Causal Associations of DNA Methylation and Cardiovascular Disease: A Two-Sample Mendelian Randomization Study.

Background: There is growing evidence that concentrations of DNA methylation are associated with cardiovascular disease; however, it is unclear whether this association reflects a causal relationship. Methods: We utilized a two-sample Mendelian randomization (MR) approach to investigate whether DNA methylation can affect the risk of developing cardiovascular disease in human life. We primarily performed the inverse variance weighted (IVW) method to analyze the causal effect of DNA methylation on multiple cardiovascular diseases. Additionally, to ensure the robustness of our findings, we conducted several sensitivity analyses using alternative methodologies. These analysis methods included maximum likelihood, MR-Egger regression, weighted median method, and weighted model methods. Results: Inverse variance weighted estimates suggested that an SD increase in DNA methylation Hannum age acceleration exposure increased the risk of cardiac arrhythmias (OR = 1.03, 95% CI 1.00-1.05, p = 0.0290) and atrial fibrillation (OR = 1.03, 95% CI 1.00-1.05, p = 0.0022). We also found that an SD increase in DNA methylation PhenoAge acceleration exposure increased the risk of heart failure (OR = 1.01, 95% CI 1.00-1.03, p = 0.0362). Exposure to DNA methylation-estimated granulocyte proportions was found to increase the risk of hypertension (OR = 1.00, 95% CI 1.00-1.0001, p = 0.0291). Exposure to DNA methylation-estimated plasminogen activator inhibitor-1 levels was found to increase the risk of heart failure (OR = 1.00, 95% CI 1.00-1.00, p = 0.0215). Conclusion: This study reveals a causal relationship between DNA methylation and CVD. Exposed to high levels of DNA methylation Hannum age acceleration inhabitants with an increased risk of cardiac arrhythmias and atrial fibrillation. DNA methylation PhenoAge acceleration levels exposure levels were positively associated with the increased risk of developing heart failure. This has important implications for the prevention of cardiovascular diseases.

Integrated analysis of single cell-RNA sequencing and Mendelian randomization identifies lactate dehydrogenase B as a target of melatonin in ischemic stroke.

AIMS: Despite the success of single-cell RNA sequencing in identifying cellular heterogeneity in ischemic stroke, clarifying the mechanisms underlying these associations of differently expressed genes remains challenging. Several studies that integrate gene expression and gene expression quantitative trait loci (eQTLs) with genome wide-association study (GWAS) data to determine their causal role have been proposed. METHODS: Here, we combined Mendelian randomization (MR) framework and single cell (sc) RNA sequencing to study how differently expressed genes (DEGs) mediating the effect of gene expression on ischemic stroke. The hub gene was further validated in the in vitro model. RESULTS: We identified 2339 DEGs in 10 cell clusters. Among these DEGs, 58 genes were associated with the risk of ischemic stroke. After external validation with eQTL dataset, lactate dehydrogenase B (LDHB) is identified to be positively associated with ischemic stroke. The expression of LDHB has also been validated in sc RNA-seq with dominant expression in microglia and astrocytes, and melatonin is able to reduce the LDHB expression and activity in vitro ischemic models. CONCLUSION: Our study identifies LDHB as a novel biomarker for ischemic stroke via combining the sc RNA-seq and MR analysis.

Dietary factors and Alzheimer's disease risk: a Mendelian randomization study.

BACKGROUND: Prior observational research has investigated the association between dietary patterns and Alzheimer's disease (AD) risk. Nevertheless, due to constraints in past observational studies, establishing a causal link between dietary habits and AD remains challenging. METHODS: Methodology involved the utilization of extensive cohorts sourced from publicly accessible genome-wide association study (GWAS) datasets of European descent for conducting Mendelian randomization (MR) analyses. The principal analytical technique utilized was the inverse-variance weighted (IVW) method. RESULTS: The MR analysis conducted in this study found no statistically significant causal association between 20 dietary habits and the risk of AD (All p > 0.05). These results were consistent across various MR methods employed, including MR-Egger, weighted median, simple mode, and weighted mode approaches. Moreover, there was no evidence of horizontal pleiotropy detected (All p > 0.05). CONCLUSION: In this MR analysis, our finding did not provide evidence to support the causal genetic relationships between dietary habits and AD risk.

