[Show abstract][Hide abstract] ABSTRACT: Recent genetic association studies have identified 55 genetic loci associated with obesity or body mass index (BMI). The vast
majority, 51 loci, however, were identified in European-ancestry populations. We conducted a meta-analysis of associations
between BMI and ∼2.5 million genotyped or imputed single nucleotide polymorphisms among 86 757 individuals of Asian ancestry,
followed by in silico and de novo replication among 7488–47 352 additional Asian-ancestry individuals. We identified four novel BMI-associated loci near the
KCNQ1 (rs2237892, P = 9.29 × 10−13), ALDH2/MYL2 (rs671, P = 3.40 × 10−11; rs12229654, P = 4.56 × 10−9), ITIH4 (rs2535633, P = 1.77 × 10−10) and NT5C2 (rs11191580, P = 3.83 × 10−8) genes. The association of BMI with rs2237892, rs671 and rs12229654 was significantly stronger among men than among women.
Of the 51 BMI-associated loci initially identified in European-ancestry populations, we confirmed eight loci at the genome-wide
significance level (P < 5.0 × 10−8) and an additional 14 at P < 1.0 × 10−3 with the same direction of effect as reported previously. Findings from this analysis expand our knowledge of the genetic
basis of obesity.
Human Molecular Genetics 05/2014; 23(20). DOI:10.1093/hmg/ddu248 · 6.39 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Candidate gene and genome-wide association studies have identified ∼60 susceptibility loci for type 2 diabetes. A majority of these loci have been discovered and tested only in European populations. The aim of this study was to assess the presence and extent of trans-ethnic effects of these loci in an East Asian population.
A total of 9,335 unrelated Chinese Han individuals, including 4,535 with type 2 diabetes and 4,800 non-diabetic ethnically matched controls, were genotyped using the Illumina 200K Metabochip. We tested 50 established loci for type 2 diabetes and related traits (fasting glucose, fasting insulin, 2 h glucose). Disease association with the additive model of inheritance was analysed with logistic regression.
We found that 14 loci significantly transferred to the Chinese population, with two loci (p = 5.7 × 10(-12) for KCNQ1; p = 5.0 × 10(-8) for CDKN2A/B-CDKN2BAS) reaching independent genome-wide statistical significance. Five of these 14 loci had similar lead single-nucleotide polymorphisms (SNPs) as were found in the European studies while the other nine were different. Further stepwise conditional analysis identified a total of seven secondary signals and an independent novel locus at the 3' end of CDKAL1.
These results suggest that many loci associated with type 2 diabetes are commonly shared between European and Chinese populations. Identification of population-specific SNPs may increase our understanding of the genetic architecture underlying type 2 diabetes in different ethnic populations.
[Show abstract][Hide abstract] ABSTRACT: Background:
The ability to identify patients with Crohn's disease (CD) at highest risk of surgery would be invaluable in guiding therapy. Genome-wide association studies have identified multiple IBD loci with unknown phenotypic consequences. The aims of this study were to: (1) identify associations between known and novel CD loci with early resective CD surgery and (2) develop the best predictive model for time to surgery using a combination of phenotypic, serologic, and genetic variables.
Genotyping was performed on 1,115 subjects using Illumina-based genome-wide technology. Univariate and multivariate analyses tested genetic associations with need for surgery within 5 years. Analyses were performed by testing known CD loci (n = 71) and by performing a genome-wide association study. Time to surgery was analyzed using Cox regression modeling. Clinical and serologic variables were included along with genotype to build predictive models for time to surgery.
Surgery occurred within 5 years in 239 subjects at a median time of 12 months. Three CD susceptibility loci were independently associated with surgery within 5 years (IL12B, IL23R, and C11orf30). Genome-wide association identified novel putative loci associated with early surgery: 7q21 (CACNA2D1) and 9q34 (RXRA, COL5A1). The most predictive models of time to surgery included genetic and clinical risk factors. More than a 20% difference in frequency of progression to surgery was seen between the lowest and highest risk groups.
Progression to surgery is faster in patients with CD with both genetic and clinical risk factors. IL12B is independently associated with need and time to early surgery in CD patients and justifies the investigation of novel and existing therapies that affect this pathway.
[Show abstract][Hide abstract] ABSTRACT: We developed a multinomial ordinal probit model with singular value decomposition for testing a large number of single nucleotide polymorphisms SNPs simultaneously for association with multidisease status when sample size is much smaller than the number of SNPs. The validity and performance of the method was evaluated via simulation. We applied the method to our real study sample recruited through the Mexican-American Coronary Artery Disease study. We found 3 genes SORCS1, AMPD1, and PPARα to be associated with the development of both IGT and IFG, while 5 genes AMPD2, PRKAA2, C5, TCF7L2, and ITR with the IGT mechanism only and 6 genes CAPN10, IL4, NOS3, CD14, GCG, and SORT1 with the IFG mechanism only. These data suggest that IGT and IFG may indicate different physiological mechanism to prediabetes, via different genetic determinants.
