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      Consistent Association of Type 2 Diabetes Risk Variants Found in Europeans in Diverse Racial and Ethnic Groups


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          It has been recently hypothesized that many of the signals detected in genome-wide association studies (GWAS) to T2D and other diseases, despite being observed to common variants, might in fact result from causal mutations that are rare. One prediction of this hypothesis is that the allelic associations should be population-specific, as the causal mutations arose after the migrations that established different populations around the world. We selected 19 common variants found to be reproducibly associated to T2D risk in European populations and studied them in a large multiethnic case-control study (6,142 cases and 7,403 controls) among men and women from 5 racial/ethnic groups (European Americans, African Americans, Latinos, Japanese Americans, and Native Hawaiians). In analysis pooled across ethnic groups, the allelic associations were in the same direction as the original report for all 19 variants, and 14 of the 19 were significantly associated with risk. In summing the number of risk alleles for each individual, the per-allele associations were highly statistically significant (P<10 −4) and similar in all populations (odds ratios 1.09–1.12) except in Japanese Americans the estimated effect per allele was larger than in the other populations (1.20; P het = 3.8×10 −4). We did not observe ethnic differences in the distribution of risk that would explain the increased prevalence of type 2 diabetes in these groups as compared to European Americans. The consistency of allelic associations in diverse racial/ethnic groups is not predicted under the hypothesis of Goldstein regarding “synthetic associations” of rare mutations in T2D.

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          Single rare causal alleles and/or collections of multiple rare alleles have been suggested to create “synthetic associations” with common variants in genome-wide association studies (GWAS). This model predicts that associations with common variants will not be consistent across populations. In this study, we examined 19 T2D variants for association with T2D risk in 6,142 cases and 7,403 controls from five racial/ethnic populations in the Multiethnic Cohort (European Americans, African Americans, Latinos, Japanese Americans, and Native Hawaiians). In racial/ethnic pooled analysis, all 19 variants were associated with T2D risk in the same direction as previous reports in Europeans, and the sum total of risk variants was significantly associated with T2D risk in each racial/ethnic group. The consistent associations across populations do not support the Goldstein hypothesis that rare causal alleles underlie GWAS signals. We also did not find evidence that these markers underlie racial/ethnic disparities in T2D prevalence. Large-scale GWAS and sequencing studies in these populations are necessary in order to both improve the current set of markers at these risk loci and identify new risk variants for T2D that may be difficult, or impossible, to detect in European populations.

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          A genome-wide association study identifies novel risk loci for type 2 diabetes.

          Type 2 diabetes mellitus results from the interaction of environmental factors with a combination of genetic variants, most of which were hitherto unknown. A systematic search for these variants was recently made possible by the development of high-density arrays that permit the genotyping of hundreds of thousands of polymorphisms. We tested 392,935 single-nucleotide polymorphisms in a French case-control cohort. Markers with the most significant difference in genotype frequencies between cases of type 2 diabetes and controls were fast-tracked for testing in a second cohort. This identified four loci containing variants that confer type 2 diabetes risk, in addition to confirming the known association with the TCF7L2 gene. These loci include a non-synonymous polymorphism in the zinc transporter SLC30A8, which is expressed exclusively in insulin-producing beta-cells, and two linkage disequilibrium blocks that contain genes potentially involved in beta-cell development or function (IDE-KIF11-HHEX and EXT2-ALX4). These associations explain a substantial portion of disease risk and constitute proof of principle for the genome-wide approach to the elucidation of complex genetic traits.
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            Rare Variants Create Synthetic Genome-Wide Associations

