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Evaluation of PrediXcan for prioritizing GWAS associations and predicting gene expression

Binglan Li, Shefali S Verma, Yogasudha C Veturi, Anurag Verma, Yuki Bradford, David W Haas, Marylyn D Ritchie
2018 Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing  
As for GWAS prioritization, predicted gene expression levels were used to obtain gene-trait associations, and background regions of significant associations were examined to decrease the likelihood of  ...  In this study, two of the most practical functions of PrediXcan were tested: 1) predicting gene expression, and 2) prioritizing GWAS results.  ...  In addition, they acknowledge the contributions of study teams and site staff for these protocols. We thank Paul J.  ... 
pmid:29218904 pmcid:PMC5749400 fatcat:di6nv42iubcytdbfymqkuomblq

Evaluation of PrediXcan for prioritizing GWAS associations and predicting gene expression

Binglan Li, Shefali S. Verma, Yogasudha C. Veturi, Anurag Verma, Yuki Bradford, David W. Haas, Marylyn D. Ritchie
2017 Biocomputing 2018  
As for GWAS prioritization, predicted gene expression levels were used to obtain gene-trait associations, and background regions of significant associations were examined to decrease the likelihood of  ...  In this study, two of the most practical functions of PrediXcan were tested: 1) predicting gene expression, and 2) prioritizing GWAS results.  ...  In addition, they acknowledge the contributions of study teams and site staff for these protocols. We thank Paul J.  ... 
doi:10.1142/9789813235533_0041 fatcat:r3elz4xgcrayzlyc5gt5pbapzi

Transcriptome wide association studies: general framework and methods

Yuhan Xie, Nayang Shan, Hongyu Zhao, Lin Hou
2021 Quantitative Biology  
With the recent progress in expression quantitative trait loci (eQTL) studies, transcriptome-wide association studies (TWAS) provide a framework to test for gene-trait associations by integrating information  ...  Genome-wide association studies (GWAS) have succeeded in identifying tens of thousands of genetic variants associated with complex human traits during the past decade, however, they are still hampered  ...  ACKNOWLEDGEMENTS We thank Zhaolong Yu for suggestions and Michael Farruggia for English language polishing. L. H. acknowledges the following fundings: the  ... 
doi:10.15302/j-qb-020-0228 fatcat:tp34rkvrmzempevsqq37lh67gq

Transcriptome-wide association study for restless legs syndrome identifies new susceptibility genes

Fulya Akçimen, Faezeh Sarayloo, Calwing Liao, Jay P. Ross, Rachel De Barros Oliveira, Patrick A. Dion, Guy A. Rouleau
2020 Communications Biology  
Overall, our findings highlight the power of integrating gene expression data with GWAS to prioritize putative causal genes for functional follow-up studies.  ...  We conducted a transcriptome-wide association study involving 15,126 RLS cases and 95,725 controls, from the most recent meta-analysis of GWAS, and gene expression weights of GTEx v7 and the CMC dorsolateral  ...  *The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.  ... 
doi:10.1038/s42003-020-1105-z pmid:32651461 fatcat:bh7viwjt4bexlkqdvdqs7angqe

Influence of tissue context on gene prioritization for predicted transcriptome-wide association studies

Binglan Li, Yogasudha Veturi, Yuki Bradford, Shefali S Verma, Anurag Verma, Anastasia M Lucas, David W Haas, Marylyn D Ritchie
2019 Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing  
TWAS integrates genotypic data with expression quantitative trait loci (eQTLs) to predict genetically regulated gene expression components and associates predictions with a trait of interest.  ...  As such, TWAS can prioritize genes whose differential expressions contribute to the trait of interest and provide mechanistic explanation of complex trait(s).  ...  Hae Kyung Im from the University of Chicago for their support.  ... 
pmid:30864331 pmcid:PMC6417797 fatcat:fip3ep7ulnb3jap7htpb22gsza

PhenomeXcan: Mapping the genome to the phenome through the transcriptome

Milton Pividori, Padma S. Rajagopal, Alvaro Barbeira, Yanyu Liang, Owen Melia, Lisa Bastarache, YoSon Park, GTEx Consortium, Xiaoquan Wen, Hae K. Im
2020 Science Advances  
Using PhenomeXcan results, we provide examples of novel and underreported genome-to-phenome associations, complex gene-trait clusters, shared causal genes between common and rare diseases via further integration  ...  We developed a novel Bayesian colocalization method, fast enrichment estimation aided colocalization analysis (fastENLOC), to prioritize likely causal gene-trait associations.  ...  Using PrediXcan allows us to derive gene-based associations with traits in context by integrating GWAS summary statistics with transcriptome-wide predicted expression and regulatory or functional information  ... 
doi:10.1126/sciadv.aba2083 pmid:32917697 fatcat:nct4rmo7krgdjo5ln7asvcvfae

