MR-pheWAS with stratification and interaction: Searching for the causal effects of smoking heaviness identified an effect on facial aging

Exploring pleiotropy in Mendelian randomisation analyses: What are genetic variants associated with 'cigarette smoking initiation' really capturing?

Genetic variants used as instruments for exposures in Mendelian randomisation (MR) analyses may have horizontal pleiotropic effects (i.e., influence outcomes via pathways other than through the exposure), which can undermine the validity of results. We examined the extent of this using smoking behaviours as an example. We first ran a phenome-wide association study in UK Biobank, using a smoking initiation genetic instrument. From the most strongly associated phenotypes, we selected those we considered could either plausibly or not plausibly be caused by smoking. We examined associations between genetic instruments for smoking initiation, smoking heaviness and lifetime smoking and these phenotypes in UK Biobank and the Avon Longitudinal Study of Parents and Children (ALSPAC). We conducted negative control analyses among never smokers, including children. We found evidence that smoking-related genetic instruments were associated with phenotypes not plausibly caused by smoking in UK Biobank and (to a lesser extent) ALSPAC. We observed associations with phenotypes among never smokers. Our results demonstrate that smoking-related genetic risk scores are associated with unexpected phenotypes that are less plausibly downstream of smoking. This may reflect horizontal pleiotropy in these genetic risk scores, and we would encourage researchers to exercise caution this when using these and genetic risk scores for other complex behavioural exposures. We outline approaches that could be taken to consider this and overcome issues caused by potential horizontal pleiotropy, for example, in genetically informed causal inference analyses (e.g., MR) it is important to consider negative control outcomes and triangulation approaches, to avoid arriving at incorrect conclusions.

Mendelian Randomization Analysis of the Causal Effect of Cigarette Smoking on Hospital Costs

INTRODUCTION

Knowledge of the impact of smoking on health care costs is important for establishing the external effects of smoking and for evaluating policies intended to modify this behavior. Conventional analysis of this association is difficult because of omitted variable bias, reverse causality, and measurement error.

AIMS AND METHODS

We approached these challenges using a Mendelian Randomization study design; genetic variants associated with smoking behaviors were used in instrumental variables models with inpatient hospital costs (calculated from electronic health records) as the outcome. We undertook genome-wide association studies to identify genetic variants associated with smoking initiation and a composite smoking index (reflecting cumulative health impacts of smoking) on up to 300 045 individuals (mean age: 57 years at baseline, range 39-72 years) in the UK Biobank. We followed individuals up for a mean of 6 years.

RESULTS

Genetic liability to initiate smoking (ever vs. never smoking) was estimated to increase mean per-patient annual inpatient hospital costs by £477 (95% confidence interval (CI): £187 to £766). A one-unit change in genetic liability to the composite smoking index (range: 0-4.0) increased inpatient hospital costs by £204 (95% CI: £105 to £303) per unit increase in this index. There was some evidence that the composite smoking index causal models violated the instrumental variable assumptions, and all Mendelian Randomization models were estimated with considerable uncertainty. Models conditioning on risk tolerance were not robust to weak instrument bias.

CONCLUSIONS

Our findings have implications for the potential cost-effectiveness of smoking interventions.

IMPLICATIONS

We report the first Mendelian Randomization analysis of the causal effect of smoking on health care costs. Using two smoking phenotypes, we identified substantial impacts of smoking on inpatient hospital costs, although the causal models were associated with considerable uncertainty. These results could be used alongside other evidence on the impact of smoking to evaluate the cost-effectiveness of antismoking interventions and to understand the scale of externalities associated with this behavior.

The association of psychological and trauma-related factors with biological and facial aging acceleration: evidence from the UK Biobank

BACKGROUND

Psychological and trauma-related factors are associated with many diseases and mortality. However, a comprehensive assessment of the association between psycho-trauma exposures and aging acceleration is currently lacking.

METHODS

Using data from 332,359 UK Biobank participants, we calculated biological aging acceleration, indexed by the presence of leukocyte telomere length (LTL) deviation (i.e., the difference between genetically determined and observed LTL > 0). The acceleration of facial aging (i.e., looking older than the chronological age) was assessed using a self-report question. Then, we estimated the associations of each psycho-trauma factor with biological and facial aging acceleration, using logistic regression models adjusted for multiple important covariates. Furthermore, restricted to 99,180 participants with complete psychological and trauma-related data, we identified clusters of individuals with distinct psycho-trauma patterns using the latent class analysis method and assessed their associations with aging acceleration using similar models.

RESULTS

We observed most of the studied psycho-trauma factors were associated with biological and facial aging acceleration. Compared to the "Absence of trauma and psychopathology" cluster, the "adverse childhood experiences (ACEs) with psychopathology" cluster showed strong associations with those aging measurements (odds ratio [OR] = 1.13 [1.05 - 1.23] for biological and 1.52 [1.18 - 1.95] for facial aging acceleration), while no such association was observed for the "ACEs without psychopathology" cluster (1.04 [0.99 - 1.09] and 1.02 [0.84 - 1.24].

CONCLUSIONS

Our study demonstrated significant associations of psycho-trauma factors with both biological and facial aging acceleration. The differential aging consequences observed among ACEs exposed individuals with and without psychopathology prompt interventions aimed to improve individuals' psychological resilience to prevent aging acceleration.

Exploring the Bidirectional Causal Pathways Between Smoking Behaviors and Headache: A Mendelian Randomization Study

INTRODUCTION

Although observational data suggest a relationship between headache and smoking, there remain questions about causality. Smoking may increase headache risk, individuals may smoke to alleviate headaches, or smoking and headache may share common risk factors. Mendelian randomization (MR) is a method that uses genetic variants as instruments for making causal inferences about an exposure and an outcome.

AIMS AND METHODS

First, we conducted logistic regression of observational data in UK Biobank assessing the association between smoking behaviors (smoking status, cigarettes per day amongst daily smokers, and lifetime smoking score) on the risk of self-reported headache (in the last month and for more than 3 months). Second, we used genetic instruments for smoking behaviors and headache (identified in independent genome-wide association studies [GWAS]) to perform bidirectional MR analysis.

RESULTS

Observationally, there is a weak association between smoking behavior and experiencing headache, with increased cigarettes per day associated with increased headache risk. In the MR analysis, genetic liability to smoking initiation and lifetime smoking increased odds of headache in the last month but not odds of headaches lasting more than 3 months. In the opposite direction, there was weak evidence for higher genetic liability to headaches decreasing the chance of quitting.

CONCLUSIONS

There was weak evidence for a partially bidirectional causal relationship between smoking behaviors and headache in the last month. Given this relationship is distinct from smoking heaviness, it suggests headache and smoking may share common risk factors such as personality traits.

IMPLICATIONS

Using MR, this study addresses the uncertainty regarding the observed relationship between headache and smoking. There was evidence for weak causal effects of smoking initiation and lifetime smoking (but not smoking heaviness) on likelihood of experiencing headache in the last month, but not over a prolonged period of more than 3 months. Those with higher genetic liability to headaches were also less likely to successfully stop smoking. This partially bidirectional causal relationship distinct from smoking heaviness suggests that observed associations are unlikely due to biological effects of tobacco smoke exposure and may be explained by shared personality traits.

