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Genetic determinants of chromatin reveal prostate cancer risk mediated by context-dependent gene regulation

Authors :
Baca, Sylvan C.
Singler, Cassandra
Zacharia, Soumya
Seo, Ji Heui
Morova, Tunc
Hach, Faraz
Ding, Yi
Schwarz, Tommer
Huang, Chia Chi Flora
Anderson, Jacob
Fay, André P.
Kalita, Cynthia
Groha, Stefan
Pomerantz, Mark M.
Wang, Victoria
Linder, Simon
Sweeney, Christopher J.
Zwart, Wilbert
Lack, Nathan A.
Pasaniuc, Bogdan
Takeda, David Y.
Gusev, Alexander
Freedman, Matthew L.
Baca, Sylvan C.
Singler, Cassandra
Zacharia, Soumya
Seo, Ji Heui
Morova, Tunc
Hach, Faraz
Ding, Yi
Schwarz, Tommer
Huang, Chia Chi Flora
Anderson, Jacob
Fay, André P.
Kalita, Cynthia
Groha, Stefan
Pomerantz, Mark M.
Wang, Victoria
Linder, Simon
Sweeney, Christopher J.
Zwart, Wilbert
Lack, Nathan A.
Pasaniuc, Bogdan
Takeda, David Y.
Gusev, Alexander
Freedman, Matthew L.
Source :
Nature Genetics vol.54 (2022) nr.9 p.1364-1375 [ISSN 1061-4036]
Publication Year :
2022

Abstract

Many genetic variants affect disease risk by altering context-dependent gene regulation. Such variants are difficult to study mechanistically using current methods that link genetic variation to steady-state gene expression levels, such as expression quantitative trait loci (eQTLs). To address this challenge, we developed the cistrome-wide association study (CWAS), a framework for identifying genotypic and allele-specific effects on chromatin that are also associated with disease. In prostate cancer, CWAS identified regulatory elements and androgen receptor-binding sites that explained the association at 52 of 98 known prostate cancer risk loci and discovered 17 additional risk loci. CWAS implicated key developmental transcription factors in prostate cancer risk that are overlooked by eQTL-based approaches due to context-dependent gene regulation. We experimentally validated associations and demonstrated the extensibility of CWAS to additional epigenomic datasets and phenotypes, including response to prostate cancer treatment. CWAS is a powerful and biologically interpretable paradigm for studying variants that influence traits by affecting transcriptional regulation.

Details

Database :
OAIster
Journal :
Nature Genetics vol.54 (2022) nr.9 p.1364-1375 [ISSN 1061-4036]
Notes :
Baca, Sylvan C.
Publication Type :
Electronic Resource
Accession number :
edsoai.on1383748890
Document Type :
Electronic Resource