MVMRmode: Introducing an R package for plurality valid estimators for multivariable Mendelian randomisation.

BACKGROUND: Mendelian randomisation (MR) is the use of genetic variants as instrumental variables. Mode-based estimators (MBE) are one of the most popular types of estimators used in univariable-MR studies and is often used as a sensitivity analysis for pleiotropy. However, because there are no plurality valid regression estimators, modal estimators for multivariable-MR have been under-explored. METHODS: We use the residual framework for multivariable-MR to introduce two multivariable modal estimators: multivariable-MBE, which uses IVW to create residuals fed into a traditional plurality valid estimator, and an estimator which instead has the residuals fed into the contamination mixture method (CM), multivariable-CM. We then use Monte-Carlo simulations to explore the performance of these estimators when compared to existing ones and re-analyse the data used by Grant and Burgess (2021) looking at the causal effect of intelligence, education, and household income on Alzheimer's disease as an applied example. RESULTS: In our simulation, we found that multivariable-MBE was generally too variable to be much use. Multivariable-CM produced more precise estimates on the other hand. Multivariable-CM performed better than MR-Egger in almost all settings, and Weighted Median under balanced pleiotropy. However, it underperformed Weighted Median when there was a moderate amount of directional pleiotropy. Our re-analysis supported the conclusion of Grant and Burgess (2021), that intelligence had a protective effect on Alzheimer's disease, while education, and household income do not have a causal effect. CONCLUSIONS: Here we introduced two, non-regression-based, plurality valid estimators for multivariable MR. Of these, "multivariable-CM" which uses IVW to create residuals fed into a contamination-mixture model, performed the best. This estimator uses a plurality of variants valid assumption, and appears to provide precise and unbiased estimates in the presence of balanced pleiotropy and small amounts of directional pleiotropy.

Risk Factors for Intracerebral Hemorrhage: Genome-Wide Association Study and Mendelian Randomization Analyses.

BACKGROUND: The genetic and nongenetic causes of intracerebral hemorrhage (ICH) remain obscure. The present study aimed to uncover the genetic and modifiable risk factors for ICH. METHODS: We meta-analyzed genome-wide association study data from 3 European biobanks, involving 7605 ICH cases and 711 818 noncases, to identify the genomic loci linked to ICH. To uncover the potential causal associations of cardiometabolic and lifestyle factors with ICH, we performed Mendelian randomization analyses using genetic instruments identified in previous genome-wide association studies of the exposures and ICH data from the present genome-wide association study meta-analysis. We performed multivariable Mendelian randomization analyses to examine the independent associations of the identified risk factors with ICH and evaluate potential mediating pathways. RESULTS: We identified 1 ICH risk locus, located at the APOE genomic region. The lead variant in this locus was rs429358 (chr19:45411941), which was associated with an odds ratio of ICH of 1.17 (95% CI, 1.11-1.20; P=6.01×10-11) per C allele. Genetically predicted higher levels of body mass index, visceral adiposity, diastolic blood pressure, systolic blood pressure, and lifetime smoking index, as well as genetic liability to type 2 diabetes, were associated with higher odds of ICH after multiple testing corrections. Additionally, a genetic increase in waist-to-hip ratio and liability to smoking initiation were consistently associated with ICH, albeit at the nominal significance level (P<0.05). Multivariable Mendelian randomization analysis showed that the association between body mass index and ICH was attenuated on adjustment for type 2 diabetes and further that type 2 diabetes may be a mediator of the body mass index-ICH relationship. CONCLUSIONS: Our findings indicate that the APOE locus contributes to ICH genetic susceptibility in European populations. Excess adiposity, elevated blood pressure, type 2 diabetes, and smoking were identified as the chief modifiable cardiometabolic and lifestyle factors for ICH.

Selecting Invalid Instruments to Improve Mendelian Randomization with Two-Sample Summary Data.