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.

Causal relationship between serum metabolites and juvenile idiopathic arthritis: a mendelian randomization study.

BACKGROUND: Juvenile Idiopathic Arthritis (JIA) is a condition that occurs when individuals under the age of 16 develop arthritis that lasts for more than six weeks, and the cause is unknown. The development of JIA may be linked to serum metabolites. Nevertheless, the association between JIA pathogenesis and serum metabolites is unclear, and there are discrepancies in the findings across studies. METHODS: In this research, the association between JIA in humans and 486 serum metabolites was assessed using genetic variation data and genome-wide association study. The identification of causal relationships was accomplished through the application of univariate Mendelian randomization (MR) analysis. Various statistical methods, including inverse variance weighted and MR-Egger, were applied to achieve this objective. To ensure that the findings from the MR analysis were trustworthy, a number of assessments were carried out. To ensure the accuracy of the obtained results, a range of techniques were utilised including the Cochran Q test, examination of the MR-Egger intercept, implementation of the leave-one-out strategy, and regression analysis of linkage disequilibrium scores. In order to identify the specific metabolic pathways associated with JIA, our primary objective was to perform pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes. RESULTS: Two-sample summary data MR analyses and sensitivity analyses showed that five metabolites were significantly causally associated with JIA, including two risk factors-kynurenine (odds ratio [OR]: 16.39, 95% confidence interval [CI]: 2.07-129.63, p = 5.11 × 10- 6) and linolenate (OR: 16.48, 95% CI: 1.32-206.22, p = 0.030)-and three protective factors-3-dehydrocarnitine (OR: 0.32, 95% CI: 0.14-0.72, p = 0.007), levulinate (4-oxovalerate) (OR: 0.40, 95% CI: 0.20-0.80, p = 0.010), and X-14,208 (phenylalanylserine) (OR: 0.68, 95% CI: 0.51-0.92, p = 0.010). Furthermore, seven metabolic pathways, including α-linolenic acid metabolism and pantothenate and CoA biosynthesis, are potentially associated with the onset and progression of JIA. CONCLUSION: Five serum metabolites, including kynurenine and 3-dehydrocarnitine, may be causally associated with JIA. These results provide a theoretical framework for developing effective JIA prevention and screening strategies.

Appendicular lean mass and the risk of stroke and Alzheimer's disease: a mendelian randomization study.

BACKGROUND: Appendicular lean mass (ALM) is a good predictive biomarker for sarcopenia. And previous studies have reported the association between ALM and stroke or Alzheimer's disease (AD), however, the causal relationship is still unclear, The purpose of this study was to evaluate whether genetically predicted ALM is causally associated with the risk of stroke and AD by performing Mendelian randomization (MR) analyses. METHODS: A two-sample MR study was designed. Genetic variants associated with the ALM were obtained from a large genome-wide association study (GWAS) and utilized as instrumental variables (IVs). Summary-level data for stroke and AD were generated from the corresponding GWASs. We used random-effect inverse-variance weighted (IVW) as the main method for estimating causal effects, complemented by several sensitivity analyses, including the weighted median, MR-Egger, and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods. Multivariable analysis was further conducted to adjust for confounding factors, including body mass index (BMI), type 2 diabetes mellitus (T2DM), low density lipoprotein-C (LDL-C), and atrial fibrillation (AF). RESULTS: The present MR study indicated significant inverse associations of genetically predicted ALM with any ischemic stroke ([AIS], odds ratio [OR], 0.93; 95% confidence interval [CI], 0.89-0.97; P = 0.002) and AD (OR, 090; 95% CI 0.85-0.96; P = 0.001). Regarding the subtypes of AIS, genetically predicted ALM was related to the risk of large artery stroke ([LAS], OR, 0.86; 95% CI 0.77-0.95; P = 0.005) and small vessel stroke ([SVS], OR, 0.80; 95% CI 0.73-0.89; P < 0.001). Regarding multivariable MR analysis, ALM retained the stable effect on AIS when adjusting for BMI, LDL-C, and AF, while a suggestive association was observed after adjusting for T2DM. And the estimated effect of ALM on LAS was significant after adjustment for BMI and AF, while a suggestive association was found after adjusting for T2DM and LDL-C. Besides, the estimated effects of ALM were still significant on SVS and AD after adjustment for BMI, T2DM, LDL-C, and AF. CONCLUSIONS: The two-sample MR analysis indicated that genetically predicted ALM was negatively related to AIS and AD. And the subgroup analysis of AIS revealed a negative causal effect of genetically predicted ALM on LAS or SVS. Future studies are required to further investigate the underlying mechanisms.

