scholarly journals Network-based metabolite ratios for an improved functional characterization of genome-wide association study results

2016 ◽  
Author(s):  
Jan Krumsiek ◽  
Ferdinand Stückler ◽  
Karsten Suhre ◽  
Christian Gieger ◽  
Tim D. Spector ◽  
...  
Keyword(s):  
Metabolic Network ◽  
Quantitative Traits ◽  
Association Studies ◽  
Small Sample ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Metabolomics Data ◽  
Association Tests ◽  
Genome Wide ◽  
Study Results

AbstractGenome-wide association studies (GWAS) with metabolite ratios as quantitative traits have successfully deepened our understanding of the complex relationship between genetic variants and metabolic phenotypes. Usually all ratio combinations are selected for association tests. However, with more metabolites being detectable, the quadratic increase of the ratio number becomes challenging from a statistical, computational and interpretational point-of-view. Therefore methods which select biologically meaningful ratios are required.We here present a network-based approach by selecting only closely connected metabolites in a given metabolic network. The feasibility of this approach was tested on in silico data derived from simulated reaction networks. Especially for small effect sizes, network-based metabolite ratios (NBRs) improved the metabolite-based prediction accuracy of genetically-influenced reactions compared to the ‘all ratios’ approach. Evaluating the NBR approach on published GWAS association results, we compared reported ‘all ratio’-SNP hits with results obtained by selecting only NBRs as candidates for association tests. Input networks for NBR selection were derived from public pathway databases or reconstructed from metabolomics data. NBR-candidates covered more than 80% of all significant ratio-SNP associations and we could replicate 7 out of 10 new associations predicted by the NBR approach.In this study we evaluated a network-based approach to select biologically meaningful metabolite ratios as quantitative traits in GWAS. Taking metabolic network information into account facilitated the analysis and the biochemical interpretation of metabolite-gene association results. For upcoming studies, for instance with case-control design, large-scale metabolomics data and small sample numbers, the analysis of all possible metabolite ratios is not feasible due to the correction for multiple testing. Here our NBR approach increases the statistical power and lowers computational demands, allowing for a better understanding of the complex interplay between individual phenotypes, genetics and metabolic profiles.

Abstract P260: Large-scale Meta-analysis of Diverse Ancestry Genome-wide Association Studies to Identify Pharmacogenomic Interactions of Sulfonylureas and ECG Phenotypes

Circulation ◽  
2016 ◽  
Vol 133 (suppl_1) ◽  
Author(s):  
James S Floyd ◽  
Colleen Sitlani ◽  
Christy L Avery ◽  
Eric A Whitsel ◽  
Leslie Lange ◽  
...  
Keyword(s):  
Repeated Measures ◽  
Qt Interval ◽  
Association Studies ◽  
Meta Analysis ◽  
Small Sample ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Meta Analyses

Introduction: Sulfonylureas are a commonly-used class of diabetes medication that can prolong the QT-interval, which is a leading cause of drug withdrawals from the market given the possible risk of life-threatening arrhythmias. Previously, we conducted a meta-analysis of genome-wide association studies of sulfonylurea-genetic interactions on QT interval among 9 European-ancestry (EA) cohorts using cross-sectional data, with null results. To improve our power to identify novel drug-gene interactions, we have included repeated measures of medication use and QT interval and expanded our study to include several additional cohorts, including African-American (AA) and Hispanic-ancestry (HA) cohorts with a high prevalence of sulfonylurea use. To identify potentially differential effects on cardiac depolarization and repolarization, we have also added two phenotypes - the JT and QRS intervals, which together comprise the QT interval. Hypothesis: The use of repeated measures and expansion of our meta-analysis to include diverse ancestry populations will allow us to identify novel pharmacogenomic interactions for sulfonylureas on the ECG phenotypes QT, JT, and QRS. Methods: Cohorts with unrelated individuals used generalized estimating equations to estimate interactions; cohorts with related individuals used mixed effect models clustered on family. For each ECG phenotype (QT, JT, QRS), we conducted ancestry-specific (EA, AA, HA) inverse variance weighted meta-analyses using standard errors based on the t-distribution to correct for small sample inflation in the test statistic. Ancestry-specific summary estimates were combined using MANTRA, an analytic method that accounts for differences in local linkage disequilibrium between ethnic groups. Results: Our study included 65,997 participants from 21 cohorts, including 4,020 (6%) sulfonylurea users, a substantial increase from the 26,986 participants and 846 sulfonylureas users in the previous meta-analysis. Preliminary ancestry-specific meta-analyses have identified genome-wide significant associations (P < 5х10–8) for each ECG phenotype, and analyses with MANTRA are in progress. Conclusions: In the setting of the largest collection of pharmacogenomic studies to date, we used repeated measurements and leveraged diverse ancestry populations to identify new pharmacogenomic loci for ECG traits associated with cardiovascular risk.

