MR-Clust: clustering of genetic variants in Mendelian randomization with similar causal estimates.

MOTIVATION: Mendelian randomization is an epidemiological technique that uses genetic variants as instrumental variables to estimate the causal effect of a risk factor on an outcome. We consider a scenario in which causal estimates based on each variant in turn differ more strongly than expected by chance alone, but the variants can be divided into distinct clusters, such that all variants in the cluster have similar causal estimates. This scenario is likely to occur when there are several distinct causal mechanisms by which a risk factor influences an outcome with different magnitudes of causal effect. We have developed an algorithm MR-Clust that finds such clusters of variants, and so can identify variants that reflect distinct causal mechanisms. Two features of our clustering algorithm are that it accounts for differential uncertainty in the causal estimates, and it includes 'null' and 'junk' clusters, to provide protection against the detection of spurious clusters. RESULTS: Our algorithm correctly detected the number of clusters in a simulation analysis, outperforming methods that either do not account for uncertainty or do not include null and junk clusters. In an applied example considering the effect of blood pressure on coronary artery disease risk, the method detected four clusters of genetic variants. A post hoc hypothesis-generating search suggested that variants in the cluster with a negative effect of blood pressure on coronary artery disease risk were more strongly related to trunk fat percentage and other adiposity measures than variants not in this cluster. AVAILABILITY AND IMPLEMENTATION: MR-Clust can be downloaded from https://github.com/cnfoley/mrclust. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

Coffee Consumption and Cardiovascular Diseases: A Mendelian Randomization Study.

Coffee consumption has been linked to a lower risk of cardiovascular disease in observational studies, but whether the associations are causal is not known. We conducted a Mendelian randomization investigation to assess the potential causal role of coffee consumption in cardiovascular disease. Twelve independent genetic variants were used to proxy coffee consumption. Summary-level data for the relations between the 12 genetic variants and cardiovascular diseases were taken from the UK Biobank with up to 35,979 cases and the FinnGen consortium with up to 17,325 cases. Genetic predisposition to higher coffee consumption was not associated with any of the 15 studied cardiovascular outcomes in univariable MR analysis. The odds ratio per 50% increase in genetically predicted coffee consumption ranged from 0.97 (95% confidence interval (CI), 0.63, 1.50) for intracerebral hemorrhage to 1.26 (95% CI, 1.00, 1.58) for deep vein thrombosis in the UK Biobank and from 0.86 (95% CI, 0.50, 1.49) for subarachnoid hemorrhage to 1.34 (95% CI, 0.81, 2.22) for intracerebral hemorrhage in FinnGen. The null findings remained in multivariable Mendelian randomization analyses adjusted for genetically predicted body mass index and smoking initiation, except for a suggestive positive association for intracerebral hemorrhage (odds ratio 1.91; 95% CI, 1.03, 3.54) in FinnGen. This Mendelian randomization study showed limited evidence that coffee consumption affects the risk of developing cardiovascular disease, suggesting that previous observational studies may have been confounded

Thyroid Function and Dysfunction in Relation to 16 Cardiovascular Diseases.

BACKGROUND: Subclinical thyroid dysfunction, defined as thyroid-stimulating hormone levels outside the reference range with normal free thyroxine levels in asymptomatic patients, is associated with alterations in cardiac hemodynamics. We used Mendelian randomization to assess the role of thyroid dysfunction for cardiovascular disease (CVD). METHODS: Single-nucleotide polymorphisms associated with thyroid function were identified from a genome-wide association meta-analysis in up to 72 167 individuals. Data for genetic associations with CVD were obtained from meta-analyses of genome-wide association studies of atrial fibrillation (n=537 409 individuals), coronary artery disease (n=184 305 individuals), and ischemic stroke (n=438 847) as well as from the UK Biobank (n=367 703 individuals). RESULTS: Genetically predicted thyroid-stimulating hormone levels and hyperthyroidism were statistically significantly associated with atrial fibrillation but no other CVDs at the Bonferroni-corrected level of significance ( P<7.8×10-4). The odds ratios of atrial fibrillation were 1.15 (95% CI, 1.11-1.19; P=2.4×10-14) per genetically predicted 1 SD decrease in thyroid-stimulating hormone levels and 1.05 (95% CI, 1.03-1.08; P=5.4×10-5) for genetic predisposition to hyperthyroidism. Genetically predicted free thyroxin levels were not statistically significantly associated with any CVD. CONCLUSIONS: This Mendelian randomization study supports evidence for a causal association of decreased thyroid-stimulating hormone levels in the direction of a mild form of hyperthyroidism with an increased risk of atrial fibrillation but no other CVDs

Estimating the Population Benefits of Blood Pressure Lowering: A Wide-Angled Mendelian Randomization Study in UK Biobank.

