Lipid levels and risk of acute pancreatitis using bidirectional Mendelian randomization.

Previous studies found lipid levels, especially triglycerides (TG), are associated with acute pancreatitis, but their causalities and bi-directions were not fully examined. We determined whether abnormal levels of TG, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) are precursors and/or consequences of acute pancreatitis using bidirectional two-sample Mendelian randomization (MR) with two non-overlapping genome-wide association study (GWAS) summary statistics for lipid levels and acute pancreatitis. We found phenotypic associations that both higher TG levels and lower HDL-C levels contributed to increased risk of acute pancreatitis. Our GWAS meta-analysis of acute pancreatitis identified seven independent signals. Genetically predicted TG was positively associated with acute pancreatitis when using the variants specifically associated with TG using univariable MR [Odds ratio (OR), 95% CI 2.02, 1.22-3.31], but the reversed direction from acute pancreatitis to TG was not observed (mean difference = 0.003, SE = 0.002, P-value = 0.138). However, a bidirectional relationship of HDL-C and acute pancreatitis was observed: A 1-SD increment of genetically predicted HDL-C was associated with lower risk of acute pancreatitis (OR, 95% CI 0.84, 0.76-0.92) and genetically predisposed individuals with acute pancreatitis have, on average, 0.005 SD lower HDL-C (mean difference = - 0.005, SE = 0.002, P-value = 0.004). Our MR analysis confirms the evidence of TG as a risk factor of acute pancreatitis but not a consequence. A potential bidirectional relationship of HDL-C and acute pancreatitis occurs and raises the prospect of HDL-C modulation in the acute pancreatitis prevention and treatment.

Characterizing the Causal Pathway From Childhood Adiposity to Right Heart Physiology and Pulmonary Circulation Using Lifecourse Mendelian Randomization.

BACKGROUND: Observational epidemiological studies have reported an association between childhood adiposity and altered cardiac morphology and function in later life. However, whether this is due to a direct consequence of being overweight during childhood has been difficult to establish, particularly as accounting for other measures of body composition throughout the lifecourse can be exceptionally challenging. METHODS AND RESULTS: In this study, we used human genetics to investigate this using a causal inference technique known as lifecourse Mendelian randomization. This approach allowed us to evaluate the effect of childhood body size on 11 measures of right heart and pulmonary circulation independent of other anthropometric traits at various stages in the lifecourse. We found strong evidence that childhood body size has a direct effect on an enlarged right heart structure in later life (eg, right ventricular end-diastolic volume: ß=0.24 [95% CI, 0.15-0.33]; P=3×10-7) independent of adulthood body size. In contrast, childhood body size effects on maximum ascending aorta diameter attenuated upon accounting for body size in adulthood, suggesting that this effect is likely attributed to individuals remaining overweight into later life. Effects of childhood body size on pulmonary artery traits and measures of right atrial function became weaker upon accounting for adulthood fat-free mass and childhood height, respectively. CONCLUSIONS: Our findings suggest that, although childhood body size has a long-term influence on an enlarged heart structure in adulthood, associations with the other structural components of the cardiovascular system and their function may be largely attributed to body composition at other stages in the lifecourse.

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.

Educational attainment, income, and attention deficit hyperactivity disorder: A mediation analysis based on two-step Mendelian randomization.

Previous studies have reported the relationship between educational attainment and attention deficit hyperactivity disorder (ADHD). However, the mechanism of this relationship remains unknown. It is well known that educational attainment correlates with income. Therefore, based on summary data from a genome-wide association study we used two-step Mendelian randomization (MR) to explore the role of income between education and ADHD. The inverse variance weighted (IVW) method was used in our analysis. The IVW results suggested that educational attainment and income were protective factors against ADHD. Educational attainment affects ADHD through income [ADHD: Beta = -0.68, 95% confidence interval (CI) = -0.87, -0.49; female: Beta = -0.87, 95% CI = -1.28, -0.47; male: Beta = -1.01, 95% CI = -1.34, -0.68; childhood: Beta = -0.52, 95% CI = -0.74, -0.30; late-diagnosed: Beta = -0.78, 95% CI = -1.11, -0.47; persistent: Beta = -0.82, 95% CI = -1.33, -0.31]. Income also affected ADHD through educational attainment [female: Beta = -1.08, 95% CI = -1.35, -0.83; male: Beta = -1.16, 95% CI = -1.57, -0.77; persistent: Beta = -1.48, 95% CI = -2.09, -0.94]. In the final analysis, data with heterogeneity were analyzed using IVW random effects results. The mechanism is that income will mediate the relationship between educational attainment and ADHD.

