Strategies to investigate and mitigate collider bias in genetic and Mendelian randomisation studies of disease progression.

Genetic studies of disease progression can be used to identify factors that may influence survival or prognosis, which may differ from factors that influence on disease susceptibility. Studies of disease progression feed directly into therapeutics for disease, whereas studies of incidence inform prevention strategies. However, studies of disease progression are known to be affected by collider (also known as "index event") bias since the disease progression phenotype can only be observed for individuals who have the disease. This applies equally to observational and genetic studies, including genome-wide association studies and Mendelian randomisation (MR) analyses. In this paper, our aim is to review several statistical methods that can be used to detect and adjust for index event bias in studies of disease progression, and how they apply to genetic and MR studies using both individual- and summary-level data. Methods to detect the presence of index event bias include the use of negative controls, a comparison of associations between risk factors for incidence in individuals with and without the disease, and an inspection of Miami plots. Methods to adjust for the bias include inverse probability weighting (with individual-level data), or Slope-Hunter and Dudbridge et al.'s index event bias adjustment (when only summary-level data are available). We also outline two approaches for sensitivity analysis. We then illustrate how three methods to minimise bias can be used in practice with two applied examples. Our first example investigates the effects of blood lipid traits on mortality from coronary heart disease, while our second example investigates genetic associations with breast cancer mortality.

Using genetic variants to evaluate the causal effect of cholesterol lowering on head and neck cancer risk: A Mendelian randomization study.

Head and neck squamous cell carcinoma (HNSCC), which includes cancers of the oral cavity and oropharynx, is a cause of substantial global morbidity and mortality. Strategies to reduce disease burden include discovery of novel therapies and repurposing of existing drugs. Statins are commonly prescribed for lowering circulating cholesterol by inhibiting HMG-CoA reductase (HMGCR). Results from some observational studies suggest that statin use may reduce HNSCC risk. We appraised the relationship of genetically-proxied cholesterol-lowering drug targets and other circulating lipid traits with oral (OC) and oropharyngeal (OPC) cancer risk using two-sample Mendelian randomization (MR). For the primary analysis, germline genetic variants in HMGCR, NPC1L1, CETP, PCSK9 and LDLR were used to proxy the effect of low-density lipoprotein cholesterol (LDL-C) lowering therapies. In secondary analyses, variants were used to proxy circulating levels of other lipid traits in a genome-wide association study (GWAS) meta-analysis of 188,578 individuals. Both primary and secondary analyses aimed to estimate the downstream causal effect of cholesterol lowering therapies on OC and OPC risk. The second sample for MR was taken from a GWAS of 6,034 OC and OPC cases and 6,585 controls (GAME-ON). Analyses were replicated in UK Biobank, using 839 OC and OPC cases and 372,016 controls and the results of the GAME-ON and UK Biobank analyses combined in a fixed-effects meta-analysis. We found limited evidence of a causal effect of genetically-proxied LDL-C lowering using HMGCR, NPC1L1, CETP or other circulating lipid traits on either OC or OPC risk. Genetically-proxied PCSK9 inhibition equivalent to a 1 mmol/L (38.7 mg/dL) reduction in LDL-C was associated with an increased risk of OC and OPC combined (OR 1.8 95%CI 1.2, 2.8, p = 9.31 x10-05), with good concordance between GAME-ON and UK Biobank (I2 = 22%). Effects for PCSK9 appeared stronger in relation to OPC (OR 2.6 95%CI 1.4, 4.9) than OC (OR 1.4 95%CI 0.8, 2.4). LDLR variants, resulting in genetically-proxied reduction in LDL-C equivalent to a 1 mmol/L (38.7 mg/dL), reduced the risk of OC and OPC combined (OR 0.7, 95%CI 0.5, 1.0, p = 0.006). A series of pleiotropy-robust and outlier detection methods showed that pleiotropy did not bias our findings. We found limited evidence for a role of cholesterol-lowering in OC and OPC risk, suggesting previous observational results may have been confounded. There was some evidence that genetically-proxied inhibition of PCSK9 increased risk, while lipid-lowering variants in LDLR, reduced risk of combined OC and OPC. This result suggests that the mechanisms of action of PCSK9 on OC and OPC risk may be independent of its cholesterol lowering effects; however, this was not supported uniformly across all sensitivity analyses and further replication of this finding is required.

Genetically proxied glucose-lowering drug target perturbation and risk of cancer: a Mendelian randomisation analysis.

