Using genetic association data to guide drug discovery and development: Review of methods and applications.

Evidence on the validity of drug targets from randomized trials is reliable but typically expensive and slow to obtain. In contrast, evidence from conventional observational epidemiological studies is less reliable because of the potential for bias from confounding and reverse causation. Mendelian randomization is a quasi-experimental approach analogous to a randomized trial that exploits naturally occurring randomization in the transmission of genetic variants. In Mendelian randomization, genetic variants that can be regarded as proxies for an intervention on the proposed drug target are leveraged as instrumental variables to investigate potential effects on biomarkers and disease outcomes in large-scale observational datasets. This approach can be implemented rapidly for a range of drug targets to provide evidence on their effects and thus inform on their priority for further investigation. In this review, we present statistical methods and their applications to showcase the diverse opportunities for applying Mendelian randomization in guiding clinical development efforts, thus enabling interventions to target the right mechanism in the right population group at the right time. These methods can inform investigators on the mechanisms underlying drug effects, their related biomarkers, implications for the timing of interventions, and the population subgroups that stand to gain the most benefit. Most methods can be implemented with publicly available data on summarized genetic associations with traits and diseases, meaning that the only major limitations to their usage are the availability of appropriately powered studies for the exposure and outcome and the existence of a suitable genetic proxy for the proposed intervention.

Relaxing parametric assumptions for non-linear Mendelian randomization using a doubly-ranked stratification method.

Non-linear Mendelian randomization is an extension to standard Mendelian randomization to explore the shape of the causal relationship between an exposure and outcome using an instrumental variable. A stratification approach to non-linear Mendelian randomization divides the population into strata and calculates separate instrumental variable estimates in each stratum. However, the standard implementation of stratification, referred to as the residual method, relies on strong parametric assumptions of linearity and homogeneity between the instrument and the exposure to form the strata. If these stratification assumptions are violated, the instrumental variable assumptions may be violated in the strata even if they are satisfied in the population, resulting in misleading estimates. We propose a new stratification method, referred to as the doubly-ranked method, that does not require strict parametric assumptions to create strata with different average levels of the exposure such that the instrumental variable assumptions are satisfied within the strata. Our simulation study indicates that the doubly-ranked method can obtain unbiased stratum-specific estimates and appropriate coverage rates even when the effect of the instrument on the exposure is non-linear or heterogeneous. Moreover, it can also provide unbiased estimates when the exposure is coarsened (that is, rounded, binned into categories, or truncated), a scenario that is common in applied practice and leads to substantial bias in the residual method. We applied the proposed doubly-ranked method to investigate the effect of alcohol intake on systolic blood pressure, and found evidence of a positive effect of alcohol intake, particularly at higher levels of alcohol consumption.

Mild-to-Moderate Kidney Dysfunction and Cardiovascular Disease: Observational and Mendelian Randomization Analyses.

BACKGROUND: End-stage renal disease is associated with a high risk of cardiovascular events. It is unknown, however, whether mild-to-moderate kidney dysfunction is causally related to coronary heart disease (CHD) and stroke. METHODS: Observational analyses were conducted using individual-level data from 4 population data sources (Emerging Risk Factors Collaboration, EPIC-CVD [European Prospective Investigation into Cancer and Nutrition-Cardiovascular Disease Study], Million Veteran Program, and UK Biobank), comprising 648 135 participants with no history of cardiovascular disease or diabetes at baseline, yielding 42 858 and 15 693 incident CHD and stroke events, respectively, during 6.8 million person-years of follow-up. Using a genetic risk score of 218 variants for estimated glomerular filtration rate (eGFR), we conducted Mendelian randomization analyses involving 413 718 participants (25 917 CHD and 8622 strokes) in EPIC-CVD, Million Veteran Program, and UK Biobank. RESULTS: There were U-shaped observational associations of creatinine-based eGFR with CHD and stroke, with higher risk in participants with eGFR values <60 or >105 mL·min-1·1.73 m-2, compared with those with eGFR between 60 and 105 mL·min-1·1.73 m-2. Mendelian randomization analyses for CHD showed an association among participants with eGFR <60 mL·min-1·1.73 m-2, with a 14% (95% CI, 3%-27%) higher CHD risk per 5 mL·min-1·1.73 m-2 lower genetically predicted eGFR, but not for those with eGFR >105 mL·min-1·1.73 m-2. Results were not materially different after adjustment for factors associated with the eGFR genetic risk score, such as lipoprotein(a), triglycerides, hemoglobin A1c, and blood pressure. Mendelian randomization results for stroke were nonsignificant but broadly similar to those for CHD. CONCLUSIONS: In people without manifest cardiovascular disease or diabetes, mild-to-moderate kidney dysfunction is causally related to risk of CHD, highlighting the potential value of preventive approaches that preserve and modulate kidney function.