            Introduction Efforts to fine map the causal variants responsible for genome-wide association studies (GWAS) signals have been largely predicated on the common disease common variant theory, postulating a common variant as the culprit for observed associations. This has led to extensive resequencing efforts that have been largely unsuccessful [1]–[5]. Here, we explore the possibility that part of the reason for this may be that the disease class causing an observed association may consist of multiple low-frequency variants across large regions of the genome—a phenomenon we call synthetic association. For convenience, these less common variants will be referred to here as “rare,” but we emphasize that we use this term loosely, only to refer to variants less common than those routinely studied in GWAS. The basic idea of how synthetic associations emerge in this model is illustrated in Figure 1, which shows how rare variants, by chance, can occur disproportionately in some parts of a gene genealogy. Any variant “higher up in the genealogy” that partitions those parts of the genealogy containing more disease variants than average will be identified as disease-associated. It is well appreciated that a noncausal variant will show association with a causal variant if the two are in strong linkage disequilibrium (LD). We use the previously introduced term synthetic association [6], however, to describe how such indirect association can occur between a common variant and at least one and possibly many rarer causal variants. Using the term synthetic as opposed to indirect emphasizes that the properties of the association signal are very different when the responsible variant or variants are much less frequent than the marker that carries the signal, as we detail below. 10.1371/journal.pbio.1000294.g001 Figure 1 Example genealogies showing causal variants and the strongest association for a common variant. (A) A genealogy with 10,000 original haplotypes was generated with 3,000 cases and 3,000 controls, genotype relative risk (γ) = 4, and nine causal variants. The branches containing the strongest synthetic association are indicated in blue. The branches containing the rare causal variants are in red. (B) A second genealogy was generated using the same parameters. These genealogies demonstrate two scenarios with genome-wide significant synthetic associations: the first (upper genealogy) had a high risk allele frequency (RAF = 0.49), and the second (lower genealogy) had a low RAF (0.08). To assess the tendency of rare disease-causing variants to create synthetic signals of association that are credited to single polymorphisms that are much more common in the population than the causal variants, we have simulated 10,000 haplotypes based on a coalescent model in a region either with or without recombination (Materials and Methods). We assumed that gene variants that influence disease have an allele frequency between 0.005 and 0.02, which is generally below the range of reliable detection (either by inclusion or indirect representation) using the genome-wide association platforms currently in use. We assumed a baseline probability of disease of φ for individuals with none of the rare genetic risk factors. The presence of at least one rare risk allele at the locus increased the probability of disease from φ to γ. We considered two values of φ (0.01, 0.1) and chose values of the penetrance γ such that the genotypic relative risk (GRR) of the rare causal variants varied incrementally between 2 and 6, where GRR is the ratio γ/φ. These values were chosen to explore the space around a GRR of 4, a threshold above which consistent linkage signals would be expected [7]. We simulated scenarios with one, three, five, seven, and nine rare causal variants. Results Across the conditions we have studied, not only is it possible to achieve genome-wide significance for common variants when one or more rare variants are the only contributors to disease, it is often the likely outcome (Figure 2). Overall, 30% of the simulations were able to detect an association with a common SNP at genome-wide significance (p 5%, Hardy-Weinberg equilibrium p-value >1×10−6, SNP call rate >95%), using the PLINK software [40]. For the sickle cell anemia GWAS, we compared 194 cases and 7,407 controls of inferred African ancestry via multidimensional scaling, with a genomic control inflation factor of 1.01. For hearing loss, we performed a GWAS on 418 cases and 6,892 control subjects, all of whom were of genetically inferred European ancestry via multidimensional scaling, with a genomic control inflation factor of 1.02.
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              The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes.

              Genetic association studies are viewed as problematic and plagued by irreproducibility. Many associations have been reported for type 2 diabetes, but none have been confirmed in multiple samples and with comprehensive controls. We evaluated 16 published genetic associations to type 2 diabetes and related sub-phenotypes using a family-based design to control for population stratification, and replication samples to increase power. We were able to confirm only one association, that of the common Pro12Ala polymorphism in peroxisome proliferator-activated receptor-gamma(PPARgamma) with type 2 diabetes. By analysing over 3,000 individuals, we found a modest (1.25-fold) but significant (P=0.002) increase in diabetes risk associated with the more common proline allele (85% frequency). Moreover, our results resolve a controversy about common variation in PPARgamma. An initial study found a threefold effect, but four of five subsequent publications failed to confirm the association. All six studies are consistent with the odds ratio we describe. The data implicate inherited variation in PPARgamma in the pathogenesis of type 2 diabetes. Because the risk allele occurs at such high frequency, its modest effect translates into a large population attributable risk-influencing as much as 25% of type 2 diabetes in the general population.

                Author and article information

                Role: Editor
                PLoS Genet
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                August 2010
                August 2010
                26 August 2010
                : 6
                : 8
                [1 ]Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, California, United States of America
                [2 ]Epidemiology Program, Cancer Research Center, University of Hawaii, Honolulu, Hawaii, United States of America
                [3 ]Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts, United States of America
                [4 ]Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America
                [5 ]Department of Molecular Biology, Massachusetts General Hospital, Boston, Massachusetts, United States of America
                [6 ]Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
                [7 ]Diabetes Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
                University of Oxford, United Kingdom
                Author notes

                Conceived and designed the experiments: KMW MTH LLM LRW GM KRM LNK BEH CAH. Performed the experiments: KMW MTH. Analyzed the data: KMW DOS CAH. Contributed reagents/materials/analysis tools: LNK BEH CAH. Wrote the paper: KMW DOS DA CAH.

                Waters et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                Page count
                Pages: 9
                Research Article
                Diabetes and Endocrinology/Type 2 Diabetes
                Genetics and Genomics
                Public Health and Epidemiology/Epidemiology



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