AIMS/HYPOTHESIS: Epidemiological studies have generated conflicting findings on the relationship between glucose-lowering medication use and cancer risk. Naturally occurring variation in genes encoding glucose-lowering drug targets can be used to investigate the effect of their pharmacological perturbation on cancer risk. METHODS: We developed genetic instruments for three glucose-lowering drug targets (peroxisome proliferator activated receptor γ [PPARG]; sulfonylurea receptor 1 [ATP binding cassette subfamily C member 8 (ABCC8)]; glucagon-like peptide 1 receptor [GLP1R]) using summary genetic association data from a genome-wide association study of type 2 diabetes in 148,726 cases and 965,732 controls in the Million Veteran Program. Genetic instruments were constructed using cis-acting genome-wide significant (p<5×10-8) SNPs permitted to be in weak linkage disequilibrium (r2<0.20). Summary genetic association estimates for these SNPs were obtained from genome-wide association study (GWAS) consortia for the following cancers: breast (122,977 cases, 105,974 controls); colorectal (58,221 cases, 67,694 controls); prostate (79,148 cases, 61,106 controls); and overall (i.e. site-combined) cancer (27,483 cases, 372,016 controls). Inverse-variance weighted random-effects models adjusting for linkage disequilibrium were employed to estimate causal associations between genetically proxied drug target perturbation and cancer risk. Co-localisation analysis was employed to examine robustness of findings to violations of Mendelian randomisation (MR) assumptions. A Bonferroni correction was employed as a heuristic to define associations from MR analyses as 'strong' and 'weak' evidence. RESULTS: In MR analysis, genetically proxied PPARG perturbation was weakly associated with higher risk of prostate cancer (for PPARG perturbation equivalent to a 1 unit decrease in inverse rank normal transformed HbA1c: OR 1.75 [95% CI 1.07, 2.85], p=0.02). In histological subtype-stratified analyses, genetically proxied PPARG perturbation was weakly associated with lower risk of oestrogen receptor-positive breast cancer (OR 0.57 [95% CI 0.38, 0.85], p=6.45×10-3). In co-localisation analysis, however, there was little evidence of shared causal variants for type 2 diabetes liability and cancer endpoints in the PPARG locus, although these analyses were likely underpowered. There was little evidence to support associations between genetically proxied PPARG perturbation and colorectal or overall cancer risk or between genetically proxied ABCC8 or GLP1R perturbation with risk across cancer endpoints. CONCLUSIONS/INTERPRETATION: Our drug target MR analyses did not find consistent evidence to support an association of genetically proxied PPARG, ABCC8 or GLP1R perturbation with breast, colorectal, prostate or overall cancer risk. Further evaluation of these drug targets using alternative molecular epidemiological approaches may help to further corroborate the findings presented in this analysis. DATA AVAILABILITY: Summary genetic association data for select cancer endpoints were obtained from the public domain: breast cancer ( https://bcac.ccge.medschl.cam.ac.uk/bcacdata/ ); and overall prostate cancer ( http://practical.icr.ac.uk/blog/ ). Summary genetic association data for colorectal cancer can be accessed by contacting GECCO (kafdem at fredhutch.org). Summary genetic association data on advanced prostate cancer can be accessed by contacting PRACTICAL (practical at icr.ac.uk). Summary genetic association data on type 2 diabetes from Vujkovic et al (Nat Genet, 2020) can be accessed through dbGAP under accession number phs001672.v3.p1 (pha004945.1 refers to the European-specific summary statistics). UK Biobank data can be accessed by registering with UK Biobank and completing the registration form in the Access Management System (AMS) ( https://www.ukbiobank.ac.uk/enable-your-research/apply-for-access ).

Association between genetically proxied PCSK9 inhibition and prostate cancer risk: A Mendelian randomisation study.

BACKGROUND: Prostate cancer (PrCa) is the second most prevalent malignancy in men worldwide. Observational studies have linked the use of low-density lipoprotein cholesterol (LDL-c) lowering therapies with reduced risk of PrCa, which may potentially be attributable to confounding factors. In this study, we performed a drug target Mendelian randomisation (MR) analysis to evaluate the association of genetically proxied inhibition of LDL-c-lowering drug targets on risk of PrCa. METHODS AND FINDINGS: Single-nucleotide polymorphisms (SNPs) associated with LDL-c (P < 5 × 10-8) from the Global Lipids Genetics Consortium genome-wide association study (GWAS) (N = 1,320,016) and located in and around the HMGCR, NPC1L1, and PCSK9 genes were used to proxy the therapeutic inhibition of these targets. Summary-level data regarding the risk of total, advanced, and early-onset PrCa were obtained from the PRACTICAL consortium. Validation analyses were performed using genetic instruments from an LDL-c GWAS conducted on male UK Biobank participants of European ancestry (N = 201,678), as well as instruments selected based on liver-derived gene expression and circulation plasma levels of targets. We also investigated whether putative mediators may play a role in findings for traits previously implicated in PrCa risk (i.e., lipoprotein a (Lp(a)), body mass index (BMI), and testosterone). Applying two-sample MR using the inverse-variance weighted approach provided strong evidence supporting an effect of genetically proxied inhibition of PCSK9 (equivalent to a standard deviation (SD) reduction in LDL-c) on lower risk of total PrCa (odds ratio (OR) = 0.85, 95% confidence interval (CI) = 0.76 to 0.96, P = 9.15 × 10-3) and early-onset PrCa (OR = 0.70, 95% CI = 0.52 to 0.95, P = 0.023). Genetically proxied HMGCR inhibition provided a similar central effect estimate on PrCa risk, although with a wider 95% CI (OR = 0.83, 95% CI = 0.62 to 1.13, P = 0.244), whereas genetically proxied NPC1L1 inhibition had an effect on higher PrCa risk with a 95% CI that likewise included the null (OR = 1.34, 95% CI = 0.87 to 2.04, P = 0.180). Analyses using male-stratified instruments provided consistent results. Secondary MR analyses supported a genetically proxied effect of liver-specific PCSK9 expression (OR = 0.90 per SD reduction in PCSK9 expression, 95% CI = 0.86 to 0.95, P = 5.50 × 10-5) and circulating plasma levels of PCSK9 (OR = 0.93 per SD reduction in PCSK9 protein levels, 95% CI = 0.87 to 0.997, P = 0.04) on PrCa risk. Colocalization analyses identified strong evidence (posterior probability (PPA) = 81.3%) of a shared genetic variant (rs553741) between liver-derived PCSK9 expression and PrCa risk, whereas weak evidence was found for HMGCR (PPA = 0.33%) and NPC1L1 expression (PPA = 0.38%). Moreover, genetically proxied PCSK9 inhibition was strongly associated with Lp(a) levels (Beta = -0.08, 95% CI = -0.12 to -0.05, P = 1.00 × 10-5), but not BMI or testosterone, indicating a possible role for Lp(a) in the biological mechanism underlying the association between PCSK9 and PrCa. Notably, we emphasise that our estimates are based on a lifelong exposure that makes direct comparisons with trial results challenging. CONCLUSIONS: Our study supports a strong association between genetically proxied inhibition of PCSK9 and a lower risk of total and early-onset PrCa, potentially through an alternative mechanism other than the on-target effect on LDL-c. Further evidence from clinical studies is needed to confirm this finding as well as the putative mediatory role of Lp(a).

