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1.  Genome-Wide Association Analysis of Autoantibody Positivity in Type 1 Diabetes Cases 
PLoS Genetics  2011;7(8):e1002216.
The genetic basis of autoantibody production is largely unknown outside of associations located in the major histocompatibility complex (MHC) human leukocyte antigen (HLA) region. The aim of this study is the discovery of new genetic associations with autoantibody positivity using genome-wide association scan single nucleotide polymorphism (SNP) data in type 1 diabetes (T1D) patients with autoantibody measurements. We measured two anti-islet autoantibodies, glutamate decarboxylase (GADA, n = 2,506), insulinoma-associated antigen 2 (IA-2A, n = 2,498), antibodies to the autoimmune thyroid (Graves') disease (AITD) autoantigen thyroid peroxidase (TPOA, n = 8,300), and antibodies against gastric parietal cells (PCA, n = 4,328) that are associated with autoimmune gastritis. Two loci passed a stringent genome-wide significance level (p<10−10): 1q23/FCRL3 with IA-2A and 9q34/ABO with PCA. Eleven of 52 non-MHC T1D loci showed evidence of association with at least one autoantibody at a false discovery rate of 16%: 16p11/IL27-IA-2A, 2q24/IFIH1-IA-2A and PCA, 2q32/STAT4-TPOA, 10p15/IL2RA-GADA, 6q15/BACH2-TPOA, 21q22/UBASH3A-TPOA, 1p13/PTPN22-TPOA, 2q33/CTLA4-TPOA, 4q27/IL2/TPOA, 15q14/RASGRP1/TPOA, and 12q24/SH2B3-GADA and TPOA. Analysis of the TPOA-associated loci in 2,477 cases with Graves' disease identified two new AITD loci (BACH2 and UBASH3A).
Author Summary
Autoantibodies are important markers for autoimmune diseases such as type 1 diabetes and Graves' disease. However, little is known about the genetic factors that control their production. To improve our understanding of this genetic basis, we measured four autoantibodies in a collection of up to 8,300 type 1 diabetes cases plasma samples. We combined these measurements with genome-wide genotype data to conduct four independent genome-wide association studies. Two loci showed unequivocal evidence of autoantibody association: the FCRL3 locus and the ABO blood group locus. Variants in the FCRL3 gene have been previously associated with autoimmune diseases, but such associations have not been reported for ABO blood group genotypes. In addition, we found extensive overlap between type 1 diabetes and autoantibody loci, and these findings provide new information about the role of these risk variants. Lastly, we hypothesized that loci associated with thyroid autoantibodies are strong candidates for association with thyroid autoimmune disorders. We confirmed this hypothesis by genotyping these variants in an independent cohort of Graves' disease cases, and we found evidence for two new Graves' disease loci.
PMCID: PMC3150451  PMID: 21829393
2.  Pilot Genome Wide Association Search Identifies Potential loci for Risk of Erectile Dysfunction in Type 1 Diabetes Using the DCCT/EDIC Study Cohort 
The Journal of urology  2012;188(2):514-520.
To identify genetic predictors of diabetes-associated ED using genome wide and candidate gene approaches in a cohort of men with type I diabetes.
We examined 528 white men with T1D (125 with ED) from the DCCT and its observational follow up EDIC Study. ED was defined from a single item of the IIEF. An Illumina Human1M BeadChip was used for genotyping. 867,125 single nucleotide polymorphisms (SNPs) were subjected to analysis. Whole genome and candidate gene approaches tested the hypothesis that genetic polymorphisms may predispose men with T1D to ED. Univariate and multivariate models were used controlling for age, HbA1c, diabetes duration, and prior randomization to intensive or conventional insulin therapy during DCCT. A stratified false discovery rate was used to perform the candidate gene approach.
Two SNPs located on chromosome 3 in one genomic loci were associated with ED with p < 1×10−6. rs9810233 had a p-value of 7 × 10−7 and rs1920201 had a p-value of 9×10−7 The nearest gene to these two SNPs is ALCAM. The genetic association results at these loci were similar in univariate and multivariate analysis. No candidate genes met criteria for statistical significance.
Two SNPs, rs9810233 and rs1920101, which are 25 kb apart, are both associated with ED, albeit not meeting the standard GWAS significance criteria of p < 5 × 10−8. Other studies with larger sample sizes will be required to determine whether ALCAM represents a novel gene in the pathogenesis of diabetes associated ED.
PMCID: PMC3764461  PMID: 22704111
Erectile Dysfunction; Diabetes; Genetics
3.  A Genome-Wide Association Search for Type 2 Diabetes Genes in African Americans 
PLoS ONE  2012;7(1):e29202.
African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.0 array in 965 African-American cases with T2DM and end-stage renal disease (T2DM-ESRD) and 1029 population-based controls. The most significant SNPs (n = 550 independent loci) were genotyped in a replication cohort and 122 SNPs (n = 98 independent loci) were further tested through genotyping three additional validation cohorts followed by meta-analysis in all five cohorts totaling 3,132 cases and 3,317 controls. Twelve SNPs had evidence of association in the GWAS (P<0.0071), were directionally consistent in the Replication cohort and were associated with T2DM in subjects without nephropathy (P<0.05). Meta-analysis in all cases and controls revealed a single SNP reaching genome-wide significance (P<2.5×10−8). SNP rs7560163 (P = 7.0×10−9, OR (95% CI) = 0.75 (0.67–0.84)) is located intergenically between RND3 and RBM43. Four additional loci (rs7542900, rs4659485, rs2722769 and rs7107217) were associated with T2DM (P<0.05) and reached more nominal levels of significance (P<2.5×10−5) in the overall analysis and may represent novel loci that contribute to T2DM. We have identified novel T2DM-susceptibility variants in the African-American population. Notably, T2DM risk was associated with the major allele and implies an interesting genetic architecture in this population. These results suggest that multiple loci underlie T2DM susceptibility in the African-American population and that these loci are distinct from those identified in other ethnic populations.
