scholarly journals Multi-SNP Mediation Intersection-Union Test

2018 ◽  
Author(s):  
Wujuan Zhong ◽  
Cassandra N. Spracklen ◽  
Karen L. Mohlke ◽  
Xiaojing Zheng ◽  
Jason Fine ◽  
...  
Keyword(s):  
Association Studies ◽  
R Package ◽  
Alternative Methods ◽  
Genome Wide Association Studies ◽  
Mediation Effects ◽  
Coding Regions ◽  
Genome Wide ◽  
Plasma Adiponectin Level ◽  
Intersection Union Test

ABSTRACTTens of thousands of reproducibly identified GWAS (Genome-Wide Association Studies) variants, with the vast majority falling in non-coding regions resulting in no eventual protein products, call urgently for mechanistic interpretations. Although numerous methods exist, there are few, if any methods, for simultaneously testing the mediation effects of multiple correlated SNPs via some mediator (for example, the expression of a gene in the neighborhood) on phenotypic outcome. We propose SMUT, multi-SNP Mediation intersection-Union Test to fill in this methodological gap. Our extensive simulations demonstrate the validity of SMUT as well as substantial, up to 92%, power gains over alternative methods. In addition, SMUT confirmed known mediators in a real dataset of Finns for plasma adiponectin level, which were missed by many alternative methods. We believe SMUT will become a useful tool to generate mechanistic hypotheses underlying GWAS variants, facilitating functional follow-up. The R package SMUT is publicly available from CRAN at https://CRAN.R-project.org/package=SMUT.

scholarly journals Multi-SNP mediation intersection-union test

2019 ◽  
Vol 35 (22) ◽  
pp. 4724-4729 ◽  
Author(s):  
Wujuan Zhong ◽  
Cassandra N Spracklen ◽  
Karen L Mohlke ◽  
Xiaojing Zheng ◽  
Jason Fine ◽  
...  
Keyword(s):  
Association Studies ◽  
R Package ◽  
Alternative Methods ◽  
Supplementary Information ◽  
Genome Wide Association Studies ◽  
Mediation Effects ◽  
Coding Regions ◽  
Genome Wide ◽  
Plasma Adiponectin Level ◽  
Intersection Union Test

Abstract Summary Tens of thousands of reproducibly identified GWAS (Genome-Wide Association Studies) variants, with the vast majority falling in non-coding regions resulting in no eventual protein products, call urgently for mechanistic interpretations. Although numerous methods exist, there are few, if any methods, for simultaneously testing the mediation effects of multiple correlated SNPs via some mediator (e.g. the expression of a gene in the neighborhood) on phenotypic outcome. We propose multi-SNP mediation intersection-union test (SMUT) to fill in this methodological gap. Our extensive simulations demonstrate the validity of SMUT as well as substantial, up to 92%, power gains over alternative methods. In addition, SMUT confirmed known mediators in a real dataset of Finns for plasma adiponectin level, which were missed by many alternative methods. We believe SMUT will become a useful tool to generate mechanistic hypotheses underlying GWAS variants, facilitating functional follow-up. Availability and implementation The R package SMUT is publicly available from CRAN at https://CRAN.R-project.org/package=SMUT. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Gene-centric functional dissection of human genetic variation uncovers regulators of hematopoiesis

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Satish K Nandakumar ◽  
Sean K McFarland ◽  
Laura M Mateyka ◽  
Caleb A Lareau ◽  
Jacob C Ulirsch ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Target Genes ◽  
Association Studies ◽  
Human Diseases ◽  
Genome Wide Association Studies ◽  
Loss Of Function ◽  
Coding Regions ◽  
Genome Wide ◽  
Causal Variants