Socioeconomic traits and the risk of Barrett’s esophagus and gastroesophageal reflux disease: A Mendelian randomization study

BACKGROUND

Previous observational studies have shown that the prevalence of gastroesophageal reflux disease (GERD) and Barrett’s esophagus (BE) is associated with socioeconomic status. However, due to the methodological limitations of traditional observational studies, it is challenging to definitively establish causality.

AIM

To explore the causal relationship between the prevalence of these conditions and socioeconomic status using Mendelian randomization (MR).

METHODS

We initially screened single nucleotide polymorphisms (SNPs) to serve as proxies for eight socioeconomic status phenotypes for univariate MR analysis. The inverse variance weighted (IVW) method was used as the primary analytical method to estimate the causal relationship between the eight socioeconomic status phenotypes and the risk of GERD and BE. We then collected combinations of SNPs as composite proxies for the eight socioeconomic phenotypes to perform multivariate MR (MVMR) analyses based on the IVW MVMR model. Furthermore, a two-step MR mediation analysis was used to examine the potential mediation of the associations by body mass index, major depressive disorder (MDD), smoking, alcohol consumption, and sleep duration.

RESULTS

The study identified three socioeconomic statuses that had a significant impact on GERD. These included household income [odds ratio (OR): 0.46; 95% confidence interval (95%CI): 0.31-0.70], education attainment (OR: 0.23; 95%CI: 0.18-0.29), and the Townsend Deprivation Index at recruitment (OR: 1.57; 95%CI: 1.04-2.37). These factors were found to independently and predominantly influence the genetic causal effect of GERD. Furthermore, the mediating effect of educational attainment on GERD was found to be mediated by MDD (proportion mediated: 10.83%). Similarly, the effect of educational attainment on BE was mediated by MDD (proportion mediated: 10.58%) and the number of cigarettes smoked per day (proportion mediated: 3.50%). Additionally, the mediating effect of household income on GERD was observed to be mediated by sleep duration (proportion mediated: 9.75%)

CONCLUSION

This MR study shed light on the link between socioeconomic status and GERD or BE, providing insights for the prevention of esophageal cancer and precancerous lesions.

Socioeconomic traits and the risk of Barrett's esophagus and gastroesophageal reflux disease: A Mendelian randomization study

BACKGROUND

Previous observational studies have shown that the prevalence of gastroesophageal reflux disease (GERD) and Barrett's esophagus (BE) is associated with socioeconomic status. However, due to the methodological limitations of traditional observational studies, it is challenging to definitively establish causality.

AIM

To explore the causal relationship between the prevalence of these conditions and socioeconomic status using Mendelian randomization (MR).

METHODS

We initially screened single nucleotide polymorphisms (SNPs) to serve as proxies for eight socioeconomic status phenotypes for univariate MR analysis. The inverse variance weighted (IVW) method was used as the primary analytical method to estimate the causal relationship between the eight socioeconomic status phenotypes and the risk of GERD and BE. We then collected combinations of SNPs as composite proxies for the eight socioeconomic phenotypes to perform multivariate MR (MVMR) analyses based on the IVW MVMR model. Furthermore, a two-step MR mediation analysis was used to examine the potential mediation of the associations by body mass index, major depressive disorder (MDD), smoking, alcohol consumption, and sleep duration.

RESULTS

The study identified three socioeconomic statuses that had a significant impact on GERD. These included household income [odds ratio (OR): 0.46; 95% confidence interval (95%CI): 0.31-0.70], education attainment (OR: 0.23; 95%CI: 0.18-0.29), and the Townsend Deprivation Index at recruitment (OR: 1.57; 95%CI: 1.04-2.37). These factors were found to independently and predominantly influence the genetic causal effect of GERD. Furthermore, the mediating effect of educational attainment on GERD was found to be mediated by MDD (proportion mediated: 10.83%). Similarly, the effect of educational attainment on BE was mediated by MDD (proportion mediated: 10.58%) and the number of cigarettes smoked per day (proportion mediated: 3.50%). Additionally, the mediating effect of household income on GERD was observed to be mediated by sleep duration (proportion mediated: 9.75%).

CONCLUSION

This MR study shed light on the link between socioeconomic status and GERD or BE, providing insights for the prevention of esophageal cancer and precancerous lesions.

Different effects of 24 dietary intakes on gastroesophageal reflux disease: A mendelian randomization

BACKGROUND

In observational studies, dietary intakes are associated with gastroesophageal reflux disease (GERD).

AIM

To conduct a two-sample mendelian randomization (MR) analysis to determine whether those associations are causal.

METHODS

To explore the relationship between dietary intake and the risk of GERD, we extracted appropriate single nucleotide polymorphisms from genome-wide association study data on 24 dietary intakes. Three methods were adopted for data analysis: Inverse variance weighting, weighted median methods, and MR-Egger's method. The odds ratio (OR) and 95% confidence interval (CI) were used to evaluate the causal association between dietary intake and GERD.

RESULTS

Our univariate Mendelian randomization (UVMR) results showed significant evidence that pork intake (OR, 2.83; 95%CI: 1.76-4.55; P = 1.84 × 10-5), beer intake (OR, 2.70, 95%CI: 2.00-3.64; P = 6.54 × 10-11), non-oily fish intake (OR, 2.41; 95%CI: 1.49-3.91; P = 3.59 × 10-4) have a protective effect on GERD. In addition, dried fruit intake (OR, 0.37; 95%CI: 0.27-0.50; 6.27 × 10-11), red wine intake (OR, 0.34; 95%CI: 0.25-0.47; P = 1.90 × 10-11), cheese intake (OR, 0.46; 95%CI: 0.39-0.55; P =3.73 × 10-19), bread intake (OR, 0.72; 95%CI: 0.56-0.92; P = 0.0009) and cereal intake (OR, 0.45; 95%CI: 0.36-0.57; P = 2.07 × 10-11) were negatively associated with the risk of GERD. There was a suggestive association for genetically predicted coffee intake (OR per one SD increase, 1.22, 95%CI: 1.03-1.44; P = 0.019). Multivariate Mendelian randomization further confirmed that dried fruit intake, red wine intake, cheese intake, and cereal intake directly affected GERD. In contrast, the impact of pork intake, beer intake, non-oily fish intake, and bread intake on GERD was partly driven by the common risk factors for GERD. However, after adjusting for all four elements, there was no longer a suggestive association between coffee intake and GERD.

CONCLUSION

This study provides MR evidence to support the causal relationship between a broad range of dietary intake and GERD, providing new insights for the treatment and prevention of GERD.

A phenome-wide association and Mendelian randomisation study of alcohol use variants in a diverse cohort comprising over 3 million individuals

BACKGROUND

Alcohol consumption is associated with numerous negative social and health outcomes. These associations may be direct consequences of drinking, or they may reflect common genetic factors that influence both alcohol consumption and other outcomes.

