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

Laboratory studies have suggested oncogenic roles of lipids, as well as anticarcinogenic effects of statins. We here assess the potential effect of statin therapy on cancer risk in Mendelian randomization analyses. We obtained genetic associations with the risk of overall and 22 site-specific cancers for 367,703 individuals in 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 (OR per 1 standard deviation increase in LDL-cholesterol 1.32, 95% CI 1.13-1.53, 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 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.

Laboratory studies have suggested oncogenic roles of lipids, as well as anticarcinogenic effects of statins.We here assess the potential effect of statin therapy on cancer risk in Mendelian randomization analyses.We obtained genetic associations with the risk of overall and 22 sitespecific cancers for 367,703 individuals in 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 (OR per 1 standard deviation increase in LDLcholesterol 1.32, 95% CI 1.13-1.53,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 1.01, 95% CI 0.98-1.05,p=0.50).Our results predict that statins reduce cancer risk, but other lipidlowering treatments do not.This suggests that statins reduce cancer risk through a cholesterol independent pathway.
Statins are inhibitors of 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase (HMGCR), which is the rate-limiting enzyme in the melavonate pathway; a pathway producing a range of cell signalling molecules with the potential to regulate oncogenesis.This is supported by strong laboratory evidence that statins induce anticarcinogenic effects on cell proliferation and survival in various cell lines [1][2][3][4] , and reduce tumour growth in a range of in vivo models [5][6][7][8][9][10] .Furthermore, epidemiological studies of pre-diagnostic use of statins have been associated with reduced risk of specific cancer types [11][12][13] .However, meta-analyses of cardiovascular-focused randomized controlled trials have shown no effect of statins on cancer 14,15 .Conclusions from these trials are limited as they lack adequate power and longitudinal follow-up necessary for assessing impact on cancer risk.At present, no clinical trials have been designed to assess the role of statins in primary cancer prevention and their role in chemoprevention remains uncertain.
A putative protective effect of statins on cancer development could be through either cholesterol dependent or independent effects [16][17][18][19] .Cholesterol is a key mediator produced by the mevalonate pathway and is essential to cell signalling and membrane structure, with evidence demonstrating the potential to drive oncogenic processes and tumour growth 20,21 .
However, the epidemiological relationships between circulating cholesterol and cancer risk remain unclear.Individual observational studies have reported positive 22,23 , inverse [22][23][24][25] and no association [26][27][28][29] between circulating levels of total cholesterol, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, and triglycerides with risk of overall and site-specific cancers.Different cancer types have distinct underlying pathophysiology, and meta-analyses of observational studies highlight a likely complex relationship which varies according to both lipid fraction 30,31 and cancer type 29,[32][33][34] .Furthermore, cancer can lower cholesterol levels for up to 20 months prior to diagnosis 35 .Thus, the true relationship between lipids and cancer development remains equivocal.
Mendelian randomization is an epidemiological approach which assesses associations between genetically-predicted levels of a risk factor and a disease outcome in order to predict the causal effect of the risk factor on an outcome 36 .The use of genetic variants minimizes the influences of reverse causality and confounding factors on estimates.Mendelian randomization studies also have the potential to predict the outcomes of trials for specific therapeutic interventions.
A limited number of Mendelian randomization studies have investigated the relationship between HMGCR inhibition and cancer [37][38][39][40][41] , with protective associations observed for prostate cancer 37 , colorectal cancer 38 , breast cancer 39,40 , and ovarian cancer 41 .However, no comprehensive Mendelian randomization investigation has evaluated the predicted impact of HMGCR inhibition or the causal role of specific lipid fractions on the risk of many of the most common site-specific cancers.
We here investigate the relationship between HMGCR inhibition and the risk of overall cancer and site-specific cancers using genetic variants in the HMGCR gene region.To understand whether statins may influence cancer risk through lipid-related mechanisms, we also assess the relationship between lipids and cancer risk by polygenic Mendelian randomization analyses using common lipid-associated genetic variants.Additionally, to mimic other lipid-lowering pharmaceutical interventions, gene-specific analyses were performed using variants in or near gene regions targeted by these therapies.
Baseline characteristics of the participants in the UK Biobank and numbers of outcomes are provided in Table 1.In total, 75,037 of the participants had a cancer event, of which 48,674 participants had one of the 22 defined site-specific cancers.Power calculations for the various analyses are presented in Supplementary Figure 1 (site-specific cancers) and Supplementary Table 1 (overall cancer).Gene-specific analyses were only well-powered for overall cancer.
Polygenic analyses were well-powered to detect moderate effects for overall cancer and for common site-specific cancers, but less well-powered for less common site-specific cancers.