Genome-wide association studies (GWAS) have identified thousands of variants associated with human diseases and traits. However, the majority of GWAS-implicated variants are in non-coding regions of the genome and require in depth follow-up to identify target genes and decipher biological mechanisms. Here, rather than focusing on causal variants, we have undertaken a pooled loss-of-function screen in primary hematopoietic cells to interrogate 389 candidate genes contained in 75 loci associated with red blood cell traits. Using this approach, we identify 77 genes at 38 GWAS loci, with most loci harboring 1–2 candidate genes. Importantly, the hit set was strongly enriched for genes validated through orthogonal genetic approaches. Genes identified by this approach are enriched in specific and relevant biological pathways, allowing regulators of human erythropoiesis and modifiers of blood diseases to be defined. More generally, this functional screen provides a paradigm for gene-centric follow up of GWAS for a variety of human diseases and traits.

scholarly journals The open targets post-GWAS analysis pipeline

2020 ◽  
Vol 36 (9) ◽  
pp. 2936-2937 ◽  
Author(s):  
Gareth Peat ◽  
William Jones ◽  
Michael Nuhn ◽  
José Carlos Marugán ◽  
William Newell ◽  
...  
Keyword(s):  
Drug Targets ◽  
Gene Expression Regulation ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Protein Coding ◽  
Data Resource ◽  
Coding Regions ◽  
Genome Wide ◽  
Causal Genes ◽  
Interactive Data

Abstract Motivation Genome-wide association studies (GWAS) are a powerful method to detect even weak associations between variants and phenotypes; however, many of the identified associated variants are in non-coding regions, and presumably influence gene expression regulation. Identifying potential drug targets, i.e. causal protein-coding genes, therefore, requires crossing the genetics results with functional data. Results We present a novel data integration pipeline that analyses GWAS results in the light of experimental epigenetic and cis-regulatory datasets, such as ChIP-Seq, Promoter-Capture Hi-C or eQTL, and presents them in a single report, which can be used for inferring likely causal genes. This pipeline was then fed into an interactive data resource. Availability and implementation The analysis code is available at www.github.com/Ensembl/postgap and the interactive data browser at postgwas.opentargets.io.

scholarly journals The Mediation Effects of Aluminum in Plasma and Dipeptidyl Peptidase Like Protein 6 (DPP6) Polymorphism on Renal Function via Genome-Wide Typing Association

2021 ◽  
Vol 18 (19) ◽  
pp. 10484
Author(s):  
Ting-Hao Chen ◽  
Chen-Cheng Yang ◽  
Kuei-Hau Luo ◽  
Chia-Yen Dai ◽  
Yao-Chung Chuang ◽  
...  
Keyword(s):  
Renal Function ◽  
Mediation Analysis ◽  
Association Studies ◽  
Dipeptidyl Peptidase ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Mediation Effects ◽  
Genome Wide ◽  
Estimated Glomerular Filtration Rates

Aluminum (Al) toxicity is related to renal failure and the failure of other systems. Although there were some genome-wide association studies (GWAS) in Australia and England, there were no GWAS about Han Chinese to our knowledge. Thus, this research focused on using whole genomic genotypes from the Taiwan Biobank for exploring the association between Al concentrations in plasma and renal function. Participants, who underwent questionnaire interviews, biomarkers, and genotyping, were from the Taiwan Biobank database. Then, we measured their plasma Al concentrations with ICP-MS in the laboratory at Kaohsiung Medical University. We used this data to link genome-wide association (GWA) tests while looking for candidate genes and associated plasma Al concentration to renal function. Furthermore, we examined the path relationship between Single Nucleotide Polymorphisms (SNPs), Al concentrations, and estimated glomerular filtration rates (eGFR) through the mediation analysis with 3000 replication bootstraps. Following the principles of GWAS, we focused on three SNPs within the dipeptidyl peptidase-like protein 6 (DPP6) gene in chromosome 7, rs10224371, rs2316242, and rs10268004, respectively. The results of the mediation analysis showed that all of the selected SNPs have indirectly affected eGFR through a mediation of Al concentrations. Our analysis revealed the association between DPP6 SNPs, plasma Al concentrations, and eGFR. However, further longitudinal studies and research on mechanism are in need. Our analysis was still be the first study that explored the association between the DPP6, SNPs, and Al in plasma affecting eGFR.

scholarly journals bGWAS: an R package to perform Bayesian genome wide association studies