Mendelian randomization (MR) is a widely-used method to estimate the causal relationship between a risk factor and disease. A fundamental part of any MR analysis is to choose appropriate genetic variants as instrumental variables. Genome-wide association studies often reveal that hundreds of genetic variants may be robustly associated with a risk factor, but in some situations investigators may have greater confidence in the instrument validity of only a smaller subset of variants. Nevertheless, the use of additional instruments may be optimal from the perspective of mean squared error even if they are slightly invalid; a small bias in estimation may be a price worth paying for a larger reduction in variance. For this purpose, we consider a method for "focused" instrument selection whereby genetic variants are selected to minimise the estimated asymptotic mean squared error of causal effect estimates. In a setting of many weak and locally invalid instruments, we propose a novel strategy to construct confidence intervals for post-selection focused estimators that guards against the worst case loss in asymptotic coverage. In empirical applications to: (i) validate lipid drug targets; and (ii) investigate vitamin D effects on a wide range of outcomes, our findings suggest that the optimal selection of instruments does not involve only a small number of biologically-justified instruments, but also many potentially invalid instruments.

LDL-c Lowering, Ischemic Stroke, and Small Vessel Disease Brain Imaging Biomarkers: A Mendelian Randomization Study.

BACKGROUND: The effects of lipid-lowering drug targets on different ischemic stroke subtypes are not fully understood. We aimed to explore the mechanisms by which lipid-lowering drug targets differentially affect the risk of ischemic stroke subtypes and their underlying pathophysiology. METHODS: Using a 2-sample Mendelian randomization approach, we assessed the effects of genetically proxied low-density lipoprotein cholesterol (LDL-c) and 3 clinically approved LDL-lowering drugs (HMGCR [3-hydroxy-3-methylglutaryl-CoA reductase], PCSK9 [proprotein convertase subtilisin/kexin type 9], and NPC1L1 [Niemann-Pick C1-Like 1]) on stroke subtypes and brain imaging biomarkers associated with small vessel stroke (SVS), including white matter hyperintensity volume and perivascular spaces. RESULTS: In genome-wide Mendelian randomization analyses, lower genetically predicted LDL-c was significantly associated with a reduced risk of any stroke, ischemic stroke, and large artery stroke, supporting previous findings. Significant associations between genetically predicted LDL-c and cardioembolic stroke, SVS, and biomarkers, perivascular space and white matter hyperintensity volume, were not identified in this study. In drug-target Mendelian randomization analysis, genetically proxied reduced LDL-c through NPC1L1 inhibition was associated with lower odds of perivascular space (odds ratio per 1-mg/dL decrease, 0.79 [95% CI, 0.67-0.93]) and with lower odds of SVS (odds ratio, 0.29 [95% CI, 0.10-0.85]). CONCLUSIONS: This study provides supporting evidence of a potentially protective effect of LDL-c lowering through NPC1L1 inhibition on perivascular space and SVS risk, highlighting novel therapeutic targets for SVS.

Sedentary lifestyle, physical activity, and gastrointestinal diseases: evidence from mendelian randomization analysis.

BACKGROUND: The causal associations of physical activity and sedentary behavior with the risk of gastrointestinal disease are unclear. We performed a Mendelian randomization analysis to examine these associations. METHODS: Genetic instruments associated with leisure screen time (LST, an indicator of a sedentary lifestyle) and moderate-to-vigorous intensity physical activity (MVPA) at the genome-wide significance (P < 5 × 10-8) level were selected from a genome-wide association study. Summary statistics for gastrointestinal diseases were obtained from the UK Biobank study, the FinnGen study, and large consortia. Multivariable MR analyses were conducted for genetically determined LST with adjustment for MVPA and vice versa. We also performed multivariable MR with adjustment for genetically proxied smoking, body mass index (BMI), waist-to-hip ratio, type 2 diabetes, and fasting insulin for both exposures. FINDINGS: Genetically proxied longer LST was associated with an increased risk of gastrointestinal reflux, gastric ulcer, duodenal ulcer, chronic gastritis, irritable bowel syndrome, diverticular disease, Crohn's disease, ulcerative colitis, non-alcoholic fatty liver disease, alcoholic liver disease, cholangitis, cholecystitis, cholelithiasis, acute pancreatitis, chronic pancreatitis, and acute appendicitis. Most associations remained after adjustment for genetic liability to MVPA. Genetic liability to MVPA was associated with decreased risk of gastroesophageal reflux, gastric ulcer, chronic gastritis, irritable bowel syndrome, cholecystitis, cholelithiasis, acute and chronic pancreatitis. The associations attenuated albeit directionally remained after adjusting for genetically predicted LST. Multivariable MR analysis found that BMI and type 2 diabetes mediated the associations of LST and MVPA with several gastrointestinal diseases. INTERPRETATION: The study suggests that a sedentary lifestyle may play a causal role in the development of many gastrointestinal diseases. FUNDING: Natural Science Fund for Distinguished Young Scholars of Zhejiang Province (LR22H260001), Natural Science Foundation of Hunan Province (2021JJ30999), Swedish Heart-Lung Foundation (Hjärt-Lungfonden, 20210351), Swedish Research Council (Vetenskapsrådet, 2019-00977), Swedish Cancer Society (Cancerfonden), the Wellcome Trust (225790/7/22/Z), United Kingdom Research and Innovation Medical Research Council (MC_UU_00002/7) and National Institute for Health Research Cambridge Biomedical Research Centre (NHIR203312).