Association of germline TYK2 variation with lung cancer and non-Hodgkin lymphoma risk.

Deucravacitinib, a novel, selective inhibitor of TYK2 is currently under review at the FDA and EMA for treatment of moderate-to-severe plaque psoriasis. It is unclear whether recent safety concerns (ie, elevated rates of lung cancer and lymphoma) related to similar medications (ie, other JAK inhibitors) are shared with this novel TYK2 inhibitor. We used a partial loss-of-function variant in TYK2 (rs34536443), previously shown to protect against psoriasis and other autoimmune diseases, to evaluate the potential effect of therapeutic TYK2 inhibition on risk of lung cancer and non-Hodgkin lymphoma. Summary genetic association data on lung cancer risk were obtained from a GWAS meta-analysis of 29 266 cases and 56 450 controls in the Integrative Analysis of Lung Cancer Risk and Aetiology (INTEGRAL) consortium. Summary genetic association data on non-Hodgkin lymphoma risk were obtained from a GWAS meta-analysis of 8489 cases and 374 506 controls in the UK Biobank and InterLymph consortium. In the primary analysis, each copy of the minor allele of rs34536443, representing partial TYK2 inhibition, was associated with an increased risk of lung cancer (OR 1.15, 95% CI 1.09-1.23, P = 2.29 × 10-6 ) and non-Hodgkin lymphoma (OR 1.18, 95% CI 1.05-1.33, P = 5.25 × 10-3 ). Our analyses using an established partial loss-of-function mutation to mimic TYK2 inhibition provide genetic evidence that therapeutic TYK2 inhibition may increase risk of lung cancer and non-Hodgkin lymphoma. These findings, consistent with recent reports from postmarketing trials of similar JAK inhibitors, could have important implications for future safety assessment of deucravacitinib and other TYK2 inhibitors in development.

Genetically proxied therapeutic inhibition of antihypertensive drug targets and risk of common cancers: A mendelian randomization analysis.

BACKGROUND: Epidemiological studies have reported conflicting findings on the potential adverse effects of long-term antihypertensive medication use on cancer risk. Naturally occurring variation in genes encoding antihypertensive drug targets can be used as proxies for these targets to examine the effect of their long-term therapeutic inhibition on disease outcomes. METHODS AND FINDINGS: We performed a mendelian randomization analysis to examine the association between genetically proxied inhibition of 3 antihypertensive drug targets and risk of 4 common cancers (breast, colorectal, lung, and prostate). Single-nucleotide polymorphisms (SNPs) in ACE, ADRB1, and SLC12A3 associated (P < 5.0 × 10-8) with systolic blood pressure (SBP) in genome-wide association studies (GWAS) were used to proxy inhibition of angiotensin-converting enzyme (ACE), ß-1 adrenergic receptor (ADRB1), and sodium-chloride symporter (NCC), respectively. Summary genetic association estimates for these SNPs were obtained from GWAS consortia for the following cancers: breast (122,977 cases, 105,974 controls), colorectal (58,221 cases, 67,694 controls), lung (29,266 cases, 56,450 controls), and prostate (79,148 cases, 61,106 controls). Replication analyses were performed in the FinnGen consortium (1,573 colorectal cancer cases, 120,006 controls). Cancer GWAS and FinnGen consortia data were restricted to individuals of European ancestry. Inverse-variance weighted random-effects models were used to examine associations between genetically proxied inhibition of these drug targets and risk of cancer. Multivariable mendelian randomization and colocalization analyses were employed to examine robustness of findings to violations of mendelian randomization assumptions. Genetically proxied ACE inhibition equivalent to a 1-mm Hg reduction in SBP was associated with increased odds of colorectal cancer (odds ratio (OR) 1.13, 95% CI 1.06 to 1.22; P = 3.6 × 10-4). This finding was replicated in the FinnGen consortium (OR 1.40, 95% CI 1.02 to 1.92; P = 0.035). There was little evidence of association of genetically proxied ACE inhibition with risk of breast cancer (OR 0.98, 95% CI 0.94 to 1.02, P = 0.35), lung cancer (OR 1.01, 95% CI 0.92 to 1.10; P = 0.93), or prostate cancer (OR 1.06, 95% CI 0.99 to 1.13; P = 0.08). Genetically proxied inhibition of ADRB1 and NCC were not associated with risk of these cancers. The primary limitations of this analysis include the modest statistical power for analyses of drug targets in relation to some less common histological subtypes of cancers examined and the restriction of the majority of analyses to participants of European ancestry. CONCLUSIONS: In this study, we observed that genetically proxied long-term ACE inhibition was associated with an increased risk of colorectal cancer, warranting comprehensive evaluation of the safety profiles of ACE inhibitors in clinical trials with adequate follow-up. There was little evidence to support associations across other drug target-cancer risk analyses, consistent with findings from short-term randomized controlled trials for these medications.

