scholarly journals Discovering patterns of pleiotropy in genome-wide association studies

2018 ◽  
Author(s):  
Jianan Zhana ◽  
Jessica van Setten ◽  
Jennifer Brody ◽  
Brenton Swenson ◽  
Anne M. Butler ◽  
...  
Keyword(s):  
Gold Standard ◽  
Disease Risk ◽  
Association Studies ◽  
Meta Analysis ◽  
Linkage Disequilibrium Block ◽  
Genome Wide Association ◽  
Superior Performance ◽  
Great Success ◽  
Genome Wide Association Studies ◽  
Genome Wide

AbstractMotivationGenome-wide association studies have had great success in identifying human genetic variants associated with disease, disease risk factors, and other biomedical phenotypes. Many variants are associated with multiple traits, even after correction for trait-trait correlation. Discovering subsets of variants associated with a shared subset of phenotypes could help reveal disease mechanisms, suggest new therapeutic options, and increase the power to detect additional variants with similar pattern of associations. Here we introduce two methods based on a Bayesian framework, SNP And Pleiotropic PHenotype Organization (SAPPHO), one modeling independent phenotypes (SAPPHO-I) and the other incorporating a full phenotype covariance structure (SAPPHO-C). These two methods learn patterns of pleiotropy from genotype and phenotype data, using identified associations to discover additional associations with shared patterns.ResultsThe SAPPHO methods, along with other recent approaches for pleiotropic association tests, were assessed using data from the Atherosclerotic Risk in Communities (ARIC) study of 8,000 individuals, whose gold-standard associations were provided by meta-analysis of 40,000 to 100,000 individuals from the CHARGE consortium. Using power to detect gold-standard associations at genome-wide significance (0.05 family-wise error rate) as a metric, SAPPHO performed best. The SAPPHO methods were also uniquely able to select the most significant variants in a parsimonious model, excluding other less likely variants within a linkage disequilibrium block. For meta-analysis, the SAPPHO methods implement summary modes that use sufficient statistics rather than full phenotype and genotype data. Meta-analysis applied to CHARGE detected 16 additional associations to the gold-standard loci, as well as 124 novel loci, at 0.05 false discovery rate. Reasons for the superior performance were explored by performing simulations over a range of scenarios describing different genetic architectures. With SAPPHO we were able to learn genetic structures that were hidden using the traditional univariate tests.Availabilityhttps://bitbucket.org/baderlab/fast/wiki/Home. SAPPHO software is available under the GNU General Public License, v2.

scholarly journals A meta-analysis of genome-wide association studies of asthma in Puerto Ricans

2017 ◽  
Vol 49 (5) ◽  
pp. 1601505 ◽  
Author(s):  
Qi Yan ◽  
John Brehm ◽  
Maria Pino-Yanes ◽  
Erick Forno ◽  
Jerome Lin ◽  
...  
Keyword(s):  
Puerto Ricans ◽  
Association Studies ◽  
Meta Analysis ◽  
Linkage Disequilibrium Block ◽  
Genome Wide Association ◽  
Health Study ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
The Usa ◽  
Meta Analyses

Puerto Ricans are disproportionately affected with asthma in the USA. In this study, we aim to identify genetic variants that confer susceptibility to asthma in Puerto Ricans.We conducted a meta-analysis of genome-wide association studies (GWAS) of asthma in Puerto Ricans, including participants from: the Genetics of Asthma in Latino Americans (GALA) I-II, the Hartford–Puerto Rico Study and the Hispanic Community Health Study. Moreover, we examined whether susceptibility loci identified in previous meta-analyses of GWAS are associated with asthma in Puerto Ricans.The only locus to achieve genome-wide significance was chromosome 17q21, as evidenced by our top single nucleotide polymorphism (SNP), rs907092 (OR 0.71, p=1.2×10−12) at IKZF3. Similar to results in non-Puerto Ricans, SNPs in genes in the same linkage disequilibrium block as IKZF3 (e.g. ZPBP2, ORMDL3 and GSDMB) were significantly associated with asthma in Puerto Ricans. With regard to results from a meta-analysis in Europeans, we replicated findings for rs2305480 at GSDMB, but not for SNPs in any other genes. On the other hand, we replicated results from a meta-analysis of North American populations for SNPs at IL1RL1, TSLP and GSDMB but not for IL33.Our findings suggest that common variants on chromosome 17q21 have the greatest effects on asthma in Puerto Ricans.

