Curr Diab Rep (2014) 14:550 DOI 10.1007/s11892-014-0550-9

GENETICS (AP MORRIS, SECTION EDITOR)

Overlap of Genetic Susceptibility to Type 1 Diabetes, Type 2 Diabetes, and Latent Autoimmune Diabetes in Adults Kevin J. Basile & Vanessa C. Guy & Stanley Schwartz & Struan F. A. Grant

# Springer Science+Business Media New York 2014

Abstract Despite the notion that there is a degree of commonality to the biological etiology of type 1 diabetes (T1D) and type 2 diabetes (T2D), the lack of overlap in the genetic factors underpinning each of them suggests very distinct mechanisms. A disorder considered to be at the “intersection” of these two diseases is “latent autoimmune diabetes in adults” (LADA). Interestingly, genetic signals from both T1D and T2D are also seen in LADA, including the key HLA and transcription factor 7-like 2 (TCF7L2) loci, but the magnitudes of these effects are more complex than just pointing to LADA as being a simple admixture of T1D and T2D. We review the current status of the understanding of the genetics of LADA and place it in the context of what is known about the genetics of its better-studied “cousins,” T1D and T2D, especially with respect to the myriad of discoveries made over the last decade through genome-wide association studies.

Keywords Type 1 diabetes . Type 2 diabetes . Latent autoimmune diabetes in adults . TCF7L2 . HLA . Genome-wide association studies This article is part of the Topical Collection on Genetics

K. J. Basile : V. C. Guy : S. F. A. Grant Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA S. Schwartz Main Line Health System, Wynnewood, PA 19104, USA S. F. A. Grant Department of Pediatrics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA S. F. A. Grant (*) Children’s Hospital of Philadelphia Research Institute, 1102D, 3615 Civic Center Blvd., Philadelphia, PA 19104, USA e-mail: [email protected]

Introduction Type 1 and type 2 diabetes (T1D and T2D) are diseases characterized by hyperglycemia, both resulting from metabolic consequences of β-cell dysfunction and/or the inability of insulin to properly regulate levels of blood glucose. Hyperglycemia associated with both T1D and T2D causes similar chronic clinical complications if not properly managed. These complications include microvascular disease and accelerated development of cardiovascular symptoms. Both T1D and T2D are classified as forms of diabetes mellitus, which affects approximately 200 million adults worldwide. Of these individuals affected, approximately 90 to 95 % are afflicted with T2D rather than T1D. The high prevalence of diabetes has put a tremendous burden on healthcare systems. According to the American Diabetes Association (ADA), the total cost of direct and indirect medical expenses related to diabetes in the USA rose to $245 billion in 2012. This figure represents a 41 % increase in costs associated with the disease in the last 5 years. Although T1D and T2D share some clinical similarities, these diseases are the result of distinct biological mechanisms. T1D typically presents in childhood and is the result of autoimmune destruction of the insulin-producing β-cells of the pancreas, while T2D typically presents in adults (>40 years of age) and occurs by reduced insulin secretion due to abnormalities in pancreatic β-cell function or decreased β-cell mass, and exacerbated in many by insulin resistance in skeletal muscle, liver, and adipose tissue. There is also phenotypic overlap between these classic descriptions, as one also sees “T1D” patients with insulin resistance and “T2D” patients with evidence of autoimmune/inflammatory destruction of β-cells. Despite suggestions that genetic similarities exist between T1D and T2D [1], the loci reported thus far for each of these phenotypes appear largely different from one another

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[2, 3], which further supports the fact that these are two distinct diseases (reviewed in more detail below). In addition to T1D and T2D, there exists another form of diabetes mellitus known as latent autoimmune diabetes in adults (LADA). According to the World Health Organization, LADA is a slowly progressing form of T1D due to the fact that it seems to be caused by a similar mechanism as T1D (i.e., autoimmune destruction of pancreatic βcells). However, despite this similarity, the pathophysiology and clinical presentation of LADA is considered less understood and less clearly defined than either T1D or T2D. Generally, LADA exhibits characteristics of both T1D and T2D, which explains why many refer to LADA as “Type 1.5 Diabetes” [2]. For example, LADA can often be clinically indistinguishable from T2D, due to the fact that it presents in adulthood and initially does not involve the requirement for insulin, typically with no absolute dependence on insulin therapy for at least the first 6 months after onset [4, 5]. However, similar to T1D, they are characterized by circulating islet auto-antibodies [6]. In fact, typically 8–10 % of apparent T2D cases are actually LADA cases that have been misclassified. Despite the recognition of LADA as a specific subset of diabetes mellitus, the clinical definition for this disease entity is still in relative disarray, including an ongoing disagreement on how the actual age of onset should be defined [7, 8].