PheWAS-based clustering of Mendelian Randomisation instruments reveals distinct mechanism-specific causal effects between obesity and educational attainment.

Mendelian Randomisation (MR) estimates causal effects between risk factors and complex outcomes using genetic instruments. Pleiotropy, heritable confounders, and heterogeneous causal effects violate MR assumptions and can lead to biases. To alleviate these, we propose an approach employing a Phenome-Wide association Clustering of the MR instruments (PWC-MR) and apply this method to revisit the surprisingly large apparent causal effect of body mass index (BMI) on educational attainment (EDU): [Formula: see text] = -0.19 [-0.22, -0.16]. First, we cluster 324 BMI-associated genetic instruments based on their association with 407 traits in the UK Biobank, which yields six distinct groups. Subsequent cluster-specific MR reveals heterogeneous causal effect estimates on EDU. A cluster enriched for socio-economic indicators yields the largest BMI-on-EDU causal effect estimate ([Formula: see text] = -0.49 [-0.56, -0.42]) whereas a cluster enriched for body-mass specific traits provides a more likely estimate ([Formula: see text] = -0.09 [-0.13, -0.05]). Follow-up analyses confirms these findings: within-sibling MR ([Formula: see text] = -0.05 [-0.09, -0.01]); MR for childhood BMI on EDU ([Formula: see text] = -0.03 [-0.06, -0.002]); step-wise multivariable MR ([Formula: see text] = -0.05 [-0.07, -0.02]) where socio-economic indicators are jointly modelled. Here we show how the in-depth examination of the BMI-EDU causal relationship demonstrates the utility of our PWC-MR approach in revealing distinct pleiotropic pathways and confounder mechanisms.

Causal relationship between lactate dehydrogenase and risk of developing ischemic stroke: A Mendelian randomized study.

BACKGROUND AND OBJECTIVE: Ischemic stroke (IS) is one of the major global health problems. It is not clear whether there is a causal relationship between lactate dehydrogenase (LDH) and the risk of IS attacks. The purpose of this study was to investigate whether LDH has a causal relationship with the development of IS. METHODS: The genome-wide association data of LDH and IS were obtained through a Mendelian randomization-based platform. Single nucleotide polymorphisms (SNP) that were significantly associated with LDH were identified and used as instrumental variables, and a two-sample Mendelian randomization study was used to examine the causal relationship between LDH and IS. The statistical methods included Inverse-variance weighted approach, MR-Egger regression, and weighted median estimator. RESULTS: We selected 15 SNPs of genome-wide significance from Genome-wide association study database with LDH as instrumental variables. A consistent causal association between LDH and IS was observed by different assessment methods. The results of the inverse-variance weighted method suggested an inverse association between LDH and higher genetic predictability of IS risk (OR, 0.997; 95%CI 0.995-0.999). The weighted median estimate showed consistent results with the MR-Egger method (weighted median estimate: OR, 0.995; 95%CI 0.992-0.999; MR-Egger method: OR, 0.996; 95%CI 0.992-0.999). The inverse-variance weighted method indicates a causal association between LDH and IS (ß = -0.002563, SE = 0.00128, p = .0453). MR-Egger analysis (ß = -0.004498, SE = 0.001877, p = .03) and the weighted median method suggested that LDH and IS also existed causal relationship (ß = -0.004861, SE = 0.001801, p = .00695). CONCLUSIONS: Our Mendelian randomization results suggest that LDH is inversely associated with the risk of developing IS, and are contrary to the results of previous observational studies.