scholarly journals Genome-wide association studies for canine hip dysplasia in single and multiple populations – implications and potential novel risk loci

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Shizhi Wang ◽  
Erling Strandberg ◽  
Per Arvelius ◽  
Dylan N. Clements ◽  
Pamela Wiener ◽  
...  
Keyword(s):  
Hip Dysplasia ◽  
Association Studies ◽  
Meta Analysis ◽  
Small Sample ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Single Population ◽  
Positional Candidate ◽  
Genome Wide ◽  
Canine Hip Dysplasia

Abstract Background Association mapping studies of quantitative trait loci (QTL) for canine hip dysplasia (CHD) can contribute to the understanding of the genetic background of this common and debilitating disease and might contribute to its genetic improvement. The power of association studies for CHD is limited by relatively small sample numbers for CHD records within countries, suggesting potential benefits of joining data across countries. However, this is complicated due to the use of different scoring systems across countries. In this study, we incorporated routinely assessed CHD records and genotype data of German Shepherd dogs from two countries (UK and Sweden) to perform genome-wide association studies (GWAS) within populations using different variations of CHD phenotypes. As phenotypes, dogs were either classified into cases and controls based on the Fédération Cynologique Internationale (FCI) five-level grading of the worst hip or the FCI grade was treated as an ordinal trait. In a subsequent meta-analysis, we added publicly available data from a Finnish population and performed the GWAS across all populations. Genetic associations for the CHD phenotypes were evaluated in a linear mixed model using 62,089 SNPs. Results Multiple SNPs with genome-wide significant and suggestive associations were detected in single-population GWAS and the meta-analysis. Few of these SNPs overlapped between populations or between single-population GWAS and the meta-analysis, suggesting that many CHD-related QTL are population-specific. More significant or suggestive SNPs were identified when FCI grades were used as phenotypes in comparison to the case-control approach. MED13 (Chr 9) and PLEKHA7 (Chr 21) emerged as novel positional candidate genes associated with hip dysplasia. Conclusions Our findings confirm the complex genetic nature of hip dysplasia in dogs, with multiple loci associated with the trait, most of which are population-specific. Routinely assessed CHD information collected across countries provide an opportunity to increase sample sizes and statistical power for association studies. While the lack of standardisation of CHD assessment schemes across countries poses a challenge, we showed that conversion of traits can be utilised to overcome this obstacle.

To stratify or not to stratify: power considerations for population-based genome-wide association studies of quantitative traits

2011 ◽  
Vol 35 (8) ◽  
pp. 867-879 ◽  
Author(s):  
Gundula Behrens ◽  
Thomas W. Winkler ◽  
Mathias Gorski ◽  
Michael F. Leitzmann ◽  
Iris M. Heid
Keyword(s):  
Quantitative Traits ◽  
Association Studies ◽  
Population Based ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals The endothelial protein C receptor (PROCR) Ser219Gly variant and risk of common thrombotic disorders: a HuGE review and meta-analysis of evidence from observational studies

Blood ◽  
2012 ◽  
Vol 119 (10) ◽  
pp. 2392-2400 ◽  
Author(s):  
Jessica Dennis ◽  
Candice Y. Johnson ◽  
Adeniyi Samuel Adediran ◽  
Mariza de Andrade ◽  
John A. Heit ◽  
...  
Keyword(s):  
Protein C ◽  
Genetic Model ◽  
Thrombus Formation ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Endothelial Protein C Receptor ◽  
Genome Wide ◽  
Study Results

Abstract The endothelial protein C receptor (EPCR) limits thrombus formation by enhancing activation of the protein C anticoagulant pathway, and therefore may play a role in the etiology of thrombotic disorders. The rs867186 single-nucleotide polymorphism in the PROCR gene (g.6936A > G, c.4600A > G), resulting in a serine-to-glycine substitution at codon 219, has been associated with reduced activation of the protein C pathway, although its association with thrombosis risk remains unclear. The present study is a highly comprehensive systematic review and meta-analysis, including unpublished genome-wide association study results, conducted to evaluate the evidence for an association between rs867186 and 2 common thrombotic outcomes, venous thromboembolism (VTE) and myocardial infarction (MI), which are hypothesized to share some etiologic pathways. MEDLINE, EMBASE, and HuGE Navigator were searched through July 2011 to identify relevant epidemiologic studies, and data were summarized using random-effects meta-analysis. Twelve candidate genes and 13 genome-wide association studies were analyzed (11 VTE and 14 MI, including 37 415 cases and 84 406 noncases). Under the additive genetic model, the odds of VTE increased by a factor of 1.22 (95% confidence interval, 1.11-1.33, P < .001) for every additional copy of the G allele. No evidence for association with MI was observed.

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