Genetics of Diabetes and Its Complications

Stephen S. Rich Department of Public Health Sciences, The Wake Forest University School of Medicine, Winston-Salem, North Carolina J Am Soc Nephrol 17: 353–360, 2006. doi: 10.1681/ASN.2005070770

iabetes constitutes a major public health problem. The genetic basis for type 2 diabetes has been difficult to Although substantial progress has been made in de- resolve. Unlike type 1 diabetes, in which there seems to be an D fining the genetic risk for specific subtypes of diabe- autoimmune process, type 2 diabetes is a disease of relative tes (e.g., maturity-onset diabetes of the young), the majority of rather than absolute insulin deficiency. In type 2 diabetes, the genetic risk of diabetes (for type 1 and type 2) remain unre- pancreatic ␤ cells become progressively less able to secrete solved. This review focuses on the current knowledge of the sufficient insulin to maintain normal carbohydrate and lipid genetic basis of diabetes and its complications, specifically di- homeostasis (7). Furthermore, there is insulin resistance cou- abetic nephropathy (DN). Ultimately, identification of genes pled with effects of aging, obesity, and reduced exercise (8). In that contribute to risk (or protection) of diabetes and its com- addition, the strength of the genetic contribution to the cause of plications will allow identification of patients who have diabe- type 2 diabetes seems to be less than that for type 1 diabetes, tes and are at risk and targeted treatment/interventional strat- with overall genetic risk ratio ranging from 2 to 4 (9). Despite egies. the relatively low genetic risk ratio for type 2 diabetes, results of several genomewide scans have reported a number of chro- Genetics of Diabetes mosomal regions that may harbor genes that are involved in Type 1 diabetes is the third most prevalent chronic disease of type 2 diabetes, with the most promising, replicated findings on childhood, affecting up to 0.4% of children in some populations chromosomes 1q21-q24, 2q37, 12q24 and 20 (reviewed in ref. by age 30 yr, with an overall lifetime risk of nearly 1% (1,2). It [10]). The finding of linkage to type 2 diabetes in Mexican is believed that a large proportion of cases of type 1 diabetes Americans to chromosome 2q37 (11) led to the characterization result from the autoimmune destruction of the pancreatic ␤ of susceptibility variants within the CAPN10 gene (12). Other cells, leading to complete dependence on exogenous insulin to type 2 diabetes linkage regions are being searched by develop- regulate blood glucose levels (3). Type 1 diabetes is strongly ment of consortia (the International 1q Consortium), and novel clustered in families with an overall genetic risk ratio (the type 2 diabetes susceptibility genes may be identified in the prevalence in siblings of a proband relative to the population ␭ future using the same approach. Several type 2 diabetes genes prevalence, S) of approximately 15 (4). (This compares with ␭ have been identified using investigations of candidate genes. the less familial but more prevalent type 2 diabetes with S of approximately 2). At least one locus that contributes strongly to Common variants in peroxisome proliferator–activated recep- ␥ this familial clustering resides within the MHC on chromosome tor- (13) and KCNJ11 (14) may predispose to type 2 diabetes 6p21, which accounts for nearly 40% of the observed familial with relatively low odds ratios (approximately 1.2). Variants clustering of type 1 diabetes, with a locus-specific genetic risk that affect insulin signaling through IRS-1 (15,16) and glucose ␭ homeostasis PTPN1 (17,18) seem to be less common in fre- ratio ( S) of approximately 3 (5). In a recent analysis of data from three previous genomewide scans (United States, United quency, suggesting that combinations of rare and common Kingdom, and Scandinavia) as well as new families collected variants contribute to risk for type 2 diabetes in different path- for the Type 1 Diabetes Genetics Consortium (http:// ways in different populations. www.t1dgc.org), 1435 multiplex families provided evidence for In summary, there is ample evidence that type 1 and type 2 linkage of type 1 diabetes to the MHC (IDDM1), insulin (INS, diabetes are, in part, genetically determined. The magnitude of IDDM2), a region that contains several genes, including CTLA4 the genetic contribution to type 1 and type 2 diabetes differs ␭ (2q31-q33 [IDDM12 and IDDM7]) and seven other chromosome dramatically (as shown by the genetic risk ratio [ S] for type 1 ␭ regions (6). diabetes of 15, but S is approximately 2 for type 2 diabetes). Furthermore, there is evidence that the genes that may contribute to risk for type 1 diabetes may differ from those that

Published online ahead of print. Publication date available at www.jasn.org. contribute to risk for type 2 diabetes. As we show below, the genetic risk for diabetic complications may be defined by yet Address correspondence to: Dr. Stephen S. Rich, Department of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC. Phone: another set of genes than those that modify risk for diabetes 336-716-5778; Fax: 336-716-5425; E-mail: [email protected] alone.