Association between alcohol consumption and peripheral artery disease: Two de novo prospective cohorts and a systematic review with meta-analysis.

AIMS: The association between alcohol consumption and risk of peripheral artery disease (PAD) is inconclusive. We conducted this study to examine the association between alcohol consumption and PAD risk in two de novo cohort studies and a meta-analysis of observational studies. METHODS AND RESULTS: A systematic review was conducted to identify studies on alcohol consumption in relation to PAD risk. We further used data from two cohorts of 70,116 Swedish and 405,406 British adults and performed a meta-analysis of results from previously published studies and current cohort studies. There was a U-shaped association between alcohol consumption and incident PAD risk in the Swedish and British cohorts. The meta-analysis of results of these two cohorts and previously published studies found that compared with non- or never-drinkers, the relative risk of PAD was 0.83 (95% confidence interval [CI] 0.77-0.89), 0.81 (95% CI 0.74-0.90), and 0.94 (95% CI 0.83-1.07) for light, moderate, and high-to-heavy alcohol drinkers, respectively. The nonlinear meta-analysis revealed a possibly U-shaped association between alcohol consumption and PAD risk (P-nonlinearity <0.001). The risk of PAD was observed to be the lowest for 2 drinks/week and to be pronounced for ≥10 drinks/week. All these associations persisted in a sensitivity meta-analysis including cohort and other type of observational studies. CONCLUSION: Alcohol intake ≤ 2 drinks/week was associated with a reduced risk of PAD and the risk of PAD became pronounced with intake ≥10 drinkers/week.

The association between alcohol consumption and the risk of peripheral artery disease is conflicting between studies and thus remains undetermined. In the two de novo cohort analyses, we found a U-shaped association between alcohol consumption and peripheral artery disease risk in the Swedish and British populations. In the meta-analysis, light-to-moderate consumption of alcohol was associated with a reduced risk of peripheral artery disease. The dose-response meta-analysis showed that the risk of peripheral artery disease became pronounced for alcohol consumption ≥10 drinkers/week. This is an observational study that cannot infer causality between alcohol consumption and peripheral artery disease risk. We are not able to assess the specific associations to different types of alcoholic beverages.

Genetic evidence for distinct biological mechanisms that link adiposity to type 2 diabetes: towards precision medicine.

We aimed to unravel the mechanisms connecting adiposity to type 2 diabetes. We employed MR-Clust to cluster independent genetic variants associated with body fat percentage (388 variants) and BMI (540 variants) based on their impact on type 2 diabetes. We identified five clusters of adiposity-increasing alleles associated with higher type 2 diabetes risk (unfavorable adiposity) and three clusters associated with lower risk (favorable adiposity). We then characterized each cluster based on various biomarkers, metabolites and Magnetic Resonance Imaging-based measures of fat distribution and muscle quality. Analyzing the metabolic signatures of these clusters revealed two primary mechanisms connecting higher adiposity to reduced type 2 diabetes risk. The first involves higher adiposity in subcutaneous tissues (abdomen and thigh), lower liver fat, improved insulin sensitivity, and decreased risk of cardiometabolic diseases and diabetes complications. The second mechanism is characterized by increased body size, enhanced muscle quality, with no impact on cardiometabolic outcomes. Furthermore, our findings unveil diverse mechanisms linking higher adiposity to higher disease risk, such as cholesterol pathways or inflammation. These results reinforce the existence of adiposity-related mechanisms that may act as protective factors against type 2 diabetes and its complications, especially when accompanied by reduced ectopic liver fat.