Morning chronotype and digestive tract cancers: Mendelian randomization study.

Morning chronotype has been associated with a reduced risk of prostate and breast cancer. However, few studies have examined whether chronotype is associated with digestive tract cancer risk. We conducted a Mendelian randomization (MR) study to assess the associations of chronotype with major digestive tract cancers. A total of 317 independent genetic variants associated with chronotype at the genome-wide significance level (P < 5 × 10-8 ) were used as instrumental variables from a genome-wide meta-analysis of 449 734 individuals. Summary-level data on overall and six digestive tract cancers, including esophageal, stomach, liver, biliary tract, pancreatic and colorectal cancers, were obtained from the UK Biobank (11 952 cases) and FinnGen (7638 cases) study. Genetic liability to morning chronotype was associated with reduced risk of overall digestive tract cancer and cancers of stomach, biliary tract and colorectum in UK Biobank. The associations for the overall digestive tract, stomach and colorectal cancers were directionally replicated in FinnGen. In the meta-analysis of the two sources, genetic liability to morning chronotype was associated with a decreased risk of overall digestive tract cancer (odds ratio [OR] 0.94, 95% confidence interval [CI]: 0.90-0.98), stomach cancer (OR 0.84, 95% CI: 0.73-0.97) and colorectal cancer (OR 0.92, 95% CI: 0.87-0.98), but not with the other studied cancers. The associations were consistent in multivariable MR analysis with adjustment for genetically predicted sleep duration, short sleep, insomnia and body mass index. The study provided MR evidence of inverse associations of morning chronotype with digestive tract cancer, particularly stomach and colorectal cancers.

Inconsistency in UK Biobank Event Definitions From Different Data Sources and Its Impact on Bias and Generalizability: A Case Study of Venous Thromboembolism.

The UK Biobank study contains several sources of diagnostic data, including hospital inpatient data and self-reported conditions for ~500,000 participants, and primary care data for ~177,000 participants (35%). Epidemiological investigations require a primary disease definition, but whether to combine sources to maximize power or focus on one to ensure a consistent outcome is not clear. The consistency of definitions was investigated for venous thromboembolism (VTE) by looking at overlap when defining cases from hospital in-patient data, primary care reports, and self-reported questionnaires. VTE cases showed little overlap between data sources, with only 6% of reported events for those with primary care data identified by all three of hospital, primary care, and self-report, while 71% appeared only in one source. Deep vein thrombosis only events represented 68% of self-reported and 36% of hospital-reported VTE cases, while pulmonary embolism only events represented 20% of self-reported and 50% of hospital-reported VTE cases. Additionally, different distributions of sociodemographic characteristics were observed; for example, 46% of hospital reported VTE cases were female, compared with 58% of self-reported VTE cases. These results illustrate how seemingly neutral decisions taken to improve data quality can affect the representativeness of a dataset.

Selenium and cancer risk: Wide-angled Mendelian randomization analysis.