For site-specific cancers, the HMGCR gene region showed positive associations for five of the six most common cancer sites (breast, prostate, melanoma, lung, and bladder; not for bowel), although none of these results individually reached a conventional level of statistical significance.There was little evidence for associations in site-specific analyses for other lipidlowering drug targets.
For site-specific cancers, there were positive associations between risk of bowel cancer and genetically-predicted levels of total cholesterol (OR 1.18, 95% CI 1.06-1.32,p=0.002) and LDL-cholesterol (OR 1.16, CI 1.04-1.29,p=0.006).Results were attenuated in robust methods (Supplementary Table 3).No other associations were statistically significant after accounting for multiple testing.
Our comprehensive Mendelian randomization investigation shows a positive association between overall cancer and variants in the HMGCR gene region which can be considered as proxies for statin therapy.However, gene regions which can be considered as proxies for alternative lipid-lowering therapies were not associated with cancer risk.Furthermore, there was little consistent evidence of an association between genetically-predicted lipid fractions and cancer outcomes in polygenic analyses either for overall cancer or for any site-specific cancer.Taken together, our findings predict that statins lower the risk of cancer, and provide important mechanistic evidence that this occurs through mechanisms other than lipid lowering.
We found that genetic variants in the HMGCR region, serving as proxies for targets of statin therapy, were associated with a 26% decrease in risk of overall cancer per standard deviation (around 39 mg/dL or 1.0 mmol/L) reduction in genetically-predicted LDL-cholesterol.For coronary artery disease, the short-term impact of statins in trials is around one-third of the Mendelian randomization estimate (which represents the impact of lifelong reduced exposure) 42 .This suggests that any reduction in cancer risk from statins is likely to be modest.
While our results should be seen as tentative until trials have demonstrated benefit, associations of HMGCR variants show broad concordance with statin therapy for many continuous phenotypes 43 , and suggest that statins reduce risk of coronary artery disease 44 , increase risk of Type 2 diabetes 45 , and increase risk of intracerebral haemorrhage 46,47 , as confirmed in clinical trials [48][49][50] .
The notion that statins could be used for chemoprevention is longstanding.Nobel Prize winners Goldstein and Brown proposed that this occurs through non-lipid lowering mechanisms 16 .We provide mechanistic evidence using human genetics supporting this theory.Our results suggest that with respect to genetically predicted HMGCR inhibition and cancer risk, LDL-cholesterol is simply a biomarker of HMGCR inhibition that is accessible, but the true causal pathway is likely via another molecule whose levels are correlated with its LDL-cholesterol lowering effect.HMGCR catalyses the rate-limiting step of the mevalonate pathway; a pathway with an arm leading to the end point of cholesterol synthesis and another arm leading to isoprenoid synthesis.Measuring levels of intra-cellular isoprenoids is challenging but these molecules are implicated in cancer via their role as major post-translational modifiers of key oncogenic proteins 17 .In particular, mevalonate and other isoprenoid metabolites are required for the prenylation and functioning of the Ras and Rho GTPases, which are oncoproteins, and involved in important cellular processes including apoptosis, phagocytosis, vascular trafficking, cell proliferation, transmigration, cytoskeleton organisation, and recruitment of inflammatory cells.
Statin inhibition of these metabolites has demonstrated anti-oncological effects in vivo and in vitro 18 including the promotion of tumour cell death and apoptosis [51][52][53][54] , inhibition of angiogenesis 55 , and reduction of tumour cell invasion and metastasis 56,57 .Other potential statinmediated mechanisms of tumour suppression include the reduction of systemic inflammatory mediators like interleukin 1-beta and tumour necrosis factor 55,58 , and epigenetic regulation through inhibiting HMGCR-mediated deacetylation 59 which contributes to colorectal cancer in mouse models 60 .Thus, our findings based on large-scale human genetic data are consistent with pre-clinical studies on statins in cancer which have repeatedly argued for a cholesterol independent mechanism for statin effects on cancer.
Our investigation has many strengths, but also limitations.The large sample size of over 360,000 participants and the broad set of outcomes analysed render this the most comprehensive Mendelian randomization analysis of lipids and cancer outcomes conducted to date.However, the investigation has a number of limitations.For many site-specific cancers, there were not enough outcome events to obtain adequate power to rule out the possibility of moderate causal effects.While there is evidence to support our assumption that genetic variants in relevant gene regions can be used as proxies for pharmacological interventions, our findings should be considered with caution until they have been replicated in clinical trials.Our investigation was able to compare subgroups of the population with different lifelong average levels of lipid fractions, but the impact of lowering a particular lipid fraction in practice is likely to differ from the genetic association, particularly quantitatively 61 .Finally, analyses were conducted in UK-based participants of European ancestries.While it is recommended to have a well-mixed study population for Mendelian randomization in order to ensure that genetic associations are not influenced by population stratification, it means that results may not be generalizable to other ethnicities or nationalities.
In conclusion, our findings suggest that HMGCR inhibition may have a chemopreventive role in cancer though non-lipid lowering properties, and that this role may apply across cancer sites.
The efficacy of statins for cancer prevention must be urgently evaluated.