Genetics of Diabetes Diabetes is considered complex for a reason—it involves an elaborate interplay between individual genetic makeup and the environment in which one resides. Despite this complexity, it has been known for many years that diabetes is influenced by genetics. For both T1D and T2D, there is evidence for this genetic contribution that includes population prevalence differences around the world (although this could also be partially explained by differential exposure), concordance rates that are higher in monozygotic twins when compared with dizygotic twins and transmission within families. As the genetic contribution to T2D has been considered relatively weak when contrasted with type 1 diabetes (T1D) [9, 10], it has proven more challenging to identify genes for T2D, with it earning the nickname of the “geneticist’s nightmare” prior to the advent of genome-wide association studies (GWAS). The utility of high-throughput single nucleotide polymorphism (SNP) genotyping arrays in recent years has allowed investigators to carry out non-hypothesis-driven GWAS analyses to uncover key genetic signals contributing to the pathogenesis of most complex traits. Indeed, combined with the well-established genes known for many years, GWAS has now clearly revealed many tens of loci driving T1D [11–19] and T2D risk [20–41].

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It is well established that common genetic variation within the human leukocyte antigen (HLA) class II loci explains a sizable proportion of the genetic risk for T1D in the young, while the strongest associated T2D variant is found within intron 3 of the gene-encoding transcription factor 7-like 2 (TCF7L2) [42]. However, unlike T1D and T2D, nonhypothesis-driven genetic studies of LADA are lacking and no novel loci for this disease have been described to date, although many candidate loci have been tested in this setting. As such, to put LADA in context, we must first review the genetic factors contributing to these two diseases. Type 1 Diabetes Prior to GWAS efforts, a number of genes were already established to be associated with T1D, based on efforts from candidate gene and linkage analyses. Clearly, the strongest association with T1D is located within the HLA class II genes (primarily the HLA-DRB1, -DQA1, and -DQB1 loci), explaining approximately 50 % of the estimated genetic component of the disease. This locus is complemented with other, albeit relatively weaker, established links with the genes encoding insulin (INS) [43–45], cytotoxic T-lymphocyteassociated protein 4 (CTLA4) [46–49], and protein tyrosine phosphatase-22 (PTPN22) [50, 51]. And just before the dawn of GWAS, two additional genes were implicated from relatively low-resolution genotyping array approaches, namely those encoding interleukin 2 receptor alpha (IL2RA) [52] and interferon-induced with helicase C domain 1 (IFIH1) [11]. GWAS has certainly added substantially to the list of loci contributing to the pathogenesis of T1D. The first locus identified in this recent era harbored the predicted KIAA0350 gene, which was subsequently renamed C-type lectin domain family 16, member A (CLEC16A) due to the presence of a predicted C-type lectin binding domain; however, there is increasing evidence that the causal gene at this locus is in fact DEXI [53]. This signal was picked up both in a US-Canadian collaboration [14] and by the Wellcome Trust Case-Control Consortium (WTCCC) [12, 21]. The latter study also uncovered signals at 12q24, 12q13, and 18p11. The subsequent combining of GWAS datasets in to larger “meta-analyses” allows one to have greater statistical power to detect additional loci and provides greater return on the sizeable investment made in generating such large genome-wide genotyping datasets. Indeed, when such studies were conducted, additional T1D risk loci were readily identified [16, 17, 19], including ubiquitin-associated and SH3 domaincontaining protein A (UBASH3A), BTB and broad complextramtrack-bric-a-brac (BTB) and cap “n” collar (CNC) homology 2′ (BACH2), protein kinase C, theta, gene (PRKCQ), cathepsin H (CTSH) and 22q13 harboring the “C1q and tumor necrosis factor related protein 6” (C1QTNF6), somatostatin receptor 3 (SSTR3), 1q32.1 (harboring the interleukin genes