Identifying molecular mediators of the relationship between body mass index and endometrial cancer risk: a Mendelian randomization analysis.

BACKGROUND: Endometrial cancer is the most common gynaecological cancer in high-income countries. Elevated body mass index (BMI) is an established modifiable risk factor for this condition and is estimated to confer a larger effect on endometrial cancer risk than any other cancer site. However, the molecular mechanisms underpinning this association remain unclear. We used Mendelian randomization (MR) to evaluate the causal role of 14 molecular risk factors (hormonal, metabolic and inflammatory markers) in endometrial cancer risk. We then evaluated and quantified the potential mediating role of these molecular traits in the relationship between BMI and endometrial cancer using multivariable MR. METHODS: Genetic instruments to proxy 14 molecular risk factors and BMI were constructed by identifying single-nucleotide polymorphisms (SNPs) reliably associated (P < 5.0 × 10-8) with each respective risk factor in previous genome-wide association studies (GWAS). Summary statistics for the association of these SNPs with overall and subtype-specific endometrial cancer risk (12,906 cases and 108,979 controls) were obtained from a GWAS meta-analysis of the Endometrial Cancer Association Consortium (ECAC), Epidemiology of Endometrial Cancer Consortium (E2C2) and UK Biobank. SNPs were combined into multi-allelic models and odds ratios (ORs) and 95% confidence intervals (95% CIs) were generated using inverse-variance weighted random-effects models. The mediating roles of the molecular risk factors in the relationship between BMI and endometrial cancer were then estimated using multivariable MR. RESULTS: In MR analyses, there was strong evidence that BMI (OR per standard deviation (SD) increase 1.88, 95% CI 1.69 to 2.09, P = 3.87 × 10-31), total testosterone (OR per inverse-normal transformed nmol/L increase 1.64, 95% CI 1.43 to 1.88, P = 1.71 × 10-12), bioavailable testosterone (OR per natural log transformed nmol/L increase: 1.46, 95% CI 1.29 to 1.65, P = 3.48 × 10-9), fasting insulin (OR per natural log transformed pmol/L increase: 3.93, 95% CI 2.29 to 6.74, P = 7.18 × 10-7) and sex hormone-binding globulin (SHBG, OR per inverse-normal transformed nmol/L increase 0.71, 95% CI 0.59 to 0.85, P = 2.07 × 10-4) had a causal effect on endometrial cancer risk. Additionally, there was suggestive evidence that total serum cholesterol (OR per mg/dL increase 0.90, 95% CI 0.81 to 1.00, P = 4.01 × 10-2) had an effect on endometrial cancer risk. In mediation analysis, we found evidence for a mediating role of fasting insulin (19% total effect mediated, 95% CI 5 to 34%, P = 9.17 × 10-3), bioavailable testosterone (15% mediated, 95% CI 10 to 20%, P = 1.43 × 10-8) and SHBG (7% mediated, 95% CI 1 to 12%, P = 1.81 × 10-2) in the relationship between BMI and endometrial cancer risk. CONCLUSIONS: Our comprehensive MR analysis provides insight into potential causal mechanisms linking BMI with endometrial cancer risk and suggests targeting of insulinemic and hormonal traits as a potential strategy for the prevention of endometrial cancer.

Circulating inflammatory cytokines and risk of five cancers: a Mendelian randomization analysis.

BACKGROUND: Epidemiological and experimental evidence has linked chronic inflammation to cancer aetiology. It is unclear whether associations for specific inflammatory biomarkers are causal or due to bias. In order to examine whether altered genetically predicted concentration of circulating cytokines are associated with cancer development, we performed a two-sample Mendelian randomisation (MR) analysis. METHODS: Up to 31,112 individuals of European descent were included in genome-wide association study (GWAS) meta-analyses of 47 circulating cytokines. Single nucleotide polymorphisms (SNPs) robustly associated with the cytokines, located in or close to their coding gene (cis), were used as instrumental variables. Inverse-variance weighted MR was used as the primary analysis, and the MR assumptions were evaluated in sensitivity and colocalization analyses and a false discovery rate (FDR) correction for multiple comparisons was applied. Corresponding germline GWAS summary data for five cancer outcomes (breast, endometrial, lung, ovarian, and prostate), and their subtypes were selected from the largest cancer-specific GWASs available (cases ranging from 12,906 for endometrial to 133,384 for breast cancer). RESULTS: There was evidence of inverse associations of macrophage migration inhibitory factor with breast cancer (OR per SD = 0.88, 95% CI 0.83 to 0.94), interleukin-1 receptor antagonist with endometrial cancer (0.86, 0.80 to 0.93), interleukin-18 with lung cancer (0.87, 0.81 to 0.93), and beta-chemokine-RANTES with ovarian cancer (0.70, 0.57 to 0.85) and positive associations of monokine induced by gamma interferon with endometrial cancer (3.73, 1.86 to 7.47) and cutaneous T-cell attracting chemokine with lung cancer (1.51, 1.22 to 1.87). These associations were similar in sensitivity analyses and supported in colocalization analyses. CONCLUSIONS: Our study adds to current knowledge on the role of specific inflammatory biomarker pathways in cancer aetiology. Further validation is needed to assess the potential of these cytokines as pharmacological or lifestyle targets for cancer prevention.