Alcohol consumption and the risk of all-cause and cause-specific mortality-a linear and nonlinear Mendelian randomization study.

BACKGROUND: Many observational studies support light-to-moderate alcohol intake as potentially protective against premature death. We used a genetic approach to evaluate the linear and nonlinear relationships between alcohol consumption and mortality from different underlying causes. METHODS: We used data from 278 093 white-British UK Biobank participants, aged 37-73 years at recruitment and with data on alcohol intake, genetic variants, and mortality. Habitual alcohol consumption was instrumented by 94 variants. Linear Mendelian randomization (MR) analyses were conducted using five complementary approaches, and nonlinear MR analyses by the doubly-ranked method. RESULTS: There were 20 834 deaths during the follow-up (median 12.6 years). In conventional analysis, the association between alcohol consumption and mortality outcomes was 'J-shaped'. In contrast, MR analyses supported a positive linear association with premature mortality, with no evidence for curvature (Pnonlinearity ≥ 0.21 for all outcomes). The odds ratio [OR] for each standard unit increase in alcohol intake was 1.27 (95% confidence interval [CI] 1.16-1.39) for all-cause mortality, 1.30 (95% CI 1.10-1.53) for cardiovascular disease, 1.20 (95% CI 1.08-1.33) for cancer, and 2.06 (95% CI 1.36-3.12) for digestive disease mortality. These results were consistent across pleiotropy-robust methods. There was no clear evidence for an association between alcohol consumption and mortality from respiratory diseases or COVID-19 (1.32, 95% CI 0.96-1.83 and 1.46, 95% CI 0.99-2.16, respectively; Pnonlinearity ≥ 0.21). CONCLUSION: Higher levels of genetically predicted alcohol consumption had a strong linear association with an increased risk of premature mortality with no evidence for any protective benefit at modest intake levels.

Incorporating biological and clinical insights into variant choice for Mendelian randomisation: examples and principles.

Mendelian randomisation is an accessible and valuable epidemiological approach to provide insight into the causal nature of relationships between risk factor exposures and disease outcomes. However, if performed without critical thought, we may simply have replaced one set of implausible assumptions (no unmeasured confounding or reverse causation) with another set of implausible assumptions (no pleiotropy or other instrument invalidity). The most critical decision to avoid pleiotropy is which genetic variants to use as instrumental variables. Two broad strategies for instrument selection are a biologically motivated strategy and a genome-wide strategy; in general, a biologically motivated strategy is preferred. In this review, we discuss various ways of implementing a biologically motivated selection strategy: using variants in a coding gene region for the exposure or a gene region that encodes a regulator of exposure levels, using a positive control variable and using a biomarker as the exposure rather than its behavioural proxy. In some cases, a genome-wide analysis can provide important complementary evidence, even when its reliability is questionable. In other cases, a biologically-motivated analysis may not be possible. The choice of genetic variants must be informed by biological and functional considerations where possible, requiring collaboration to combine biological and clinical insights with appropriate statistical methodology.

Genetic investigation into the broad health implications of caffeine: evidence from phenome-wide, proteome-wide and metabolome-wide Mendelian randomization.