scholarly journals Ethnic and trans-ethnic genome-wide association studies identify new loci influencing Japanese Alzheimer’s disease risk

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Daichi Shigemizu ◽  
Risa Mitsumori ◽  
Shintaro Akiyama ◽  
Akinori Miyashita ◽  
Takashi Morizono ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Japanese Population ◽  
Disease Risk ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
A Genome

AbstractAlzheimer’s disease (AD) has no cure, but early detection and risk prediction could allow earlier intervention. Genetic risk factors may differ between ethnic populations. To discover novel susceptibility loci of AD in the Japanese population, we conducted a genome-wide association study (GWAS) with 3962 AD cases and 4074 controls. Out of 4,852,957 genetic markers that passed stringent quality control filters, 134 in nine loci, including APOE and SORL1, were convincingly associated with AD. Lead SNPs located in seven novel loci were genotyped in an independent Japanese AD case–control cohort. The novel locus FAM47E reached genome-wide significance in a meta-analysis of association results. This is the first report associating the FAM47E locus with AD in the Japanese population. A trans-ethnic meta-analysis combining the results of the Japanese data sets with summary statistics from stage 1 data of the International Genomics of Alzheimer’s Project identified an additional novel susceptibility locus in OR2B2. Our data highlight the importance of performing GWAS in non-European populations.

scholarly journals A meta-analysis of genome-wide association studies identifies 17 new Parkinson's disease risk loci

2017 ◽  
Vol 49 (10) ◽  
pp. 1511-1516 ◽  
Author(s):  
Diana Chang ◽  
◽  
Mike A Nalls ◽  
Ingileif B Hallgrímsdóttir ◽  
Julie Hunkapiller ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Disease Risk ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals Summary statistics knockoff inference empowers identification of putative causal variants in genome-wide association studies

2021 ◽  
Author(s):  
Zihuai He ◽  
Linxi Liu ◽  
Michael E. Belloy ◽  
Yann Le Guen ◽  
Aaron Sossin ◽  
...  
Keyword(s):  
Genome Sequencing ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Superior Performance ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Genome Wide ◽  
Causal Variants ◽  
The Uk

AbstractRecent advances in genome sequencing and imputation technologies provide an exciting opportunity to comprehensively study the contribution of genetic variants to complex phenotypes. However, our ability to translate genetic discoveries into mechanistic insights remains limited at this point. In this paper, we propose an efficient knockoff-based method, GhostKnockoff, for genome-wide association studies (GWAS) that leads to improved power and ability to prioritize putative causal variants relative to conventional GWAS approaches. The method requires only Z-scores from conventional GWAS and hence can be easily applied to enhance existing and future studies. The method can also be applied to meta-analysis of multiple GWAS allowing for arbitrary sample overlap. We demonstrate its performance using empirical simulations and two applications: (1) analysis of 1,403 binary phenotypes from the UK Biobank data in 408,961 samples of European ancestry, and (2) a meta-analysis for Alzheimer’s disease (AD) comprising nine overlapping large-scale GWAS, whole-exome and whole-genome sequencing studies. The UK Biobank analysis demonstrates superior performance of the proposed method compared to conventional GWAS in both statistical power (2.05-fold more discoveries) and localization of putative causal variants at each locus (46% less proxy variants due to linkage disequilibrium). The AD meta-analysis identified 55 risk loci (including 31 new loci) with ~70% of the proximal genes at these loci showing suggestive signal in downstream single-cell transcriptomic analyses. Our results demonstrate that GhostKnockoff can identify putatively functional variants with weaker statistical effects that are missed by conventional association tests.

