Testing for non-linear causal effects using a binary genotype in a Mendelian randomization study: application to alcohol and cardiovascular traits

Alcohol consumption and its association with cancer, cardiovascular, liver and brain diseases: a systematic review of Mendelian randomization studies

Background

The health effects of alcohol consumption, particularly regarding potential protective benefits of light to moderate intake compared to abstinence, remain a subject of ongoing debate. However, epidemiological studies face limitations due to imprecise exposure measurements and the potential for bias through residual confounding and reverse causation. To address these limitations, we conducted a systematic review of Mendelian Randomization (MR) studies examining the causal relationship between alcohol consumption and cancers, cardiovascular, liver, and neurological diseases.

Methodology

We searched PubMed, ScienceDirect and Embase and Europe PMC up to 05/2024 for MR studies investigating the association of genetically predicted alcohol consumption with cancers, cardiovascular, liver and neurological diseases. We assessed methodological quality based on key elements of the MR design a genetic association studies tool.

Results

We included 70 MR studies that matched our inclusion criteria. Our review showed a significant association of alcohol consumption with multiple cancers such as oral and oropharyngeal, esophageal, colorectal cancers, hepatocellular carcinoma and cutaneous melanoma. While the available studies did not consistently confirm the adverse or protective effects of alcohol on other cancers, such as lung cancer, as suggested by observational studies. Additionally, MR studies confirmed a likely causal effect of alcohol on the risk of hypertension, atrial fibrillation, myocardial infraction and vessels disease. However, there was no evidence to support the protective effects of light to moderate alcohol consumption on cognitive function, Alzheimer's disease, and amyotrophic lateral sclerosis, as reported in observational studies while our review revealed an increased risk of epilepsy and multiple sclerosis. The available studies provided limited results on the link between alcohol consumption and liver disease.

Conclusions

Despite the valuable insights into the causal relationship between alcohol consumption and various health outcomes that MR studies provided, it is worth noting that the inconsistent ability of genetic instrumental variables to distinguish between abstainers, light and moderate drinkers makes it difficult to differentiate between U or J-shaped vs. linear relationships between exposure and outcome. Additional research is necessary to establish formal quality assessment tools for MR studies and to conduct more studies in diverse populations, including non-European ancestries.

Systematic Review Registration

www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021246154, Identifier: PROSPERO (CRD42021246154).

Non-linear Mendelian randomization: detection of biases using negative controls with a focus on BMI, Vitamin D and LDL cholesterol

Mendelian randomisation (MR) is an established technique in epidemiological investigation, using the principle of random allocation of genetic variants at conception to estimate the causal linear effect of an exposure on an outcome. Extensions to this technique include non-linear approaches that allow for differential effects of the exposure on the outcome depending on the level of the exposure. A widely used non-linear method is the residual approach, which estimates the causal effect within different strata of the non-genetically predicted exposure (i.e. the "residual" exposure). These "local" causal estimates are then used to make inferences about non-linear effects. Recent work has identified that this method can lead to estimates that are seriously biased, and a new method-the doubly-ranked method-has been introduced as a possibly more robust approach. In this paper, we perform negative control outcome analyses in the MR context. These are analyses with outcomes onto which the exposure should have no predicted causal effect. Using both methods we find clearly biased estimates in certain situations. We additionally examined a situation for which there are robust randomised controlled trial estimates of effects-that of low-density lipoprotein cholesterol (LDL-C) reduction onto myocardial infarction, where randomised trials have provided strong evidence of the shape of the relationship. The doubly-ranked method did not identify the same shape as the trial data, and for LDL-C and other lipids they generated some highly implausible findings. Therefore, we suggest there should be extensive simulation and empirical methodological examination of performance of both methods for NLMR under different conditions before further use of these methods. In the interim, use of NLMR methods needs justification, and a number of sanity checks (such as analysis of negative and positive control outcomes, sensitivity analyses excluding removal of strata at the extremes of the distribution, examination of biological plausibility and triangulation of results) should be performed.

Is low-level alcohol consumption really health-protective? A critical review of approaches to promote causal inference and recent applications

Heavy and disordered alcohol consumption is a known risk factor for several health conditions and is associated with considerable disease burden. However, at low-to-moderate levels, evidence suggests that drinking is associated with reduced risk for certain health outcomes. Whether these findings represent genuine protective effects or mere methodological artifacts remains unclear, but has substantial consequences for policy and practice. This critical review introduces methodological advances capable of enhancing causal inference from observational research, focusing on the 'G-methods' and Mendelian Randomization. We also present and evaluate recent research applying these methods and compare findings to the existing evidence base. Future directions are proposed for improving our causal understanding of the relationships between alcohol and long-term health outcomes.

Association between alcohol consumption and sleep traits: observational and mendelian randomization studies in the UK biobank

Previous studies have shown that excessive alcohol consumption is associated with poor sleep. However, the health risks of light-to-moderate alcohol consumption in relation to sleep traits (e.g., insomnia, snoring, sleep duration and chronotype) remain undefined, and their causality is still unclear in the general population. To identify the association between alcohol consumption and multiple sleep traits using an observational and Mendelian randomization (MR) design. Observational analyses and one-sample MR (linear and nonlinear) were performed using clinical and individual-level genetic data from the UK Biobank (UKB). Two-sample MR was assessed using summary data from genome-wide association studies from the UKB and other external consortia. Phenotype analyses were externally validated using data from the National Health and Nutrition Examination Survey (2017-2018). Data analysis was conducted from January 2022 to October 2022. The association between alcohol consumption and six self-reported sleep traits (short sleep duration, long sleep duration, chronotype, snoring, waking up in the morning, and insomnia) were analysed. This study included 383,357 UKB participants (mean [SD] age, 57.0 [8.0] years; 46% male) who consumed a mean (SD) of 9.0 (10.0) standard drinks (one standard drink equivalent to 14 g of alcohol) per week. In the observational analyses, alcohol consumption was significantly associated with all sleep traits. Light-moderate-heavy alcohol consumption was linearly linked to snoring and the evening chronotype but nonlinearly associated with insomnia, sleep duration, and napping. In linear MR analyses, a 1-SD (14 g) increase in genetically predicted alcohol consumption was associated with a 1.14-fold (95% CI, 1.07-1.22) higher risk of snoring (P < 0.001), a 1.28-fold (95% CI, 1.20-1.37) higher risk of evening chronotype (P < 0.001) and a 1.24-fold (95% CI, 1.13-1.36) higher risk of difficulty waking up in the morning (P < 0.001). Nonlinear MR analyses did not reveal significant results after Bonferroni adjustment. The results of the two-sample MR analyses were consistent with those of the one-sample MR analyses, but with a slightly attenuated overall estimate. Our findings suggest that even low levels of alcohol consumption may affect sleep health, particularly by increasing the risk of snoring and evening chronotypes. The negative effects of alcohol consumption on sleep should be made clear to the public in order to promote public health.

A comprehensive evaluation of the longitudinal association between alcohol consumption and a measure of inflammation: Multiverse and vibration of effects analyses

BACKGROUND

Moderate alcohol consumption appears to be associated with reduced inflammation. Determining whether this association is robust to common variations in research parameters has wide-reaching implications for our understanding of disease aetiology and public health policy. We aimed to conduct comprehensive multiverse and vibration of effects analyses evaluating the associations between alcohol consumption and a measure of inflammation.

METHODS

A secondary analysis of the 1970 British Birth Cohort Study was performed, using data from 1970 through 2016. Measurements of alcohol consumption were taken in early/mid-adulthood (ages 34 and 42), and level of inflammation marker high-sensitivity C-reactive protein (hsCRP) at age 46. Multiverse analyses were applied to comparisons of low-to-moderate consumption and consumption above various international drinking guidelines with an 'abstinent' reference. Research parameters of interest related to: definitions of drinking and reference groups; alcohol consumption measurement year; outcome variable transformation; and breadth of covariate adjustment. After identifying various analytic options within these parameters and running the analysis over each unique option combination, specification curve plots, volcano plots, effect ranges, and variance decomposition metrics were used to assess consistency of results.

RESULTS

A total of 3101 individuals were included in the final analyses, with primary analyses limited to those where occasional consumers served as reference. All combinations of research specifications resulted in lower levels of inflammation amongst low-to-moderate consumers compared to occasional consumers (1st percentile effect: -0.21; 99th percentile effect: -0.04). Estimates comparing above-guidelines drinking with occasional consumers were less definitive (1st percentile effect: -0.26; 99th percentile effect: 0.43).

CONCLUSIONS

The association between low-to-moderate drinking and lower hsCRP levels is largely robust to common variations in researcher-defined parameters, warranting further research to establish whether this relationship is causal. The association between above-guidelines drinking and hsCRP levels is less definitive.

