model (Greenland, 1989). Crude and adjusted OR (Gordis, 2004; Epi Info, 2007) were reported along with 95% confidence intervals for the population ORs (see shell table). The HLA

Class II antigens ORs were considered to be statistically significant at the 0.05-level if the confidence interval excludes the null value of 1.

Case-Control Group A

This is a case-controlled HLA Class II typing of 306 cases [of which 110 have T2DM and

196 do not have T2DM (control without family history of T2DM)]. Assuming a 50% difference

(Perez-Luque, Malacara, Olivo-Diaz, Alaez, Debaz, & Vazquez-Garcia, et al., 2000; Perez-

Luque, Alaez, Malacara, Garay, Fajardo, Nava, et al., 2003; Patel, Preliminary Study, 2007) in

T2DM and a 25% difference in control related T2DM patients (46% T2DM patient, 23% control unrelated to T2DM) exists between T2DM samples and control samples, the minimum sample size (n=136) would allow an 80% chance of detecting a difference at the usual level of statistical significance (P ≤ 0.05). The sample size, power, and OR calculation were derived from Epi Info statistical analysis software (sample size calculation, see table #10 and #11).

Case-Control Group B

This is a case-controlled HLA Class II typing of 134 cases [of which 110 have T2DM and

24 do not have T2DM (control with family history of T2DM)]. Assuming a 50% difference

(Perez-Luque, Malacara, Olivo-Diaz, Alaez, Debaz, & Vazquez-Garcia, et al., 2000; Perez-

Luque, Alaez, Malacara, Garay, Fajardo, Nava, et al., 2003; Patel, Preliminary Study, 2007) in

T2DM and a 25% difference in control related T2DM patients (46% T2DM patient 34.5% control

related to T2DM) exists between T2DM samples and control samples, the minimum sample size

(n=136) would allow an 80% chance of detecting a difference at the usual level of statistical significance (P ≤ 0.05). The sample size, power, and OR calculation were derived from Epi Info statistical analysis software (sample size calculation, see table #12 and #13).

Part II

Research Question #3: What is the relationship between specific HLA Class II (HLA- DRB1*,

HLA-DQA1*, HLA-DQB1* locus) alleles and T2DM among MA?

The research question #3 consisted of two sets of samples:

Research Design (Set #1)

The case-controlled study design consisted of 28 cases of frozen samples with T2DM and their past exposure to suspected etiological factors was compared with that of 29 controls of frozen samples that do not have T2DM using inclusion and exclusion criteria for the cases and controls. The study was conducted with permission from Dr. Martinez to use the samples and demographic information derived from (IRB Research Protocol #2454, Appendix: N and O) Title

“A Pilot Study to Examine the Presence of Apolipoprotein E Polymorphism among Mexican

Americans with and without T2DM in the El Paso Region.” The frozen samples were included with the second set for sample size, power, and statistical analysis calculation. The HLA Class II

Alleles typing was performed at the Las Palmas Medical Center Histocompatibility and

Immunogenetics Laboratory, El Paso, Texas.

The (cases) frozen samples of 28 MA diagnosed with T2DM and the (control) frozen samples of 29 MA without T2DM and without family history of T2DM.

Protection of Human Subjects–IRB (Set #1)

This study involved approximately 28 cases (T2DM) of frozen samples and 29 frozen samples used as controls (without T2DM and without family history of T2DM), which were derived from a study conducted by Dr. Nelda C. Martinez, Associate Professor, School of

Nursing, University of Texas at El Paso; Dr. Martinez’s study was approved by the Institutional

Review Board (IRB Research Protocol #2454, Appendix: N and O). Demographic information was requested for analysis. Following attainment of access and use of these samples, a formal request was submitted to the UTEP IRB for approval; this request accompanied the formal dissertation proposal regarding the HLA-DNA alleles testing. Following IRB approval, the HLA-

DNA alleles testing and analysis of the HLA-DNA alleles was performed at the Las Palmas

Medical Center. All samples in HLA Class II alleles’ data identification were kept secure during the study and after completion of study. Sample data subject names were not available or linked with sample data identification throughout the study.

Inclusion/Exclusion Criteria for Acceptance (Set #1)

This study of frozen samples selected was based on the inclusion and exclusion criteria described as follows:

Inclusion criteria (1) Age: 40 to 75 years; (2) Mexican origin or Mexican descendent, with both parents of

Mexican origin/descent; (3) male or female; and (4) diagnosis for T2DM in accordance

with criteria outlined by Expert Committee of American Diabetes Association.

Exclusion criteria (1) Age: <40 years and/or >75 years; (2) clinical or known history of cerebral vascular

disease; (3) history of coronary artery disease or myocardial infarct; and (4) not Mexican

origin.

Research Design (Set #2)

The case-controlled study design that consisted of 10 cases of frozen samples with T2DM and their past exposure to suspected etiological factors was compared with that of 12 controls of frozen samples that do not have T2DM. The frozen samples will be selected based on inclusion and exclusion criteria for case and control. The study’s frozen samples were derived from the

Sierra Medical Center, Transplant Immunology Laboratory, El Paso, Texas with Institutional

Review Board Approval (Appendix I to M: IRB Net ID #84647-1).

Table 12 Clinical features of the Case-Control (Question #3)

Subjects Group I Group II Case (T2DM) (n=38) Control (without T2DM and without family history of T2DM) (n=41) Age Groups Frequencies (%) Frequencies (%) 41-50 2 (5.26%) 10 (24.39%) 51-60 5 (13.16%) 8 (19.51%) 61-70 8 (21.05%) 14 (34.15%) 71-80 23 (60.53%) 9 (21.95%)

Table 12 shows the summary of clinical features of the cases and controls set #1 and #2 to age groups, frequencies, and percentages.

Protection of Human Subjects – IRB (Set #2)

This study involved 22 frozen samples collected from 1992 to 2007. These frozen samples were derived from the Sierra Medical Center Transplant Immunology Laboratory with

Institutional Review Board Approval (See Appendix I to M: IRB Net ID #84647-1). All samples of ‘HLA Class II alleles’ identification were kept secure during the study and after its completion.

Sample data subject names were not available or linked with sample data identification throughout the study.

Inclusion/Exclusion Criteria for Acceptance (Set #2)

This set consists of 22 frozen samples, they based on the inclusion and exclusion criteria described as follows:

Inclusion:

(1) Age: 40 to 80 years; (2) BMI: <39; (3) Mexican origin or Mexican descendent with

either parents of Mexican origin/descent; and (4) male or female (7) With T2DM.

Exclusion:

(1) Age: <40 and or >80 years; (2) active malignancy or infection; (3) active hepatitis B or

C; (4) ongoing substance abuse; (5) intractable cardiac disease; (6) intractable vascular

disease; (7) intractable pulmonary disease; (8) acute MI within 6 months; (9) morbid

obesity; (10) HIV/AIDS; (11) chronic Gastrointestinal disease; (12) life expectancy less

than 3 years; and (13) active psychosis.

In this case-controlled portion of the study (Set #1), 57 frozen samples were used (of which 28 have T2DM and 29 did not have T2DM). For Set #2, also case-controlled, 22 frozen samples were used (10 of which were T2DM cases and 12 did not have T2DM. Assuming a 50% difference (Perez-Luque, Malacara, Olivo-Diaz, Alaez, Debaz, & Vazquez-Garcia, et al., 2000;

Perez-Luque, Alaez, Malacara, Garay, Fajardo, Nava, et al., 2003; Patel, Preliminary Study,

2007) in T2DM and a 25% difference in control related T2DM patients (46% T2DM patient, 23% control unrelated to T2DM) exists between T2DM subjects and control subjects, the minimum sample size (n=80) would allow an 80% chance of detecting a difference at the usual level of statistical significance (P ≤ 0.05). The sample size, power, and OR calculation were derived from

Epi Info statistical analysis software (sample size calculation, see table #10 and #11).

In this case-controlled portion of the study (Set #1), 57 frozen samples were used (of which 28 were T2DM and 29 did not have T2DM). Set #2 was also case-control and involved 22 frozen samples, 10 of which had T2DM and 12 did not. Assuming a 50% difference (Perez-

Luque, Malacara, Olivo-Diaz, Alaez, Debaz, & Vazquez-Garcia, et al., 2000; Perez-Luque, Alaez,

Malacara, Garay, Fajardo, Nava, et al., 2003; Patel, Preliminary Study, 2007) in T2DM and a

25% difference in control related T2DM patients (46% T2DM patients, 23% control unrelated to

T2DM) exists between T2DM subjects and control subjects, the minimum sample size (n=80) would allow an 80% chance of detecting a difference at the usual level of statistical significance

(P ≤ 0.05). The sample size, power, and OR calculation were derived from Epi Info statistical analysis software (sample size calculation, see table #10 and #11).

Research Methodology

The present study included two sets of frozen samples to perform medium to high resolution Class II (HLA-DRB1*, HLA-DQA1*, and HLA-DQB1* locus) typing by the

LABType reverse sequence specific oligonucleotide (rSSO) using the Luminex technology.

Luminex Technology allows for the simultaneous measurement (multiplexing) of multiple analytes in a single reaction well. The Luminex 200 IS system consists of three core components: the first is the microspheres, 100 groups of highly uniform polystyrene particles with varying amounts of fluorochrome that are embedded within the microsphere resulting in a unique fluorescent signal for each group; the second component is a flow-based analyzer containing two lasers, one to classify each microsphere and the second to quantify the fluorescently labeled reporter molecule bond to the surface of the microsphere; the third component is the software that is designed for template-based data acquisition and provides analysis of the microspheres as they are processed through the analyzer.

The rSSO system is based on the hybridization of a labeled single-stranded polymerase chain reaction (PCR) product to SSO probes. Target DNA is amplified by PCR using group specific Class I and Class II primers. The PCR product is biotinylated, which allows detection by

R-Phycoerythrin-conjugated Strepavidin (SAPE). The PCR product is denatured and allowed to re-hybridize to complementary DNA probes conjugated to fluorescently coded microbeads. A flow analyzer, the LABScan 200, identifies the fluorescent intensity of Phycoerythrin on each bead. The assignment of the HLA typing is done with a LABType software program and is based on the reaction pattern compared to patterns associated with published HLA gene sequences.

The microsphere mixture consists of a set of fluorescently labeled microspheres that bear unique sequence-specific oligonucleotide probes for HLA Class II alleles. Each microsphere mixture includes negative and positive control probes that bear microspheres for subtraction of non-specific background signals and normalization of raw data to adjust for possible variation in sample quantity and reaction efficiency.

DNA Extraction Procedure

Frozen buffy coat samples were used for DNA extraction. Genomic DNA was extracted and purified using the Puregene Isolation kit by Gentra System, Minneapolis, MN, and QIAamp

DNA purification from a buffy coat mini kit by QIAGEN, Valencia, CA. DNA purity was assessed spectrophotometrically (A260/A280 ratio). DNA concentration was adjusted to 25 to 70 ng/µl. DNA samples was stored at 4°C. Frozen samples (buffy coats) or frozen lymphocytes were used to extract DNA. All pre-DNA procedures were performed in the Biological Safety Hood.

Figure 9 lists steps which were used for frozen samples for DNA extraction.

Summary of DNA Extraction Step

Frozen cells, blood, or buffy coat sample

↓

Lysis of erythrocytes by Osmotic (NH4Cl)

↓

Lysis of nucleated cells and nuclei by detergents and proteolytic enzymes

↓

Separation of DNA from proteins by 2-Propanol

↓

Purification of DNA from solution by precipitation

↓

DNA hydration at 63°C

↓

Adjust to 25-50 ng/µl for rSSO method.

Figure 9 Summary of DNA Extraction Step

LABType (rSSO) Class II Alleles Typing Procedure

DNA samples were obtained as previously discussed. The concentration of DNA used for rSSO methodology was between 25 and 50 ng/µl. The polymorphic Exon 2 and Exon 3 were amplified for the Class II (HLA-DRB1*, HLA-DQA1*, and HLA- DQB1* locus) by PCR. The

HLA DRB1*, DQA1*, and DQB1* bead probe sequence alleles and protocol were used from the product insert provided by One Lambda Inc., Canoga Park, CA, and the HLA alleles are listed in

Appendix E.

HLA Class II alleles typing were performed using LABType rSSO typing technique (One

Lambda, Inc. LABType rSSO typing Test Rev. 11A: DNA typing of High Definition (HD) Class

II Alleles, Products Insert, 2006). GoTaq Flexi DNA Polymerase Taq used from Promega

Corporation, Product Insert, Madison, WI.

Summary of LABType rSSO Typing Step

Amplification step consists of D-Mix, primer and Taq polymerase

↓

Amplify sample using PCR program

↓

Denaturation/neutralization in 96-well PCR tray mix denaturation buffer &

amplified DNA.

↓

Bead mixture and hybridization buffer vortex in 96-well PCR tray at 60ºC

thermocycler.

↓

Labeling 1X SAPE and incubate at 60ºC in thermocycler ↓

Ready to data acquisition in Luminex- 200.

Figure 10 Summary of LABType rSSO Typing Step

Table 13 Amplification mixture for three reactions

# of reactions D-Mix µl Primer µl Taq Polymerase µl 1 13.8 4 0.2 2 27.6 8 0.4 3 41.4 12 0.6

Table 13 shows the amplification mixture amounts for three reactions (for two alleles)

Data Acquisition- Sample reading in the Luminex-200: The instrument was

calibrated using the manufacture’s guidelines. A file name was created for the sample runs. The

sample ID was entered, the plate was loaded on the XY platform, and the reservoir with sheath

fluid was filled. The instrument was started by clicking on the START button to initiate the

session. After the samples were run, the output file was saved in a .csv file.

Expected outcomes: The fluorescence intensity (FI) generated by the Luminex

Data Collector software contains the FI for each bead (or probe bond to the bead) per

sample. The percent positive value was calculated using following formula:

Percent Positive Value = 100X [ FI (Probe n) – FI (Probe Negative Control)/ (Probe Positive Control)-FI(Probe Negative Control)]

The positive reaction was defined by the percent of positive values for probes higher than

the pre-set cut-off value for the probe. The negative reaction was defined as the percent of

positive values lower than the cut-off value. The HLA Class II alleles of the sample were

determined by matching patterns of positive and negative bead IDs with the information in the

LABType SSO worksheet (see Appendices J-L for list of known alleles). Figure 9 depicts the

summary of steps of LABType rSSO procedure using LABScan-200 (Luminex–200).

LABType® Procedure

1. Denaturation (10 min.) & Neutralization 2. Add Beads

3. Hybridization 7. Read (15min. at 60ºC) Amplification (90 min.)

6. Wash Step 4. Wash Step • Add Wash Buffer 5. Add SAPE • Vortex • Spin (5 min. at 60ºC) • Remove sup.

Figure 9 LAB type rSSO procedures (Harrell & Muradyan’s Presentation, 2008)

Limitations

The limitation in this study consists of the frozen samples that were obtained from two sets: Set #1 consisted of 28 cases and 29 controls from Dr. Martinez’s APO-E study and Set #2 consisted of 22 frozen samples of the participants in the kidney transplant program at Sierra

Medical Center, El Paso, TX. The LABType rSSO system combines an HLA locus-specific DNA amplification process and DNA-DNA hybridization process. The procedure, as well as the equipment calibration described in this product, must be strictly followed. In comparison of other

assays like HLA-DNA-SSP, the rSSO has more ambiguities because the probes used in rSSO can discriminate sample DNA at only one region per test, and SSP can discriminate sample DNA at two regions per test. This is a basic limitation of the rSSO method. The list of Class II alleles that are identified in the study is provided in greater detail in the Appendix E.

Statistical Analysis

Logistic regression was used to calculate crude and adjusted OR for T2DM, the binary outcome. The data was analyzed using PROC LOGISTIC in the SAS software version 9.1 for

Windows (Allison, 2001). The two main exposure variables of interest were the susceptible and protective Class II (HLA-DRB1*, HLA-DQB1*, HLA-DQA1*) alleles. It was hypothesized that the presence of susceptible (Class II alleles) alleles would increase the risk of developing T2DM, whereas protective (Class II alleles) alleles would reduce the risk.

The following variables were considered potential confounders of the association under study: age (a continuous variable), sex (a categorical), demographic factors, and family history of diabetes. The exposure variable of interest, the term composed of the two HLA II alleles described earlier, was forced into the model, while the significance level for potential confounders to remain in the model was 0.20. Mickey and Greenland (1989) have shown that by using Monte

Carlo simulations, this type of significance testing method can perform acceptably in selecting confounders if the significance level is set much higher than conventional levels (for example,

0.20 or greater). The method that was employed generally agrees with the change-in-estimate method, which is popular among epidemiologists, as long as the alpha is 0.20 or higher (Mickey

& Greenland, 1989; Greenland, 1989). The change-in-estimate method does not rely on p-values, but rather on the change in the OR associated with the exposure of interest as one or more variables are added to the model (Greenland, 1989). Crude and adjusted OR (Gordis, 2004; Epi

Info, 2007) was reported along with 95% confidence intervals for the population ORs. The HLA

II allele’s ORs was considered to be statistically significant at the 0.05-level if the confidence interval excludes the null value of 1.

In Set 1, 57 frozen samples were used (of which 28 were T2DM cases and 29 did not have T2DM). Set 2: In this case-controlled portion of the study, 22 frozen samples were used

(10 of which were T2DM cases and 12 were not). Assuming a 50% difference (Perez-Luque,

Malacara, Olivo-Diaz, Alaez, Debaz, & Vazquez-Garcia, et al., 2000; Perez-Luque, Alaez,

Malacara, Garay, Fajardo, Nava, et al., 2003; Patel, Preliminary Study, 2007) in T2DM and a

25% difference in control related T2DM patients (46% T2DM patients, 23% control unrelated to

T2DM) exists between T2DM subjects and control subjects, the minimum sample size (n=80) would allow an 80% chance of detecting a difference at the usual level of statistical significance

(P ≤ 0.05). The sample size, power, and OR calculation were derived from Epi Info statistical analysis software (sample size calculation, see table #10 and #11).

Summary

This section outlines the serological and molecular typing methods used to type the subjects. Details of the test methods and their scope, as well as limitations and precautions to be observed are described in detail. The statistical methods used in the data analysis are also outlined.

Results

Part I of the study data was derived from 330 Mexican-American subjects (110 cases and

196 controls #1 and 24 Control #2) and part II of study data was derived from Mexican-

Americans subjects (38 cases and 41 controls). Both serologic and molecular methods were used to study the subjects. The data was analyzed using PROC LOGISTIC in the SAS software version

9.1 for Windows. Logistic regressions were used to calculate crude OR and adjusted OR with age and sex, chi-square, or Fisher’s Exact Test P-value calculated with the binary outcome for T2DM for Class I (HLA- A, HLA-B, HLA-C) Class II (HLA- DR, DQ) antigens (Part I) and Class II

(DRB1*, DQA1*, DQB1*) alleles (Part II). This OR will provide information regarding HLA associated with T2DM among MA.

This study consists of three research questions divided in to two parts: Part I: Consists of serological analysis, addressed into two questions.

Research Question #1: What is the relationship between HLA Class I (HLA-A, HLA-B and HLA-C locus) antigens and T2DM among MA?

This was addressed using serological Class I (HLA-A, B, C locus) antigens typing. Whenever possible, the unclear HLA antigens typing for Class I was confirmed by Sequence Specific

Primers (SSP). The comparison was between the following: One hundred and ten cases with

T2DM and 196 controls #1 without family history of T2DM (Case-Control Group A) and 110 cases and 24 controls #2 with family history of T2DM (Case-Control Group B).

Case-Control Group A (Case-Control #1)

Table 14 Clinical features of the Case (T2DM)-Control #1 (without T2DM and without family history of T2DM)

Patients Case (T2DM) (n=110) Control #1 (without T2DM and (or) without family history T2DM) Controls (n=196)

Age Groups Frequencies (%) Frequencies (%) 21-30 0 (0%) 0 (0%) 31-40 1 (1%) 12 (6%) 41-50 29 (27%) 116 (59%) 51-60 47 (43%) 54 (27.5%) 61-70 30 (27%) 13 (7%) 71-80 3 (3%) 1 (0.5%)

Table 14 summarizes the clinical features of the case (T2DM)-control #1 with regard to age groups, frequencies, and percentages. Age group 21-30: case = 0 (0%) and control #1 = 0

(0%). Age group 31-40: case = 1(1%) and control #1 = 12 (6%). Age group 41-50: case = 29

(27%) and control #1 = 116 (59%). Age group 51-60: case = 47 (43%) and control #1 = 54

(27.5%). Age group 61-70: case = 30 (27%) and control#1 = 13 (7%). Age group 71-80: case = 3

(3%) and control #1 = 1(0.5%).