METHODS

We performed exploratory phenome-wide association studies (PheWAS) of three of the best studied protective single nucleotide polymorphisms (SNPs) in genes encoding ethanol metabolising enzymes (ADH1B: rs1229984-T, rs2066702-A; ADH1C: rs698-T) using up to 1109 health outcomes across 28 phenotypic categories (e.g., substance-use, mental health, sleep, immune, cardiovascular, metabolic) from a diverse 23andMe cohort, including European (N ≤ 2,619,939), Latin American (N ≤ 446,646) and African American (N ≤ 146,776) populations to uncover new and perhaps unexpected associations. These SNPs have been consistently implicated by both candidate gene studies and genome-wide association studies of alcohol-related behaviours but have not been investigated in detail for other relevant phenotypes in a hypothesis-free approach in such a large cohort of multiple ancestries. To provide insight into potential causal effects of alcohol consumption on the outcomes significant in the PheWAS, we performed univariable two-sample and one-sample Mendelian randomisation (MR) analyses.

FINDINGS

The minor allele rs1229984-T, which is protective against alcohol behaviours, showed the highest number of PheWAS associations across the three cohorts (N = 232, European; N = 29, Latin American; N = 7, African American). rs1229984-T influenced multiple domains of health. We replicated associations with alcohol-related behaviours, mental and sleep conditions, and cardio-metabolic health. We also found associations with understudied traits related to neurological (migraines, epilepsy), immune (allergies), musculoskeletal (fibromyalgia), and reproductive health (preeclampsia). MR analyses identified evidence of causal effects of alcohol consumption on liability for 35 of these outcomes in the European cohort.

INTERPRETATION

Our work demonstrates that polymorphisms in genes encoding alcohol metabolising enzymes affect multiple domains of health beyond alcohol-related behaviours. Understanding the underlying mechanisms of these effects could have implications for treatments and preventative medicine.

FUNDING

MVJ, NCK, SBB, SSR and AAP were supported by T32IR5226 and 28IR-0070. SSR was also supported by NIDA DP1DA054394. NCK and RBC were also supported by R25MH081482. ASH was supported by funds from NIAAA K01AA030083. JLMO was supported by VA 1IK2CX002095. JLMO and JJMM were also supported by NIDA R21DA050160. JJMM was also supported by the Kavli Postdoctoral Award for Academic Diversity. EGA was supported by K01MH121659 from the NIMH/NIH, the Caroline Wiess Law Fund for Research in Molecular Medicine and the ARCO Foundation Young Teacher-Investigator Fund at Baylor College of Medicine. MSA was supported by the Instituto de Salud Carlos III and co-funded by the European Union Found: Fondo Social Europeo Plus (FSE+) (P19/01224, PI22/00464 and CP22/00128).

Iron status and sarcopenia-related traits: a bi-directional Mendelian randomization study

Although serum iron status and sarcopenia are closely linked, the presence of comprehensive evidence to establish a causal relationship between them remains insufficient. The objective of this study is to employ Mendelian randomization techniques to clarify the association between serum iron status and sarcopenia. We conducted a bi-directional Mendelian randomization (MR) analysis to investigate the potential causal relationship between iron status and sarcopenia. MR analyses were performed using inverse variance weighted (IVW), MR-Egger, and weighted median methods. Additionally, sensitivity analyses were conducted to verify the reliability of the causal association results. Then, we harvested a combination of SNPs as an integrated proxy for iron status to perform a MVMR analysis based on IVW MVMR model. UVMR analyses based on IVW method identified causal effect of ferritin on appendicular lean mass (ALM, β = - 0.051, 95% CI - 0.072, - 0.031, p = 7.325 × 10-07). Sensitivity analyses did not detect pleiotropic effects or result fluctuation by outlying SNPs in the effect estimates of four iron status on sarcopenia-related traits. After adjusting for PA, the analysis still revealed that each standard deviation higher genetically predicted ferritin was associated with lower ALM (β = - 0.054, 95% CI - 0.092, - 0.015, p = 0.006). Further, MVMR analyses determined a predominant role of ferritin (β = - 0.068, 95% CI - 0.12, - 0.017, p = 9.658 × 10-03) in the associations of iron status with ALM. Our study revealed a causal association between serum iron status and sarcopenia, with ferritin playing a key role in this relationship. These findings contribute to our understanding of the complex interplay between iron metabolism and muscle health.

The relationship between emotional disorders and heart rate variability: A Mendelian randomization study

OBJECTIVE

Previous studies have shown that emotional disorders are negatively associated with heart rate variability (HRV), but the potential causal relationship between genetic susceptibility to emotional disorders and HRV remains unclear. We aimed to perform a Mendelian randomization (MR) study to investigate the potential association between emotional disorders and HRV.

METHODS

The data used for this study were obtained from publicly available genome-wide association study datasets. Five models, including the inverse variance weighted model (IVW), the weighted median estimation model (WME), the weighted model-based method (WM), the simple model (SM) and the MR-Egger regression model (MER), were utilized for MR. The leave-one-out sensitivity test, MR pleiotropy residual sum and outlier test (MR-PRESSO) and Cochran's Q test were used to confirm heterogeneity and pleiotropy.

RESULTS

MR analysis revealed that genetic susceptibility to broad depression was negatively correlated with HRV (pvRSA/HF) (OR = 0.380, 95% CI 0.146-0.992; p = 0.048). However, genetic susceptibility to irritability was positively correlated with HRV (pvRSA/HF, SDNN) (OR = 2.017, 95% CI 1.152-3.534, p = 0.008) (OR = 1.154, 95% CI 1.000-1.331, p = 0.044). Genetic susceptibility to anxiety was positively correlated with HRV (RMSSD) (OR = 2.106, 95% CI 1.032-4.299; p = 0.041). No significant directional pleiotropy or heterogeneity was detected. The accuracy and robustness of these findings were confirmed through a sensitivity analysis.

CONCLUSIONS

Our MR study provides genetic support for the causal effects of broad depression, irritable mood, and anxiety on HRV.

Estimating the health impact of nicotine exposure by dissecting the effects of nicotine versus non-nicotine constituents of tobacco smoke: A multivariable Mendelian randomisation study

The detrimental health effects of smoking are well-known, but the impact of regular nicotine use without exposure to the other constituents of tobacco is less clear. Given the increasing daily use of alternative nicotine delivery systems, such as e-cigarettes, it is increasingly important to understand and separate the effects of nicotine use from the impact of tobacco smoke exposure. Using a multivariable Mendelian randomisation framework, we explored the direct effects of nicotine compared with the non-nicotine constituents of tobacco smoke on health outcomes (lung cancer, chronic obstructive pulmonary disease [COPD], forced expiratory volume in one second [FEV-1], forced vital capacity [FVC], coronary heart disease [CHD], and heart rate [HR]). We used Genome-Wide Association Study (GWAS) summary statistics from Buchwald and colleagues, the GWAS and Sequencing Consortium of Alcohol and Nicotine, the International Lung Cancer Consortium, and UK Biobank. Increased nicotine metabolism increased the risk of COPD, lung cancer, and lung function in the univariable analysis. However, when accounting for smoking heaviness in the multivariable analysis, we found that increased nicotine metabolite ratio (indicative of decreased nicotine exposure per cigarette smoked) decreases heart rate (b = -0.30, 95% CI -0.50 to -0.10) and lung function (b = -33.33, 95% CI -41.76 to -24.90). There was no clear evidence of an effect on the remaining outcomes. The results suggest that these smoking-related outcomes are not due to nicotine exposure but are caused by the other components of tobacco smoke; however, there are multiple potential sources of bias, and the results should be triangulated using evidence from a range of methodologies.