Evidence on the association between selenium and cancer risk is inconclusive. We conducted a Mendelian randomization study to examine the associations of selenium levels with 22 site-specific cancers and any cancer. Single nucleotide polymorphisms (SNPs) strongly associated with toenail and blood (TAB) and blood selenium levels in mild linkage disequilibrium (r2 < .3) were used as instrumental variables. Genetic associations of selenium-associated SNPs with cancer were obtained from the UK Biobank including a total of 59 647 cancer cases and 307 914 controls. Associations with P < .1 in UK Biobank were tested for replication in the FinnGen consortium comprising more than 180 000 individuals. The inverse-variance weighted method accounting for linkage disequilibrium was used to estimate the associations. Genetically predicted TAB selenium levels were not associated with the risk of the 22 site-specific cancers or any cancer (all 22 site-specific cancers). Similarly, we observed no strong association for genetically predicted blood selenium levels. However, genetically predicted blood selenium levels showed suggestive associations with risk of kidney cancer (odds ratio [OR] per one-unit increase in log-transformed levels: 0.83; 95% confidence interval [CI]: 0.67-1.03) and multiple myeloma (OR: 1.40; 95% CI: 1.02-1.93). The same direction of association for kidney cancer but not for multiple myeloma was observed in FinnGen. In the metaanalysis of UK Biobank and FinnGen, the OR of kidney cancer was 0.83 (95% CI: 0.69-1.00). Our study suggests that high selenium status may not prevent cancer development. The associations for kidney cancer and multiple myeloma need to be verified in well-powered studies.

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.

Dose-response relationship between genetically proxied average blood glucose levels and incident coronary heart disease in individuals without diabetes mellitus.

AIMS/HYPOTHESIS: Our aim was to investigate the relationship between average blood glucose levels and incident CHD in individuals without diabetes mellitus. METHODS: To investigate average blood glucose levels, we studied HbA1c as predicted by 40 variants previously shown to be associated with both type 2 diabetes and HbA1c. Linear and non-linear Mendelian randomisation analyses were performed to investigate associations with incident CHD risk in 324,830 European ancestry individuals from the UK Biobank without diabetes mellitus. RESULTS: Every one mmol/mol increase in genetically proxied HbA1c was associated with an 11% higher CHD risk (HR 1.11, 95% CI 1.05, 1.18). The dose-response curve increased at all levels of HbA1c, and there was no evidence favouring a non-linear relationship over a linear one. CONCLUSIONS/INTERPRETATIONS: In individuals without diabetes mellitus, lowering average blood glucose levels may reduce CHD risk in a dose-dependent way.

Metabolic Traits and Stroke Risk in Individuals of African Ancestry: Mendelian Randomization Analysis.

BACKGROUND AND PURPOSE: Metabolic traits affect ischemic stroke (IS) risk, but the degree to which this varies across different ethnic ancestries is not known. Our aim was to apply Mendelian randomization to investigate the causal effects of type 2 diabetes (T2D) liability and lipid traits on IS risk in African ancestry individuals, and to compare them to estimates obtained in European ancestry individuals. METHODS: For African ancestry individuals, genetic proxies for T2D liability and circulating lipids were obtained from a meta-analysis of the African Partnership for Chronic Disease Research study, the UK Biobank, and the Million Veteran Program (total N=77 061). Genetic association estimates for IS risk were obtained from the Consortium of Minority Population Genome-Wide Association Studies of Stroke (3734 cases and 18 317 controls). For European ancestry individuals, genetic proxies for the same metabolic traits were obtained from Million Veteran Program (lipids N=297 626, T2D N=148 726 cases, and 965 732 controls), and genetic association estimates for IS risk were obtained from the MEGASTROKE study (34 217 cases and 406 111 controls). Random-effects inverse-variance weighted Mendelian randomization was used as the main method, complemented with sensitivity analyses more robust to pleiotropy. RESULTS: Higher genetically proxied T2D liability, LDL-C (low-density lipoprotein cholesterol), total cholesterol and lower genetically proxied HDL-C (high-density lipoprotein cholesterol) were associated with increased risk of IS in African ancestry individuals (odds ratio per doubling the odds of T2D liability [95% CI], 1.09 [1.07-1.11]; per standard-deviation increase in LDL-C, 1.12 [1.04-1.21]; total cholesterol: 1.23 [1.06-1.43]; HDL-C, 0.93 [0.89-0.99]). There was no evidence for differences in these estimates when performing analyses in European ancestry individuals. CONCLUSIONS: Our analyses support a causal effect of T2D liability and lipid traits on IS risk in African ancestry individuals, with Mendelian randomization estimates similar to those obtained in European ancestry individuals.

