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

The PRACTICAL Consortium

Research output: Contribution to journalArticle

6 Citations (Scopus)

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.

Original languageEnglish (US)
Article number4079
JournalNature Communications
Volume9
Issue number1
DOIs
StatePublished - Dec 1 2018

Fingerprint

Transcriptome
genes
Prostatic Neoplasms
Genes
cancer
genome
Genome-Wide Association Study
splicing
loci
Prostate
tumors
Bayes Theorem
gene expression
Tumors
Alternative Splicing
lists
Single Nucleotide Polymorphism
Tissue
Neoplasms
Carcinogenesis

ASJC Scopus subject areas

  • Chemistry(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Physics and Astronomy(all)

Cite this

Large-scale transcriptome-wide association study identifies new prostate cancer risk regions. / The PRACTICAL Consortium.

In: Nature Communications, Vol. 9, No. 1, 4079, 01.12.2018.

Research output: Contribution to journalArticle

@article{22ea4499cfc54ca1aaac725ac7cb4291,
title = "Large-scale transcriptome-wide association study identifies new prostate cancer risk regions",
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.",
author = "{The PRACTICAL Consortium} and Nicholas Mancuso and Simon Gayther and Alexander Gusev and Wei Zheng and Penney, {Kathryn L.} and Zsofia Kote-Jarai and Rosalind Eeles and Matthew Freedman and Christopher Haiman and Bogdan Pasaniuc and Henderson, {Brian E.} and Sara Benlloch and Schumacher, {Fredrick R.} and Olama, {Ali Amin Al} and Kenneth Muir and Berndt, {Sonja I.} and Conti, {David V.} and Fredrik Wiklund and Stephen Chanock and Stevens, {Victoria L.} and Tangen, {Catherine M.} and Jyotsna Batra and Judith Clements and Henrik Gronberg and Nora Pashayan and Johanna Schleutker and Demetrius Albanes and Stephanie Weinstein and Alicja Wolk and Catharine West and Lorelei Mucci and G{\'e}raldine Cancel-Tassin and Stella Koutros and Sorensen, {Karina Dalsgaard} and Lovise Maehle and Neal, {David E.} and Hamdy, {Freddie C.} and Donovan, {Jenny L.} and Travis, {Ruth C.} and Hamilton, {Robert J.} and Ingles, {Sue Ann} and Barry Rosenstein and Lu, {Yong Jie} and Giles, {Graham G.} and Kibel, {Adam S.} and Ana Vega and Manolis Kogevinas and Park, {Jong Y.} and Stanford, {Janet L.} and Thibodeau, {Stephen N}",
year = "2018",
month = "12",
day = "1",
doi = "10.1038/s41467-018-06302-1",
language = "English (US)",
volume = "9",
journal = "Nature Communications",
issn = "2041-1723",
publisher = "Nature Publishing Group",
number = "1",

}

TY - JOUR

T1 - Large-scale transcriptome-wide association study identifies new prostate cancer risk regions

AU - The PRACTICAL Consortium

AU - Mancuso, Nicholas

AU - Gayther, Simon

AU - Gusev, Alexander

AU - Zheng, Wei

AU - Penney, Kathryn L.

AU - Kote-Jarai, Zsofia

AU - Eeles, Rosalind

AU - Freedman, Matthew

AU - Haiman, Christopher

AU - Pasaniuc, Bogdan

AU - Henderson, Brian E.

AU - Benlloch, Sara

AU - Schumacher, Fredrick R.

AU - Olama, Ali Amin Al

AU - Muir, Kenneth

AU - Berndt, Sonja I.

AU - Conti, David V.

AU - Wiklund, Fredrik

AU - Chanock, Stephen

AU - Stevens, Victoria L.

AU - Tangen, Catherine M.

AU - Batra, Jyotsna

AU - Clements, Judith

AU - Gronberg, Henrik

AU - Pashayan, Nora

AU - Schleutker, Johanna

AU - Albanes, Demetrius

AU - Weinstein, Stephanie

AU - Wolk, Alicja

AU - West, Catharine

AU - Mucci, Lorelei

AU - Cancel-Tassin, Géraldine

AU - Koutros, Stella

AU - Sorensen, Karina Dalsgaard

AU - Maehle, Lovise

AU - Neal, David E.

AU - Hamdy, Freddie C.

AU - Donovan, Jenny L.

AU - Travis, Ruth C.

AU - Hamilton, Robert J.

AU - Ingles, Sue Ann

AU - Rosenstein, Barry

AU - Lu, Yong Jie

AU - Giles, Graham G.

AU - Kibel, Adam S.

AU - Vega, Ana

AU - Kogevinas, Manolis

AU - Park, Jong Y.

AU - Stanford, Janet L.

AU - Thibodeau, Stephen N

PY - 2018/12/1

Y1 - 2018/12/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85054455296&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85054455296&partnerID=8YFLogxK

U2 - 10.1038/s41467-018-06302-1

DO - 10.1038/s41467-018-06302-1

M3 - Article

C2 - 30287866

AN - SCOPUS:85054455296

VL - 9

JO - Nature Communications

JF - Nature Communications

SN - 2041-1723

IS - 1

M1 - 4079

ER -