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Nat Commun. 2018 Oct 4;9(1):4079. doi: 10.1038/s41467-018-06302-1.

Large-scale transcriptome-wide association study identifies new prostate cancer risk regions.

Author information

1
Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, 90095, CA, USA. nmancuso@mednet.ucla.edu.
2
The Center for Bioinformatics and Functional Genomics, Cedars-Sinai Medical Center, Los Angeles, 90048, CA, USA.
3
Dana Farber Cancer Institute, Boston, 02215, MA, USA.
4
Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, 37232, TN, USA.
5
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, 02115, MA, USA.
6
Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital/Harvard Medical School, Boston, 02115, MA, USA.
7
Division of Genetics and Epidemiology, The Institute of Cancer Research, London, SW7 3RP, UK.
8
Royal Marsden NHS Foundation Trust, London, SW3 6JJ, UK.
9
Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, 02215, MA, USA.
10
Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, 90015, CA, USA.
11
Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, 90095, CA, USA.
12
Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, 90095, CA, USA.
13
Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, 90095, CA, USA.

Abstract

Although genome-wide association studies (GWAS) for prostate cancer (PrCa) have identified more than 100 risk regions, most of the risk genes at these regions remain largely unknown. Here we integrate the largest PrCa GWAS (N = 142,392) with gene expression measured in 45 tissues (N = 4458), including normal and tumor prostate, to perform a multi-tissue transcriptome-wide association study (TWAS) for PrCa. We identify 217 genes at 84 independent 1 Mb regions associated with PrCa risk, 9 of which are regions with no genome-wide significant SNP within 2 Mb. 23 genes are significant in TWAS only for alternative splicing models in prostate tumor thus supporting the hypothesis of splicing driving risk for continued oncogenesis. Finally, we use a Bayesian probabilistic approach to estimate credible sets of genes containing the causal gene at a pre-defined level; this reduced the list of 217 associations to 109 genes in the 90% credible set. Overall, our findings highlight the power of integrating expression with PrCa GWAS to identify novel risk loci and prioritize putative causal genes at known risk loci.

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