PMCID: PMC3251563  PMID: 22238593
4.  Meta-Analysis of Genome-Wide Association Studies in African Americans Provides Insights into the Genetic Architecture of Type 2 Diabetes 
Ng, Maggie C. Y. | Shriner, Daniel | Chen, Brian H. | Li, Jiang | Chen, Wei-Min | Guo, Xiuqing | Liu, Jiankang | Bielinski, Suzette J. | Yanek, Lisa R. | Nalls, Michael A. | Comeau, Mary E. | Rasmussen-Torvik, Laura J. | Jensen, Richard A. | Evans, Daniel S. | Sun, Yan V. | An, Ping | Patel, Sanjay R. | Lu, Yingchang | Long, Jirong | Armstrong, Loren L. | Wagenknecht, Lynne | Yang, Lingyao | Snively, Beverly M. | Palmer, Nicholette D. | Mudgal, Poorva | Langefeld, Carl D. | Keene, Keith L. | Freedman, Barry I. | Mychaleckyj, Josyf C. | Nayak, Uma | Raffel, Leslie J. | Goodarzi, Mark O. | Chen, Y-D Ida | Taylor, Herman A. | Correa, Adolfo | Sims, Mario | Couper, David | Pankow, James S. | Boerwinkle, Eric | Adeyemo, Adebowale | Doumatey, Ayo | Chen, Guanjie | Mathias, Rasika A. | Vaidya, Dhananjay | Singleton, Andrew B. | Zonderman, Alan B. | Igo, Robert P. | Sedor, John R. | Kabagambe, Edmond K. | Siscovick, David S. | McKnight, Barbara | Rice, Kenneth | Liu, Yongmei | Hsueh, Wen-Chi | Zhao, Wei | Bielak, Lawrence F. | Kraja, Aldi | Province, Michael A. | Bottinger, Erwin P. | Gottesman, Omri | Cai, Qiuyin | Zheng, Wei | Blot, William J. | Lowe, William L. | Pacheco, Jennifer A. | Crawford, Dana C. | Grundberg, Elin | Rich, Stephen S. | Hayes, M. Geoffrey | Shu, Xiao-Ou | Loos, Ruth J. F. | Borecki, Ingrid B. | Peyser, Patricia A. | Cummings, Steven R. | Psaty, Bruce M. | Fornage, Myriam | Iyengar, Sudha K. | Evans, Michele K. | Becker, Diane M. | Kao, W. H. Linda | Wilson, James G. | Rotter, Jerome I. | Sale, Michèle M. | Liu, Simin | Rotimi, Charles N. | Bowden, Donald W.
PLoS Genetics  2014;10(8):e1004517.
Type 2 diabetes (T2D) is more prevalent in African Americans than in Europeans. However, little is known about the genetic risk in African Americans despite the recent identification of more than 70 T2D loci primarily by genome-wide association studies (GWAS) in individuals of European ancestry. In order to investigate the genetic architecture of T2D in African Americans, the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium examined 17 GWAS on T2D comprising 8,284 cases and 15,543 controls in African Americans in stage 1 analysis. Single nucleotide polymorphisms (SNPs) association analysis was conducted in each study under the additive model after adjustment for age, sex, study site, and principal components. Meta-analysis of approximately 2.6 million genotyped and imputed SNPs in all studies was conducted using an inverse variance-weighted fixed effect model. Replications were performed to follow up 21 loci in up to 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry. We identified three known loci (TCF7L2, HMGA2 and KCNQ1) and two novel loci (HLA-B and INS-IGF2) at genome-wide significance (4.15×10−94
Author Summary
Despite the higher prevalence of type 2 diabetes (T2D) in African Americans than in Europeans, recent genome-wide association studies (GWAS) were examined primarily in individuals of European ancestry. In this study, we performed meta-analysis of 17 GWAS in 8,284 cases and 15,543 controls to explore the genetic architecture of T2D in African Americans. Following replication in additional 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry, we identified two novel and three previous reported T2D loci reaching genome-wide significance. We also examined 158 loci previously reported to be associated with T2D or regulating glucose homeostasis. While 56% of these loci were shared between African Americans and the other populations, the strongest associations in African Americans are often found in nearby single nucleotide polymorphisms (SNPs) instead of the original SNPs reported in other populations due to differential genetic architecture across populations. Our results highlight the importance of performing genetic studies in non-European populations to fine map the causal genetic variants.
PMCID: PMC4125087  PMID: 25102180
PLoS ONE  2008;3(8):e3019.
Genome-wide association (GWA) studies identified a series of novel type 2 diabetes risk loci. Most of them were subsequently demonstrated to affect insulin secretion of pancreatic β-cells. Very recently, a meta-analysis of GWA data revealed nine additional risk loci with still undefined roles in the pathogenesis of type 2 diabetes. Using our thoroughly phenotyped cohort of subjects at an increased risk for type 2 diabetes, we assessed the association of the nine latest genetic variants with the predominant prediabetes traits, i.e., obesity, impaired insulin secretion, and insulin resistance.
Methodology/Principal Findings
One thousand five hundred and seventy-eight metabolically characterized non-diabetic German subjects were genotyped for the reported candidate single nucleotide polymorphisms (SNPs) JAZF1 rs864745, CDC123/CAMK1D rs12779790, TSPAN8/LGR5 rs7961581, THADA rs7578597, ADAMTS9 rs4607103, NOTCH2 rs10923931, DCD rs1153188, VEGFA rs9472138, and BCL11A rs10490072. Insulin sensitivity was derived from fasting glucose and insulin concentrations, oral glucose tolerance test (OGTT), and hyperinsulinemic-euglycemic clamp. Insulin secretion was estimated from OGTT data. After appropriate adjustment for confounding variables and Bonferroni correction for multiple comparisons (corrected α-level: p = 0.0014), none of the SNPs was reliably associated with adiposity, insulin sensitivity, or insulin secretion (all p≥0.0117, dominant inheritance model). The risk alleles of ADAMTS9 SNP rs4607103 and VEGFA SNP rs9472138 tended to associate with more than one measure of insulin sensitivity and insulin secretion, respectively, but did not reach formal statistical significance. The study was sufficiently powered (1-β = 0.8) to detect effect sizes of 0.19≤d≤0.25 (α = 0.0014) and 0.13≤d≤0.16 (α = 0.05).
In contrast to the first series of GWA-derived type 2 diabetes candidate SNPs, we could not detect reliable associations of the novel risk loci with prediabetic phenotypes. Possible weak effects of ADAMTS9 SNP rs4607103 and VEGFA SNP rs9472138 on insulin sensitivity and insulin secretion, respectively, await further confirmation by larger studies.
PMCID: PMC2500187  PMID: 18714373
PLoS Computational Biology  2013;9(6):e1003101.