Table 15 Demographic data of Case (T2DM)-Control #1 (without T2DM and without family history of T2DM)

Case (T2DM) (n=110) Control #1 (without T2DM and without family history of T2DM (n=196)

Age Mean 55.66 48.68 Age SD 7.72 6.79 Male 76 (69%) 86 (44%) Female 34 (31%) 110 (56%) Race (MA) 100% 100%

Table 15 shows the summary of patients and normal controls: The mean age of

the patients was 55.66 years with a standard deviation (SD) of ± 7.72, and for the controls, the mean age was 48.68 years with a SD of ± 6.79. The male to female frequencies vary between the cases and the controls (69% male and 31% female in cases and 44% male and 56% female in controls)

Table 16 SAS Analysis of HLA-A antigens: Case (T2DM)-Control #1 (without family history and without T2DM) 1 of 2

HLA- A Case Control Crude OR Chi-Square or OR Adjusted 95% Confidence Chi-Square Locus (n=110) (n=196) Fisher’s for Age and Interval for Age or Fisher’s Exact Test* Sex and Sex Exact Test* Antigens Frequencies Frequencies OR P-value OR OR P-value A1 20 (18%) 28 (14%) 1.3 0.36 1.12 0.55-2.28 0.763 A2 52 (47%) 84 (43%) 1.2 0.46 1.2 0.71-2.05 0.491 A3 9 (8.5%) 33 (17%) 0.44 0.03 0.39 0.16-0.96 0.041 A11 8 (7.5%) 22 (11%) 0.62 0.26 0.67 0.25-1.78 0.424 A23 5 (5%) 14 (7%) 0.61 0.36 0.43 0.14-1.34 0.146 A24 31 (28%) 55 (28%) 1 0.98 1.07 0.59-1.93 0.827 A25 2 (2%) 8 (4%) 0.43 *0.34 0.71 0.13-3.94 0.697 A26 5 (5%) 12 (6%) 0.73 0.56 0.68 0.19-2.35 0.537 A28 6 (6%) 5 (3%) 2.2 *0.29 1.49 0.33-6.70 0.607 A29 8 (7.5%) 11 (6%) 1.3 0.56 1.91 0.69-5.33 0.214 A30 10 (9.5%) 18 (9%) 0.99 0.97 1.24 0.51-3.00 0.638 A31 15 (14%) 26 (13%) 1.03 0.92 1.02 0.47-2.20 0.97 A32 5 (5%) 10 (5%) 0.89 0.83 0.82 0.24-2.80 0.75 A33 6 (6%) 6 (3%) 1.83 *0.36 1.90 0.55-6.65 0.313 A34 1 (1%) 2 (1%) 0.89 *1.0 1.06 0.08-14.35 0.965

*25%-50% of the antigens have expected counts less than 5; Fisher’s Exact Test Two-sided P-value was used. ** Quasi-complete separation of data points detected. Validity of the model fit is questionable. *** One or more risk estimates not computed ….. Zero cell.

Table 16 SAS Analysis of HLA-A antigens: Case (T2DM)-Control #1 (without family history and without T2DM) 2 of 2

HLA- A Case Control Crude OR Chi-Square OR Adjusted 95% Confidence Chi-Square Locus (n=110) (n=196) or Fisher’s for Age and Interval for Age or Fisher’s Exact Test* Sex and Sex) Exact Test*

Antigens Frequencies Frequencies OR P-value OR OR P-value A36 0 (0%) 3 (1.5%) ***NA *0.56 **NA **NA **NA A66 0 (0%) 2 (1%) ***NA *0.54 **NA **NA **NA A68 20 (18%) 24 (12%) 1.59 0.16 1.49 0.72-3.01 0.282 A69 0 (0%) 1 (0.5%) ***NA *1.0 **NA **NA **NA A74 0 (0%) 2 (1%) ***NA *0.53 **NA **NA **NA A80 2 (2%) 1(0.5%) 3.6 *0.29 10.72 0.73-156.8 0.083

Table 17 SAS Analysis of HLA-B antigens: Case (T2DM)-Control #1 (without family history and without T2DM) 1 of 3

HLA- B Case Control Crude OR Chi-Square OR Adjusted 95% Confidence Chi-Square Locus or Fisher’s for Age and Interval for Age or Fisher’s (n=110) (n=196) Exact Test* Sex and Sex Exact Test* Antigens Frequencie Frequencies OR P-value OR OR P-value B7 9 (8%) 23 (12%) 0.67 0.33 0.62 0.26-1.52 0.300 B8 11 (10%) 18 (9%) 1.1 0.82 1.27 0.53-3.02 0.592 B13 2 (2%) 7 (4%) 0.5 *0.5 0.48 0.09-2.66 0.398 B14 4 (4%) 4 (4%) 1.81 *0.46 1.11 0.23-5.26 0.900 B15 0 (0%) 1 (0.5%) ***NA *1.0 **NA **NA **NA B18 10 (9%) 20 (10%) 0.88 0.75 1.25 0.51-3.05 0.623 B21 0 (0%) 1 (0.5%) ***NA *1.0 **NA **NA **NA B27 5 (5%) 13 (7%) 0.67 0.46 0.44 0.12-1.61 0.215 B35 25 (23%) 67 (34%) 0.57 0.036 0.51 0.28-0.94 0.031 B37 2 (2%) 6 (3%) 0.59 *0.72 1.02 0.18-5.72 0.984 B38 4 (4%) 10 (5%) 0.7 0.56 0.62 0.17-2.29 0.477 B39 17 (15.5%) 27 (14%) 1.14 0.69 1.20 0.57-2.55 0.631 B40 0 (0%) 1 (0.5%) ***NA *1.0 **NA **NA **NA B41 4 (4%) 2 (1%) 3.7 *0.19 3.29 0.45-23.88 0.239 B42 2 (2%) 2 (1%) 1.8 *0.62 1.48 0.16-13.96 0.734

Table 17 SAS Analysis of HLA-B antigens: Case (T2DM)-Control #1 (without family history and without T2DM) 2 of 3

HLA- B Case Control Crude Chi-Square OR Adjusted 95% Confidence Chi-Square OR or Fisher’s for Age and Interval for Age or Fisher’s Locus (n=110) (n=196) Exact Test* Sex and Sex Exact Test* Antigens Frequencie Frequencies OR P-value OR OR P-value B44 21 (19%) 23 (12%) 1.8 0.08 2.37 1.14-4.91 0.021 B45 2 (2%) 6 (3%) 0.59 *0.72 0.52 0.09-2.88 0.455 B46 0 (0%) 1(0.5%) ***NA *1.0 **NA **NA **NA B47 0 (0%) 2 (1%) ***NA *0.54 **NA **NA **N.A B48 6 (5.5%) 12 (6%) 0.88 0.81 0.62 0.19-2.05 0.434 B49 8 (7%) 5 (3%) 3.0 *0.07 3.53 1.0-12.46 0.050 B50 8 (7%) 7 (4%) 2.11 0.15 3.40 1.02-11.39 0.047 B51 11(10%) 27(14%) 0.7 0.34 0.73 0.31-1.71 0.464 B52 3 (3%) 13 (7%) 0.4 0.14 0.42 0.10-1.78 0.237 B53 4 (4%) 3 (1.5%) 0.43 *0.26 3.56 0.68-18.82 0.134 B55 2 (2%) 1 (0.5%) 3.6 *0.29 1.49 0.13-17.04 0.751

Table 17 SAS Analysis of HLA-B antigens: Case (T2DM)-Control #1 (without T2DM and family history of T2DM) 3 of 3 HLA- B Case Control Crude Chi-Square OR Adjusted 95% Confidence Chi-Square OR or Fisher’s for Age and Interval for Age or Fisher’s Locus (n=110) (n=196) Exact Test* Sex and Sex Exact Test* Antigens Frequencie Frequencies OR P-value OR OR P-value B56 1 (1%) 1 (0.5%) 1.79 *1.0 1.08 0.05-24.46 0.960 B57 4 (4%) 6 (3%) 1.2 *0.75 0.95 0.28-3.95 0.948 B58 1 (1%) 4 (2%) 0.44 *0.66 0.60 0.50-7.37 0.690 B60 5 (5%) 4 (2%) 2.3 *0.29 2.20 0.53-9.22 0.279 B61 16 (15%) 22 (11%) 1.35 0.4 1.48 0.69-3.18 0.314 B62 13 (12%) 19 (10%) 1.25 0.56 1.19 0.51-2.78 0.683 B63 1 (1%) 3 (1.5%) 0.59 *1.0 1.41 0.14-14.46 0.770 B65 7 (6%) 7 (4%) 1.84 0.26 1.33 0.39-4.51 0.644 B67 0 (0%) 1 (0.5%) ***NA *1.0 **NA **NA **NA B70 0 (0%) 3 (1.5%) ***NA *0.56 **NA **NA **NA B71 0 (0%) 1 (0.5%) ***NA *1.0 **NA **NA **NA B72 0 (0%) 3 (1.5%) ***NA *0.56 **NA **NA **NA B75 0 (0%) 1 (0.5%) ***NA *1.0 **NA **NA **N.A B4005 3 (3%) 2 (1%) 2.72 *0.35 1.16 0.16-8.36 0.883

Table 18 SAS Analysis of HLA-C antigens: Case (T2DM)-Control #1 (without T2DM and family history of T2DM)

HLA- C Case Control Crude OR Chi-Square OR Adjusted 95% Confidence Chi-Square or Fisher’s for Age and Interval for Age or Fisher’s Locus (n=110) (n=196) Exact Test* Sex and Sex Exact Test* Antigens Frequencies Frequencies OR P-value OR OR P-value C1 11 (10%) 17 (8.7%) 1.7 0.7 0.97 0.39-2.45 0.952 C2 5 (4.6%) 13 (6.6%) 0.67 0.46 0.49 0.14-1.72 0.267 C3 19 (17%) 45 (23%) 0.7 0.24 0.72 0.37-1.4 0.331 C4 28 (25.5%) 57 (29%) 0.83 0.5 0.78 0.43-1.42 0.421 C5 16 (14.6%) 18 (9%) 1.68 0.15 2.26 1.01-5.08 0.048 C6 11 (10%) 26 (13%) 0.73 0.4 1.01 0.44-2.35 0.980 C7 41 (37%) 65 (33%) 1.2 0.47 1.28 0.74-2.23 0.375 C8 14 (12.7%) 20 (10%) 1.3 0.5 0.87 0.38-1.97 0.730 C9 2 (2%) 2 (1%) 1.8 *0.62 1.64 0.18-15.07 0.662 C12 1 (1%) 1 (0.5%) 1.79 *1.0 4.17 0.20-88.14 0.359 C14 0 (0%) 1 (0.5%) ***NA *1.0 **NA **NA **NA C15 1 (1%) 1 (0.5%) 1.79 *1.0 2.89 0.16-51.03 0.469 C16 1 (1%) 0 (0%) ***NA *0.36 **NA **NA **NA C17 2 (2%) 2 (1%) 1.8 *0.62 1.27 0.13-12.14 0.838

SAS Analysis of Class I Antigens (Case-Control #1)

HLA antigens data were analyzed using PROC LOGISTIC in the SAS software package (Version 9.1) for Windows. Logistic regression was used to calculate exposure odds ratios (OR). Statistical significance of the crude OR was assessed using a chi-squire or Fisher’s exact test as appropriate. To clarify, if one or more of the expected cell counts was less than 5, then the p-value from the Fisher’s exact test was reported. A result was considered statistically significant if the p-value was 0.05 or less. After univariate analyses, ORs were adjusted for age and sex. Ninety-five percent confidence intervals (CI) were also calculated. At times a quasi-complete separation of the data points was detected during a multivariate analysis and hence the validity of the model fit was questionable. In these situations the reader is alerted to this fact. The reason for this numerical problem was the presence of a zero cell frequency (e.g., all of the cases were exposed/had the antigen). The HLA Class I antigens typing data used in analysis, which are listed in Appendix: F.

Results of Class I Antigens (Case-Control #1)

Table 16 shows Class I HLA-A locus antigens: crude OR ranged from 0.43- 3.60

(p= 0.03-1.0). The adjusted OR for age and sex ranged from 0.39-10.72 (p= 0.041-

0.965).

The HLA-A3 antigen was significant in its protective association with T2DM in the univariate analysis (crude OR = 0.44, p = 0.03). In the multivariate analysis which controlled for age and sex, a significant protective association was observed (adjusted OR

= 0.39, p = 0.04, 95% confidence interval (CI) 0.16-0.965).

The HLA-A80 antigen was not associated with T2DM in the univariate (crude OR

= 3.6, p = 0.29). However, in the multivariate analysis which controlled for age and sex,

OR suggestive of susceptible association with T2DM was observed (adjusted OR =

10.72, p = 0.083 (95% CI, 0.73-156.8). The susceptibility was more pronounced when

OR adjusted for age and sex indicating a confounding effect of disease and antigen association.

Table 17 shows that the Class I HLA-B locus antigens: crude OR ranged from

0.40 - 3.70 (p= 0.036-1.0). The adjusted OR for age and sex ranged from 0.42-3.56 (p- value 0.021-0.984).

The HLA-B35 antigen was significant in its protective association with T2DM in the univariate analysis (crude OR = 0.57, p = 0.036). In the multivariate analysis which controlled for age and sex, a significant protective association was observed (adjusted

OR= 0.51, p = 0.031, 95% CI, 0.28-0.94).

The HLA-B44 antigen OR was suggestive of susceptible association with T2DM in the univariate analysis (crude OR = 1.8, p = 0.08). However, in the multivariate analysis which controlled for age and sex, significant susceptible association was observed with T2DM (adjusted OR= 2.7, p = 0.021, 95% CI, 1.14-4.91).

The HLA-B49 antigen OR also was suggestive of susceptible association with

T2DM in the univariate analysis (crude OR = 3.0, p = 0.07). However, in the multivariate analysis which controlled for age and sex, a significant susceptible association was observed (adjusted OR = 3.53, p = 0.050, 95% CI, 1.0- 12.46).

The observations were similar with HLA-B50 antigen OR was suggestive of susceptible association with T2DM in the univariate analysis (OR = 2.11, p = 0.15).

However, in the multivariate analysis which controlled for age and sex, a significant susceptible association was observed with T2DM (adjusted OR=3.40, p=0.047, 95% CI,

1.02- 11.39).

Table 18 shows the Class I HLA-C locus antigens: crude OR ranged from 0.67-

1.80 (p= 0.15-1.0). The adjusted for age and sex, Ors, ranged from 0.49-4.17 (p= 0.048-

0.980).

The HLA-C5 antigen OR was not associated with T2DM in the univariate analysis (crude OR=1.68, p = 0.15). However, in the multivariate analysis which controlled for age and sex, a significant susceptible association was observed (adjusted

OR= 2.26, p = 0.048, 95% CI, 1.01-5.08).

Case-Control Group B (Case-Control #2)

Table 19 Clinical features of the Case (T2DM)-Control #2 (without T2DM and with family history of T2DM)

Patients Case (T2DM) (n=110) Control #2 (without T2DM with (or) family history of T2DM) Controls (n=24)

Age Groups Frequencies Frequencies 21-30 0 (0%) 10 (41.5%) 31-40 1 (1%) 5 (21%) 41-50 29 (27%) 6 (25%) 51-60 47 (43%) 3 (12.5%) 61-70 30 (27%) 0 (0%) 71-80 3 (3%) 0 (0%)

Table 19 shows the summary of clinical features cases and controls #2 of age groups, frequencies, and percentages. Age group 21-30: case = 0 (0%) and control #2 =

10 (41.5%). Age group 31-40: case = 1(1%) and control #2 = 5 (21%). Age group 41-50: case =29 (27%) and control #2 = 6 (25%). Age group 51-60: case = 47 (43%) and control

#2 = 3(12.5%). Age group 61-70: case = 30 (27%) and control #2 = 0 (0%). Age group

71-80: case = 3 (3%) and control #2 = 0 (0%).

Table 20 Demographic data of Case (T2DM)-Control #2 (without T2DM and with family history of T2DM)

Case (T2DM) Control #2 (without T2DM (n=110) with family history of T2DM) (n=24) Age Mean 55.66 36.21 Age SD 7.72 10.79 Male 76 (69%) 12 (50%) Female 34 (31%) 12 (50%) Race (MA) 100% 100%

Table 20, shows the summary of case and control subjects: The mean age of the patients was 55.66 years and the standard deviation (SD) was ±7.72; for the controls, the mean age was 36.21 years with an SD of ±10.79. The male to female frequencies vary between the cases and the controls (69% male and 31 % female in cases and 50% male and 50% female in controls).

Table 21 SAS Analysis of HLA-A antigens: Case (T2DM)-Control #2 (with family history and without T2DM) 1 of 2

HLA- A Case Control Crude OR Chi-Square Adjusted OR 95% Confidence Chi-Square or Locus (n=110) (n=24) or Fisher’s for Age and Interval for Age Fisher’s Exact Test* Sex and Sex Exact Test*

Antigens Frequencies Frequencies OR P-value OR OR P-value A1 20 (18%) 5 (20.83%) 0.84 *0.775 1.13 0.21-6.0 0.889 A2 52 (47%) 20 (83.33%) 0.18 0.0013 0.23 0.05-1.06 0.059 A3 9 (8.5%) 1 (4.17%) 2.05 0.69 4.97 0.36-68.75 0.231 A11 8 (7.5%) 2 (8.33%) 0.86 *1.0 0.22 0.03-1.57 0.131 A23 5 (5%) 0 (0%) ***NA *0. 585 **NA **NA **0. 980 A24 31 (28%) 8 (33.33%) 0.78 0.615 1.51 0.32-7.07 0.603 A25 2 (2%) 3 (12.50) 0.13 *0.040 3.5 0.11-114.05 0.479 A26 5 (5%) 0 (0%) ***NA *0.585 **NA **NA **0.984 A28 6 (6%) 3 (12.50%) 0.40 0.203 0.01 <0.001-0.24 0.004 A29 8 (7.5%) 1 (4.17%0 1.80 *1.0 0.5 0.04-5.71 0.580 A30 10 (9.5%) 0 (0%) ***NA *0.208 **NA **NA **0.966 A31 15 (14%) 2 (8.33%) 1.74 *0.737 0.97 0.07-13.56 0.983 A32 5 (5%) 0 (0%) ***NA *0.585 **NA **NA **0.978 A33 6 (6%) 0 (0%) ***NA *0.591 **NA **NA **0.977 A34 1 (1%) 0 (0%) ***NA *1.0 **NA **NA **990

Table 21 SAS Analysis of HLA-A antigens: Case (T2DM)-Control #2 (without T2DM and with family history of T2DM) 2of 2

HLA- A Case Control Crude OR Chi-Square OR Adjusted 95% Confidence Chi-Square Locus (n=110) (n=24) or Fisher’s for Age and Interval for Age or Fisher’s Exact Test* Sex and Sex Exact Test*

Antigens Frequencies Frequencies OR P-value OR OR P-value A36 0 (0%) 0 (0%) ***NA **NA **NA **NA **NA A66 0 (0%) 0 (0%) ***NA **NA **NA **NA **NA A68 20 (18%) 1 (4.17%) 5.11 0.122 1.90 0.20-18.46 0.579 A69 0 (0%) 0 (0%) ***NA **NA **NA **NA **NA A74 0 (0%) 0 (0%) ***NA **NA **NA **NA **NA A80 2 (2%) 0 (0%) ***NA *1.0 **NA **NA **0.989

Table 22 SAS Analysis of HLA-B antigens: Case (T2DM)-Control #2 (without T2DM and with family history of T2DM) 1 of 2

HLA- B Case Control Crude OR Chi-Square OR Adjusted 95% Confidence Chi-Square or Fisher’s for Age and Interval for Age or Fisher’s Locus (n=110) (n=24) Exact Test* Sex and Sex Exact Test* Antigens Frequencies Frequencies OR P–value OR OR P-value B7 9 (8%) 2 (8.33%) 0.98 *1.0 0.40 0.05-3.58 0.414 B8 11 (10%) 2 (8.33) 1.22 *1.0 7.31 0.31-170.73 0.216 B13 2 (2%) 0 (0%) ***NA **NA **NA **NA **0.988 B14 4 (4%) 1 (4.17%) 0.87 *1.0 0.25 0.02-3.87 0.319 B15 0 (0%) 0 (0%) ***NA **NA NA NA **NA B18 10 (9%) 3 (12.50%) 0.70 *0.702 5.63 0.30-105.43 0.248 B21 0 (0%) 0 (0%) ***NA **NA **NA **NA **NA B27 5 (5%) 0 (0%) ***NA *0.585 **NA **NA **0.983 B35 25 (23%) 8(33.33%) 0.59 0.275 0.23 0.05-1.02 0.054 B37 2 (2%) 0 (0%) ***NA *1.0 NA NA **0.985 B38 4 (4%) 1 (4.17%) 0.87 *1.0 0.24 0.02-3.79 0.313 B39 17 (15.5%) 3 (12.50%) 1.28 *1.0 0.98 0.17-5.72 0.981 B40 0 (0%) 0 (0%) ***NA **NA **NA **NA **NA B41 4 (4%) 3 (12.50%) 0.26 *0.109 0.28 0.02-4.49 0.367 B42 2 (2%) 0 (0%) ***NA *1.0 **NA **NA **0.984 B44 21 (19%) 6 (25%) 0.71 0.576 0.54 0.12-2.45 0.42 B45 2 (2%) 0 (0%) ***NA *1.0 **NA **NA **0.988 B46 0 (0%) 0 (0%) ***NA **NA **NA **NA **NA B47 0 (0%) 0 (0%) ***NA **NA **NA **NA **NA B48 6 (5.5%) 0 (0%) ***NA *0.591 **NA **NA *0.981 *25%-50% of the antigens have expected counts less than 5; Fisher’s Exact Test Two-sided P-value was used. ** Quasi-complete separation of data points detected. Validity of the model fit is questionable. *** One or more risk estimates not computed ….. Zero cell.