Cardiac MRI to guide heart failure and atrial fibrillation drug discovery: a Mendelian randomization analysis

Background

drug development and disease prevention of heart failure (HF) and atrial fibrillation (AF) are impeded by a lack of robust early-stage surrogates. We determined to what extent cardiac magnetic resonance (CMR) measurements act as surrogates for the development of HF or AF in healthy individuals.

Methods

Genetic data was sourced on the association with 22 atrial and ventricular CMR measurements. Mendelian randomization was used to determine CMR associations with atrial fibrillation (AF), heart failure (HF), non-ischemic cardiomyopathy (CMP), and dilated cardiomyopathy (DCM). Additionally, for the CMR surrogates of AF and HF, we explored their association with non-cardiac traits.

Results

In total we found that 9 CMR measures were associated with the development of HF, 7 with development of non-ischemic CMR, 6 with DCM, and 12 with AF. biventricular ejection fraction (EF), biventricular or end-systolic volumes (ESV) and left-ventricular (LV) end diastolic volume (EDV) were associated with all 4 cardiac outcomes. Increased LV-MVR (mass to volume ratio) affected HF (odds ratio (OR) 0.83, 95%CI 0.79; 0.88), and DCM (OR 0.26, 95%CI 0.20; 0.34. We were able to identify 9 CMR surrogates for HF and/or AF (including LV-MVR, biventricular EDV, ESV, and right-ventricular EF) which associated with non-cardiac traits such as blood pressure, lung function traits, BMI, cardioembolic stroke, and late-onset Alzheimer's disease.

Conclusion

CMR measurements may act as surrogate endpoints for the development of HF (including non-ischemic CMP and DCM) or AF. Additionally, we show that changes in cardiac function and structure measured through CMR, may affect diseases of other organs leading to lung disease or late-onset Alzheimer's disease.

Investigating the causal relationships between excess adiposity and cardiometabolic health in men and women

AIMS/HYPOTHESIS

Excess adiposity is differentially associated with increased risk of cardiometabolic disease in men and women, according to observational studies. Causal inference studies largely assume a linear relationship between BMI and cardiometabolic outcomes, which may not be the case. In this study, we investigated the shapes of the causal relationships between BMI and cardiometabolic diseases and risk factors. We further investigated sex differences within the causal framework.

METHODS

To assess causal relationships between BMI and the outcomes, we used two-stage least-squares Mendelian randomisation (MR), with a polygenic risk score for BMI as the instrumental variable. To elucidate the shapes of the causal relationships, we used a non-linear MR fractional polynomial method, and used piecewise MR to investigate threshold relationships and confirm the shapes.

RESULTS

BMI was associated with type 2 diabetes (OR 3.10; 95% CI 2.73, 3.53), hypertension (OR 1.53; 95% CI 1.44, 1.62) and coronary artery disease (OR 1.20; 95% CI 1.08, 1.33), but not chronic kidney disease (OR 1.08; 95% CI 0.67, 1.72) or stroke (OR 1.08; 95% CI 0.92, 1.28). The data suggest that these relationships are non-linear. For cardiometabolic risk factors, BMI was positively associated with glucose, HbA1c, triacylglycerol levels and both systolic and diastolic BP. BMI had an inverse causal relationship with total cholesterol, LDL-cholesterol and HDL-cholesterol. The data suggest a non-linear causal relationship between BMI and BP and other biomarkers (p<0.001) except lipoprotein A. The piecewise MR results were consistent with the fractional polynomial results. The causal effect of BMI on coronary artery disease, total cholesterol and LDL-cholesterol was different in men and women, but this sex difference was only significant for LDL-cholesterol after controlling for multiple testing (p<0.001). Further, the causal effect of BMI on coronary artery disease varied by menopause status in women.

CONCLUSIONS/INTERPRETATION

We describe the shapes of causal effects of BMI on cardiometabolic diseases and risk factors, and report sex differences in the causal effects of BMI on LDL-cholesterol. We found evidence of non-linearity in the causal effect of BMI on diseases and risk factor biomarkers. Reducing excess adiposity is highly beneficial for health, but there is greater need to consider biological sex in the management of adiposity.

Age at menarche and ischemic heart disease: An update mendelian randomization study

Background: Although earlier menarche age has been associated with ischemic heart disease in previous observational studies, the relationship's causation has not been shown. Through two-sample Mendelian randomization (MR), we were able to define the causal connection. Methods: We performed Mendelian Randomization (MR) analysis to explore the associations between genetically predicted AAM and IHD. Summary-level databases for exposure and outcome were selected from the MR-Base database (https://gwas.mrcieu.ac.uk/). Single-nucleotide polymorphisms (SNPs) connected to AAM at genome-wide significance level (p < 5 × 10-8) were considered as instrumental variables (IVs). We used four methods to pool MR estimates, including fixed-effects inverse variance weighting (fe-IVW), multiplicative random-effects inverse variance weighting (mre-IVW), weighted median (WM), and MR-Egger regression methods. Sensitivity analyses were performed to evaluate the robustness of the results. PhenoScanner searches and Multivariable Mendelian randomization (MVMR) analysis was used for assessing confounders. Results: 117 SNPs significantly correlated with AAM were screened as instruments, the results of three main methods showed that genetically earlier AAM may have a causal effect on the higher risk of IHD (fe-IVW: OR = 0.80, 95% CI: 0.72-0.88, p < 0.001; mre-IVW: OR = 0.80, 95% CI: 0.70-0.90, p < 0.001; WE: OR = 0.79, 95% CI: 0.66-0.93, p = 0.006). These results were consistent across sensitivity analyses. MR analysis revealed that there was still a relationship between AAM and IHD even when pleiotropic SNPs of confounders were removed employing PhenoScanner searches. In MVMR, the significant association remained after adjusting for biological sex, but it was attenuated with adjustment of body mass index including childhood and adult. Conclusion: Our MR analysis revealed a substantial genetically determined confounder-mediated relationship between an increase in genetically predicted AAM and a lower risk of IHD. By addressing the intervention of body mass index, the risk of IHD may be lowered.

Causal inference on neuroimaging data with Mendelian randomisation

While population-scale neuroimaging studies offer the promise of discovery and characterisation of subtle risk factors, massive sample sizes increase the power for both meaningful associations and those attributable to confounds. This motivates the need for causal modelling of observational data that goes beyond statements of association and towards deeper understanding of complex relationships between individual traits and phenotypes, clinical biomarkers, genetic variation, and brain-related measures of health. Mendelian randomisation (MR) presents a way to obtain causal inference on the basis of genetic data and explicit assumptions about the relationship between genetic variables, exposure and outcome. In this work, we provide an introduction to and overview of causal inference methods based on Mendelian randomisation, with examples involving imaging-derived phenotypes from UK Biobank to make these methods accessible to neuroimaging researchers. We motivate the use of MR techniques, lay out the underlying assumptions, introduce common MR methods and focus on several scenarios in which modelling assumptions are potentially violated, resulting in biased effect estimates. Importantly, we give a detailed account of necessary steps to increase the reliability of MR results with rigorous sensitivity analyses.

Triangulating evidence for the causal impact of single-intervention zinc supplement on glycaemic control for type 2 diabetes: systematic review and meta-analysis of randomised controlled trial and two-sample Mendelian randomisation

Although previous studies suggested the protective effect of Zn for type 2 diabetes (T2D), the unitary causal effect remains inconclusive. We investigated the causal effect of Zn as a single intervention on glycaemic control for T2D, using a systematic review of randomised controlled trials and two-sample Mendelian randomisation (MR). Four primary outcomes were identified: fasting blood glucose/fasting glucose, HbA1c, homeostatic model assessment for insulin resistance (HOMA-IR) and serum insulin/fasting insulin level. In the systematic review, four databases were searched until June 2021. Studies, in which participants had T2D and intervention did not comprise another co-supplement, were included. Results were synthesised through the random-effects meta-analysis. In the two-sample MR, we used single-nucleotide polymorphisms (SNP) from MR-base, strongly related to Zn supplements, to infer the relationship causally, but not specified T2D. In the systematic review and meta-analysis, fourteen trials were included with overall 897 participants initially. The Zn supplement led to a significant reduction in the post-trial mean of fasting blood glucose (mean difference (MD): −26·52 mg/dl, 95 % CI (−35·13, −17·91)), HbA1c (MD: −0·52 %, 95 % CI: (−0·90, −0·13)) and HOMA-IR (MD: −1·65, 95 % CI (−2·62, −0·68)), compared to the control group. In the two-sample MR, Zn supplement with two SNP reduced the fasting glucose (inverse-variance weighted coefficient: −2·04 mmol/l, 95 % CI (−3·26, −0·83)). From the two methods, Zn supplementation alone may causally improve glycaemic control among T2D patients. The findings are limited by power from the small number of studies and SNP included in the systematic review and two-sample MR analysis, respectively.