BACKGROUND: Caffeine is one of the most utilized drugs in the world, yet its clinical effects are not fully understood. Circulating caffeine levels are influenced by the interplay between consumption behaviour and metabolism. This study aimed to investigate the effects of circulating caffeine levels by considering genetically predicted variation in caffeine metabolism. METHODS: Leveraging genetic variants related to caffeine metabolism that affect its circulating levels, we investigated the clinical effects of plasma caffeine in a phenome-wide association study (PheWAS). We validated novel findings using a two-sample Mendelian randomization framework and explored the potential mechanisms underlying these effects in proteome-wide and metabolome-wide Mendelian randomization. RESULTS: Higher levels of genetically predicted circulating caffeine among caffeine consumers were associated with a lower risk of obesity (odds ratio (OR) per standard deviation increase in caffeine = 0.97, 95% confidence interval (CI) CI: 0.95-0.98, p = 2.47 × 10-4), osteoarthrosis (OR = 0.97, 95% CI: 0.96-0.98, P=1.10 × 10-8) and osteoarthritis (OR: 0.97, 95% CI: 0.96 to 0.98, P = 1.09 × 10-6). Approximately one third of the protective effect of plasma caffeine on osteoarthritis risk was estimated to be mediated through lower bodyweight. Proteomic and metabolomic perturbations indicated lower chronic inflammation, improved lipid profiles, and altered protein and glycogen metabolism as potential biological mechanisms underlying these effects. CONCLUSIONS: We report novel evidence suggesting that long-term increases in circulating caffeine may reduce bodyweight and the risk of osteoarthrosis and osteoarthritis. We confirm prior genetic evidence of a protective effect of plasma caffeine on risk of overweight and obesity. Further clinical study is warranted to understand the translational relevance of these findings before clinical practice or lifestyle interventions related to caffeine consumption are introduced.

A data-adaptive method for investigating effect heterogeneity with high-dimensional covariates in Mendelian randomization.

BACKGROUND: Mendelian randomization is a popular method for causal inference with observational data that uses genetic variants as instrumental variables. Similarly to a randomized trial, a standard Mendelian randomization analysis estimates the population-averaged effect of an exposure on an outcome. Dividing the population into subgroups can reveal effect heterogeneity to inform who would most benefit from intervention on the exposure. However, as covariates are measured post-"randomization", naive stratification typically induces collider bias in stratum-specific estimates. METHOD: We extend a previously proposed stratification method (the "doubly-ranked method") to form strata based on a single covariate, and introduce a data-adaptive random forest method to calculate stratum-specific estimates that are robust to collider bias based on a high-dimensional covariate set. We also propose measures based on the Q statistic to assess heterogeneity between stratum-specific estimates (to understand whether estimates are more variable than expected due to chance alone) and variable importance (to identify the key drivers of effect heterogeneity). RESULT: We show that the effect of body mass index (BMI) on lung function is heterogeneous, depending most strongly on hip circumference and weight. While for most individuals, the predicted effect of increasing BMI on lung function is negative, it is positive for some individuals and strongly negative for others. CONCLUSION: Our data-adaptive approach allows for the exploration of effect heterogeneity in the relationship between an exposure and an outcome within a Mendelian randomization framework. This can yield valuable insights into disease aetiology and help identify specific groups of individuals who would derive the greatest benefit from targeted interventions on the exposure.

Proteomic Associations of NT-proBNP (N-Terminal Pro-B-Type Natriuretic Peptide) in Heart Failure With Preserved Ejection Fraction.