Exploiting the GTEx resources to decipher the mechanisms at GWAS loci

Alvaro N. Barbeira, GTEx GWAS Working Group, Rodrigo Bonazzola, Eric R. Gamazon, Yanyu Liang, YoSon Park, Sarah Kim-Hellmuth, Gao Wang, Zhuoxun Jiang, Dan Zhou, Farhad Hormozdiari, Boxiang Liu (+18 others)
2021 Genome Biology  
Using colocalization and association approaches that take into account the observed allelic heterogeneity of gene expression, we propose potential target genes for 47% (2519 out of 5385) of the GWAS loci  ...  We develop a data-driven framework to benchmark methods that prioritize causal genes and find no single approach outperforms the combination of multiple approaches.  ...  Acknowledgements We thank the donors and their families for their generous gifts of organ donation for transplantation, and tissue donations for the GTEx research project; Mariya Khan and Christopher Stolte  ... 
doi:10.1186/s13059-020-02252-4 pmid:33499903 pmcid:PMC7836161 fatcat:lvok3l4c6zcp5haxdiqvhikmje

A Multi-tissue Transcriptome Analysis of Human Metabolites Guides Interpretability of Associations Based on Multi-SNP Models for Gene Expression

Anne Ndungu, Anthony Payne, Jason M. Torres, Martijn van de Bunt, Mark I. McCarthy
2020 American Journal of Human Genetics  
There is particular interest in transcriptome-wide association studies (TWAS) gene-level tests based on multi-SNP predictive models of gene expression-for identifying causal genes at loci associated with  ...  We characterized the performance of single- and multi-SNP models for identifying causal genes in GWAS data for 46 circulating metabolites.  ...  The views expressed are those of the author and not necessarily those of the National Health Service (NHS), the NIHR, or the Department of Health.  ... 
doi:10.1016/j.ajhg.2020.01.003 pmid:31978332 pmcid:PMC7010967 fatcat:eqrvw5oitzhtxonc7qlp456ebi

A multi-tissue transcriptome analysis of human metabolites guides the interpretability of associations based on multi-SNP models for gene expression [article]

Anne Ndungu, Anthony Payne, Jason M Torres, Martijn van de Bunt, Mark McCarthy
2019 biorxiv/medrxiv   pre-print
There is particular interest in transcriptome-wide association studies (TWAS) - gene-level tests based on multi-SNP predictive models of gene expression - for identifying causal genes at loci associated  ...  We characterized the performance of single- and multi-SNP TWAS models for identifying causal genes in GWAS data for 46 circulating metabolites.  ...  The views expressed are those of the author and not necessarily those of the National Health Service (NHS), the NIHR, or the Department of Health.  ... 
doi:10.1101/773630 fatcat:6epleeqvknbr5bxq5dtfjbf7sa

Transcriptome‐wide association study reveals candidate causal genes for lung cancer

Yohan Bossé, Zhonglin Li, Jun Xia, Venkata Manem, Robert Carreras‐Torres, Aurélie Gabriel, Nathalie Gaudreault, Demetrius Albanes, Melinda C. Aldrich, Angeline Andrew, Susanne Arnold, Heike Bickeböller (+36 others)
2019 International Journal of Cancer  
A new lung adenocarcinoma susceptibility locus was revealed on 9p13.3 and associated with higher predicted expression of AQP3 (pTWAS = 3.72E-6).  ...  Among the 45 previously described lung cancer GWAS loci, we mapped candidate target gene for 17 of them. The association AQP3-adenocarcinoma on 9p13.3 was replicated using GTEx (pTWAS = 6.55E-5).  ...  Amos is a Research Scholar of the Cancer Prevention Research Institute of Texas. Functional studies for this grant and partial effort support for Drs. Amos and Xia were supported by CPRIT RR17004.  ... 
doi:10.1002/ijc.32771 pmid:31696517 pmcid:PMC7008463 fatcat:ypawxwbm4naj5gca7yrrxvln3e