Sleep duration and risk of overall and 22 site-specific cancers: A Mendelian randomization study.

Studies of sleep duration in relation to the risk of site-specific cancers other than breast cancer are scarce. Furthermore, the available results are inconclusive and the causality remains unclear. We aimed to investigate the potential causal associations of sleep duration with overall and site-specific cancers using the Mendelian randomization (MR) design. Single-nucleotide polymorphisms associated with the sleep traits identified from a genome-wide association study were used as instrumental variables to estimate the association with overall cancer and 22 site-specific cancers among 367 586 UK Biobank participants. A replication analysis was performed using data from the FinnGen consortium (up to 121 579 individuals). There was suggestive evidence that genetic liability to short-sleep duration was associated with higher odds of cancers of the stomach (odds ratio [OR], 2.22; 95% confidence interval [CI], 1.15-4.30; P = .018), pancreas (OR, 2.18; 95% CI, 1.32-3.62; P = .002) and colorectum (OR, 1.48; 95% CI, 1.12-1.95; P = .006), but with lower odds of multiple myeloma (OR, 0.47; 95% CI, 0.22-0.99; P = .047). Suggestive evidence of association of genetic liability to long-sleep duration with lower odds of pancreatic cancer (OR, 0.44; 95% CI, 0.25-0.79; P = .005) and kidney cancer (OR, 0.44; 95% CI, 0.21-0.90; P = .025) was observed. However, none of these associations passed the multiple comparison threshold and two-sample MR analysis using FinnGen data did not confirm these findings. In conclusion, this MR study does not provide strong evidence to support causal associations of sleep duration with risk of overall and site-specific cancers. Further MR studies are required.

Body size and composition and risk of site-specific cancers in the UK Biobank and large international consortia: A mendelian randomisation study.

BACKGROUND: Evidence for the impact of body size and composition on cancer risk is limited. This mendelian randomisation (MR) study investigates evidence supporting causal relationships of body mass index (BMI), fat mass index (FMI), fat-free mass index (FFMI), and height with cancer risk. METHODS AND FINDINGS: Single nucleotide polymorphisms (SNPs) were used as instrumental variables for BMI (312 SNPs), FMI (577 SNPs), FFMI (577 SNPs), and height (293 SNPs). Associations of the genetic variants with 22 site-specific cancers and overall cancer were estimated in 367,561 individuals from the UK Biobank (UKBB) and with lung, breast, ovarian, uterine, and prostate cancer in large international consortia. In the UKBB, genetically predicted BMI was positively associated with overall cancer (odds ratio [OR] per 1 kg/m2 increase 1.01, 95% confidence interval [CI] 1.00-1.02; p = 0.043); several digestive system cancers: stomach (OR 1.13, 95% CI 1.06-1.21; p < 0.001), esophagus (OR 1.10, 95% CI 1.03, 1.17; p = 0.003), liver (OR 1.13, 95% CI 1.03-1.25; p = 0.012), and pancreas (OR 1.06, 95% CI 1.01-1.12; p = 0.016); and lung cancer (OR 1.08, 95% CI 1.04-1.12; p < 0.001). For sex-specific cancers, genetically predicted elevated BMI was associated with an increased risk of uterine cancer (OR 1.10, 95% CI 1.05-1.15; p < 0.001) and with a lower risk of prostate cancer (OR 0.97, 95% CI 0.94-0.99; p = 0.009). When dividing cancers into digestive system versus non-digestive system, genetically predicted BMI was positively associated with digestive system cancers (OR 1.04, 95% CI 1.02-1.06; p < 0.001) but not with non-digestive system cancers (OR 1.01, 95% CI 0.99-1.02; p = 0.369). Genetically predicted FMI was positively associated with liver, pancreatic, and lung cancer and inversely associated with melanoma and prostate cancer. Genetically predicted FFMI was positively associated with non-Hodgkin lymphoma and melanoma. Genetically predicted height was associated with increased risk of overall cancer (OR per 1 standard deviation increase 1.09; 95% CI 1.05-1.12; p < 0.001) and multiple site-specific cancers. Similar results were observed in analyses using the weighted median and MR-Egger methods. Results based on consortium data confirmed the positive associations between BMI and lung and uterine cancer risk as well as the inverse association between BMI and prostate cancer, and, additionally, showed an inverse association between genetically predicted BMI and breast cancer. The main limitations are the assumption that genetic associations with cancer outcomes are mediated via the proposed risk factors and that estimates for some lower frequency cancer types are subject to low precision. CONCLUSIONS: Our results show that the evidence for BMI as a causal risk factor for cancer is mixed. We find that BMI has a consistent causal role in increasing risk of digestive system cancers and a role for sex-specific cancers with inconsistent directions of effect. In contrast, increased height appears to have a consistent risk-increasing effect on overall and site-specific cancers.

