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.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
All CETP inhibitors show modest SBP increasing effects, and this appears to be most pronounced for torcetrapib.
“while all CETP inhibitors show modest SBP increasing effects, this appears to be most pronounced for torcetrapib 78 74 .”
From Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development (2021) · cites this paper as [74]
CETP inhibitors were primarily developed on the basis that they increased HDL-C rather than for any effect on cholesterol in apolipoprotein B containing lipoproteins.
“CETP inhibitors that were primarily developed on the basis that they increased HDL-C (rather than for any effect on cholesterol in apolipoprotein B containing lipoproteins) 74 .”
From Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development (2021) · cites this paper as [74]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
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 · see citing works
Bowden, J., Davey Smith, G., & Burgess, S. (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyv080 · Cited by 9,816 · see citing works
Bowden, J., Davey Smith, G., Haycock, P. C., & Burgess, S. (2016) · Genetic Epidemiology · doi:10.1002/gepi.21965 · Cited by 8,922 · see citing works
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 · see citing works
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 · see citing works
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× · see citing works
“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 · see citing works
Willer (2013) · doi:10.1038/ng.2797 · Cited by 2,983 · see citing works
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 · see citing works
Burgess, S., & Thompson, S. G. (2015) · American Journal of Epidemiology · doi:10.1093/aje/kwu283 · Cited by 1,605 · see citing works
Brown, M. S., & Goldstein, J. L. (1980) · Journal of Lipid Research · doi:10.1016/s0022-2275(20)42221-7 · Cited by 1,210 · see citing works
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 · see citing works
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 · see citing works
Burgess, S., Dudbridge, F., & Thompson, S. G. (2015) · American Journal of Epidemiology · doi:10.1093/aje/kwv017 · Cited by 945 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
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 503 · see citing works
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 · see citing works
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 · see citing works
Henderson, J. T., Webber, E. M., & Sawaya, G. F. (2018) · JAMA · doi:10.1001/jama.2017.21421 · Cited by 348 · see citing works
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 274 · cited 1× · see citing works
“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 · see citing works
Burgess, S., Zuber, V., Valdés‐Márquez, E., Sun, B. B., & Hopewell, J. C. (2017) · Genetic Epidemiology · doi:10.1002/gepi.22077 · Cited by 204 · see citing works
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 186 · see citing works
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 · see citing works
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 · see citing works
Self-citationRusk, N. (2018) · Nature Methods · doi:10.1038/s41592-018-0245-2 · Cited by 124 · see citing works
Do 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 122 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
Flagged first, then by citations
4 of the 41 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Global epidemiology of epithelial ovarian cancer
Webb, P. M., & Jordan, S. J. (2024) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-024-00881-3 · Cited by 623 · see citing works
“The observation that genetic proxies of HMG-CoA reductase inhibition are also associated with ovarian cancer risk 89 supports a genuine association, although the same study also revealed no association with genetic proxies of LDL-cholesterol, suggesting that any effect of statins on ovarian cancer…”
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 · see citing works
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 · see citing works
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 137 · see citing works
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 132 · see citing works
Involvement of LDL and ox-LDL in Cancer Development and Its Therapeutical Potential
Deng, C., Zhu, N., Zhao, T., Li, H., Gu, J., Liao, D., & Li, Q. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.803473 · Cited by 113 · see citing works
“In the Mendelian randomization analysis of 22,406 patients with invasive epithelial ovarian cancer, no association was found between the genetic variation that controls circulating LDL-C and the risk of epithelial ovarian cancer (165).”
