Abstract
Genome-wide association studies (GWAS) have successfully identified many genetic variants associated with complex traits. However, GWAS experience power issues, resulting in the failure to detect certain associated variants. Additionally, GWAS are often unable to parse the biological mechanisms of driving associations. An existing gene-based association test framework, Transcriptome-Wide Association Studies (TWAS), leverages expression quantitative trait loci data to increase the power of association tests and illuminate the biological mechanisms by which genetic variants modulate complex traits. We extend the TWAS methodology to incorporate somatic information from tumors. By integrating germline and somatic data we are able to leverage information from the nuanced somatic landscape of tumors. Thus we can augment the power of TWAS-type tests to detect germline genetic variants associated with cancer phenotypes. We use somatic and germline data on lung adenocarcinomas from The Cancer Genome Atlas in conjunction with a meta-analyzed lung cancer GWAS to identify novel genes associated with lung cancer.
Original language | English (US) |
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Pages (from-to) | 233-247 |
Number of pages | 15 |
Journal | Genetic epidemiology |
Volume | 44 |
Issue number | 3 |
DOIs | |
State | Published - Apr 1 2020 |
Bibliographical note
Funding Information:We thank the reviewers for many helpful suggestions and insightful comments. This study was supported by the National Institutes of Health grants T32GM108557, R21AG057038, R01HL116720, R01GM113250, R01GM126002 and R01HL105397, and by the Minnesota Supercomputing Institute at the University of Minnesota.
Funding Information:
We thank the reviewers for many helpful suggestions and insightful comments. This study was supported by the National Institutes of Health grants T32GM108557, R21AG057038, R01HL116720, R01GM113250, R01GM126002 and R01HL105397, and by the Minnesota Supercomputing Institute at the University of Minnesota.
Publisher Copyright:
© 2019 Wiley Periodicals, Inc.
Keywords
- PrediXcan
- SSU test
- TWAS
- aSPU test
- eQTL
- sum test