Applying Mendelian randomization to appraise causality in relationships between nutrition and cancer.

Dietary factors are assumed to play an important role in cancer risk, apparent in consensus recommendations for cancer prevention that promote nutritional changes. However, the evidence in this field has been generated predominantly through observational studies, which may result in biased effect estimates because of confounding, exposure misclassification, and reverse causality. With major geographical differences and rapid changes in cancer incidence over time, it is crucial to establish which of the observational associations reflect causality and to identify novel risk factors as these may be modified to prevent the onset of cancer and reduce its progression. Mendelian randomization (MR) uses the special properties of germline genetic variation to strengthen causal inference regarding potentially modifiable exposures and disease risk. MR can be implemented through instrumental variable (IV) analysis and, when robustly performed, is generally less prone to confounding, reverse causation and measurement error than conventional observational methods and has different sources of bias (discussed in detail below). It is increasingly used to facilitate causal inference in epidemiology and provides an opportunity to explore the effects of nutritional exposures on cancer incidence and progression in a cost-effective and timely manner. Here, we introduce the concept of MR and discuss its current application in understanding the impact of nutritional factors (e.g., any measure of diet and nutritional intake, circulating biomarkers, patterns, preference or behaviour) on cancer aetiology and, thus, opportunities for MR to contribute to the development of nutritional recommendations and policies for cancer prevention. We provide applied examples of MR studies examining the role of nutritional factors in cancer to illustrate how this method can be used to help prioritise or deprioritise the evaluation of specific nutritional factors as intervention targets in randomised controlled trials. We describe possible biases when using MR, and methodological developments aimed at investigating and potentially overcoming these biases when present. Lastly, we consider the use of MR in identifying causally relevant nutritional risk factors for various cancers in different regions across the world, given notable geographical differences in some cancers. We also discuss how MR results could be translated into further research and policy. We conclude that findings from MR studies, which corroborate those from other well-conducted studies with different and orthogonal biases, are poised to substantially improve our understanding of nutritional influences on cancer. For such corroboration, there is a requirement for an interdisciplinary and collaborative approach to investigate risk factors for cancer incidence and progression.

Statins as Potential Chemoprevention or Therapeutic Agents in Cancer: a Model for Evaluating Repurposed Drugs.

PURPOSE OF REVIEW: Repurposing established medicines for a new therapeutic indication potentially has important global and societal impact. The high costs and slow pace of new drug development have increased interest in more cost-effective repurposed drugs, particularly in the cancer arena. The conventional drug development pathway and evidence framework are not designed for drug repurposing and there is currently no consensus on establishing the evidence base before embarking on a large, resource intensive, potential practice changing phase III randomised controlled trial (RCT). Numerous observational studies have suggested a potential role for statins as a repurposed drug for cancer chemoprevention and therapy, and we review the strength of the cumulative evidence here. RECENT FINDINGS: In the setting of cancer, a potential repurposed drug, like statins, typically goes through a cyclical history, with initial use for several years in another disease setting, prior to epidemiological research identifying a possible chemo-protective effect. However, further information is required, including review of RCT data in the initial disease setting with exploration of cancer outcomes. Additionally, more contemporary methods should be considered, such as Mendelian randomization and pharmaco-epidemiological research with "target" trial design emulation using electronic health records. Pre-clinical and traditional observational data potentially support the role of statins in the treatment of cancer; however, randomised trial evidence is not supportive. Evaluation of contemporary methods provides little added support for the use of statin therapy in cancer. We provide complementary evidence of alternative study designs to enable a robust critical appraisal from a number of sources of the go/no-go decision for a prospective phase III RCT of statins in the treatment of cancer.

Strengthening the Reporting of Observational Studies in Epidemiology Using Mendelian Randomization: The STROBE-MR Statement.

Importance: Mendelian randomization (MR) studies use genetic variation associated with modifiable exposures to assess their possible causal relationship with outcomes and aim to reduce potential bias from confounding and reverse causation. Objective: To develop the STROBE-MR Statement as a stand-alone extension to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guideline for the reporting of MR studies. Design, Setting, and Participants: The development of the STROBE-MR Statement followed the Enhancing the Quality and Transparency of Health Research (EQUATOR) framework guidance and used the STROBE Statement as a starting point to draft a checklist tailored to MR studies. The project was initiated in 2018 by reviewing the literature on the reporting of instrumental variable and MR studies. A group of 17 experts, including MR methodologists, MR study design users, developers of previous reporting guidelines, and journal editors, participated in a workshop in May 2019 to define the scope of the Statement and draft the checklist. The draft checklist was published as a preprint in July 2019 and discussed on the preprint platform, in social media, and at the 4th Mendelian Randomization Conference. The checklist was then revised based on comments, further refined through 2020, and finalized in July 2021. Findings: The STROBE-MR checklist is organized into 6 sections (Title and Abstract, Introduction, Methods, Results, Discussion, and Other Information) and includes 20 main items and 30 subitems. It covers both 1-sample and 2-sample MR studies that assess 1 or multiple exposures and outcomes, and addresses MR studies that follow a genome-wide association study and are reported in the same article. The checklist asks authors to justify why MR is a helpful method to address the study question and state prespecified causal hypotheses. The measurement, quality, and selection of genetic variants must be described and attempts to assess validity of MR-specific assumptions should be well reported. An item on data sharing includes reporting when the data and statistical code required to replicate the analyses can be accessed. Conclusions and Relevance: STROBE-MR provides guidelines for reporting MR studies. Improved reporting of these studies could facilitate their evaluation by editors, peer reviewers, researchers, clinicians, and other readers, and enhance the interpretation of their results.