BackgroundPCSK9 and cancer: Rethinking the link
Mahboobnia, K., Pirro, M., Marini, E., Grignani, F., Bezsonov, E. E., Jamialahmadi, T., & Sahebkar, A. (2021) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2021.111758 · Cited by 107 · see citing works
Systematic review of Mendelian randomization studies on risk of cancer
Markozannes, G., Kanellopoulou, A., Dimopoulou, O., Kosmidis, D., Zhang, X., Wang, L., Τheodoratou, E., Gill, D., Burgess, S., & Tsilidis, K. K. (2022) · BMC Medicine · doi:10.1186/s12916-022-02246-y · Cited by 89 · see citing works
“The 10 robust associations from the lipid metabolism biomarkers category pertained to high-density lipoprotein cholesterol (HDL-C) with increased risk of breast (total, ER+, ER−) [279] but decreased risk of overall cancer [197]; triglycerides (TGL) with decreased risk of breast [207]; lowdensity lipoprotein cholestero…”
BackgroundTargeting the mevalonate pathway suppresses ARID1A-inactivated cancers by promoting pyroptosis
Zhou, W., Liu, H., Yuan, Z., Zundell, J. A., Towers, M., Lin, J., Lombardi, S., Nie, H., Murphy, B., Yang, T., et al. (2023) · Cancer Cell · doi:10.1016/j.ccell.2023.03.002 · Cited by 94 · see citing works
LDL, HDL and endocrine-related cancer: From pathogenic mechanisms to therapies
Revilla, G., Cedó, L., Tondo, M., Moral, A., Pérez, J. I., Corcoy, R., Lerma, E., Fusté, V., Reddy, S. T., Blanco‐Vaca, F., et al. (2020) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2020.11.012 · Cited by 81 · see citing works
Effects of statins on brain tumors: a review
Afshari, A. R., Mollazadeh, H., Henney, N. C., Jamialahmadi, T., & Sahebkar, A. (2020) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2020.08.002 · Cited by 78 · see citing works
Proprotein convertase subtilisin/kexin type 9 (PCSK9): A potential multifaceted player in cancer
Bhattacharya, A., Chowdhury, A., Chaudhury, K., & Shukla, P. C. (2021) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/j.bbcan.2021.188581 · Cited by 67 · see citing works
Cardio-Oncology: A Myriad of Relationships Between Cardiovascular Disease and Cancer
Wang, Y., Wang, Y., Han, X., Sun, J. H., Li, C., Adhikari, B. K., Zhang, J., Miao, X., & Chen, Z. (2022) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2022.727487 · Cited by 62 · see citing works
Cholesterol homeostasis and cancer: a new perspective on the low-density lipoprotein receptor
Gu, J., Zhu, N., Li, H., Zhao, T., Zhang, C., Liao, D.-F., & Li, Q. (2022) · Cellular Oncology · doi:10.1007/s13402-022-00694-5 · Cited by 57 · see citing works
Fang, S., Yarmolinsky, J., Gill, D., Bull, C. J., Perks, C. M., the PRACTICAL Consortium, Davey Smith, G., Gaunt, T. R., & Richardson, T. G. (2023) · PLOS Medicine · doi:10.1371/journal.pmed.1003988 · Cited by 55 · see citing works
“This approach has also been applied to suggest that statins may provide additional benefit towards the lowering of ovarian cancer risk [23], as well as a recent study by Sun and colleagues that investigated evidence of association between genetically proxied lipid-lowering drugs with breast and prostate cancer [12].”
BackgroundSelf-citationCholesterol: An important actor on the cancer immune scene
Halimi, H., & Farjadian, S. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.1057546 · Cited by 56 · see citing works
“Other research documented the importance of HMGCoA reductase in ovarian cancer, finding that genetically proxied inhibition of HMG-CoA reductase was related to a lower rate of ovarian cancer (107).”
BackgroundStatin use and survival following a diagnosis of ovarian cancer: A prospective observational study
Majidi, A., Na, R.-H., Jordan, S., Defazio, A., & Webb, P. (2020) · International Journal of Cancer · doi:10.1002/ijc.33333 · Cited by 38 · see citing works
Cholesterol Metabolism in Cancer and Cell Death
Chen, F., Lu, Y., Lin, J., Kang, R., & Liu, J. (2023) · Antioxidants and Redox Signaling · doi:10.1089/ars.2023.0340 · Cited by 50 · see citing works
Enzymes in the Cholesterol Synthesis Pathway: Interactomics in the Cancer Context
Ershov, P., Kaluzhskiy, L. A., Mezentsev, Y. V., Yablokov, E. O., Gnedenko, O. V., & Ivanov, A. S. (2021) · Biomedicines · doi:10.3390/biomedicines9080895 · Cited by 47 · see citing works
Common medications and survival in women with ovarian cancer: A systematic review and meta-analysis
Majidi, A., Na, R., Dixon‐Suen, S. C., Jordan, S. J., & Webb, P. M. (2020) · Gynecologic Oncology · doi:10.1016/j.ygyno.2020.03.028 · Cited by 45 · see citing works
Luo, S., Schooling, C. M., Wong, I. C. K., & Yeung, S. L. A. (2020) · Diabetologia · doi:10.1007/s00125-020-05243-z · Cited by 44 · see citing works
Sun, L., Ding, H., Jia, Y., Shi, M., Guo, D., Yang, P., Wang, Y., Liu, F., Zhang, Y., & Zhu, Z. (2022) · Breast Cancer Research · doi:10.1186/s13058-022-01508-0 · Cited by 43 · see citing works
“Recently, genetically proxied inhibition of HMG-CoA reductase but not NPC1L1 and PCSK9 was associated with lower odds of epithelial ovarian cancer in MR study, while no such MR study was currently available for breast cancer and prostate cancer [27].”