Associations between varicose veins and heart failure: A genetic correlation and mendelian randomization study.

Varicose veins and heart failure (HF) are increasingly prevalent. Although numbers of observational studies have indicated that varicose veins might contribute to the risk of HF, the causal relationship between them remains unclear due to the uncontrolled confounding factors and reverse causation bias. Therefore, this study aimed to explore the potential causal relationship between varicose veins and HF. Based on publicly released genome-wide association studies (GWAS), gene correlation was assessed using linkage disequilibrium score (LDSC) regression, and we conducted a two-sample Mendelian randomization (TSMR) analysis to infer the causal relationship. We performed the Inverse variance weighted (IVW) method as the primary analysis, and used Weighted median, MR-Egger, weighted mode, simple mode, and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods to detect and correct for horizontal pleiotropy. LDSC revealed there was a positive genetic correlation between varicose veins and HF (rg = 0.1726184, Se = 0.04511803, P = .0001). The results of the IVW method indicated that genetically predicted varicose veins were associated with an increased risk of HF (odds ratio (OR) = 1.03; 95% confidence interval (CI): 1.01-1.06; P = .009). Our findings illustrated the significant causal effect of varicose veins on HF, suggesting that people with varicose veins might have a higher risk of HF. The results provided a novel and important perspective into the development mechanism of HF.

Association between allergic diseases and both psoriasis and psoriatic arthritis: a bidirectional 2-sample Mendelian randomization study.

Background An increasing body of observational studies has indicated a potential link between allergic diseases, namely atopic dermatitis (AD), allergic rhinitis (AR), allergic asthma (AA), and psoriasis (PSO) as well as psoriatic arthritis (PSA). However, the presence and causal direction of this association remain uncertain. Methods We conducted two-sample Mendelian randomization (TSMR) analyses utilizing summary statistics derived from genome-wide association studies (GWAS) consortia. The summary statistics were obtained from a substantial participant cohort, consisting of 116,000 individuals (21,000 AD cases and 95,000 controls), 462,933 individuals (26,107 AR cases and 436,826 controls), and 140,308 individuals (4859 AA cases and 135,449 controls). The summary statistics for PSO (9267 cases and 360,471 controls) and PSA (3186 cases and 240,862 controls) were sourced from the FinnGen database. The primary analytical approach employed inverse variance weighting (IVW) as the main method within TSMR. We validated our findings through a series of sensitivity analyses. Furthermore, we performed reverse TSMR analyses to evaluate the potential presence of reverse causality. Results Our investigation revealed a potential protective effect of AD against both PSO (OR = 0.922, 95% CI = 0.863-0.984, p = 0.015)and PSA(OR = 0.915, 95% CI = 0.843-0.993, p = 0.033). Moreover, employing inverse MR analysis, we obtained compelling evidence supporting the protective role of PSO in preventing AD (OR = 0.891, 95% CI = 0.829-0.958, p = 0.002), as well as AR (OR = 0.998, 95% CI = 0.996-0.999, p = 0.008), these associations remained statistically significant even after Bonferroni correction was applied to account for multiple comparisons. Furthermore, our findings did not reveal any substantial causal relationship between AA and either PSO or PSA. Conclusion Our study provides compelling evidence that PSO significantly confers protection against both AD and AR, while AD is likely to act as a protective factor for both PSO and PSA. Despite previous studies suggesting an association between allergic diseases and the incidence of PSO and PSA, our findings do not support this claim. To obtain more accurate and reliable conclusions regarding the causal mechanisms involved, larger sample sizes in randomized controlled trials or MR studies are warranted.

Associations between immune cells signatures and osteoarthritis: An integrated analysis of bidirectional Mendelian randomization and Bayesian colocalization.