Table 22 SAS Analysis of HLA-B antigens: Case (T2DM)-Control #2 (without T2DM and with family history of T2DM) 2 of 2

HLA- B Case Control Crude OR Chi-Square OR Adjusted 95% Chi-Square or Fisher’s for Age and Confidence or Fisher’s Locus (n=110) (n=24) Exact Test* Sex Interval for Exact Test* Age and Sex Antigens Frequencies Frequencies OR P–value OR OR P-value B49 8 (7%) 2 (8.33%) 0.86 *1.0 3.33 0.08-133.92 0.542 B50 8 (7%) 4 (16.67%) 0.39 *0.23 6.12 0.29-129.30 0.245 B51 11 (10%) 1 (4.17%) 2.56 *0.69 1.7 0.14-20.27 0.677 B52 3 (3%) 0 (0%) NA *1.0 NA NA **0.983 B53 4 (4%) 0 (0%) NA *1.0 NA NA **0.978 B55 2 (2%) 0 (0%) NA *1.0 NA NA **0.988 B56 1 (1%) 1 (4.17%) 0.21 *0.327 0.005 <0.001-0.19 0.0038 B57 4 (4%) 3 (12.50%) 0.26 *0.109 0.081 0.009-0.69 0.0215 B58 1 (1%) 0 (0%) NA *1.0 NA NA **0.993 B60 5 (5%) 0 (0%) NA *0.59 NA NA **0.979 B61 16 (15%) 1 (4.17%) 3.91 *0.307 3.55 0.32-39.82 0.304 B62 13 (12%) 3 (12.50%) 0.94 *1.0 2.32 0.18-30.15 0.521 B63 1 (1%) 0 (0%) ***NA *1.0 **NA **NA **0.990 B65 7 (6%) 1 (4.17%) 1.56 *1.0 6.51 0.07-600.38 0.417 B67 0 (0%) 0 (0%) ***NA **NA **NA **NA **NA B70 0 (0%) 0 (0%) ***NA **NA **NA **NA **NA B71 0 (0%) 0 (0%) ***NA **NA **NA **NA **NA B72 0 (0%) 0 (0%) ***NA **NA **NA **NA **NA B75 0 (0%) 0 (0%) ***NA **NA **NA **NA **NA B4005 3 (3%) 0 (0%) ***NA *1.0 **NA **NA **0.987 *25%-50% of the antigens have expected counts less than 5; Fisher’s Exact Test Two-sided P-value was used. ** Quasi-complete separation of data points detected. Validity of the model fit is questionable. *** One or more risk estimates not computed ….. Zero cell.

Table 23 SAS Analysis of HLA-C antigens: Case (T2DM)-Control #2 (with family history T2DM and without of T2DM)

HLA- C CASE Control Crude OR Chi-Square OR Adjusted 95% Confidence Chi-Square or Fisher’s for Age and Interval for Age or Fisher’s Locus (110) (24) Exact Test* Sex and Sex Exact Test* Antigens Frequencies Frequencies OR P-value OR OR P-value C1 11 (10%) 2 (8.33%) 1.22 *1.0 2.04 0.03-168.89 0.752 C2 5 (4.6%) 0 (0%) ***NA *0.585 **NA **NA **0.983 C3 19 (17%) 0 (0%) ***NA *0.024 **NA **NA **0.969 C4 28 (25.5%) 4 (16.67%) 1.7 0.360 0.77 0.18-3.30 0.724 C5 16 (14.6%) 4 (16.67%) 0.85 *0.757 1.25 0.20-7.71 0.809 C6 11 (10%) 1 (4.17%) 2.56 *0.693 3.91 0.39-39.54 0.248 C7 41 (37%) 8 (33.33%) 1.19 0.717 1.02 0.24-4.33 0.982 C8 14 (12.7%) 1 (4.17%) 3.35 *0.306 7.22 0.10-506.32 0.362 C9 2 (2%) 0 (0%) ***NA *1.0 **NA **NA **0.989 C12 1 (1%) 0 (0%) ***NA *1.0 **NA **NA **0.991 C14 0 (0%) 0 (0%) ***NA **NA **NA **NA **NA C15 1 (1%) 0 (0%) ***NA *1.0 **NA **NA **0.991 C16 1 (1%) 0 (0%) ***NA *1.0 **NA **NA **0.991 C17 2 (2%) 0 (0%) ***NA *1.0 **NA **NA **0.988

SAS Analysis of Class I Antigens (Case-Control #2)

Results of Class I Antigens (Case-Control #2)

Table 21 shows that the Class I HLA-A locus antigens: crude OR ranged from

0.13-5.11 (p=0.0013- 1.0). The adjusted OR for age and sex ranged from 0.01-4.97, p=

0.004-0.990).

The HLA-A2 antigen was significant in its protective association with T2DM in the univariate analysis (crude OR= 0.18, p= 0.0013). However, in the multivariate analysis which controlled for age and sex, OR suggestive protective association with

T2DM was observed (adjusted OR=0.23, p= 0.059, 95% CI, 0.05-1.06).

The HLA-A25 antigen showed statistically significant protective association with

T2DM in the univariate analysis (crude OR= 0.13, p= 0.040). However, in the multivariate analysis which controlled for age and sex, it was not a significant susceptible association with T2DM (adjusted OR=3.5, p=0.479, 95% CI, 0.11-114.05).

The HLA-A28 antigen was not associated with T2DM in the univariate analysis

(crude OR=0.40, p=0.203). However, in the multivariate analysis which controlled for age and sex, a protective association was observed with T2DM (adjusted OR= 0.01, p=

0.004, 95% CI, <0.001-0.24).

Table 22 shows that the Class I HLA-B locus antigens: crude OR ranged from

0.21-3.91 (p=0.109-1.0). The adjusted OR for age and sex ranged from 0.005-7.31 (p=

0.0038-0.990).

The HLA-B35 antigen was not associated with T2DM in the univariate analysis

(crude OR=0.59, p=0.275). However, in the multivariate analysis which controlled for age and sex, a protective association was observed with T2DM (adjusted OR= 0.23, p=

0.05, 95% CI, 0.05-1.02).

The HLA- B56 antigen was not associated with T2DM in the univariate analysis

(crude OR= 0.21, p=0.327). However, in the multivariate analysis which controlled for age and sex, a protective association was observed with T2DM (adjusted OR= 0.005, p=

0.0038, 95% CI, <0.001-0.19).

The HLA- B57 antigen was also not associated with T2DM in the univariate analysis (OR= 0.26, p= 0.11), However, in the multivariate analysis which controlled for age and sex, a protective association was observed with T2DM (adjusted OR= 0.08, p=0.02, 95% CI, 0.009-0.69).

Table 23 shows that the Class I HLA-C locus antigens: Crude OR ranged from

0.85-3.35, p=0.024-1.0). The adjusted OR for age and sex ranged from 0.77-7.22,

(p=0.248 - 0.99).

The HLA- C antigens were not a protective or susceptible in association with t2DM in the univariate analysis or in the multivariate analysis which controlled for age and sex, perhaps due to the sample size of control #2.

Research Question #2 What is the relationship between HLA Class II (HLA-DR, and HLA-DQ locus) antigens and T2DM among MA?

This was addressed using serological Class II (HLA-DR and DQ locus) antigens typing.

However, as stated earlier whenever possible, the unclear HLA antigen typing for Class

II was confirmed by Sequence Specific Primers (SSP). There were 110 cases with

T2DM and 196 controls #1 without family history of T2DM (Case-Control Group A) and

110 cases and 24 control #2 with family history of T2DM (Case-Control Group B).

Case-Control Group A (Case-Control #1)

Table 24 Clinical features of the Case (T2DM)-Control #1 (without T2DM and without family history of T2DM)

Patients Case (T2DM) Control #1 (without T2DM (or) (n=110) without family history of Controls T2DM) (n=196) Age Groups Frequencies (%) Frequencies (%) 21-30 0 (0%) 0 (0%) 31-40 1 (1%) 12 (6%) 41-50 29 (27%) 116 (59%) 51-60 47 (43%) 54 (27.5%) 61-70 30 (27%) 13 (7%) 71-80 3 (3%) 1 (0.5%)

Table 24 shows the summary of clinical features cases and control #1 of age groups frequencies and percentages presented. Age group 21-30: case = 0 (0%) and

control #1 = 0 (0%). Age group 31-40: case = 1 (1%) and control #1 = 12 (6%). Age group 41-50: case = 29 (27%) and control #1 = 116 (59%). Age group 51-60: case = 47

(43%) and control #1 = 54 (27.5%). Age group 61-70: case = 30 (27%) and control #1 =

13 (7%). Age group 71-80: cases=3(3%) and control #1 = 1(0.5%).

Table 25 Demographic data of Case (T2DM)-Control #1 (without T2DM and without family history of T2DM)

Case (T2DM) (n=110) Control #1(without T2DM without family history of T2DM) (n=196) Age Mean 55.66 48.68 Age SD 7.72 6.79 Male 76 (69%) 86 (44%) Female 34 (31%) 110 (56%) Race (MA) 100% 100%

Table 25 shows the summary of patient and normal controls: The mean age was

55.66 years with a standard deviation (SD) of ±7.72, and the mean age of the controls was 48.68 years with a SD ±6.79. The male to female frequencies vary between the cases and the controls (69% male and 31% female in cases and 44% male and 56% female in controls).

Table 26 SAS Analysis of HLA-DR antigens: Case (T2DM)-Control #1 (without T2DM and without family history of T2DM)

HLA-DR Case Control Crude OR Chi-Square OR Adjusted 95% Confidence Chi-Square or Fisher’s for Age and Interval for Age or Fisher’s Locus (n=110) (n=196) Exact Test* Sex and Sex Exact Test* Antigens Frequencies Frequencies OR P-value OR OR P-value DR1 12 (11%) 24 (12%) 0.88 0.73 0.53 0.27-1.56 0.337 DR2 1 (1%) 11 (6%) 0.15 *0.06 0.12 0.01-1.09 0.060 DR3 2 (2%) 6 (3%) 0.59 *0.72 0.73 0.13-4.01 0.713 DR4 41 (37%) 81 (41%) 0.84 0.49 1.09 0.64-1.88 0.750 DR6 5 (5%) 7 (3.5%) 1.3 *0.76 0.62 0.15-2.53 0.507 DR7 11 (10%) 29 (15%) 0.64 0.23 0.76 0.34-1.70 0.502 DR8 25 (23%) 44 (22%) 1.02 0.96 1.05 0.56-1.97 0.872 DR9 4 (4%) 5 (2.5%) 1.44 *0.73 1.01 0.22-4.55 0.992 DR10 1 (1%) 6 (3%) 0.29 *0.43 0.43 0.04-4.64 0.488 DR11 20 (18%) 36 (18%) 0.99 0.97 0.85 0.43-1.68 0.643 DR12 1 (1%) 7 (3.5%) 0.25 *0.27 0.29 0.03-2.50 0.258 DR13 18 (16%) 20 (10%) 1.72 0.12 1.62 0.79-3.42 0.205 DR14 21 (19%) 22 (11%) 1.87 0.06 1.77 0.85-3.70 0.128 DR15 15 (14%) 31 (16%) 0.84 0.61 0.89 0.42-1.90 0.768 DR16 6 (5.5%) 8 (4%) 1.36 0.58 1.4 0.41-4.80 0.589 DR17 17 (15.5%) 31 (16%) 0.97 0.93 1.01 0.49-2.09 0.982 DR18 0 (0%) 2 (1%) ***NA *053 **NA **NA **NA DR103 3 (3%) 3 (1.5%) 1.8 *0.67 2.25 0.39-13.12 0.366

Table 27 SAS Analysis of HLA-DQ antigens: Case (T2DM)-Control #1 (without T2DM and without family history of T2DM)

HLA-DQ Case Control Crude OR Chi-Square OR Adjusted for 95% Confidence Chi-Square or Fisher’s Age and Sex Interval for Age or Fisher’s Locus (n=110) (n=196) Exact Test* and Sex Exact Test* Antigens Frequencies Frequencies OR P-value OR OR P-value DQ1 19 (17%) 26 (13%) 1.37 0.34 1.11 0.53-2.30 0.790 DQ2 28 (25%) 52 (26.5%) 0.95 0.84 1.08 0.59-1.97 0.798 DQ3 11 (10%) 27 (14%) 0.7 0.34 1.05 0.47-2.36 0.902 DQ4 24 (22%) 45 (23%) 0.94 0.81 0.99 0.53-1.85 0.971 DQ5 9 (8%) 22 (11%) 0.7 0.4 0.81 0.32-2.04 0.660 DQ6 19 (17%) 31 (16%) 1.11 0.74 1.35 0.67-2.72 0.405 DQ7 40 (36%) 63 (32%) 1.2 0.45 0.93 0.53-1.62 0.787 DQ8 23 (21%) 47 (24%) 0.84 0.54 0.97 0.51-1.83 0.925 DQ9 1 (1%) 4 (2%) 0.44 0.66 0.58 0.05-6.44 0.658

SAS Analysis of Class II Antigens (Case-Control #1)

HLA antigens data were analyzed using PROC LOGISTIC in the SAS software package (Version 9.1) for Windows. Logistic regression was used to calculate exposure odds ratios (OR). Statistical significance of the crude OR was assessed using a chi-squire or Fisher’s exact test as appropriate. To clarify, if one or more of the expected cell counts was less than 5, then the p-value from the Fisher’s exact test was reported. A result was considered statistically significant if the p-value was 0.05 or less. After univariate analyses, ORs were adjusted for age and sex. Ninety-five percent confidence intervals (CI) were also calculated. At times a quasi-complete separation of the data points was detected during a multivariate analysis and hence the validity of the model fit was questionable. In these situations the reader is alerted to this fact. The reason for this numerical problem was the presence of a zero cell frequency (e.g., all of the cases were exposed/had the antigen). The HLA Class II antigens typing data used in analysis, which are listed in Appendix: G.

Results of Class II Antigens (Case-Control #1)

Table 26 shows that the Class II HLA-DR locus antigens: crude OR ranged from

0.15-1.87 (p= 0.06-0.97) and the adjusted OR for age and sex ranged from 0.12-2.25 (p=

0.060-0.99).

The HLA-DR2 antigen was suggestive protective association with T2DM in univariate analysis (crude OR=0.15, p=0.06). Also, in multivariate analysis which controlled for age and sex was suggestive protective association observed with T2DM

(adjusted OR=0.12, p=0.06, 95% CI, 0.01-1.0.9).

The HLA-DR14 antigen also was suggestive susceptible association with T2DM in the univariate analysis (crude OR=1.87, p=0.06). However, in the multivariate analysis which controlled for age and sex, was not susceptible associated with T2DM (adjusted

OR=1.77, p=0.13, 95% CI, 0.85-3.7).

Table 27 shows that the Class II HLA-DQ locus antigens: crude OR ranged from

0.44-1.37 (p= 0.34-0.84). The adjusted OR for age and sex ranged from 0.58-1.35

(p=0.405 to 0.97).

The HLA- DQ antigens were not protective or susceptible a significant association with T2DM in the univariate analysis or multivariate analysis which controlled for age and sex.(case-control #1).

Case-Control Group B (Case-Control #2)

Table 28 Clinical Features of the Case (T2DM)-Control #2 (without T2DM and with family history of T2DM)

Patients Case (T2DM) Control #2 (without T2DM with (or) (n=110) family history of T2DM) Controls (n=24)

Age Groups Frequencies (%) Frequencies (%) 21-30 0 (0%) 10 (41.5%) 31-40 1 (1%) 5 (21%) 41-50 29 (27%) 6 (25%) 51-60 47 (43%) 3 (12.5%) 61-70 30 (27%) 0 (0%) 71-80 3 (3%) 0 (0%)

Table 28 shows the summary of the clinical features of case (T2DM)-control #2 with regard to the age groups, frequencies, and percentages. Age group 21-30: case = 0

(0%) and control #2 = 10 (41.5%). Age group 31-40: cases = 1(1%) and control #2 = 5

(21%). Age group 41-50: cases=29 (27%) and control #2=6(25%). Age group 51-60:

cases=47 (43%) and control #2=3(12.5%). Age group 61-70: cases=30 (27%) and control

#2=0(0%). Age group 71-80: cases=3(3%) and control #2=0 (0%).

Table 29 Demographic data of Case (T2DM)-Control #2 (without T2DM and with family history of T2DM)

Case(T2DM) Control #2(without T2DM with family (n=110) history of T2DM) (n=24) Age Mean 55.66 36.21 Age SD 7.72 10.79 Male 76 (69%) 12 (50%) Female 34 (31%) 12 (50%) Race (MA) 100% 100%

Table 29 shows the summary of case and control subjects: The patients’ mean age was 55.66 years with an SD of ± 7.72. The mean age of the controls was 36.21 years with an SD of ± 10.79. The male to female frequencies vary between the cases and the controls (69% male and 31 % female in cases and 50% male and 50% female in controls).

Table 30 SAS Analysis of HLA-DR antigens: Case (T2DM)-Control #2 (without T2DM and with family history T2DM)

HLA-DR Case Control Crude OR Chi-Square OR Adjusted 95% Confidence Chi-Square or Fisher’s for Age and Interval for Age or Fisher’s Locus (n=110) (n=24) Exact Test* Sex and Sex Exact Test* Antigens Frequencies Frequencies OR P-value OR OR P-value DR1 12 (11%) 3 (12.5%) 0.86 *0.732 0.77 0.08-7.96 0.830 DR2 1 (1%) 2 (8.33%) 0.10 *0.08 0.07 <0.001-20.43 0.356 DR3 2 (2%) 1 (4.17%) 0.43 *0.450 4.22 0.006-799.99 0.664 DR4 41 (37%) 6 (25.0%) 1.78 0.254 2.58 0.58-11.49 0.214 DR6 5 (5%) 1 (4.17%) 1.10 *1.0 0.41 0.002-73.71 0.734 DR7 11 (10%) 4 (16.67%) 0.56 *0.472 0.25 0.04-1.52 0.132 DR8 25 (23%) 4 (16.67%) 1.47 0.514 0.60 0.12-3.04 0.530 DR9 4 (4%) 0 (0%) ***NA *1.0 **NA **NA **0.981 DR10 1 (1%) 1 (4.17%) 0.21 *0.327 0.40 <0.001- >99.99 0.872 DR11 20 (18%) 6 (25%) 0.67 *0.57 0.28 0.057-1.33 0.108 DR12 1 (1%) 0 (0%) ***NA *1.0 **NA **NA **0.991 DR13 18 (16%) 5 (20.83%) 0.74 *0.562 0.60 0.10-3.49 0.569 DR14 21 (19%) 6 (25%) 0.71 0.576 0.76 0.16-3.74 0.73 DR15 15 (14%) 4 (16.67%) *0.790 *0.748 1.29 0.16-10.53 0.82 DR16 6 (5.5%) 0 (0%) ***NA *0.591 **NA **NA **0.982 DR17 17 (15.5%) 1 (4.17%) 4.20 *0.195 15.22 0.65-356.47 0.091 DR18 0 (0%) 0 (0%) ***NA **NA **NA **NA **NA DR103 3 (3%) 1 (4.17%) 0.64 *0.550 0.19 0.014-2.78 0.227

Table 31 SAS Analysis of HLA-DQ antigens: Case (T2DM)-Control #2 (without T2DM and with family history T2DM)

HLA-DQ Case Control Crude OR Chi-Square OR Adjusted 95% Confidence Chi-Square or Fisher’s for Age and Interval for Age or Fisher’s Locus (n=110) (n=24) Exact Test* Sex and Sex Exact Test* Antigens Frequencies Frequencies OR P-value OR OR P-value DQ1 19 (17%) 7 (29.17%) 0.51 0.252 0.16 0.026-0.95 0.044 DQ2 28 (25%) 5 (20.83%) 1.30 0.634 2.12 0.41-10.84 0.367 DQ3 11 (10%) 1 (4.17%0 2.56 *0.693 2.37 0.24-23.20 0.460 DQ4 24 (22%) 4 (16.67%) 1.4 *0.574 0.84 0.17-4.13 0.823 DQ5 9 (8%) 5 (20.83%) 0.34 *0.131 1.76 0.18-17.64 0.629 DQ6 19 (17%) 0 (0%0 ***NA *0.024 **NA **NA **0.970 DQ7 40 (36%) 12(50.0% ) 0.57 0.214 0.43 0.10-1.78 0.242 DQ8 23 (21%) 0 (0%) ***NA *0.014 **NA **NA **0.970 DQ9 1 (1%) 1 (4.17%) 0.21 *0.327 0.08 0.004-1.62 0.100

SAS Analysis of Class II Antigens (Case-Control #2)

HLA antigens data were analyzed using PROC LOGISTIC in the SAS software package (Version 9.1) for Windows. Logistic regression was used to calculate exposure odds ratios (OR). Statistical significance of the crude OR was assessed using a chi-squire or Fisher’s exact test as appropriate. To clarify, if one or more of the expected cell counts was less than 5, then the p-value from the Fisher’s exact test was reported. A result was considered statistically significant if the p-value was 0.05 or less. After univariate analyses, ORs were adjusted for age and sex. Ninety-five percent confidence intervals (CI) were also calculated. At times a quasi-complete separation of the data points was detected during a multivariate analysis and hence the validity of the model fit was questionable. In these situations the reader is alerted to this fact. The reason for this numerical problem was the presence of a zero cell frequency (e.g., all of the cases were exposed/had the antigen). The HLA Class II antigens typing data used in analysis, which are listed in Appendix: G.