Study design and data sources
We performed two-sample Mendelian randomization analyses, taking genetic associations with risk factors (i.e., serum lipid levels) from one dataset, and genetic associations with cancer outcomes from an independent dataset, as performed previously for cardiovascular diseases 62 .
We obtained genetic associations with serum lipid concentrations (total cholesterol, LDLcholesterol, HDL-cholesterol, and triglycerides) from the Global Lipids Genetic Consortium (GLGC) on up to 188,577 individuals of European ancestry 63 .Genetic associations were estimated with adjustment for age, sex, and genomic principal components within each participating study after inverse rank quantile normalization of lipid concentrations, and then meta-analysed across studies.
We estimated genetic associations with cancer outcomes on 367,703 unrelated individuals of European ancestry from UK Biobank, a population-based cohort recruited between 2006-2010 at 22 assessment centres throughout the UK and followed-up until 31st March 2017 or their date of death (recorded until 14th February 2018) 64 .We defined cancer outcomes for overall cancer and for the 22 most common site-specific cancers in the UK (Supplementary Table 4).
Outcomes were based on electronic health records, hospital episode statistics data, national cancer registry data, and death certification data, which were all coded according to ICD-9 and ICD-10 diagnoses.Further cancer outcomes were captured by self-reported information validated by interview with a trained nurse, and from cancer histology data in the national cancer registry.To obtain genetic association estimates for each outcome, we conducted logistic regression with adjustment for age, sex, and 10 genomic principal components using the snptest software program.For sex-specific cancers (breast, uterus, and cervix for women, prostate and testes for men), analyses were restricted to individuals of the relevant sex.

Gene-specific analyses for HMGCR and other drug proxy variants
We performed targeted analyses for variants in the HMGCR gene region that can be considered as proxies for statin therapy.Additionally, we conducted separate analyses for the PCSK9, LDLR, NPC1L1, APOC3, and LPL gene regions, mimicking other lipid altering therapies (Supplementary Table 5).These regions were chosen as they contain variants that explain enough variance in lipids to perform adequately powered analyses.Variants in each gene region explained 0.4% (HMGCR), 1.2% (PCSK9), 1.0% (LDLR), 0.2% (NPC1L1), 0.1% (APOC3) and <0.1% (LPL) of the variance in LDL-cholesterol.The APOC3 and LPL variants also explained 1.0% and 0.9% of the variance in triglycerides respectively.We performed the inverse-variance weighted method accounting for correlations between the variants 65 .
Estimates for the HMGCR, PCSK9, LDLR and NPC1L1 gene regions are scaled to a 1 standard deviation increase in LDL-cholesterol, whereas estimates for the APOC3 and LPL gene regions are scaled to a 1 standard deviation increase in triglycerides.