Mendelian randomisation analysis of circulating adipokines and C-reactive protein on breast cancer risk.

Circulating adipokines and C-reactive protein (CRP) have been linked to breast cancer risk in observational epidemiological studies. The causal nature of these associations is unclear because of the susceptibility of conventional observational designs to residual confounding, reverse causation and other forms of bias. Mendelian randomisation (MR) uses genetic variants as proxies for risk factors to strengthen causal inference in observational settings. We performed a MR analysis to evaluate the causal relevance of six previously reported circulating adipokines [adiponectin, hepatocyte growth factor (HGF), interleukin-6, leptin receptor, plasminogen activator inhibitor-1 and resistin] and CRP in risk of overall and oestrogen receptor-stratified breast cancer in up to 122,977 cases and 105,974 controls of European ancestry. Genetic instruments were constructed from single-nucleotide polymorphisms robustly (p < 5 × 10-8 ) associated with risk factors in genome-wide association studies. Colocalisation was performed as a sensitivity analysis to examine whether findings reflected shared causal variants or genomic confounding. In MR analyses, there was evidence for an association of HGF with oestrogen receptor-negative cancer (odds ratio per standard deviation increase: 1.17, 95% confidence interval: 1.01-1.35; p = 0.035) but little evidence for associations of other adipokines or CRP with overall or oestrogen receptor-stratified breast cancer. Colocalisation analysis suggested that the association of HGF with oestrogen receptor-negative breast cancer was unlikely to reflect a causal association. Collectively, these findings do not support an important aetiological role of various adipokines or CRP in overall or oestrogen receptor-specific breast cancer risk.

Association Between Genetically Proxied Inhibition of HMG-CoA Reductase and Epithelial Ovarian Cancer.

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.

Appraising the role of previously reported risk factors in epithelial ovarian cancer risk: A Mendelian randomization analysis.

BACKGROUND: Various risk factors have been associated with epithelial ovarian cancer risk in observational epidemiological studies. However, the causal nature of the risk factors reported, and thus their suitability as effective intervention targets, is unclear given the susceptibility of conventional observational designs to residual confounding and reverse causation. Mendelian randomization (MR) uses genetic variants as proxies for risk factors to strengthen causal inference in observational studies. We used MR to evaluate the association of 12 previously reported risk factors (reproductive, anthropometric, clinical, lifestyle, and molecular factors) with risk of invasive epithelial ovarian cancer, invasive epithelial ovarian cancer histotypes, and low malignant potential tumours. METHODS AND FINDINGS: Genetic instruments to proxy 12 risk factors were constructed by identifying single nucleotide polymorphisms (SNPs) that were robustly (P < 5 × 10-8) and independently associated with each respective risk factor in previously reported genome-wide association studies. These risk factors included genetic liability to 3 factors (endometriosis, polycystic ovary syndrome, type 2 diabetes) scaled to reflect a 50% higher odds liability to disease. We obtained summary statistics for the association of these SNPs with risk of overall and histotype-specific invasive epithelial ovarian cancer (22,406 cases; 40,941 controls) and low malignant potential tumours (3,103 cases; 40,941 controls) from the Ovarian Cancer Association Consortium (OCAC). The OCAC dataset comprises 63 genotyping project/case-control sets with participants of European ancestry recruited from 14 countries (US, Australia, Belarus, Germany, Belgium, Denmark, Finland, Norway, Canada, Poland, UK, Spain, Netherlands, and Sweden). SNPs were combined into multi-allelic inverse-variance-weighted fixed or random effects models to generate effect estimates and 95% confidence intervals (CIs). Three complementary sensitivity analyses were performed to examine violations of MR assumptions: MR-Egger regression and weighted median and mode estimators. A Bonferroni-corrected P value threshold was used to establish strong evidence (P < 0.0042) and suggestive evidence (0.0042 < P < 0.05) for associations. In MR analyses, there was strong or suggestive evidence that 2 of the 12 risk factors were associated with invasive epithelial ovarian cancer and 8 of the 12 were associated with 1 or more invasive epithelial ovarian cancer histotypes. There was strong evidence that genetic liability to endometriosis was associated with an increased risk of invasive epithelial ovarian cancer (odds ratio [OR] per 50% higher odds liability: 1.10, 95% CI 1.06-1.15; P = 6.94 × 10-7) and suggestive evidence that lifetime smoking exposure was associated with an increased risk of invasive epithelial ovarian cancer (OR per unit increase in smoking score: 1.36, 95% CI 1.04-1.78; P = 0.02). In analyses examining histotypes and low malignant potential tumours, the strongest associations found were between height and clear cell carcinoma (OR per SD increase: 1.36, 95% CI 1.15-1.61; P = 0.0003); age at natural menopause and endometrioid carcinoma (OR per year later onset: 1.09, 95% CI 1.02-1.16; P = 0.007); and genetic liability to polycystic ovary syndrome and endometrioid carcinoma (OR per 50% higher odds liability: 0.89, 95% CI 0.82-0.96; P = 0.002). There was little evidence for an association of genetic liability to type 2 diabetes, parity, or circulating levels of 25-hydroxyvitamin D and sex hormone binding globulin with ovarian cancer or its subtypes. The primary limitations of this analysis include the modest statistical power for analyses of risk factors in relation to some less common ovarian cancer histotypes (low grade serous, mucinous, and clear cell carcinomas), the inability to directly examine the association of some ovarian cancer risk factors that did not have robust genetic variants available to serve as proxies (e.g., oral contraceptive use, hormone replacement therapy), and the assumption of linear relationships between risk factors and ovarian cancer risk. CONCLUSIONS: Our comprehensive examination of possible aetiological drivers of ovarian carcinogenesis using germline genetic variants to proxy risk factors supports a role for few of these factors in invasive epithelial ovarian cancer overall and suggests distinct aetiologies across histotypes. The identification of novel risk factors remains an important priority for the prevention of epithelial ovarian cancer.