Gene-environment interaction in myopia

Myopia is a health issue that has attracted global attention due to its high prevalence and vision-threatening complications. It is well known that the onset and progression of myopia are related to both genetic and environmental factors: more than 450 common genetic loci have been found to be associated with myopia, while near work and outdoor time are the main environmental risk factors. As for many complex traits, gene-environment interactions are implicated in myopia development. To date, several genetic loci have been found to interact with near work or educational level. Gene-environment interaction research on myopia could yield models that provide more accurate risk predictions, thus improving targeted treatments and preventive strategies. Additionally, such investigations might have the potential to reveal novel genetic information. In this review, we summarised the findings in this field and proposed some topics for future investigations.

Association between adiposity and facial aging: results from a Mendelian randomization study

BACKGROUND

Skin, as a sociologically meaningful interface, has psychological implications different from other organs, particularly in the context of the global population aging. Growing evidence suggests that facial aging is associated with an increased risk of adiposity. Existing research, however, were observational, and while they may find some correlations, it is difficult to simply disentangle non-causal or reverse-causal links because these associations may be confounded or fail to accurately reflect true causative linkages.

OBJECTIVES

We conducted a 2-sample Mendelian randomization (MR) study to examine the potential effect of facial aging on the risk of broad obesity and its three major adiposity indicators, including body mass index (BMI), body fat percentage (BF%) and waist circumference (WC).

METHODS

Genetic instruments from IEU OpenGWAS project, one of the largest available genome-wide association studies (GWAS) for facial aging (423,999 samples) were used to investigate the relation to broad obesity (32,858 cases, 65,839 controls). Using the inverse-variance weighted (IVW) technique, single nucleotide polymorphisms (SNPs) associated with adiposity indicators (BMI (461,460 samples), BF% (454,633 samples), and WC (462,166 samples)) were investigated in relationship to facial aging. Further sensitivity analyses were performed, including Mendelian randomization-Egger (MR-Egger), weighted median estimates, and leave-one-out analysis, to evaluate the consistency of the results and related potential issues in MR studies.

RESULTS

We identified strong and significant correlations between adiposity and facial aging in the 17 broad obesity-associated SNPs (IVW estimate of odds ratio OR = 1.020, 95% CI 1.010-1.029, P = 7.303e - 05), 458 BMI-associated SNPs (IVW estimate of odds ratio OR = 1.047, 95% CI 1.0357-1.058, P = 1.154e - 16),for the 395 BF%-associated SNPs (OR = 1.056, 95%CI 1.040-1.072,P = 7.617e - 12), or for the 374 WC-associated SNPs (OR = 1.072, 95% CI 1057-1.087,P = 1.229e - 23). A range of complementary methodologies have been employed to evaluate horizontal pleiotropy and related potential caveats occurring in MR research.

CONCLUSIONS

Using Mendelian randomization as an alternative approach to investigate causality, we found a causal relationship between adiposity and facial aging, which was statistically strong and significant.

Evaluation for causal effects of socioeconomic traits on risk of female genital prolapse (FGP): a multivariable Mendelian randomization analysis

BACKGROUND

Although observational studies have established some socioeconomic traits to be independent risk factors for pelvic organ prolapse (POP), they can not infer causality since they are easily biased by confounding factors and reverse causality. Moreover, it remains ambiguous which one or several of socioeconomic traits play predominant roles in the associations with POP risk. Mendelian randomization (MR) overcomes these biases and can even determine one or several socioeconomic traits predominantly accounting for the associations.

OBJECTIVE

We conducted a multivariable Mendelian randomization (MVMR) analysis to disentangle whether one or more of five categories of socioeconomic traits, "age at which full-time education completed (abbreviated as "EA")", "job involving heavy manual or physical work ("heavy work")", "average total household income before tax (income)", "Townsend deprivation index at recruitment (TDI)", and "leisure/social activities" exerted independent and predominant effects on POP risk.

METHODS

We first screened single-nucleotide polymorphisms (SNPs) as proxies for five individual socioeconomic traits and female genital prolapse (FGP, approximate surrogate for POP due to no GWASs for POP) to conduct Univariable Mendelian randomization (UVMR) analyses to estimate causal associations of five socioeconomic traits with FGP risk using IVW method as major analysis. Additionally, we conducted heterogeneity, pleiotropy, and sensitivity analysis to assess the robustness of our results. Then, we harvested a combination of SNPs as an integrated proxy for the five socioeconomic traits to perform a MVMR analysis based on IVW MVMR model.

RESULTS

UVMR analyses based on IVW method identified causal effect of EA (OR 0.759, 95%CI 0.629-0.916, p = 0.004), but denied that of the other five traits on FGP risk (all p > 0.05). Heterogeneity analyses, pleiotropy analyses, "leave-one-out" sensitivity analyses and MR-PRESSO adjustments did not detect heterogeneity, pleiotropic effects, or result fluctuation by outlying SNPs in the effect estimates of six socioeconomic traits on FGP risk (all p > 0.05). Further, MVMR analyses determined a predominant role of EA playing in the associations of socioeconomic traits with FGP risk based on both MVMR Model 1 (OR 0.842, 95%CI 0.744-0.953, p = 0.006) and Model 2 (OR 0.857, 95%CI 0.759-0.967, p = 0.012).

CONCLUSION

Our UVMR and MVMR analyses provided genetic evidence that one socioeconomic trait, lower educational attainment, is associated with risk of female genital prolapse, and even independently and predominantly accounts for the associations of socioeconomic traits with risk of female genital prolapse.

Associations between health behaviours, fertility and reproductive outcomes: triangulation of evidence in the Norwegian Mother, Father and Child Cohort Study (MoBa)

BACKGROUND

Guidance to improve fertility includes reducing alcohol and caffeine consumption, achieving healthy weight-range and stopping smoking. Advice is informed by observational evidence, which is often biased by confounding.

METHODS

This study primarily used data from a pregnancy cohort, the Norwegian Mother, Father and Child Cohort Study. First, we conducted multivariable regression of health behaviours (alcohol and caffeine consumption, body-mass index (BMI), and smoking) on fertility outcomes (e.g. time to conception) and reproductive outcomes (e.g. age at first birth) (n = 84,075 females, 68,002 males), adjusting for birth year, education and attention-deficit and hyperactive-impulsive (ADHD) traits. Second, we used individual-level Mendelian randomisation (MR) to explore possible causal effects of health behaviours on fertility/reproductive outcomes (n = 63,376 females, 45,460 males). Finally, we performed summary-level MR for available outcomes in UK Biobank (n = 91,462-1,232,091) and controlled for education and ADHD liability using multivariable MR.