Indirect Evidence that Favors a Genetic Basis basis of disease as well as the available source of subjects of DN (Figure 1). Susceptibility genes that are prevalent with large The complications of diabetes involve several organ systems effect are unlikely to exist (single Mendelian genes with and are often categorized as microvascular (retinopathy, ne- large effect are usually rare). Similarly, genes that are rare with phropathy, and neuropathy) or macrovascular (cardiovascular small effect are unlikely to be detectable with current analytical and cerebrovascular). There is mounting evidence for the role strategies. In contrast, prevalent genes with small effect (com- of genetic factors in several diabetic complications, particularly mon variant) or rare with large effect (rare variant) may be DN, and cardiovascular and cerebrovascular complications of identified (32–34). Under a common variant hypothesis, asso- diabetes (19). DN remains the most common and rapidly in- ciation approaches (case-control, cohort studies) using a dense creasing cause of ESRD in developed nations. Approximately marker map have been proposed (whole genome association 35% of European Americans with diabetes are at risk for the scans). Under a rare variant hypothesis, linkage approaches development of overt proteinuria, chronic renal insufficiency, using extended families or sibling pairs (whole genome linkage and ESRD, with higher proportions observed among diabetic scans) often have been performed (Figure 2). African Americans, Hispanic Americans, and Native Ameri- Within either the common variant or rare variant hypotheses, cans (20). Genetic predisposition or protection may be the most both candidate gene evaluations and genome scans have been important DN risk determinants in type 1 diabetes. Only ap- conducted. The characterization of the contribution of variants proximately one half of patients with poor glycemic control within candidate genes has evolved into two (often overlap- develop DN, whereas some patients do so despite relatively ping) strategies. The first strategy involves the study of poly- good control (21). Familial clustering of DN has been demon- morphisms within individual genes that should (based on the strated by several investigators (22–24). underlying biologic knowledge) have an effect on risk. The The majority of individuals with diabetes will develop back- second is to explore a cluster of genes that may be involved in ground diabetic retinopathy; however, only one third of indi- a pathophysiologic pathway, recognizing that multiple genes in viduals with diabetes will develop overt kidney disease (25). the pathway may have recognized effects with each other and The factors that initiate overt nephropathy are unclear, but unrecognized effects on genes in the pathway and other genes consistent familial aggregation of kidney disease (albuminuria, (35–37). In each scenario, issues related to candidate gene se- creatinine clearance, and ESRD) and renal histologic changes lection, polymorphism evaluation within candidate genes, and have been observed frequently. The familial clustering of overt analysis of multiple genes in pathways remain a significant and DN and diabetic ESRD has been observed widely in multiple unresolved area of research. racial and ethnic groups, with the earliest reports of familial aggregation of diabetic kidney disease in patients with type 1 Pathways and Candidate Genes Involved in diabetes (22,24). Family members with diabetes, even in the DN absence of clinical nephropathy, demonstrate similar patterns Current knowledge of the pathophysiology of DN suggests a of glomerular involvement. Renal biopsy material from sibling complex interaction of multiple pathways associated with al- pairs with type 1 diabetes were evaluated, and evidence of terations in the balance between extracellular matrix produc- familial concordance in the percentage of the glomerulus occu- tion and removal, with interactions between genetic and envi- pied by mesangial matrix and the patterns of injury (presence ronmental factors. These pathophysiologic concepts have been of thickened glomerular basement membrane) were observed reviewed previously (38,39). The genes that contribute to vari- (26). In addition, consistent evidence across multiple studies ation and expression in the pathways are just now being ex- also supports familial aggregation of albuminuria (27,28), GFR, plored in the context of complex metabolic networks. Complex- and creatinine clearance (29–31).