Genetic and observational evidence supports a causal role of sex hormones on the development of asthma.

INTRODUCTION: Males have a higher prevalence of asthma in childhood, whereas females have a higher prevalence in adolescence and adulthood. The 'adolescent switch' observed between sexes during puberty has been hypothesised to be due to fluctuating sex hormones. Robust evidence of the involvement of sex hormones in asthma could lead to development of therapeutic interventions. METHODS: We combine observational evidence using longitudinal data on sex hormone-binding globulin (SHBG), total and bioavailable testosterone and asthma from a subset of males (n=512) in the Avon Longitudinal Study of Parents and Children, and genetic evidence of SHBG and asthma using two-sample Mendelian randomisation (MR), a method of causal inference. We meta-analysed two-sample MR results across two large data sets, the Trans-National Asthma Genetics Consortium genome-wide association study of asthma and UK Biobank (over 460 000 individuals combined). RESULTS: Observational evidence indicated weak evidence of a protective effect of increased circulating testosterone on asthma in males in adolescence, but no strong pattern of association with SHBG. Genetic evidence using two-sample MR indicated a protective effect of increased SHBG, with an OR for asthma of 0.86 (95% CI 0.74 to 1.00) for the inverse-variance weighted approach and an OR of 0.83 (95% CI 0.72 to 0.96) for the weighted median estimator, per unit increase in natural log SHBG. A sex-stratified sensitivity analysis suggested the protective effect of SHBG was mostly evident in females. CONCLUSION: We report the first suggestive evidence of a protective effect of genetically elevated SHBG on asthma, which may provide a biological explanation behind the observed asthma sex discordance. Further work is required to disentangle the downstream effects of SHBG on asthma and the molecular pathways involved.

Mendelian randomization does not support serum calcium in prostate cancer risk.

PURPOSE: Observational studies suggest that dietary and serum calcium are risk factors for prostate cancer. However, such studies suffer from residual confounding (due to unmeasured or imprecisely measured confounders), undermining causal inference. Mendelian randomization uses randomly assigned (hence unconfounded and pre-disease onset) germline genetic variation to proxy for phenotypes and strengthen causal inference in observational studies. We tested the hypothesis that serum calcium is associated with an increased risk of overall and advanced prostate cancer. METHODS: A genetic instrument was constructed using five single-nucleotide polymorphisms robustly associated with serum calcium in a genome-wide association study (n ≤ 61,079). This instrument was then used to test the effect of a 0.5 mg/dL increase (1 standard deviation, SD) in serum calcium on risk of prostate cancer in 72,729 men in the PRACTICAL (Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome) Consortium (44,825 cases, 27,904 controls) and risk of advanced prostate cancer in 33,498 men (6,263 cases, 27,235 controls). RESULTS: We found weak evidence for a protective effect of serum calcium on prostate cancer risk (odds ratio [OR] per 0.5 mg/dL increase in calcium: 0.83, 95% CI 0.63-1.08; p = 0.12). We did not find strong evidence for an effect of serum calcium on advanced prostate cancer (OR per 0.5 mg/dL increase in calcium: 0.98, 95% CI 0.57-1.70; p = 0.93). CONCLUSIONS: Our Mendelian randomization analysis does not support the hypothesis that serum calcium increases risk of overall or advanced prostate cancer.

Artificially Sweetened Beverage Consumption Is Positively Associated with Newly Diagnosed Diabetes in Normal-Weight but Not in Overweight or Obese Brazilian Adults.

BACKGROUND: Recent animal studies suggest that artificially sweetened beverage (ASB) consumption increases diabetes risk. OBJECTIVE: We examined the relation of ASB intake with newly diagnosed diabetes and measures of glucose homeostasis in a large Brazilian cohort of adults. METHODS: We used cross-sectional data from 12,884 participants from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). ASB use was assessed by questionnaire and newly diagnosed diabetes by a 2-h 75-g oral glucose tolerance test and/or glycated hemoglobin. Logistic and linear regression analyses were performed to examine the association of ASB consumption with diabetes and continuous measures of glucose homeostasis, respectively. RESULTS: Although ASB consumption was not associated with diabetes in logistic regression analyses after adjustment for body mass index (BMI; in kg/m(2)) overall, the association varied across BMI categories (P-interaction = 0.04). Among those with a BMI <25, we found a 15% increase in the adjusted odds of diabetes for each increase in the frequency of ASB consumption per day (P = 0.001); compared with nonusers, ASB users presented monotonic increases in the adjusted ORs (95% CIs) of diabetes with increased frequency of consumption: 1.03 (0.60, 1.77), 1.43 (0.93, 2.20), 1.62 (1.08, 2.44), and 2.51 (1.40, 4.50) for infrequent, 1-2, 3-4, and >4 times/d, respectively. In linear regression analyses, among normal-weight individuals, greater ASB consumption was also associated with increased fasting glucose concentrations (P = 0.01) and poorer ß-cell function (P = 0.009). No such associations were seen for those with BMI ≥25. In fact, in overweight or obese participants, greater ASB consumption was significantly associated with improved indexes of insulin resistance and 2-h postload glucose. CONCLUSIONS: Normal-weight, but not excess-weight, individuals with greater ASB consumption presented diabetes more frequently and had higher fasting glucose and poorer ß-cell function.