The potential shared role of inflammation in insulin resistance and schizophrenia: A bidirectional two-sample mendelian randomization study.

BACKGROUND: Insulin resistance predisposes to cardiometabolic disorders, which are commonly comorbid with schizophrenia and are key contributors to the significant excess mortality in schizophrenia. Mechanisms for the comorbidity remain unclear, but observational studies have implicated inflammation in both schizophrenia and cardiometabolic disorders separately. We aimed to examine whether there is genetic evidence that insulin resistance and 7 related cardiometabolic traits may be causally associated with schizophrenia, and whether evidence supports inflammation as a common mechanism for cardiometabolic disorders and schizophrenia. METHODS AND FINDINGS: We used summary data from genome-wide association studies of mostly European adults from large consortia (Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) featuring up to 108,557 participants; Diabetes Genetics Replication And Meta-analysis (DIAGRAM) featuring up to 435,387 participants; Global Lipids Genetics Consortium (GLGC) featuring up to 173,082 participants; Genetic Investigation of Anthropometric Traits (GIANT) featuring up to 339,224 participants; Psychiatric Genomics Consortium (PGC) featuring up to 105,318 participants; and Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium featuring up to 204,402 participants). We conducted two-sample uni- and multivariable mendelian randomization (MR) analysis to test whether (i) 10 cardiometabolic traits (fasting insulin, high-density lipoprotein and triglycerides representing an insulin resistance phenotype, and 7 related cardiometabolic traits: low-density lipoprotein, fasting plasma glucose, glycated haemoglobin, leptin, body mass index, glucose tolerance, and type 2 diabetes) could be causally associated with schizophrenia; and (ii) inflammation could be a shared mechanism for these phenotypes. We conducted a detailed set of sensitivity analyses to test the assumptions for a valid MR analysis. We did not find statistically significant evidence in support of a causal relationship between cardiometabolic traits and schizophrenia, or vice versa. However, we report that a genetically predicted inflammation-related insulin resistance phenotype (raised fasting insulin (raised fasting insulin (Wald ratio OR = 2.95, 95% C.I, 1.38-6.34, Holm-Bonferroni corrected p-value (p) = 0.035) and lower high-density lipoprotein (Wald ratio OR = 0.55, 95% C.I., 0.36-0.84; p = 0.035)) was associated with schizophrenia. Evidence for these associations attenuated to the null in multivariable MR analyses after adjusting for C-reactive protein, an archetypal inflammatory marker: (fasting insulin Wald ratio OR = 1.02, 95% C.I, 0.37-2.78, p = 0.975), high-density lipoprotein (Wald ratio OR = 1.00, 95% C.I., 0.85-1.16; p = 0.849), suggesting that the associations could be fully explained by inflammation. One potential limitation of the study is that the full range of gene products from the genetic variants we used as proxies for the exposures is unknown, and so we are unable to comment on potential biological mechanisms of association other than inflammation, which may also be relevant. CONCLUSIONS: Our findings support a role for inflammation as a common cause for insulin resistance and schizophrenia, which may at least partly explain why the traits commonly co-occur in clinical practice. Inflammation and immune pathways may represent novel therapeutic targets for the prevention or treatment of schizophrenia and comorbid insulin resistance. Future work is needed to understand how inflammation may contribute to the risk of schizophrenia and insulin resistance.