Alcohol consumption in relation to cardiovascular diseases and mortality: a systematic review of Mendelian randomization studies

The causal effects of alcohol-in-moderation on cardiometabolic health are continuously debated. Mendelian randomization (MR) is an established method to address causal questions in observational studies. We performed a systematic review of the current evidence from MR studies on the association between alcohol consumption and cardiometabolic diseases, all-cause mortality and cardiovascular risk factors. We performed a systematic search of the literature, including search terms on type of design and exposure. We assessed methodological quality based on key elements of the MR design: use of a full instrumental variable analysis and validation of the three key MR assumptions. We additionally looked at exploration of non-linearity. We reported the direction of the studied associations. Our search yielded 24 studies that were eligible for inclusion. A full instrumental variable analysis was performed in 17 studies (71%) and 13 out of 24 studies (54%) validated all three key assumptions. Five studies (21%) assessed potential non-linearity. In general, null associations were reported for genetically predicted alcohol consumption with the primary outcomes cardiovascular disease (67%) and diabetes (75%), while the only study on all-cause mortality reported a detrimental association. Considering the heterogeneity in methodological quality of the included MR studies, it is not yet possible to draw conclusions on the causal role of moderate alcohol consumption on cardiometabolic health. As MR is a rapidly evolving field, we expect that future MR studies, especially with recent developments regarding instrument selection and non-linearity methodology, will further substantiate this discussion.

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.

Association of Habitual Alcohol Intake With Risk of Cardiovascular Disease

IMPORTANCE

Observational studies have consistently proposed cardiovascular benefits associated with light alcohol consumption, while recent genetic analyses (ie, mendelian randomization studies) have suggested a possible causal link between alcohol intake and increased risk of cardiovascular disease. However, traditional approaches to genetic epidemiology assume a linear association and thus have not fully evaluated dose-response estimates of risk across different levels of alcohol intake.

OBJECTIVES

To assess the association of habitual alcohol intake with cardiovascular disease risk and to evaluate the direction and relative magnitude of cardiovascular risk associated with different amounts of alcohol consumption.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study used the UK Biobank (2006-2010, follow-up until 2016) to examine confounding in epidemiologic associations between alcohol intake and cardiovascular diseases. Using both traditional (ie, linear) and nonlinear mendelian randomization, potential associations between alcohol consumption and cardiovascular diseases (eg, hypertension and coronary artery disease) as well as corresponding association shapes were assessed. Data analysis was conducted from July 2019 to January 2022.

EXPOSURES

Genetic predisposition to alcohol intake.

MAIN OUTCOMES AND MEASURES

The association between alcohol consumption and cardiovascular diseases, including hypertension, coronary artery disease, myocardial infarction, stroke, heart failure, and atrial fibrillation.

RESULTS

This study included 371 463 participants (mean [SD] age, 57.0 [7.9] years; 172 400 [46%] men), who consumed a mean (SD) 9.2 (10.6) standard drinks per week. Overall, 121 708 participants (33%) had hypertension. Light to moderate alcohol consumption was associated with healthier lifestyle factors, adjustment for which attenuated the cardioprotective epidemiologic associations with modest intake. In linear mendelian randomization analyses, a 1-SD increase in genetically predicted alcohol consumption was associated with 1.3-fold (95% CI, 1.2-1.4) higher risk of hypertension (P < .001) and 1.4-fold (95% CI, 1.1-1.8) higher risk of coronary artery disease (P = .006). Nonlinear mendelian randomization analyses suggested nonlinear associations between alcohol consumption and both hypertension and coronary artery disease: light alcohol intake was associated with minimal increases in cardiovascular risk, whereas heavier consumption was associated with exponential increases in risk of both clinical and subclinical cardiovascular disease.

CONCLUSIONS AND RELEVANCE

In this cohort study, coincident, favorable lifestyle factors attenuated the observational benefits of modest alcohol intake. Genetic epidemiology suggested that alcohol consumption of all amounts was associated with increased cardiovascular risk, but marked risk differences exist across levels of intake, including those accepted by current national guidelines.

Mendelian randomization

Mendelian randomization (MR) is a term that applies to the use of genetic variation to address causal questions about how modifiable exposures influence different outcomes. The principles of MR are based on Mendel's laws of inheritance and instrumental variable estimation methods, which enable the inference of causal effects in the presence of unobserved confounding. In this Primer, we outline the principles of MR, the instrumental variable conditions underlying MR estimation and some of the methods used for estimation. We go on to discuss how the assumptions underlying an MR study can be assessed and give methods of estimation that are robust to certain violations of these assumptions. We give examples of a range of studies in which MR has been applied, the limitations of current methods of analysis and the outlook for MR in the future. The difference between the assumptions required for MR analysis and other forms of non-interventional epidemiological studies means that MR can be used as part of a triangulation across multiple sources of evidence for causal inference.

Are there non-linear relationships between alcohol consumption and long-term health?: a systematic review of observational studies employing approaches to improve causal inference

Background

Research has long found ‘J-shaped’ relationships between alcohol consumption and certain health outcomes, indicating a protective effect of moderate consumption. However, methodological limitations in most studies hinder causal inference. This review aimed to identify all observational studies employing improved approaches to mitigate confounding in characterizing alcohol–long-term health relationships, and to qualitatively synthesize their findings.

Methods

Eligible studies met the above description, were longitudinal (with pre-defined exceptions), discretized alcohol consumption, and were conducted with human populations. MEDLINE, PsycINFO, Embase and SCOPUS were searched in May 2020, yielding 16 published manuscripts reporting on cancer, diabetes, dementia, mental health, cardiovascular health, mortality, HIV seroconversion, and musculoskeletal health. Risk of bias of cohort studies was evaluated using the Newcastle-Ottawa Scale, and a recently developed tool was used for Mendelian Randomization studies.

Results

A variety of functional forms were found, including reverse J/J-shaped relationships for prostate cancer and related mortality, dementia risk, mental health, and certain lipids. However, most outcomes were only evaluated by a single study, and few studies provided information on the role of alcohol consumption pattern.

Conclusions

More research employing enhanced causal inference methods is urgently required to accurately characterize alcohol–long-term health relationships. Those studies that have been conducted find a variety of linear and non-linear functional forms, with results tending to be discrepant even within specific health outcomes.

Trial registration

PROSPERO registration number CRD42020185861.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-021-01486-5.

Alcohol Consumption and Cardiovascular Disease Risk: Placing New Data in Context

PURPOSE OF REVIEW

A clear link between excessive alcohol consumption and cardiovascular disease (CVD) has been established, but no consensus exists on the effects of moderate alcohol consumption on CVD.

RECENT FINDINGS

A lower risk of coronary heart disease and myocardial infarction among moderate drinkers compared to abstainers has been consistently observed in epidemiological studies and meta-analyses of these studies. However, ambiguity remains on the effect of alcohol on other CVDs and all-cause mortality. Short-term randomized controlled trials (RCT) have identified potentially beneficial effects of alcohol consumption on cardiovascular risk factors, but studies investigating genetic polymorphisms that influence alcohol consumption (i.e., Mendelian randomization) have yielded inconclusive results. To date, a long-term RCT providing causal evidence is lacking but urgently needed. Triangulation of evidence from different study designs, including long-term RCTs, pragmatic trials and the evaluation of policy measures, combined will lead to the best available evidence.

Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development

Drug development in cardiovascular disease is stagnating, with lack of efficacy and adverse effects being barriers to innovation. Human genetics can provide compelling evidence of causation through approaches such as Mendelian randomization, with genetic support for causation increasing the probability of a clinical trial succeeding. Mendelian randomization applied to quantitative traits can identify risk factors for disease that are both causal and amenable to therapeutic modification. However, important differences exist between genetic investigations of a biomarker (such as HDL cholesterol) and a drug target aimed at modifying the same biomarker of interest (such as cholesteryl ester transfer protein), with implications for the methodology, interpretation and application of Mendelian randomization to drug development. Differences include the comparative nature of the genetic architecture - that is, biomarkers are typically polygenic, whereas protein drug targets are influenced by either cis-acting or trans-acting genetic variants - and the potential for drug targets to show disease associations that might differ from those of the biomarker that they are intended to modify (target-mediated pleiotropy). In this Review, we compare and contrast the use of Mendelian randomization to evaluate potential drug targets versus quantitative traits. We explain how genetic epidemiological studies can be used to assess the aetiological roles of biomarkers in disease and to prioritize drug targets, including designing their evaluation in clinical trials.

The causal effect of interleukin-17 on the risk of psoriatic arthritis: a Mendelian randomization study

OBJECTIVE

To determine causal associations between genetically predicted TNF-α, IL-12p70 and IL-17 levels and risk of PsA.