Results of Class II (Case-Control #2)

Table 30 shows that the Class II HLA-DR locus antigens: crude OR ranged from

0.10-4.20 (p=0.08-1.0). The adjusted OR for age and sex ranged from 0.07-15.22

(p=0.091-0.99).

The HLA-DR2 antigen OR suggestive of protective association with T2DM in the univariate analysis (crude OR= 0.10, p= 0.08). The multivariate analysis which controlled for age and sex, OR suggestive of protective association with T2DM (adjusted

OR=0.07, p=0.356, 95% CI, <0.001-20.43).

The HLA-DR17 antigen OR suggestive of susceptible association with T2DM in the univariate analysis (crude OR=4.20, p=.195). The multivariate analysis which controlled for age and sex also suggestive of susceptible association with T2DM

(Adjusted OR=15.22, p= 0.091, 95% CI, 0.65-356.47).

Table 31 shows that the Class II of HLA-DQ locus antigens: crude OR ranged from 0.34-2.56 (p=0.014-0.69). The adjusted OR for age and sex ranged from 0.08-2.37

(p= 0.044-0.970).

The HLA- DQ1 antigen was not associated with T2DM in the univariate analysis

(crude OR=0.51, p=0.25). However, in the multivariate analysis which controlled for age and sex, a protective association was observed (adjusted OR=0.16, p=0.04, 95% CI,

0.026-0.95).

Part II: Consists of Research Question #3:

Research Question #3: What is the relationship between specific HLA Class II

(HLA-DRB1*, HLA-DQA1*, HLA-DQB1* locus) alleles and T2DM among MA?

HLA Class II (HLA-DRB1*, DQA1*, DQB1*) consist of set #1 and Set #2 alleles typing by rSSO of 38 (48.10%) cases with T2DM and 41(51.90%) controls without history of T2DM and summary of age groups are as follows:

Case-Control (Set #1 & #2)

Table 32 Clinical Features of the Case (T2DM)-Control (without T2DM and without family history of T2DM) - Questions #3

Patients Case (T2DM) Control (without T2DM (or) (n=38) and without family history Controls T2DM) (n=41)

Age Groups Frequencies (%) Frequencies (%) 41-50 2 (5.26%) 10 (24.39%) 51-60 5 (13.16%) 8 (19.51%) 61-70 8 (21.05%) 14 (34.15%) 71-80 23 (60.53%) 9 (21.95%)

Table 32 summarizes the clinical features of the cases and controls with regard to their age groups, frequencies, and percentages. Age group 41-50: cases=2 (5.26%) and control = 10 (24.39%). Age group 51-60: case = 5 (13.16%) and control = 8 (19.51%).

Age group 61-70: case = 8 (21.05%) and control = 14 (34.15%). Age group 71-80: case =

23(60.53%) and control = 9 (21.95%).

HLA Class II (HLA-DRB1*, DQA1*, DQB1*) consists of set #1 and set #2 alleles typing by rSSO of 38 (48.10%) cases with T2DM and 41(51.90%) controls without history of T2DM. Summary of demographic data is as follows:

Table 33 HLA Data Analysis of Case (T2DM)-Control (without T2DM and without family history of T2DM) - Questions #3

Case (T2DM) (n=38) Control (without T2DM and without family history of T2DM) (n=41) Age Mean 56.87 51.80 Age SD 12.47 7.60 Male 13 (34%) 11 (27%) Female 25 (66%) 30 (73%) Race (MA) 100% 100%

Table 33 show the summary of case and control subjects: The mean age of patients was 56.87 years and SD was ±12.47; for the controls, the mean age was 51.80 years with SD of ± 7.60. The male to female frequencies varied between the cases and the controls (34% male and 66% female in cases and 27% male and 73% female in controls).

Table 34 SAS Analysis of HLA-DRB1 alleles: Case (T2DM)-Control (without T2DM and without family history of T2DM) 1 of 2

HLA- DRB1* Case Control Crude OR Chi-Square OR Adjusted 95% Confidence Chi-Square or Fisher’s for Age and Interval for Age or Fisher’s Locus (n=38) (n=41) Exact Test* Sex and Sex Exact Test* Alleles Frequencies Frequencies OR P-value OR OR P-value DRB1*0101 0 (0%) 0 (0%) ***NA **NA **NA **NA **NA DRB1*0102 2 (5.26%) 5 (12.2%) 0.4 *0.434 0.33 0.05-2.13 0.244 DRB1*0103 1 (2.63%) 1 (2.44) 1.1 *1.0 1.80 0.11-30.97 0.686 DRB1*0301 7 (18.42%) 4(9.76%) 2.1 0.266 1.67 0.40-6.95 0.479 DRB1*0401 0 (0%0 0 (0%) ***NA **NA **NA **NA **NA DRB1*0404 1 (2.63%) 6 (14.63%) 0.16 *0.110 0.30 0.03-2.86 0.294 DRB1*0405 1 (2.63%) 1(2.63%) 1.1 *1.0 2.63 0.15-46.82 0.508 DRB1*0407 9 (23.68%) 5 (12.20%) 2.23 0.181 1.64 0.43-6.2 0.468 DRB1*0410 1 (2.63%) 0 (0%) ***NA *0.481 **NA **NA **0.987 DRB1*0701 5 (13.16%) 7(17.07%) 0.74 0.628 0.58 0.15-2.19 0.419 DRB1*0705 0 (0%) 1(2.44%) NA *1.0 **NA **NA **0.985 DRB1*0802 7 (18.42%) 13(31.71%) 0.49 0.175 0.44 0.14-1.38 0.158 DRB1*0901 1 (2.63%) 1 (2.44%) 0.53 *1.0 0.60 0.05-7.67 0.693 DRB1*1001 0 (0%) 1 (2.44%) ***NA * 1.0 **NA **NA **0.986 DRB1*1101 1 (2.6%) 1 (2.44%) 1.1 *1.0 1.89 0.08-44.40 0.694 DRB1*1102 2 (5.26%) 0 (0%) ***NA *0.228 **NA **NA **0.980 DRB1*1104 5 (13.16%) 5 (12.20%) 1.1 *1.0 0.91 0.22-3.79 0.893 DRB1*1201 2 (5.26%) 0 (0%) ***NA *0.228 **NA **NA **0.980

Table 34 SAS Analysis of HLA-DRB1 alleles: Case (T2DM)-Control (without T2DM and without family history of T2DM) 2 of 2

Table 35 SAS Analysis of HLA-DRA1 alleles: Case (T2DM)-Control (without T2DM and without family history of T2DM)

HLA- DQA1* Case Control Crude OR Chi-Square OR Adjusted 95% Confidence Chi-Square or Fisher’s for Age and Interval for Age or Fisher’s Locus (n=38) (n=41) Exact Test* Sex and Sex Exact Test* Alleles Frequencies Frequencies OR P-value OR P-value DQA1*0101 7 (18.42%) 11 (28.83%) 0.62 0.373 0.78 0.24-2.50 0.674 DQA1*0102 7 (18.42%) 7 (17.07%) 1.1 0.875 1.04 0.29-3.71 0.958 DQA1*0103 5 (13.16%) 8 (19.51%) 0.63 0.447 0.97 0.26-3.64 0.959 DQA1*0201 6 (15.79%) 8 (19.51%) 0.77 0.665 0.56 0.16-1.99 0.370 DQA1*0301 13 (34.21%0 14 (34.15%) 1.0 0.995 1.08 0.39-3.03 0.878 DQA1*0401 7 (18.42%0 11 (26.83%) 0.62 0.373 0.54 0.17-1.74 0.302 DQA1*0501 8 (21.05%) 4 (9.76%) 2.47 0.162 2.02 0.51-8.03 0.316 DQA1*0503 6 (15.79%) 7 (17.07%) 0.91 0.878 1.14 0.30-4.33 0.847 DQA1*0505 11 (28.95%) 8 (19.51%0 1.68 0.327 1.49 0.49-4.54 0.481 DQA1*0601 0 (0%) 1 (2.44%) ***NA *1.0 **NA **NA **0.986

Table 36 SAS Analysis of HLA-DRB1 alleles: Case (T2DM)-Control (without T2DM and without Family History of T2DM)

HLA- DQB1* Case Control Crude OR Chi-Square OR Adjusted 95% Confidence Chi-Square or Fisher’s for Age and Interval for Age or Fisher’s Locus (n=38) (n=41) Exact Test* Sex and Sex Exact Test* Alleles Frequencies Frequencies OR P-value OR P-value DQB1*0201 7 (18.42%) 4 (9.76%) 2.1 0.266 1.67 0.40-6.95 0.479 DQB1*0202 6 (15.79%) 15 (36.59%) 0.77 0.665 0.56 0.15-2.0 0.369 DQB1*0301 14 (36.84%) 15 (36.59%) 1.01 0.981 1.18 0.44-3.2 0.744 DQB1*0302 13 (34.21%) 11 (26.59%) 1.42 0.476 1.46 0.50-4.34 0.491 DQB1*0303 2 (5.26%) 2 2 (4.88%) 1.1 *1.0 1.04 0.12-8.84 0.973 DQB1*0319 3 (7.89%) 1 (2.44%) 3.43 *0.347 2.61 0.24-28.38 0.431 DQB1*0402 8 (21.05%0 13 (13.71%) 0.57 0.284 0.41 0.13-1.30 0.130 DQB1*0501 7 (18.42%) 9 (21.95%) 0.80 0.697 0.95 0.29-5.15 0.94 DQB1*0502 0 (0%) 1 (2.44%) ***NA *1.0 **NA **NA **0.987 DQB1*0503 0 (0%) 2 (4.88%) ***NA *0.494 **NA **NA **0.981 DQB1*0602 6 (15.79%) 2 (4.88%) 3.66 *0.145 3.05 0.52-17.93 0.216 DQB1*0603 4 (10.53%) 8 (19.51%) 0.49 0.266 0.71 0.18-2.87 0.631 DQB1*0604 1(2.63%) 2 (4.88%) 0.53 *1.0 1.56 0.12-21.04 0.738 DQB1*0609 1 (2.63%) 2 (4.88%) 0.53 *1.0 0.12 0.01-1.80 0.125

SAS Analysis of Class II Alleles (Case-Control Set #1 & #2)

HLA antigens data were analyzed using PROC LOGISTIC in the SAS software package

(Version 9.1) for Windows. Logistic regression was used to calculate exposure odds ratios (OR).

Statistical significance of the crude OR was assessed using a chi-squire or Fisher’s exact test as

appropriate. To clarify, if one or more of the expected cell counts was less than 5, then the p-value

from the Fisher’s exact test was reported. A result was considered statistically significant if the p-

value was 0.05 or less. After univariate analyses, ORs were adjusted for age and sex. Ninety-five

percent confidence intervals (CI) were also calculated. At times a quasi-complete separation of the

data points was detected during a multivariate analysis and hence the validity of the model fit was

questionable. In these situations the reader is alerted to this fact. The reason for this numerical

problem was the presence of a zero cell frequency (e.g., all of the cases were exposed/had the

antigen). The HLA Class II alleles typing data used in analysis, which are listed in Appendix: H.

Results of Class II Alleles (Case-Control Set #1 & #2)

Table 34 shows that the Class II of HLA-DRB1 alleles: crude OR ranged from 0.16-3.66

(p=0.11-1.0) and the adjusted OR for age and sex ranged from 0.30-3.26 (p=0.16-0.987).

DRB1*0407 OR suggestive of susceptible association with T2DM in the univariate analysis

(crude OR 2.23 (p=0.18) and was not associated with T2DM in the multivariate analysis which

controlled for age and sex (adjusted OR=1.64, p=0.47).

DRB1*1501 OR suggestive of susceptible association with T2DM in the univariate analysis

(crude OR 3.66 (p=0.15) and was not associated with T2DM in the multivariate analysis which

controlled for age and sex (adjusted OR=3.05, p=0.22).

DRB1*0402 OR suggestive of protective association with T2DM in the univariate analysis

(crude OR 0.16 (p=0.11) and was not associated with T2DM in the multivariate analysis which

controlled for age and sex (adjusted OR=0.30, p=0.29)

DRB1*0802 OR suggestive of protective association with T2DM in the univariate analysis

(crude OR 0.49 (p=0.17) and was also OR suggestive of protective associated with T2DM in the multivariate analysis which controlled for age and sex (adjusted OR=0.44, p=0.16).

Table 35 shows that the Class II of HLA-DQA1 alleles: crude OR ranged from 0.62-2.47

(p=0.16-1.0) and the adjusted OR for age and sex ranged from 0.54-2.02 (p= 0.30-0.99).

DQA1*0501 OR suggestive of susceptible association with T2DM in the univariate analysis

(crude OR 2.47 (p=0.16) and was not associated with T2DM in the multivariate analysis which controlled for age and sex (adjusted OR=2.02, p=0.32).

Table 36 shows that the Class II HLA-DQB1 alleles: crude OR ranged from 0.49-3.66

(p=0.15-1.0) and the adjusted OR for age and sex ranged from 0.12-3.05 (p=0.13-0.99).

DRB1*0602 OR suggestive of susceptible association with T2DM in the univariate analysis

(crude OR 3.66 (p=0.15) and was not associated with T2DM in the multivariate analysis which

controlled for age and sex (adjusted OR=3.05, p=0.22).

Discussion

This study has shown statistically significant susceptible or protective association with selective Class I and Class II antigens and Alleles in a Mexican American (MA) ethnic group, with type 2 diabetes mellitus (T2DM) in the El Paso, Texas region.

Results of this preliminary study provide information to support efforts to further explore the association of HLA Class I, Class II antigens, and Class II alleles with T2DM among MA.

This study consists of three research questions divided into two parts: Part I was a serological

analysis of Class I and Class II antigens (whenever possible unclear HLA antigens were confirmed

by SSP-DNA methods). The HLA antigens data was derived from Sierra Medical Center, El Paso,

Texas; 330 Mexican American subjects (110 cases and 196 controls #1 = group A and 24 controls

#2 = group B) were included. Part II of the study was an analysis of HLA alleles (rSSO methods)

and the data was obtained from 79 Mexican Americans subjects (38 cases and 41 controls). The data

were analyzed using PROC LOGISTIC in the SAS software version 9.1 for Windows. Logistic regressions were used to calculate crude and adjusted OR for age and sex, chi-square or Fisher’s

Exact Test p-value calculated with the binary outcome for T2DM for Class I (HLA- A, HLA-B,

HLA-C), Class II (HLA- DR, DQ) antigens (Part I), and Class II (DRB1*, DQA1*, DQB1*) alleles

(Part II).

HLA Class I (HLA-A, HLA-B and HLA-C locus) antigens (Case-Control #1, group A):

Mathematically there was no confounding with crude OR as compared with Adjusted OR, but this definition was considered too strict for practical purpose (Greenland, 1989). When the estimated crude OR was compared with adjusted OR differed by 10% or more. In such observations the epidemiologists considered confounding to be present, and an adjustment for one or more variables not a matter of concern (Greenland, 1989).

The HLA-A3 antigen showed statistically significant protective association with T2DM, the

crude OR = 0.44, p = 0.03 and when adjusted for age and sex the OR = 0.39, p = 0.04 (95% confidence interval (CI), 0.16-0.96). The results of HLA-A80 antigen did not indicate susceptible association with T2DM in the crude OR= 3.6 with p-value of 0.29. However, when it was adjusted for age and sex OR = 10.72, p = 0.083 (95% CI, 0.73-156.8) a discernable association with T2DM was evident. In these studies, it was interesting to note that the susceptibility was more pronounced when adjusted for age and sex, indicating a confounding effect of disease and antigens association.

The HLA-B35 antigen showed statistically significant protective association with T2DM.

The crude OR = 0.57, p = 0.036 and adjusted age and sex OR = 0.51, and p = 0.031 (95% CI, 0.28-

0.94). The HLA-B44 antigen did not demonstrate significant susceptible association with T2DM with crude OR=1.8 and p-values= 0.08, but there was a statistically significant association with

T2DM when OR was adjusted with age and sex (OR = 2.7, p = 0.021, 95% CI, 1.14-4.91). The

HLA-B49 antigen showed a similar pattern having no statistically significant susceptible association with T2DM in the crude OR = 3.0, p = 0.07, but a statistically significant association with T2DM when adjusted for age and sex (OR = 3.53, p = 0.050, 95% CI, 1.0-12.46). The observations were similar in HLA-B50 antigen also, where susceptible association with T2DM was not significant association in the crude OR = 2.11, p = 0.15, but when the values were adjusted for age and sex, there was a statistically significant association with T2DM (OR = 3.40, p = 0.047, 95% CI, 1.02-

11.39).

The HLA-C5 antigen showed statistically significant susceptible association with T2DM when adjusted for age and sex (OR = 2.26, p = 0.048, 95% CI, 1.01-5.08), but it did not show statistically significant association in the crude OR = 1.68, p = 0.15.

The overall sample size (N= 110 cases and N=196 controls #1) was enough to find

statistically significant OR risk at α = 0.05; p-value and power (1- β) = 80% in two-sided hypothesis

testing (Gordis, 2004).

HLA Class I (HLA-A, HLA-B and HLA-C locus) antigens (Case-Control #2, group B):

The HLA-A2 antigen showed statistically significant protective association with T2DM in the crude OR = 0.18, p = 0.0013 (95% CI, <0.001-20.43), but it was not shown when adjusted with age and sex (OR = 0.10, p = 0.08).

The HLA-A25 antigen showed statistically significant protective association with T2DM.

The crude OR was 0.13 with a p-value of 0.040. However, when it was adjusted with age and sex, it did not demonstrate a statistically significant susceptible association with T2DM (OR= 3.5, p-value was 0.479, 95% CI, 0.11-114.05).

The HLA- A28 antigen showed statistically significant protective association with T2DM when adjusted for age and sex (OR = 0.01, p = 0.004, 95% CI, <0.001-0.24). But it did not show significant association with crude OR =0.40, p = 0.203. It showed confounding factor with age and sex.

The HLA-B35, B56 and B57 antigens showed similarly statistically significant protective association when adjusted for age and sex (OR = 0.23, p = 0.054, 95% CI, 0.05-0.1.02); OR = 0.005, p = 0.0038 (95% CI, <0.001-0.19); OR = 0.081, p = 0.0215 (95% CI, 0.009-0.69), respectively, but no significant association with crude OR = 0.59, p = 0.275, crude OR = 021, p = 0327 and crude OR

= 0.26, p = 0.109, respectively.

The HLA- C antigen showed no association of protective or susceptible association with

T2DM, most likely due to sample size of control #2.

The overall sample size (N= 110 cases and N=24 controls #2) had enough case subjects – but

not control #2 – to find statistically significant OR risk at α = 0.05 p-value and power (1- β) = 80% in two-sided hypothesis testing (Gordis, 2004). It was interesting to note that in this group B, the protective associations observed were more greater than those in group A.

HLA Class II (HLA-DR, and HLA-DQ locus) Antigens (Case-Control #1, Group A):

The HLA-DR2 antigen was suggestive of protective association with T2DM in the Crude OR

and adjusted OR for age and sex.

The HLA-DR14 antigen also was suggestive of susceptible association with T2DM in the

crude OR. However, when adjusted for age and sex association with T2DM was not seen..

The HLA-DQ antigens were not indicative of any significant protective or susceptible

association with T2DM. This observation was not limited by sample size, as overall sample size (n

= 110 cases and n = 196 controls #1) had enough subjects to find statistically significant OR risk at α

= 0.05 p-value and power (1- β) = 80% in two-sided hypothesis testing (Gordis, 2004).

HLA Class II (HLA-DR, and HLA-DQ locus) Antigens (Case-Control #2, Group B:

The HLA-DR2 antigen was suggestive of protective association with T2DM in the Crude OR when adjusted OR for age and sex.

The HLA-DR17 antigen was suggestive of susceptible association with T2DM in the crude

OR when adjusted for age and sex this was also suggestive of susceptible associated with T2DM.

The HLA-DQ1 antigen was not associated with T2DM in the crude OR. However, adjusted

OR which controlled for age and sex, demonstrated a protective association was observed.

The HLA- DQ6 and DQ8 antigens showed crude p = 0.024 and p = 0.014, respectively, but crude OR is not available due to 0 (0%) in the controls. The overall sample size (N= 110 cases and

N=24 controls #2) was not large enough for control subjects to find statistically significant OR risk

at α = 0.05 p-value and power (1- β) = 80% in two-sided hypothesis testing (Gordis, 2004).