RESULTS

In multivariable regression analyses, higher BMI associated with fertility (longer time to conception, increased odds of infertility treatment and miscarriage), and smoking was associated with longer time to conception. In individual-level MR analyses, there was strong evidence for effects of smoking initiation and higher BMI on younger age at first birth, of higher BMI on increased time to conception, and weak evidence for effects of smoking initiation on increased time to conception. Age at first birth associations were replicated in summary-level MR analysis; however, effects attenuated using multivariable MR.

CONCLUSIONS

Smoking behaviour and BMI showed the most consistent associations for increased time to conception and a younger age at first birth. Given that age at first birth and time to conception are positively correlated, this suggests that the mechanisms for reproductive outcomes are distinct to the mechanisms acting on fertility outcomes. Multivariable MR suggested that effects on age at first birth might be explained by underlying liability to ADHD and education.

Effects of insomnia and non-vasomotor menopausal symptoms on coronary heart disease risk: a mendelian randomization study

Background

Previous studies suggested that vasomotor symptoms were associated with an increasing risk of coronary heart diseases (CHD) but not clear with menopausal symptoms other than vasomotor symptoms. Given the heterogeneity and interrelationship among menopausal symptoms, it is not easy to make causal inferences based on observational studies. We performed a Mendelian randomization (MR) to investigate the association of individual non-vasomotor menopausal symptoms and the risk of CHDs.

Methods

A sample of 177,497 British women aged ≥51 years old (average age at menopause) without related cardiovascular diseases from the UK biobank is selected as our study population. Non-vasomotor menopausal symptoms, including anxiety, nervous, insomnia, urinary tract infection, fatigue, and vertigo, were selected as exposures based on the modified Kupperman index. Outcome variable is CHD.

Results

In total, 54, 47, 24, 33, 22, and 81 instrumental variables were selected for anxiety, insomnia, fatigue, vertigo, urinary tract infection and nervous respectively. We conducted MR analyses of menopausal symptoms and CHD. Only insomnia symptoms increased the lifetime risk of CHD with OR 1.394 (p = 0.0003). There were no significant causal relationships with CHD and other menopausal symptoms. Insomnia near menopause age (45-50 years) does not increase the risk of CHD. However, postmenopausal (over 51) insomnia increases the risk of CHD.

Conclusion

MR analyses support that among non-vasomotor menopausal symptoms, only insomnia symptoms may increase the lifetime risk of CHD. Insomnia at different ages near menopause has differential impacts on CHD risk.

An integrated genome and phenome-wide association study approach to understanding Alzheimer's disease predisposition

Genome-wide association studies (GWAS) have identified common single nucleotide polymorphisms (SNPs) that increase late-onset Alzheimer's disease (LOAD) risk. To identify additional LOAD-associated variants and provide insight into underlying disease biology, we performed a phenome-wide association study on 23 known LOAD-associated SNPs and 4:1 matched control SNPs using UK Biobank data. LOAD-associated SNPs were significantly enriched for associations with 8/778 queried traits, including 3 platelet traits. The strongest enrichment was for platelet distribution width (PDW) (p = 1.2 × 10-5), but increased PDW was not associated with LOAD susceptibility in Mendelian randomization analysis. Of 384 PDW-associated SNPs identified by prior GWAS, 36 were nominally associated with LOAD risk (17,008 cases; 37,154 controls) and 5 survived false-discovery rate correction. Associations confirmed known LOAD risk loci near PICALM, CD2AP, SPI1, and NDUFAF6, and identified a novel risk locus in epidermal growth factor receptor. Integrating GWAS and phenome-wide association study data reveals substantial pleiotropy between genetic determinants of LOAD and of platelet morphology, and for the first time implicates epidermal growth factor receptor - a mediator of β-amyloid toxicity - in Alzheimer's disease susceptibility.

Identifying potential causal effects of age at menopause: a Mendelian randomization phenome-wide association study

Age at natural menopause (ANM) is associated with a range of health-related traits, including bone health, female reproductive cancers, and cardiometabolic health. Our objective was to conduct a Mendelian randomization phenome-wide association study (MR-pheWAS) of ANM. We conducted a hypothesis-free analysis of the genetic risk score (GRS) for ANM with 18,961 health-related traits among 181,279 women in UK Biobank. We also stratified the GRS according to the involvement of SNPs in DNA damage response. We sought to replicate our findings in independent cohorts. We conducted a negative control MR-pheWAS among men. Among women, we identified potential effects of ANM on 221 traits (1.17% of all traits) at a false discovery rate (P value ≤ 5.83 × 10^-4), and 91 (0.48%) potential effects when using Bonferroni threshold (P value ≤ 2.64 × 10^-6). Our findings included 55 traits directly related to ANM (e.g. hormone replacement therapy, gynaecological conditions and menstrual conditions), and liver function, kidney function, lung function, blood-cell composition, breast cancer and bone and cardiometabolic health. Replication analyses confirmed that younger ANM was associated with HbA1c (adjusted mean difference 0.003 mmol/mol; 95% CI 0.001, 0.006 per year decrease in ANM), breast cancer (adjusted OR 0.96; 95% CI 0.95, 0.98), and bone-mineral density (adjusted mean difference - 0.05; 95% CI - 0.07, - 0.03 for lumbar spine). In men, 30 traits were associated with the GRS at a false discovery rate (P value ≤ 5.49 × 10^-6), and 11 potential effects when using Bonferroni threshold (P value ≤ 2.75 × 10^-6). In conclusion, our results suggest that younger ANM has potential causal effects on a range of health-related traits.

Phenotypic Causal Inference Using Genome-Wide Association Study Data: Mendelian Randomization and Beyond

statistics for genome-wide association studies (GWAS) are increasingly available for downstream analyses. Meanwhile, the popularity of causal inference methods has grown as we look to gather robust evidence for novel medical and public health interventions. This has led to the development of methods that use GWAS summary statistics for causal inference. Here, we describe these methods in order of their escalating complexity, from genetic associations to extensions of Mendelian randomization that consider thousands of phenotypes simultaneously. We also cover the assumptions and limitations of these approaches before considering the challenges faced by researchers performing causal inference using GWAS data. GWAS summary statistics constitute an important data source for causal inference research that offers a counterpoint to nongenetic methods when triangulating evidence. Continued efforts to address the challenges in using GWAS data for causal inference will allow the full impact of these approaches to be realized.

Vitamin D and brain health: an observational and Mendelian randomization study

BACKGROUND

Higher vitamin D status has been suggested to have beneficial effects on the brain.

OBJECTIVES

To investigate the association between 25-hydroxyvitamin D [25(OH)D], neuroimaging features, and the risk of dementia and stroke.

METHODS

We used prospective data from the UK Biobank (37-73 y at baseline) to examine the association between 25(OH)D concentrations with neuroimaging outcomes (N = 33,523) and the risk of dementia and stroke (N = 427,690; 3414 and 5339 incident cases, respectively). Observational analyses were adjusted for age, sex, ethnicity, month, center, and socioeconomic, lifestyle, sun behavior, and illness-related factors. Nonlinear Mendelian randomization (MR) analyses were used to test for underlying causality for neuroimaging outcomes (N = 23,901) and dementia and stroke (N = 294,514; 2399 and 3760 cases, respectively).