METHODS

The publicly available summary-level findings from genome-wide association studies (GWAS) was used to identify loci influencing normal physiological concentrations of TNF-α, IL-12p70 and IL-17 (n = 8293) among healthy individuals as exposure and a GWAS for PsA from the UK Biobank (PsA = 900, control = 462 033) as the outcome. A two-sample Mendelian randomization (MR) analysis was performed using the inverse-variance weighted (IVW), weighted median and MR-Egger regression methods. Sensitivity analysis and MR-Egger regression analysis were performed to evaluate the heterogeneity and pleiotropic effects of each variant.

RESULTS

Single-nucleotide polymorphisms (SNPs) at genome-wide significance from GWASs on TNF-α, IL-12p70 and IL-17 were identified as the instrumental variables. The IVW method indicated a causal association between increased IL-17 level and risk of PsA (β = -0.00186 per allele, s.e. = 0.00043, P = 0.002). Results were consistent in the weighted median method (β = -0.00145 per allele, s.e. = 0.00059, P = 0.014) although the MR-Egger method suggested a non-significant association (β = -0.00133 per allele, s.e. = 0.00087; P = 0.087). Single SNP MR results revealed that the C allele of rs117556572 was robustly associated with risk of PsA (β = 0.00210, s.e. = 0.00069, P = 0.002). However, no evidence for a causal effect was observed between TNF-α, IL-12p70, decreased IL-17 levels and risk of PsA.

CONCLUSION

Our findings provide preliminary evidence that genetic variants predisposing to higher physiological IL-17 level are associated with decreased risk of PsA.

Evidence of detrimental effects of prenatal alcohol exposure on offspring birthweight and neurodevelopment from a systematic review of quasi-experimental studies

BACKGROUND

Systematic reviews of prenatal alcohol exposure effects generally only include conventional observational studies. However, estimates from such studies are prone to confounding and other biases.

OBJECTIVES

To systematically review the evidence on the effects of prenatal alcohol exposure from randomized controlled trials (RCTs) and observational designs using alternative analytical approaches to improve causal inference.

SEARCH STRATEGY

Medline, Embase, Web of Science, PsychINFO from inception to 21 June 2018. Manual searches of reference lists of retrieved papers.

SELECTION CRITERIA

RCTs of interventions to stop/reduce drinking in pregnancy and observational studies using alternative analytical methods (quasi-experimental studies e.g. Mendelian randomization and natural experiments, negative control comparisons) to determine the causal effects of prenatal alcohol exposure on pregnancy and longer-term offspring outcomes in human studies.

DATA COLLECTION AND ANALYSIS

One reviewer extracted data and another checked extracted data. Risk of bias was assessed using customized risk of bias tools. A narrative synthesis of findings was carried out and a meta-analysis for one outcome.

MAIN RESULTS

Twenty-three studies were included, representing five types of study design, including 1 RCT, 9 Mendelian randomization and 7 natural experiment studies, and reporting on over 30 outcomes. One study design-outcome combination included enough independent results to meta-analyse. Based on evidence from several studies, we found a likely causal detrimental role of prenatal alcohol exposure on cognitive outcomes, and weaker evidence for a role in low birthweight.

CONCLUSION

None of the included studies was judged to be at low risk of bias in all domains, results should therefore be interpreted with caution.

SYSTEMATIC REVIEW REGISTRATION

This study is registered with PROSPERO, registration number CRD42015015941.

Negative Effects of Age at Menarche on Risk of Cardiometabolic Diseases in Adulthood: A Mendelian Randomization Study

CONTEXT

Observational studies have demonstrated that early menarche is associated with cardiometabolic diseases, but confounding factors make it difficult to infer causality.

OBJECTIVE

We used Mendelian randomization (MR) to examine whether age at menarche (AAM) is causally associated with type 2 diabetes (T2D), coronary artery disease (CAD) and cardiometabolic traits.

DESIGN AND METHODS

A 2-sample MR analysis was conducted using genome-wide association study (GWAS) summary statistics from the Diabetes Genetics Replication and Meta-analysis (DIAGRAM) consortium (n = 159 208) for T2D and the Coronary Artery Disease Genome-wide Replication and Meta-analysis plus the Coronary Artery Disease Genetics (CARDIoGRAMplusC4D) consortium (n = 184 305) for CAD. We used 122 instrumental variables (IVs) extracted from a published GWAS meta-analysis incorporating 182 416 women to determine the causal effect of AAM on cardiometabolic diseases, treating childhood and adult body mass index (BMI) as the confounders. Sensitivity analyses were also performed to detect the pleiotropy of the IVs.

RESULTS

Employing the MR approach, we found that later AAM was associated with decreased risk of CAD (OR, 0.92 [95% CI, 0.88-0.96]; P = 2.06 × 10-4) in adults, as well as lower blood levels of log fasting insulin, log homeostatic model assessment of insulin resistance (HOMA-IR), log HOMA of β-cell function (HOMA-B), triglycerides, and diastolic blood pressure, but higher blood level of high-density lipoprotein. However, the associations were substantially attenuated after excluding BMI-related variants. MR analyses provide little evidence on the causal effect between AAM and T2D.

CONCLUSIONS

Our findings showed that AAM did not appear to have a causal effect on the risk of cardiometabolic diseases in adult life, as their associations observed in epidemiological studies might be largely mediated through excessive adiposity. We propose adiposity might be a primary target in future intervention strategy.

Effect of glutamate and aspartate on ischemic heart disease, blood pressure, and diabetes: a Mendelian randomization study

BACKGROUND

Evolutionary biology suggests reproduction trades off against longevity. Genetic selection in favor of fertility and ischemic heart disease (IHD) exists in humans. Observationally, soy protects against IHD. Soy amino acids, glutamate and aspartate, may lower androgens. No large randomized controlled trials testing their health effects exist.

OBJECTIVE

Using Mendelian randomization, we assessed how genetically predicted glutamate and aspartate affected IHD, blood pressure, and diabetes.

METHODS

A separate sample instrumental variable analysis with genetic instruments was used to obtain unconfounded estimates using genetic variants strongly (P < 5 × 10(-8)) and solely associated with glutamate or aspartate applied to an IHD case (n ≤76,014)-control (n ≤ 264,785) study (based on a meta-analysis of CARDIoGRAMplusC4D 1000 Genomes, UK Biobank CAD SOFT GWAS and Myocardial Infarction Genetics and CARDIoGRAM Exome), blood pressure from the UK Biobank (n ≤ 361,194), and the DIAbetes Genetics Replication And Meta-analysis diabetes case (n = 26,676)-control (n = 132,532) study. A weighted median and MR-Egger were used for a sensitivity analysis.

RESULTS

Glutamate was not associated with IHD, blood pressure, or diabetes after correction for multiple comparisons. Aspartate was inversely associated with IHD (odds ratio (OR) 0.92 per log-transformed standard deviation (SD); 95% confidence interval (CI) 0.88, 0.96) and diastolic blood pressure (-0.03; 95% CI -0.04, -0.02) using inverse variance weighting, but not diabetes (OR 1.00; 95% CI 0.91, 1.09). Associations were robust to the sensitivity analysis.

CONCLUSIONS

Our findings suggest aspartate may play a role in IHD and blood pressure, potentially underlying cardiovascular benefits of soy. Clarifying the mechanisms would be valuable for IHD prevention and for defining a healthy diet.

Effect of linoleic acid on ischemic heart disease and its risk factors: a Mendelian randomization study

BACKGROUND

The role of n-6 polyunsaturated fatty acids (PUFAs) in ischemic heart disease (IHD) is controversial, and dietary guidelines vary. Observationally, lower saturated fat intake and higher intake of vegetable oils rich in linoleic acid (LA), the main n-6 PUFA, is associated with lower IHD and diabetes; however, randomized controlled trials have not fully corroborated these benefits. We assessed how genetically predicted LA affected IHD and its risk factors, including diabetes, lipids, and blood pressure. We also assessed the role of LA in reticulocyte count, the red blood cell precursor, which has recently been identified as a possible causal factor in IHD.

METHODS

Two-sample instrumental variable analysis with genetic instruments, i.e., Mendelian randomization, was used to obtain unconfounded estimates using genetic variants strongly (p value < 5 × 10-8) and solely associated with LA, applied to an IHD case (n ≤ 76,014)-control (n ≤ 264,785) study (mainly based on the meta-analysis of CARDIoGRAMplusC4D 1000 Genomes and UK Biobank CAD SOFT GWAS), the DIAbetes Genetics Replication And Meta-analysis diabetes case (n = 26,676)-control (n = 132,532) study, lipids from the Global Lipids Genetics Consortium Results (n = 196,475), and reticulocyte count and blood pressure from the UK Biobank (n ≤ 361,194). A weighted median and Mendelian randomization Egger were used for sensitivity analysis.

RESULTS

Genetically predicted LA was not associated with IHD or systolic blood pressure. Genetically predicted higher serum LA was associated with lower diabetes (odds ratio (OR) 0.97 per percentage in total fatty acid increase in LA, 95% confidence interval (CI) 0.96 to 0.99) and lower lipids (low-density lipoprotein, high-density lipoprotein, and total cholesterol), but may be associated with higher diastolic blood pressure. The findings were robust to different single nucleotide polymorphism (SNP) selections, analytic methods, and correction for multiple testing.