HLA Class II (HLA- DRB1*, HLA-DQA1* and HLA-DQB1* locus) alleles (Case-Control,

Set #1 and #2):

HLA Class II alleles study consisted of 38 case (T2DM) subjects (48.10%) and 41 control

(without T2DM and without history of T2DM) subjects (51.90%).

DRB1*0407 OR was suggestive of susceptible association with T2DM in the crude OR but not in the adjusted OR which controlled for age and sex.

DRB1*1501 OR was suggestive of susceptible association with T2DM in the crude OR but

not in the adjusted OR which controlled for age and sex.

DRB1*0402 OR was suggestive of protective association with T2DM in the crude OR but

not in the adjusted OR which controlled for age and sex.

DRB1*0802 OR was suggestive of protective association with T2DM in the crude OR and

was also OR suggestive of protective associated with T2DM in the adjusted OR when controlled for

age and sex.

DQA1*0501 was OR suggestive of susceptible association with T2DM in the crude OR but

not in the adjusted OR which controlled for age and sex.

DRB1*0602 OR suggestive of susceptible association with T2DM in the crude OR and was

not associated with T2DM in the adjusted OR which controlled for age and sex.

The overall sample size (n= 38 cases and n= 41 controls) did not have enough subjects to

find a statistically significant OR risk at α = 0.05 p-value and power (1- β) = 80% in two-sided

hypothesis testing (Gordis, 2004).

These observations provided strong support that polymorphic genetic factors are involved in the pathogenesis of these disorders. They also established HLA markers as being powerful tools in unraveling the genetics of the conditions. These studies add credibility to earlier observations that the HLA susceptibility to type 1 diabetes mellitus was positively associated with Class I antigens,

HLA-B8 and B15, and negatively associated with, HLA-B7. Moreover, it appeared that HLA-B8/15 heterozygosity was associated with a higher risk than other genotypes. This suggested the existence of two different susceptibility factors that interact in those carrying both antigens (Thomsen &

Bodmer, 1977). This conclusion has not changed with the subsequent discovery that these Class I associations are due to linkage disequilibrium with Class II factors (HLA-B8 with DR3, B15 with

DR4 and DQ8), and B7 with DR2). Previous studies with serologic antigens showed an association with T2DM and Class I antigens (Dittmer, Woodfield, & Simpson, 1998; Omar, Hammond, Motala,

& Seedat, 1988; Williams, Knowler, Butler, Pettitt, Lisse, Bennett, et al., 1981) but not Class II antigens (Dittmer, Woodfield, & Simpson, 1998) in non-European populations (Omar, Hammond,

Motala, & Seedat, 1988; Jabbar, Mezaal, & Dawood, 1989). Also two studies in Finnish subjects showed Class I and Class II antigens were associated with T2DM (Groop, Miettinen, Groop, Meri,

Koskimies, & Bottazzo, 1988) antigens were associated with T2DM and HLA-A2 association with

T2DM in Pima Indians (Williams, Knowler, Butler, Pettitt, Lisse, Bennett, et al., 1981).

Another important advancement in understanding the genetics of HLA-associated disorders was the realization that HLA-associated genes in patients are identical to those present in healthy individuals; the associations are not due to rare mutations (Svejgaard, Platz, Ryder, Nielsen, &

Thomsen, 1975). It has also become clear that not all individuals carrying a disease-associated factor develop the condition in question. This may be attributed to the existence of as yet unknown HLA genes, which must then be in linkage disequilibrium with the genes now known to be associated

and/or to the fact that very few of the HLA-associated diseases are classical genetic diseases. The diseases are not inherited as such; it is the susceptibility that was inherited with HLA factors as

genetic markers (Tiwari & Terasaki, 1985, Lechler & Warrens, 2000).

In exploring causality regarding the presence of certain HLA antigens and their association

with T2DM outcome, this study identified certain protective and susceptible associations. However,

the associations alone do not constitute a cause-effect relationship for definitive manifestation of the

disease. While the study was able to demonstrate a genetic link between certain antigens and T2DM

as a predictive factor, it does not present evidence of cause and effect. Future studies are required;

especially those that would elucidate the biological plausibility of these HLA antigen and allele

associations as a causal effect of T2DM (Hennekens, Buring, & Mayrent, (Ed), 1987).

The pathogenesis in Type 2 diabetes was by both insulin resistance and an insulin secretory

defect. (DeFronzo, Ferrannini & Simonson, 1989; Porte & Kahn, 2001). The reports indicate that the

pathogenesis was manifested by an impairment of postprandial glucose uptake by muscle with

endogenously secreted insulin (Mitrakou, Kelley,Veneman, Jenssen, Pangburn, Reilly et al., 1997;

Ferarannini, Simonson, Katz, Reichard, Bevilacqua, Barrett, et al., 1988). In patients with fasting

hyperglycemia (having Type 2 diabetes) insulin levels have been found to be twofold to fourfold

higher than in non-diabetics (DeFronzo, Ferrannini & Simonson, 1989). The present study had

addressed only genetic factors for the cause of Type 2 diabetes. The pathogenesis of the disease

caused by both insulin resistance and an insulin secretory defects falls beyond the scope of this study

(DeFronzo, Ferrannini & Simonson, 1989; Porte & Kahn, 2001). The present study while

addressing the genetic involvement, did not lend much scope to the study of pathogenesis in detail.

Other researchers have found that there are defects in receptor function, insulin receptor-signal

transduction pathway, glucose transport and phosphorylation, glycogen synthesis, and glucose

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oxidation in muscle tissue that contribute to insulin resistance (DeFronzo, 1997). Further studies are

needed to address the basal rates of hepatic gluconeogenesis, which were reported to be excessive,

despite elevated insulin levels. Both genetic factors and the metabolic defects contribute equally to

excessive postprandial serum glucose levels (Ferarannini, Simonson, Katz, Reichard, Bevilacqua,

Barrett, et al., 1988). This study has provided insight into the role of genetic factors (HLA Antigens)

in inducing the Type 2 diabetes. However, the role of pathogenic factors cannot be ignored.

The disadvantages of individual matching study are (1) Individual matching in case-control

study, the selection bias introduced by the matching process can occur whether or not there is

confounding by the matched factors in the source population. (2) Individual matching, often each

matched set is treated as a distinct stratum if a stratified analysis is conducted. Individual case-

control matching study increase cost.

The potential problem in my study was a case-control study can be inefficient for the

evaluation of rare exposure, unless the attributable-risk percent is high. It cannot directly compute

incidence rates of disease in exposed and non-exposed individuals, unless the study is population

based. In some situations, the temporal relationship between exposure and disease may be difficult to establish. It is particularly prone to bias compared with other analytic designs, such as selection and recall bias. It does not prevent confounding.

In Part I of my study a potential problem in my study was included only Mexican American

population and the HLA class I and Class II antigens data will be derived from the type 2 diabetes

mellitus with end stage renal disease patient (case) and donor (control) from kidney transplant

program at Sierra Medical Center collected for Kidney Transplant program, all demographic

information collected by Sierra Transplant Clinic, the inclusion and exclusion criteria obtained

archived database of Transplant Immunology Laboratory of Sierra Medical Center. Also the

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serology typing method optimum typing yields are dependent on proper expression of the target antigen on the surface of the cell.

The part II of study will revise with the frozen samples will be obtained from Apo-E study.

The type 2 diabetes mellitus without end stage renal disease patient (case) and donor (control) of about 30 cases and 30 controls. Additional 10 (cases) and 12 (controls) frozen samples with end stage renal disease will be included. The LABType rSSO system combines an HLA locus specific

DNA amplification process and DNA-DNA hybridization process. The procedure, as well as the equipment calibration described in this product, must be strictly followed. In comparison of other assays like HLA-DNA-SSP, the rSSO has more ambiguities because the probes used in rSSO can discriminate sample DNA at only one region per test, and SSP can discriminate sample DNA at two regions per test. This is a basic limitation of the rSSO method.

Advantage of case-control study is relatively quick and inexpensive compared with other analytic designs. It can examine multiple etiologic factors for singe disease. It enhanced efficiency that it sometimes affords for the control of confounding. Disadvantages of the use of individual matching in a case-control study can be inefficient for the evaluation of rare exposure, unless the attributable-risk percent is high. It cannot directly compute incidence rates of disease in exposed and non-exposed individuals, unless study is population based. In some situations, the temporal relationship between exposure and disease may be difficult to establish. It is particular prone to bias compared with other analytic designs, in particular selection and recall bias. It does not prevent confounding.

In my proposal I am only looking HLA antigen and alleles association with T2DM. HLA system is the single strongest association with T1DM. A history of T2DM in a first-degree relative doubles the risk of T1DM.

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Multivariate analysis allows for the efficient estimate of measures of association while

controlling for number of confounding factors simultaneously, even in situation where stratification

would fail because of insufficient numbers. In general, a multivariate technique refers to any analysis

of data that takes into account a number of variables simultaneously. All types of multivariate analysis involve the construction of a mathematical model to describe most efficiently the association between exposure and disease as well as other variables that may be confound or modify the effect of exposure. The common way that many factors are controlled for simultaneously is through the use of multiple regression models.

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Limitations, Problems, and Future Study

A potential problem is that a case-controlled study such as this could be inefficient for the

evaluation of rare exposure, unless the attributable-risk percent would be high. Unless the study is

population based, it cannot directly compute incidence rates of disease in exposed and non-exposed

individuals. In some situations, the temporal relationship between exposure and disease may be

difficult to establish. It would be particularly prone to bias compared with other analytic designs, in

particular selection and recall bias. It would not prevent confounding.

Mexican American populations were the study subjects. The samples were derived from

T2DM with end-stage renal disease for serological analysis (part I) and for the allelic study of the

subjects derived from Apo-E study where T2DM patients had no end stage renal disease (part II, set

1). This set comprises of 28 cases and 29 control frozen samples. Additional 10 (cases) and 12

(controls) frozen samples with end stage renal disease were included (part II, set 2). All patient and

donor demographic information for serologic data was derived from the self-reported information provided to the transplant clinic of Sierra Medical Center. Due to self-reported there is no way to

confirm the accuracy of reported race/ethnicity information.

At the methodology level, the universal limitation to a serological typing is the cell surface

antigen expression; for allelic analysis, the LABType rSSO system combines an HLA locus specific

DNA amplification process and DNA-DNA hybridization process. The procedure, as well as the

equipment calibration described in this product, must be strictly followed. In comparison to other

assays like HLA-DNA-SSP, the rSSO has more ambiguities, because the probes used in rSSO can

discriminate sample DNA at only one region per test, and SSP can discriminate sample DNA at two

regions per test. This was a basic limitation of the rSSO method.

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The advantage of a case-controlled study was that the results can be obtained relatively quickly and inexpensively as compared to other analytic designs. Also, it would be possible to examine multiple etiologic factors for a singe disease. Because of its greater efficiency, it may sometimes help to control confounding.

The study’s focus was to look at HLA antigens and alleles in association with T2DM. The

HLA system has the single strongest association with T1DM. A history of T2DM in a first-degree relative doubles the risk of T1DM.

The present study would provide the preliminary data to conduct future studies such as:

1. To explore the high resolution alleles typing for Class II (HLA-DRB1*, DQA1*, DQB1*,

and DPB1* Locus) alleles among Mexican Americans comparing other ethnic groups.

2. Determine the association of the HLA-BW4*, HLA-C* locus, KIR*, and MICA* alleles

among MAs with and without T2DM.

3. Investigate the inheritance of HLA Class I and Class II antigens haplotypes in the family

members with T2DM.

4. Explore the HLA Class I and Class II alleles in obese children to determine an early

diagnosis and prevention.

5. Conduct a large scale study to examine HLA Class I and Class II high resolution sequencing

typing alleles association with type T2DM in Mexican Americans.

6. To explore the metabolic profile, hemoglobin A1c (HgA1c), cholesterol, triglyceride, C-

reactive protein, urine protein levels, anti-glutamic acid decarboxylase (GAD), and islet cell

autoantibody among MAs with and without T2DM.

7. In an effort to improve accuracy of race/ethnicity data, collection of full family, including

parents and grandparents, information is recommended for future studies.

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This study serves as a foundation for the early diagnosis and or prevention of T2DM

for this high risk MA population. Given escalating healthcare costs, any studies leading to the prevention of chronic disease would tremendously benefit the community in general and, more particularly, the susceptible population.

106

Summary and Conclusions

Summary:

Methodology of this case-controlled study was divided into two parts: Part I focused on data

analysis for HLA-A, B, C, DR, and DQ antigens in association with T2DM. The study – which

consisted of 110 cases, 196 controls #1 (without family history of T2DM), and 24 controls #2 (with

family history of T2DM) – analyzed historical serological HLA data derived from the Sierra Medical

Center, Transplant Immunology Laboratory.

Part II of the study involved 57 frozen samples derived from a previous study conducted at

The University of Texas at El Paso. Additional testing and analysis included 22 frozen blood

samples that were derived from Sierra Medical Center, El Paso, Texas.

The HLA-DNA allele tests were performed at Las Palmas Medical Center using Genomic

DNA extracted from human leukocytes. Extracted DNA was used for identifying HLA DRB1*,

DQA1*, and DQB1* alleles. The process included reverse sequence-specific oligogonucleotide probes (rSSO) methodology was employed in the study using LABType, Luminex technology that discriminates between the different alleles. Following a polymerase chain reaction (PCR) process, the amplified DNA product was biotinylated, which allows detection though the use of R-

Phycoerythrin-conjugated Strepavidin (SAPE).

The data were analyzed using PROC LOGISTIC in the SAS software version 9.1 for

Windows. Logistic regression was used to calculate crude and adjusted OR, chi square, and p-value

with the binary outcome for T2DM.

The results of SAS analysis showed statistical significance protective and susceptible

association with controls and T2DM. The protective association showed with T2DM and control #1

(without T2DM and without history of T2DM) for HLA-A3 antigen (crude OR = 0.44, p = 0.03 and

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adjusted for age and sex OR = 0.39, p = 0.041. HLA- B35 antigen (crude OR = 0.57, p = 0.036 and

adjusted for age and sex OR = 0.51, p = 0.031). The susceptible association with T2DM and control

#1 for HLA- B44, B49, B50, and C5 antigens with adjustment for age and sex (OR = 2.37, p =

0.021; OR= 3.53, p = 0.050; OR= 3.40, p = 0.047; OR = 2.26, p = 0.048, respectively), and not significant association with crude OR.

The protective association showed with controls #2 (without T2DM and with family history of T2DM) and T2DM. The HLA-A2 antigen (crude OR= 0.18, p = 0.013) had no statistically significant association with adjusted for age and sex OR. The HLA-A28, B-56, B57, and DQ1 antigens showed statistically significant protective association with adjusted for age and sex (OR=

0.01, p = 0.004; OR= 0.005, p = 0.004; OR= 0.081, p = 0.0215; OR= 0.16, p = 0.044, respectively) and no significance association with the crude OR. All these association has showed confounding factor with age and sex with case-control #1 and case-control #2. Case-control of allelic analysis did not show a statistically significant protective or susceptible association with T2DM, perhaps due to smaller sample size.

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Conclusions

This study clearly demonstrated that there was evidence for high prevalence of type 2 diabetes mellitus (T2DM) in the Mexican American population of El Paso, Texas region. There was statically significant susceptible or protective association with Class I (HLA-A, B, and C locus) antigens. The study revealed that the association was more pronounced with certain HLA-A, HLA-

B, and HLA-C antigens. The Class II (HLA-DR and DQ locus) antigenic analysis showed minor

HLA-DR and HLA-DQ antigens association with T2DM. The HLA Class II alleles had not revealed a statistically significance association with T2DM for DRB1*, DQA1*, and DQB1* possible, due to smaller samples size. A larger study would be needed to address for Class II alleles and haplotype distribution of T2DM among Mexican Americans (MA) and to confirm the susceptible or protective association of the Class II alleles and haplotypes with the T2DM pathogenesis and of the response to therapy.

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Abbreviations

AABB- American Association of Blood Banks Ab- antibody ACD- acid (trisodium) citrate dextrose Ag- antigen ABHI- American board of histocompatibility and immunogenetics AIDS- acquired immunodeficiency syndrome ASHI- American Society for Histocompatibility and Immunogenetics APA- American Psychological Association BMI- body mass index CDC Centers for Disease Control and Prevention DNA- deoxyribose nucleic acid dNTP- deoxyribonucleotide triphosphate DR- D locus related antigen EB- ethidium bromide EDTA- ethylene diamine tetraacetic acid ESRD- end stage renal disease Fab- antigen-binding fragment Fc- crystallizable fragment GFR- glomerular filtration rate G1M- gamma globulin light chain genetic marker GREG- cross-reactive groups HCL- hydrochloric acid HDL- high density cholesterol HIV- human immunodeficiency virus HLA- human leukocyte antigen Ig- immunoglobulin IGT- impaire glucose tolérance IDDM- insulin-dependent diabetes mellitus (T1DM) IIDM- insulin Independent diabetes mellitus (T2DM) IR- insulin resistance

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IRB- institutional review board DKA- diabetes ketoacidosis LD- linkage disequilibrium LDL- low density cholesterol LPMC- Las Palmas Medical Center MA- Mexican Americans MAB- monoclonal antibody MHC- major histocompatibility complex MI- myocardial infraction MS- metabolic Syndrome NA not available NC- negative control NK- natural killer NIDDM non-insulin-dependent diabetes mellitus (T2DM) OR- odds ratio PC- positive control PCR- polymerase chain reaction RBC- red blood cell RT- room temperature RSSO- reverse sequence specific oligonucleotide SAS- statistical analysis system SD- standard deviation SPSS- Statistical Package for the Social Sciences SSP- sequence specific primers SMC- Sierra Medical Center SPHN- Sierra Providence Health Network Taq- thermos aquaticus (polymerase) T2DM- type 2 diabetes mellites T1DM- type 1 diabetes mellitus TBE Tris base Boric acid Ethylene diamine tetraacetic acid UV- ultra violate WBC- white blood cell WHO- World Health Organization

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Title of Appendix

Appendix A: Demographic data and HLA Class I antigens

No Age Sex Race Subjects A1 A2 B1 B2 C1 C2

1 57 F MA Case 2 33 49 51 7 9 2 69 F MA Case 2 3 44 61 2 5 3 42 F MA Case 24 25 35 39 4 7 4 48 M MA Case 32 68 44 5 5 54 M MA Case 3 31 7 39 7 6 56 F MA Case 3 33 7 65 7 8 7 65 M MA Case 11 24 35 4 8 44 F MA Case 24 61 62 3 9 68 M MA Case 24 31 35 39 4 7 10 57 M MA Case 1 68 7 8 7 11 62 F MA Control 1 23 8 7 12 58 M MA Control 24 25 35 51 4 9 13 51 F MA Control 2 24 37 61 3 6 14 47 M MA Control 24 68 35 39 4 7 15 45 F MA Control 3 25 38 47 16 52 M MA Control 24 68 39 48 7 8 17 55 M MA Control 2 51 61 3 8 18 43 F MA Control 24 68 35 48 4 8 19 60 M MA Control 2 23 14 8 20 43 F MA Control 31 35 61 3 4 21 40 M MA Control 2 31 38 61 3 22 43 M MA Control 1 24 7 48 7 8

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Appendix B: Demographic data and HLA Class II antigens

NO Age Sex Race Subjects DR1 DR2 DQ1 DQ2

1 57 F MA Case 8 13 2 4 2 69 F MA Case 1 15 5 6 3 42 F MA Case 8 4 4 48 M MA Case 1 9 5 9 5 54 M MA Case 13 14 6 7 6 56 F MA Case 11 15 1 7 7 65 M MA Case 4 11 7 8 8 44 F MA Case 13 14 6 7 9 68 M MA Case 8 14 4 7 10 57 M MA Case 15 17 2 6 11 62 F MA Control 17 13 2 4 12 58 M MA Control 8 9 4 9 13 51 F MA Control 8 10 4 5 14 47 M MA Control 8 14 4 7 15 45 F MA Control 4 13 1 3 16 52 M MA Control 8 14 4 7 17 55 M MA Control 4 3 18 43 F MA Control 4 11 7 8 19 60 M MA Control 1 7 2 5 20 43 F MA Control 4 14 7 8 21 40 M MA Control 8 13 1 4 22 43 M MA Control 8 15 4 6

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Appendix C: HLA Class I Antigens Nomenclature

Locus Antigens A 1 2 3 9 10 1119 23 24 25 26 28 A 29 30 31 32 33 3436 43 66 68 69 74 A 80 B 5 7 8 12 13 1415 16 17 18 21 22 B 27 35 37 38 39 4041 42 44 45 46 47 B 48 49 50 4005 51 5253 54 55 56 57 58 B 59 60 61 62 63 6465 67 70 71 72 73 B 75 76 77 78 82 C 1 2 3 4 5 67 8 9 10 12 14 C 15 16 17

Appendix D: HLA Class II Antigens Nomenclature

Locus Antigens DR 01 103 02 03 04 05 06 07 08 09 10 DR 11 12 13 14 15 16 17 18 DQ 01 02 03 04 05 06 07 08 09

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Appendix E: HLA Class II (DRB1) Alleles Nomenclature (1 of 2)