Approaches to Identifying DN Susceptibility Genes Multiple strategies exist for exploring the human genome for evidence of genetic factors that contribute to risk for complex disease (e.g., not determined by a defect in a single gene, often termed “Mendelian”). DN is an example of a complex human disease, with many genes and environmental risk factors con- tributing to susceptibility. These risk factors may be of differing magnitude, and not all may be required for initiation or progression of disease. Furthermore, the constellation of factors may vary from one population to another. All approaches to detect disease susceptibility genes are based on demonstrating segregation of a trait (DN) with a measure of genetic variation. These approaches are dependent Figure 1. Effect and frequency of risk alleles dictate mapping on the unobservable “true” genetic architecture of the genetic strategies. J Am Soc Nephrol 17: 353–360, 2006 Genetics of Diabetes and Its Complications 355

be due to many reasons, including small sample size, incom- plete genetic dissection of the polymorphisms in the candidate gene, and extensive genetic and phenotypic heterogeneity. A partial list of candidate genes for DN is provided in Table 1.

Search for DN Susceptibility Genes The search for genes that influence risk for DN can take place at many levels. The two classical approaches are the case- control and family-based designs. Within the case-control design, the vast majority of studies have used a candidate gene approach, whether interrogating individual candidate genes or genes related to specific biologic pathways. The case-control Figure 2. Methods for genetic dissection of complex human design determines the evidence of association between a ge- traits. Solid symbols represent patients (diabetic nephropathy); netic variant and the outcome of DN or an intermediate, quan- open symbols represent control subjects (individuals with dia- titative phenotype (quantitative trait locus [QTL]). Within the betes of long duration without nephropathy). family-based approach, the unit of analysis is often a pair of siblings, as parents are often unavailable for study (except in the case of type 1 DN). Several general analyses of family data ity is also observed in the variation in structural features (e.g., have been used: The genome scan for linkage of DN, the the thickness in the capillary wall, mesangial matrix volume, candidate gene evaluation of linkage, and the family-based and width of the GBM), which have been shown to be deter- association approach. Recently, interest in mapping QTL for mined, in part, by genetic factors (26). Furthermore, the diabetic complex disease has been increasing. For example, the clinical state itself can modify the observed genetically determined phenotype (DN) is the result of multiple genetic and environ- structures. mental factors; however, the underlying physiologic (quantita- The major hypotheses as to how the diabetic state leads to tive) trait (e.g., urinary albumin excretion) may have stronger DN include (1) increased activity of a variety of growth factors, genetic effects (in the absence of those environmental factors including TGF-␤, growth hormone, IGF-1, vascular endothelial that lead to overt disease). Thus, the genetic predisposition to growth factor, and EGF; (2) activation of protein kinase C nephropathy may be reflected in the level of urinary albumin isoforms; (3) increased release of hormones, including renin, excretion as a quantitative trait, and, with exposure to diabetes, angiotensin, endothelin, and bradykinin; (4) formation of reac- high-normal levels of urinary albumin excretion may worsen to tive oxygen species; (5) increased formation of advanced gly- microalbuminuria and overt proteinuria. An implication of this cation end-products (AGE); (6) increased activity of the aldose hypothesis is that the genetic variation in the quantity of albu- reductase pathway; and (7) abnormalities in glucose transport min excreted in the urine is determined by the same QTL as mechanisms. The various hypotheses are interrelated, and the those genes that predispose to nephropathy but may not be key components of the pathways are genetically determined. dependent on the diabetic state. Results of mapping genes for Recently, a unifying hypothesis that links several important DN or urinary albumin excretion, under this model, would lead pathways in the pathogenesis of DN was developed (40). This to the same subset of genes in a common pathway. concept theorizes that hyperglycemia-induced mitochondrial In a genome screen, no a priori hypothesis is made as to the superoxide overproduction results in an increased activation of nature or the location of the specific genetic susceptibility genes protein kinase C isoforms, increased formation of AGE, accel- for DN or its intermediate phenotypes. Instead, the genetic eration of glucose flux through the aldose reductase pathway, determinants of these phenotypes are tested on a large number and an increased glucose flux into the hexosamine pathway. of polymorphic DNA markers scattered at roughly equal inter- These perturbations, with variation determined in part by vals throughout the human genome. This approach has been genes in the specific pathways that interact with environmental applied successfully in a number of Mendelian disorders, with factors, stimulate growth factors that result in extracellular investigations proceeding from positive linkage results to link- matrix accumulation, leading to DN. age disequilibrium mapping to gene identification. Once link- Many studies of candidate genes have examined functional age has identified a region in the genome that may contain a polymorphisms that affect levels (or activity) in many candi- susceptibility gene, use of markers in the narrow region in cases date pathways, including the renin-angiotensin, nitric oxide, and controls (for example) could find markers that are associ- and bradykinin systems. Other pathways that are involved ated (rather than linked) to the disease. Current strategy uses with insulin resistance, lipid production, and metabolism and haplotype-tagging single-nucleotide polymorphisms (SNP) de- glucose homeostasis, including aldose reductase, TGF-␤, and rived from HapMap Project, which allows the definition of glucose transporter-1, have been explored because of common causative “haplotypes” that segregate with disease in the fam- mechanisms that may be involved in several disease processes. ilies. There has been no consistent and replicated evidence for the It is, however, a much greater challenge to apply this ap- contributions by a set of candidate gene(s) or surrogate markers proach to genetically complex disorders. For most complex for DN risk (or protection). Failure to identify risk genes could diseases, it is likely that multiple genes influence disease ex- 356 Journal of the American Society of Nephrology J Am Soc Nephrol 17: 353–360, 2006