CONCLUSIONS

Our novel study suggests a benefit of LA for diabetes and lipids but no benefit for IHD, blood pressure, or reticulocyte count. Explicating these paradoxical findings would facilitate identification of effective new interventions for diabetes and IHD.

Alcohol consumption and diabetes risk in a Chinese population: a Mendelian randomization analysis

AIM

To assess the causality between alcohol intake, diabetes risk and related traits.

DESIGN

Mendelian randomization (MR) study. Subgroup analysis, standard instrumental variable analysis and local average treatment effect (LATE) methods were applied to assess linear and non-linear causality.

SETTING

China.

PARTICIPANTS

A total of 4536 participants, including 721 diabetes cases.

FINDINGS

Carriage of an ALDH2 rs671 A allele reduced alcohol consumption by 44.63% [95% confidence interval (CI) = -49.44%, -39.37%]. In males, additional carriage of an A allele was significantly connected to decreased diabetes risk for the overall population [odds ratio (OR) = 0.716, 95% CI = 0.567-0.904, P = 0.005] or moderate drinkers (OR = 0.564, 95% CI = 0.355-0.894, P = 0.015). In instrumental variable (IV) analysis, increasing alcohol consumption by 1.7-fold was associated with an incidence-rate ratio of 1.32 (95% CI = 1.06-1.67, P = 0.014) for diabetes risk, and elevated alcohol intake was causally connected to natural log-transformed fasting, 2-hour post-load plasma glucose (β = 0.036, 95% CI = 0.018-0.054; β = 0.072, 95% CI = 0.035-0.108) and insulin resistance [homeostatic model assessment for IR (HOMA-IR] (β = 0.104, 95% CI = 0.039-0.169), but was not associated with beta-cell function (HOMA-beta). In addition, the LATE method did not identify significant U-shaped causality between alcohol consumption and diabetes-related traits. In females, the effects of alcohol intake on all the outcomes were non-significant.

CONCLUSION

Among men in China, higher alcohol intake appears to be causally associated with increased diabetes risk and worsened related traits, even for moderate drinkers. This study found no significant U-shaped causality between alcohol consumption and diabetes-related traits.

No Causal Effect of Telomere Length on Ischemic Stroke and Its Subtypes: A Mendelian Randomization Study

Background: Epidemiological studies observing inconsistent associations of telomere length (TL) with ischemic stroke (IS) are susceptible to bias according to reverse causation and residual confounding. We aimed to assess the causal association between TL, IS, and the subtypes of IS, including large artery stroke (LAS), small vessel stroke (SVS), and cardioembolic stroke (CES) by performing a series of two-sample Mendelian randomization (MR) approaches. Methods: Seven single nucleotide polymorphisms (SNPs) were involved as candidate instrumental variables (IVs), summarized from a genome-wide meta-analysis including 37,684 participants of European descent. We analyzed the largest ever genome-wide association studies of stroke in Europe from the MEGASTROKE collaboration with 40,585 stroke cases and 406,111 controls. The weighted median (WM), the penalized weighted median (PWM), the inverse variance weighted (IVW), the penalized inverse variance weighted (PIVW), the robust inverse variance weighted (RIVW), and the Mendelian randomization-Egger (MR-Egger) methods were conducted for the MR analysis to estimate a causal effect and detect the directional pleiotropy. Results: No significant association between genetically determined TL with overall IS, LAS, or CES were found (all p > 0.05). SVS was associated with TL by the RIVW method (odds ratio (OR) = 0.72, 95% confidence interval (CI): 0.54–0.97, p = 0.028), after excluding rs9420907, rs10936599, and rs2736100. Conclusions: By a series of causal inference approaches using SNPs as IVs, no strong evidence to support the causal effect of shorter TL on IS and its subtypes were found.

Evaluation of the causal effects between subjective wellbeing and cardiometabolic health: mendelian randomisation study

OBJECTIVES

To investigate whether the association between subjective wellbeing (subjective happiness and life satisfaction) and cardiometabolic health is causal.

DESIGN

Two sample, bidirectional mendelian randomisation study.

SETTING

Genetic data taken from various cohorts comprised of the general population (mostly individuals of European ancestry, plus a small proportion of other ancestries); follow-up analysis included individuals from the United Kingdom.

PARTICIPANTS

Summary data were used from previous genome wide association studies (number of participants ranging from 83 198 to 339 224), which investigated traits related to cardiovascular or metabolic health, had the largest sample sizes, and consisted of the most similar populations while minimising sample overlap. A follow-up analysis included 337 112 individuals from the UK Biobank (54% female (n=181 363), mean age 56.87 years (standard deviation 8.00) at recruitment).

MAIN OUTCOME MEASURES

Subjective wellbeing and 11 measures of cardiometabolic health (coronary artery disease; myocardial infarction; total, high density lipoprotein, and low density lipoprotein cholesterol; diastolic and systolic blood pressure; body fat; waist to hip ratio; waist circumference; and body mass index).

RESULTS

Evidence of a causal effect of body mass index on subjective wellbeing was seen; each 1 kg/m2 increase in body mass index caused a -0.045 (95% confidence interval -0.084 to -0.006, P=0.02) standard deviation reduction in subjective wellbeing. Follow-up analysis of this association in an independent sample from the UK Biobank provided strong evidence of an effect of body mass index on satisfaction with health (β=-0.035 unit decrease in health satisfaction (95% confidence interval -0.043 to -0.027) per standard deviation increase in body mass index, P<0.001). No clear evidence of a causal effect was seen between subjective wellbeing and the other cardiometabolic health measures, in either direction.

CONCLUSIONS

These results suggest that a higher body mass index is associated with a lower subjective wellbeing. A follow-up analysis confirmed this finding, suggesting that the effect in middle aged people could be driven by satisfaction with health. Body mass index is a modifiable determinant, and therefore, this study provides further motivation to tackle the obesity epidemic because of the knock-on effects of higher body mass index on subjective wellbeing.

Exploring causality in the association between circulating 25-hydroxyvitamin D and colorectal cancer risk: a large Mendelian randomisation study

BACKGROUND

Whilst observational studies establish that lower plasma 25-hydroxyvitamin D (25-OHD) levels are associated with higher risk of colorectal cancer (CRC), establishing causality has proven challenging. Since vitamin D is modifiable, these observations have substantial clinical and public health implications. Indeed, many health agencies already recommend supplemental vitamin D. Here, we explore causality in a large Mendelian randomisation (MR) study using an improved genetic instrument for circulating 25-OHD.

METHODS

We developed a weighted genetic score for circulating 25-OHD using six genetic variants that we recently reported to be associated with circulating 25-OHD in a large genome-wide association study (GWAS) meta-analysis. Using this score as instrumental variable in MR analyses, we sought to determine whether circulating 25-OHD is causally linked with CRC risk. We conducted MR analysis using individual-level data from 10,725 CRC cases and 30,794 controls (Scotland, UK Biobank and Croatia). We then applied estimates from meta-analysis of 11 GWAS of CRC risk (18,967 cases; 48,168 controls) in a summary statistics MR approach.

RESULTS

The new genetic score for 25-OHD was strongly associated with measured plasma 25-OHD levels in 2821 healthy Scottish controls (P = 1.47 × 10- 11), improving upon previous genetic instruments (F-statistic 46.0 vs. 13.0). However, individual-level MR revealed no association between 25-OHD score and CRC risk (OR 1.03/unit log-transformed circulating 25-OHD, 95% CI 0.51-2.07, P = 0.93). Similarly, we found no evidence for a causal relationship between 25-OHD and CRC risk using summary statistics MR analysis (OR 0.91, 95% CI 0.69-1.19, P = 0.48).

CONCLUSIONS

Despite the scale of this study and employing an improved score capturing more of the genetic contribution to circulating 25-OHD, we found no evidence for a causal relationship between circulating 25-OHD and CRC risk. Although the magnitude of effect for vitamin D suggested by observational studies can confidently be excluded, smaller effects sizes and non-linear relationships remain plausible. Circulating vitamin D may be a CRC biomarker, but a causal effect on CRC risk remains unproven.

Common Methods for Performing Mendelian Randomization

Mendelian randomization (MR) is a framework for assessing causal inference using cross-sectional data in combination with genetic information. This paper summarizes statistical methods commonly applied and strait forward to use for conducting MR analyses including those taking advantage of the rich dataset of SNP-trait associations that were revealed in the last decade through large-scale genome-wide association studies. Using these data, powerful MR studies are possible. However, the causal estimate may be biased in case the assumptions of MR are violated. The source and the type of this bias are described while providing a summary of the mathematical formulas that should help estimating the magnitude and direction of the potential bias depending on the specific research setting. Finally, methods for relaxing the assumptions and for conducting sensitivity analyses are discussed. Future researches in the field of MR include the assessment of non-linear causal effects, and automatic detection of invalid instruments.