BackgroundMethodAssociation between abnormal lipid metabolism and tumor
Li, C., Wang, F., Cui, L., Li, S., Zhao, J., & Liao, L. (2023) · Frontiers in Endocrinology · doi:10.3389/fendo.2023.1134154 · Cited by 42 · see citing works
“Some studies have found that the inhibition of HMGCR is significantly related to the reduction of incidence rate of epithelial ovarian cancer (8).”
BackgroundMarkowska, A., Antoszczak, M., Markowska, J., & Huczyński, A. (2020) · Pharmaceuticals · doi:10.3390/ph13120422 · Cited by 42 · see citing works
“The differences in the incidence of OC associated with the use of statins are partly explained by genetic studies on the inhibition of HMG-CoA reductase, which is affected by statins which lower the synthesis of endogenous cholesterol [72].”
BackgroundReview of Mendelian Randomization Studies on Ovarian Cancer
Guo, J.-Z., Xiao, Q., Gao, S., Li, X., Wu, Q., & Gong, T. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.681396 · Cited by 44 · see citing works
“Similarly, in BRCA1/2 mutation carriers, genetically proxied HMG-CoA reductase inhibition was associated with lower OC risk (36).”
BackgroundSmoking is significantly associated with increased risk of COVID-19 and other respiratory infections
Rosoff, D. B., Yoo, J., & Lohoff, F. W. (2021) · Communications Biology · doi:10.1038/s42003-021-02685-y · Cited by 45 · see citing works
Wang, X., Li, Y., Hou, X., Li, J., & Ma, X. (2024) · Cell Communication and Signaling · doi:10.1186/s12964-024-01792-7 · Cited by 38 · see citing works
“Besides, genetic alternation-induced HMGCR inactivation indicated reduced risk of ovarian cancer and breast cancer [93, 94], which lays a theoretic basis for the reuse of statins in anti-tumor treatment.”
BackgroundCarter, P., Vithayathil, M. K., Kar, S., Potluri, R., Mason, A. M., Larsson, S. C., & Burgess, S. (2020) · eLife · doi:10.7554/elife.57191 · Cited by 38 · see citing works
Nakae, A., Kodama, M., Okamoto, T., Tokunaga, M., Shimura, H., Hashimoto, K., Sawada, K., Kodama, T., Copeland, N. G., Jenkins, N. A., et al. (2021) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2021.03.049 · Cited by 35 · see citing works
Low‐density lipoprotein cholesterol and lifespan: A Mendelian randomization study
Daghlas, I., & Gill, D. (2021) · British Journal of Clinical Pharmacology · doi:10.1111/bcp.14811 · Cited by 34 · see citing works
“encoding drug targets for LDL-c lowering therapies, we selected variants previously identified as genetic proxies for modulation of HMGCR (targeted by statins), NPC1L1 (targeted by ezetimibe) and PCSK9 (targeted by PCSK9 inhibitors).(29) For these single gene analyses, we considered variants with a genome-wide signifi…”
BackgroundJoharatnam‐Hogan, N., Alexandre, L., Yarmolinsky, J., Lake, B., Capps, N. E., Martin, R. M., Ring, A. E., Cafferty, F. H., & Langley, R. E. (2021) · Current Oncology Reports · doi:10.1007/s11912-021-01023-z · Cited by 34 · see citing works
Self-citationCrosstalk between Statins and Cancer Prevention and Therapy: An Update
Grabarek, B. O., Boroń, D., Morawiec, E., Michalski, P., Palazzo-Michalska, V., Pach, Ł., Dziuk, B., Świder, M., & Zmarzły, N. (2021) · Pharmaceuticals · doi:10.3390/ph14121220 · Cited by 34 · see citing works
“Yarmolinsky, JAMA [120] (2020) n = 25,509 ovarian n = 3887 BRCA 1/2 OR 0.”
Coming Back to Physiology: Extra Hepatic Functions of Proprotein Convertase Subtilisin/Kexin Type 9
Schlüter, K., Wolf, A., & Schreckenberg, R. (2020) · Frontiers in Physiology · doi:10.3389/fphys.2020.598649 · Cited by 32 · see citing works
Genetically predicted circulating protein biomarkers and ovarian cancer risk
Considine, D., Jia, G., Shu, X., Schildkraut, J. M., Pharoah, P. D. P., Zheng, W., & Kar, S. (2020) · Gynecologic Oncology · doi:10.1016/j.ygyno.2020.11.016 · Cited by 29 · see citing works
Badr-Eldin, S. M., Alhakamy, N. A., Fahmy, U. A., Ahmed, O. A. A., Asfour, H. Z., Althagafi, A. A., Aldawsari, H. M., Rizg, W. Y., Mahdi, W. A., Alghaith, A. F., et al. (2021) · Frontiers in Pharmacology · doi:10.3389/fphar.2020.642171 · Cited by 29 · see citing works
Gormley, M., Yarmolinsky, J., Dudding, T., Burrows, K., Martin, R. M., Thomas, S. J., Tyrrell, J., Brennan, P., Pring, M., Boccia, S., et al. (2021) · PLoS Genetics · doi:10.1371/journal.pgen.1009525 · Cited by 30 · see citing works
“Nonetheless, recent MR studies [29, 30] have identified an association between variants in HMGCR with cancer risk, but not alternative cholesterol-lowering treatments or genetically-predicted LDL-C, suggesting that statins may reduce cancer risk through a cholesterol independent pathway.”