Penalized Multiple Regression (PMR) can be used to discover novel disease associations in GWAS datasets. In practice, proposed PMR methods have not been able to identify well-supported associations in GWAS that are undetectable by standard association tests and thus these methods are not widely applied. Here, we present a combined algorithmic and heuristic framework for PUMA (Penalized Unified Multiple-locus Association) analysis that solves the problems of previously proposed methods including computational speed, poor performance on genome-scale simulated data, and identification of too many associations for real data to be biologically plausible. The framework includes a new minorize-maximization (MM) algorithm for generalized linear models (GLM) combined with heuristic model selection and testing methods for identification of robust associations. The PUMA framework implements the penalized maximum likelihood penalties previously proposed for GWAS analysis (i.e. Lasso, Adaptive Lasso, NEG, MCP), as well as a penalty that has not been previously applied to GWAS (i.e. LOG). Using simulations that closely mirror real GWAS data, we show that our framework has high performance and reliably increases power to detect weak associations, while existing PMR methods can perform worse than single marker testing in overall performance. To demonstrate the empirical value of PUMA, we analyzed GWAS data for type 1 diabetes, Crohns's disease, and rheumatoid arthritis, three autoimmune diseases from the original Wellcome Trust Case Control Consortium. Our analysis replicates known associations for these diseases and we discover novel etiologically relevant susceptibility loci that are invisible to standard single marker tests, including six novel associations implicating genes involved in pancreatic function, insulin pathways and immune-cell function in type 1 diabetes; three novel associations implicating genes in pro- and anti-inflammatory pathways in Crohn's disease; and one novel association implicating a gene involved in apoptosis pathways in rheumatoid arthritis. We provide software for applying our PUMA analysis framework.
Author Summary
Genome-wide association studies (GWAS) have identified hundreds of regions of the human genome that are associated with susceptibility to common diseases. Yet many lines of evidence indicate that many susceptibility loci, which cannot be detected by standard statistical methods, remain to be discovered. We have developed PUMA, a framework for applying a family of penalized regression methods that simultaneously consider multiple susceptibility loci in the same statistical model. We demonstrate through simulations that our framework has increased power to detect weak associations compared to both standard GWAS analysis methods and previous applications of penalized methods. We applied PUMA to identify novel susceptibility loci for type 1 diabetes, Crohn's disease and rheumatoid arthritis, where the novel disease loci we identified have been previously associated with similar diseases or are known to function in relevant biological pathways.
PMCID: PMC3694815  PMID: 23825936
Diabetes  2009;58(6):1403-1410.
Despite extensive evidence for genetic susceptibility to diabetic nephropathy, the identification of susceptibility genes and their variants has had limited success. To search for genes that contribute to diabetic nephropathy, a genome-wide association scan was implemented on the Genetics of Kidneys in Diabetes collection.
We genotyped ∼360,000 single nucleotide polymorphisms (SNPs) in 820 case subjects (284 with proteinuria and 536 with end-stage renal disease) and 885 control subjects with type 1 diabetes. Confirmation of implicated SNPs was sought in 1,304 participants of the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) study, a long-term, prospective investigation of the development of diabetes-associated complications.
A total of 13 SNPs located in four genomic loci were associated with diabetic nephropathy with P < 1 × 10−5. The strongest association was at the FRMD3 (4.1 protein ezrin, radixin, moesin [FERM] domain containing 3) locus (odds ratio [OR] = 1.45, P = 5.0 × 10−7). A strong association was also identified at the CARS (cysteinyl-tRNA synthetase) locus (OR = 1.36, P = 3.1 × 10−6). Associations between both loci and time to onset of diabetic nephropathy were supported in the DCCT/EDIC study (hazard ratio [HR] = 1.33, P = 0.02, and HR = 1.32, P = 0.01, respectively). We demonstratedexpression of both FRMD3 and CARS in human kidney.
We identified genetic associations for susceptibility to diabetic nephropathy at two novel candidate loci near the FRMD3 and CARS genes. Their identification implicates previously unsuspected pathways in the pathogenesis of this important late complication of type 1 diabetes.
PMCID: PMC2682673  PMID: 19252134
PLoS Genetics  2011;7(2):e1002004.
Epidemiology and candidate gene studies indicate a shared genetic basis for celiac disease (CD) and rheumatoid arthritis (RA), but the extent of this sharing has not been systematically explored. Previous studies demonstrate that 6 of the established non-HLA CD and RA risk loci (out of 26 loci for each disease) are shared between both diseases. We hypothesized that there are additional shared risk alleles and that combining genome-wide association study (GWAS) data from each disease would increase power to identify these shared risk alleles. We performed a meta-analysis of two published GWAS on CD (4,533 cases and 10,750 controls) and RA (5,539 cases and 17,231 controls). After genotyping the top associated SNPs in 2,169 CD cases and 2,255 controls, and 2,845 RA cases and 4,944 controls, 8 additional SNPs demonstrated P<5×10−8 in a combined analysis of all 50,266 samples, including four SNPs that have not been previously confirmed in either disease: rs10892279 near the DDX6 gene (Pcombined = 1.2×10−12), rs864537 near CD247 (Pcombined = 2.2×10−11), rs2298428 near UBE2L3 (Pcombined = 2.5×10−10), and rs11203203 near UBASH3A (Pcombined = 1.1×10−8). We also confirmed that 4 gene loci previously established in either CD or RA are associated with the other autoimmune disease at combined P<5×10−8 (SH2B3, 8q24, STAT4, and TRAF1-C5). From the 14 shared gene loci, 7 SNPs showed a genome-wide significant effect on expression of one or more transcripts in the linkage disequilibrium (LD) block around the SNP. These associations implicate antigen presentation and T-cell activation as a shared mechanism of disease pathogenesis and underscore the utility of cross-disease meta-analysis for identification of genetic risk factors with pleiotropic effects between two clinically distinct diseases.
Author Summary
Celiac disease (CD) and rheumatoid arthritis (RA) are two autoimmune diseases characterized by distinct clinical features but increased co-occurrence in families and individuals. Genome-wide association studies (GWAS) performed in CD and RA have identified the HLA region and 26 non-HLA genetic risk loci in each disease. Of the 26 CD and 26 RA risk loci, previous studies have shown that six are shared between the two diseases. In this study we aimed to identify additional shared risk alleles and, in doing so, gain more insight into shared disease pathogenesis. We first empirically investigated the distribution of putative risk alleles from GWAS across both diseases (after removing known risk loci for both diseases). We found that CD risk alleles are non-randomly distributed in the RA GWAS (and vice versa), indicating that CD risk alleles have an increased prior probability of being associated with RA (and vice versa). Next, we performed a GWAS meta-analysis to search for shared risk alleles by combing the RA and CD GWAS, performing both directional and opposite allelic effect analyses, followed by replication testing in independent case-control datasets in both diseases. In addition to the already established six non-HLA shared risk loci, we observed statistically robust associations at eight SNPs, thereby increasing the number of shared non-HLA risk loci to fourteen. Finally, we used gene expression studies and pathway analysis tools to identify the plausible candidate genes in the fourteen associated loci. We observed remarkable overrepresentation of T-cell signaling molecules among the shared genes.
PMCID: PMC3044685  PMID: 21383967
Diabetes  2008;57(10):2858-2861.
OBJECTIVE— The Type 1 Diabetes Genetics Consortium (T1DGC) has assembled and genotyped a large collection of multiplex families for the purpose of mapping genomic regions linked to type 1 diabetes. In the current study, we tested for evidence of loci associated with type 1 diabetes utilizing genome-wide linkage scan data and family-based association methods.