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IL10, IL19, and IL20), Glis family zinc finger protein 3 (GLIS3), CD69, and interleukin 27 (IL27). And the most recent and largest T1D meta-analysis reported to date uncovered three additional loci, namely encoding EFR3 homolog B (EFR3B), 6q27, and LIM domain 7 (LMO7) [18]. Type 2 Diabetes Due to the sheer prevalence of T2D, this disease has received widespread attention by the GWAS field and has typically led the way in how to appropriately tackle the discovery of loci in this very high-throughput setting and has thus been the focus of more GWAS analyses than any other disorder studied to date. As with T1D, this has proved largely successful in identifying novel loci to complement those already implicated in the candidate gene era, in this case, peroxisome proliferatoractivated receptor gamma (PPARG) [54] and potassium inwardly rectifying channel, subfamily J, member 11 (KCNJ11) [55]. The first GWAS reports for T2D [20–24] were relatively consistent in what they observed, with the strongest signal clearly being at a locus harboring the gene encoding transcription factor 7-like 2 (TCF7L2). Interestingly, this locus was first identified a year earlier as a consequence of following up of a linkage region detected in extended Icelandic pedigrees [42]; indeed, this association has gone on to be widely replicated in cohorts of European, Asian, and African populations [56], and is therefore now largely viewed as the strongest common variant genetic association with T2D in the vast majority of ethnicities [57, 58]. Indeed, the first functional studies of TCF7L2 in this context have pointed to a role in insulin secretion, via the pancreatic β-cell, either directly or indirectly [59, 60]. In addition to TCF7L2, these first studies uncovered additional loci harboring the genes encoding homeobox hematopoietically expressed (HHEX), solute carrier family 30 (zinc transporter), member 8 (SLC30A8), CDK5 regulatory subunit associated protein 1-like 1 (CDKAL1), insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2), cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B), and an intragenic region on 11p12. The first meta-analysis of T2D [25] subsequently found six additional loci, namely ADAM metallopeptidase with thrombospondin type 1 motif, 9 (ADAMTS9), tetraspanin 8/leucine-rich repeat-containing G protein-coupled receptor 5 (TSPAN8-LGR5), cell division cycle 123 homolog/calcium/calmodulin-dependent protein kinase ID (CDC123-CAMK1D), NOTCH2, thyroid adenoma associated (THADA), juxtaposed with another zinc finger gene 1 (JAZF1). In parallel, a study in East Asia revealed potassium voltage-gated channel, KQT-like subfamily, member 1 (KCNQ1) to be associated with the trait [27, 28]. Subsequent meta-analyses-related approaches have revealed common loci of increasingly diminishingly small effect sizes [25, 26,

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29–32, 34–39, 41], with the latest seven loci resulting from a trans-ancestry meta-analysis consisting of 26,488 cases and 83,964 controls of European, East Asian, South Asian, and Mexican and Mexican-American ancestry in the discovery stage, uncovering transmembrane protein 154 (TMEM154), signal sequence receptor, alpha/ras responsive element binding protein 1 (SSR1-RREB1), Fas-associated factor 1 (FAF1), POU class 5 homeobox 1/transcription factor 19 (POU5F1TCF19), ADP-ribosylation factor-like 15 (ARL15), and Mphase phosphoprotein 9 (MPHOSPH9) [37]. Furthermore, sequence variants in solute carrier family 16, member 11 (SLC16A11) have been recently implicated as a common risk factor for T2D in Mexico [61]. In addition to the common variants that are amenable for detection with GWAS, sequencing studies are now starting to be reported for T2D, with examples of rare variants contributing to T2D now appearing in the literature, including within HNF1 homeobox A (HNF1A) [62], cyclin D2 (CCND2), peptidylglycine alpha-amidating monooxygenase (PAM), and pancreatic and duodenal homeobox 1 (PDX1) [63] plus evidence of rare loss-of-function variants in solute carrier family 30 (SLC30A8) conferring protection [64]. However, very large sample sizes are required to detect such variants so even bigger cohorts will be required to uncover additional signals. As such, tens of T2D loci have now been reported. Although these findings have been heralded as a success, many more signals will need to be uncovered to account for the “missing heritability” [65] that remains uncharacterized for T2D.

Genetic Commonality to T1D and T2D? It has long been thought that T1D and T2D may share a degree of common genetic predisposition [1], given that they both result from abnormal β-cell function and/or destruction. However, the established susceptibility genes for these diseases have generally not been shown to overlap [2, 3, 66]. Most notably, there is no correlation between the TCF7L2 locus and T1D [66–68]. However, a recent study did implicate the T2D genes encoding melatonin receptor 1B (MTNR1B) and HNF1A in T1D [69]. In the latest trans-ethnic metaanalysis (also described above), given that POU5F1-TCF19 is within the major histocompatibility complex (MHC), the authors did also note that when they considered the T1D loci reported to date, they found a degree of evidence of association with two of them, namely GLIS3 and 6q22.32 [37]. As such, based on these genetic observations, the mechanistic underpinnings of T1D and T2D appear to be primarily distinct; in fact, at this point in our understanding, the genetics of T2D look more similar to that of cancer than that of T1D [70], based on what we have learnt from GWAS outcomes.