Limitations of vitamin D supplementation trials: Why observational studies will continue to help determine the role of vitamin D in health

Observational studies have shown that low vitamin D status is associated with an increased risk of a wide range of diseases. The body of observational evidence now is so large, that there have been many calls for randomized controlled trials (RCT) of vitamin D supplementation to confirm once and for all whether increasing body vitamin D levels prevents these diseases. These calls have arisen because of concern that confounding and reverse causation may explain many of the results from observational studies. However, RCTs also are prone to limitations that compromise their validity. These include low response rates that affect their external validity; and biases that affect their internal validity, such as recruitment of vitamin D sufficient people which decreases the power to detect beneficial effects, studies of long-term outcomes requiring participation for many years which decreases compliance and retention, and easy access for participants to vitamin D supplements and blood testing which increase contamination and unblinding. Because of these potential limitations, it is possible that RCTs of vitamin D supplementation may not to give a clear answer by themselves. Future decisions about the role of vitamin D in health are likely to be based on the evidence from a range of study designs including RCTs, mendelian randomization studies and other observational designs.

ADH1B: From alcoholism, natural selection, and cancer to the human phenome

The ADH1B (Alcohol Dehydrogenase 1B (class I), Beta Polypeptide) gene and its best-known functional alleles, Arg48His (rs1229984, ADH1B*2) and Arg370Cys (rs2066702, ADH1B*3), have been investigated in relation to many phenotypic traits; most frequently including alcohol metabolism and alcohol drinking behaviors, but also human evolution, liver function, cancer, and, recently, the comprehensive human phenome. To understand ADH1B functions and consequences, we provide here a bioinformatic analysis of its gene regulation and molecular functions, literature review of studies focused on this gene, and a discussion regarding future research perspectives. Certain ADH1B alleles have large effects on alcohol metabolism, and this relationship particularly encourages further investigations in relation to alcoholism and alcohol-associated cancer to understand better the mechanisms by which alcohol metabolism contributes to alcohol abuse and carcinogenesis. We also observed that ADH1B has complex mechanisms that regulate its expression across multiple human tissues, and these may be involved in cardiac and metabolic traits. Evolutionary data strongly suggest that the selection signatures at the ADH1B locus are primarily related to effects other than those on alcohol metabolism. This is also supported by the involvement of ADH1B in multiple molecular pathways and by the findings of our recent phenome-wide association study. Accordingly, future studies should also investigate other functions of ADH1B potentially relevant for the human phenome. © 2017 Wiley Periodicals, Inc.

Alcohol Consumption and Common Carotid Intima-Media Thickness: The USE-IMT Study

Aims

Epidemiological evidence indicates a protective effect of light to moderate alcohol consumption compared to non-drinking and heavy drinking. Although several mechanisms have been suggested, the effect of alcohol on atherosclerotic changes in vessel walls is unclear. Therefore, we explored the relationship between alcohol consumption and common carotid intima media thickness, a marker of early atherosclerosis in the general population.

Methods

Individual participant data from eight cohorts, involving 37,494 individuals from the USE-IMT collaboration were used. Multilevel age and sex adjusted linear regression models were applied to estimate mean differences in common carotid intima-media thickness (CIMT) with alcohol consumption.

Results

The mean age was 57.9 years (SD 8.6) and the mean CIMT was 0.75 mm (SD 0.177). About, 40.5% reported no alcohol consumed, and among those who drank, mean consumption was 13.3 g per day (SD 16.4). Those consuming no alcohol or a very small amount (<5 g per day) had significantly lower common CIMT values than those consuming >10 g per day, after adjusting for a range of confounding factors.

Conclusion

In this large CIMT consortium, we did not find evidence to support a protective effect of alcohol on CIMT.

Age at menarche and lung function: a Mendelian randomization study

A trend towards earlier menarche in women has been associated with childhood factors (e.g. obesity) and hypothesised environmental exposures (e.g. endocrine disruptors present in household products). Observational evidence has shown detrimental effects of early menarche on various health outcomes including adult lung function, but these might represent spurious associations due to confounding. To address this we used Mendelian randomization where genetic variants are used as proxies for age at menarche, since genetic associations are not affected by classical confounding. We estimated the effects of age at menarche on forced vital capacity (FVC), a proxy for restrictive lung impairment, and ratio of forced expiratory volume in one second to FVC (FEV1/FVC), a measure of airway obstruction, in both adulthood and adolescence. We derived SNP-age at menarche association estimates for 122 variants from a published genome-wide meta-analysis (N = 182,416), with SNP-lung function estimates obtained by meta-analysing three studies of adult women (N = 46,944) and two of adolescent girls (N = 3025). We investigated the impact of departures from the assumption of no pleiotropy through sensitivity analyses. In adult women, in line with previous evidence, we found an effect on restrictive lung impairment with a 24.8 mL increase in FVC per year increase in age at menarche (95% CI 1.8-47.9; p = 0.035); evidence was stronger after excluding potential pleiotropic variants (43.6 mL; 17.2-69.9; p = 0.001). In adolescent girls we found an opposite effect (-56.5 mL; -108.3 to -4.7; p = 0.033), suggesting that the detrimental effect in adulthood may be preceded by a short-term post-pubertal benefit. Our secondary analyses showing results in the same direction in men and boys, in whom age at menarche SNPs have also shown association with sexual development, suggest a role for pubertal timing in general rather than menarche specifically. We found no effect on airway obstruction (FEV1/FVC).

Vascular Endothelial Growth Factor and Ischemic Heart Disease Risk: A Mendelian Randomization Study

BACKGROUND

Vascular endothelial growth factor (VEGF) has angiogenic and possibly proatherosclerotic properties. Observationally it is positively associated with cardiovascular disease, although these observations could be confounded or due to reverse causation. We assessed ischemic heart disease (IHD) risk by genetically predicted VEGF, ie, using Mendelian randomization.

METHODS AND RESULTS

Single nucleotide polymorphisms (SNPs) predicting VEGF level, at genome-wide significance, were applied to the CARDIoGRAMplusC4D 1000 Genomes-based genome-wide association study IHD case (n=60 801)-control (n=123 504) study. We obtained unconfounded estimates using instrumental variable analysis by combining the Wald estimates for each SNP using inverse variance weighting and Mendelian randomization-Egger regression. Based on 9 SNPs independently predicting VEGF (rs1740073 [C6orf223], rs2375981 [KCNV2], rs2639990 [ZADH2], rs4782371 [ZFPM1], rs6921438 [LOC100132354], rs7043199 [VLDLR-AS1], rs10761741 [JMJD1C], rs6993770 [ZFPM2], and rs114694170 [MEF2C]), VEGF was unrelated to IHD (odds ratio 0.99 per log-transformed pg/mL, 95%CI 0.96-1.02) using inverse variance weighting. However, Mendelian randomization-Egger regression suggested an inverse relation of VEGF with IHD (odds ratio 0.95, 95%CI 0.91-0.99), although the association was not evident after excluding the lead SNP (rs6921438) or additionally excluding the pleiotropic SNP (rs6993770).

CONCLUSIONS

Our study does not provide strong evidence for a positive effect of VEGF on IHD but does not rule out the possibility that some specific types of VEGF, for which genetic predictors have not yet been identified, might play a role.

Causal Associations of Adiposity and Body Fat Distribution With Coronary Heart Disease, Stroke Subtypes, and Type 2 Diabetes Mellitus: A Mendelian Randomization Analysis

BACKGROUND

The implications of different adiposity measures on cardiovascular disease etiology remain unclear. In this article, we quantify and contrast causal associations of central adiposity (waist-to-hip ratio adjusted for body mass index [WHRadjBMI]) and general adiposity (body mass index [BMI]) with cardiometabolic disease.

METHODS

Ninety-seven independent single-nucleotide polymorphisms for BMI and 49 single-nucleotide polymorphisms for WHRadjBMI were used to conduct Mendelian randomization analyses in 14 prospective studies supplemented with coronary heart disease (CHD) data from CARDIoGRAMplusC4D (Coronary Artery Disease Genome-wide Replication and Meta-analysis [CARDIoGRAM] plus The Coronary Artery Disease [C4D] Genetics; combined total 66 842 cases), stroke from METASTROKE (12 389 ischemic stroke cases), type 2 diabetes mellitus from DIAGRAM (Diabetes Genetics Replication and Meta-analysis; 34 840 cases), and lipids from GLGC (Global Lipids Genetic Consortium; 213 500 participants) consortia. Primary outcomes were CHD, type 2 diabetes mellitus, and major stroke subtypes; secondary analyses included 18 cardiometabolic traits.