Polygenic analyses for all lipid-related variants
We carried out polygenic analyses based on 184 genetic variants previously demonstrated to be associated with at least one of total cholesterol, LDL-cholesterol, HDL-cholesterol or triglycerides at a genome-wide level of significance (p < 5 × 10 −8 ) in the GLGC 66 .These variants explained 15.0% of the variance in total cholesterol, 14.6% in LDL-cholesterol, 13.7% in HDL-cholesterol, and 11.7% in triglycerides in the GLGC.
To obtain the associations of genetically-predicted values of LDL-cholesterol, HDLcholesterol and triglycerides with each cancer outcome while accounting for measured genetic pleiotropy via each other, we performed multivariable Mendelian randomization analyses using the inverse-variance weighted method 67 .For total cholesterol, we performed univariable Mendelian randomization analyses using the inverse-variance weighted method 68 .To account for between-variant heterogeneity, we used random-effects models in all analyses.For polygenic analyses that provided evidence of a causal effect, we additionally performed robust methods for Mendelian randomization, in particular the MR-Egger 69 and weighted median methods 70 .All estimates are expressed per 1 standard deviation increase in the corresponding lipid fraction (in the GLGC, 1 standard deviation was 45.6 mg/dL for total cholesterol, 39.0 mg/dL for LDL-cholesterol, 15.8 mg/dL for HDL-cholesterol, and 90.5 mg/dL for triglycerides).
As power calculators have not been developed for multivariable Mendelian randomization analyses, we performed power calculations for polygenic analyses based on univariable Mendelian randomization for each lipid fraction in turn, and for gene-specific analyses for each gene region in turn 71 .We carried out all analyses using R (version 3.4.4)unless otherwise stated.All statistical tests and p-values presented are two-sided.

Table 1 :
Baseline characteristics of UK Biobank participants included in this study and numbers of outcome events Figure1: Gene-specific Mendelian randomization estimates (odds ratio with 95% confidence interval per 1 standard deviation increase in lipid fraction) for variants in gene regions representing targets of lipidlowering treatments.Estimates are scaled to a 1 standard deviation increase in LDL-cholesterol for the HMGCR, PCSK9, LDLR and NPC1L1 regions, and to a 1 standard deviation increase in triglycerides for the APOC3 and LPL regions.A: associations with overall cancer for each gene region in turn.B: associations with site-specific cancers for variants in the HMGCR gene region.

Table 1 :
Power calculations for polygenic and gene-specific analyses, representing the power to detect a given effect size (odds ratio per 1 standard deviation increase in lipid fraction) at a significance threshold of p<0.05 for overall cancer (367,703 total individuals, 75,037 cases) Gene-specific Mendelian randomization estimates (odds ratio with 95% confidence interval per 1 standard deviation increase in LDL-cholesterol) for variants in the PCSK9 gene region Supplementary Figure3: Gene-specific Mendelian randomization estimates (odds ratio with 95% confidence interval per 1 standard deviation increase in LDL-cholesterol) for variants in the LDLR gene region Supplementary Figure4: Gene-specific Mendelian randomization estimates (odds ratio with 95% confidence interval per 1 standard deviation increase in LDL-cholesterol) for variants in the NPC1L1 gene region Supplementary Figure5: Gene-specific Mendelian randomization estimates (odds ratio with 95% confidence interval per 1 standard deviation increase in triglycerides) for variants in the APOC3 gene region Supplementary Figure6: Gene-specific Mendelian randomization estimates (odds ratio with 95% confidence interval per 1 standard deviation increase in LDL-cholesterol) for variants in the LPL gene region

Table 2 :
Estimates (odds ratio per 1 standard deviation increase in lipid fraction and 95% confidence interval) from polygenic multivariable Mendelian randomization analyses including all lipidrelated variants.Estimates with p < 0.05 are reported in bold.