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Latent Autoimmune Diabetes in Adults The genetic component of LADA has still to be elucidated. Despite the fact that LADA is at least two times more common than T1D, very few efforts have been made to elucidate the genetic etiology of this trait, primarily due to an ongoing debate about its precise definition. However, the studies that have been conducted to date largely attack the question from the standpoint that there may be some degree of contribution from both T1D and T2D given that phenotypically, it roughly falls in between these two more investigated diseases. As such, testing already-established genetic associations with either T1D or T2D in the context of LADA has provided the first insight in to the genetic makeup of this disease. Despite there being only a few cohorts of sufficient sample size to look at the correlation between genetic variants and LADA, a number of studies have already reported what T1D loci are doing in this setting [4, 71–75]. The most obvious place to start is with the HLA locus, given that it confers approximately half of the genetic susceptibility to T1D [76]. Indeed, there is strong evidence that the HLA locus does indeed contribute to LADA [4, 71, 73], although the effect does not appear as marked, with DQB1 *0201/*0302 being a greater driver for T1D risk compared to that of LADA, while the T1D protective genotypes of *0602/X and 0603/X are found more frequently among LADA cases [4]. When turning to other T1D loci, most of these remain to be tested, but the very established INS locus does appear to confer the same magnitude of risk to both T1D [77] and LADA [72], while the PTPN22 association is substantially weaker in LADA [78]. Analyses of T2D loci in the context of LADA have largely focused on TCF7L2, primarily due to the fact that it was discovered relatively early on in the GWAS era and generally confers the strongest risk to T2D among common variants. Despite the fact that the TCF7L2 locus shows absolutely no association with T1D, Cervin et al. found that this locus conferred a similar magnitude of effect in LADA as in T2D [78] and has now been supported by others [79]. A subsequent study not only observed the same correlation but also noted that fasting C peptide serum concentrations were lower among LADA patients homozygous for the T2D risk TCF7L2 variant [80]. However, it is becoming increasingly clear that the magnitude of the association between LADA and TCF7L2 is correlated with antibody titer, where the lower it is, the stronger the association [69, 81]. Furthermore, it has even been proposed that TCF7L2 genotype status can be used to discriminate between middle-aged antibody-positive patients from those that are young antibody-positive [82]. A very recent study expanded on the TCF7L2 observations by testing all established GWAS-implicated T2D loci in the context of LADA [69]. In addition to TCF7L2, the authors also found strong evidence for the zinc finger, MIZ-type

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containing 1 (ZMIZ1) locus being associated with the disease. When considering only low titer glutamate decarboxylase antibody (GADab) positive subjects, there was observed association with KCNQ1, HHEX, and MTNR1B, which may reflect that this subform of LADA is phenotypically closer to T2D. However, and most interestingly, they found evidence for kelch-like family member 42 (KLHDC5), tumor protein p53 inducible nuclear protein 1 (TP53INP1), CDKAL1, and prospero homeobox 1 (PROX1) in high GADab titer LADA patients. As such, these observations speak to the possibility that LADA is either an admixture of T1D and T2D [83] or some other distinct form of diabetes [84]. Indeed, some of these variants could possibly be used to distinguish juvenile onset T1D from LADA. In addition, given that many genetic studies of T2D do not account for the likely presence of GADab positive cases, it is possible that some observed associations may be driven by LADA rather than T2D, leading one to ask if some loci reported for T2D may in fact be LADA loci. LADA—a Major Confounder in Genetic Studies of T2D? Based on the observations outlined above, it is apparent that the genetics of diabetes as a whole can be confusing and, thus, elucidating the genetics of LADA (however, the phenotype is ultimately defined) should help clarify the overall picture. As larger and larger sample sizes are required in GWAS meta-analyses and sequencing efforts to find additional loci that are becoming increasingly diminutive in their effect size and/or frequency, the need for greater LADA genetics knowledge only grows stronger so as to avoid reporting possible artifacts. This can be highlighted by the gradual decrease in reported odds ratios (OR) by GWAS meta-analyses, from the top GWAS signal for T2D in Caucasians (TCF7L2, OR ~1.4) to the latest trans-ethnic meta-analysis-uncovered loci with an OR magnitude substantially lower than 1.1. As such, the subsequent and even larger meta-analyses are going after variants which may well have an OR magnitude of approximately 1.01. These extremely small effect size variants that can only be uncovered in such large sample sets begs the question—could this diminished return with respect to OR also be compounded by obvious comorbidities that have not been accounted for, such as antibody positivity, among a cohort of apparent T2D cases? As replication cohorts are typically designed in a similar fashion and, thus, may also harbor unaccounted comorbidities, a certain variant may continue to be inappropriately assigned to a trait. The rising risk of artifacts as sample sizes enlarge in the search for variants of more modest effects can only increase the likelihood of incorrect assignments. Given that the presence of antibody positivity among a random group of T2D cases is approximately 8–10 %, this large contaminant could

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be driving many of the recent observations. For instance, the GLIS3 and ZMIZ1 loci assigned to T2D risk are wellestablished autoimmune loci and could be involved in driving the association by the presence of LADA cases in these T2D GWAS analyses. It would seem that investigators should consider ascertaining GADab-positive participants in their T2D genetic studies (or at least in a subset) going forward to determine the principal driver of the signal. After all, would any other experimental setting be considered credible if 10 % of samples were not correctly assigned?