Journal of Probability and Statistics 09/2012; 2012. DOI:10.1155/2012/419832
[Show abstract][Hide abstract] ABSTRACT: Genetic association studies usually involve a large number of single-nucleotide polymorphisms (SNPs) (k) and a relative small sample size (n), which produces the situation that k is much greater than n. Because conventional statistical approaches are unable to deal with multiple SNPs simultaneously when k is much greater than n, single-SNP association studies have been used to identify genes involved in a disease's pathophysiology, which causes a multiple testing problem. To evaluate the contribution of multiple SNPs simultaneously to disease traits when k is much greater than n, we developed the Bayesian regression with singular value decomposition (BRSVD) method. The method reduces the dimension of the design matrix from k to n by applying singular value decomposition to the design matrix. We evaluated the model using a Markov chain Monte Carlo simulation with Gibbs sampler constructed from the posterior densities driven by conjugate prior densities. Permutation was incorporated to generate empirical p-values. We applied the BRSVD method to the sequence data provided by Genetic Analysis Workshop 17 and found that the BRSVD method is a practical method that can be used to analyze sequence data in comparison to the single-SNP association test and the penalized regression method.
[Show abstract][Hide abstract] ABSTRACT: The pathogenesis of polycystic ovary syndrome (PCOS) is poorly understood. PCOS-like phenotypes are produced by prenatal androgenization (PA) of female rhesus monkeys. We hypothesize that perturbation of the epigenome, through altered DNA methylation, is one of the mechanisms whereby PA reprograms monkeys to develop PCOS. Infant and adult visceral adipose tissues (VAT) harvested from 15 PA and 10 control monkeys were studied. Bisulfite treated samples were subjected to genome-wide CpG methylation analysis, designed to simultaneously measure methylation levels at 27,578 CpG sites. Analysis was carried out using Bayesian Classification with Singular Value Decomposition (BCSVD), testing all probes simultaneously in a single test. Stringent criteria were then applied to filter out invalid probes due to sequence dissimilarities between human probes and monkey DNA, and then mapped to the rhesus genome. This yielded differentially methylated loci between PA and control monkeys, 163 in infant VAT, and 325 in adult VAT (BCSVD P<0.05). Among these two sets of genes, we identified several significant pathways, including the antiproliferative role of TOB in T cell signaling and transforming growth factor-β (TGF-β) signaling. Our results suggest PA may modify DNA methylation patterns in both infant and adult VAT. This pilot study suggests that excess fetal androgen exposure in female nonhuman primates may predispose to PCOS via alteration of the epigenome, providing a novel avenue to understand PCOS in humans.
PLoS ONE 11/2011; 6(11):e27286. DOI:10.1371/journal.pone.0027286 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: To evaluate association with polycystic ovary syndrome (PCOS) of 295 variants in 39 genes central to metabolic insulin signaling and glycogen synthase kinase 3β (GSK-3β) regulation, followed by replication efforts.
Case-control association study, with discovery and replication cohorts.
Subjects were recruited from reproductive endocrinology clinics, and controls were recruited from communities surrounding the University of Alabama at Birmingham and Erasmus Medical Center, Rotterdam.
A total of 273 cases with PCOS and 173 control subjects in the discovery cohort; and 526 cases and 3,585 control subjects in the replication cohort. All subjects were caucasian.
Phenotypic and genotypic assessment.
Detection of 295 single-nucleotide polymorphisms (SNPs), PCOS status.
Several SNPs were associated with PCOS in the discovery cohort. Four insulin receptor (INSR) SNPs and three insulin receptor substrate 2 (IRS2) SNPs associated with PCOS were genotyped in the replication cohort. One INSR SNP (rs2252673) replicated association with PCOS. The minor allele conferred increased odds of PCOS in both cohorts, independent of body mass index.
A pathway-based tagging SNP approach allowed us to identify novel INSR SNPs associated with PCOS, one of which confirmed association in a large replication cohort.
Fertility and sterility 02/2011; 95(5):1736-41.e1-11. DOI:10.1016/j.fertnstert.2011.01.015 · 4.59 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Little data are available from genome-wide association studies (GWASs) of liver histology in patients with nonalcoholic fatty liver disease (NAFLD). We conducted a pilot GWAS in patients with NAFLD, characterized by histology, who were enrolled in the NASH Clinical Research Network (CRN) Database Study.
We studied clinical, laboratory, and histologic data from 236 non-Hispanic white women with NAFLD. We analyzed 324,623 single nucleotide polymorphisms (SNPs) from the 22 autosomal chromosomes. Multivariate-adjusted logistic regression analyses were conducted for binary outcomes, and linear regression analysis was applied for quantitative traits. A P value < 1 × 10(-6) was considered to be significant.