Causal role of immune cell traits in stroke: A Mendelian randomization study.

OBJECTIVES: Immune mechanisms play a crucial role in the development of stroke. However, immune-related phenotypes are diverse and their associations with stroke are largely unknown. Here, we aimed to systematically explore the causal role of immune cell traits in stroke and its subtypes by leveraging data from genome-wide association studies (GWASs). MATERIALS AND METHODS: Exposure data were obtained from a recent GWAS on 731 immune cell traits profiled by flow cytometry involving 3757 individuals. By conducting two-sample univariable Mendelian randomization (MR) analyses, each immune cell trait was assessed for causal relationships with stroke outcomes from the MEGASTROKE Consortium (40,585 cases and 406,111 controls). The robustness of the MR results was verified by a series of sensitivity analyses. RESULTS: We identified three significant associations after Bonferroni correction (P < 1.37E-05). Increased CD27 expression on memory B cell (OR = 1.23, 95% CI = 1.14-1.33, P = 2.78E-08), IgD-CD38dim B cell (OR = 1.16, 95% CI = 1.09-1.23, P = 5.98E-06) and unswitched memory B cell (OR = 1.18, 95% CI = 1.10-1.27, P = 1.09E-05) were associated with a higher risk of large-artery atherosclerotic stroke (LAS). Furthermore, expression quantitative trait loci data also indicated elevated blood CD27 mRNA level was a risk factor for LAS (OR = 1.37, 95% CI = 1.02-1.84, P = 0.037). CONCLUSIONS: This study provided genetic evidence of the causal relationship between immune cell traits and stroke, highlighting the role of CD27 on memory B cell as a novel factor for LAS risk.

The Effect of Rheumatoid Arthritis on Features Associated with Sarcopenia: A Mendelian Randomization Study.

Previous epidemiological evidence suggests rheumatoid arthritis is associated with sarcopenia-related features. However, most of the current evidence is from cross-sectional studies, and the causal link of this association is still to be determined. Therefore, this study was committed to a two-sample Mendelian randomization analysis to assess the causal effect of rheumatoid arthritis on sarcopenia-related features. In this two-sample Mendelian randomization study, instrumental variables for rheumatoid arthritis were obtained from the Non-Cancer Disease Study, and data for the five relevant characteristics of sarcopenia were pooled from UKBiobank. Inverse variance weighting is the primary analysis method for assessing causal effects. MR-Egger regression and weighted median are complementary analysis methods for causal effects. Leave-one-out analysis, horizontal pleiotropy test, and Heterogeneity test are applied as a sensitivity analysis to assess the robustness of causal effect estimates. The inverse variance weighted results for the five characteristics associated with sarcopenia and rheumatoid arthritis were: hand grip strength (right) (beta = - 2.309, se = 0.206, p = 3.340E-29), hand grip strength (left) (beta = - 2.046, se = 0.205, p = 2.166E-23), whole body lean mass (beta = - 0.843, se = 0.135, p = 4.67E-10), appendicular lean mass (beta = - 2.444, se = 0.208, p = 6.069E-32), Usual walking pace (OR 0.340, 95% CI (0.238, 0.484), p = 2.471E-09). The sensitivity analyses did not support that horizontal pleiotropy distorted causal effect estimates. The beta coefficient quantifies the number of standard deviations of the continuous outcome variables (hand grip strength, whole body lean mass, and appendicular lean mass) that change on average with each increase in the standard deviation of the binary exposure variable (rheumatoid arthritis). The odds ratios indicate the increased risk of the binary outcome variable (usual walking pace) per rheumatoid arthritis standard deviation increase. This study has demonstrated a negative causal effect of rheumatoid arthritis with five major sarcopenia-related features in a European population.

Genetic influences on circulating retinol and its relationship to human health.