Genetically predicted circulating B vitamins in relation to digestive system cancers.

BACKGROUND: Folate, vitamin B6 and vitamin B12 have been associated with digestive system cancers. We conducted a two-sample Mendelian randomisation study to assess the causality of these associations. METHODS: Two, one and 14 independent single nucleotide polymorphisms associated with serum folate, vitamin B6 and vitamin B12 at the genome-wide significance threshold were selected as genetic instruments. Summary-level data for the associations of the vitamin-associated genetic variants with cancer were obtained from the UK Biobank study including 367,561 individuals and FinnGen consortium comprising up to 176,899 participants. RESULTS: Genetically predicted folate and vitamin B6 concentrations were not associated with overall cancer, overall digestive system cancer or oesophageal, gastric, colorectal or pancreatic cancer. Genetically predicted vitamin B12 concentrations were positively associated with overall digestive system cancer (ORSD, 1.12; 95% CI 1.04, 1.21, p = 0.003) and colorectal cancer (ORSD 1.16; 95% CI 1.06, 1.26, p = 0.001) in UK Biobank. Results for colorectal cancer were consistent in FinnGen and the combined ORSD was 1.16 (95% CI 1.08, 1.25, p < 0.001). There was no association of genetically predicted vitamin B12 with any other site-specific digestive system cancers or overall cancer. CONCLUSIONS: These results provide evidence to suggest that elevated serum vitamin B12 concentrations are associated with colorectal cancer.

Homocysteine, B vitamins, and cardiovascular disease: a Mendelian randomization study.

BACKGROUND: Whether a modestly elevated homocysteine level is causally associated with an increased risk of cardiovascular disease remains unestablished. We conducted a Mendelian randomization study to assess the associations of circulating total homocysteine (tHcy) and B vitamin levels with cardiovascular diseases in the general population. METHODS: Independent single nucleotide polymorphisms associated with tHcy (n = 14), folate (n = 2), vitamin B6 (n = 1), and vitamin B12 (n = 14) at the genome-wide significance level were selected as instrumental variables. Summary-level data for 12 cardiovascular endpoints were obtained from genetic consortia, the UK Biobank study, and the FinnGen consortium. RESULTS: Higher genetically predicted circulating tHcy levels were associated with an increased risk of stroke. For each one standard deviation (SD) increase in genetically predicted tHcy levels, the odds ratio (OR) was 1.11 (95% confidence interval (CI), 1.03, 1.21; p = 0.008) for any stroke, 1.26 (95% CI, 1.05, 1.51; p = 0.013) for subarachnoid hemorrhage, and 1.11 (95% CI, 1.03, 1.21; p = 0.011) for ischemic stroke. Higher genetically predicted folate levels were associated with decreased risk of coronary artery disease (ORSD, 0.88; 95% CI, 0.78, 1.00, p = 0.049) and any stroke (ORSD, 0.86; 95% CI, 0.76, 0.97, p = 0.012). Genetically predicted increased vitamin B6 levels were associated with a reduced risk of ischemic stroke (ORSD, 0.88; 95% CI, 0.81, 0.97, p = 0.009). None of these associations persisted after multiple testing correction. There was no association between genetically predicted vitamin B12 and cardiovascular disease. CONCLUSIONS: This study reveals suggestive evidence that B vitamin therapy and lowering of tHcy may reduce the risk of stroke, particularly subarachnoid hemorrhage and ischemic stroke.

Shared mechanisms between coronary heart disease and depression: findings from a large UK general population-based cohort.