RESULTS

Associations between 25(OH)D and total, gray matter, white matter, and hippocampal volumes were nonlinear, with lower volumes both for low and high concentrations (adjusted P-nonlinear ≤ 0.04). 25(OH)D had an inverse association with white matter hyperintensity volume [per 10 nmol/L 25(OH)D; adjusted β: -6.1; 95% CI: -11.5, -7.0]. Vitamin D deficiency was associated with an increased risk of dementia and stroke, with the strongest associations for those with 25(OH)D <25 nmol/L (compared with 50-75.9 nmol/L; adjusted HR: 1.79; 95% CI: 1.57, 2.04 and HR: 1.40; 95% CI: 1.26, 1.56, respectively). Nonlinear MR analyses confirmed the threshold effect of 25(OH)D on dementia, with the risk predicted to be 54% (95% CI: 1.21, 1.96) higher for participants at 25 nmol/L compared with 50 nmol/L. 25(OH)D was not associated with neuroimaging outcomes or the risk of stroke in MR analyses. Potential impact fraction suggests 17% (95% CI: 7.22, 30.58) of dementia could be prevented by increasing 25(OH)D to 50 nmol/L.

CONCLUSIONS

Low vitamin D status was associated with neuroimaging outcomes and the risks of dementia and stroke even after extensive covariate adjustment. MR analyses support a causal effect of vitamin D deficiency on dementia but not on stroke risk.

Exploring and mitigating potential bias when genetic instrumental variables are associated with multiple non-exposure traits in Mendelian randomization

With the increasing size and number of genome-wide association studies, individual single nucleotide polymorphisms are increasingly found to associate with multiple traits. Many different mechanisms could result in proposed genetic IVs for an exposure of interest being associated with multiple non-exposure traits, some of which could bias MR results. We describe and illustrate, through causal diagrams, a range of scenarios that could result in proposed IVs being related to non-exposure traits in MR studies. These associations could occur due to five scenarios: (i) confounding, (ii) vertical pleiotropy, (iii) horizontal pleiotropy, (iv) reverse causation and (v) selection bias. For each of these scenarios we outline steps that could be taken to explore the underlying mechanism and mitigate any resulting bias in the MR estimation. We recommend MR studies explore possible IV-non-exposure associations across a wider range of traits than is usually the case. We highlight the pros and cons of relying on sensitivity analyses without considering particular pleiotropic paths versus systematically exploring and controlling for potential pleiotropic or other biasing paths via known traits. We apply our recommendations to an illustrative example of the effect of maternal insomnia on offspring birthweight in UK Biobank.

Nonparametric bounds in two-sample summary-data Mendelian randomization: Some cautionary tales for practice

Recently, in genetic epidemiology, Mendelian randomization (MR) has become a popular approach to estimate causal exposure effects by using single nucleotide polymorphisms from genome-wide association studies (GWAS) as instruments. The most popular type of MR study, a two-sample summary-data MR study, relies on having summary statistics from two independent GWAS and using parametric methods for estimation. However, little is understood about using a nonparametric bound-based analysis, a popular approach in traditional instrumental variables frameworks, to study causal effects in two-sample MR. In this article, we explore using a nonparametric, bound-based analysis in two-sample MR studies, focusing primarily on implications for practice. We also propose a framework to assess how likely one can obtain more informative bounds if we used a different MR design, notably a one-sample MR design. We conclude by demonstrating our findings through two real data analyses concerning the causal effect of smoking on lung cancer and the causal effect of high cholesterol on heart attacks. Overall, our results suggest that while a bound-based analysis may be appealing due to its nonparametric nature, it is far more conservative in two-sample settings than in one-sample settings to get informative bounds on the causal exposure effect.

Systematic review of Mendelian randomization studies on risk of cancer

BACKGROUND

We aimed to map and describe the current state of Mendelian randomization (MR) literature on cancer risk and to identify associations supported by robust evidence.

METHODS

We searched PubMed and Scopus up to 06/10/2020 for MR studies investigating the association of any genetically predicted risk factor with cancer risk. We categorized the reported associations based on a priori designed levels of evidence supporting a causal association into four categories, namely robust, probable, suggestive, and insufficient, based on the significance and concordance of the main MR analysis results and at least one of the MR-Egger, weighed median, MRPRESSO, and multivariable MR analyses. Associations not presenting any of the aforementioned sensitivity analyses were not graded.

RESULTS

We included 190 publications reporting on 4667 MR analyses. Most analyses (3200; 68.6%) were not accompanied by any of the assessed sensitivity analyses. Of the 1467 evaluable analyses, 87 (5.9%) were supported by robust, 275 (18.7%) by probable, and 89 (6.1%) by suggestive evidence. The most prominent robust associations were observed for anthropometric indices with risk of breast, kidney, and endometrial cancers; circulating telomere length with risk of kidney, lung, osteosarcoma, skin, thyroid, and hematological cancers; sex steroid hormones and risk of breast and endometrial cancer; and lipids with risk of breast, endometrial, and ovarian cancer.

CONCLUSIONS

Despite the large amount of research on genetically predicted risk factors for cancer risk, limited associations are supported by robust evidence for causality. Most associations did not present a MR sensitivity analysis and were thus non-evaluable. Future research should focus on more thorough assessment of sensitivity MR analyses and on more transparent reporting.

The Promise of Mendelian Randomization in Parkinson's Disease: Has the Smoke Cleared Yet for Smoking and Parkinson's Disease Risk?

This commentary discusses the strengths and limitations of utilizing the Mendelian randomization (MR) approach in Parkinson's disease (PD) studies. Epidemiologists proposed to employ MR when genetic instruments are available that represent reliable proxies for modifiable lifelong exposures which elude easy measurement in studies of late onset diseases like PD. Here, we are using smoking as an example. The great promise of the MR approach is its resilience to confounding and reverse causation. Nevertheless, the approach has some drawbacks such as being liable to selection- and survival-bias, it makes some strong assumptions about the genetic instruments employed, and requires very large sample sizes. When interpreted carefully and put into the context of other studies that take both genetics and the environment into consideration, MR studies help us to not only ask interesting questions but also can support causal inference and provide novel insights.

Smoking is significantly associated with increased risk of COVID-19 and other respiratory infections

Observational studies suggest smoking, cannabis use, alcohol consumption, and substance use disorders (SUDs) may impact risk for respiratory infections, including coronavirus 2019 (COVID-2019). However, causal inference is challenging due to comorbid substance use. Using summary-level European ancestry data (>1.7 million participants), we performed single-variable and multivariable Mendelian randomization (MR) to evaluate relationships between substance use behaviors, COVID-19 and other respiratory infections. Genetic liability for smoking demonstrated the strongest associations with COVID-19 infection risk, including the risk for very severe respiratory confirmed COVID-19 (odds ratio (OR) = 2.69, 95% CI, 1.42, 5.10, P-value = 0.002), and COVID-19 infections requiring hospitalization (OR = 3.49, 95% CI, 2.23, 5.44, P-value = 3.74 × 10-8); these associations generally remained robust in models accounting for other substance use and cardiometabolic risk factors. Smoking was also strongly associated with increased risk of other respiratory infections, including asthma-related pneumonia/sepsis (OR = 3.64, 95% CI, 2.16, 6.11, P-value = 1.07 × 10-6), chronic lower respiratory diseases (OR = 2.29, 95% CI, 1.80, 2.91, P-value = 1.69 × 10-11), and bacterial pneumonia (OR = 2.14, 95% CI, 1.42, 3.24, P-value = 2.84 × 10-4). We provide strong genetic evidence showing smoking increases the risk for COVID-19 and other respiratory infections even after accounting for other substance use behaviors and cardiometabolic diseases, which suggests that prevention programs aimed at reducing smoking may be important for the COVID-19 pandemic and have substantial public health benefits.