BACKGROUND: NT-proBNP (N-terminal pro-B-type natriuretic peptide) levels are variably elevated in heart failure with preserved ejection fraction (HFpEF), even in the presence of increased left ventricular filling pressures. NT-proBNP levels are prognostic in HFpEF and have been used as an inclusion criterion for several recent randomized clinical trials. However, the underlying biologic differences between HFpEF participants with high and low NT-proBNP levels remain to be fully understood. METHODS: We measured 4928 proteins using an aptamer-based proteomic assay (SOMAScan) in available plasma samples from 2 cohorts: (1) Participants with HFpEF enrolled in the PHFS (Penn Heart Failure Study; n=253); (2) TOPCAT (Treatment of Preserved Cardiac Function Heart Failure With an Aldosterone Antagonist Trial) participants in the Americas (n=218). We assessed the relationship between SOMAScan-derived plasma NT-proBNP and levels of other proteins available in the SOMAScan assay version 4 using robust linear regression, with correction for multiple comparisons, followed by pathway analysis. RESULTS: NT-proBNP levels exhibited prominent proteome-wide associations in PHFS and TOPCAT cohorts. Proteins most strongly associated with NT-proBNP in both cohorts included SVEP1 (sushi, von Willebrand factor type-A, epidermal growth factor, and pentraxin domain containing 1; ßTOPCAT=0.539; P<0.0001; ßPHFS=0.516; P<0.0001) and ANGPT2 (angiopoietin 2; ßTOPCAT=0.571; P<0.0001; ßPHFS=0.459; P<0.0001). Canonical pathway analysis demonstrated consistent associations with multiple pathways related to fibrosis and inflammation. These included hepatic fibrosis and inhibition of matrix metalloproteases. Analyses using cut points corresponding to estimated quantitative concentrations of 360 pg/mL (and 480 pg/mL in atrial fibrillation) revealed similar proteomic associations. CONCLUSIONS: Circulating NT-proBNP levels exhibit prominent proteomic associations in HFpEF. Our findings suggest that higher NT-proBNP levels in HFpEF are a marker of fibrosis and inflammation. These findings will aid the interpretation of NT-proBNP levels in HFpEF and may guide the selection of participants in future HFpEF clinical trials.

The role of thyroid function in borderline personality disorder and schizophrenia: a Mendelian Randomisation study.

BACKGROUND: Genome-wide association studies have reported a genetic overlap between borderline personality disorder (BPD) and schizophrenia (SCZ). Epidemiologically, the direction and causality of the association between thyroid function and risk of BPD and SCZ are unclear. We aim to test whether genetically predicted variations in TSH and FT4 levels or hypothyroidism are associated with the risk of BPD and SCZ. METHODS: We employed Mendelian Randomisation (MR) analyses using genetic instruments associated with TSH and FT4 levels as well as hypothyroidism to examine the effects of genetically predicted thyroid function on BPD and SCZ risk. Bidirectional MR analyses were employed to investigate a potential reverse causal association. RESULTS: Genetically predicted higher FT4 was not associated with the risk of BPD (OR: 1.18; P = 0.60, IVW) or the risk of SCZ (OR: 0.93; P = 0.19, IVW). Genetically predicted higher TSH was not associated with the risk of BPD (OR: 1.11; P = 0.51, IVW) or SCZ (OR: 0.98, P = 0.55, IVW). Genetically predicted hypothyroidism was not associated with BPD or SCZ. We found no evidence for a reverse causal effect between BPD or SCZ on thyroid function. CONCLUSIONS: We report evidence for a null association between genetically predicted FT4, TSH or hypothyroidism with BPD or SCZ risk. There was no evidence for reverse causality.

Proteomic Associations of Adverse Outcomes in Human Heart Failure.

BACKGROUND: Identifying novel molecular drivers of disease progression in heart failure (HF) is a high-priority goal that may provide new therapeutic targets to improve patient outcomes. The authors investigated the relationship between plasma proteins and adverse outcomes in HF and their putative causal role using Mendelian randomization. METHODS AND RESULTS: The authors measured 4776 plasma proteins among 1964 participants with HF with a reduced left ventricular ejection fraction enrolled in PHFS (Penn Heart Failure Study). Assessed were the observational relationship between plasma proteins and (1) all-cause death or (2) death or HF-related hospital admission (DHFA). The authors replicated nominally significant associations in the Washington University HF registry (N=1080). Proteins significantly associated with outcomes were the subject of 2-sample Mendelian randomization and colocalization analyses. After correction for multiple testing, 243 and 126 proteins were found to be significantly associated with death and DHFA, respectively. These included small ubiquitin-like modifier 2 (standardized hazard ratio [sHR], 1.56; P<0.0001), growth differentiation factor-15 (sHR, 1.68; P<0.0001) for death, A disintegrin and metalloproteinase with thrombospondin motifs-like protein (sHR, 1.40; P<0.0001), and pulmonary-associated surfactant protein C (sHR, 1.24; P<0.0001) for DHFA. In pathway analyses, top canonical pathways associated with death and DHFA included fibrotic, inflammatory, and coagulation pathways. Genomic analyses provided evidence of nominally significant associations between levels of 6 genetically predicted proteins with DHFA and 11 genetically predicted proteins with death. CONCLUSIONS: This study implicates multiple novel proteins in HF and provides preliminary evidence of associations between genetically predicted plasma levels of 17 candidate proteins and the risk for adverse outcomes in human HF.