2020 ◽  
Vol 36 (15) ◽  
pp. 4374-4376
Author(s):  
Ninon Mounier ◽  
Zoltán Kutalik
Keyword(s):  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
R Package ◽  
Genome Wide Association ◽  
Supplementary Information ◽  
Genome Wide Association Studies ◽  
Biological Mechanisms ◽  
Genome Wide ◽  
Related Risk

Abstract Summary Increasing sample size is not the only strategy to improve discovery in Genome Wide Association Studies (GWASs) and we propose here an approach that leverages published studies of related traits to improve inference. Our Bayesian GWAS method derives informative prior effects by leveraging GWASs of related risk factors and their causal effect estimates on the focal trait using multivariable Mendelian randomization. These prior effects are combined with the observed effects to yield Bayes Factors, posterior and direct effects. The approach not only increases power, but also has the potential to dissect direct and indirect biological mechanisms. Availability and implementation bGWAS package is freely available under a GPL-2 License, and can be accessed, alongside with user guides and tutorials, from https://github.com/n-mounier/bGWAS. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Qtlizer: comprehensive QTL annotation of GWAS results

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Matthias Munz ◽  
Inken Wohlers ◽  
Eric Simon ◽  
Tobias Reinberger ◽  
Hauke Busch ◽  
...  
Keyword(s):  
Association Studies ◽  
Housekeeping Genes ◽  
R Package ◽  
Genome Wide Association Studies ◽  
Protein Abundance ◽  
Base Pairs ◽  
Link Type ◽  
Genome Wide ◽  
Wide Range ◽  
Distance Limit

AbstractExploration of genetic variant-to-gene relationships by quantitative trait loci such as expression QTLs is a frequently used tool in genome-wide association studies. However, the wide range of public QTL databases and the lack of batch annotation features complicate a comprehensive annotation of GWAS results. In this work, we introduce the tool “Qtlizer” for annotating lists of variants in human with associated changes in gene expression and protein abundance using an integrated database of published QTLs. Features include incorporation of variants in linkage disequilibrium and reverse search by gene names. Analyzing the database for base pair distances between best significant eQTLs and their affected genes suggests that the commonly used cis-distance limit of 1,000,000 base pairs might be too restrictive, implicating a substantial amount of wrongly and yet undetected eQTLs. We also ranked genes with respect to the maximum number of tissue-specific eQTL studies in which a most significant eQTL signal was consistent. For the top 100 genes we observed the strongest enrichment with housekeeping genes (P = 2 × 10–6) and with the 10% highest expressed genes (P = 0.005) after grouping eQTLs by r2 > 0.95, underlining the relevance of LD information in eQTL analyses. Qtlizer can be accessed via https://genehopper.de/qtlizer or by using the respective Bioconductor R-package (https://doi.org/10.18129/B9.bioc.Qtlizer).

SMARCA2 common variant association and rare variant excess in Schizophrenia patients from an Algerian Trio Cohort

2011 ◽  
Vol 26 (S2) ◽  
pp. 1346-1346
Author(s):  
D. Benmessaoud ◽  
A.-M. Lepagnol-Bestel ◽  
M. Delepine ◽  
J. Hager ◽  
J.-M. Moalic ◽  
...  
Keyword(s):  
Rare Variants ◽  
Association Studies ◽  
Common Variant ◽  
Genome Wide Association Studies ◽  
Common Variants ◽  
Fisher Test ◽  
Coding Regions ◽  
Genome Wide ◽  
Whole Exome ◽  
Positive Evolution