InfluentialSelf-citationHigh-affinity SOAT1 ligands remodeled cholesterol metabolism program to inhibit tumor growth
Wang, Z., Wang, M., Zhang, M., Xu, K., Zhang, X., Xie, Y., Zhang, Y., Chang, C., Li, X., Sun, A., et al. (2022) · BMC Medicine · doi:10.1186/s12916-022-02436-8 · Cited by 32 · see citing works
“For example, statins exert anticancer effects by inhibiting the activity of the key rate-limiting enzyme 3-hydroxy3-methylglutaryl-coenzyme A reductase (HMGCR) in the cholesterol synthesis signaling pathway [5], and itraconazole directly binds to the sterol-sensitive domain of NPC intracellular cholesterol transporter…”
BackgroundStatins as Repurposed Drugs in Gynecological Cancer: A Review
Wang, K., Liu, C., & Ding, D. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms232213937 · Cited by 27 · see citing works
Gut microbiome: A possible common therapeutic target for treatment of atherosclerosis and cancer
Wu, W., Ivanova, E. A., & Orekhov, A. N. (2020) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2020.06.017 · Cited by 26 · see citing works
Statin use and survival among women with ovarian cancer: an Australian national data-linkage study
Feng, J., Dixon‐Suen, S. C., Jordan, S. J., & Webb, P. M. (2021) · British Journal of Cancer · doi:10.1038/s41416-021-01460-4 · Cited by 25 · see citing works
Profiling the metabolome of uterine fluid for early detection of ovarian cancer
Wang, P., Ma, J., Li, W., Wang, Q., Xiao, Y., Jiang, Y., Gu, X., Wu, Y., Dong, S., Guo, H., et al. (2023) · Cell Reports Medicine · doi:10.1016/j.xcrm.2023.101061 · Cited by 24 · see citing works
“The delayed diagnosis of OC is usually attributed to the occult initiation of tumor formation and the absence of effective early-detection methods.(7,8) Generally, cancer antigen 125 (CA125) and human epididymis protein 4 (HE4) blood tests have been used as methods for OC detection.”
MethodIntroduction to Mendelian randomization
Yeung, S. L. A., Luo, S., Iwagami, M., & Goto, A. (2024) · Annals of Clinical Epidemiology · doi:10.37737/ace.25004 · Cited by 24 · see citing works
The Role of Cholesterol Metabolism and Its Regulation in Tumor Development
Wu, Y., Song, W., Su, M., He, J., Hu, R., & Zhao, Y. (2025) · Cancer Medicine · doi:10.1002/cam4.70783 · Cited by 23 · see citing works
Zhang, R., Zeng, J., Liu, W., Meng, J., Wang, C., Shi, L., Yang, S., Chang, J., & Xing, D. (2022) · Frontiers in Pharmacology · doi:10.3389/fphar.2022.956619 · Cited by 22 · see citing works
“When the analysis was limited to the general population or BRCA1/2 mutation carriers, there was no significant association between genetically close NPC1L1 or PCSK9 inhibition or lowdensity lipoprotein cholesterol levels and epithelial ovarian cancer in the Mendelian randomized analysis of 22,406 women with invasive e…”
BackgroundNounu, A., Greenhough, A., Heesom, K. J., Richmond, R. C., Zheng, J., Weinstein, S. J., Albanes, D., Baron, J. A., Hopper, J. L., Figueiredo, J. C., et al. (2021) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-20-1176 · Cited by 23 · see citing works
Self-citationA phenome-wide association study of genetically mimicked statins
Li, S., & Schooling, C. M. (2021) · BMC Medicine · doi:10.1186/s12916-021-02013-5 · Cited by 20 · see citing works
“Statins, 3-hydroxy-3-methyl-glutaryl coenzyme A reductase (HMGCR) inhibitors, reduce low-density lipoprotein cholesterol (LDL-c) significantly, resulting in a commeasurable reduction in morbidity and mortality from cardiovascular disease (CVD) [1, 2].”