Retinol is a fat-soluble vitamin that plays an essential role in many biological processes throughout the human lifespan. Here, we perform the largest genome-wide association study (GWAS) of retinol to date in up to 22,274 participants. We identify eight common variant loci associated with retinol, as well as a rare-variant signal. An integrative gene prioritisation pipeline supports novel retinol-associated genes outside of the main retinol transport complex (RBP4:TTR) related to lipid biology, energy homoeostasis, and endocrine signalling. Genetic proxies of circulating retinol were then used to estimate causal relationships with almost 20,000 clinical phenotypes via a phenome-wide Mendelian randomisation study (MR-pheWAS). The MR-pheWAS suggests that retinol may exert causal effects on inflammation, adiposity, ocular measures, the microbiome, and MRI-derived brain phenotypes, amongst several others. Conversely, circulating retinol may be causally influenced by factors including lipids and serum creatinine. Finally, we demonstrate how a retinol polygenic score could identify individuals more likely to fall outside of the normative range of circulating retinol for a given age. In summary, this study provides a comprehensive evaluation of the genetics of circulating retinol, as well as revealing traits which should be prioritised for further investigation with respect to retinol related therapies or nutritional intervention.

Investigating the association between genetically proxied circulating levels of immune checkpoint proteins and cancer survival: protocol for a Mendelian randomisation analysis.

INTRODUCTION: Compared with the traditional drug development pathway, investigating alternative uses for existing drugs (ie, drug repurposing) requires substantially less time, cost and resources. Immune checkpoint inhibitors are licensed for the treatment of certain breast, colorectal, head and neck, lung and melanoma cancers. These drugs target immune checkpoint proteins to reduce the suppression of T cell activation by cancer cells. As T cell suppression is a hallmark of cancer common across anatomical sites, we hypothesise that immune checkpoint inhibitors could be repurposed for the treatment of additional cancers beyond the ones already indicated. METHODS AND ANALYSIS: We will use two-sample Mendelian randomisation to investigate the effect of genetically proxied levels of protein targets of two immune checkpoint inhibitors-programmed cell death protein 1 and programmed death ligand 1-on survival of seven cancer types (breast, colorectal, head and neck, lung, melanoma, ovarian and prostate). Summary genetic association data will be obtained from prior genome-wide association studies of circulating protein levels and cancer survival in populations of European ancestry. Various sensitivity analyses will be performed to examine the robustness of findings to potential violations of Mendelian randomisation assumptions, collider bias and the impact of alternative genetic instrument construction strategies. The impact of treatment history and tumour stage on the findings will also be investigated using summary-level and individual-level genetic data where available. ETHICS AND DISSEMINATION: No separate ethics approval will be required for these analyses as we will be using data from previously published genome-wide association studies which individually gained ethical approval and participant consent. Results from analyses will be submitted as an open-access peer-reviewed publication and statistical code will be made freely available on the completion of the analysis.

Evidence for a causal link between intra-pancreatic fat deposition and pancreatic cancer: A prospective cohort and Mendelian randomization study.

Prior observational studies suggest an association between intra-pancreatic fat deposition (IPFD) and pancreatic ductal adenocarcinoma (PDAC); however, the causal relationship is unclear. To elucidate causality, we conduct a prospective observational study using magnetic resonance imaging (MRI)-measured IPFD data and also perform a Mendelian randomization study using genetic instruments for IPFD. In the observational study, we use UK Biobank data (N = 29,463, median follow-up: 4.5 years) and find that high IPFD (>10%) is associated with PDAC risk (adjusted hazard ratio [HR]: 3.35, 95% confidence interval [95% CI]: 1.60-7.00). In the Mendelian randomization study, we leverage eight out of nine IPFD-associated genetic variants (p < 5 × 10-8) from a genome-wide association study in the UK Biobank (N = 25,617) and find that genetically determined IPFD is associated with PDAC (odds ratio [OR] per 1-standard deviation [SD] increase in IPFD: 2.46, 95% CI: 1.38-4.40) in the Pancreatic Cancer Cohort Consortium I, II, III (PanScan I-III)/Pancreatic Cancer Case-Control Consortium (PanC4) dataset (8,275 PDAC cases and 6,723 non-cases). This study provides evidence for a potential causal role of IPFD in the pathogenesis of PDAC. Thus, reducing IPFD may lower PDAC risk.