Robust use of phenotypic heterogeneity at drug target genes for mechanistic insights: Application of cis-multivariable Mendelian randomization to GLP1R gene region.

Phenotypic heterogeneity at genomic loci encoding drug targets can be exploited by multivariable Mendelian randomization to provide insight into the pathways by which pharmacological interventions may affect disease risk. However, statistical inference in such investigations may be poor if overdispersion heterogeneity in measured genetic associations is unaccounted for. In this work, we first develop conditional F statistics for dimension-reduced genetic associations that enable more accurate measurement of phenotypic heterogeneity. We then develop a novel extension for two-sample multivariable Mendelian randomization that accounts for overdispersion heterogeneity in dimension-reduced genetic associations. Our empirical focus is to use genetic variants in the GLP1R gene region to understand the mechanism by which GLP1R agonism affects coronary artery disease (CAD) risk. Colocalization analyses indicate that distinct variants in the GLP1R gene region are associated with body mass index and type 2 diabetes (T2D). Multivariable Mendelian randomization analyses that were corrected for overdispersion heterogeneity suggest that bodyweight lowering rather than T2D liability lowering effects of GLP1R agonism are more likely contributing to reduced CAD risk. Tissue-specific analyses prioritized brain tissue as the most likely to be relevant for CAD risk, of the tissues considered. We hope the multivariable Mendelian randomization approach illustrated here is widely applicable to better understand mechanisms linking drug targets to diseases outcomes, and hence to guide drug development efforts.

Genetic Associations of Circulating Cardiovascular Proteins With Gestational Hypertension and Preeclampsia.

Importance: Hypertensive disorders of pregnancy (HDPs), including gestational hypertension and preeclampsia, are important contributors to maternal morbidity and mortality worldwide. In addition, women with HDPs face an elevated long-term risk of cardiovascular disease. Objective: To identify proteins in the circulation associated with HDPs. Design, Setting, and Participants: Two-sample mendelian randomization (MR) tested the associations of genetic instruments for cardiovascular disease-related proteins with gestational hypertension and preeclampsia. In downstream analyses, a systematic review of observational data was conducted to evaluate the identified proteins' dynamics across gestation in hypertensive vs normotensive pregnancies, and phenome-wide MR analyses were performed to identify potential non-HDP-related effects associated with the prioritized proteins. Genetic association data for cardiovascular disease-related proteins were obtained from the Systematic and Combined Analysis of Olink Proteins (SCALLOP) consortium. Genetic association data for the HDPs were obtained from recent European-ancestry genome-wide association study meta-analyses for gestational hypertension and preeclampsia. Study data were analyzed October 2022 to October 2023. Exposures: Genetic instruments for 90 candidate proteins implicated in cardiovascular diseases, constructed using cis-protein quantitative trait loci (cis-pQTLs). Main Outcomes and Measures: Gestational hypertension and preeclampsia. Results: Genetic association data for cardiovascular disease-related proteins were obtained from 21 758 participants from the SCALLOP consortium. Genetic association data for the HDPs were obtained from 393 238 female individuals (8636 cases and 384 602 controls) for gestational hypertension and 606 903 female individuals (16 032 cases and 590 871 controls) for preeclampsia. Seventy-five of 90 proteins (83.3%) had at least 1 valid cis-pQTL. Of those, 10 proteins (13.3%) were significantly associated with HDPs. Four were robust to sensitivity analyses for gestational hypertension (cluster of differentiation 40, eosinophil cationic protein [ECP], galectin 3, N-terminal pro-brain natriuretic peptide [NT-proBNP]), and 2 were robust for preeclampsia (cystatin B, heat shock protein 27 [HSP27]). Consistent with the MR findings, observational data revealed that lower NT-proBNP (0.76- to 0.88-fold difference vs no HDPs) and higher HSP27 (2.40-fold difference vs no HDPs) levels during the first trimester of pregnancy were associated with increased risk of HDPs, as were higher levels of ECP (1.60-fold difference vs no HDPs). Phenome-wide MR analyses identified 37 unique non-HDP-related protein-disease associations, suggesting potential on-target effects associated with interventions lowering HDP risk through the identified proteins. Conclusions and Relevance: Study findings suggest genetic associations of 4 cardiovascular disease-related proteins with gestational hypertension and 2 associated with preeclampsia. Future studies are required to test the efficacy of targeting the corresponding pathways to reduce HDP risk.