BackgroundMethodInfluentialChen, Y., Huang, M., Xuan, Y., Li, K., Xu, X. P., Wang, L., Sun, Y., Xiao, L., Xu, P., Kong, W., et al. (2021) · Journal of Personalized Medicine · doi:10.3390/jpm11111171 · Cited by 21 · see citing works
Abnormal lipid synthesis as a therapeutic target for cancer stem cells
Wang, S., Hu, Q., Wu, T., Xia, J., Tao, X., & Cheng, B. (2022) · World Journal of Stem Cells · doi:10.4252/wjsc.v14.i2.146 · Cited by 21 · see citing works
Bell, A. S., Rosoff, D. B., Mavromatis, L. A., Jung, J., Wagner, J., & Lohoff, F. W. (2022) · Journal of the American Heart Association · doi:10.1161/jaha.122.026122 · Cited by 18 · see citing works
Lin, Q., Liu, W., Song, X., & Sun, L. (2021) · Archives of Gynecology and Obstetrics · doi:10.1007/s00404-021-06215-3 · Cited by 17 · see citing works
Dai, H., Zheng, L., Zhu, Z., Geng, X., Hou, T., Wang, Q., Zhu, Y., Lin, H., Wang, S., Zheng, R., et al. (2023) · Journal of Bone and Mineral Research · doi:10.1002/jbmr.4880 · Cited by 16 · see citing works
Rosoff, D. B., Bell, A. S., Wagner, J., Mavromatis, L. A., Hamandi, A. M., Park, L. Y., Jung, J., & Lohoff, F. W. (2023) · Cellular and Molecular Gastroenterology and Hepatology · doi:10.1016/j.jcmgh.2023.09.001 · Cited by 15 · see citing works
“61 Therefore, future studies are needed to further assess potential bene fi cial effects of HMGCR inhibition on LFT levels.”
Background(2023) · PubMed Central · Cited by 15 · see citing works
Wu, Y., Wang, C., Guo, Y., Zhang, Y., Zhang, X., Wang, P., Yue, W., Zhu, X., Liu, Z., Zhang, Y., et al. (2025) · Journal of Nanobiotechnology · doi:10.1186/s12951-025-03348-4 · Cited by 14 · see citing works
“Around 90% of OC cases are epithelial ovarian cancer (EOC), one of the most aggressive malignant neoplasms [1], whose 5-year survival rate drops from 92% at the early stage to 29% at the late stage [2–4].”
Chan, W.-C., Liu, L.-L., Bouras, E., Zuber, V., Wen, W., Long, J., Gill, D., Murphy, N., Gunter, M., Assimes, T., et al. (2024) · British Journal of Cancer · doi:10.1038/s41416-024-02900-7 · Cited by 14 · see citing works
Dysregulation of Cholesterol Homeostasis in Ovarian Cancer
Qusairy, Z., Gangloff, A., & Leung, S. O. A. (2023) · Current Oncology · doi:10.3390/curroncol30090609 · Cited by 13 · see citing works
“There is emerging evidence which suggests a significant association between cholesterol levels and cancer [11,15–17].”
BackgroundYe, C., Dou, C., Liu, D., Kong, L., Chen, M., Xu, M., Xu, Y., Li, M., Zhao, Z., Zheng, J., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-64985-9 · Cited by 13 · see citing works
Liu, L., Sheng, C., Lyu, Z., Dai, H., & Chen, K. (2021) · Frontiers in Nutrition · doi:10.3389/fnut.2021.755834 · Cited by 12 · see citing works
“employed this method and identified a reverse relationship between genetically proxied HMGCR inhibitor and ovarian cancer risk (16).”
MethodKang, T., Zhou, Y., Fan, C., Zhang, Y., Yu, Y., & Jiang, J. C. (2024) · The EPMA Journal · doi:10.1007/s13167-024-00373-5 · Cited by 11 · see citing works
“Recently, MR analyses have been widely used to predict the potential effects of drug targets on cardiovascular diseases [32], neurological diseases [33], and neoplasms [34].”
Wang, L., Jiang, F., Sun, J., Zhao, J., He, Y., Gill, D., Burgess, S., Larsson, S. C., Yuan, S., & Li, X. (2025) · International Journal of Epidemiology · doi:10.1093/ije/dyaf020 · Cited by 11 · see citing works
“We also established a genetic score to proxy overall LDL-C levels (not specific to any lipid-lowering drug target) that included 237 independent SNPs ( r 2 0.001) associated with LDL-C levels at genome-wide significance level ( P 5.0 × 10 − 8 ), serving as a positive control [28].”