Table 1. A subset of candidate genes for diabetic nephropathya

Symbol Name Position Rationale (References)

NHE-1 (SLC9A1) Naϩ/H ϩ antiport-1 1p36.1-p35 NHE-1 activity is increased in type 1 diabetes with nephropathy (51,52) TGF-␤ (TGF-␤1, Transforming growth factor- 19q12-q13.31, 1q41, 14q24 TGF-␤ mRNA, proteins (and TGF-␤2, TGF-␤3) ␤ (1, 2, 3) TGF-␤-receptor mRNA) identified in rodent glomerular cells (53–55) GH1 Growth hormone 17q24.2 Diabetes causes decreased hepatic production of IGF- IGF-1, IGF-1R Insulin-like growth factor-1, 12q22-q23, 15q26.3 1; this decrease leads to an insulin-like growth factor- increased in growth 1 receptor hormone secretion (56–60) VEGF Vascular endothelial growth 6p12 VEGF expression increased factor in glomeruli of diabetic animals; diabetic rats that are treated with anti- VEGF antibody do not have hyperfiltration and reduced AER (61–63) RAAS ACE, AGT, AT1 (AGTR1), 17q23, 1q42-q43, 3q21-q25, BP regulation and sodium AT2 (AGTR2) Xq22-q23 homeostasis are crucial to progression of nephropathy (64–66)

aAER, albumin excretion ratio, RAAS, renin-angiotensin-aldosterone system; ACE, angiotensin-converting enzyme inhibitor; AGT, angiotensin-1; AT1, angiotensin II receptor type 1; AT2, angiotensin II receptor type 2.

