TY - JOUR
T1 - Mining GWAS and eQTL data for CF lung disease modifiers by gene expression imputation
AU - Dang, Hong
AU - Polineni, Deepika
AU - Pace, Rhonda G.
AU - Stonebraker, Jaclyn R.
AU - Corvol, Harriet
AU - Cutting, Garry R.
AU - Drumm, Mitchell L.
AU - Strug, Lisa J.
AU - O’Neal, Wanda K.
AU - Knowles, Michael R.
N1 - Funding Information:
H.D. was supported by Cystic Fibrosis Foundation grant, DANG16I0. M.R.K. was supported by Cystic Fibrosis Foundation grant, KNOWLE00A0. CFF URL: https://www.cff.org/ Research/Researcher-Resources/Awards-and-Grants/ The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank Dr. Nancy J. Cox, Vanderbilt University, Division of Genetic Medicine, Dr. Fred Wright, North Carolina State University, Bioinformatics Research Center, and Dr. Ani W. 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, Department of Human Genetics, Dr. Alexander Gusev and lab, Harvard University, Dana Farber Cancer Institute, and the Genotype-Tissue Expression (GTEx) project, for making their software tools and databases (PrediXcan and TWAS) open source and publicly available.
Publisher Copyright:
© 2020 Dang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2020/11
Y1 - 2020/11
N2 - Genome wide association studies (GWAS) have identified several genomic loci with candidate modifiers of cystic fibrosis (CF) lung disease, but only a small proportion of the expected genetic contribution is accounted for at these loci. We leveraged expression data from CF cohorts, and Genotype-Tissue Expression (GTEx) reference data sets from multiple human tissues to generate predictive models, which were used to impute transcriptional regulation from genetic variance in our GWAS population. 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. We delved into 52 modifier candidates that showed consensus between approaches, and 28 of them were near known GWAS loci. A number of these genes are implicated in the pathophysiology of CF lung disease (e.g., immunity, infection, inflammation, HLA pathways, glycosylation, and mucociliary clearance) and the CFTR protein biology (e.g., cytoskeleton, microtubule, mitochondrial function, lipid metabolism, endoplasmic reticulum/Golgi, and ubiquitination). Gene set enrichment results are consistent with current knowledge of CF lung disease pathogenesis. HLA Class II genes on chr6, and CEP72, EXOC3, and TPPP near the GWAS peak on chr5 are most consistently associated with CF lung disease severity across the tissues tested. 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.
AB - Genome wide association studies (GWAS) have identified several genomic loci with candidate modifiers of cystic fibrosis (CF) lung disease, but only a small proportion of the expected genetic contribution is accounted for at these loci. We leveraged expression data from CF cohorts, and Genotype-Tissue Expression (GTEx) reference data sets from multiple human tissues to generate predictive models, which were used to impute transcriptional regulation from genetic variance in our GWAS population. 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. We delved into 52 modifier candidates that showed consensus between approaches, and 28 of them were near known GWAS loci. A number of these genes are implicated in the pathophysiology of CF lung disease (e.g., immunity, infection, inflammation, HLA pathways, glycosylation, and mucociliary clearance) and the CFTR protein biology (e.g., cytoskeleton, microtubule, mitochondrial function, lipid metabolism, endoplasmic reticulum/Golgi, and ubiquitination). Gene set enrichment results are consistent with current knowledge of CF lung disease pathogenesis. HLA Class II genes on chr6, and CEP72, EXOC3, and TPPP near the GWAS peak on chr5 are most consistently associated with CF lung disease severity across the tissues tested. 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.
UR - http://www.scopus.com/inward/record.url?scp=85097034775&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85097034775&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0239189
DO - 10.1371/journal.pone.0239189
M3 - Article
C2 - 33253230
AN - SCOPUS:85097034775
SN - 1932-6203
VL - 15
JO - PloS one
JF - PloS one
IS - 11 November
M1 - e0239189
ER -