InfluentialZhang, A., Liu, K., Liang, X., Li, H., Fu, X., Zhu, N., Li, F., & Yang, J. (2023) · Nanomedicine Nanotechnology Biology and Medicine · doi:10.1016/j.nano.2023.102700 · Cited by 10 · see citing works
The Role of Statins in the Prevention of Ovarian and Endometrial Cancers
Zeleznik, O. A., Irvin, S., Samimi, G., & Trabert, B. L. (2023) · Cancer Prevention Research · doi:10.1158/1940-6207.capr-22-0374 · Cited by 9 · see citing works
Pham, K., Mulugeta, A., Lumsden, A. L., & Hyppönen, E. (2023) · British Journal of Clinical Pharmacology · doi:10.1111/bcp.15793 · Cited by 8 · see citing works
“Similarly, an earlier study found evidence to support an association between the HMGCR gene and decreased risk of prostate, breast and ovarian cancers.(44,45) Although our MR-PheWAS of the phecodes did not identify a significant association with any cancers, the biomarker analyses found an association between”
ResultLi, Y., Liu, H., Shen, C., Liu, F., Liu, F., Huang, K., Gu, D., Lu, X., & Lu, X. (2024) · BMC Medicine · doi:10.1186/s12916-024-03407-x · Cited by 9 · see citing works
“…with LDL-C at genome-wide significance level ( P 5.0 × 10 –8 ) and were permitted to be in weak linkage disequilibrium ( r 2 0.20) with each other to increase the proportion of variance in each respective drug target explained by the instruments, maximizing the instrument strength [23].”
BackgroundInfluentialKobayashi, Y., Takeda, T., Kunitomi, H., Chiwaki, F., Komatsu, M., Nagai, S., Nogami, Y., Tsuji, K., Masuda, K., Ogiwara, H., et al. (2022) · Pharmaceuticals · doi:10.3390/ph15020124 · Cited by 8 · see citing works
Cholesterol: The driving force behind the remodeling of tumor microenvironment in colorectal cancer
Wang, K., Zhang, Y., Si, C., Cao, Y., Shao, P., Zhang, P., Wang, N., Su, G., Qian, J., & Liu, Y. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e39425 · Cited by 7 · see citing works
Liu, S., Lin, H. R., Zhang, K., Zhou, Q., & Shen, Y. (2025) · Journal of Ovarian Research · doi:10.1186/s13048-025-01620-7 · Cited by 7 · see citing works
Genetic evidence implicating circulating lipids and lipid drug targets in pterygium
Cai, Y., Fang, F., Zhou, T., Shi, W., Cai, X., & Fu, Y. (2023) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2023.11.002 · Cited by 6 · see citing works
“While drug-target MR analyses have been applied in diverse disease contexts, genomic evidence of potential drug targets for pterygium remains unexplored [26 – 30].”
BackgroundHuang, J., Lin, Z., Lin, J., Xie, S., Xia, S., Chen, G., Zheng, Z., Xu, Z., Liu, F., Wu, H., et al. (2023) · Thorax · doi:10.1136/thorax-2023-220789 · Cited by 6 · see citing works
“15 16 In this study, we aimed to elucidate the causal effect of lipid profiles on PAP using a large observational patient cohort and MR analysis and to identify potential mediating factors and drug targets.”
BackgroundResearch progress of lipid metabolism reprogramming and related drug therapy in ovarian cancer
Li, X., Guo, R., Yang, G., Zhu, L., Liu, R., Xia, L., & Zhang, Q. (2025) · The Journal of Steroid Biochemistry and Molecular Biology · doi:10.1016/j.jsbmb.2025.106816 · Cited by 6 · see citing works
Wei, H., Li, Z., Qian, K., Du, W., Ju, L., Shan, D., Yu, M., Fang, Y., Zhang, Y., Xiao, Y., et al. (2024) · The Pharmacogenomics Journal · doi:10.1038/s41397-024-00346-x · Cited by 6 · see citing works
“The remaining data can be accessed in the article or Supplementary information.”
HMG-Coenzyme A Reductase as a Drug Target for the Prevention of Ankylosing Spondylitis
Zhong, Z., Feng, X., Su, G., Du, L., Liao, W., Liu, S., Li, F., Zuo, X., & Yang, P. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.731072 · Cited by 6 · see citing works
“A similar approach had been used previously (Yarmolinsky et al., 2020).”
ResultInfluentialRosoff, D. B., Yoo, J., & Lohoff, F. W. (2021) · medRxiv · doi:10.1101/2021.02.11.21251581 · Cited by 6 · see citing works
“, lifestyle, or environmental factors), MR studies, are in theory, less susceptible to confounding or reverse causality than traditional observational studies.(23) Therefore, MR are an important analytical approach to strengthen causal inference when RCTs are challenging due to methodological or ethical constraints.”