Background The causal relevance of elevated blood pressure for several cardiovascular diseases (CVDs) is uncertain, as is the population impact of blood pressure lowering. This study systematically assesses evidence of causality for various CVDs in a 2-sample Mendelian randomization framework, and estimates the potential reduction in the prevalence of these diseases attributable to long-term population shifts in the distribution of systolic blood pressure (SBP). Methods and Results We investigated associations of genetically predicted SBP as predicted by 256 genetic variants with 21 CVDs in UK Biobank, a population-based cohort of UK residents. The sample consisted of 376 703 participants of European ancestry, aged 40 to 69 years at recruitment. Genetically predicted SBP was positively associated with 14 of the outcomes (P<0.002), including dilated cardiomyopathy, endocarditis, peripheral vascular disease, and rheumatic heart disease. Using genetic variation to estimate the long-term impact of blood pressure lowering on disease in a middle-aged to early late-aged UK-based population, population reductions in SBP were predicted to result in an overall 16.9% (95% CI, 12.2%-21.3%) decrease in morbidity for a 5-mm Hg decrease from a population mean of 137.7 mm Hg, 30.8% (95% CI, 22.8%-38.0%) decrease for a 10-mm Hg decrease, and 56.2% (95% CI, 43.7%-65.9%) decrease for a 22.7-mm Hg decrease in SBP (22.7 mm Hg represents a shift from the current mean SBP to 115 mm Hg). Conclusions Risk of many CVDs is influenced by long-term differences in SBP. The burden of a broad range of CVDs could be substantially reduced by long-term population-wide reductions in the distribution of blood pressure

Insulin-like growth factor-1 and site-specific cancers: A Mendelian randomization study.

Insulin-like growth factor-1 (IGF-1) is involved in several processes relevant to carcinogenesis. We used 416 single-nucleotide polymorphisms robustly associated with serum IGF-1 levels to assess the potential causal associations between this hormone and site-specific cancers through Mendelian randomization. Summary-level genetic association estimates for prostate, breast, ovarian, and lung cancer were obtained from large-scale consortia including individuals of European-descent. Furthermore, we estimated genetic associations with 14 site-specific cancers in European-descent individuals in UK Biobank. Supplementary analyses were conducted for six site-specific cancers using summary-level data from the BioBank Japan Project. Genetically predicted serum IGF-1 levels were associated with colorectal cancer. The odds ratio (OR) per standard deviation increase of IGF-1 levels was 1.11 (95% confidence interval [CI] 1.01-1.22; P = .03) in UK Biobank and 1.22 (95% CI 1.09-1.36; P = 3.9 × 10-4 ) in the BioBank Japan Project. For prostate cancer, the corresponding OR was 1.10 (95% CI 1.01-1.21; P = .04) in UK Biobank, 1.03 (95% CI 0.97-1.09; P = .41) in the prostate cancer consortium, and 1.08 (95% CI 0.95-1.22; P = .24) in the BioBank Japan Project. For breast cancer, the corresponding OR was 0.99 (95% CI 0.92-1.07; P = .85) in UK Biobank and 1.08 (95% CI 1.02-1.13; P = 4.4 × 10-3 ) in the Breast Cancer Association Consortium. There was no statistically significant association between genetically predicted IGF-1 levels and 14 other cancers. This study found some support for a causal association between elevated serum IGF-1 levels and increased risk of colorectal cancer. There was inconclusive or no evidence of a causal association of IGF-1 levels with prostate, breast, and other cancers

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

Funder: National Institute for Health Research; FundRef: http://dx.doi.org/10.13039/501100000272Laboratory studies have suggested oncogenic roles of lipids, as well as anticarcinogenic effects of statins. Here we assess the potential effect of statin therapy on cancer risk using evidence from human genetics. We obtained associations of lipid-related genetic variants with the risk of overall and 22 site-specific cancers for 367,703 individuals in the 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 (odds ratio [OR] per one standard deviation decrease in low-density lipoprotein [LDL] cholesterol 0.76, 95% confidence interval [CI] 0.65–0.88, 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 per standard deviation increase 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

Smoking, alcohol consumption, and cancer: A mendelian randomisation study in UK Biobank and international genetic consortia participants.