BACKGROUND: Previous investigations have explored the associations between immune cell signatures and osteoarthritis (OA); however, causality remains unclear. This study employs an integrated analysis, combining bidirectional Mendelian randomization (MR) and Bayesian colocalization (Coloc), to investigate causal relationships between 731 immune cells signatures and OA, identifying shared causal variants. METHODS: Utilizing publicly available summary data, this study primarily employs inverse variance weighting (IVW). Supplementary methods include MR-Egger regression, weighted median, weight mode, and simple mode. Various sensitivity tests, including Cochran's Q test, MR pleiotropy Residual Sum and Outlier, and leave-one-out tests, were conducted to assess the robustness of the analysis results. Coloc was employed to identify shared causal genetic variants among potential associations. RESULTS: IVW analysis revealed 196 immune cell signatures potentially linked to OA across diverse subtypes. Reverse MR analyses indicated the causal impact of OA on the levels of 140 immune cell signatures, with subtype-specific variations. Notably, several specific associations, including CD64 on CD14-CD16 + monocyte for Hip OA (OR = 1.0593, 95 % CI: 1.0260-1.0938, P = 0.0004), HLA-DR on CD14 + CD16- monocyte (OR = 0.9664, 95 % CI: 0.9497-0.9834, P = 0.0001), HLA-DR on CD14 + monocyte (OR = 0.9680, 95 % CI: 0.9509-0.9853, P = 0.0003) in the Knee or Hip OA, PDL-1 on CD14-CD16 + monocyte by All OA (OR = 1.7091, 95 %CI:1.2494-2.3378, P = 0.0008), and herpesvirus entry mediator on effector memory CD4 + T cell by Spine OA (OR = 0.5200, 95 %CI:0.3577-0.7561, P = 0.0006) remained significant post-Bonferroni correction. Sensitivity tests validated the credibility of the IVW analysis. Additionally, Coloc revealed several potential associations among shared genetic variants, including rs115328872, rs1800973, and rs317667. CONCLUSIONS: Our findings provide evidence for the potential involvement of immune cell signatures in OA development, revealing avenues for early prevention and innovative therapeutic strategies.

Causal relationship of interleukin-6 and its receptor on sarcopenia traits using mendelian randomization.

BACKGROUND: Previous research has extensively examined the role of interleukin 6 (IL-6) in sarcopenia. However, the presence of a causal relationship between IL-6, its receptor (IL-6R), and sarcopenia remains unclear. METHOD: In this study, we utilized summary-level data from genome-wide association studies (GWAS) focused on appendicular lean mass (ALM), hand grip strength, and walking pace. Single nucleotide polymorphisms (SNPs) were employed as genetic instruments for IL-6 and IL-6R to estimate the causal effect of sarcopenia traits. We adopted the Mendelian randomization (MR) approach to investigate these associations using the inverse variance weighted (IVW) method as the primary analytical approach. Additionally, we performed sensitivity analyses to validate the reliability of the MR results. RESULT: This study revealed a significant negative association between main IL-6R and eQTL IL-6R on the left grip strength were - 0.013 (SE = 0.004, p < 0.001) and -0.029 (SE = 0.007, p < 0.001), respectively. While for the right grip strength, the estimates were - 0.011 (SE = 0.001, p < 0.001) and - 0.021 (SE = 0.008, p = 0.005). However, no evidence of an association for IL-6R with ALM and walking pace. In addition, IL-6 did not affect sarcopenia traits. CONCLUSION: Our study findings suggest a negative association between IL-6R and hand grip strength. Additionally, targeting IL-6R may hold potential value as a therapeutic approach for the treatment of hand grip-related issues.

Association of dietary nutrient intake with type 2 diabetes: A Mendelian randomization study.