RESEARCH DESIGN AND METHODS— A total of 2,496 multiplex families with type 1 diabetes were genotyped with a panel of 6,090 single nucleotide polymorphisms (SNPs). Evidence of association to disease was evaluated by the pedigree disequilibrium test. Significant results were followed up by genotyping and analyses in two independent sets of samples: 2,214 parent-affected child trio families and a panel of 7,721 case and 9,679 control subjects.
RESULTS— Three of the SNPs most strongly associated with type 1 diabetes localized to previously identified type 1 diabetes risk loci: INS, IFIH1, and KIAA0350. A fourth strongly associated SNP, rs876498 (P = 1.0 × 10−4), occurred in the sixth intron of the UBASH3A locus at chromosome 21q22.3. Support for this disease association was obtained in two additional independent sample sets: families with type 1 diabetes (odds ratio [OR] 1.06 [95% CI 1.00–1.11]; P = 0.023) and case and control subjects (1.14 [1.09–1.19]; P = 7.5 × 10−8).
CONCLUSIONS— The T1DGC 6K SNP scan and follow-up studies reported here confirm previously reported type 1 diabetes associations at INS, IFIH1, and KIAA0350 and identify an additional disease association on chromosome 21q22.3 in the UBASH3A locus (OR 1.10 [95% CI 1.07–1.13]; P = 4.4 × 10−12). This gene and its flanking regions are now validated targets for further resequencing, genotyping, and functional studies in type 1 diabetes.
PMCID: PMC2551699  PMID: 18647951
PLoS ONE  2013;8(4):e60646.
The ubiquitin associated and Src-homology 3 (SH3) domain containing A (UBASH3a) is a suppressor of T-cell receptor signaling, underscoring antigen presentation to T-cells as a critical shared mechanism of diseases pathogenesis. The aim of the present study was to determine whether the UBASH3a gene influence the susceptibility to systemic lupus erythematosus (SLE) in Caucasian populations. We evaluated five UBASH3a polymorphisms (rs2277798, rs2277800, rs9976767, rs13048049 and rs17114930), using TaqMan® allelic discrimination assays, in a discovery cohort that included 906 SLE patients and 1165 healthy controls from Spain. The SNPs that exhibit statistical significance difference were evaluated in a German replication cohort of 360 SLE patients and 379 healthy controls. The case-control analysis in the Spanish population showed a significant association between the rs9976767 and SLE (Pc = 9.9E-03 OR = 1.21 95%CI = 1.07–1.37) and a trend of association for the rs2277798 analysis (P = 0.09 OR = 0.9 95%CI = 0.79–1.02). The replication in a German cohort and the meta-analysis confirmed that the rs9976767 (Pc = 0.02; Pc = 2.4E-04, for German cohort and meta-analysis, respectively) and rs2277798 (Pc = 0.013; Pc = 4.7E-03, for German cohort and meta-analysis, respectively) UBASH3a variants are susceptibility factors for SLE. Finally, a conditional regression analysis suggested that the most likely genetic variation responsible for the association was the rs9976767 polymorphism. Our results suggest that UBASH3a gene plays a role in the susceptibility to SLE. Moreover, our study indicates that UBASH3a can be considered as a common genetic factor in autoimmune diseases.
PMCID: PMC3614928  PMID: 23565265
PLoS ONE  2014;9(4):e93193.
Five novel loci recently found to be associated with body mass in two GWAS of East Asian populations were evaluated in two cohorts of Swedish and Greek children and adolescents. These loci are located within, or in the proximity of: CDKAL1, PCSK1, GP2, PAX6 and KLF9. No association with body mass has previously been reported for these loci in GWAS performed on European populations. The single nucleotide polymorphisms (SNPs) with the strongest association at each loci in the East Asian GWAS were genotyped in two cohorts, one obesity case control cohort of Swedish children and adolescents consisting of 496 cases and 520 controls and one cross-sectional cohort of 2293 nine-to-thirteen year old Greek children and adolescents. SNPs were surveyed for association with body mass and other phenotypic traits commonly associated with obesity, including adipose tissue distribution, insulin resistance and daily caloric intake. No association with body mass was found in either cohort. However, among the Greek children, association with insulin resistance could be observed for the two CDKAL1-related SNPs: rs9356744 (β = 0.018, p = 0.014) and rs2206734 (β = 0.024, p = 0.001). CDKAL1-related variants have previously been associated with type 2 diabetes and insulin response. This study reports association of CDKAL1-related SNPs with insulin resistance, a clinical marker related to type 2 diabetes in a cross-sectional cohort of Greek children and adolescents of European descent.
PMCID: PMC3973700  PMID: 24695378
Diabetes  2005;54(4):1238-1244.
The development and progression of microvascular complications have been extensively documented in a cohort of type 1 diabetic subjects enrolled in the Diabetes Control and Complications Trial (DCCT) and followed in the Epidemiology of Diabetes Interventions and Complications (EDIC) study. We describe the association of genetic variation in the ACE gene in 1,365 DCCT/EDIC subjects with incident persistent microalbuminuria (n = 312) and severe nephropathy (n = 115). We studied three markers (rs1800764, insertion/deletion, and rs9896208) in the ACE gene that allowed us to capture genetic variation in the common haplotypes occurring at frequencies of >5% in Caucasians. Compared with the more frequent genotype (D/I) for the insertion/deletion polymorphism, in multivariate models, the I/I genotype conferred a lower risk for persistent microalbuminuria (hazard ratio [HR] 0.62 [95% CI 0.43–0.89], P = 0.009) and severe nephropathy (0.56 [0.32–0.96], P = 0.033). Variation at the two other markers, rs1800764 and rs9896208, were also associated with these renal outcomes. In addition, homozygosity for the common haplotype TIC (which corresponded to the T, insertion, and C alleles at the three markers, rs1800764, insertion/deletion, and rs9896208, respectively) versus the CDT/TIC haplotype pair was associated with lower risk for development of persistent microalbuminuria (HR 0.49 [0.32–0.75], P = 0.0009) and severe nephropathy (0.41 [0.22–0.78], P = 0.006). Our findings in the DCCT/EDIC cohort provide strong evidence that genetic variation at the ACE gene is associated with the development of nephropathy in patients with type 1 diabetes.