In multivariate models adjusted for age, body mass index, diabetes, waist/hip ratios, and levels of glycated hemoglobin, the NAFLD activity score was associated with the SNP rs2645424 on chromosome 8 in farnesyl diphosphate farnesyl transferase 1 (FDFT1) (P = 6.8 × 10(-7)). The degree of fibrosis was associated with the SNP rs343062 on chromosome 7 (P = 2.7 × 10(-8)). SNPs associated with lobular inflammation included SNP rs1227756 on chromosome 10 in COL13A1 (P = 2.0 × 10(-7)), rs6591182 on chromosome 11 (P = 8.6 × 10(-7)), and rs887304 on chromosome 12 in EFCAB4B (P = 7.7 × 10(-7)). SNPs associated with serum levels of alanine aminotransferase included rs2499604 on chromosome 1 (P = 2.2 × 10(-6)), rs6487679 on chromosome 12 in PZP (P = 1.3 × 10(-6)), rs1421201 on chromosome 18 (P = 1.0 × 10(-5)), and rs2710833 on chromosome 4 (P = 6.3 × 10(-7)). No significant associations were observed between genotypes and steatosis, ballooning degeneration, portal inflammation, or other features of NAFLD.
A GWAS significantly associated genetic variants with features of hepatic histology in patients with NAFLD. These findings should be validated in larger and more diverse cohorts.
[Show abstract][Hide abstract] ABSTRACT: Acute severe ulcerative colitis (UC) remains a significant clinical challenge and the ability to predict, at an early stage, those individuals at risk of colectomy for medically refractory UC (MR-UC) would be a major clinical advance. The aim of this study was to use a genome-wide association study (GWAS) in a well-characterized cohort of UC patients to identify genetic variation that contributes to MR-UC.
A GWAS comparing 324 MR-UC patients with 537 non-MR-UC patients was analyzed using logistic regression and Cox proportional hazards methods. In addition, the MR-UC patients were compared with 2601 healthy controls.
MR-UC was associated with more extensive disease (P = 2.7 × 10(-6)) and a positive family history of UC (P = 0.004). A risk score based on the combination of 46 single nucleotide polymorphisms (SNPs) associated with MR-UC explained 48% of the variance for colectomy risk in our cohort. Risk scores divided into quarters showed the risk of colectomy to be 0%, 17%, 74%, and 100% in the four groups. Comparison of the MR-UC subjects with healthy controls confirmed the contribution of the major histocompatibility complex to severe UC (peak association: rs17207986, P = 1.4 × 10(-16)) and provided genome-wide suggestive association at the TNFSF15 (TL1A) locus (peak association: rs11554257, P = 1.4 × 10(-6)).
A SNP-based risk scoring system, identified here by GWAS analyses, may provide a useful adjunct to clinical parameters for predicting the natural history of UC. Furthermore, discovery of genetic processes underlying disease severity may help to identify pathways for novel therapeutic intervention in severe UC.
[Show abstract][Hide abstract] ABSTRACT: We developed a multinomial probit model with singular value decomposition for testing a large number of single nucleotide polymorphisms (SNPs) simultaneously, using maximum likelihood estimation and permutation. The method was validated by simulation. We simulated 1000 SNPs, including 9 associated with disease states, and 8 of the 9 were successfully identified. Applying the method to study 32 genes in our Mexican-American samples for association with prediabetes through either impaired glucose tolerance (IGT) or impaired fasting glucose (IFG), we found 3 genes (SORCS1, AMPD1, PPAR) associated with both IGT and IFG, while 5 genes (AMPD2, PRKAA2, C5, TCF7L2, ITR) with the IGT mechanism only and 6 genes (CAPN10, IL4,NOS3, CD14, GCG, SORT1) with the IFG mechanism only. These data suggest that IGT and IFG may indicate different physiological mechanism to prediabetes, via different genetic determinants.
[Show abstract][Hide abstract] ABSTRACT: ABSTRACT : To analyze multiple single-nucleotide polymorphisms simultaneously when the number of markers is much larger than the number of studied individuals, as is the situation we have in genome-wide association studies (GWAS), we developed the iterative Bayesian variable selection method and successfully applied it to the simulated rheumatoid arthritis data provided by the Genetic Analysis Workshop 15 (GAW15). One drawback for applying our iterative Bayesian variable selection method is the relatively long running time required for evaluation of GWAS data. To improve computing speed, we recently developed a Bayesian classification with singular value decomposition (BCSVD) method. We have applied the BCSVD method here to the rheumatoid arthritis data distributed by GAW16 Problem 1 and demonstrated that the BCSVD method works well for analyzing GWAS data.
[Show abstract][Hide abstract] ABSTRACT: Genome-wide association studies usually involve several hundred thousand of single-nucleotide polymorphisms (SNPs). Conventional approaches face challenges when there are enormous number of SNPs but a relatively small number of samples and, in some cases, are not feasible. We introduce here an iterative Bayesian variable selection method that provides a unique tool for association studies with a large number of SNPs (p) but a relatively small sample size (n). We applied this method to the simulated case-control sample provided by the Genetic Analysis Workshop 15 and compared its performance with stepwise variable selection method. We demonstrated that the results of iterative Bayesian variable selection applied to when p t n are as comparable as those of stepwise variable selection implemented to when n t p. When n > p, the iterative Bayesian variable selection performs better than stepwise variable selection does.