Observational research suggests that the evidence linking dietary nutrient intake (encompassing minerals, vitamins, amino acids, and unsaturated fatty acids) to type 2 diabetes (T2D) is both inconsistent and limited. This study aims to explore the potential causal relationship between dietary nutrients and T2D. Causal estimation utilized Mendelian randomization techniques. Single nucleotide polymorphisms linked to dietary nutrients were identified from existing genome-wide association studies and used as instrumental variables. Genome-wide association studies data pertinent to T2D were sourced from the DIMANTE consortium and the FinnGen database. Techniques including inverse variance weighting (IVW), weighted mode, weighted median, and Mendelian randomization-Egger were employed for causal inference, complemented by sensitivity analysis. Genetically predicted higher phenylalanine (IVW: odds ratio = 1.10 95% confidence interval 1.04-1.17, P = 1.5 × 10-3, q_pval = 3.4 × 10-2) and dihomo-gamma-linolenic acid (IVW: odds ratio = 1.001 95% confidence interval 1.0006-1.003, P = 3.7 × 10-3, q_pval = 4.1 × 10-2) levels were directly associated with T2D risk. Conversely, no causal relationships between other nutrients and T2D were established. We hypothesize that phenylalanine and dihomo-gamma-linolenic acid contribute to the pathogenesis of T2D. Clinically, the use of foods with high phenylalanine content may pose potential risks for patients with a heightened risk of T2D. Our study provides evidence supporting a causal link between dietary nutrient intake and the development of T2D.

Association between air pollution and skin cutaneous melanoma: A Mendelian randomization study.

There has been a consistent and notable increase in the global prevalence of skin cutaneous melanoma (SKCM). Although genetic factors are closely associated with the occurrence and development of melanoma, the potential influence of environmental factors cannot be overlooked. The existing literature lacks a definitive consensus on the correlation between air pollution and the incidence rate of SKCM. This study seeks to investigate the causal relationship between air pollution, specifically focusing on particulate matter (PM) 2.5, PM2.5-10, PM10, and nitrogen oxides, and the risk of SKCM. A 2-sample Mendelian randomization (MR) method was applied, utilizing extensive publicly accessible genome-wide association studies summary datasets within European populations. The primary analytical method employed was the inverse variance weighted method. Supplementary methods, including the weighted median model, MR-Egger, simple model, and weighted model, were chosen to ensure robust analysis. Heterogeneity assessment was conducted using Cochran's Q test. To identify potential pleiotropy, both MR-Egger regression and the MR-PRESSO global test were employed. Additionally, a sensitivity analysis was performed using the leave-one-out method. The analysis revealed no statistically significant association between air pollution and SKCM risk, with specific findings as follows: PM2.5 (P = .485), PM2.5-10 (P = .535), PM10 (P = .136), and nitrogen oxides (P = .745). While some results exhibited heterogeneity, all findings demonstrated an absence of pleiotropy. This study did not find substantive evidence supporting a causal relationship between air pollution and the risk of SKCM within European populations. The comprehensive MR analysis, encompassing various pollutants, suggests that environmental factors such as air pollution may not be significant contributors to the development of SKCM.

Genome- and epigenome-wide association studies identify susceptibility of CpG sites and regions for metabolic syndrome in a Korean population.

BACKGROUND: While multiple studies have investigated the relationship between metabolic syndrome (MetS) and its related traits (fasting glucose, triglyceride, HDL cholesterol, blood pressure, waist circumference) and DNA methylation, our understanding of the epigenetic mechanisms in MetS remains limited. Therefore, we performed an epigenome-wide meta-analysis of blood DNA methylation to identify differentially methylated probes (DMPs) and differentially methylated regions (DMRs) associated with MetS and its components using two independent cohorts comprising a total of 2,334 participants. We also investigated the specific genetic effects on DNA methylation, identified methylation quantitative trait loci (meQTLs) through genome-wide association studies and further utilized Mendelian randomization (MR) to assess how these meQTLs subsequently influence MetS status. RESULTS: We identified 40 DMPs and 27 DMRs that are significantly associated with MetS. In addition, we identified many novel DMPs and DMRs underlying inflammatory and steroid hormonal processes. The most significant associations were observed in 3 DMPs (cg19693031, cg26974062, cg02988288) and a DMR (chr1:145440444-145441553) at the TXNIP, which are involved in lipid metabolism. These CpG sites were identified as coregulators of DNA methylation in MetS, TG and FAG levels. We identified a total of 144 cis-meQTLs, out of which only 13 were found to be associated with DMPs for MetS. Among these, we confirmed the identified causal mediators of genetic effects at CpG sites cg01881899 at ABCG1 and cg00021659 at the TANK genes for MetS. CONCLUSIONS: This study observed whether specific CpGs and methylated regions act independently or are influenced by genetic effects for MetS and its components in the Korean population. These associations between the identified DNA methylation and MetS, along with its individual components, may serve as promising targets for the development of preventive interventions for MetS.