SUMMIT: An integrative approach for better transcriptomic data imputation improves causal gene identification [article]

Zichen Zhang, Ye Eun Bae, Jonathan R. Bradley, Lang Wu, Chong Wu
2021 medRxiv   pre-print
Through simulation studies and analyses of GWAS summary statistics for 24 complex traits, we show that SUMMIT substantially improves the accuracy of expression prediction in blood, successfully builds  ...  expression prediction models for genes with low expression heritability, and achieves higher statistical power than several benchmark methods.  ...  Second, statistical associations are estimated between predicted gene expression levels for GWAS samples and the trait of interest.  ... 
doi:10.1101/2021.12.09.21267570 fatcat:wfahkirxobeubmoptfb5xr6ffm

CoMM: A Collaborative Mixed Model That Integrates GWAS and eQTL Data Sets to Investigate the Genetic Architecture of Complex Traits

Kar-Fu Yeung, Yi Yang, Can Yang, Jin Liu
2019 Bioinformatics and Biology Insights  
The gene expression levels for the GWAS data set are then 'imputed' using the prediction model, and the imputed expression levels are tested for their association with the phenotype.  ...  Methods such as PrediXcan and transcriptome-wide association study (TWAS) use the transcriptome data set to fit a predictive model for gene expression, with genetic variants as covariates.  ...  Acknowledgement The authors thank the National Supercomputing Centre, Singapore, for providing computational resources for the project.  ... 
doi:10.1177/1177932219881435 pmid:31662603 pmcid:PMC6792274 fatcat:xttqjhe4zjblhi7eqowv23vkti

Vulnerabilities of transcriptome-wide association studies [article]

Michael Wainberg, Nasa Sinnott-Armstrong, David Knowles, David Golan, Raili Ermel, Arno Ruusalepp, Thomas Quertermous, Ke Hao, Johan L. M. Bjorkegren, Manuel A. Rivas, Anshul Kundaje
2017 bioRxiv   pre-print
Transcriptome-wide association studies (TWAS) integrate GWAS and expression quantitative trait locus (eQTL) datasets to discover candidate causal gene-trait associations.  ...  We integrate multi-tissue expression panels and summary GWAS for LDL cholesterol and Crohn's disease to show that TWAS are highly vulnerable to discovering non-causal genes, because variants at a single  ...  Acknowledgements We gratefully acknowledge Jonathan Pritchard, Hua Tang and members of the Zaitlen lab for helpful discussions. This work was funded in part by the Natural Sciences and Engineering  ... 
doi:10.1101/206961 fatcat:vevcpi5g7zh4jh47s64gs5yrpu

Integrating predicted transcriptome from multiple tissues improves association detection

Alvaro N. Barbeira, Milton Pividori, Jiamao Zheng, Heather E. Wheeler, Dan L. Nicolae, Hae Kyung Im, Vincent Plagnol
2019 PLoS Genetics  
Gene-level association methods such as PrediXcan can prioritize candidate targets.  ...  Integration of genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) studies is needed to improve our understanding of the biological mechanisms underlying GWAS hits, and  ...  This is a study led by the Kaiser Permanente Research Program on Genes, Environment, and Health (RPGEH) and the UCSF Institute for Human Genetics with over 100,000 participants. This  ... 
doi:10.1371/journal.pgen.1007889 pmid:30668570 pmcid:PMC6358100 fatcat:hunzofvvi5crvoas6gbgs7ub2i

Mining GWAS and eQTL data for CF lung disease modifiers by gene expression imputation

Hong Dang, Deepika Polineni, Rhonda G. Pace, Jaclyn R. Stonebraker, Harriet Corvol, Garry R. Cutting, Mitchell L. Drumm, Lisa J. Strug, Wanda K. O'Neal, Michael R. Knowles, Dylan Glubb
2020 PLoS ONE  
The results help to prioritize genes in the GWAS regions, predict direction of gene expression regulation, and identify new candidate modifiers throughout the genome for potential therapeutic development  ...  The imputed gene expression was tested for association with CF lung disease severity. By comparing and combining results from alternative approaches, we identified 379 candidate modifier genes.  ...  Manichaikul, University of Virginia, Center for Public Health Genomics, for guidance, advisement, and discussion. We also like to thank Dr. Hae Kyung Im and lab, University of Chicago,  ... 
doi:10.1371/journal.pone.0239189 pmid:33253230 fatcat:acyhtl5oazaelg5s75qnqqw62q
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