Genome wide association studies (GWAS) of Schizophrenia (SZ) patients have identified common variants in ten genes including SMARCA2 (Koga et al., HMG, 2009). We found that the SZ-GWAS genes are part of an interacting network centered on SMARCA2 (Loe-Mie et al., HMG, 2010). Furthermore, SMARCA2 was found disrupted in SZ (Walsh et al., Science, 2008). SMARCA2 encodes the ATPase (BRM) of the SWI/SNF chromatin remodeling complex that is at the interface of genome and environmental adaptation.Taking advantage of an Algerian trio cohort of one hundred SZ patients (Benmessaoud et al., BMC Psychiatry, 2008), we replicated the association of SNP rs2296212 localized in exon 33, already shown associated in Koga study and resulting in D1546E amino acid change in the SMARCA2 protein. We studied SMARCA2 codons and found that exon 33 displays a signature of positive evolution in the primate lineage.Our working hypothesis is that the coding regions displaying positive selection are target of novel rare variants. To address this question, we sequenced two exons displaying positive evolution and one exon without evidence of positive evolution.We found (i) that rare variants are significantly in excess in SZ-patients compared to their parents (p = 0.038, Fisher test) and (ii) a higher proportion of rare variants in the primate-accelerated exons compared with the non-evolutionary exon in SZ-patients (p = 0.032, Fisher test).SMARCA2 exon sequencing and whole exome sequencing from patients harboring SNP rs2296212 common variant are under progress. Altogether, these results are expected to give new insights into the genetic architecture of SZ.

scholarly journals Genome-wide association studies of cardiac electrical phenotypes

2020 ◽  
Vol 116 (9) ◽  
pp. 1620-1634
Author(s):  
Charlotte Glinge ◽  
Najim Lahrouchi ◽  
Reza Jabbari ◽  
Jacob Tfelt-Hansen ◽  
Connie R Bezzina
Keyword(s):  
Genetic Basis ◽  
Association Studies ◽  
Individual Variability ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
Challenges And Opportunities ◽  
Electrocardiographic Parameters

Abstract The genetic basis of cardiac electrical phenotypes has in the last 25 years been the subject of intense investigation. While in the first years, such efforts were dominated by the study of familial arrhythmia syndromes, in recent years, large consortia of investigators have successfully pursued genome-wide association studies (GWAS) for the identification of single-nucleotide polymorphisms that govern inter-individual variability in electrocardiographic parameters in the general population. We here provide a review of GWAS conducted on cardiac electrical phenotypes in the last 14 years and discuss the implications of these discoveries for our understanding of the genetic basis of disease susceptibility and variability in disease severity. Furthermore, we review functional follow-up studies that have been conducted on GWAS loci associated with cardiac electrical phenotypes and highlight the challenges and opportunities offered by such studies.

scholarly journals Alternative Methods for H1 Simulations in Genome-Wide Association Studies

2012 ◽  
Vol 73 (2) ◽  
pp. 95-104 ◽  
Author(s):  
V. Perduca ◽  
C. Sinoquet ◽  
R. Mourad ◽  
G. Nuel
Keyword(s):  
Association Studies ◽  
Genome Wide Association ◽  
Alternative Methods ◽  
Genome Wide Association Studies ◽  
Genome Wide

Efficient estimation of disease odds ratios for follow-up genetic association studies

2017 ◽  
Vol 28 (7) ◽  
pp. 1927-1941
Author(s):  
Jiyuan Hu ◽  
Wei Zhang ◽  
Xinmin Li ◽  
Dongdong Pan ◽  
Qizhai Li
Keyword(s):  
Genetic Association ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Efficient Estimation ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Odds Ratios ◽  
Genome Wide ◽  
Follow Up Studies

In the past decade, genome-wide association studies have identified thousands of susceptible variants associated with complex human diseases and traits. Conducting follow-up genetic association studies has become a standard approach to validate the findings of genome-wide association studies. One problem of high interest in genetic association studies is to accurately estimate the strength of the association, which is often quantified by odds ratios in case-control studies. However, estimating the association directly by follow-up studies is inefficient since this approach ignores information from the genome-wide association studies. In this article, an estimator called GFcom, which integrates information from genome-wide association studies and follow-up studies, is proposed. The estimator includes both the point estimate and corresponding confidence interval. GFcom is more efficient than competing estimators regarding MSE and the length of confidence intervals. The superiority of GFcom is particularly evident when the genome-wide association study suffers from severe selection bias. Comprehensive simulation studies and applications to three real follow-up studies demonstrate the performance of the proposed estimator. An R package, “GFcom”, implementing our method is publicly available at https://github.com/JiyuanHu/GFcom .

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