Causal influence of gut microbiota on small cell lung cancer: a Mendelian randomization study.

BACKGROUND: Previous studies have hinted at a significant link between lung cancer and the gut microbiome, yet their causal relationship remains to be elucidated. METHODS: GWAS data for small cell lung cancer (SCLC) was extracted from the FinnGen consortium, comprising 179 cases and 218 613 controls. Genetic variation data for 211 gut microbiota were obtained as instrumental variables from MiBioGen. Mendelian randomization (MR) was employed to determine the causal relationship between the two, with inverse variance weighting (IVW) being the primary method for causal analysis. The MR results were validated through several sensitivity analyses. RESULTS: The study identified a protective effect against SCLC for the genus Eubacterium ruminantium group (OR = 0.413, 95% CI: 0.223-0.767, p = 0.00513), genus Barnesiella (OR = 0.208, 95% CI: 0.0640-0.678, p = 0.00919), family Lachnospiraceae (OR = 0.319, 95% CI: 0.107-0.948, p = 0.03979), and genus Butyricimonas (OR = 0.376, 95% CI: 0.144-0.984, p = 0.04634). Conversely, genus Intestinibacter (OR = 3.214, 95% CI: 1.303-7.926, p = 0.01125), genus Eubacterium oxidoreducens group (OR = 3.391, 95% CI: 1.215-9.467, p = 0.01973), genus Bilophila (OR = 3.547, 95% CI: 1.106-11.371, p = 0.03315), and order Bacillales (OR = 1.860, 95% CI: 1.034-3.347, p = 0.03842) were found to potentially promote the onset of SCLC. CONCLUSION: We identified potential causal relationships between certain gut microbiota and SCLC, offering new insights into microbiome-mediated mechanisms of SCLC pathogenesis, resistance, mutations, and more.

Multiple coronary heart diseases are risk factors for mental health disorders: A mendelian randomization study.

BACKGROUND: Previous observational studies have suggested associations between Coronary Heart Disease (CHD) and Mental Health Disorders (MHD). However, the causal nature of these relationships has remained elusive. OBJECTIVE: The purpose of this study is to elucidate the causal relationships between eight distinct types of CHD and six types of MHD using Mendelian randomization (MR) analysis. METHODS: The MR analysis employed a suite of methods including inverse variance-weighted (IVW), MR-Egger, weighted mode, weighted median, and simple mode techniques. To assess heterogeneity, IVW and MR-Egger tests were utilized. MR-Egger regression also served to investigate potential pleiotropy. The stability of IVW results was verified by leave-one-out sensitivity analysis. RESULTS: We analyzed data from over 2,473,005 CHD and 803,801 MHD patients, informed by instrumental variables from large-scale genomic studies on European populations. The analysis revealed a causal increase in the risk of Major Depressive Disorder and Mania associated with Coronary Artery Disease and Myocardial Infarction. Heart Failure was found to causally increase the risk for Bipolar Disorder and Schizophrenia. Atrial Fibrillation and Ischemic Heart Diseases were positively linked to Generalized Anxiety Disorder and Mania, respectively. There was no significant evidence of an association between Hypertensive Heart Disease, Hypertrophic Cardiomyopathy, Pulmonary Heart Disease, and MHD. Reverse MR analysis indicated that MHD do not serve as risk factors for CHD. CONCLUSIONS: The findings suggest that specific types of CHD may act as risk factors for certain MHDs. Consequently, incorporating psychological assessments into the management of patients with CHD could be advantageous.

Collider bias correction for multiple covariates in GWAS using robust multivariable Mendelian randomization.