Conclusions LADA is clearly a complex and heterogeneous disorder [83], which still requires a tighter definition. Although many studies have discovered underlying genetic susceptibility to T1D and T2D, relatively little is known about the genetics of LADA. Additionally, it remains unclear whether LADA is (1) simply a late manifestation of T1D, (2) an amalgamation of T1D and T2D, or (3) a completely separate and distinct form of diabetes mellitus. Additionally, despite all the progress made in finding the genetic contribution of T1D and T2D, much of the genetic heritability of these two diseases remains to be elucidated. Therefore, attempts to fill in the “missing pieces” may also help to more clearly define LADA. Additionally, it is crucial to perform further genetic analyses for LADA itself. Progress has been impeded, however, due to the challenges in determining LADA precisely, generally requiring the ascertainment of GADab levels and dealing with the lack of agreement on a definition even among clinicians. That said, a large-scale genome-wide survey of LADA would provide key insights into this disease category, with the positive control loci of TCF7L2 and the MHC acting as guides while searching for novel genetic signals. And, finally, we call upon the T2D GWAS community to strongly consider GADab status, at least in a subset of their cohorts in a consortia-based meta-analysis setting, in order to elucidate which trait is the principal driver of signals that will be undoubtedly reported in the future. With these types of meta-analyses, where analysts combine more and more datasets, the biology may sometimes be obscured, but this has to be addressed if large genetic efforts are going to bear consistently credible fruit. Compliance with Ethics Guidelines Conflict of Interest Kevin J. Basile, Vanessa C. Guy, Stanley Schwartz, and Struan F.A. Grant report grants from the National Institutes of Health during the conduct of the study.

Page 5 of 7, 550 Human and Animal Rights and Informed Consent This article does not contain any studies with human or animal subjects performed by any of the authors.

References 1. Wilkin TJ. The accelerator hypothesis: weight gain as the missing link between type I and type II diabetes. Diabetologia. 2001;44:914– 22. 2. Schernthaner G, Hink S, Kopp HP, Muzyka B, Streit G, Kroiss A. Progress in the characterization of slowly progressive autoimmune diabetes in adult patients (LADA or type 1.5 diabetes). Exp Clin Endocrinol Diabetes. 2001;109 Suppl 2:S94–S108. 3. Qu HQ, Grant SF, Bradfield JP, et al. Association analysis of type 2 diabetes loci in type 1 diabetes. Diabetes. 2008;57:1983–6. 4. Tuomi T, Carlsson A, Li H, et al. Clinical and genetic characteristics of type 2 diabetes with and without GAD antibodies. Diabetes. 1999;48:150–7. 5. Tuomi T, Groop LC, Zimmet PZ, Rowley MJ, Knowles W, Mackay IR. Antibodies to glutamic acid decarboxylase reveal latent autoimmune diabetes mellitus in adults with a non-insulin-dependent onset of disease. Diabetes. 1993;42:359–62. 6. Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med. 1998;15:539–53. 7. Gottsater A, Landin-Olsson M, Lernmark A, Fernlund P, Sundkvist G, Hagopian WA. Glutamate decarboxylase antibody levels predict rate of beta-cell decline in adult-onset diabetes. Diabetes Res Clin Pract. 1995;27:133–40. 8. Turner R, Stratton I, Horton V, et al. UKPDS 25: autoantibodies to islet-cell cytoplasm and glutamic acid decarboxylase for prediction of insulin requirement in type 2 diabetes. UK Prospective Diabetes Study Group. Lancet. 1997;350:1288–93. 9. Rich SS. Mapping genes in diabetes. Genetic epidemiological perspective. Diabetes. 1990;39:1315–9. 10. Clayton DG. Prediction and interaction in complex disease genetics: experience in type 1 diabetes. PLoS Genet. 2009;5:e1000540. 11. Smyth DJ, Cooper JD, Bailey R, et al. A genome-wide association study of nonsynonymous SNPs identifies a type 1 diabetes locus in the interferon-induced helicase (IFIH1) region. Nat Genet. 2006;38: 617–9. 12. Todd JA, Walker NM, Cooper JD, et al. Robust associations of four new chromosome regions from genome-wide analyses of type 1 diabetes. Nat Genet. 2007;39:857–64. 13. Hakonarson H, Qu HQ, Bradfield JP, et al. A novel susceptibility locus for type 1 diabetes on Chr12q13 identified by a genome-wide association study. Diabetes. 2008;57:1143–6. 14. Hakonarson H, Grant SF, Bradfield JP, et al. A genome-wide association study identifies KIAA0350 as a type 1 diabetes gene. Nature. 2007;448:591–4. 15. Concannon P, Onengut-Gumuscu S, Todd JA, et al. A human type 1 diabetes susceptibility locus maps to chromosome 21q22.3. Diabetes. 2008;57:2858–61. 16. Cooper JD, Smyth DJ, Smiles AM, et al. Meta-analysis of genomewide association study data identifies additional type 1 diabetes risk loci. Nat Genet. 2008;40:1399–401. 17. Grant SF, Qu HQ, Bradfield JP, et al. Follow-up analysis of genomewide association data identifies novel loci for type 1 diabetes. Diabetes. 2009;58:290–5. 18. Bradfield JP, Qu HQ, Wang K, et al. A genome-wide meta-analysis of six type 1 diabetes cohorts identifies multiple associated loci. PLoS Genet. 2011;7:e1002293.