PMCID: PMC1621110  PMID: 15793268
Genome-wide Association Studies (GWAS) revealed novel genetic markers for breast cancer susceptibility. But little is known about the risk factors and molecular events associated with breast cancer in Arab Population. Therefore, we designed a broad study to investigate the susceptibility and prognostic implications of the GWAS breast cancer loci in the Tunisian population. In a cohort of 640 unrelated patients with breast cancer and 371 healthy control subjects, we characterized the variation of 9 single nucleotide polymorphisms (SNPs), namely rs1219648, rs2981582; rs8051542, rs12443621, and rs3803662; rs889312; rs3817198; rs13387042 and rs13281615. Only 5 out of 9 GWAS breast cancer loci were found to be significantly associated with breast cancer in Tunisians: The rs1219648 (G vs. A allele: OR = 1.36, P = 1 × 10−3) and rs2981582 (A vs. G allele: OR = 1.55, P = 3 × 10−6) of FGFR2 gene; the rs8051542 of the TNRC9 gene (T vs. C allele: OR = 1.40, P = 4 × 10−4); the rs889312 of the MAP3K1 gene (C vs. A allele: OR = 1.33, P = 3 × 10−3) and the rs13281615 located on 8q24 (G vs. A allele: OR = 1.21, P = 0.03). Homozygous variant genotypes of rs2981582 were strongly related to lymph node negative breast cancer (OR = 3.33, P = 6 × 10−7) and the minor allele of rs2981582 was associated with increased risk of ER+ tumors (OR = 1.57, P = 0.02; OR = 2.15, P = 0.001, for heterozygous and homozygous variant genotypes, respectively) and increased risk of distant metastasis development (OR = 2.30, P = 4 × 10−3; OR = 3.57, P = 6 × 10−5, for heterozygous and homozygous variant genotypes, respectively) in a dose dependent manner. The association for rs8051542 was stronger for high-grade SBR tumors (OR = 2.54, P = 2 × 10−4). GG genotype of rs13387042 on 2q35 showed a significant association with the risk of developing distant metastasis (OR = 1.94, P = 0.02). The G allele of rs1219648 in FGFR2 and the A allele of rs13387042 on 2q35 indicated a better prognosis by showing a significantly higher overall survival rates (P = 0.013 and P = 0.005, respectively). In conclusion, GWAS breast cancer FGFR2, TNRC9, MAP3K1, and 8q24 loci are associated with an increased risk of breast cancer and genetic variation in FGFR2 gene may predict the aggressiveness of breast cancer in Tunisians.
Electronic supplementary material
The online version of this article (doi:10.1007/s10549-012-2202-6) contains supplementary material, which is available to authorized users.
PMCID: PMC3439608  PMID: 22910930
Breast cancer; Tunisians; Arabs; GWAS; Prognosis; Survival
BMC Medical Genetics  2008;9:59.
Recent genome-wide association (GWA) studies have identified several unsuspected genes associated with type 2 diabetes (T2D) with previously unknown functions. In this investigation, we have examined the role of 9 most significant SNPs reported in GWA studies: [peroxisome proliferator-activated receptor gamma 2 (PPARG2; rs 1801282); insulin-like growth factor two binding protein 2 (IGF2BP2; rs 4402960); cyclin-dependent kinase 5, a regulatory subunit-associated protein1-like 1 (CDK5; rs7754840); a zinc transporter and member of solute carrier family 30 (SLC30A8; rs13266634); a variant found near cyclin-dependent kinase inhibitor 2A (CDKN2A; rs10811661); hematopoietically expressed homeobox (HHEX; rs 1111875); transcription factor-7-like 2 (TCF7L2; rs 10885409); potassium inwardly rectifying channel subfamily J member 11(KCNJ11; rs 5219); and fat mass obesity-associated gene (FTO; rs 9939609)].
We genotyped these SNPs in a case-control sample of 918 individuals consisting of 532 T2D cases and 386 normal glucose tolerant (NGT) subjects of an Asian Sikh community from North India. We tested the association between T2D and each SNP using unconditional logistic regression before and after adjusting for age, gender, and other covariates. We also examined the impact of these variants on body mass index (BMI), waist to hip ratio (WHR), fasting insulin, and glucose and lipid levels using multiple linear regression analysis.
Four of the nine SNPs revealed a significant association with T2D; PPARG2 (Pro12Ala) [odds ratio (OR) 0.12; 95% confidence interval (CI) (0.03–0.52); p = 0.005], IGF2BP2 [OR 1.37; 95% CI (1.04–1.82); p = 0.027], TCF7L2 [OR 1.64; 95% CI (1.20–2.24); p = 0.001] and FTO [OR 1.46; 95% CI (1.11–1.93); p = 0.007] after adjusting for age, sex and BMI. Multiple linear regression analysis revealed significant association of two of nine investigated loci with diabetes-related quantitative traits. The 'C' (risk) allele of CDK5 (rs 7754840) was significantly associated with decreased HDL-cholesterol levels in both NGT (p = 0.005) and combined (NGT and T2D) (0.005) groups. The less common 'C' (risk) allele of TCF7L2 (rs 10885409) was associated with increased LDL-cholesterol (p = 0.010) in NGT and total and LDL-cholesterol levels (p = 0.008; p = 0.003, respectively) in combined cohort.
To our knowledge, this is first study reporting the role of some recently emerged loci with T2D in a high risk population of Asian Indian origin. Further investigations are warranted to understand the pathway-based functional implications of these important loci in T2D pathophysiology in different ethnicities.
PMCID: PMC2481250  PMID: 18598350
Diabetes  1999;48(2):383-390.
The Epidemiology of Diabetes Interventions and Complications (EDIC) is a multicenter longitudinal observational study of the Diabetes Control and Complications Trial (DCCT) cohort. One of the major objectives of EDIC is to study the development and progression of atherosclerotic cardiovascular disease in type 1 diabetes. In this study, we evaluated the role of cardiovascular risk factors and antecedent therapy in the DCCT on carotid intima-media wall thickness (IMT) in type 1 diabetes. At ~18 months after the end of the DCCT, high-resolution B-mode ultrasonography was used to assess the carotid arteries of 1,325 patients with type 1 diabetes, 19–51 years of age, with duration of diabetes ranging from 6.3 to 26.1 years. An age- and sex-matched nondiabetic population (n = 153) was studied with the same protocol. The ultrasound protocol was carried out in 28 EDIC clinics by centrally trained and certified sonographers using one of three scanning systems. Determination of IMT from videotaped images was performed by a single reader at the Central Ultrasound Reading Unit. Univariate associations with greater IMT were strongest for older age and longer diabetes duration, greater waist-to-hip ratio (men only), higher blood pressure, higher LDL cholesterol, and smoking. The DCCT therapy group (intensive versus conventional) and HbA1c, measured at the time of the ultrasound or the mean HbA1c during the DCCT, were not significantly related to IMT. Multivariate analyses suggest that age, height, smoking, and BMI were the major predictors of common carotid IMT, whereas age, smoking, and LDL cholesterol predicted internal carotid IMT. There were significant differences between the IMT values of the internal carotid artery in the EDIC male cohort and similarly aged male nondiabetic control subjects. There were no significant differences between the IMT values in the EDIC female cohort and similarly aged female nondiabetic control subjects. At this point in the planned 10-year follow-up of the DCCT cohort, neither intensive therapy nor HbA1c level appears to influence the early signs of atherosclerosis. Traditional risk factors, including age, smoking, and LDL cholesterol, were related to IMT. As the cohort is only now entering the age interval during which rapid progression and clinical expression of atherosclerosis are expected, further follow-up will help to determine the role of hyperglycemia, and its interaction with other risk factors, on the development of atherosclerosis.