Genome-wide association and Mendelian randomization analysis provide insights into the shared genetic architecture between high-dimensional electrocardiographic features and ischemic heart disease.

Observational studies have revealed that ischemic heart disease (IHD) has a unique manifestation on electrocardiographic (ECG). However, the genetic relationships between IHD and ECG remain unclear. We took 12-lead ECG as phenotypes to conduct genome-wide association studies (GWAS) for 41,960 samples from UK-Biobank (UKB). By leveraging large-scale GWAS summary of ECG and IHD (downloaded from FinnGen database), we performed LD score regression (LDSC), Mendelian randomization (MR), and polygenic risk score (PRS) regression to explore genetic relationships between IHD and ECG. Finally, we constructed an XGBoost model to predict IHD by integrating PRS and ECG. The GWAS identified 114 independent SNPs significantly (P value < 5 × 10-8/800, where 800 denotes the number of ECG features) associated with ECG. LDSC analysis indicated significant (P value < 0.05) genetic correlations between 39 ECG features and IHD. MR analysis performed by five approaches showed a putative causal effect of IHD on four S wave related ECG features at lead III. Integrating PRS for these ECG features with age and gender, the XGBoost model achieved Area Under Curve (AUC) 0.72 in predicting IHD. Here, we provide genetic evidence supporting S wave related ECG features at lead III to monitor the IHD risk, and open up a unique approach to integrate ECG with genetic factors for pre-warning IHD.

Nine dietary habits and risk of colorectal cancer: a Mendelian randomization study.

BACKGROUND: Epidemiological studies have provided evidence that there is an association between diet and colorectal cancer. However, the causal relationship between dietary habits and colorectal cancer remains unknown. METHODS: The UK Biobank provided summary-level genome-wide association study data for nine dietary habits, including alcohol consumption (n = 549,703), instant coffee consumption (n = 250,308), fruit consumption (n = 210,947), meat consumption (n = 210,947), full cream milk consumption (n = 41,306), sweets consumption (n = 25,521), tea consumption (n = 501,494), vegetable consumption (n = 210,947), and yogurt/ice cream consumption (n = 210,947). Additionally, data on colorectal cancer were collected, consisting of 5,567 cases and 372,016 controls. The MR analysis employed inverse variance weighted, weighted median, MR-Egger regression, and MR multivariate residuals tests. RESULTS: In the predominantly European population, a positive association was observed between vegetables (OR = 1.014, 95% CI = 1.000-1.029, p = 0.048) and an increased risk of colorectal cancer. The results for vegetable did not survive correction for multiple comparisons. However, no strong evidence was found for other dietary factors, such as alcohol (OR = 1.012, 95% CI = 0.974-1.051, p = 0.556), fruit (OR = 1.007, 95% CI = 0.986-1.029, p = 0.512), meat (OR = 1.000, 95% CI = 0.987-1.026, p = 0.968), full cream milk (OR = 1.019, 95% CI = 0.979-1.061, p = 0.357), sweets (OR = 0.998, 95% CI = 0.991-1.004, p = 0.524), and tea (OR = 1.002, 95% CI = 0.994-1.009, p = 0.672), with regards to colorectal cancer risk in the European population. CONCLUSIONS: Our study highlights the need for a more nuanced approach to dietary recommendations for CRC prevention, with greater emphasis adherence to the Mediterranean dietary pattern.

The causal effect of Helicobacter pylori infection on coronary heart disease is mediated by the body mass index: a Mendelian randomization study.