550, Page 6 of 7 19. Barrett JC, Clayton DG, Concannon P, et al. Genome-wide association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes. Nat Genet. 2009;41:703–7. 20. Sladek R, Rocheleau G, Rung J, et al. A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature. 2007;445: 881–5. 21. Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature. 2007;447:661–78. 22. Saxena R, Voight BF, Lyssenko V, et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science. 2007;316:1331–6. 23. Zeggini E, Weedon MN, Lindgren CM, et al. Replication of genomewide association signals in UK samples reveals risk loci for type 2 diabetes. Science. 2007;316:1336–41. 24. Scott LJ, Mohlke KL, Bonnycastle LL, et al. A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science. 2007;316:1341–5. 25. Zeggini E, Scott LJ, Saxena R, et al. Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nat Genet. 2008;40:638–45. 26. Steinthorsdottir V, Thorleifsson G, Reynisdottir I, et al. A variant in CDKAL1 influences insulin response and risk of type 2 diabetes. Nat Genet. 2007;39:770–5. 27. Unoki H, Takahashi A, Kawaguchi T, et al. SNPs in KCNQ1 are associated with susceptibility to type 2 diabetes in East Asian and European populations. Nat Genet. 2008;40:1098–102. 28. Yasuda K, Miyake K, Horikawa Y, et al. Variants in KCNQ1 are associated with susceptibility to type 2 diabetes mellitus. Nat Genet. 2008;40:1092–7. 29. Voight BF, Scott LJ, Steinthorsdottir V, et al. Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis. Nat Genet. 2010;42:579–89. 30. Rung J, Cauchi S, Albrechtsen A, et al. Genetic variant near IRS1 is associated with type 2 diabetes, insulin resistance and hyperinsulinemia. Nat Genet. 2009;41:1110–5. 31. Gudmundsson J, Sulem P, Steinthorsdottir V, et al. Two variants on chromosome 17 confer prostate cancer risk, and the one in TCF2 protects against type 2 diabetes. Nat Genet. 2007;39:977–83. 32. Dupuis J, Langenberg C, Prokopenko I, et al. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat Genet. 2010;42:105–16. 33. Salonen JT, Uimari P, Aalto JM, et al. Type 2 diabetes whole-genome association study in four populations: the DiaGen Consortium. Am J Hum Genet. 2007;81:338–45. 34. DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility. Nat Genet. 46:234-244 35. Cho YS, Chen CH, Hu C, et al. Meta-analysis of genome-wide association studies identifies eight new loci for type 2 diabetes in East Asians. Nat Genet. 2011;44:67–72. 36. Kooner JS, Saleheen D, Sim X, et al. Genome-wide association study in individuals of South Asian ancestry identifies six new type 2 diabetes susceptibility loci. Nat Genet. 2011;43:984–9. 37. DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility. Nat Genet. 2014;46:234–44. 38. Bouatia-Naji N, Bonnefond A, Cavalcanti-Proenca C, et al. A variant near MTNR1B is associated with increased fasting plasma glucose levels and type 2 diabetes risk. Nat Genet. 2009;41: 89–94. 39. Lyssenko V, Nagorny CL, Erdos MR, et al. Common variant in MTNR1B associated with increased risk of type 2 diabetes and impaired early insulin secretion. Nat Genet. 2009;41:82–8.

