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Association Between Genetically Proxied Inhibition of HMG-CoA Reductase and Epithelial Ovarian Cancer
Open accessAbstract
Importance: Preclinical and epidemiological studies indicate a potential chemopreventive role of statins in epithelial ovarian cancer risk. Objective: To evaluate the association of genetically proxied inhibition of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase (ie, genetic variants related to lower function of HMG-CoA reductase, target of statins) with epithelial ovarian cancer among the general population and in BRCA1/2 mutation carriers. Design, Setting, and Participants: Single-nucleotide polymorphisms (SNPs) in HMGCR, NPC1L1, and PCSK9 associated with low-density lipoprotein (LDL) cholesterol in a genome-wide association study (GWAS) meta-analysis (N ≤196 475) were used to proxy therapeutic inhibition of HMG-CoA reductase, Niemann-Pick C1-Like 1 (NPC1L1) and proprotein convertase subtilisin/kexin type 9 (PCSK9), respectively. Summary statistics were obtained for these SNPs from a GWAS meta-analysis of case-control analyses of invasive epithelial ovarian cancer in the Ovarian Cancer Association Consortium (OCAC; N = 63 347) and from a GWAS meta-analysis of retrospective cohort analyses of epithelial ovarian cancer among BRCA1/2 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA; N = 31 448). Across the 2 consortia, participants were enrolled between 1973 and 2014 and followed up through 2015. OCAC participants came from 14 countries and CIMBA participants came from 25 countries. SNPs were combined into multi-allelic models and mendelian randomization estimates representing lifelong inhibition of targets were generated using inverse-variance weighted random-effects models. Exposures: Primary exposure was genetically proxied inhibition of HMG-CoA reductase and secondary exposures were genetically proxied inhibition of NPC1L1 and PCSK9 and genetically proxied circulating LDL cholesterol levels. Main Outcomes and Measures: Overall and histotype-specific invasive epithelial ovarian cancer (general population) and epithelial ovarian cancer (BRCA1/2 mutation carriers), measured as ovarian cancer odds (general population) and hazard ratio (BRCA1/2 mutation carriers). Results: The OCAC sample included 22 406 women with invasive epithelial ovarian cancer and 40 941 control individuals and the CIMBA sample included 3887 women with epithelial ovarian cancer and 27 561 control individuals. Median ages for the cohorts ranged from 41.5 to 59.0 years and all participants were of European ancestry. In the primary analysis, genetically proxied HMG-CoA reductase inhibition equivalent to a 1-mmol/L (38.7-mg/dL) reduction in LDL cholesterol was associated with lower odds of epithelial ovarian cancer (odds ratio [OR], 0.60 [95% CI, 0.43-0.83]; P = .002). In BRCA1/2 mutation carriers, genetically proxied HMG-CoA reductase inhibition was associated with lower ovarian cancer risk (hazard ratio, 0.69 [95% CI, 0.51-0.93]; P = .01). In secondary analyses, there were no significant associations of genetically proxied inhibition of NPC1L1 (OR, 0.97 [95% CI, 0.53-1.75]; P = .91), PCSK9 (OR, 0.98 [95% CI, 0.85-1.13]; P = .80), or circulating LDL cholesterol (OR, 0.98 [95% CI, 0.91-1.05]; P = .55) with epithelial ovarian cancer. Conclusions and Relevance: Genetically proxied inhibition of HMG-CoA reductase was significantly associated with lower odds of epithelial ovarian cancer. However, these findings do not indicate risk reduction from medications that inhibit HMG-CoA reductase; further research is needed to understand whether there is a similar association with such medications.
