The relationship between circulating lipids and breast cancer risk
Kelsey E. Johnson , Katherine M. Siewert , Derek Klarin, Scott M. Damrauer, Kyong-Mi Chang, Philip S. Tsao, Themistocles L. Assimes, Kara N. Maxwell, Benjamin F. Voight
Abstract
Background
Numerous epidemiological and genetic studies have investigated the potential link between circulating lipid levels and the risk of various cancers, including breast cancer (BC). However, it remains uncertain whether there is a causal relationship between lipids and BC. If altering lipid levels could also reduce the risk of BC, it would present a potential target for disease prevention. This study aimed to assess the potential causal relationship between genetic variants associated with plasma lipid traits (high-density lipoprotein, HDL; low-density lipoprotein, LDL; triglycerides, TGs) and BC risk using Mendelian randomization (MR).
Introduction
Breast cancer (BC) is the second leading cause of death among women, highlighting the need for a better understanding of its causes and more effective treatments. Cholesterol is a known risk factor for several diseases that have been associated with BC, such as obesity, heart disease, and diabetes. However, it remains unknown whether cholesterol plays a causal role in BC susceptibility.
Methods
Study populations
The study obtained lipid genome-wide association study (GWAS) summary statistics from the Million Veteran Program (MVP) (including up to 215,551 European individuals) and the Global Lipids Genetics Consortium (GLGC) (including up to 188,577 genotyped individuals). As additional exposures in multivariable MR analyses, the study used body mass index (BMI) summary statistics from a meta-analysis of GWAS in up to 795,640 individuals and age at menarche summary statistics from a meta-analysis of GWAS in up to 329,345 women of European ancestry. BC GWAS summary statistics from 122,977 cases and 105,974 controls were obtained from the Breast Cancer Association Consortium (BCAC). Ethical approval and consent protocols were followed for each respective cohort.
Discussion
Using Mendelian randomization, this study provides evidence suggesting that genetically elevated HDL and LDL levels are associated with an increased risk of BC, supporting a causal hypothesis. Previous meta-analyses of observational studies on BC risk and lipids have reported mixed results, with negative associations with HDL and no clear relationship with LDL. Individual studies have reported either a positive relationship with HDL or no relationship with HDL or LDL. The use of Mendelian randomization helps clarify these inconsistent findings and allows for the inference of a direction of effect, which is challenging in observational studies due to potential reverse causation. Additionally, the study identifies genetic correlations between certain lipid traits and BC at the genome-wide level, as well as local genetic correlation at the ABO locus. While some studies have found an association between blood group and BC risk, haplotype patterns suggest that ABO gene expression, rather than blood group itself, may be the causal mechanism. However, due to the pleiotropic nature of the ABO locus, it remains unclear whether the association between BC and ABO is mediated by the lipid associations.
Citation: Johnson KE, Siewert KM, Klarin D, Damrauer SM, the VA Million Veteran Program, Chang K-M, et al. (2020) The relationship between circulating lipids and breast cancer risk: A Mendelian randomization study. PLoS Med 17(9): e1003302. https://doi.org/10.1371/journal.pmed.1003302
Academic Editor: Cosetta Minelli, Imperial College London, UNITED KINGDOM
Received: October 18, 2019; Accepted: August 10, 2020; Published: September 11, 2020
This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
Data Availability: The summary statistics for the MR instrumental variables are available in S1, S2 and S3 Tables. Genome-wide summary statistics are available from the Global Lipids Genetics Consortium (GLGC) at http://csg.sph.umich.edu/abecasis/public/lipids2013/ and the Breast Cancer Association Consortium (BCAC) at http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/oncoarray-and-combined-summary-result/gwas-summary-results-breast-cancer-risk-2017/. The Million Veterans Program (MVP) lipid GWAS results are available in dbGAP. The dbGAP accession number for MVP overall is phs001672.v3.p1. The accession numbers for the European-specific MVP data are TC: pha004834.1, LDL: pha004831.1, HDL: pha004828.1, and TG: pha004837.1. BMI summary statistics from Yengo et al. are available at https://portals.broadinstitute.org/collaboration/giant/index.php/GIANT_consortium_data_files#2018_GIANT_and_UK_BioBank_Meta-analysis. Age of menarche summary statistics from Day et al are available at https://www.reprogen.org/data_download.html. The UK10K data utilized in the study cannot be shared publicly (per data use access agreement) but are available by Institutional Data Access request for researchers who meet the criteria for access at https://www.sanger.ac.uk/legal/DAA/MasterController.
Funding: This work was supported by the US National Institutes of Health (R01 DK101478 and HG010067 for BFV, T32 GM008216 for KEJ, T32 HG000046 for KMS) and a Linda Pechenik Montague Investigator award (to BFV). This research is based on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration and was supported by award #MVP000. This research was also supported by two additional Department of Veterans Affairs awards (I01-BX003362 [PST/KC], IK2-CX001780 [Damrauer]). This publication does not represent the views of the Department of Veterans Affairs or the United States Government. This study makes use of data generated by the UK10K Consortium, derived from samples from the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Department of Twin Research and Genetic Epidemiology (DTR), the TWINSUK Cohort. A full list of the investigators who contributed to the generation of the data is available from www.UK10K.org. Funding for UK10K was provided by the Wellcome Trust under award WT091310. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: SMD declares research support to institution from Renalytix AI and a patent application filed by VA on drug repurposing for lipid reduction.
Abbreviations: ABCA1, ATP Binding Cassette Subfamily A Member 1; APOC, Apolipoprotein C1; APOE, Apolipoprotein E; BC, breast cancer; BCAC, Breast Cancer Association Consortium; BMI, body mass index; CETP, Cholesteryl Ester Transfer Protein; CI, confidence interval; ER, estrogen receptor; GLGC, Global Lipids Genetics Consortium; GWAS, genome-wide association study; HDL, high-density lipoprotein; HMGCR, 3-Hydroxy-3-Methylglutaryl-CoA Reductase; LCAT, Lecithin-Cholesterol Acyltransferase; LD, linkage disequilibrium; LDL, low-density lipoprotein; LDLR, LDL Receptor; LIPC, Lipase C, Hepatic Type; LIPG, Lipase G, Endothelial Type; LPA, Lipoprotein(A); MR, Mendelian randomization; MVP, Million Veteran Program; MYLIP, Myosin Regulatory Light Chain Interacting Protein; NPC1L1, NPC1-Like Intracellular Cholesterol Transporter 1; OR, odds ratio; PCSK9, Proprotein Convertase Subtilisin/Kexin Type 9; PLTP, Phospholipid Transfer Protein; SCARB1, Scavenger Receptor Class B Member 1; STROBE, Strengthening the Reporting of Observational Studies in Epidemiology; TC, total cholesterol; TG, triglyceride