BackgroundYang, L., Xu, M., Gao, X., Liu, J., Zhang, D., Zhang, Z., Ye, Z., Wen, J., & Liu, P. (2024) · Reviews in Cardiovascular Medicine · doi:10.31083/j.rcm2508292 · Cited by 6 · see citing works
“Several prior studies have utilized drug targets of PCSK9 and HMGCR to explore their effects across diverse health domains, including cardiovascular diseases, diabetes, cancer, and neurocognitive function [25,27,37,38].”
BackgroundNiu, Q., Zhang, T., Mao, R., Zhao, N., & Deng, S. (2024) · Scientific Reports · doi:10.1038/s41598-024-69180-2 · Cited by 5 · see citing works
“Our approach in selecting genetic variants mirrored methodologies implemented in earlier research endeavors 16,29 .”
MethodHan, X., Liu, F., Hidru, T. H., Yang, X., Wang, C., & Xia, Y. (2022) · Oxidative Medicine and Cellular Longevity · doi:10.1155/2022/5104351 · Cited by 5 · see citing works
“Therefore, proper utilization of statins should be encouraged to lower the risk of CVD, because positive outcomes have [30], EC [31], and OC [32] patients.”
Yarmolinsky, J., Lee, M. A., Lau, E., Moratalla-Navarro, F., Vincent, E. E., Li‐Gao, R., Rensen, P. C. N., van Dijk, K. W., Tsilidis, K. K., Sangphukieo, A., et al. (2025) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djaf137 · Cited by 5 · see citing works
Self-citationLi, S., & Schooling, C. (2022) · Scientific Reports · doi:10.1038/s41598-022-07344-8 · Cited by 8 · see citing works
Carter, P., Vithayathil, M. K., Kar, S., Potluri, R., Mason, A. M., Larsson, S. C., & Burgess, S. (2020) · medRxiv · doi:10.1101/2020.02.28.20028902 · Cited by 5 · see citing works
Nordestgaard, L. T., Luo, J., Emanuelsson, F., Leyden, G. M., Sanderson, E. C. M., Smith, G. D., Christoffersen, M., Afzal, S., Benn, M., Nordestgaard, B. G., et al. (2025) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgaf662 · Cited by 4 · see citing works
Self-citationRosoff, D. B., Wagner, J., Perlstein, T., Reitz, J., Jung, J., Blaney, H. L., Gharib, A. M., Hsu, C., Heller, T., Koh, C., et al. (2026) · Journal of Hepatology · doi:10.1016/j.jhep.2026.01.025 · Cited by 4 · see citing works
Self-citationZheng, P., Zheng, Z., Liu, Z.-Y., He, J., Rong, J., & Pan, H.-W. (2024) · Nutrition & Metabolism · doi:10.1186/s12986-024-00849-1 · Cited by 4 · see citing works
“While MR historically focussed on unravelling causal links between circulating biomarkers and disease phenotypes [12–14], its current application has expanded to further investigate the causal relationships between potential drug targets and diseases [15–17].”
BackgroundFu, L., Liu, Q., Cheng, H., Zhao, X., Xiong, J., & Mi, J. (2025) · Journal of the American Heart Association · doi:10.1161/jaha.124.038857 · Cited by 4 · see citing works
“Following methodologies established in prior studies, 48,49 we chose SNVs situated within a range of ±100 kb surrounding the target gene locations that were strongly correlated with triglycerides and LDL-C levels ( P value 5E-08) based on findings from the Global Lipids Genetics Consortium.”
Mechanisms of chemoresistance and approaches to overcome its impact in gynecologic cancers
Sabnis, N. A., Mathew, E., Dossou, A. S., Zheng, A., Nagarajan, B., Fudala, R., & Lacko, A. G. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-824299-5.00008-3 · Cited by 4 · see citing works
Genotype‐driven NPC1L1 and PCSK9 inhibition and reduced risk of periodontitis
Baumeister, S., Holtfreter, B., Reckelkamm, S. L., Kocher, T., Alayash, Z., Ehmke, B., Baurecht, H., & Nolde, M. (2022) · Journal Of Clinical Periodontology · doi:10.1111/jcpe.13719 · Cited by 4 · see citing works
Xiao, W., Li, Y., Zhuang, Z., Song, Z., Wang, W., Huang, N., Dong, X. Y., Jia, J., Liu, Z., Zhao, Y., et al. (2024) · Lipids in Health and Disease · doi:10.1186/s12944-024-02133-w · Cited by 4 · see citing works
“For drug-target MR analysis, genetic variants were selected as written in guidelines and previous research [12, 13, 19] to reflect pharmacological perturbation of the drug based on associations with biomarkers.”