BACKGROUND: Smoking is a well-established cause of lung cancer and there is strong evidence that smoking also increases the risk of several other cancers. Alcohol consumption has been inconsistently associated with cancer risk in observational studies. This mendelian randomisation (MR) study sought to investigate associations in support of a causal relationship between smoking and alcohol consumption and 19 site-specific cancers. METHODS AND FINDINGS: We used summary-level data for genetic variants associated with smoking initiation (ever smoked regularly) and alcohol consumption, and the corresponding associations with lung, breast, ovarian, and prostate cancer from genome-wide association studies consortia, including participants of European ancestry. We additionally estimated genetic associations with 19 site-specific cancers among 367,643 individuals of European descent in UK Biobank who were 37 to 73 years of age when recruited from 2006 to 2010. Associations were considered statistically significant at a Bonferroni corrected p-value below 0.0013. Genetic predisposition to smoking initiation was associated with statistically significant higher odds of lung cancer in the International Lung Cancer Consortium (odds ratio [OR] 1.80; 95% confidence interval [CI] 1.59-2.03; p = 2.26 × 10-21) and UK Biobank (OR 2.26; 95% CI 1.92-2.65; p = 1.17 × 10-22). Additionally, genetic predisposition to smoking was associated with statistically significant higher odds of cancer of the oesophagus (OR 1.83; 95% CI 1.34-2.49; p = 1.31 × 10-4), cervix (OR 1.55; 95% CI 1.27-1.88; p = 1.24 × 10-5), and bladder (OR 1.40; 95% CI 1.92-2.65; p = 9.40 × 10-5) and with statistically nonsignificant higher odds of head and neck (OR 1.40; 95% CI 1.13-1.74; p = 0.002) and stomach cancer (OR 1.46; 95% CI 1.05-2.03; p = 0.024). In contrast, there was an inverse association between genetic predisposition to smoking and prostate cancer in the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome consortium (OR 0.90; 95% CI 0.83-0.98; p = 0.011) and in UK Biobank (OR 0.90; 95% CI 0.80-1.02; p = 0.104), but the associations did not reach statistical significance. We found no statistically significant association between genetically predicted alcohol consumption and overall cancer (n = 75,037 cases; OR 0.95; 95% CI 0.84-1.07; p = 0.376). Genetically predicted alcohol consumption was statistically significantly associated with lung cancer in the International Lung Cancer Consortium (OR 1.94; 95% CI 1.41-2.68; p = 4.68 × 10-5) but not in UK Biobank (OR 1.12; 95% CI 0.65-1.93; p = 0.686). There was no statistically significant association between alcohol consumption and any other site-specific cancer. The main limitation of this study is that precision was low in some analyses, particularly for analyses of alcohol consumption and site-specific cancers. CONCLUSIONS: Our findings support the well-established relationship between smoking and lung cancer and suggest that smoking may also be a risk factor for cancer of the head and neck, oesophagus, stomach, cervix, and bladder. We found no evidence supporting a relationship between alcohol consumption and overall or site-specific cancer risk

Is Type 2 Diabetes Causally Associated With Cancer Risk? Evidence From a Two-Sample Mendelian Randomization Study.

We conducted a two-sample Mendelian randomization study to investigate the causal associations of type 2 diabetes mellitus (T2DM) with risk of overall cancer and 22 site-specific cancers. Summary-level data for cancer were extracted from the Breast Cancer Association Consortium and UK Biobank. Genetic predisposition to T2DM was associated with higher odds of pancreatic, kidney, uterine, and cervical cancer and lower odds of esophageal cancer and melanoma but not associated with 16 other site-specific cancers or overall cancer. The odds ratios (ORs) were 1.13 (95% CI 1.04, 1.22), 1.08 (1.00, 1.17), 1.08 (1.01, 1.15), 1.07 (1.01, 1.15), 0.89 (0.81, 0.98), and 0.93 (0.89, 0.97) for pancreatic, kidney, uterine, cervical, and esophageal cancer and melanoma, respectively. The association between T2DM and pancreatic cancer was also observed in a meta-analysis of this and a previous Mendelian randomization study (OR 1.08; 95% CI 1.02, 1.14; P = 0.009). There was limited evidence supporting causal associations between fasting glucose and cancer. Genetically predicted fasting insulin levels were positively associated with cancers of the uterus, kidney, pancreas, and lung. The current study found causal detrimental effects of T2DM on several cancers. We suggest reinforcing the cancer screening in T2DM patients to enable the early detection of cancer