Chain Alleles DRB1* 0101 0102 0103 0104 0105 0106 0107 DRB1* 0108 0109 0110 0111 0112 0113 0114 DRB1* 0115 0116 0301 0302 0303 0304 0305 DRB1* 0306 0307 0308 0309 0310 0311 0312 DRB1* 0313 0314 0315 0316 0317 0318 0319 DRB1* 0320 0321 0322 0323 0324 0325 0326 DRB1* 0327 0328 0329 0330 0331 0332 0333 DRB1* 0334 0335 0336 0337 0338 0339 0340 DRB1* 0401 0402 0403 0404 0405 0406 0407 DRB1* 0408 0409 0410 0411 0412 0413 0414 DRB1* 0415 0416 0417 0418 0419 0420 0421 DRB1* 0422 0423 0424 0425 0426 0427 0428 DRB1* 0429 0430 0431 0432 0433 0434 0435 DRB1* 0436 0437 0438 0439 0440 0441 0442 DRB1* 0443 0444 0445 0446 0447 0448 0449 DRB1* 0450 0451 0452 0453 0454 0455 0456 DRB1* 0457 0458 0459 0460 0461 0462 0463 DRB1* 0464 0465 0466 0467 0468 0469 0470 DRB1* 0471 0472 0473 0474 0475 0476 0477 DRB1* 0478 0701 0703 0704 0705 0706 0707 DRB1* 0708 0709 0710N 0711 0712 0713 0714 DRB1* 0715 0801 0802 0803 0804 0805 0806 DRB1* 0807 0808 0809 0810 0811 0812 0813 DRB1* 0814 0815 0816 0817 0818 0819 0820 DRB1* 0821 0822 0823 0824 0825 0826 0827 DRB1* 0828 0829 0830 0831 0832 0833 0834 DRB1* 0835 0836 0901 0902 0903 0904 0905 DRB1* 0906 0908 1001 1002 1003 1101 1102 DRB1* 1103 1104 1105 1106 1107 1108 1109 DRB1* 1110 1111 1112 1113 1114 1115 1116 DRB1* 1117 1118 1119 1120 1121 1122 1123 DRB1* 1124 1125 1126 1127 1128 1129 1131 DRB1* 1132 1133 1134 1135 1136 1137 1138 DRB1* 1139 1140 1141 1142 1143 1144 1145 DRB1* 1147 1148 1149 1150 1151 1152 1153 DRB1* 1154 1155 1156 1157 1158 1159 1160 DRB1* 1161 1163 1164 1165 1166 1167 1168 DRB1* 1169 1170 1201 1202 1203 1204 1205 DRB1* 1206 1207 1208 1209 1210 1211 1212 DRB1* 1213 1214 1215 1216 1218 1301 1302 DRB1* 1303 1304 1305 1306 1307 1308 1309 DRB1* 1310 1311 1312 1313 1314 1315 1316

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Appendix E: HLA Class II (DRB1) Alleles Nomenclature (2 of 2)

Chain Alleles DRB1* 1317 1318 1319 1320 1321 1322 1323 DRB1* 1324 1325 1326 1327 1328 1329 1330 DRB1* 1331 1332 1333 1334 1335 1336 1337 DRB1* 1338 1339 1340 1341 1342 1343 1344 DRB1* 1345 1346 1347 1348 1349 1350 1351 DRB1* 1352 1353 1354 1355 1356 1357 1358 DRB1* 1359 1360 1361 1362 1363 1364 1365 DRB1* 1366 1367 1368 1369 1370 1371 1372 DRB1* 1373 1374 1375 1376 1377 1378 1379 DRB1* 1381 1382 1383 1384 1385 1386 1387 DRB1* 1401 1402 1403 1404 1405 1406 1407 DRB1* 1408 1409 1410 1411 1412 1413 1414 DRB1* 1415 1417 1418 1419 1420 1421 1422 DRB1* 1423 1424 1425 1426 1427 1428 1429 DRB1* 1430 1431 1432 1433 1434 1435 1436 DRB1* 1437 1438 1439 1440 1441 1442 1443 DRB1* 1444 1445 1446 1447 1448 1449 1450 DRB1* 1451 1452 1453 1454 1455 1456 1457 DRB1* 1458 1459 1460 1461 1462 1463 1464 DRB1* 1465 1466 1467 1468 1469 1470 1471 DRB1* 1472 1473 1474 1475 1476 1477 1478 DRB1* 1479 1480 1481 1482 1483 1501 1502 DRB1* 1503 1504 1505 1506 1507 1508 1509 DRB1* 1510 1511 1512 1513 1514 1515 1516 DRB1* 1517N 1518 1521 1522 1523 1524 1525 DRB1* 1526 1527 1528 1529 1530 1531 1601 DRB1* 1602 1603 1604 1605 1607 1608 1609 DRB1* 1610 1611 1612 1613N

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Appendix E: HLA Class II (DQA1) Alleles Nomenclature

Chain Alleles DQA1* 0101 0102 0103 0104 0105 0106 0107 DQA1* 0201 0301 0302 0303 0401 0402 0403N DQA1* 0404 0501 0502 0503 0504 0505 0506 DQA1* 0507 0508 0509 0601 0602

Appendix E: HLA Class II (DQB1) Alleles Nomenclature

Chain Alleles DQB1* 0201 0202 0203 0204 0205 0301 0302 DQB1* 0303 0304 0305 0306 0307 0308 0309 DQB1* 0310 0311 0312 0313 0314 0315 0316 DQB1* 0317 0318 0319 0320 0321 0322 0323 DQB1* 0401 0402 0403 0501 0502 0503 0504 DQB1* 0505 0601 0602 0603 0604 0605 0606 DQB1* 0607 0608 0609 0610 0611 0612 0613 DQB1* 0614 0615 0616 0617 0618 0619 0620 DQB1* 0621 0622 0623 0624 0625 0626N 0627 DQB1* 0628 0629 0630 0631 0632 0633

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Appendix F: HLA Class I Antigens – Control #1 (1 of 7)

ID Race Subjects Age Sex A1 A2 B1 B2 C1 C2 1 MA Control 40 F 26 68 44 48 5 2 MA Control 40 M 2 26 45 49 6 7 3 MA Control 40 M 30 18 71 3 5 4 MA Control 40 F 2 28 40 70 5 MA Control 40 M 2 31 38 61 3 6 MA Control 40 F 2 31 35 39 4 7 7 MA Control 40 F 2 30 8 13 6 7 8 MA Control 40 F 11 24 35 44 9 MA Control 40 M 2 3 48 62 3 3 10 MA Control 40 F 3 30 18 35 4 5 11 MA Control 40 F 2 80 51 58 7 12 MA Control 40 F 11 24 39 44 3 5 13 MA Control 41 M 23 31 44 61 3 4 14 MA Control 41 F 2 24 35 62 1 4 15 MA Control 41 F 3 24 7 57 6 7 16 MA Control 41 M 3 24 38 39 17 MA Control 41 M 2 29 27 50 1 6 18 MA Control 41 F 1 31 7 61 9 7 19 MA Control 41 M 11 26 27 52 2 20 MA Control 41 M 3 68 7 48 7 8 21 MA Control 41 F 11 31 27 61 1 3 22 MA Control 41 F 2 39 50 6 7 23 MA Control 41 F 24 68 51 62 1 24 MA Control 41 M 2 35 39 4 7 25 MA Control 41 F 23 24 35 50 4 6 26 MA Control 41 M 1 31 35 47 4 27 MA Control 41 M 1 30 8 13 6 7 28 MA Control 41 M 2 2 61 48 3 29 MA Control 41 F 2 24 7 35 4 7 30 MA Control 41 F 2 24 39 62 1 7 31 MA Control 42 M 2 30 18 35 32 MA Control 42 F 26 29 18 61 2

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Appendix F: HLA Class I Antigens – Control #1 (2 of 7)

ID Race Subjects Age Sex A1 A2 B1 B2 C1 C2 33 MA Control 42 M 1 36 8 52 7 34 MA Control 42 F 28 29 27 44 35 MA Control 42 F 24 26 35 38 3 36 MA Control 42 M 3 68 7 35 7 37 MA Control 42 F 2 24 35 50 4 6 38 MA Control 42 F 1 11 37 49 6 7 39 MA Control 42 M 3 11 35 38 4 40 MA Control 42 F 2 31 35 67 4 12 41 MA Control 43 M 2 11 18 35 4 7 42 MA Control 43 F 2 24 35 4 43 MA Control 43 F 23 24 7 60 3 7 44 MA Control 43 M 2 11 35 38 4 6 45 MA Control 43 M 28 29 37 62 1 6 46 MA Control 43 M 31 32 7 35 2 7 47 MA Control 43 F 31 35 61 3 4 48 MA Control 43 F 2 24 27 35 2 4 49 MA Control 43 F 24 35 61 50 MA Control 43 M 24 4005 51 3 8 51 MA Control 43 M 2 24 35 50 52 MA Control 43 F 24 30 18 39 5 7 53 MA Control 43 F 2 28 35 53 4 54 MA Control 43 F 24 68 35 48 4 8 55 MA Control 43 F 11 31 39 62 56 MA Control 43 M 1 24 7 48 7 8 57 MA Control 43 F 24 36 18 51 3 58 MA Control 43 M 1 32 37 62 3 6 59 MA Control 44 F 1 2 51 75 3 60 MA Control 44 F 2 31 7 51 61 MA Control 44 F 2 11 21 52 3 62 MA Control 44 F 2 23 35 58 4 7 63 MA Control 44 F 3 25 8 62 3 7 64 MA Control 45 M 2 18 56 1 5

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Appendix F: HLA Class I Antigens – Control #1 (3 of 7)

ID Race Subjects Age Sex A1 A2 B1 B2 C1 C2 65 MA Control 45 F 2 68 39 65 3 8 66 MA Control 45 F 3 25 38 47 67 MA Control 45 F 29 68 44 49 4 7 68 MA Control 45 F 2 24 27 39 1 7 69 MA Control 45 M 30 31 18 27 2 5 70 MA Control 45 F 3 68 35 4 71 MA Control 45 M 3 26 35 44 2 4 72 MA Control 45 M 3 68 61 65 3 8 73 MA Control 45 F 2 25 18 35 74 MA Control 45 F 2 13 35 6 7 75 MA Control 46 F 1 8 52 76 MA Control 46 M 2 29 7 7 77 MA Control 46 F 11 24 35 44 4 78 MA Control 46 M 26 30 13 35 4 79 MA Control 46 M 26 29 27 44 2 5 80 MA Control 46 F 25 32 18 6 7 81 MA Control 46 M 2 68 61 63 82 MA Control 46 F 2 31 44 51 4 5 83 MA Control 46 F 33 68 14 35 84 MA Control 46 M 3 24 7 39 7 85 MA Control 47 F 1 2 8 58 3 7 86 MA Control 47 F 2 74 39 42 7 87 MA Control 47 M 24 68 39 61 3 7 88 MA Control 47 F 2 3 35 51 1 89 MA Control 47 F 2 32 44 48 5 8 90 MA Control 47 F 1 11 8 52 91 MA Control 47 M 1 3 35 57 4 6 92 MA Control 47 M 24 68 35 39 4 7 93 MA Control 47 M 24 34 8 70 3 7 94 MA Control 47 M 3 24 35 62 1 4 95 MA Control 47 M 1 2 37 57 6 96 MA Control 47 M 24 68 45 48 6 8

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Appendix F: HLA Class I Antigens – Control #1 (4 of 7)

ID Race Subjects Age Sex A1 A2 B1 B2 C1 C2 97 MA Control 47 M 1 24 8 35 4 7 98 MA Control 48 M 2 30 35 70 2 4 99 MA Control 48 M 11 30 13 52 6 100 MA Control 48 F 3 24 8 51 7 101 MA Control 48 M 3 23 7 45 4 7 102 MA Control 48 F 32 68 39 63 7 103 MA Control 48 F 3 24 7 51 7 15 104 MA Control 48 F 2 11 21 52 7 105 MA Control 48 F 2 25 18 51 106 MA Control 48 F 11 24 18 27 2 2 107 MA Control 48 F 2 24 15 51 1 15 108 MA Control 48 M 2 31 44 51 4 5 109 MA Control 48 F 24 31 52 62 1 110 MA Control 49 F 3 32 35 63 111 MA Control 49 F 1 2 8 3 7 112 MA Control 49 F 2 39 61 3 7 113 MA Control 49 M 3 23 38 45 6 114 MA Control 49 F 3 33 51 14 8 115 MA Control 49 F 2 29 18 39 116 MA Control 49 F 2 32 35 52 117 MA Control 49 F 2 68 52 62 1 3 118 MA Control 49 F 29 31 35 62 3 4 119 MA Control 49 M 68 68 39 48 120 MA Control 49 F 11 33 44 51 7 121 MA Control 50 F 2 35 44 4 5 122 MA Control 50 F 24 30 7 18 7 123 MA Control 50 M 2 68 39 61 3 4 124 MA Control 50 M 3 11 13 35 4 6 125 MA Control 50 M 2 44 50 5 126 MA Control 50 M 2 23 65 8 127 MA Control 50 M 1 3 7 38 7 128 MA Control 50 M 1 11 8 39

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Appendix F: HLA Class I Antigens – Control #1 (5 of 7)

ID Race Subjects Age Sex A1 A2 B1 B2 C1 C2 129 MA Control 51 F 1 36 44 57 6 130 MA Control 51 F 2 24 37 61 3 6 131 MA Control 51 F 24 26 44 53 132 MA Control 51 F 2 24 39 61 3 7 133 MA Control 51 M 2 49 62 1 7 134 MA Control 51 M 2 32 35 60 135 MA Control 51 F 24 25 41 62 3 136 MA Control 51 F 2 31 51 61 3 137 MA Control 51 M 3 66 41 60 3 17 138 MA Control 51 M 2 30 7 45 6 7 139 MA Control 52 F 2 35 48 4 140 MA Control 52 F 2 11 35 44 4 5 141 MA Control 52 M 24 68 39 48 7 8 142 MA Control 52 F 24 26 44 52 3 5 143 MA Control 52 F 31 31 35 51 4 8 144 MA Control 52 F 2 35 52 4 3 145 MA Control 53 M 1 24 39 51 3 146 MA Control 53 F 2 24 51 61 3 14 147 MA Control 53 F 25 31 18 51 4 148 MA Control 53 M 2 68 13 35 149 MA Control 53 M 2 24 35 48 8 150 MA Control 53 M 3 31 7 35 4 7 151 MA Control 53 F 30 31 18 62 4 5 152 MA Control 53 M 23 74 14 49 153 MA Control 53 F 1 29 35 44 4 154 MA Control 54 F 24 33 35 58 3 4 155 MA Control 54 F 2 30 51 60 8 8 156 MA Control 54 F 2 7 51 7 157 MA Control 54 F 2 33 44 65 5 8 158 MA Control 55 M 2 34 8 62 3 7 159 MA Control 55 F 3 29 8 45 6 7 160 MA Control 55 M 1 2 8 15

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Appendix F: HLA Class I Antigens – Control #1 (6 of 7)

ID Race Subjects Age Sex A1 A2 B1 B2 C1 C2 161 MA Control 55 M 2 18 35 4 162 MA Control 55 M 2 51 61 3 8 163 MA Control 55 F 2 35 57 164 MA Control 55 F 3 30 35 72 2 4 165 MA Control 55 M 2 24 39 7 166 MA Control 55 M 3 26 35 38 4 167 MA Control 55 F 23 31 27 50 168 MA Control 56 M 3 68 18 53 4 169 MA Control 56 M 11 24 37 55 4 7 170 MA Control 56 F 11 68 27 61 1 3 171 MA Control 56 F 24 30 61 72 2 3 172 MA Control 56 M 2 24 27 39 1 7 173 MA Control 56 F 33 66 7 35 4 7 174 MA Control 56 M 2 2 35 46 1 4 175 MA Control 57 F 24 39 7 176 MA Control 58 M 2 23 35 39 4 7 177 MA Control 58 M 24 25 35 51 4 9 178 MA Control 59 F 24 69 35 51 179 MA Control 59 F 1 31 8 35 180 MA Control 59 M 2 28 8 44 7 181 MA Control 60 M 2 23 14 8 182 MA Control 60 F 31 32 51 62 3 3 183 MA Control 61 F 2 7 65 7 8 184 MA Control 61 M 30 68 4005 72 2 3 185 MA Control 61 M 3 30 42 62 3 17 186 MA Control 61 F 23 68 61 65 3 8 187 MA Control 62 F 1 23 8 7 188 MA Control 62 M 1 2 35 57 4 6 189 MA Control 63 M 1 2 7 18 5 7 190 MA Control 64 F 1 24 35 38 4 191 MA Control 64 F 3 24 61 62 3 6

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Appendix F: HLA Class I Antigens – Control #1 (7 of 7)

ID Race Subjects Age Sex A1 A2 B1 B2 C1 C2 192 MA Control 65 M 1 11 35 52 193 MA Control 66 M 2 26 27 2 7 194 MA Control 68 M 23 32 7 51 7 195 MA Control 70 F 1 31 7 35 4 7 196 MA Control 73 M 3 31 44 65 8

Appendix F: HLA Class I Antigens – Control #2

ID Race Subjects Age Sex A1 A2 B1 B2 C1 C2 1 MA Control - FH 21 F 2 25 18 50 2 MA Control - FH 24 F 1 2 8 50 7 3 MA Control - FH 25 F 2 24 44 5 4 MA Control - FH 26 F 28 31 35 65 7 8 5 MA Control - FH 26 M 2 24 49 62 1 7 6 MA Control - FH 26 M 2 24 49 62 1 7 7 MA Control - FH 27 M 2 25 18 50 8 MA Control - FH 27 M 2 24 39 41 9 MA Control - FH 27 M 1 2 8 35 10 MA Control - FH 28 M 2 25 18 50 11 MA Control - FH 33 M 2 24 44 5 12 MA Control - FH 35 F 2 41 62 13 MA Control - FH 35 F 2 24 44 5 14 MA Control - FH 36 F 1 3 7 35 15 MA Control - FH 38 M 2 31 51 61 16 MA Control - FH 42 F 2 24 35 57 4 6 17 MA Control - FH 45 M 2 35 38 4 18 MA Control - FH 45 F 1 2 39 57 7 19 MA Control - FH 45 M 11 68 35 44 4 20 MA Control - FH 45 F 24 28 14 35 21 MA Control - FH 50 F 2 11 7 35 4 7 22 MA Control - FH 53 F 1 2 44 57 5 7 23 MA Control - FH 54 M 2 29 41 44 7 24 MA Control - FH 56 M 2 28 39 56

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Appendix F: HLA Class I Antigens – Cases of T2DM (1 of 4)

ID Race Subjects Age Sex A1 A2 B1 B2 C1 C2 1 MA T2DM 40 M 2 3 44 50 4 6 2 MA T2DM 42 F 24 25 39 35 4 7 3 MA T2DM 42 F 1 2 37 41 6 17 4 MA T2DM 44 F 3 34 53 63 4 7 5 MA T2DM 44 M 24 29 44 61 3 6 MA T2DM 44 F 1 30 8 18 5 7 7 MA T2DM 44 M 2 30 39 42 8 MA T2DM 44 F 24 61 62 3 9 MA T2DM 44 M 24 68 39 61 3 7 10 MA T2DM 44 M 1 30 18 37 5 6 11 MA T2DM 45 F 2 3 35 65 4 8 12 MA T2DM 46 F 1 26 8 44 5 7 13 MA T2DM 46 F 2 68 18 39 5 7 14 MA T2DM 46 F 2 80 49 51 15 MA T2DM 47 M 2 30 50 53 4 16 MA T2DM 47 F 1 24 8 44 2 7 17 MA T2DM 48 M 2 38 44 6 18 MA T2DM 48 M 32 68 44 5 19 MA T2DM 48 F 2 50 51 4 20 MA T2DM 48 F 2 11 7 50 6 7 21 MA T2DM 48 M 24 68 60 61 22 MA T2DM 48 M 33 68 18 62 7 23 MA T2DM 48 F 1 2 8 35 7 24 MA T2DM 49 M 1 30 53 57 4 6 25 MA T2DM 49 M 2 32 39 50 6 7 26 MA T2DM 49 M 2 52 61 12 15 27 MA T2DM 49 M 2 29 44 51 28 MA T2DM 50 M 24 68 39 61 3 7 29 MA T2DM 50 F 3 11 60 65 3 8 30 MA T2DM 50 M 11 24 51 61 31 MA T2DM 51 M 2 23 49 65 7 8 32 MA T2DM 51 M 24 31 35 62 1 3

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Appendix F: HLA Class I Antigens – Cases of T2DM (2 of 4)