Genome-Wide Association Studies Identify Two Novel Loci Conferring Susceptibility to Diabetic Retinopathy in Japanese Patients with Type 2 Diabetes

2021 ◽  
Author(s):  
Minako Imamura ◽  
Atsushi Takahashi ◽  
Masatoshi Matsunami ◽  
Momoko Horikoshi ◽  
Minoru Iwata ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Diabetic Retinopathy ◽  
Association Studies ◽  
Meta Analysis ◽  
Japanese Patients ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Stage 1

Abstract Several reports have suggested that genetic susceptibility contributes to the development and progression of diabetic retinopathy. We aimed to identify genetic loci that confer susceptibility to diabetic retinopathy in Japanese patients with type 2 diabetes. We analysed 5 790 508 single nucleotide polymorphisms (SNPs) in 8880 Japanese patients with type 2 diabetes, 4839 retinopathy cases and 4041 controls, as well as 2217 independent Japanese patients with type 2 diabetes, 693 retinopathy cases, and 1524 controls. The results of these two genome-wide association studies (GWAS) were combined with an inverse variance meta-analysis (Stage-1), followed by de novo genotyping for the candidate SNP loci (p < 1.0 × 10−4) in an independent case–control study (Stage-2, 2260 cases and 723 controls). After combining the association data (Stage-1 and -2) using meta-analysis, the associations of two loci reached a genome-wide significance level: rs12630354 near STT3B on chromosome 3, p = 1.62 × 10−9, odds ratio (OR) = 1.17, 95% confidence interval (CI) 1.11–1.23, and rs140508424 within PALM2 on chromosome 9, p = 4.19 × 10−8, OR = 1.61, 95% CI 1.36–1.91. However, the association of these two loci were not replicated in Korean, European, or African American populations. Gene-based analysis using Stage-1 GWAS data identified a gene-level association of EHD3 with susceptibility to diabetic retinopathy (p = 2.17 × 10−6). In conclusion, we identified two novel SNP loci, STT3B and PALM2, and a novel gene, EHD3, that confers susceptibility to diabetic retinopathy; however, further replication studies are required to validate these associations.

scholarly journals A meta-analysis of genome-wide association studies for average daily gain and lean meat percentage in two Duroc pig populations

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Shenping Zhou ◽  
Rongrong Ding ◽  
Fanming Meng ◽  
Xingwang Wang ◽  
Zhanwei Zhuang ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Growth And Development ◽  
Genetic Architecture ◽  
Association Studies ◽  
Meta Analysis ◽  
Average Daily Gain ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Daily Gain

Abstract Background Average daily gain (ADG) and lean meat percentage (LMP) are the main production performance indicators of pigs. Nevertheless, the genetic architecture of ADG and LMP is still elusive. Here, we conducted genome-wide association studies (GWAS) and meta-analysis for ADG and LMP in 3770 American and 2090 Canadian Duroc pigs. Results In the American Duroc pigs, one novel pleiotropic quantitative trait locus (QTL) on Sus scrofa chromosome 1 (SSC1) was identified to be associated with ADG and LMP, which spans 2.53 Mb (from 159.66 to 162.19 Mb). In the Canadian Duroc pigs, two novel QTLs on SSC1 were detected for LMP, which were situated in 3.86 Mb (from 157.99 to 161.85 Mb) and 555 kb (from 37.63 to 38.19 Mb) regions. The meta-analysis identified ten and 20 additional SNPs for ADG and LMP, respectively. Finally, four genes (PHLPP1, STC1, DYRK1B, and PIK3C2A) were detected to be associated with ADG and/or LMP. Further bioinformatics analysis showed that the candidate genes for ADG are mainly involved in bone growth and development, whereas the candidate genes for LMP mainly participated in adipose tissue and muscle tissue growth and development. Conclusions We performed GWAS and meta-analysis for ADG and LMP based on a large sample size consisting of two Duroc pig populations. One pleiotropic QTL that shared a 2.19 Mb haplotype block from 159.66 to 161.85 Mb on SSC1 was found to affect ADG and LMP in the two Duroc pig populations. Furthermore, the combination of single-population and meta-analysis of GWAS improved the efficiency of detecting additional SNPs for the analyzed traits. Our results provide new insights into the genetic architecture of ADG and LMP traits in pigs. Moreover, some significant SNPs associated with ADG and/or LMP in this study may be useful for marker-assisted selection in pig breeding.

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