While comorbidity between coronary heart disease (CHD) and depression is evident, it is unclear whether the two diseases have shared underlying mechanisms. We performed a range of analyses in 367,703 unrelated middle-aged participants of European ancestry from UK Biobank, a population-based cohort study, to assess whether comorbidity is primarily due to genetic or environmental factors, and to test whether cardiovascular risk factors and CHD are likely to be causally related to depression using Mendelian randomization. We showed family history of heart disease was associated with a 20% increase in depression risk (95% confidence interval [CI] 16-24%, p < 0.0001), but a genetic risk score that is strongly associated with CHD risk was not associated with depression. An increase of 1 standard deviation in the CHD genetic risk score was associated with 71% higher CHD risk, but 1% higher depression risk (95% CI 0-3%; p = 0.11). Mendelian randomization analyses suggested that triglycerides, interleukin-6 (IL-6), and C-reactive protein (CRP) are likely causal risk factors for depression. The odds ratio for depression per standard deviation increase in genetically-predicted triglycerides was 1.18 (95% CI 1.09-1.27; p = 2 × 10-5); per unit increase in genetically-predicted log-transformed IL-6 was 0.74 (95% CI 0.62-0.89; p = 0.0012); and per unit increase in genetically-predicted log-transformed CRP was 1.18 (95% CI 1.07-1.29; p = 0.0009). Our analyses suggest that comorbidity between depression and CHD arises largely from shared environmental factors. IL-6, CRP and triglycerides are likely to be causally linked with depression, so could be targets for treatment and prevention of depression.

Genetic liability to insomnia in relation to cardiovascular diseases: a Mendelian randomisation study.

The present study aimed to determine the associations between insomnia and cardiovascular diseases (CVDs) using Mendelian randomisation (MR) analysis. As instrumental variables, we used 208 independent single-nucleotide polymorphisms associated with insomnia at the genome-wide significance threshold in a meta-analysis of genome-wide association studies in the UK Biobank and 23andMe including a total of 397 959 self-reported insomnia cases and 933 057 non-cases. Summary-level data for nine CVDs were obtained from the UK Biobank including 367 586 individuals of European ancestry. After correction for multiple testing, genetic liability to insomnia was associated with higher odds of six CVDs, including peripheral arterial disease (odd ratio (OR) 1.22; 95% confidence interval (CI), 1.21, 1.33), heart failure (OR 1.21; 95% CI, 1.13, 1.30), coronary artery disease (OR 1.19; 95% CI, 1.14, 1.25), ischaemic stroke (OR 1.15; 95% CI, 1.06, 1.25), venous thromboembolism (OR 1.13; 95% CI, 1.07, 1.19) and atrial fibrillation (OR 1.10; 95% CI, 1.05, 1.15). There were suggestive associations for aortic valve stenosis (OR, 1.17; 95% CI, 1.04, 1.32) and haemorrhagic stroke (OR 1.14; 95% CI, 1.00, 1.29) but no association for abdominal aortic aneurysm (OR, 1.14, 95% CI, 0.98, 1.33). The patterns of associations remained with mild attenuation in multivariable MR analyses adjusting for genetically correlated phenotypes and potential mediators, including sleep duration, depression, body mass index, type 2 diabetes and smoking. The present MR study suggests potential causal associations of genetic liability to insomnia with increased risk of a broad range of CVDs.

Body mass index and body composition in relation to 14 cardiovascular conditions in UK Biobank: a Mendelian randomization study.

AIMS: The causal role of adiposity for several cardiovascular diseases (CVDs) is unclear. Our primary aim was to apply the Mendelian randomization design to investigate the associations of body mass index (BMI) with 13 CVDs and arterial hypertension. We also assessed the roles of fat mass and fat-free mass on the same outcomes. METHODS AND RESULTS: Single-nucleotide polymorphisms associated with BMI and fat mass and fat-free mass indices were used as instrumental variables to estimate the associations with the cardiovascular conditions among 367 703 UK Biobank participants. After correcting for multiple testing, genetically predicted BMI was significantly positively associated with eight outcomes, including and with decreasing magnitude of association: aortic valve stenosis, heart failure, deep vein thrombosis, arterial hypertension, peripheral artery disease, coronary artery disease, atrial fibrillation, and pulmonary embolism. The odds ratio (OR) per 1 kg/m2 increase in BMI ranged from 1.06 [95% confidence interval (CI) 1.02-1.11; P = 2.6 × 10-3] for pulmonary embolism to 1.13 (95% CI 1.05-1.21; P = 1.2 × 10-3) for aortic valve stenosis. There was suggestive evidence of positive associations of genetically predicted fat mass index with nine outcomes (P < 0.05). The strongest magnitude of association was with aortic valve stenosis (OR per 1 kg/m2 increase in fat mass index 1.46, 95% CI 1.13-1.88; P = 3.9 × 10-3). There was suggestive evidence of inverse associations of fat-free mass index with atrial fibrillation, ischaemic stroke, and abdominal aortic aneurysm. CONCLUSION: This study provides evidence that higher BMI and particularly fat mass index are associated with increased risk of aortic valve stenosis and most other cardiovascular conditions.