PMCID: PMC2622732  PMID: 10334318
BMC Medical Genetics  2011;12:20.
Chronic hyperglycemia confers increased risk for long-term diabetes-associated complications and repeated hemoglobin A1c (HbA1c) measures are a widely used marker for glycemic control in diabetes treatment and follow-up. A recent genome-wide association study revealed four genetic loci, which were associated with HbA1c levels in adults with type 1 diabetes. We aimed to evaluate the effect of these loci on glycemic control in type 2 diabetes.
We genotyped 1,486 subjects with type 2 diabetes from a Norwegian population-based cohort (HUNT2) for single-nucleotide polymorphisms (SNPs) located near the BNC2, SORCS1, GSC and WDR72 loci. Through regression models, we examined their effects on HbA1c and non-fasting glucose levels individually and in a combined genetic score model.
No significant associations with HbA1c or glucose levels were found for the SORCS1, BNC2, GSC or WDR72 variants (all P-values > 0.05). Although the observed effects were non-significant and of much smaller magnitude than previously reported in type 1 diabetes, the SORCS1 risk variant showed a direction consistent with increased HbA1c and glucose levels, with an observed effect of 0.11% (P = 0.13) and 0.13 mmol/l (P = 0.43) increase per risk allele for HbA1c and glucose, respectively. In contrast, the WDR72 risk variant showed a borderline association with reduced HbA1c levels (β = -0.21, P = 0.06), and direction consistent with decreased glucose levels (β = -0.29, P = 0.29). The allele count model gave no evidence for a relationship between increasing number of risk alleles and increasing HbA1c levels (β = 0.04, P = 0.38).
The four recently reported SNPs affecting glycemic control in type 1 diabetes had no apparent effect on HbA1c in type 2 diabetes individually or by using a combined genetic score model. However, for the SORCS1 SNP, our findings do not rule out a possible relationship with HbA1c levels. Hence, further studies in other populations are needed to elucidate whether these novel sequence variants, especially rs1358030 near the SORCS1 locus, affect glycemic control in type 2 diabetes.
PMCID: PMC3044669  PMID: 21294870
Obesity (Silver Spring, Md.)  2011;20(3):622-627.
Recent genome-wide association studies (GWAS) have identified multiple novel loci associated with obesity in Europeans but results in other ethnicities are less convincing. Here, we report a two-stage GWAS of BMI in African Americans. The GWAS was performed using the Affymetrix 6.0 platform in 816 nondiabetic and 899 diabetic nephropathy subjects. 746,626 single-nucleotide polymorphisms (SNPs) were tested for association with BMI after adjustment for age, gender, disease status, and population structure. Sixty high scoring SNPs that showed nominal association in both GWAS cohorts were further replicated in 3,274 additional subjects in four replication cohorts and a meta-analysis was computed. Meta-analysis of 4,989 subjects revealed five SNPs (rs6794092, rs268972, rs2033195, rs815611, and rs6088887) at four loci showing consistent associations in both GWAS (P < 0.0001) and replication cohorts (P < 0.05) with combined P values range from 2.4 × 10−6 to 5 × 10−5. These loci are located near PP13439-TMEM212, CDH12, MFAP3-GALNT10, and FER1L4 and had effect sizes between 0.091 and 0.167 s.d. unit (or 0.67–1.24 kg/m2) of BMI for each copy of the effect allele. Our findings suggest the presence of novel loci potentially associated with adiposity in African Americans. Further replication and meta-analysis in African Americans and other populations will shed light on the role of these loci in different ethnic populations.
PMCID: PMC3291470  PMID: 21701570
PLoS Genetics  2009;5(10):e1000678.
Genome-wide association studies (GWAS) have been fruitful in identifying disease susceptibility loci for common and complex diseases. A remaining question is whether we can quantify individual disease risk based on genotype data, in order to facilitate personalized prevention and treatment for complex diseases. Previous studies have typically failed to achieve satisfactory performance, primarily due to the use of only a limited number of confirmed susceptibility loci. Here we propose that sophisticated machine-learning approaches with a large ensemble of markers may improve the performance of disease risk assessment. We applied a Support Vector Machine (SVM) algorithm on a GWAS dataset generated on the Affymetrix genotyping platform for type 1 diabetes (T1D) and optimized a risk assessment model with hundreds of markers. We subsequently tested this model on an independent Illumina-genotyped dataset with imputed genotypes (1,008 cases and 1,000 controls), as well as a separate Affymetrix-genotyped dataset (1,529 cases and 1,458 controls), resulting in area under ROC curve (AUC) of ∼0.84 in both datasets. In contrast, poor performance was achieved when limited to dozens of known susceptibility loci in the SVM model or logistic regression model. Our study suggests that improved disease risk assessment can be achieved by using algorithms that take into account interactions between a large ensemble of markers. We are optimistic that genotype-based disease risk assessment may be feasible for diseases where a notable proportion of the risk has already been captured by SNP arrays.
Author Summary
An often touted utility of genome-wide association studies (GWAS) is that the resulting discoveries can facilitate implementation of personalized medicine, in which preventive and therapeutic interventions for complex diseases can be tailored to individual genetic profiles. However, recent studies using whole-genome SNP genotype data for disease risk assessment have generally failed to achieve satisfactory results, leading to a pessimistic view of the utility of genotype data for such purposes. Here we propose that sophisticated machine-learning approaches on a large ensemble of markers, which contain both confirmed and as yet unconfirmed disease susceptibility variants, may improve the performance of disease risk assessment. We tested an algorithm called Support Vector Machine (SVM) on three large-scale datasets for type 1 diabetes and demonstrated that risk assessment can be highly accurate for the disease. Our results suggest that individualized disease risk assessment using whole-genome data may be more successful for some diseases (such as T1D) than other diseases. However, the predictive accuracy will be dependent on the heritability of the disease under study, the proportion of the genetic risk that is known, and that the right set of markers and right algorithms are being used.
PMCID: PMC2748686  PMID: 19816555
Lancet  2011;378(9795):1006-1014.
We aimed to identify novel genetic variants affecting asthma risk, since these might provide novel insights into molecular mechanisms underlying asthma.