ID Race Subjects Age Sex A1 A2 B1 B2 C1 C2 33 MA T2DM 51 M 2 68 8 41 34 MA T2DM 51 M 1 23 44 57 4 7 35 MA T2DM 51 M 24 68 8 39 7 36 MA T2DM 52 M 2 24 18 35 4 5 37 MA T2DM 52 M 2 31 35 44 5 7 38 MA T2DM 52 F 29 7 44 7 16 39 MA T2DM 52 M 26 29 7 14 7 8 40 MA T2DM 52 M 23 32 44 62 41 MA T2DM 52 M 33 14 8 42 MA T2DM 53 F 2 30 18 51 5 43 MA T2DM 53 M 31 35 61 3 4 44 MA T2DM 53 M 31 68 60 3 45 MA T2DM 53 M 2 30 13 62 1 6 46 MA T2DM 53 F 23 24 39 49 7 47 MA T2DM 54 M 1 2 48 55 8 9 48 MA T2DM 54 M 3 31 7 39 7 49 MA T2DM 54 F 30 31 35 45 4 50 MA T2DM 54 M 2 24 7 62 1 7 51 MA T2DM 55 M 2 11 7 35 4 7 52 MA T2DM 55 M 24 68 35 61 3 4 53 MA T2DM 55 M 1 2 49 51 1 7 54 MA T2DM 55 M 2 24 35 62 1 4 55 MA T2DM 55 M 2 24 18 61 3 5 56 MA T2DM 55 F 2 29 44 62 57 MA T2DM 55 M 2 4005 52 3 58 MA T2DM 55 M 2 25 8 49 7 59 MA T2DM 56 M 68 39 7 60 MA T2DM 56 F 3 33 7 65 7 8 61 MA T2DM 56 M 30 68 18 60 5 62 MA T2DM 56 M 2 26 38 44 63 MA T2DM 57 M 2 31 38 62 4 64 MA T2DM 57 M 1 2 8 35 4 7

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Appendix F: HLA Class I Antigens – Cases of T2DM (3 of 4)

ID Race Subjects Age Sex A1 A2 B1 B2 C1 C2 65 MA T2DM 57 M 1 68 7 8 7 66 MA T2DM 57 F 2 33 49 51 7 9 67 MA T2DM 57 M 2 68 7 42 7 17 68 MA T2DM 58 F 29 31 27 44 2 69 MA T2DM 58 M 23 68 49 65 7 8 70 MA T2DM 58 F 24 31 35 44 4 5 71 MA T2DM 58 M 24 31 61 3 72 MA T2DM 59 M 2 11 35 44 4 7 73 MA T2DM 59 M 2 29 44 40 5 74 MA T2DM 59 M 2 35 0 60 75 MA T2DM 59 M 1 68 8 61 3 7 76 MA T2DM 60 M 1 31 58 62 1 7 77 MA T2DM 60 M 24 33 35 65 4 8 78 MA T2DM 61 F 1 8 57 7 79 MA T2DM 61 M 2 2 14 50 80 MA T2DM 61 M 2 28 39 56 81 MA T2DM 62 M 2 68 35 41 3 82 MA T2DM 62 M 29 30 13 45 83 MA T2DM 62 F 2 31 35 44 4 5 84 MA T2DM 62 F 2 80 44 53 5 6 85 MA T2DM 62 M 2 24 35 40 3 4 86 MA T2DM 62 M 11 26 27 050 1 6 87 MA T2DM 62 M 2 33 14 48 8 88 MA T2DM 63 M 24 68 39 48 7 8 89 MA T2DM 63 F 24 28 27 61 2 3 90 MA T2DM 63 M 2 18 48 5 8 91 MA T2DM 63 F 28 32 18 49 92 MA T2DM 63 F 24 31 39 51 93 MA T2DM 63 M 2 32 38 35 4 94 MA T2DM 64 F 1 31 35 51 4 95 MA T2DM 64 M 2 24 39 62 1 7 96 MA T2DM 65 M 1 28 57 62

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Appendix F: HLA Class I Antigens – Cases of T2DM (4 of 4)

ID Race Subjects Age Sex A1 A2 B1 B2 C1 C2 97 MA T2DM 65 M 11 24 35 4 98 MA T2DM 66 M 1 2 48 52 8 99 MA T2DM 66 M 24 61 65 3 8 100 MA T2DM 66 F 1 24 55 61 3 101 MA T2DM 66 M 2 68 44 62 1 4 102 MA T2DM 67 M 26 28 48 51 103 MA T2DM 68 M 24 31 35 39 4 7 104 MA T2DM 68 F 1 68 15 35 1 4 105 MA T2DM 68 F 24 28 39 3 7 106 MA T2DM 69 M 2 11 27 41 1 7 107 MA T2DM 69 F 2 3 44 61 2 5 108 MA T2DM 72 M 3 35 4 109 MA T2DM 74 M 2 24 50 51 6 110 MA T2DM 75 M 3 24 27 39 2 7

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Appendix G: HLA Class II Antigens - Control #1 (1 of 7)

ID Race Subjects Age Sex DR1 DR2 DQ1 DQ2 1 MA Control 40 F 4 7 2 8 2 MA Control 40 M 7 15 1 2 3 MA Control 40 M 12 17 2 5 4 MA Control 40 F 10 4 5 MA Control 40 M 8 13 1 4 6 MA Control 40 F 4 8 3 4 7 MA Control 40 F 4 17 2 8 8 MA Control 40 F 4 11 9 MA Control 40 M 4 16 7 8 10 MA Control 40 F 4 17 2 8 11 MA Control 40 F 1 8 4 5 12 MA Control 40 F 4 11 3 7 13 MA Control 41 M 7 16 2 7 14 MA Control 41 F 4 8 4 8 15 MA Control 41 F 7 15 6 9 16 MA Control 41 M 11 13 1 7 17 MA Control 41 M 1 17 2 5 18 MA Control 41 F 14 15 5 6 19 MA Control 41 M 4 15 6 8 20 MA Control 41 M 4 15 3 6 21 MA Control 41 F 1 8 4 5 22 MA Control 41 F 4 7 2 8 23 MA Control 41 F 8 4 24 MA Control 41 M 8 4 25 MA Control 41 F 8 4 7 26 MA Control 41 M 1 4 1 8 27 MA Control 41 M 7 2 28 MA Control 41 M 6 8 4 7 29 MA Control 41 F 8 15 4 6 30 MA Control 41 F 4 3 8 31 MA Control 42 M 1 17 32 MA Control 42 F 11 17 2 7

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Appendix G: HLA Class II Antigens - Control #1 (2 of 7)

ID Race Subjects Age Sex DR1 DR2 DQ1 DQ2 33 MA Control 42 M 1 15 5 6 34 MA Control 42 F 6 9 35 MA Control 42 F 4 7 2 3 36 MA Control 42 M 4 15 6 8 37 MA Control 42 F 11 17 2 7 38 MA Control 42 F 4 10 5 8 39 MA Control 42 M 1 7 2 5 40 MA Control 42 F 4 15 4 6 41 MA Control 43 M 1 2 1 42 MA Control 43 F 11 14 3 7 43 MA Control 43 F 4 15 6 8 44 MA Control 43 M 17 14 1 2 45 MA Control 43 M 7 11 2 7 46 MA Control 43 M 4 15 3 6 47 MA Control 43 F 4 14 7 8 48 MA Control 43 F 14 16 3 7 49 MA Control 43 F 2 8 50 MA Control 43 M 4 8 3 4 51 MA Control 43 M 14 17 52 MA Control 43 F 4 17 2 8 53 MA Control 43 F 4 8 4 8 54 MA Control 43 F 4 11 7 8 55 MA Control 43 F 2 4 56 MA Control 43 M 8 15 4 6 57 MA Control 43 F 4 17 2 3 58 MA Control 43 M 10 12 5 7 59 MA Control 44 F 9 11 7 9 60 MA Control 44 F 4 103 61 MA Control 44 F 8 14 1 4 62 MA Control 44 F 13 14 3 7 63 MA Control 44 F 13 17 2 6 64 MA Control 45 M 4 17 2 8

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Appendix G: HLA Class II Antigens - Control #1 (3 of 7)

ID Race Subjects Age Sex DR1 DR2 DQ1 DQ2 65 MA Control 45 F 1 4 1 3 66 MA Control 45 F 4 13 1 3 67 MA Control 45 F 7 10 2 5 68 MA Control 45 F 1 4 5 8 69 MA Control 45 M 14 17 2 7 70 MA Control 45 F 1 11 1 7 71 MA Control 45 M 1 4 5 8 72 MA Control 45 M 8 4 73 MA Control 45 F 8 15 74 MA Control 45 F 4 7 2 8 75 MA Control 46 F 2 3 76 MA Control 46 M 103 7 1 3 77 MA Control 46 F 7 14 2 5 78 MA Control 46 M 7 2 79 MA Control 46 M 1 11 5 7 80 MA Control 46 F 8 15 1 4 81 MA Control 46 M 4 6 82 MA Control 46 F 1 4 1 8 83 MA Control 46 F 8 84 MA Control 46 M 14 15 4 7 85 MA Control 47 F 15 17 2 6 86 MA Control 47 F 8 12 1 4 87 MA Control 47 M 4 8 4 8 88 MA Control 47 F 4 7 2 8 89 MA Control 47 F 11 16 7 90 MA Control 47 F 2 3 91 MA Control 47 M 7 16 3 7 92 MA Control 47 M 8 14 4 7 93 MA Control 47 M 17 18 2 4 94 MA Control 47 M 4 11 3 7 95 MA Control 47 M 7 11 3 7 96 MA Control 47 M 8 17 2 4

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Appendix G: HLA Class II Antigens - Control #1 (4 of 7)

ID Race Subjects Age Sex DR1 DR2 DQ1 DQ2 97 MA Control 47 M 11 17 2 7 98 MA Control 48 M 11 13 2 6 99 MA Control 48 M 13 15 1 100 MA Control 48 F 17 13 2 7 101 MA Control 48 M 4 11 4 7 102 MA Control 48 F 4 13 1 8 103 MA Control 48 F 8 15 4 6 104 MA Control 48 F 14 15 6 7 105 MA Control 48 F 7 15 2 6 106 MA Control 48 F 8 11 4 7 107 MA Control 48 F 4 14 7 8 108 MA Control 48 M 1 4 1 8 109 MA Control 48 F 4 15 6 8 110 MA Control 49 F 11 13 6 7 111 MA Control 49 F 4 14 1 8 112 MA Control 49 F 4 8 4 8 113 MA Control 49 M 13 15 6 114 MA Control 49 F 1 16 1 115 MA Control 49 F 3 4 116 MA Control 49 F 4 8 117 MA Control 49 F 2 6 7 118 MA Control 49 F 4 8 3 4 119 MA Control 49 M 2 4 120 MA Control 49 F 1 7 2 5 121 MA Control 50 F 4 12 7 8 122 MA Control 50 F 11 15 6 7 123 MA Control 50 M 4 8 124 MA Control 50 M 11 13 6 7 125 MA Control 50 M 7 11 3 7 126 MA Control 50 M 1 7 1 2 127 MA Control 50 M 13 15 6 6 128 MA Control 50 M 2 3

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Appendix G: HLA Class II Antigens - Control #1 (5 of 7)

ID Race Subjects Age Sex DR1 DR2 DQ1 DQ2 129 MA Control 51 F 7 2 9 130 MA Control 51 F 8 10 4 5 131 MA Control 51 F 4 10 132 MA Control 51 F 4 4 8 133 MA Control 51 M 4 11 3 7 134 MA Control 51 M 11 135 MA Control 51 F 13 6 136 MA Control 51 F 4 12 7 8 137 MA Control 51 M 7 11 2 7 138 MA Control 51 M 4 13 1 8 139 MA Control 52 F 4 8 4 8 140 MA Control 52 F 4 16 3 7 141 MA Control 52 M 8 14 4 7 142 MA Control 52 F 4 8 3 4 143 MA Control 52 F 4 14 8 144 MA Control 52 F 4 8 4 8 145 MA Control 53 M 7 14 2 7 146 MA Control 53 F 4 11 7 8 147 MA Control 53 F 2 4 1 8 148 MA Control 53 M 3 4 149 MA Control 53 M 4 14 7 8 150 MA Control 53 M 8 15 6 4 151 MA Control 53 F 8 17 2 4 152 MA Control 53 M 9 17 153 MA Control 53 F 11 15 1 154 MA Control 54 F 11 7 155 MA Control 54 F 8 11 4 7 156 MA Control 54 F 103 15 5 6 157 MA Control 54 F 1 4 5 7 158 MA Control 55 M 12 17 2 7 159 MA Control 55 F 9 17 2 160 MA Control 55 M 4 17

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Appendix G: HLA Class II Antigens - Control #1 (6 of 7)

ID Race Subjects Age Sex DR1 DR2 DQ1 DQ2 161 MA Control 55 M 8 17 2 4 162 MA Control 55 M 4 3 163 MA Control 55 F 13 18 164 MA Control 55 F 1 8 4 5 165 MA Control 55 M 8 14 4 7 166 MA Control 55 M 4 15 6 8 167 MA Control 55 F 3 4 168 MA Control 56 M 14 1 2 169 MA Control 56 M 11 3 7 170 MA Control 56 F 6 7 2 7 171 MA Control 56 F 4 13 6 8 172 MA Control 56 M 1 4 5 8 173 MA Control 56 F 4 16 3 7 174 MA Control 56 M 4 15 3 6 175 MA Control 57 F 6 7 2 7 176 MA Control 58 M 1 4 5 8 177 MA Control 58 M 8 9 4 9 178 MA Control 59 F 8 11 4 7 179 MA Control 59 F 8 13 180 MA Control 59 M 7 17 2 181 MA Control 60 M 1 7 2 5 182 MA Control 60 F 4 12 7 3 183 MA Control 61 F 1 11 1 7 184 MA Control 61 M 4 11 1 8 185 MA Control 61 M 11 17 2 7 186 MA Control 61 F 8 17 2 4 187 MA Control 62 F 17 13 2 4 188 MA Control 62 M 8 13 4 7 189 MA Control 63 M 15 17 2 6 190 MA Control 64 F 2 7 2 7 191 MA Control 64 F 4 14 7 8

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Appendix G: HLA Class II Antigens - Control #1 (7 of 7)

ID Race Subjects Age Sex DR1 DR2 DQ1 DQ2 192 MA Control 65 M 2 4 193 MA Control 66 M 4 6 7 8 194 MA Control 68 M 11 11 7 7 195 MA Control 70 F 11 15 6 196 MA Control 73 M 17 2

Appendix G: HLA Class II Antigens - Control #2

ID Race Subjects Age Sex DR1 DR2 DQ1 DQ2 1 MA Control - FH 21 F 11 15 1 7 2 MA Control - FH 24 F 3 11 2 7 3 MA Control - FH 25 F 4 14 5 7 4 MA Control - FH 26 F 1 7 1 2 5 MA Control - FH 26 M 13 13 5 7 6 MA Control - FH 26 M 13 13 5 7 7 MA Control - FH 27 M 10 15 1 8 MA Control - FH 27 M 13 14 9 MA Control - FH 27 M 8 17 2 4 10 MA Control - FH 28 M 1 15 1 7 11 MA Control - FH 33 M 4 14 5 7 12 MA Control - FH 35 F 4 6 13 MA Control - FH 35 F 4 14 5 7 14 MA Control - FH 36 F 2 15 MA Control - FH 38 M 2 4 16 MA Control - FH 42 F 7 8 3 4 17 MA Control - FH 45 M 8 13 1 4 18 MA Control - FH 45 F 8 11 4 7 19 MA Control - FH 45 M 14 15 1 2 20 MA Control - FH 45 F 1 14 21 MA Control - FH 50 F 11 103 1 7 22 MA Control - FH 53 F 7 11 7 9 23 MA Control - FH 54 M 7 13 2 7 24 MA Control - FH 56 M 4 11

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Appendix G: HLA Class II - Cases of T2DM (1 of 4)

ID Race Subjects Age Sex DR1 DR2 DQ1 DQ2 1 MA T2DM 40 M 7 11 2 6 2 MA T2DM 42 F 8 4 3 MA T2DM 42 F 4 4 8 4 MA T2DM 44 F 1 15 5 6 5 MA T2DM 44 M 8 15 4 6 6 MA T2DM 44 F 17 2 7 MA T2DM 44 M 4 17 8 MA T2DM 44 F 13 14 6 7 9 MA T2DM 44 M 4 16 7 8 10 MA T2DM 44 M 4 17 2 3 11 MA T2DM 45 F 14 17 2 7 12 MA T2DM 46 F 4 17 2 3 13 MA T2DM 46 F 4 17 2 8 14 MA T2DM 46 F 11 15 MA T2DM 47 M 11 14 5 7 16 MA T2DM 47 F 4 17 2 3 17 MA T2DM 48 M 4 13 6 8 18 MA T2DM 48 M 1 9 5 9 19 MA T2DM 48 F 13 14 7 20 MA T2DM 48 F 103 11 1 7 21 MA T2DM 48 M 4 14 22 MA T2DM 48 M 4 11 3 7 23 MA T2DM 48 F 3 4 2 3 24 MA T2DM 49 M 13 15 6 25 MA T2DM 49 M 4 13 6 8 26 MA T2DM 49 M 15 16 5 6 27 MA T2DM 49 M 4 7 2 8 28 MA T2DM 50 M 4 8 4 8 29 MA T2DM 50 F 4 3 7 30 MA T2DM 50 M 4 11 31 MA T2DM 51 M 11 6 7 32 MA T2DM 51 M 4 8 4 8

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Appendix G: HLA Class II - Cases of T2DM (2 of 4)

ID Race Subjects Age Sex DR1 DR2 DQ1 DQ2 33 MA T2DM 51 M 13 17 34 MA T2DM 51 M 7 2 3 35 MA T2DM 51 M 11 14 1 7 36 MA T2DM 52 M 11 17 2 7 37 MA T2DM 52 M 7 15 2 6 38 MA T2DM 52 F 4 7 2 8 39 MA T2DM 52 M 4 13 6 8 40 MA T2DM 52 M 7 12 2 7 41 MA T2DM 52 M 1 13 1 42 MA T2DM 53 F 8 17 2 4 43 MA T2DM 53 M 4 8 4 8 44 MA T2DM 53 M 4 14 1 8 45 MA T2DM 53 M 4 14 3 7 46 MA T2DM 53 F 8 15 4 6 47 MA T2DM 54 M 4 14 5 8 48 MA T2DM 54 M 13 14 6 7 49 MA T2DM 54 F 7 15 2 7 50 MA T2DM 54 M 11 13 1 7 51 MA T2DM 55 M 11 103 5 7 52 MA T2DM 55 M 4 14 7 8 53 MA T2DM 55 M 8 13 1 4 54 MA T2DM 55 M 4 8 4 8 55 MA T2DM 55 M 8 17 2 4 56 MA T2DM 55 F 4 7 57 MA T2DM 55 M 8 4 7 58 MA T2DM 55 M 13 6 59 MA T2DM 56 M 4 8 60 MA T2DM 56 F 11 15 1 7 61 MA T2DM 56 M 17 4 2 3 62 MA T2DM 56 M 1 13 63 MA T2DM 57 M 6 13 1 7 64 MA T2DM 57 M 14 17 2 7

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Appendix G: HLA Class II - Cases of T2DM (3 of 4)

ID Race Subjects Age Sex DR1 DR2 DQ1 DQ2 65 MA T2DM 57 M 15 17 2 6 66 MA T2DM 57 F 8 13 2 4 67 MA T2DM 57 M 103 8 1 7 68 MA T2DM 58 F 7 8 2 4 69 MA T2DM 58 M 1 15 1 70 MA T2DM 58 F 4 8 4 7 71 MA T2DM 58 M 4 16 7 8 72 MA T2DM 59 M 8 14 4 5 73 MA T2DM 59 M 15 14 6 7 74 MA T2DM 59 M 6 8 75 MA T2DM 59 M 8 17 2 4 76 MA T2DM 60 M 8 17 2 4 77 MA T2DM 60 M 13 16 6 7 78 MA T2DM 61 F 11 3 7 79 MA T2DM 61 M 10 11 7 1 80 MA T2DM 61 M 4 11 81 MA T2DM 62 M 4 9 2 8 82 MA T2DM 62 M 1 7 83 MA T2DM 62 F 8 11 4 7 84 MA T2DM 62 F 9 2 85 MA T2DM 62 M 4 8 4 8 86 MA T2DM 62 M 1 9 1 2 87 MA T2DM 62 M 1 8 1 4 88 MA T2DM 63 M 4 8 89 MA T2DM 63 F 11 14 3 7 90 MA T2DM 63 M 17 14 91 MA T2DM 63 F 3 4 92 MA T2DM 63 F 4 14 93 MA T2DM 63 M 6 8 1 4 94 MA T2DM 64 F 2 2 1 95 MA T2DM 64 M 14 7 96 MA T2DM 65 M 7 11

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Appendix G: HLA Class II - Cases of T2DM (4 of 4)

ID Race Subjects Age Sex DR1 DR2 DQ1 DQ2 97 MA T2DM 65 M 4 11 7 8 98 MA T2DM 66 M 15 16 6 7 99 MA T2DM 66 M 8 1 4 100 MA T2DM 66 F 4 14 1 8 101 MA T2DM 66 M 4 15 2 8 102 MA T2DM 67 M 4 15 103 MA T2DM 68 M 8 14 4 7 104 MA T2DM 68 F 13 16 7 105 MA T2DM 68 F 4 6 7 106 MA T2DM 69 M 1 13 1 7 107 MA T2DM 69 F 1 15 5 6 108 MA T2DM 72 M 1 5 109 MA T2DM 74 M 1 6 1 7 110 MA T2DM 75 M 11 14 7

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Appendix H: HLA Class II alleles - Set #1 (1 of 2)