The association between Helicobacter pylori (H. pylori) infection and coronary heart disease (CHD) remains controversial, with an unclear causal link. This study employed bidirectional Mendelian randomization (MR) method, using H. pylori infection as the exposure, to investigate its causal relationship with CHD diagnosis, prognosis, and potential pathogenesis. H. pylori infection exhibited a causal association with body mass index (BMI) (ß = 0.022; 95% CI 0.008-0.036; p = 0.001). Conversely, there was no discernible connection between H. pylori infection and the diagnosis of CHD (OR = 0.991; 95% CI 0.904-1.078; p = 0.842; IEU database; OR = 1.049; 95% CI 0.980-1.118; p = 0.178; FinnGen database) or CHD prognosis (OR = 0.999; 95% CI 0.997-1.001; p = 0.391; IEU database; OR = 1.022; 95% CI 0.922-1.123; p = 0.663; FinnGen database). Reverse MR analysis showed no causal effect of CHD on H. pylori infection. Our findings further support that H. pylori infection exerts a causal effect on CHD incidence, mediated by BMI. Consequently, eradicating or preventing H. pylori infection may provide an indirect clinical benefit for patients with CHD.

Leukocyte Telomere Length and Cardiac Structure and Function: A Mendelian Randomization Study.

BACKGROUND: Existing research demonstrates the association of shorter leukocyte telomere length with increased risk of age-related health outcomes including cardiovascular diseases. However, the direct causality of these relationships has not been definitively established. Cardiovascular aging at an organ level may be captured using image-derived phenotypes of cardiac anatomy and function. METHODS AND RESULTS: In the current study, we use 2-sample Mendelian randomization to assess the causal link between leukocyte telomere length and 54 cardiac magnetic resonance imaging measures representing structure and function across the 4 cardiac chambers. Genetically predicted shorter leukocyte telomere length was causally linked to smaller ventricular cavity sizes including left ventricular end-systolic volume, left ventricular end-diastolic volume, lower left ventricular mass, and pulmonary artery. The association with left ventricular mass (ß =0.217, Pfalse discovery rate=0.016) remained significant after multiple testing adjustment, whereas other associations were attenuated. CONCLUSIONS: Our findings support a causal role for shorter leukocyte telomere length and faster cardiac aging, with the most prominent relationship with left ventricular mass.

MRSamePopTest: introducing a simple falsification test for the two-sample mendelian randomisation 'same population' assumption.

Two-sample MR is an increasingly popular method for strengthening causal inference in epidemiological studies. For the effect estimates to be meaningful, variant-exposure and variant-outcome associations must come from comparable populations. A recent systematic review of two-sample MR studies found that, if assessed at all, MR studies evaluated this assumption by checking that the genetic association studies had similar demographics. However, it is unclear if this is sufficient because less easily accessible factors may also be important. Here we propose an easy-to-implement falsification test. Since recent theoretical developments in causal inference suggest that a causal effect estimate can generalise from one study to another if there is exchangeability of effect modifiers, we suggest testing the homogeneity of variant-phenotype associations for a phenotype which has been measured in both genetic association studies as a method of exploring the 'same-population' test. This test could be used to facilitate designing MR studies with diverse populations. We developed a simple R package to facilitate the implementation of our proposed test. We hope that this research note will result in increased attention to the same-population assumption, and the development of better sensitivity analyses.

KEY MESSAGE: • Two-sample Mendelian randomisation (2SMR) can be used to estimate the lifetime effect of a modifiable exposure on an outcome of interest. • 2SMR point estimates are not interpretable if the exposure and outcome GWASs do not come from homogeneous populations, so called 'same population' assumption. However, this assumption is often not validated in applied studies. • We propose and validate a novel sensitivity analysis for this assumption, which checks if SNP effects for the same trait are homogeneous across the two populations.

simmrd: An open-source tool to perform simulations in Mendelian randomization.

Mendelian randomization (MR) has become a popular tool for inferring causality of risk factors on disease. There are currently over 45 different methods available to perform MR, reflecting this extremely active research area. It would be desirable to have a standard simulation environment to objectively evaluate the existing and future methods. We present simmrd, an open-source software for performing simulations to evaluate the performance of MR methods in a range of scenarios encountered in practice. Researchers can directly modify the simmrd source code so that the research community may arrive at a widely accepted framework for researchers to evaluate the performance of different MR methods.