Investigating the causal effect of previously reported therapeutic agents for colorectal cancer prevention: protocol for a Mendelian randomization analysis.

Background: Colorectal cancer (CRC) is the third most common cancer worldwide, with 1.9 million new cases in 2020 and a predicted rise to 3.2 million in 2040. Screening programmes are already in place to aid early detection and secondary prevention of CRC, but the rising prevalence means additional approaches are required in both primary and secondary prevention settings. Preventive therapy, whereby natural or synthetic agents are used to prevent, reverse or delay disease development, could be an effective strategy to further reduce cancer risk and potential agents have already been identified in conventional observational studies. However, as such studies are vulnerable to confounding and reverse causation, we aim to evaluate these observed relationships using Mendelian randomization (MR), an alternative causal inference approach which should be less susceptible to these biases. Methods and analysis: We will use two-sample MR, which uses two independent samples for the exposure and outcome data, to investigate previously reported observational associations of multiple potential preventive agents with CRC risk. We define preventive agents as any synthetic (e.g. approved medication) or natural (e.g. micronutrient, endogenous hormone) molecule used to reduce the risk of cancer. We will first extract potential preventive agents that have been previously linked to CRC risk in observational studies from reviews of the literature. We will then evaluate whether we can develop a genetic instrument for each preventive agent from previously published genome-wide association studies (GWASs) of direct measures of molecular traits (e.g. circulating levels of protein drug targets, blood-based biomarkers of dietary vitamins). The summary statistics from these GWASs, and a large GWAS of CRC, will be used in two-sample MR analyses to investigate the causal effect of putative preventive therapy agents on CRC risk. Sensitivity analyses will be conducted to evaluate the robustness of findings to potential violations of MR assumptions.

Colorectal cancer is the third most common cancer worldwide and the second most common cause of cancer-related death. An individual's chances of surviving the disease are increased if it is caught early or even prevented from developing in the first place. Currently, screening in the UK is offered to everyone over the age of 50 and whilst this can be effective in early cancer detection and secondary prevention, additional prevention strategies are needed to reduce cancer rates. Previous research has investigated whether intake of certain medications, dietary micronutrients or hormones can help prevent colorectal cancer development. There is some evidence to show that taking aspirin can reduce your risk of developing colorectal cancer, however, given potential adverse side effects to taking aspirin (e.g. gastrointestinal bleeding), this medication is not suitable for everyone. We wanted to assess whether other previously identified medications, micronutrients or hormones have any effect on reducing risk of cancer development. If we can identify a compound that could reduce an individual's risk of developing colorectal cancer, it could be used as an additional cancer prevention strategy. We curated a list of potential preventive compounds from previously conducted studies that used observational epidemiological (i.e. non-randomised) methods. Distinguishing statistical correlations from causal relationships when using observational methods can be difficult. This can be due to additional factors in the study affecting both the use of potential preventive compounds and an individual's risk of cancer development (e.g. those taking vitamin supplements having a healthier diet) or the observed relationship may be causal but in the opposite direction (e.g. a cancer diagnosis has a subsequent effect on dietary habits). We will use an alternative epidemiological method, called Mendelian randomization, which uses genetics to attempt to overcome this issue and enable us to determine if a specific compound is reducing cancer risk.

Investigating the association between genetically proxied circulating levels of immune checkpoint proteins and cancer survival: protocol for a Mendelian randomisation analysis.

INTRODUCTION: Compared with the traditional drug development pathway, investigating alternative uses for existing drugs (ie, drug repurposing) requires substantially less time, cost and resources. Immune checkpoint inhibitors are licensed for the treatment of certain breast, colorectal, head and neck, lung and melanoma cancers. These drugs target immune checkpoint proteins to reduce the suppression of T cell activation by cancer cells. As T cell suppression is a hallmark of cancer common across anatomical sites, we hypothesise that immune checkpoint inhibitors could be repurposed for the treatment of additional cancers beyond the ones already indicated. METHODS AND ANALYSIS: We will use two-sample Mendelian randomisation to investigate the effect of genetically proxied levels of protein targets of two immune checkpoint inhibitors-programmed cell death protein 1 and programmed death ligand 1-on survival of seven cancer types (breast, colorectal, head and neck, lung, melanoma, ovarian and prostate). Summary genetic association data will be obtained from prior genome-wide association studies of circulating protein levels and cancer survival in populations of European ancestry. Various sensitivity analyses will be performed to examine the robustness of findings to potential violations of Mendelian randomisation assumptions, collider bias and the impact of alternative genetic instrument construction strategies. The impact of treatment history and tumour stage on the findings will also be investigated using summary-level and individual-level genetic data where available. ETHICS AND DISSEMINATION: No separate ethics approval will be required for these analyses as we will be using data from previously published genome-wide association studies which individually gained ethical approval and participant consent. Results from analyses will be submitted as an open-access peer-reviewed publication and statistical code will be made freely available on the completion of the analysis.