In:
Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 32, No. 9 ( 2023-09-01), p. 1198-1207
Abstract:
Predicting protein levels from genotypes for proteome-wide association studies (PWAS) may provide insight into the mechanisms underlying cancer susceptibility. Methods: We performed PWAS of breast, endometrial, ovarian, and prostate cancers and their subtypes in several large European-ancestry discovery consortia (effective sample size: 237,483 cases/317,006 controls) and tested the results for replication in an independent European-ancestry GWAS (31,969 cases/410,350 controls). We performed PWAS using the cancer GWAS summary statistics and two sets of plasma protein prediction models, followed by colocalization analysis. Results: Using Atherosclerosis Risk in Communities (ARIC) models, we identified 93 protein–cancer associations [false discovery rate (FDR) & lt; 0.05]. We then performed a meta-analysis of the discovery and replication PWAS, resulting in 61 significant protein–cancer associations (FDR & lt; 0.05). Ten of 15 protein–cancer pairs that could be tested using Trans-Omics for Precision Medicine (TOPMed) protein prediction models replicated with the same directions of effect in both cancer GWAS (P & lt; 0.05). To further support our results, we applied Bayesian colocalization analysis and found colocalized SNPs for SERPINA3 protein levels and prostate cancer (posterior probability, PP = 0.65) and SNUPN protein levels and breast cancer (PP = 0.62). Conclusions: We used PWAS to identify potential biomarkers of hormone-related cancer risk. SNPs in SERPINA3 and SNUPN did not reach genome-wide significance for cancer in the original GWAS, highlighting the power of PWAS for novel locus discovery, with the added advantage of providing directions of protein effect. Impact: PWAS and colocalization are promising methods to identify potential molecular mechanisms underlying complex traits.
Type of Medium:
Online Resource
ISSN:
1055-9965
,
1538-7755
DOI:
10.1158/1055-9965.EPI-23-0309
Language:
English
Publisher:
American Association for Cancer Research (AACR)
Publication Date:
2023
detail.hit.zdb_id:
2036781-8
detail.hit.zdb_id:
1153420-5