We performed a genome-wide association study (GWAS) in 2,669 physician-diagnosed asthmatics and 4,528 controls from Australia. Seven loci were prioritised for replication after combining our results with those from the GABRIEL consortium (n=26,475), and these were tested in an additional 25,358 independent samples from four in-silico cohorts. Quantitative multi-SNP scores of genetic load were constructed on the basis of results from the GABRIEL study and tested for association with asthma in our Australian GWAS dataset.
Two loci were confirmed to associate with asthma risk in the replication cohorts and reached genome-wide significance in the combined analysis of all available studies (n=57,800): rs4129267 (OR=1.09, combined P=2.4×10−8) in the interleukin-6 receptor gene (IL6R) and rs7130588 (OR=1.09, P=1.8×10−8) on chromosome 11q13.5 near the leucine-rich repeat containing 32 gene (LRRC32, also known as GARP). The 11q13.5 locus was significantly associated with atopic status among asthmatics (OR = 1.33, P = 7×10−4), suggesting that it is a risk factor for allergic but not non-allergic asthma. Multi-SNP association results are consistent with a highly polygenic contribution to asthma risk, including loci with weak effects that may be shared with other immune-related diseases, such as NDFIP1, HLA-B, LPP and BACH2.
The IL6R association further supports the hypothesis that cytokine signalling dysregulation affects asthma risk, and raises the possibility that an IL6R antagonist (tocilizumab) may be effective to treat the disease, perhaps in a genotype-dependent manner. Results for the 11q13.5 locus suggest that it directly increases the risk of allergic sensitisation which, in turn, increases the risk of subsequent development of asthma. Larger or more functionally focused studies are needed to characterise the many loci with modest effects that remain to be identified for asthma.
A full list of funding sources appears at the end of the paper.
PMCID: PMC3517659  PMID: 21907864
PLoS Genetics  2010;6(9):e1001127.
Although more than 20 genetic susceptibility loci have been reported for type 2 diabetes (T2D), most reported variants have small to moderate effects and account for only a small proportion of the heritability of T2D, suggesting that the majority of inter-person genetic variation in this disease remains to be determined. We conducted a multistage, genome-wide association study (GWAS) within the Asian Consortium of Diabetes to search for T2D susceptibility markers. From 590,887 SNPs genotyped in 1,019 T2D cases and 1,710 controls selected from Chinese women in Shanghai, we selected the top 2,100 SNPs that were not in linkage disequilibrium (r2<0.2) with known T2D loci for in silico replication in three T2D GWAS conducted among European Americans, Koreans, and Singapore Chinese. The 5 most promising SNPs were genotyped in an independent set of 1,645 cases and 1,649 controls from Shanghai, and 4 of them were further genotyped in 1,487 cases and 3,316 controls from 2 additional Chinese studies. Consistent associations across all studies were found for rs1359790 (13q31.1), rs10906115 (10p13), and rs1436955 (15q22.2) with P-values (per allele OR, 95%CI) of 6.49×10−9 (1.15, 1.10–1.20), 1.45×10−8 (1.13, 1.08–1.18), and 7.14×10−7 (1.13, 1.08–1.19), respectively, in combined analyses of 9,794 cases and 14,615 controls. Our study provides strong evidence for a novel T2D susceptibility locus at 13q31.1 and the presence of new independent risk variants near regions (10p13 and 15q22.2) reported by previous GWAS.
Author Summary
Type 2 diabetes, a complex disease affecting more than a billion people worldwide, is believed to be caused by both environmental and genetic factors. Although some studies have shown that certain genes may make some people more susceptible to type 2 diabetes than others, the genes reported to date have only a small effect and account for a small proportion of type 2 diabetes cases. Furthermore, few of these studies have been conducted in Asian populations, although Asians are known to be more susceptible to insulin resistance than people living in Western countries, and incidence of type 2 diabetes has been increasing alarmingly in Asian countries. We conducted a multi-stage study involving 9,794 type 2 diabetes cases and 14,615 controls, predominantly Asians, to discover genes related to susceptibility to type 2 diabetes. We identified 3 genetic regions that are related to increased risk of type 2 diabetes.
PMCID: PMC2940731  PMID: 20862305
BMC Medical Genomics  2008;1:44.
Late-onset Alzheimer's disease (LOAD) is an age related neurodegenerative disease with a high prevalence that places major demands on healthcare resources in societies with increasingly aged populations. The only extensively replicable genetic risk factor for LOAD is the apolipoprotein E gene. In order to identify additional genetic risk loci we have conducted a genome-wide association (GWA) study in a large LOAD case – control sample, reducing costs through the use of DNA pooling.
DNA samples were collected from 1,082 individuals with LOAD and 1,239 control subjects. Age at onset ranged from 60 to 95 and Controls were matched for age (mean = 76.53 years, SD = 33), gender and ethnicity. Equimolar amounts of each DNA sample were added to either a case or control pool. The pools were genotyped using Illumina HumanHap300 and Illumina Sentrix HumanHap240S arrays testing 561,494 SNPs. 114 of our best hit SNPs from the pooling data were identified and then individually genotyped in the case – control sample used to construct the pools.
Highly significant association with LOAD was observed at the APOE locus confirming the validity of the pooled genotyping approach.
For 109 SNPs outside the APOE locus, we obtained uncorrected p-values ≤ 0.05 for 74 after individual genotyping. To further test these associations, we added control data from 1400 subjects from the 1958 Birth Cohort with the evidence for association increasing to 3.4 × 10-6 for our strongest finding, rs727153.
rs727153 lies 13 kb from the start of transcription of lecithin retinol acyltransferase (phosphatidylcholine – retinol O-acyltransferase, LRAT). Five of seven tag SNPs chosen to cover LRAT showed significant association with LOAD with a SNP in intron 2 of LRAT, showing greatest evidence of association (rs201825, p-value = 6.1 × 10-7).
We have validated the pooling method for GWA studies by both identifying the APOE locus and by observing a strong enrichment for significantly associated SNPs. We provide evidence for LRAT as a novel candidate gene for LOAD. LRAT plays a prominent role in the Vitamin A cascade, a system that has been previously implicated in LOAD.
PMCID: PMC2570675  PMID: 18823527
PLoS ONE  2011;6(10):e26911.
Several novel susceptibility loci for type 2 diabetes have been identified through genome-wide association studies (GWAS) for type 2 diabetes or quantitative traits related to glucose metabolism in European populations. To investigate the association of the 13 new European GWAS-derived susceptibility loci with type 2 diabetes in the Japanese population, we conducted a replication study using 3 independent Japanese case-control studies.