Using Mendelian randomization analysis to better understand the relationship between mental health and substance use: a systematic review

BACKGROUND

Poor mental health has consistently been associated with substance use (smoking, alcohol drinking, cannabis use, and consumption of caffeinated drinks). To properly inform public health policy it is crucial to understand the mechanisms underlying these associations, and most importantly, whether or not they are causal.

METHODS

In this pre-registered systematic review, we assessed the evidence for causal relationships between mental health and substance use from Mendelian randomization (MR) studies, following PRISMA. We rated the quality of included studies using a scoring system that incorporates important indices of quality, such as the quality of phenotype measurement, instrument strength, and use of sensitivity methods.

RESULTS

Sixty-three studies were included for qualitative synthesis. The final quality rating was '-' for 16 studies, '- +' for 37 studies, and '+'for 10 studies. There was robust evidence that higher educational attainment decreases smoking and that there is a bi-directional, increasing relationship between smoking and (symptoms of) mental disorders. Another robust finding was that higher educational attainment increases alcohol use frequency, but decreases binge-drinking and alcohol use problems, and that mental disorders causally lead to more alcohol drinking without evidence for the reverse.

CONCLUSIONS

The current MR literature increases our understanding of the relationship between mental health and substance use. Bi-directional causal relationships are indicated, especially for smoking, providing further incentive to strengthen public health efforts to decrease substance use. Future MR studies should make use of large(r) samples in combination with detailed phenotypes, a wide range of sensitivity methods, and triangulate with other research methods.

Proxy gene-by-environment Mendelian randomization study confirms a causal effect of maternal smoking on offspring birthweight, but little evidence of long-term influences on offspring health

Background

A lack of genetic data across generations makes transgenerational Mendelian randomization (MR) difficult. We used UK Biobank and a novel proxy gene-by-environment MR to investigate effects of maternal smoking heaviness in pregnancy on offspring health, using participants’ (generation one: G1) genotype (rs16969968 in CHRNA5) as a proxy for their mothers’ (G0) genotype.

Methods

We validated this approach by replicating an established effect of maternal smoking heaviness on offspring birthweight. Then we applied this approach to explore effects of maternal (G0) smoking heaviness on offspring (G1) later life outcomes and on birthweight of G1 women’s children (G2).

Results

Each additional smoking-increasing allele in offspring (G1) was associated with a 0.018 [95% confidence interval (CI): -0.026, -0.009] kg lower G1 birthweight in maternal (G0) smoking stratum, but no meaningful effect (-0.002 kg; 95% CI: -0.008, 0.003) in maternal non-smoking stratum (interaction P-value = 0.004). The differences in associations of rs16969968 with grandchild’s (G2) birthweight between grandmothers (G0) who did, versus did not, smoke were heterogeneous (interaction P-value = 0.042) among mothers (G1) who did (-0.020 kg/allele; 95% CI: -0.044, 0.003), versus did not (0.007 kg/allele; 95% CI: -0.005, 0.020), smoke in pregnancy.

Conclusions

Our study demonstrated how offspring genotype can be used to proxy for the mother’s genotype in gene-by-environment MR. We confirmed the causal effect of maternal (G0) smoking on offspring (G1) birthweight, but found little evidence of an effect on G1 longer-term health outcomes. For grandchild’s (G2) birthweight, the effect of grandmother’s (G0) smoking heaviness in pregnancy may be modulated by maternal (G1) smoking status in pregnancy.

Selection into shift work is influenced by educational attainment and body mass index: a Mendelian randomization study in the UK Biobank

BACKGROUND

Shift work is associated with increased cardiometabolic disease risk. This observation may be partly explained by cardiometabolic risk factors having a role in the selection of individuals into or out of shift work. We performed Mendelian randomization (MR) analyses in the UK Biobank (UKB) to test this hypothesis.

METHODS

We used genetic risk scores (GRS) to proxy nine cardiometabolic risk factors and diseases (including educational attainment, body mass index (BMI), smoking, and alcohol consumption), and tested associations of each GRS with self-reported frequency of current shift work among employed UKB participants of European ancestry (n = 190 573). We used summary-level MR sensitivity analyses to assess robustness of the identified effects, and we tested whether effects were mediated through sleep timing preference.

RESULTS

Genetically instrumented liability to lower educational attainment (odds ratio (OR) per 3.6 fewer years in educational attainment = 2.40, 95% confidence interval (CI) = 2.22-2.59, P = 4.84 × 10-20) and higher body mass index (OR per 4.7 kg/m2 higher BMI = 1.30, 95% CI = 1.14-1.47, P = 5.85 × 10-5) increased odds of reporting participation in frequent shift work. Results were unchanged in sensitivity analyses allowing for different assumptions regarding horizontal pleiotropy. No selection effects were evident for the remaining exposures, nor for any exposures on selection out of shift work. Sleep timing preference did not mediate the effects of BMI and educational attainment on selection into shift work.

CONCLUSIONS

Liability to lower educational attainment and higher BMI may influence selection into shift work. This phenomenon may bias epidemiological studies of shift work that are performed in the UKB.

A genetically-informed study disentangling the relationships between tobacco smoking, cannabis use, alcohol consumption, substance use disorders and respiratory infections, including COVID-19

Background

Observational studies suggest smoking, cannabis use, alcohol consumption, cannabis use, and substance use disorders (SUDs) may play a role in the susceptibility for respiratory infections and disease, including coronavirus 2019 (COVID-2019). However, causal inference is challenging due to comorbid substance use.

Methods

Using genome-wide association study data of European ancestry (data from >1.7 million individuals), we performed single-variable and multivariable Mendelian randomization to evaluate relationships between smoking, cannabis use, alcohol consumption, SUDs, and respiratory infections.

Results

Genetically predicted lifetime smoking was found to be associated with increased risk for hospitalized COVID-19 (odds ratio (OR)=4.039, 95% CI 2.335-6.985, P-value=5.93×10-7) and very severe hospitalized COVID-19 (OR=3.091, 95% CI, 1.883-5.092, P-value=8.40×10-6). Genetically predicted lifetime smoking was also associated with increased risk pneumoniae (OR=1.589, 95% CI, 1.214-2.078, P-value=7.33×10-4), lower respiratory infections (OR=2.303, 95% CI, 1.713-3.097, P-value=3.40×10-8), and several others. Genetically predicted cannabis use disorder (CUD) was associated with increased bronchitis risk (OR=1.078, 95% CI, 1.020-1.128, P-value=0.007).