pression, making it difficult to isolate and characterize the genes). The advantage of the genome screen strategy is the effects of each disease-determining locus. Genes may interact comprehensive evaluation of the entire genome. (epistasis) or induce susceptibility independently (heterogene- To date, only a few full descriptions of genome scans for DN ity). In addition, complex diseases such as DN are influenced have been published. The first genome scan that searched for by environmental factors. nephropathy and retinopathy loci (microvascular complica- Despite these complicating factors, the genome screen strat- tions) was performed in the Pima Indians (44). The strongest egy has been successful for type 1 diabetes (6), type 2 diabetes evidence for linkage was observed on chromosome 7q. Addi- (12), Crohn’s disease (41), asthma (42), and schizophrenia (43). tional evidence for linkage was found on chromosomes 3 and 9 The likelihood of success has increased with advances in high- (DN and retinopathy) and 20 (DN only). A similar approach throughput genotyping, development of semiparametric ge- was used in families with type 1 diabetes (45), in which linkage netic analysis methods, the potential to accumulate sufficient was found to a region that contains the angiotensin II type 1 patient and family materials, and more refined definition and receptor gene (AGTR1). Other genome scans were completed measurement of phenotypes. Although the most complex to recently. Members of a large Turkish kindred that contains execute, genome scans of appropriate family collections with multiple individuals who have type 2 DN (with multiple cous- significant prevalence of DN offer hope for identifying the in–cousin marriages and significant inbreeding) were subjected primary genetic components of DN. For complex genetic enti- to a genome scan, and a strong linkage peak was observed on ties such as DN, analysis of 1000 DNA (or more) from many chromosome 18 (46). Evaluation of these loci in the Pima Indi- different families is necessary. This corresponds to Ͼ400,000 ans also showed evidence of linkage, although this region was genotypes. The microsatellite or SNP markers are not specifi- not linked in the original Pima genome scan. The first genome cally associated with genes but are markers for the inheritance scan of DN in African American families has only now been of each small segment of the human genome within which they completed (47). Evidence for a nephropathy locus on chromo- lie. When the genome scan is completed, the result is a data set some 3 was detected in approximately 30% of the families, on that follows the inheritance of every part of every chromosome chromosome 7p in approximately 40% of the families (those in each individual in the study. The resulting statistical analy- with longer duration of diabetes before diagnosis of ESRD), and ses would identify those chromosomal regions with the stron- on chromosome 18q in approximately 65% of the families gest evidence of linkage (assumed to contain the susceptibility (those with early age of diabetes diagnosis). Although these J Am Soc Nephrol 17: 353–360, 2006 Genetics of Diabetes and Its Complications 357 genome scan studies have been performed in diverse popula- complications for targeted intervention and to continue to ex- tions with different study designs and analytical methods, in- plore underlying mechanisms that contribute to their greater vestigators can take some encouragement from the results. risk for disease. Genetic characterization is one important facet Several of these linkage locations are consistent between stud- of an individual’s risk profile that has yet to be proved as an ies. These complementary data increase the likelihood that efficacious strategy, yet it has the potential to allow a targeted several chromosomal locations mapped by linkage analysis and effective approach to identify a smaller subset of patients reflect the presence of true DN genes. for whom specific interventions/treatments should be most A major limitation in gene identification has been adequate effective. sample size with carefully and consistently phenotyped indi- It is apparent from genetic studies of DN and studies of other viduals. Several major multicenter studies are examining sub- diseases such as type 1 diabetes and type 2 diabetes that con- jects and establishing renewable resources for genetic studies, firmation of results in different populations are of great value in particularly in the area of DN. These initiatives include GoKinD trying to assess the validity of individual findings. Evidence of (Genetics of Kidney in Diabetes), FIND (Family Investigation of confirmation from multiple studies is the most widely used Nephropathy and Diabetes), and EDIC (Epidemiology of Dia- metric for accepting evidence of the importance of a gene in betes In Complications) Genetics. The purpose of the GoKinD contribution to variation to risk for diabetes and its complica- Study is to establish a repository of DNA and clinical informa- tions. Although this outcome would be comforting, there are (at tion from adults with long-term type 1 diabetes, with or with- least) two situations that limit the utility of population replica- out kidney disease, along with their parents (trios). The Go- tion as a means for determining success of susceptibility gene KinD study has screened Ͼ5500 participants and obtained identification. One limitation is if the “truth” in the genetics of DNA to generate lymphoblast cell lines that are available for diabetes or complications is in a series of population-specific researchers. The FIND study also has established immortalized private mutations within a common susceptibility framework. cell lines from approximately 6000 individuals in families that In this case, each population would be consistent with evidence are enriched for the presence of overt DN (mainly from type 2 for linkage at multiple sites, but the specific pattern of muta- diabetes). A data from a sibling without diabetes has also been tions could be different. A second limitation is that the same collected for mapping of type 2 diabetes genes. African Amer- constellation of genetic factors contributes to susceptibility in ican, European American, Mexican American, and American all populations, but the subset of factors and effect sizes may Indian families are being recruited in nearly equal numbers. differ. Thus, simple comparison of results across populations The EDIC Genetics study has recruited nearly 1500 individuals may provide erroneous “failure to replicate.” with type 1 diabetes (including measures of nephropathy and The technology for carrying out large-scale molecular genetic retinopathy) and 3000 relatives. Thus, in the near future, a studies is rapidly improving. In the near future, it will be significant set of resources will become available for investiga- possible to combine the power and the ease of association tors of the genetic basis of type 1 and 2 diabetes and DN. studies with comprehensive examination of the genome (whole genome association). One intriguing study that used elements Summary of this approach has been reported (50) with 55,000 gene-based For effective reduction of the effect of diabetes and its com- SNP loci. A single gene encoding solute carrier family 12 mem- plications and numerous public and personal health conse- ber3(SLC12A3), the gene associated with Gitelman’s syn- quences, every effort must be made to minimize the develop- drome, exhibited consistent evidence for association with DN ment of diabetes and early progression to diabetic susceptibility with a single SNP in intron 24 having statistically complications. A current limitation of progress in this regard is significant association. The results suggested that the uncertainty on who is “at risk.” Although there are no recog- Arg913Gln substitution in the SLC12A3 gene provided protec- nized preventive measures for type 1 diabetes, numerous stud- tion from development of DN. 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