ID Race Subjects Age Sex DRB1 DRB2 DQA1 DQA2 DQB1 DQB2 1A MA Control 51 F 0301 1401 0101 0501 0201 0503 2A MA Control 62 F 1501 1602 0102 0505 0301 0602 3A MA Control 47 F 0405 0407 0301 0301 0302 0302 4A MA Control 59 F 0802 1406 0401 0503 0301 0402 5A MA Control 54 F 0802 1406 0401 0503 0319 0402 6A MA Control 46 F 0407 1301 0103 0301 0302 0603 7A MA Control 49 M 0102 0701 0101 0201 0303 0501 8A MA Control 53 F 1301 1602 0103 0505 0301 0603 9A MA Control 51 F 0103 0901 0101 0301 0202 0501 10A MA T2DM 49 F 0407 0407 0301 0301 0302 0302 11A MA Control 55 M 0802 1104 0505 0601 0301 0402 12A MA Control 49 F 0404 1301 0103 0301 0302 0603 13A MA Control 56 F 0701 1104 0201 0505 0202 0301 14A MA T2DM 52 M 0301 1402 0501 0503 0201 0301 15A MA Control 44 F 0802 1401 0101 0503 0301 0503 A 16A MA Control 69 F 0407 1302 0102 0301 0302 0609 17A MA T2DM 71 M 0301 1402 0501 0503 0201 0302 18A MA Control 56 F 0407 0701 0201 0301 0202 0301 19A MA Control 52 F 0301 1301 0103 0501 0201 0603 20A MA Control 55 M 1104 1301 0103 0505 0301 0603 21A MA Control 50 F 0101 1104 0101 0505 0301 0501 22A MA Control 41 F 0101 1402 0101 0503 0301 0501 23A MA T2DM 52 F 1302 1502 0102 0103 0601 0604 24A MA Control 49 F 0102 0701 0101 0201 0202 0501 25A MA Control 50 F 0102 0701 0101 0201 0202 0501 26A MA Control 70 F 1301 1302 0102 0103 0603 0609 27A MA Control 42 F 0404 1601 0102 0301 0302 0502 28A MA T2DM 57 F 1102 1406 0501 0503 0301 0319 30A MA Control 41 F 1301 1302 0102 0103 0603 0604 31A MA T2DM 60 F 0407 1101 0301 0505 0301 0302 32A MA T2DM 48 F 0407 1301 0103 0301 0302 0603 33A MA T2DM 70 F 0701 0802 0201 0401 0202 0402

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Appendix H: HLA Class II alleles - Set #1 (2 of 2)

ID Race Subjects Age Sex DRB1 DRB2 DQA1 DQA2 DQB1 DQB2 34A MA T2DM 54 F 0701 0802 0201 0401 0202 0402 35A MA T2DM 57 F 0701 1102 0201 0505 0202 0319 36A MA T2DM 59 F 0404 1301 0103 0301 0302 0603 37A MA T2DM 72 F 0407 0410 0301 0301 0302 0402 38A MA T2DM 68 M 0802 1104 0401 0505 0319 0402 39A MA T2DM 57 M 1201 1501 0102 0505 0301 0602 40A MA T2DM 73 F 0407 1402 0301 0301 0302 0302 41A MA T2DM 64 M 0407 1602 0301 0505 0301 0302 42A MA Control 65 F 0705 0802 0201 0401 0202 0402 43A MA T2DM 60 F 0407 1201 0301 0505 0301 0302 44A MA T2DM 51 F 0103 0802 0401 0505 0301 0402 45A MA T2DM 70 F 0407 0701 0201 0301 0202 0302 46A MA T2DM 72 F 0102 0301 0101 0501 0201 0501 47A MA Control 52 F 0701 0802 0201 0401 0202 0402 48A MA T2DM 62 F 1302 1501 0102 0102 0602 0609 49A MA Control 55 M 0301 0404 0301 0501 0201 0302 50A MA T2DM 62 F 0407 1301 0301 0301 0302 0303 51A MA Control 61 F 0102 0802 0101 0401 0402 0501 52A MA T2DM 48 F 0101 0405 0101 0301 0302 0501 53A MA T2DM 47 F 0102 0301 0101 0501 0201 0501 54A MA Control 41 F 0404 1101 0301 0505 0301 0302 55A MA T2DM 59 F 0101 1104 0101 0505 0301 0501 56A MA T2DM 54 M 0101 1104 0101 0505 0301 0501 57A MA T2DM 53 M 0301 1501 0102 0501 0201 0602 58A MA T2DM 60 M 0301 0701 0201 0501 0201 0202

154

Appendix H: HLA Class II alleles - Set #2)

ID Race Subjects Age Sex Race DRB2 DQA1 DQA2 DQB1 DQB2 1B MA Control 43 M 0802 1501 0102 0401 0402 0602 2B MA Control 47 M 0802 1406 0401 0503 0301 0402 3B MA Control 45 F 0402 1301 0103 0301 0302 0603 4B MA Control 52 M 0802 1406 0401 0503 0301 0402 5B MA Control 55 M 0407 0407 0301 0301 0302 0302 6B MA Control 43 F 0404 1104 0301 0505 0301 0302 7B MA T2DM 57 F 0802 1303 0201 0401 0202 0402 8B MA Control 60 M 0102 0701 0101 0201 0202 0501 9B MA T2DM 69 F 0101 1501 0101 0102 0501 0602 10B MA T2DM 42 F 0802 0802 0401 0401 0402 0402 11B MA Control 43 F 0404 1406 0301 0503 0301 0302 12B MA T2DM 44 F 1301 1406 0103 0503 0301 0603 13B MA Control 62 F 0301 1303 0302 0501 0201 0402 14B MA T2DM 48 M 0101 0901 0101 0301 0303 0501 15B MA T2DM 54 M 1301 1406 0103 0503 0301 0603 16B MA Control 58 M 0802 0901 0301 0401 0303 0402 17B MA T2DM 68 M 0802 1406 0401 0503 0301 0402 18B MA T2DM 57 M 0301 1501 0102 0501 0201 0602 19B MA Control 51 F 0802 1001 0101 0401 0402 0501 20B MA T2DM 56 F 1104 1501 0102 0505 0301 0602 21B MA T2DM 65 M 0402 1104 0301 0505 0301 0302 22B MA Control 40 M 0802 1302 0102 0401 0402 0604

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Appendix I: Sierra Providence Health Network (SPHN) IRB Approval

156

Appendix J: Sierra Providence Health Network IRB Renewal

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Appendix K: University of Texas at El Paso IRB Approval

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Appendix L: University of Texas at El Paso IRB Approval (1 of 2)

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Appendix L: University of Texas at El Paso IRB Approval (2 of 2)

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Appendix M: University of Texas at El Paso IRB Approval Apo-E Pilot Study

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Appendix N: Approval to Use Samples and Demographic Information of APO-E Study

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Appendix O: Las Palmas Medical Center (LMPC) IRB Approval for rSSO Testing

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Appendix P: Las Palmas Medical Center IRB Renewal for rSSO Testing

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Appendix Q: University of Texas at El Paso IRB Approval for Dissertation

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Appendix R: NIH Web-based Training Course Protecting Human Research Participants

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A Biographic Sketch

Kantibhai Motiram Patel was born in Visnagar (N.G.), India. I completed my elementary school education at Kumar Shala #1 in 1956 and my junior high school education at Adarsh Middle

School, Visnagar (N.G.) in 1960. I completed my high school education at the Nootan Serva

Vidyalaya High School, Visnagar (N.G.) in 1964. I attended Gujarat University (India) to obtain an

undergraduate degree in Biology and graduated in May 1968. In 1970, I attended Florida A&M

University in Tallahassee and completed my Master’s degree in Agriculture in June 1972. I then

attended Northeastern Illinois University at Chicago to complete courses for a Master of Science in

Biology. In 1979, I took a position at Northwestern University Medical School in Chicago Illinois

as Medical Technologist in the Immunogenetics (HLA) Laboratory. From 1980 to 1982, I took

classes in medical immunology, immunogenetics, biochemistry, and statistics. In 1984, I completed

received a certificate for completion of fifteen hours in Computer Studies. I have been certified as a

Technologist in Immunology by the American Society of Clinical Pathology (ASCP) since 1983 and

as a Clinical Histocompatibility and Immunogenetics Specialist by the American Board of

Histocompatibility and Immunogenetics (ABHI) since 1989. In 1990, I accepted a position at

Humana Hospital in Las Vegas as the Transplant Immunology Laboratory Supervisor. In 1992, I

moved to El Paso, Texas, to accept the position of Transplant Immunology Laboratory Supervisor at

Sierra Medical Center which had a relatively new transplant program. This position presented me

with the opportunity to contribute to the growth and development of a newly established transplant

program. I worked closely with the medical directors and physicians involved in the transplant

program enhancing policies and procedures as well as developing laboratory protocols for the

program. I left Sierra Medical Center in February 2008 to take a position at Las Palmas Medical

Center as the Director of the Histocompatibility and Immunogenetics Laboratory. Las Palmas

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Medical Center began working on a transplant program as a new service in 2008. This new position has given me the opportunity to assist in establishing a new program from the ground up and the ability to contribute and share my knowledge and experience in Transplant Immunology and

Immunogenetics. I am currently a Ph.D. student in Interdisciplinary Health Science at University of

Texas at El Paso. As of October 2009, I have completed 71 credit hours toward my PhD. including

four classes at the University of Texas at Houston, El Paso Campus. My Dissertation Title is “The

Association of Human Leukocyte Antigen (HLA) Alleles and Type 2 Diabetes Mellitus among

Mexican Americans (MA).

Permanent Address: 6333 Franklin Summit Drive

El Paso, Texas 79912

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Curriculum Vita

Kantibhai Motiram Patel 6333 Franklin Summit Drive El Paso, Texas 79912-8151 Home Telephone: (915) 584-5559 Work Telephone: (915) 521-1841 Work Fax: (915) 599-4161 Email: [email protected]

Education/Training: University of Texas at El Paso, PhD (2005-Present) Interdisciplinary Health Science Northwestern University, Chicago, IL, 15-hour Certificate (1983) Computer Studies Northeastern Illinois University, Chicago, IL, MS Courses (1978) Biology Florida A & M University, Tallahassee, FL, MEd (1972) Agriculture Education Gujarat University Ahmedabad-9, INDIA, BS (1968) Biology

Present: Working on Doctorate in the Interdisciplinary Health Science, College of Heath Sciences, University of Texas at El Paso, TX.

Dissertation Title: “The Association of the Human Leukocyte Antigen Alleles and Type 2 Diabetes Mellitus among Mexican Americans”

Objective: Involve in clinical research to identify genetic markers (HLA, KIR and MICA) and environmental factors closely associated with T2DM and other diseases.

Employment:

2008–Present: Director, Histocompatibility & Immunogenetics Lab, Las Palmas Medical Center, El Paso, TX Responsibilities include:  Designing laboratory area, ordering equipment, setting-up a histocompatibility and immunogenetics laboratory.  Hiring, orienting and training all laboratory personnel regarding HLA testing procedures.  Directing the performance of parallels testing of HLA- A, B, C, DRB1, DQA1, DQB3, DRB4 and DRB5, using SSP-DNA and LABType rSSO techniques.  Conducting and overseeing the antibody screening and specificity by flow PRA and LABScreen by Luminex. Flow cytometry Class I and Class II crossmatch and immunophenotyping.  Achieving and maintaining the accreditation of CLIA, ASHI, and UNOS certification for the laboratory.  Maintaining responsibility for quality control and quality assurance of all HLA testing.  Completing computerization of laboratory and preparation of annual budget and billing procedures.

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 Preparing technical, procedural, and policy manuals and final HLA report.  Coordinating the transplant immunology services with the hospital transplant program.  Maintaining 24-hour availability for consulting, reviewing, trouble shooting, and directing all testing.

1992–2008: Supervisor, Transplant Immunology Lab, Sierra Medical Center, El Paso, TX Responsibilities included:  Maintaining the transplant immunology laboratory that met all UNOS, ASHI, CAP, and AABB accreditation requirements.  Organizing the transplant immunology laboratory.  Performing all quality control tests, HLA-A, B, C, and DR typing.  Maintaining supervision of laboratory technologists.  Orienting, presenting and training new personnel, which included assigning their daily work schedule, supervising their performance, and writing their performance appraisal.  Preparing the annual budget and maintenance of billing procedures.  Preparing and maintaining the technical, procedural, and policy manuals and final HLA report.  Coordinating the transplant immunology services with the hospital transplant program.  Achievements: Under my supervision the present laboratory received its first ASHI accreditation. Recently, the HLA-DNA typing laboratory and flow cytometry laboratory of immunophenotypes, lymphoma/leukemia and transplant flow-crossmatch, flow PRA and specificities services were placed under my supervision.  Maintaining involvement in the computerization of transplant immunology laboratory, and working on the process to setup Luminex for HLA PRA, specificities, and rSSOP HLA Class I and II DNA typing.

1990–1992: Supervisor, Transplant Immunology Lab, Humana Hospital, Las Vegas, NV Responsibilities included:  Setting-up a transplant immunology laboratory test known for quality control of HLA-A, B, C, DR, and DQ typing, HLA antibody screen, HLA crossmatch, and MLC test.  Establishing the process for flow cytometry crossmatch test and computerization of transplant immunology laboratory.  Supervising the laboratory technologists, this included producing their daily work schedule and assignments.  Preparing the annual budget, development of laboratory procedures, and final HLA report. Assisted in a flow cytometry laboratory for DNA analysis, immunophenotyping, immunology, and virology laboratory.

1985–1990: Assistant Supervisor, HLA Lab, Northwestern University, Chicago, IL Responsibilities included:  Supervising technologist in absence of supervisor  Conducting separation of lymphocytes, T, and B lymphocytes  Conducting HLA-A, B, C, and DR typing.  Determining HLA antibodies in patient’s serum and crossmatch tests.  Performing mixed lymphocytes reaction.  Performing tissue culture.

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 Trouble shooting in the tissue typing laboratory.  Developing and standardizing new techniques.  Maintaining responsibility for computer programming and data analysis.  Maintaining responsibility for instruction and training of medical residents and pathologists in clinical HLA testing.  Maintaining adequate supply level of laboratory supply and equipment and ordering them as necessary.

1980–1985: Medical Technologist, HLA Lab, Northwestern University, Chicago, IL Responsibilities included:  Developed proficiency in HLA typing and immunologically related testing of clinical and research samples for kidney and bone marrow transplantation, platelet, and granulocyte transfusions and HLA associated diseases.  Conducted immunological testing and patient monitoring involved the typing, crossmatching and identification of HLA-A, B, C, and DR antigens.  Solely responsible for the operation of computer and analysis of serum data.  Worked on the gestational diabetes mellitus project in addition to the regular laboratory work.  Participated in a project of the clinical efficacy study of Isobact (antimicrobial) treated surgical drapes (1982–1984).

1979–1980: Research Technologist, Immunology Lab, Northwestern University, Chicago, IL Responsibilities included:  Identification of T and B Lymphocytes by sheep erythrocyte (E)-rosetting technique and immunofluorescent staining of surface immunoglobulin, respectively.  Preparation of ALL and IA Antiserum in rabbits and absorbed non-specific antibodies.  Maintenance of various cell lines.  Utilized knowledge and increased experience in mixed lymphocytes reaction testing.

1977–1979: R & D Technologist, Biochemistry/Microbiology Lab, Marlan Co., Chicago, IL Responsibilities included:  Responsible for bacterial identification, research and development, and quality control in dairy products.

1973–1977: Q.C. Supervisor/R & D Technologist, Food Lab, Newly Weds Foods, Inc., Chicago IL Responsibilities included:  Responsible for supervision of technologists in the area of analysis of salt, ash, moisture, pH, viscosity, granulation, and color of food products.  Participated and remained involved in analysis and development of new products.

1974–1978: Research Assistant, Biochemistry/Microbiology Lab, Northeastern Illinois University, Chicago, IL Responsibilities included:  Conducted independent research on mold spore germination, bacterial identification, and micro- sectioning and staining techniques.

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Professional Memberships: 1982–Present: American Society for Histocompatibility and Immunogenetics 1985–Present: American Society for Clinical Pathologists 2006–2008: Clinical Laboratory Science 1992–1999: Texas Transplantation Society 1993–1998: Clinical Laboratory Management Association. 2001–2002: Clinical Laboratory Management Association 1991–1995: American Association of Blood Bank. 1993–1994: American Association for the Advancement of Science. 1997–1999: American Association for the Advancement of Science.

Certifications: ASCP, Technologist in Immunology, 1984 ABHI, Clinical Histocompatibility Specialist, 1989 Nevada State License for Supervisor of Transplant Immunology Laboratory, 1991–1992 ASHI Accreditation Program Inspector, 2001–2002

Committee Memberships: ABHI Continuing Certification Committee Member, 1995–1997 SEOPF Scientific Affairs Committee Member, 1998 ABHI Examination Committee Member, 1999–2001 ASHI Quality Assurance Standards Committee Member, 2002–2004

Honors: 2008: Awarded the University of Texas at El Paso, College of Health Sciences, and the Graduate Enhancement Research/Scholarship Award to facilitate my research.

2005: Awarded the University of Texas at El Paso, the Graduate School Professional Funding Award to assist for Conference or Professional Meeting Information.

1995–1999: UCLA International Cell Exchange Proficiency Testing Surveys, under my supervision our laboratory was recognized for having perfect records.

1973–1978 Scholarship: Was awarded a full tuition fee during my Masters of Science course work from Northeastern Illinois University.

1970–1971 Scholarship: Was recipient of a scholarship for out-of-state tuition fee during my M.Ed. degree from Florida A&M University.

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B. Selected peer-reviewed publications (in chronological order):

Publications:

Radvany, R. M., Patel, K. M., Duria, R. F., Lee, A., Remendado, I. O., Andersen, R. L., & Hsieh, Y. (1984).Factors responsible for successful HLA-DR typing of mononuclear cells from cord blood. Tissue Antigen. 24 (4), 265–269.

Conn, Jr. J., Bornhoeft, J., Almgren. C., Mucha, D. P., Olderman, J., Patel, K. M., & Herring, C. M. (1988). An in vivo study of an antimicrobial surgical drape system. Journal of Clinical Microbiology. 24 (5), 803–808.

Radvany, R. M., Vaisrub, N., Ober, C., Patel, K. M., & Hecht, F. (1987). Human sex ratio: Increase in first-born males to parent with shared HLA-DR antigen. Tissue Antigen, 29 (1), 34–42.

Radvany, R. M., & Patel, K. M. (1988). DST, donor-recipient HLA compatibility, recipient haplotype, and antibody production. Transfusion. 28 (2), 137–141.

Patel, K. M. (1967). The Cell. Year Book. M. N. College, Visnagar (N.G.): India,16–18.

Abstract:

Radvany, R. M., Vaisrub, N., Patel, K. M., Ober, C., & Hecht, F. (1986). Sex ratio in HLA-DR compatible mother-child pairs varies with birth order. Journal of Reproductive Immunology, supplement.

Case Study:

Patel, K. M., Dominguez, D. C., and Wilson, H. (2007). Case studies with flow cytometry for leukemia diagnosis. El Paso Physician, 1, 23–26 (in press).

Presentation in conference:

Patel, K. M. (2005). HLA Association with type 2 diabetes in Mexican American population of El Paso, Texas region. Second International Summer School on Immunogenetics, Guanajuato, Mexico.

Acknowledgment:

Hsu, C. C. S. (1981).Coexpression of multiple immunoglobulin (Ig) heavy chain classes on human leukemic B lymphocytes (B Cells). Clinical Immunology and Immunopathology,18, 101–107. Morgan, E and Hsu, C. C. S. (1981). Relationship of a leukemia-associated antigen to the presence of lymphoblast in the peripheral blood in children with acute lymphocytic leukemia. Blood, 57 (5), 879–882.

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Radvany, R. M., Soper, W. D., Andersen, R. L. and Wolf, J. S. (1983). Positive autologous crossmatches and a successful transplant with an HLA-identical, but no with an HLA- nonidentical, kidney. Transplantation, 36 (6), 654–658.

Radvany, R. M., and Vaisrub, N. (1984). HLA-DR typing as a predictor of MLC compatibility. Transplantation, 38 (4), 347–351.

Hsu, C. C. S. (1984). Coexpression of multiple immunoglobulin isotypes of human B-lymphocytes. Immunological Communications, 13 (5), 403–418.

Labotka, R. J., and Radvany, R. (1985). Graft-versus-host disease in rhabdomyosarcoma following transfusion with nonirradiated blood products. Medical and Pediatric Oncology, 13, 101–104.

Ober, C., Simpson, J. L., Ward, M., Radvany, R., Andersen, R., Elias, S., & et al. (1987). Prenatal effects of maternal-fetal HLA compatibility. American Journal of Reproductive Immunology and Microbiology, 15, 141–149.

Radvany, R., Pachman, L. M., Rich, K. C., Sweeny, M. L., and Conneally, M. (1985). HLA antigens and extended HLA-BF-GLO haplotypes in 24 patients with pauciarticular juvenile rheumatoid arthritis and their families, Unpublished. Manuscript.

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