Mendelian Randomization Applied to Neurology: Promises and Challenges

The Mendelian randomization (MR) paradigm allows for causal inferences to be drawn using genetic data. In recent years, the expansion of well-powered publicly available genetic association data related to phenotypes such as brain tissue gene expression, brain imaging, and neurologic diseases offers exciting opportunities for the application of MR in the field of neurology. In this review, we discuss the basic principles of MR, its myriad applications to research in neurology, and potential pitfalls of injudicious applications. Throughout, we provide examples where MR-informed findings have shed light on long-standing epidemiologic controversies, provided insights into the pathophysiology of neurologic conditions, prioritized drug targets, and informed drug repurposing opportunities. With the ever-expanding availability of genome-wide association data, we project MR to become a key driver of progress in the field of neurology. It is therefore paramount that academics and clinicians within the field are familiar with the approach.

Mediating Factors in the Association of Maternal Educational Level With Pregnancy Outcomes: A Mendelian Randomization Study.

Importance: Lower educational attainment is associated with increased risk of adverse pregnancy outcomes, but it is unclear which pathways mediate this association. Objective: To investigate the association between educational attainment and pregnancy outcomes and the proportion of this association that is mediated through modifiable cardiometabolic risk factors. Design, Setting, and Participants: In this 2-sample mendelian randomization (MR) cohort study, uncorrelated (R2 < 0.01) single-nucleotide variants (formerly single-nucleotide polymorphisms) associated with the exposure (P < 5 × 10-8) and mediators and genetic associations with the pregnancy outcomes from genome-wide association studies were extracted. All participants were of European ancestry and were largely from Finland, Iceland, the United Kingdom, or the US. The inverse variance-weighted method was used in the main analysis, and the weighted median, weighted mode, and MR Egger regression were used in sensitivity analyses. In mediation analyses, the direct effect of educational attainment estimated in multivariable MR was compared with the total effect estimated in the main univariable MR analysis. Data were extracted between December 1, 2022, and April 30, 2023. Exposure: Genetically estimated educational attainment. The mediators considered were genetically estimated type 2 diabetes, body mass index, smoking, high-density lipoprotein cholesterol level, and systolic blood pressure. Main Outcomes and Measures: Ectopic pregnancy, hyperemesis gravidarum, gestational diabetes, preeclampsia, preterm birth, and offspring birth weight. Results: The analyses included 3 037 499 individuals with data on educational attainment, and those included in studies on pregnancy outcomes ranged from 141 014 for ectopic pregnancy to 270 002 with data on offspring birth weight. Each SD increase in genetically estimated educational attainment (ie, 3.4 years) was associated with an increased birth weight of 42 (95% CI, 28-56) g and an odds ratio ranging from 0.53 (95% CI, 0.46-0.60) for ectopic pregnancy to 0.81 (95% CI, 0.71-0.93) for preeclampsia. The combined proportion of the association that was mediated by the 5 cardiometabolic risk factors ranged from -17% (95% CI, -46% to 26%) for hyperemesis gravidarum to 78% (95% CI, 10%-208%) for preeclampsia. Sensitivity analyses accounting for pleiotropy were consistent with the main analyses. Conclusions and Relevance: In this MR cohort study, intervening for type 2 diabetes, body mass index, smoking, high-density lipoprotein cholesterol level, and systolic blood pressure may lead to reductions in several adverse pregnancy outcomes associated with lower levels of education. Such public health interventions would serve to reduce health disparities attributable to social inequalities.