Methodology/Principal Findings
We examined the association of single nucleotide polymorphisms (SNPs) within 13 loci (MTNR1B, GCK, IRS1, PROX1, BCL11A, ZBED3, KLF14, TP53INP1, KCNQ1, CENTD2, HMGA2, ZFAND6 and PRC1) with type 2 diabetes using 4,964 participants (2,839 cases and 2,125 controls) from 3 independent Japanese samples. The association of each SNP with type 2 diabetes was analyzed by logistic regression analysis. Further, we performed combined meta-analyses for the 3 studies and previously performed Japanese GWAS data (4,470 cases vs. 3,071 controls). The meta-analysis revealed that rs2943641 in the IRS1 locus was significantly associated with type 2 diabetes, (P = 0.0034, OR = 1.15 95% confidence interval; 1.05–1.26) and 3 SNPs, rs10930963 in the MTNR1B locus, rs972283 in the KLF14 locus, and rs231362 in the KCNQ1 locus, had nominal association with type 2 diabetes in the present Japanese samples (P<0.05).
These results indicate that IRS1 locus may be common locus for type 2 diabetes across different ethnicities.
PMCID: PMC3202571  PMID: 22046406
PLoS Genetics  2014;10(5):e1004367.
Genome-wide association studies (GWAS) for type 1 diabetes (T1D) have successfully identified more than 40 independent T1D associated tagging single nucleotide polymorphisms (SNPs). However, owing to technical limitations of copy number variants (CNVs) genotyping assays, the assessment of the role of CNVs has been limited to the subset of these in high linkage disequilibrium with tag SNPs. The contribution of untagged CNVs, often multi-allelic and difficult to genotype using existing assays, to the heritability of T1D remains an open question. To investigate this issue, we designed a custom comparative genetic hybridization array (aCGH) specifically designed to assay untagged CNV loci identified from a variety of sources. To overcome the technical limitations of the case control design for this class of CNVs, we genotyped the Type 1 Diabetes Genetics Consortium (T1DGC) family resource (representing 3,903 transmissions from parents to affected offspring) and used an association testing strategy that does not necessitate obtaining discrete genotypes. Our design targeted 4,309 CNVs, of which 3,410 passed stringent quality control filters. As a positive control, the scan confirmed the known T1D association at the INS locus by direct typing of the 5′ variable number of tandem repeat (VNTR) locus. Our results clarify the fact that the disease association is indistinguishable from the two main polymorphic allele classes of the INS VNTR, class I-and class III. We also identified novel technical artifacts resulting into spurious associations at the somatically rearranging loci, T cell receptor, TCRA/TCRD and TCRB, and Immunoglobulin heavy chain, IGH, loci on chromosomes 14q11.2, 7q34 and 14q32.33, respectively. However, our data did not identify novel T1D loci. Our results do not support a major role of untagged CNVs in T1D heritability.
Author Summary
For many complex traits, and in particular type 1 diabetes (T1D), the genome-wide association study (GWAS) design has been successful at detecting a large number of loci that contribute disease risk. However, in the case of T1D as well as almost all other traits, the sum of these loci does not fully explain the heritability estimated from familial studies. This observation raises the possibility that additional variants exist but have not yet been found because they have not effectively been targeted by the GWAS design. Here, we focus on a specific class of large deletions/duplications called copy number variants (CNVs), and more precisely to the subset of these loci that mutate rapidly, which are highly polymorphic. A consequence of this high level of polymorphism is that these variants have typically not been captured by previous GWAS studies. We use a family based design that is optimized to capture these previously untested variants. We then perform a genome-wide scan to assess their contribution to T1D. Our scan was technically successful but did not identify novel associations. This suggests that little was missed by the GWAS strategy, and that the remaining heritability of T1D is most likely driven by a large number of variants, either rare of common, but with a small individual contribution to disease risk.
PMCID: PMC4038470  PMID: 24875393
Genetic epidemiology  2010;34(2):107-118.
A central issue in genome-wide association (GWA) studies is assessing statistical significance while adjusting for multiple hypothesis testing. An equally important question is the statistical efficiency of the GWA design as compared to the traditional sequential approach in which genome-wide linkage analysis is followed by region-wise association mapping. Nevertheless, GWA is becoming more popular due in part to cost efficiency: commercially available 1M chips are nearly as inexpensive as a custom-designed 10K chip. It is becoming apparent, however, that most of the on-going GWA studies with 2,000~5,000 samples are in fact underpowered. As a means to improve power, we emphasize the importance of utilizing prior information such as results of previous linkage studies via a stratified false discovery rate (FDR) control. The essence of the stratified FDR control is to prioritize the genome and maintain power to interrogate candidate regions within the GWA study. These candidate regions can be defined as, but are by no means limited to, linkage-peak regions. Furthermore, we theoretically unify the stratified FDR approach and the weighted p-value method, and we show that stratified FDR can be formulated as a robust version of weighted FDR. Finally, we demonstrate the utility of the methods in two GWA datasets: Type 2 Diabetes (FUSION) and an on-going study of long-term diabetic complications (DCCT/EDIC). The methods are implemented as a user-friendly software package, SFDR. The same stratification framework can be readily applied to other type of studies, for example, using GWA results to improve the power of sequencing data analyses.
PMCID: PMC2811772  PMID: 19626703
genome-wide association; genome-wide linkage; statistical power; prior information; false discovery rate
The purpose of this study is to attempt to replicate the top single nucleotide polymorphism (SNP) associations from a previous genome-wide association study (GWAS) for the sight-threatening complications of diabetic retinopathy in an independent cohort of diabetic subjects from the Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR).
This study included 469 type 1 diabetic, Caucasian subjects from WESDR. Cases (n = 208) were defined by prior laser treatment for either proliferative diabetic retinopathy or diabetic macular edema. Controls (n = 261) were all other subjects in the cohort. Three hundred eighty-nine SNPs were tested for association using the Illumina GoldenGate custom array. A retinopathy-only subanalysis was conducted in 437 subjects by removing those with end-stage renal disease. Evaluation for association between cases and controls was conducted by using chi-square tests. A combined analysis incorporated the results from WESDR with the prior GWAS.
No associations were significant at a genome-wide level. The analysis did identify SNPs that can be pursued in future replication studies. The top association was at rs4865047, an intronic SNP, in the gene CEP135 (P value 2.06 × 10−5). The top association from the subanalysis was at rs1902491 (P value 2.81 × 10−5), a SNP that sits upstream of the gene NPY2R.
This study nominates several novel genetic loci that may be associated with severe diabetic retinopathy. In order to confirm these findings, replication and extension in additional cohorts will be necessary as susceptibility alleles for diabetic retinopathy appear to be of modest effect.
In an attempt to replicate the top single nucleotide polymorphism associations from a previous genome-wide association, this study nominates genetic loci that may be associated with severe diabetic retinopathy.
PMCID: PMC3777289  PMID: 22427569

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