Curr Diab Rep (2014) 14:550 40. Prokopenko I, Langenberg C, Florez JC, et al. Variants in MTNR1B influence fasting glucose levels. Nat Genet. 2009;41:77–81. 41. Morris AP, Voight BF, Teslovich TM, et al. Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat Genet. 2012;44:981–90. 42. Grant SF, Thorleifsson G, Reynisdottir I, et al. Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes. Nat Genet. 2006;38:320–3. 43. Bell GI, Horita S, Karam JH. A polymorphic locus near the human insulin gene is associated with insulin-dependent diabetes mellitus. Diabetes. 1984;33:176–83. 44. Bennett ST, Lucassen AM, Gough SC, et al. Susceptibility to human type 1 diabetes at IDDM2 is determined by tandem repeat variation at the insulin gene minisatellite locus. Nat Genet. 1995;9:284–92. 45. Barratt BJ, Payne F, Lowe CE, et al. Remapping the insulin gene/ IDDM2 locus in type 1 diabetes. Diabetes. 2004;53:1884–9. 46. Kristiansen OP, Larsen ZM, Pociot F. CTLA-4 in autoimmune diseases—a general susceptibility gene to autoimmunity? Genes Immun. 2000;1:170–84. 47. Ueda H, Howson JM, Esposito L, et al. Association of the T-cell regulatory gene CTLA4 with susceptibility to autoimmune disease. Nature. 2003;423:506–11. 48. Anjos SM, Tessier MC, Polychronakos C. Association of the cytotoxic T lymphocyte-associated antigen 4 gene with type 1 diabetes: evidence for independent effects of two polymorphisms on the same haplotype block. J Clin Endocrinol Metab. 2004;89:6257–65. 49. Nistico L, Buzzetti R, Pritchard LE, et al. The CTLA-4 gene region of chromosome 2q33 is linked to, and associated with, type 1 diabetes. Belgian Diabetes Registry. Hum Mol Genet. 1996;5:1075–80. 50. Bottini N, Musumeci L, Alonso A, et al. A functional variant of lymphoid tyrosine phosphatase is associated with type I diabetes. Nat Genet. 2004;36:337–8. 51. Smyth D, Cooper JD, Collins JE, et al. Replication of an association between the lymphoid tyrosine phosphatase locus (LYP/PTPN22) with type 1 diabetes, and evidence for its role as a general autoimmunity locus. Diabetes. 2004;53:3020–3. 52. Lowe CE, Cooper JD, Brusko T, et al. Large-scale genetic fine mapping and genotype-phenotype associations implicate polymorphism in the IL2RA region in type 1 diabetes. Nat Genet. 2007;39: 1074–82. 53. Davison LJ, Wallace C, Cooper JD, et al. Long-range DNA looping and gene expression analyses identify DEXI as an autoimmune disease candidate gene. Hum Mol Genet. 2012;21:322–33. 54. Altshuler D, Hirschhorn JN, Klannemark M, et al. The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes. Nat Genet. 2000;26:76–80. 55. Gloyn AL, Weedon MN, Owen KR, et al. Large-scale association studies of variants in genes encoding the pancreatic beta-cell KATP channel subunits Kir6.2 (KCNJ11) and SUR1 (ABCC8) confirm that the KCNJ11 E23K variant is associated with type 2 diabetes. Diabetes. 2003;52:568–72. 56. Cauchi S, El Achhab Y, Choquet H, et al. TCF7L2 is reproducibly associated with type 2 diabetes in various ethnic groups: a global meta-analysis. J Mol Med. 2007;85:777–82. 57. Zeggini E, McCarthy MI. TCF7L2: the biggest story in diabetes genetics since HLA? Diabetologia. 2007;50:1–4. 58. Weedon MN. The importance of TCF7L2. Diabet Med. 2007;24: 1062–6. 59. Lyssenko V, Lupi R, Marchetti P, et al. Mechanisms by which common variants in the TCF7L2 gene increase risk of type 2 diabetes. J Clin Invest. 2007;117:2155–63. 60. Hattersley AT. Prime suspect: the TCF7L2 gene and type 2 diabetes risk. J Clin Invest. 2007;117:2077–9. 61. Williams AL, Jacobs SB, Moreno-Macias H, et al. Sequence variants in SLC16A11 are a common risk factor for type 2 diabetes in Mexico. Nature. 2014;506:97–101.

