Predicting the effect of statins on cancer risk using genetic variants from a Mendelian randomization study in the UK Biobank

Abstract

Laboratory studies have suggested oncogenic roles of lipids, as well as anticarcinogenic effects of statins. Here we assess the potential effect of statin therapy on cancer risk using evidence from human genetics. We obtained associations of lipid-related genetic variants with the risk of overall and 22 site-specific cancers for 367,703 individuals in the UK Biobank. In total, 75,037 individuals had a cancer event. Variants in the HMGCR gene region, which represent proxies for statin treatment, were associated with overall cancer risk (odds ratio [OR] per one standard deviation decrease in low-density lipoprotein [LDL] cholesterol 0.76, 95% confidence interval [CI] 0.65–0.88, p=0.0003) but variants in gene regions representing alternative lipid-lowering treatment targets (PCSK9, LDLR, NPC1L1, APOC3, LPL) were not. Genetically predicted LDL-cholesterol was not associated with overall cancer risk (OR per standard deviation increase 1.01, 95% CI 0.98–1.05, p=0.50). Our results predict that statins reduce cancer risk but other lipid-lowering treatments do not. This suggests that statins reduce cancer risk through a cholesterol independent pathway.

Publication DOI: https://doi.org/10.7554/elife.57191
Divisions: College of Health & Life Sciences > Aston Medical School
Additional Information: Copyright Carter et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
Uncontrolled Keywords: General Biochemistry, Genetics and Molecular Biology,General Immunology and Microbiology,General Neuroscience,General Medicine,General Immunology and Microbiology,General Biochemistry,Genetics and Molecular Biology,General Neuroscience
Publication ISSN: 2050-084X
Last Modified: 11 Nov 2024 08:29
Date Deposited: 26 Oct 2020 11:03
Full Text Link:
Related URLs: https://elifesc ... /articles/57191 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2020-10-13
Accepted Date: 2020-09-23
Authors: Carter, Paul
Vithayathil, Mathew
Kar, Siddhartha
Potluri, Rahul
Mason, Amy M
Larsson, Susanna C
Burgess, Stephen

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