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Citations
Cites
Measuring inconsistency in meta-analyses
Higgins, J. P. T., Thompson, S. G., Deeks, J. J., & Altman, D. G. (2003) · BMJ · doi:10.1136/bmj.327.7414.557 · Cited by 63,139
Bowden, J., Davey Smith, G., & Burgess, S. (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyv080 · Cited by 9,816
Bowden, J., Davey Smith, G., Haycock, P. C., & Burgess, S. (2016) · Genetic Epidemiology · doi:10.1002/gepi.21965 · Cited by 8,922
Genetic studies of body mass index yield new insights for obesity biology
Study, T. L. C., Locke, A. E., The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The, G. L. G. C., The, I. C. B. P., The MAGIC Investigators, The MuTHER Consortium, et al. (2015) · Nature · doi:10.1038/nature14177 · Cited by 4,534
Avoiding bias from weak instruments in Mendelian randomization studies
Burgess, S., Thompson, S. G., & CRP CHD Genetics Collaboration (2011) · International Journal of Epidemiology · doi:10.1093/ije/dyr036 · Cited by 3,952
Ovarian cancer statistics, 2018
Torre, L. A., Trabert, B., DeSantis, C. E., Miller, K. D., Samimi, G., Runowicz, C. D., Gaudet, M. M., Jemal, A., & Siegel, R. L. (2018) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21456 · Cited by 3,492 · cited 1×
“Statistical Analysis Mendelian randomization analysis assumes that the genetic instrument used to proxy a risk factor (1) is associated with the risk factor (“relevance”), (2) does not share a common cause with the outcome (“exchangeability”), and (3) affects the outcome only through the risk factor (“exclusion restri…”
Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption
Hartwig, F. P., Davey Smith, G., & Bowden, J. (2017) · International Journal of Epidemiology · doi:10.1093/ije/dyx102 · Cited by 3,485
Willer (2013) · doi:10.1038/ng.2797 · Cited by 2,983
Risks of Breast, Ovarian, and Contralateral Breast Cancer for BRCA1 and BRCA2 Mutation Carriers
Kuchenbaecker, K. B., Hopper, J. L., Barnes, D. R., Phillips, K.-A., Mooij, T. M., Roos-Blom, M.-J., Jervis, S., van Leeuwen, F. E., Milne, R. L., Andrieu, N., et al. (2017) · JAMA · doi:10.1001/jama.2017.7112 · Cited by 2,954
Burgess, S., & Thompson, S. G. (2015) · American Journal of Epidemiology · doi:10.1093/aje/kwu283 · Cited by 1,605
Brown, M. S., & Goldstein, J. L. (1980) · Journal of Lipid Research · doi:10.1016/s0022-2275(20)42221-7 · Cited by 1,210
Genome-wide meta-analyses identify multiple loci associated with smoking behavior
The Tobacco and Genetics Consortium (2010) · Nature Genetics · doi:10.1038/ng.571 · Cited by 1,098
Lin, J. S., Bowles, E. J. A., Williams, S. B., & Morrison, C. C. (2017) · JAMA · doi:10.1001/jama.2017.0562 · Cited by 1,082
Burgess, S., Dudbridge, F., & Thompson, S. G. (2015) · American Journal of Epidemiology · doi:10.1093/aje/kwv017 · Cited by 930
Colocalization of GWAS and eQTL Signals Detects Target Genes
Hormozdiari, F., van de Bunt, M., Segrè, A. V., Li, X., Joo, J. W. J., Bilow, M., Sul, J. H., Sankararaman, S., Pasaniuc, B., & Eskin, E. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.10.003 · Cited by 697
Parker, W. H., Broder, M. S., Chang, E., Feskanich, D., Farquhar, C., Liu, Z., Shoupe, D., Berek, J. S., Hankinson, S., & Manson, J. E. (2009) · Obstetrics & Gynecology · doi:10.1097/aog.0b013e3181a11c64 · Cited by 640
Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche
Study, A. O. C., Perry, J. R. B., The GENICA Network, kConFab, Study, T. L. C., The InterAct Consortium, Early Growth Genetics (EGG) Consortium, Day, F., Elks, C. E., Sulem, P., et al. (2014) · Nature · doi:10.1038/nature13545 · Cited by 604
Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer
Phelan, C. M., Kuchenbaecker, K. B., Tyrer, J. P., Kar, S., Lawrenson, K., Winham, S. J., Dennis, J., Pirie, A., Riggan, M. J., Chornokur, G., et al. (2017) · Nature Genetics · doi:10.1038/ng.3826 · Cited by 489
Parker, W. H., Feskanich, D., Broder, M. S., Chang, E., Shoupe, D., Farquhar, C. M., Berek, J. S., & Manson, J. E. (2013) · Obstetrics & Gynecology · doi:10.1097/aog.0b013e3182864350 · Cited by 454
The PRACTICAL Consortium, Day, F. R., kConFab Investigators, AOCS Investigators, Scotland, G., EPIC-InterAct Consortium, Study, L. C., Ruth, K. S., Thompson, D. J., Lunetta, K. L., et al. (2015) · Nature Genetics · doi:10.1038/ng.3412 · Cited by 402
Henderson, J. T., Webber, E. M., & Sawaya, G. F. (2018) · JAMA · doi:10.1001/jama.2017.21421 · Cited by 348
Statin use and cancer risk: a comprehensive review
Boudreau, D. M., Yu, O., & Johnson, J. (2010) · Expert Opinion on Drug Safety · doi:10.1517/14740331003662620 · Cited by 279 · cited 1×
“Statistical Analysis Mendelian randomization analysis assumes that the genetic instrument used to proxy a risk factor (1) is associated with the risk factor (“relevance”), (2) does not share a common cause with the outcome (“exchangeability”), and (3) affects the outcome only through the risk factor (“exclusion restri…”
Ovarian carcinoma pathology and genetics: recent advances
Gilks, C. B., & Prat, J. (2009) · Human Pathology · doi:10.1016/j.humpath.2009.04.017 · Cited by 250
Burgess, S., Zuber, V., Valdés‐Márquez, E., Sun, B. B., & Hopewell, J. C. (2017) · Genetic Epidemiology · doi:10.1002/gepi.22077 · Cited by 196
Causal Inference in Cancer Epidemiology: What Is the Role of Mendelian Randomization?
Yarmolinsky, J., Wade, K. H., Richmond, R. C., Langdon, R., Bull, C. J., Tilling, K. M., Relton, C. L., Lewis, S. J., Smith, G. D., & Martin, R. M. (2018) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-17-1177 · Cited by 189
Self-citationMartirosyan, A., Clendening, J. W., Goard, C. A., & Penn, L. Z. (2010) · BMC Cancer · doi:10.1186/1471-2407-10-103 · Cited by 160
Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche.
Perry, J. R. B., Day, F. R., Elks, C. E., Sulem, P., Thompson, D. J., Ferreira, T. C., He, C., Chasman, D. I., Esko, T., Þorleifsson, G., et al. (2014) · White Rose Research Online (University of Leeds, The University of Sheffield, University of York) · doi:10.17863/cam.17982 · Cited by 158
Self-citationDo the cholesterol-lowering properties of statins affect cancer risk?
Solomon, K. R., & Freeman, M. R. (2008) · Trends in Endocrinology and Metabolism · doi:10.1016/j.tem.2007.12.004 · Cited by 124
Rusk, N. (2018) · Nature Methods · doi:10.1038/s41592-018-0245-2 · Cited by 124
Liu, Y., Qin, A., Li, T., Qin, X. Y., & Li, S. (2014) · Gynecologic Oncology · doi:10.1016/j.ygyno.2014.04.007 · Cited by 66
Kobayashi, Y., Kashima, H., Wu, R., Jung, J.-G., Kuan, J.-C., Gu, J., Xuan, J., Sokoll, L. J., Visvanathan, K., Shih, I., et al. (2015) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-14-3368 · Cited by 64
Ose, J., Poole, E. M., Schöck, H., Lehtinen, M., Arslan, A. A., Zeleniuch‐Jacquotte, A., Visvanathan, K., Helzlsouer, K. J., Buring, J. E., Lee, I.-M. M., et al. (2017) · Cancer Research · doi:10.1158/0008-5472.can-16-3322 · Cited by 63
Greenaway, J. B., Virtanen, C., Osz, K., Révay, T., Hardy, D. B., Shepherd, T. G., DiMattia, G. E., & Petrik, J. (2016) · Oncotarget · doi:10.18632/oncotarget.10121 · Cited by 51
Statin therapy and association with ovarian cancer risk in the New England Case Control (NEC) study
Akinwunmi, B. O., Vitonis, A. F., Titus, L. J., Terry, K. L., & Cramer, D. W. (2018) · International Journal of Cancer · doi:10.1002/ijc.31758 · Cited by 48