Conclusions

We provide strong genetic evidence showing smoking increases the risk for respiratory infections and diseases even after accounting for other substance use and abuse. Additionally, we provide find CUD may increase the risk for bronchitis, which taken together, may guide future research SUDs and respiratory outcomes.

Unhealthy Behaviours and Risk of Parkinson's Disease: A Mendelian Randomisation Study

BACKGROUND

Tobacco smoking and alcohol intake have been identified in observational studies as potentially protective factors against developing Parkinson's disease (PD); the impact of body mass index (BMI) on PD risk is debated. Whether such epidemiological associations are causal remains unclear. Mendelian randomsation (MR) uses genetic variants to explore the effects of exposures on outcomes; potentially reducing bias from residual confounding and reverse causation.

OBJECTIVE

Using MR, we examined relationships between PD risk and three unhealthy behaviours: tobacco smoking, alcohol intake, and higher BMI.

METHODS

19,924 PD cases and 2,413,087 controls were included in the analysis. We performed genome-wide association studies to identify single nucleotide polymorphisms associated with tobacco smoking, alcohol intake, and BMI. MR analysis of the relationship between each exposure and PD was undertaken using a split-sample design.

RESULTS

Ever-smoking reduced the risk of PD (OR 0.955; 95%confidence interval [CI] 0.921-0.991; p = 0.013). Higher daily alcohol intake increased the risk of PD (OR 1.125, 95%CI 1.025-1.235; p = 0.013) and a 1 kg/m2 higher BMI reduced the risk of PD (OR 0.988, 95%CI 0.979-0.997; p = 0.008). Sensitivity analyses did not suggest bias from horizontal pleiotropy or invalid instruments.

CONCLUSION

Using split-sample MR in over 2.4 million participants, we observed a protective effect of smoking on risk of PD. In contrast to observational data, alcohol consumption appeared to increase the risk of PD. Higher BMI had a protective effect on PD, but the effect was small.

Relationship between smoking and ALS: Mendelian randomisation interrogation of causality

OBJECTIVE

Smoking has been widely studied as a susceptibility factor for amyotrophic lateral sclerosis (ALS), but results are conflicting and at risk of confounding bias. We used the results of recently published large genome-wide association studies and Mendelian randomisation methods to reduce confounding to assess the relationship between smoking and ALS.

METHODS

Two genome-wide association studies investigating lifetime smoking (n=463 003) and ever smoking (n=1 232 091) were identified and used to define instrumental variables for smoking. A genome-wide association study of ALS (20 806 cases; 59 804 controls) was used as the outcome for inverse variance weighted Mendelian randomisation, and four other Mendelian randomisation methods, to test whether smoking is causal for ALS. Analyses were bidirectional to assess reverse causality.

RESULTS

There was no strong evidence for a causal or reverse causal relationship between smoking and ALS. The results of Mendelian randomisation using the inverse variance weighted method were: lifetime smoking OR 0.94 (95% CI 0.74 to 1.19), p value 0.59; ever smoking OR 1.10 (95% CI 1 to 1.23), p value 0.05.

CONCLUSIONS

Using multiple methods, large sample sizes and sensitivity analyses, we find no evidence with Mendelian randomisation techniques that smoking causes ALS. Other smoking phenotypes, such as current smoking, may be suitable for future Mendelian randomisation studies.

Mendelian randomization case-control PheWAS in UK Biobank shows evidence of causality for smoking intensity in 28 distinct clinical conditions

BACKGROUND

Smoking is one of the greatest threats to public health worldwide. We integrated phenome-wide association study (PheWAS) and Mendelian randomization (MR) approaches to explore causal effects of genetically predicted smoking intensity across the human disease spectrum.

METHODS

We conducted PheWAS case-control analyses in 152,483 ever smokers of White-British ancestry, aged 39-73 years. Disease diagnoses were based on hospital inpatient and mortality registrations. Smoking intensity was instrumented by four genetic variants, and disease risks estimated for one cigarette per day heavier intakes. Associations passing the FDR threshold (p<0•0025) were assessed for causality using several complementary MR approaches.

FINDINGS

Genetically instrumented smoking intensity was associated with 48 conditions, with MR supporting a possible causal effect for 28 distinct outcomes. Each cigarette smoked per day elevated the odds of respiratory diseases by 5% to 33% (nine distinct diseases, including pneumonia, emphysema, obstructive chronic bronchitis, pleurisy, pulmonary collapse, respiratory failure) and the odds of circulatory disease by 5% to 23% (seven diseases, including atherosclerosis, myocardial infarction, congestive heart failure, arterial embolisms). Further effects were seen for cancer within the respiratory system and other neoplasms, renal failure, septicaemia, and retinal disorders. No associations were observed in sensitivity analyses on 185,002 never smokers.

INTERPRETATION

These genetic data demonstrate the substantial adverse health impacts by smoking intensity and suggest notable increases in the risks of several diseases. Public health initiatives should highlight the damage caused by smoking intensity and the potential benefits of reducing or ideally quitting smoking.

Identifying potential causal effects of age at menarche: a Mendelian randomization phenome-wide association study

BACKGROUND

Age at menarche has been associated with various health outcomes. We aimed to identify potential causal effects of age at menarche on health-related traits in a hypothesis-free manner.

METHODS

We conducted a Mendelian randomization phenome-wide association study (MR-pheWAS) of age at menarche with 17,893 health-related traits in UK Biobank (n = 181,318) using PHESANT. The exposure of interest was the genetic risk score for age at menarche. We conducted a second MR-pheWAS after excluding SNPs associated with BMI from the genetic risk score, to examine whether results might be due to the genetic overlap between age at menarche and BMI. We followed up a subset of health-related traits to investigate MR assumptions and seek replication in independent study populations.

RESULTS

Of the 17,893 tests performed in our MR-pheWAS, we identified 619 associations with the genetic risk score for age at menarche at a 5% false discovery rate threshold, of which 295 were below a Bonferroni-corrected P value threshold. These included potential effects of younger age at menarche on lower lung function, higher heel bone-mineral density, greater burden of psychosocial/mental health problems, younger age at first birth, higher risk of childhood sexual abuse, poorer cardiometabolic health, and lower physical activity. After exclusion of variants associated with BMI, the genetic risk score for age at menarche was related to 37 traits at a 5% false discovery rate, of which 29 were below a Bonferroni-corrected P value threshold. We attempted to replicate findings for bone-mineral density, lung function, neuroticism, and childhood sexual abuse using 5 independent cohorts/consortia. While estimates for lung function, higher bone-mineral density, neuroticism, and childhood sexual abuse in replication cohorts were consistent with UK Biobank estimates, confidence intervals were wide and often included the null.

CONCLUSIONS

The genetic risk score for age at menarche was related to a broad range of health-related traits. Follow-up analyses indicated imprecise evidence of an effect of younger age at menarche on greater bone-mineral density, lower lung function, higher neuroticism score, and greater risk of childhood sexual abuse in the smaller replication samples available; hence, these findings need further exploration when larger independent samples become available.