Curr Diab Rep (2014) 14:550 62. Estrada K, Aukrust I, Bjorkhaug L, et al. Association of a lowfrequency variant in HNF1A with type 2 diabetes in a Latino population. JAMA. 2014;311:2305–14. 63. Steinthorsdottir V, Thorleifsson G, Sulem P, et al. Identification of low-frequency and rare sequence variants associated with elevated or reduced risk of type 2 diabetes. Nat Genet. 2014;46:294–8. 64. Flannick J, Thorleifsson G, Beer NL, et al. Loss-of-function mutations in SLC30A8 protect against type 2 diabetes. Nat Genet. 2014;46:357–63. 65. Manolio TA, Collins FS, Cox NJ, et al. Finding the missing heritability of complex diseases. Nature. 2009;461:747–53. 66. Raj SM, Howson JM, Walker NM, et al. No association of multiple type 2 diabetes loci with type 1 diabetes. Diabetologia. 2009;52: 2109–16. 67. Qu HQ, Polychronakos C. The TCF7L2 locus and type 1 diabetes. BMC Med Genet. 2007;8:51. 68. Field SF, Howson JM, Smyth DJ, Walker NM, Dunger DB, Todd JA. Analysis of the type 2 diabetes gene, TCF7L2, in 13,795 type 1 diabetes cases and control subjects. Diabetologia. 2007;50:212–3. 69. Andersen MK, Sterner M, Forsen T, et al. Type 2 diabetes susceptibility gene variants predispose to adult-onset autoimmune diabetes. Diabetologia. 2014; [Epub ahead of print]. 70. Frayling TM, Colhoun H, Florez JC. A genetic link between type 2 diabetes and prostate cancer. Diabetologia. 2008;51:1757–60. 71. Desai M, Zeggini E, Horton VA, et al. An association analysis of the HLA gene region in latent autoimmune diabetes in adults. Diabetologia. 2007;50:68–73. 72. Desai M, Zeggini E, Horton VA, et al. The variable number of tandem repeats upstream of the insulin gene is a susceptibility locus for latent autoimmune diabetes in adults. Diabetes. 2006;55:1890–4. 73. Horton V, Stratton I, Bottazzo GF, et al. Genetic heterogeneity of autoimmune diabetes: age of presentation in adults is influenced by HLA DRB1 and DQB1 genotypes (UKPDS 43). UK Prospective Diabetes Study (UKPDS) Group. Diabetologia. 1999;42:608–16. 74. Hosszufalusi N, Vatay A, Rajczy K, et al. Similar genetic features and different islet cell autoantibody pattern of latent autoimmune diabetes

Page 7 of 7, 550

75.

76.

77. 78.

79.

80.

81.

82.

83.

84.

in adults (LADA) compared with adult-onset type 1 diabetes with rapid progression. Diabetes Care. 2003;26:452–7. Gambelunghe G, Ghaderi M, Tortoioli C, et al. Two distinct MICA gene markers discriminate major autoimmune diabetes types. J Clin Endocrinol Metab. 2001;86:3754–60. Kantarova D, Buc M. Genetic susceptibility to type 1 diabetes mellitus in humans. Physiol Res Acad Sci Bohemoslovaca. 2007;56:255–66. Bennett ST, Todd JA. Human type 1 diabetes and the insulin gene: principles of mapping polygenes. Annu Rev Genet. 1996;30:343–70. Cervin C, Lyssenko V, Bakhtadze E, et al. Genetic similarities between latent autoimmune diabetes in adults, type 1 diabetes, and type 2 diabetes. Diabetes. 2008;57:1433–7. Lukacs K, Hosszufalusi N, Dinya E, Bakacs M, Madacsy L, Panczel P. The type 2 diabetes-associated variant in TCF7L2 is associated with latent autoimmune diabetes in adult Europeans and the gene effect is modified by obesity: a meta-analysis and an individual study. Diabetologia. 2012;55:689–93. Szepietowska B, Moczulski D, Wawrusiewicz-Kurylonek N, Grzeszczak W, Gorska M, Szelachowska M. Transcription factor 7like 2-gene polymorphism is related to fasting C peptide in latent autoimmune diabetes in adults (LADA). Acta Diabetologica. 2009; [Epub ahead of print]. Zampetti S, Spoletini M, Petrone A, et al. Association of TCF7L2 gene variants with low GAD autoantibody titre in LADA subjects (NIRAD Study 5). Diabet Med J Br Diabet Assoc. 2010;27:701–4. Bakhtadze E, Cervin C, Lindholm E, et al. Common variants in the TCF7L2 gene help to differentiate autoimmune from nonautoimmune diabetes in young (15–34 years) but not in middleaged (40–59 years) diabetic patients. Diabetologia. 2008;51:2224– 32. Tuomi T, Santoro N, Caprio S, Cai M, Weng J, Groop L. The many faces of diabetes: a disease with increasing heterogeneity. Lancet. 2014;383:1084–94. Grant SF, Hakonarson H, Schwartz S. Can the genetics of type 1 and type 2 diabetes shed light on the genetics of latent autoimmune diabetes in adults? Endocr Rev. 2010;31:183–93.