Statin use and risk for ovarian cancer: a Danish nationwide case–control study
Baandrup, L., Dehlendorff, C., Friis, S., Olsen, J. H., & Kjær, S. K. (2014) · British Journal of Cancer · doi:10.1038/bjc.2014.574 · Cited by 45
Ovarian Cancer Prevention in High-risk Women
Temkin, S. M., Bergstrom, J., Samimi, G., & Minasian, L. M. (2017) · Clinical Obstetrics & Gynecology · doi:10.1097/grf.0000000000000318 · Cited by 39
Differences between hereditary and sporadic ovarian cancer
Zweemer, R. P., Verheijen, R. H. M., Menko, F. H., Gille, J. J. P., van Diest, P. J., Coebergh, J. W. W., Shaw, P. A., Jacobs, I. J., & Kenemans, P. (1999) · European Journal of Obstetrics & Gynecology and Reproductive Biology · doi:10.1016/s0301-2115(98)00218-8 · Cited by 18
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Webb, P. M., & Jordan, S. J. (2024) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-024-00881-3 · Cited by 623
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Holmes, M. V., Richardson, T. G., Ference, B. A., Davies, N. M., & Davey Smith, G. (2021) · Nature Reviews Cardiology · doi:10.1038/s41569-020-00493-1 · Cited by 184
Self-citationInfluence of cholesterol on cancer progression and therapy
Mayengbam, S. S., Singh, A., Pillai, A. D., & Bhat, M. K. (2021) · Translational Oncology · doi:10.1016/j.tranon.2021.101043 · Cited by 155
Li, Z., Zhang, B., Liu, Q., Tao, Z., Ding, L., Guo, B., Zhang, E., Zhang, H., Meng, Z., Guo, S., et al. (2023) · EBioMedicine · doi:10.1016/j.ebiom.2023.104543 · Cited by 136
Lipid metabolism in pancreatic cancer: emerging roles and potential targets
Yin, X., Xu, R., Song, J., Ruze, R., Chen, Y., Wang, C., & Xu, Q. (2022) · 癌症:英文版 · doi:10.1002/cac2.12360 · Cited by 134
Metadata
- Authors
- Yarmolinsky, J., Bull, C. J., Vincent, E. E., Robinson, J., Walther, A., Smith, G. D., Lewis, S. J., Relton, C. L., & Martin, R. M.
- Affiliations
- University of Bristol (GB)
- University Hospitals Bristol NHS Foundation Trust (GB)
- Corresponding author
- Martin, Richard M.
- ORCID
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2020-02-18
- Volume
- 323
- Issue
- 7
- Pages
- 646
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- PMC
- PMC7042851
- OpenAlex
- W3008748669
- Cited by
- 124
- References
- 41
- Citations by year
- 2026: 7 · 2025: 14 · 2024: 24 · 2023: 21 · 2022: 22 · 2021: 24 · 2020: 12
- FWCI
- 7.18
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- public-domain
- Locations
- JAMA (publishedVersion, public-domain)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Explore Bristol Research (publishedVersion, other-oa)
- Funders
- Cancer Research UK (29019, S_3332, 19169)
- Medical Research Council (MC_UU_00011/1)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer, Lipids, and Metabolism
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › BRCA gene mutations in cancer
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipoproteins and Cardiovascular Health
- Keywords
- epithelial ovarian cancer, HMG-CoA reductase inhibition, statins, chemoprevention, NPC1L1, PCSK9, LDL cholesterol, BRCA1 mutation carriers, BRCA2 mutation carriers, genetic variants, Mendelian randomization, cancer risk, lipid-lowering drugs, Ovarian Cancer Association Consortium
- MeSH terms
- Proprotein Convertase 9, Carcinoma, Ovarian Epithelial, Adult, Female, Humans, Hydroxymethylglutaryl CoA Reductases, Cholesterol, LDL, Middle Aged, Mutation, Ovarian Neoplasms, Retrospective Studies, Risk, Odds Ratio, Case-Control Studies, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Genes, BRCA1, Polymorphism, Single Nucleotide, Genes, BRCA2, Membrane Transport Proteins, Mendelian Randomization Analysis
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