Background Genome-wide association studies (GWAS) have identified many common variants associated at low effect sizes with various cancers. Summing the effects of these variants into polygenic risk scores (PRS) can improve cancer risk prediction. However, these PRS have largely been analyzed in cohorts restricted to individuals of European descent, and research into potential cross-cancer and cross-phenotype pleiotropic associations of cancer-specific PRS is limited.

Methods Using logistic regression models, we tested the association of 13 cancer-specific PRS (bladder, colorectal, esophageal, glioma, lung, melanoma, oral cavity, pancreatic, renal, thyroid, breast, prostate, and testicular) with curated phenotypes representing the same 13 cancers and 340 cancer and cardiometabolic phecodes in 560,287 individuals (114,255 African ancestry, AFR and 446,032 European ancestry, EUR) from the Million Veteran Program (MVP), a large, ancestrally-diverse biobank. Logistic regression models were stratified by ancestry and used age, principal components, and cancer-specific PRS as independent variables.

Results All 13 cancer-specific PRS were significantly associated (p<0.002) with their respective cancers among EUR individuals (OR 1.05 to 1.70). Among AFR individuals, cancer-specific PRS were significantly associated with their respective cancers for five of 13 cancers (bladder, breast in females, colorectal, prostate, and thyroid, OR 1.19 to 1.48). In cancer-cancer pleiotropy studies, only the renal cancer-specific PRS was significantly associated with skin cancer (OR=1.04, P=4.5×10−06) among EUR individuals. PheWAS demonstrated five positive pleotropic associations with cardiometabolic conditions (thyroid cancer PRS with thyroid goiter, oral cancer PRS with type 1 diabetes, ophthalmic and renal diabetic complications, and hypothyroidism) and two negative associations (oral and lung cancer PRS separately with coronary artery disease). There were no significant cancer-phecode associations among AFR individuals.

Conclusions We confirm the validity of 13 cancer-specific PRS on predicting their corresponding cancer in MVP, observing stronger associations per cancer among EUR versus AFR individuals. In contrast to PRS of other chronic diseases, our study shows that the majority of cancer-related PRS are highly specific and pleiotropic associations with other cancers and cardiometabolic traits are relatively uncommon.

JAL, CCT, and KMP report grants from Alnylam Pharmaceuticals, Inc., AstraZeneca Pharmaceuticals LP, Biodesix, Inc, Janssen Pharmaceuticals, Inc., Novartis International AG, Parexel International Corporation through the University of Utah or Western Institute for Veteran Research outside the submitted work. The other authors declare no conflicts of interest.

This research is based on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration, and was supported by MVP003/028 as well as award I01-BX003362. The authors acknowledge the support of the MVP Core Team (Supplement). This work was supported using resources and facilities of the Department of Veterans Affairs (VA) Informatics and Computing Infrastructure (VINCI), including data analytics conducted by its Precision Medicine research team, which is funded under the research priority to Put VA Data to Work for Veterans (VA ORD 24-D4V-02). This publication does not reflect views of the Department of Veterans Affairs or the United States government.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

This retrospective cohort study used data analyzed as part of an MVP research study protocol that was approved by the US Department of Veterans Affairs (VA) Central Institutional Review Board. All participants provided written informed consent and Health Insurance Portability and Accountability Act authorization (what we used to submit on med archive).

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It is not possible for the authors to directly share the individual-level data that were obtained from the MVP due to constraints stipulated in the informed consent. Anyone wishing to gain access to this data should inquire directly to MVP at MVPLOIva.gov. The data generated from our analyses are included in the manuscript main text, tables, and figures and online Supplementary Materials (available online). The summary data for MVP are available through dbGAP, accession number phs001672.