Genetic predisposition to smoking in relation to 14 cardiovascular diseases.

AIMS: The aim of this study was to use Mendelian randomization (MR) to determine the causality of the association between smoking and 14 different cardiovascular diseases (CVDs). METHODS AND RESULTS: Our primary genetic instrument comprised 361 single-nucleotide polymorphisms (SNPs) associated with smoking initiation (ever smoked regularly) at genome-wide significance. Data on the associations between the SNPs and 14 CVDs were obtained from the UK Biobank study (N = 367 643 individuals), CARDIoGRAMplusC4D consortium (N = 184 305 individuals), Atrial Fibrillation Consortium (2017 dataset; N = 154 432 individuals), and Million Veteran Program (MVP; N = 190 266 individuals). The main analyses were conducted using the random-effects inverse-variance weighted method and complemented with multivariable MR analyses and the weighted median and MR-Egger approaches. Genetic predisposition to smoking initiation was most strongly and consistently associated with higher odds of coronary artery disease, heart failure, abdominal aortic aneurysm, ischaemic stroke, transient ischaemic attack, peripheral arterial disease, and arterial hypertension. Genetic predisposition to smoking initiation was additionally associated with higher odds of deep vein thrombosis and pulmonary embolism in the UK Biobank but not with venous thromboembolism in the MVP. There was limited evidence of causal associations of smoking initiation with atrial fibrillation, aortic valve stenosis, thoracic aortic aneurysm, and intracerebral and subarachnoid haemorrhage. CONCLUSION: This MR study supports a causal association between smoking and a broad range of CVDs, in particular, coronary artery disease, heart failure, abdominal aortic aneurysm, ischaemic stroke, transient ischaemic attack, peripheral arterial disease, and arterial hypertension.

Causal associations of thyroid function and dysfunction with overall, breast and thyroid cancer: A two-sample Mendelian randomization study.

Whether thyroid dysfunction plays a causal role in the development of cancer remains inconclusive. We conducted a two-sample Mendelian randomization study to investigate the associations between genetic predisposition to thyroid dysfunction and 22 site-specific cancers. Single-nucleotide polymorphisms associated with four traits of thyroid function were selected from a genome-wide association meta-analysis with up to 72,167 European-descent individuals. Summary-level data for breast cancer and 21 other cancers were extracted from the Breast Cancer Association Consortium (122,977 breast cancer cases and 105,974 controls) and UK Biobank (367,643 individuals). For breast cancer, a meta-analysis was performed using data from both sources. Genetically predicted thyroid dysfunction was associated with breast cancer, with similar patterns of associations in the Breast Cancer Association Consortium and UK Biobank. The combined odds ratios of breast cancer were 0.94 (0.91-0.98; p = 0.007) per genetically predicted one standard deviation increase in TSH levels, 0.96 (0.91-1.00; p = 0.053) for genetic predisposition to hypothyroidism, 1.04 (1.01-1.07; p = 0.005) for genetic predisposition to hyperthyroidism and 1.07 (1.02-1.12; p = 0.003) per genetically predicted one standard deviation increase in free thyroxine levels. Genetically predicted TSH levels and hypothyroidism were inversely with thyroid cancer; the odds ratios were 0.47 (0.30-0.73; p = 0.001) and 0.70 (0.51-0.98; p = 0.038), respectively. Our study provides evidence of a causal association between thyroid dysfunction and breast cancer (mainly ER-positive tumors) risk. The role of TSH and hypothyroidism for thyroid cancer and the associations between thyroid dysfunction and other cancers need further exploration.

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.