Maternal plasma cortisol's effect on offspring birth weight: a Mendelian Randomisation study.

BACKGROUND: Observational studies and randomized controlled trials have found evidence that higher maternal circulating cortisol levels in pregnancy are associated with lower offspring birth weight. However, it is possible that the observational associations are due to residual confounding. METHODS: We performed two-sample Mendelian Randomisation (MR) using a single genetic variant (rs9989237) associated with morning plasma cortisol (GWAS; sample 1; N = 25,314). The association between this maternal genetic variant and offspring birth weight, adjusted for fetal genotype, was obtained from the published EGG Consortium and UK Biobank meta-analysis (GWAS; sample 2; N = up to 406,063) and a Wald ratio was used to estimate the causal effect. We also performed an alternative analysis using all GWAS reported cortisol variants that takes account of linkage disequilibrium. We also tested the genetic variant's effect on pregnancy cortisol and performed PheWas to search for potential pleiotropic effects. RESULTS: The estimated effect of maternal circulating cortisol on birth weight was a 50 gram (95% CI, -109 to 10) lower birth weight per 1 SD higher log-transformed maternal circulating cortisol levels, using a single variant. The alternative analysis gave similar results (-33 grams (95% CI, -77 to 11)). The effect of the cortisol variant on pregnancy cortisol was 2-fold weaker than in the original GWAS, and evidence was found of pleiotropy. CONCLUSIONS: Our findings provide some evidence that higher maternal morning plasma cortisol causes lower birth weight. Identification of more independent genetic instruments for morning plasma cortisol are necessary to explore the potential bias identified.

Causal Associations of Education Level With Cardiovascular Diseases, Cardiovascular Biomarkers, and Socioeconomic Factors.

An inverse association of education level with cardiovascular diseases has been documented in observational studies, yet the causality and potential mechanisms remain to be determined. To systematically investigate the causal associations of education level with cardiovascular diseases, cardiovascular biomarkers, and socioeconomic factors, a 2-sample Mendelian randomization was performed. The results revealed that higher genetically determined education level was associated with lower risks of type 2 diabetes mellitus (odds ratio [OR] 0.54, 95% confidence interval [CI] 0.47 to 0.61, p = 3.04 × 10-23), peripheral artery disease (OR 0.62, 95% CI 0.51 to 0.76, p = 2.14 × 10-06), hypertension (OR 0.62, 95% CI 0.56 to 0.70, p = 4.22 × 10-16), coronary heart disease (OR 0.62, 95% CI 0.56 to 0.69, p = 3.50 × 10-19), myocardial infarction (OR 0.62, 95% CI 0.55 to 0.69, p = 2.58 × 10-16), ischemic stroke (OR 0.67, 95% CI 0.62 to 0.74, p = 6.00 × 10-19), deep vein thrombosis (OR 0.69, 95% CI 0.55 to 0.87, p = 0.0017), atrial fibrillation (OR 0.70, 95% CI 0.57 to 0.86, p = 0.0007), cardiac death (OR 0.71, 95% CI 0.60 to 0.86, p = 0.0003), heart failure (OR 0.72, 95% CI 0.65 to 0.79, p = 6.37 × 10-12), transient ischemic attack (OR 0.76, 95% CI 0.64 to 0.90, p = 0.0010), and venous thromboembolism (OR 0.79, 95% CI 0.67 to 0.92, p = 0.0028). Systolic blood pressure, diastolic blood pressure, C-reactive protein, body mass index, waist circumference, and triglycerides were decreased, whereas telomere length was increased. Subjects with higher education were less likely to smoke, intake salt, or be exposed to air pollution and depression state. They were more likely to take physical activity and possess more household income. In conclusion, higher education may causally decrease cardiovascular diseases through socioeconomic factors and cardiovascular biomarkers. Reducing education inequality is important in the management of cardiovascular diseases.