MethodYarmolinsky, J., Lau, E., Koskeridis, F., Gunter, M. J., Wang, D. Y. Q., Dehghan, A., & Tzoulaki, I. (2025) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.125.322433 · Cited by 3 · see citing works
“–66 Fifth, as advised by the authors of PLACO, we removed variants with Z 2 >80 to minimize bias from extremely large effect sizes.”
Self-citationTang, W., & Ma, X. (2024) · Discover Oncology · doi:10.1007/s12672-024-01460-9 · Cited by 3 · see citing works
Sun, L., Zhang, Q., Shi, M., Liu, Y., Zhu, Z., Zhang, J., Peng, H. Y., Wang, A., Chen, J., Xu, T., et al. (2024) · Journal of the American Heart Association · doi:10.1161/jaha.124.036544 · Cited by 3 · see citing works
Shao, H., Xu, C., Zhang, C., Li, L., Wu, P., Chen, Z., & Guan, R. (2025) · International Journal of Women s Health · doi:10.2147/ijwh.s496268 · Cited by 3 · see citing works
He, J., Zhang, X., Wang, K., & Lv, W. (2022) · Journal of Nutrition · doi:10.1093/jn/nxac012 · Cited by 3 · see citing works
Min, Y., Liu, Z.-R., Wei, Z.-G., Li, R., Jin, J., Zhang, Y., & Peng, X.-C. (2022) · Pharmaceuticals · doi:10.3390/ph15121474 · Cited by 3 · see citing works
Solikhah, T. I., & Solikhah, G. P. (2024) · Research Journal of Pharmacy and Technology · doi:10.52711/0974-360x.2024.00112 · Cited by 3 · see citing works
Ji, X., Guo, H., Han, M., Peng, H., & Yuan, H. (2024) · International Journal of Rheumatic Diseases · doi:10.1111/1756-185x.15106 · Cited by 3 · see citing works
Tang, S., Chen, K., Zheng, F., Fu, Z., Niu, Y., Liu, X., Ni, H., Yuan, X., Cui, Z., Lv, W., et al. (2025) · Oncogene · doi:10.1038/s41388-025-03609-4 · Cited by 2 · see citing works
“E Kaplan-Meier curves of progression-free survival according to serum LDL levels (T1-low, T2-mid, T3-high). with EOC risk [8].”
Alnoor, A. A., Abdalla, A. N., Bar, F. M. A., Hamdi, O. A. A., Elzubier, M. E., Mohmed, H. H. A., Salkini, M. A., Kuse, M., Moglad, E. H. O., & Mira, A. (2024) · Arab Journal of Basic and Applied Sciences · doi:10.1080/25765299.2024.2370093 · Cited by 2 · see citing works
Tang, S., Zheng, F., Chen, K., Niu, Y., Fu, Z., Wu, Y., Xia, D., & Lü, W. (2024) · International Journal of Gynecological Cancer · doi:10.1136/ijgc-2024-005768 · Cited by 2 · see citing works
“Yarmolinsky et al 13 showed that 3- hydroxy- 3- methyl- glutaryl-coa (HMG-CoA) reductase inhibition, reducing low density lipoprotein cholesterol (LDL-C) levels, was associated with a lower risk of epithelial ovarian cancer, both in general patients and BRCA1/2 mutation carriers.”
Jiang, H., Li, L., Zhang, X. Z., He, J., Chen, C., Sun, R., Chen, Y., Xia, L., Lei, W., Chen, Y., et al. (2024) · Journal of Cachexia Sarcopenia and Muscle · doi:10.1002/jcsm.13575 · Cited by 2 · see citing works
Tang, K., Wang, W., Chang, W., & Wu, X. (2024) · Health Science Reports · doi:10.1002/hsr2.70162 · Cited by 2 · see citing works
“For each of these drug targets, SNPs used as instruments were permitted to be in weak linkage disequilibrium (LD, r 2 0.30) with each other to increase the proportion of variance in each respective drug target explained by the instrument, maximising instrument strength [21].”
MethodInfluentialMa, Y., Zhou, Z., Li, X., Ding, K., Xiao, H., Wu, Y., Wu, T., & Chen, D. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2022.1009095 · Cited by 2 · see citing works
“Inhibition of 3hydroxy-3-methylglutaryl-CoA reductase (HMGCR), which is the intended drug target to reduce LDL cholesterol concentration, was significantly associatedwith lower odds of epithelial ovarian cancer (40).”
Background
- 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 › Surgery › 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