RESULTS

Each one standard deviation (SD) higher WHRadjBMI (1 SD≈0.08 U) associated with a 48% excess risk of CHD (odds ratio [OR] for CHD, 1.48; 95% confidence interval [CI], 1.28-1.71), similar to findings for BMI (1 SD≈4.6 kg/m²; OR for CHD, 1.36; 95% CI, 1.22-1.52). Only WHRadjBMI increased risk of ischemic stroke (OR, 1.32; 95% CI, 1.03-1.70). For type 2 diabetes mellitus, both measures had large effects: OR, 1.82 (95% CI, 1.38-2.42) and OR, 1.98 (95% CI, 1.41-2.78) per 1 SD higher WHRadjBMI and BMI, respectively. Both WHRadjBMI and BMI were associated with higher left ventricular hypertrophy, glycemic traits, interleukin 6, and circulating lipids. WHRadjBMI was also associated with higher carotid intima-media thickness (39%; 95% CI, 9%-77% per 1 SD).

CONCLUSIONS

Both general and central adiposity have causal effects on CHD and type 2 diabetes mellitus. Central adiposity may have a stronger effect on stroke risk. Future estimates of the burden of adiposity on health should include measures of central and general adiposity.

Association between clinically recorded alcohol consumption and initial presentation of 12 cardiovascular diseases: population based cohort study using linked health records

Objectives To investigate the association between alcohol consumption and cardiovascular disease at higher resolution by examining the initial lifetime presentation of 12 cardiac, cerebrovascular, abdominal, or peripheral vascular diseases among five categories of consumption.Design Population based cohort study of linked electronic health records covering primary care, hospital admissions, and mortality in 1997-2010 (median follow-up six years).Setting CALIBER (ClinicAl research using LInked Bespoke studies and Electronic health Records).Participants 1 937 360 adults (51% women), aged ≥30 who were free from cardiovascular disease at baseline.Main outcome measures 12 common symptomatic manifestations of cardiovascular disease, including chronic stable angina, unstable angina, acute myocardial infarction, unheralded coronary heart disease death, heart failure, sudden coronary death/cardiac arrest, transient ischaemic attack, ischaemic stroke, intracerebral and subarachnoid haemorrhage, peripheral arterial disease, and abdominal aortic aneurysm.Results 114 859 individuals received an incident cardiovascular diagnosis during follow-up. Non-drinking was associated with an increased risk of unstable angina (hazard ratio 1.33, 95% confidence interval 1.21 to 1.45), myocardial infarction (1.32, 1.24 to1.41), unheralded coronary death (1.56, 1.38 to 1.76), heart failure (1.24, 1.11 to 1.38), ischaemic stroke (1.12, 1.01 to 1.24), peripheral arterial disease (1.22, 1.13 to 1.32), and abdominal aortic aneurysm (1.32, 1.17 to 1.49) compared with moderate drinking (consumption within contemporaneous UK weekly/daily guidelines of 21/3 and 14/2 units for men and women, respectively). Heavy drinking (exceeding guidelines) conferred an increased risk of presenting with unheralded coronary death (1.21, 1.08 to 1.35), heart failure (1.22, 1.08 to 1.37), cardiac arrest (1.50, 1.26 to 1.77), transient ischaemic attack (1.11, 1.02 to 1.37), ischaemic stroke (1.33, 1.09 to 1.63), intracerebral haemorrhage (1.37, 1.16 to 1.62), and peripheral arterial disease (1.35; 1.23 to 1.48), but a lower risk of myocardial infarction (0.88, 0.79 to 1.00) or stable angina (0.93, 0.86 to 1.00).Conclusions Heterogeneous associations exist between level of alcohol consumption and the initial presentation of cardiovascular diseases. This has implications for counselling patients, public health communication, and clinical research, suggesting a more nuanced approach to the role of alcohol in prevention of cardiovascular disease is necessary.Registration clinicaltrails.gov (NCT01864031).

Semiparametric methods for estimation of a nonlinear exposure-outcome relationship using instrumental variables with application to Mendelian randomization

Mendelian randomization, the use of genetic variants as instrumental variables (IV), can test for and estimate the causal effect of an exposure on an outcome. Most IV methods assume that the function relating the exposure to the expected value of the outcome (the exposure‐outcome relationship) is linear. However, in practice, this assumption may not hold. Indeed, often the primary question of interest is to assess the shape of this relationship. We present two novel IV methods for investigating the shape of the exposure‐outcome relationship: a fractional polynomial method and a piecewise linear method. We divide the population into strata using the exposure distribution, and estimate a causal effect, referred to as a localized average causal effect (LACE), in each stratum of population. The fractional polynomial method performs metaregression on these LACE estimates. The piecewise linear method estimates a continuous piecewise linear function, the gradient of which is the LACE estimate in each stratum. Both methods were demonstrated in a simulation study to estimate the true exposure‐outcome relationship well, particularly when the relationship was a fractional polynomial (for the fractional polynomial method) or was piecewise linear (for the piecewise linear method). The methods were used to investigate the shape of relationship of body mass index with systolic blood pressure and diastolic blood pressure.

Using Genetic Variation to Explore the Causal Effect of Maternal Pregnancy Adiposity on Future Offspring Adiposity: A Mendelian Randomisation Study

BACKGROUND

It has been suggested that greater maternal adiposity during pregnancy affects lifelong risk of offspring fatness via intrauterine mechanisms. Our aim was to use Mendelian randomisation (MR) to investigate the causal effect of intrauterine exposure to greater maternal body mass index (BMI) on offspring BMI and fat mass from childhood to early adulthood.

METHODS AND FINDINGS

We used maternal genetic variants as instrumental variables (IVs) to test the causal effect of maternal BMI in pregnancy on offspring fatness (BMI and dual-energy X-ray absorptiometry [DXA] determined fat mass index [FMI]) in a MR approach. This was investigated, with repeat measurements, from ages 7 to 18 in the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 2,521 to 3,720 for different ages). We then sought to replicate findings with results for BMI at age 6 in Generation R (n = 2,337 for replication sample; n = 6,057 for total pooled sample). In confounder-adjusted multivariable regression in ALSPAC, a 1 standard deviation (SD, equivalent of 3.7 kg/m2) increase in maternal BMI was associated with a 0.25 SD (95% CI 0.21-0.29) increase in offspring BMI at age 7, with similar results at later ages and when FMI was used as the outcome. A weighted genetic risk score was generated from 32 genetic variants robustly associated with BMI (minimum F-statistic = 45 in ALSPAC). The MR results using this genetic risk score as an IV in ALSPAC were close to the null at all ages (e.g., 0.04 SD (95% CI -0.21-0.30) at age 7 and 0.03 SD (95% CI -0.26-0.32) at age 18 per SD increase in maternal BMI), which was similar when a 97 variant generic risk score was used in ALSPAC. When findings from age 7 in ALSPAC were meta-analysed with those from age 6 in Generation R, the pooled confounder-adjusted multivariable regression association was 0.22 SD (95% CI 0.19-0.25) per SD increase in maternal BMI and the pooled MR effect (pooling the 97 variant score results from ALSPAC with the 32 variant score results from Generation R) was 0.05 SD (95%CI -0.11-0.21) per SD increase in maternal BMI (p-value for difference between the two results = 0.05). A number of sensitivity analyses exploring violation of the MR results supported our main findings. However, power was limited for some of the sensitivity tests and further studies with relevant data on maternal, offspring, and paternal genotype are required to obtain more precise (and unbiased) causal estimates.

CONCLUSIONS

Our findings provide little evidence to support a strong causal intrauterine effect of incrementally greater maternal BMI resulting in greater offspring adiposity.

Estimating Marginal Healthcare Costs Using Genetic Variants as Instrumental Variables: Mendelian Randomization in Economic Evaluation

Accurate measurement of the marginal healthcare costs associated with different diseases and health conditions is important, especially for increasingly prevalent conditions such as obesity. However, existing observational study designs cannot identify the causal impact of disease on healthcare costs. This paper explores the possibilities for causal inference offered by Mendelian randomization, a form of instrumental variable analysis that uses genetic variation as a proxy for modifiable risk exposures, to estimate the effect of health conditions on cost. Well-conducted genome-wide association studies provide robust evidence of the associations of genetic variants with health conditions or disease risk factors. The subsequent causal effects of these health conditions on cost can be estimated using genetic variants as instruments for the health conditions. This is because the approximately random allocation of genotypes at conception means that many genetic variants are orthogonal to observable and unobservable confounders. Datasets with linked genotypic and resource use information obtained from electronic medical records or from routinely collected administrative data are now becoming available and will facilitate this form of analysis. We describe some of the methodological issues that arise in this type of analysis, which we illustrate by considering how Mendelian randomization could be used to estimate the causal impact of obesity, a complex trait, on healthcare costs. We describe some of the data sources that could be used for this type of analysis. We conclude by considering the challenges and opportunities offered by Mendelian randomization for economic evaluation.

Twenty-year trajectories of alcohol consumption during midlife and atherosclerotic thickening in early old age: findings from two British population cohort studies

BACKGROUND

Epidemiological evidence indicates a protective effect of light-moderate drinking on cardiovascular disease and an increased risk for heavier drinking. Nevertheless, the effect of alcohol on atherosclerotic changes in vessel walls is disputed. Most previous studies have only looked at the cross-sectional relationship between alcohol and carotid intima media thickness (cIMT) - a surrogate marker of atherosclerosis. Single measurements of alcohol assume that alcohol exposure is stable and ignore the possible cumulative effects of harm, leading to possibly incorrect inferences.

METHODS

Data were retrieved from two UK population based cohort studies: the Whitehall II cohort of civil servants and the MRC National Survey of Health and Development (combined sample size of 5403 men and women). Twenty year-drinking trajectories during midlife were linked to measures of cIMT when participants were in early old age, and adjusted for age, sex, socioeconomic position, ethnicity and smoking.

RESULTS

Those who consistently drank heavily had an increased cIMT compared to stable moderate drinkers (pooled difference in cIMT 0.021 mm; 95 % CI 0.002 to 0.039), after adjustment for covariates. This was not detected in cross-sectional analyses. Former drinkers also had an increased cIMT compared to moderate drinkers (pooled difference in cIMT 0.021; 95 % CI 0.005 to 0.037). There were no appreciable differences in cIMT between non-drinkers and consistent moderate drinkers.

CONCLUSION

The drinking habits among adults during midlife affect the atherosclerotic process and sustained heavy drinking is associated with an increased cIMT compared to stable moderate drinkers. This finding was not seen when only using cross-sectional analyses, thus highlighting the importance of taking a life course approach. There was no evidence of a favourable atherosclerotic profile from stable moderate drinking compared to stable non-drinking.

Mendelian Randomisation study of the influence of eGFR on coronary heart disease

Impaired kidney function, as measured by reduced estimated glomerular filtration rate (eGFR), has been associated with increased risk of coronary heart disease (CHD) in observational studies, but it is unclear whether this association is causal or the result of confounding or reverse causation. In this study we applied Mendelian randomisation analysis using 17 genetic variants previously associated with eGFR to investigate the causal role of kidney function on CHD. We used 13,145 participants from the UCL-LSHTM-Edinburgh-Bristol (UCLEB) Consortium and 194,427 participants from the Coronary ARtery DIsease Genome-wide Replication and Meta-analysis plus Coronary Artery Disease (CARDIoGRAMplusC4D) consortium. We observed significant association of an unweighted gene score with CHD risk (odds ratio = 0.983 per additional eGFR-increasing allele, 95% CI = 0.970–0.996, p = 0.008). However, using weights calculated from UCLEB, the gene score was not associated with disease risk (p = 0.11). These conflicting results could be explained by a single SNP, rs653178, which was not associated with eGFR in the UCLEB sample, but has known pleiotropic effects that prevent us from drawing a causal conclusion. The observational association between low eGFR and increased CHD risk was not explained by potential confounders, and there was no evidence of reverse causation, therefore leaving the remaining unexplained association as an open question.

Modelling the impact of alcohol consumption on cardiovascular disease mortality for comparative risk assessments: an overview

BACKGROUND

Although alcohol consumption has long been considered as a risk factor for chronic disease, the relationship to cardiovascular disease (CVD) is complex and involves at least two dimensions: average volume of alcohol consumption and patterns of drinking. The objective of this contribution was to estimate the burden of CVD mortality caused by alcohol consumption.

METHODS

Risk assessment modelling with alcohol-attributable CVD mortality as primary outcome. The mortality burden of ischaemic heart disease (IHD) and ischaemic stroke (IS) attributable to alcohol consumption was estimated using attributable-fraction methodology. Relative Risk (RR) data for IHD and IS were obtained from the most comprehensive meta-analyses (except for Russia and surrounding countries where alcohol RR data were obtained from a large cohort study). Age-group specific RRs were calculated, based on large studies. Data on mortality were obtained from the World Health Organization's Global Health Estimates and alcohol consumption data were obtained from the Global Information System on Alcohol and Health. Risk of former drinkers was modelled taking into account global differences in the prevalence of sick quitters among former drinkers. Alcohol-attributable mortality estimates for all other CVD causes except IHD and IS were obtained from the 2014 Global Status Report on Alcohol and Health.

RESULTS

An estimated 780,381 CVD deaths (441,893 and 338,490 CVD deaths among men and women respectively) were attributable to alcohol consumption globally in 2012, accounting for 1.4 % of all deaths and 26.6 % of all alcohol-attributable deaths. This is in contrast to the previously estimated 1,128,273 CVD deaths attributable to alcohol consumption globally, and represents a decrease of 30.8 % in alcohol-attributable CVD mortality and of 10.6 % in the global burden of all alcohol-attributable deaths.

CONCLUSIONS

When the most comprehensive and recent systematic reviews and meta-analyses are taken as bases, the net impact of alcohol consumption on CVD is lower than previously estimated.

Genetic Evidence for Causal Relationships Between Maternal Obesity-Related Traits and Birth Weight

IMPORTANCE

Neonates born to overweight or obese women are larger and at higher risk of birth complications. Many maternal obesity-related traits are observationally associated with birth weight, but the causal nature of these associations is uncertain.

OBJECTIVE

To test for genetic evidence of causal associations of maternal body mass index (BMI) and related traits with birth weight.

DESIGN, SETTING, AND PARTICIPANTS

Mendelian randomization to test whether maternal BMI and obesity-related traits are potentially causally related to offspring birth weight. Data from 30,487 women in 18 studies were analyzed. Participants were of European ancestry from population- or community-based studies in Europe, North America, or Australia and were part of the Early Growth Genetics Consortium. Live, term, singleton offspring born between 1929 and 2013 were included.

EXPOSURES

Genetic scores for BMI, fasting glucose level, type 2 diabetes, systolic blood pressure (SBP), triglyceride level, high-density lipoprotein cholesterol (HDL-C) level, vitamin D status, and adiponectin level.

MAIN OUTCOME AND MEASURE

Offspring birth weight from 18 studies.

RESULTS

Among the 30,487 newborns the mean birth weight in the various cohorts ranged from 3325 g to 3679 g. The maternal genetic score for BMI was associated with a 2-g (95% CI, 0 to 3 g) higher offspring birth weight per maternal BMI-raising allele (P = .008). The maternal genetic scores for fasting glucose and SBP were also associated with birth weight with effect sizes of 8 g (95% CI, 6 to 10 g) per glucose-raising allele (P = 7 × 10(-14)) and -4 g (95% CI, -6 to -2 g) per SBP-raising allele (P = 1×10(-5)), respectively. A 1-SD ( ≈ 4 points) genetically higher maternal BMI was associated with a 55-g higher offspring birth weight (95% CI, 17 to 93 g). A 1-SD ( ≈ 7.2 mg/dL) genetically higher maternal fasting glucose concentration was associated with 114-g higher offspring birth weight (95% CI, 80 to 147 g). However, a 1-SD ( ≈ 10 mm Hg) genetically higher maternal SBP was associated with a 208-g lower offspring birth weight (95% CI, -394 to -21 g). For BMI and fasting glucose, genetic associations were consistent with the observational associations, but for systolic blood pressure, the genetic and observational associations were in opposite directions.

CONCLUSIONS AND RELEVANCE

In this mendelian randomization study, genetically elevated maternal BMI and blood glucose levels were potentially causally associated with higher offspring birth weight, whereas genetically elevated maternal SBP was potentially causally related to lower birth weight. If replicated, these findings may have implications for counseling and managing pregnancies to avoid adverse weight-related birth outcomes.

A review of instrumental variable estimators for Mendelian randomization

Instrumental variable analysis is an approach for obtaining causal inferences on the effect of an exposure (risk factor) on an outcome from observational data. It has gained in popularity over the past decade with the use of genetic variants as instrumental variables, known as Mendelian randomization. An instrumental variable is associated with the exposure, but not associated with any confounder of the exposure–outcome association, nor is there any causal pathway from the instrumental variable to the outcome other than via the exposure. Under the assumption that a single instrumental variable or a set of instrumental variables for the exposure is available, the causal effect of the exposure on the outcome can be estimated. There are several methods available for instrumental variable estimation; we consider the ratio method, two-stage methods, likelihood-based methods, and semi-parametric methods. Techniques for obtaining statistical inferences and confidence intervals are presented. The statistical properties of estimates from these methods are compared, and practical advice is given about choosing a suitable analysis method. In particular, bias and coverage properties of estimators are considered, especially with weak instruments. Settings particularly relevant to Mendelian randomization are prioritized in the paper, notably the scenario of a continuous exposure and a continuous or binary outcome.