Genome-wide association studies (GWAS) have identified many genetic loci associated with complex traits and diseases in the past 20 years. Multiple heritable covariates may be added into GWAS regression models to estimate direct effects of genetic variants on a focal trait, or to improve the power by accounting for environmental effects and other sources of trait variations. When one or more covariates are causally affected by both genetic variants and hidden confounders, adjusting for them in GWAS will produce biased estimation of SNP effects, known as collider bias. Several approaches have been developed to correct collider bias through estimating the bias by Mendelian randomization (MR). However, these methods work for only one covariate, some of which utilize MR methods with relatively strong assumptions, both of which may not hold in practice. In this paper, we extend the bias-correction approaches in two aspects: first we derive an analytical expression for the collider bias in the presence of multiple covariates, then we propose estimating the bias using a robust multivariable MR (MVMR) method based on constrained maximum likelihood (called MVMR-cML), allowing the presence of invalid instrumental variables (IVs) and correlated pleiotropy. We also established the estimation consistency and asymptotic normality of the new bias-corrected estimator. We conducted simulations to show that all methods mitigated collider bias under various scenarios. In real data analyses, we applied the methods to two GWAS examples, the first a GWAS of waist-hip ratio with adjustment for only one covariate, body-mass index (BMI), and the second a GWAS of BMI adjusting metabolomic principle components as multiple covariates, illustrating the effectiveness of bias correction.

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.

Systemic Inflammatory Regulators Associated with Osteoporosis: A Bidirectional Mendelian Randomization Study.

To elucidate the precise upstream and downstream regulatory mechanisms of inflammatory factors in osteoporosis (OP) progression and to establish a causal relationship between inflammatory factors and OP. We conducted bidirectional Mendelian randomization (MR) analyses using data for 41 cytokines obtained from three independent cohorts comprising 8293 Finnish individuals. Estimated bone mineral density (eBMD) data were derived from 426,824 UK Biobank White British individuals (55% female) and fracture data from 416,795 UK Biobank participants of European ancestry. The inverse variance-weighted method was the primary MR analysis approach. We employed other methods as complementary approaches for mutual corroboration. To test for pleiotropy and heterogeneity, we used the MR-Egger regression, MR-pleiotropy residual sum and outlier global test, and the Cochrane Q test. Macrophage inflammatory protein (MIP)-1α and interleukin (IL)-12p70 expression associated negatively and causally with eBMD (ß = -0.017 [MIP-1α], ß = -0.011 [IL-12p70]). Conversely, tumor necrosis factor-related apoptosis-inducing ligand was associated with a decreased risk of fractures (Odds Ratio: 0.980). Additionally, OP influenced the expression of multiple inflammatory factors, including growth-regulated oncogene-α, interferon-gamma, IL-6, beta nerve growth factor, and IL-2. Finally, we discovered complex bidirectional causal relationships between IL-8, IL-10, and OP. Specific inflammatory factors may contribute to OP development or may be causally affected by OP. We identified a bidirectional causal relationship between certain inflammatory factors and OP. These findings provide new perspectives for early prediction and targeted treatment of OP. Larger cohort studies are necessary in the future to further validate these findings.

The causal role of circulating immunity-inflammation in preeclampsia: A Mendelian randomization.

Patients with systemic autoimmune diseases, such as systemic lupus erythematosus, were at a higher risk for preeclampsia. The causal relationship between immunological inflammation and preeclampsia (PE) remains uncertain. We aimed to investigate the causal relationship between circulating immune inflammation and PE. Genetically predicted blood immune cells and circulating inflammatory proteins were identified using two genome-wide association studies (GWAS). We used a two-sample Mendelian randomization (MR) method to determine whether circulating immunological inflammation causes PE. Our findings indicated that ten immunophenotypes were identified to be significantly associated with PE risk: CD62L- Dendritic Cell Absolute Count, CD86+ myeloid Dendritic Cell %Dendritic Cell, CD62L- myeloid Dendritic Cell Absolute Count, CD86+ myeloid Dendritic Cell Absolute Count, CD62L- myeloid Dendritic Cell %Dendritic Cell, CD62L- CD86+ myeloid Dendritic Cell %Dendritic Cell, CD62L- CD86+ myeloid Dendritic Cell Absolute Count, CD16 on CD14+ CD16+ monocyte, HLA DR+ Natural Killer Absolute Count, and T cell Absolute Count. Ninety-one inflammation-related proteins had no statistically significant effect on PE following false discovery rate (FDR) correction. Certain proteins exhibited unadjusted low p-values that merited mention. These proteins include interleukin-10 (OR = 0.76, 95%CI = 0.63-0.93, p = .006), fibroblast growth factor 21 (OR = 1.23, 95%CI = 1.01-1.47, p = .035), and Caspase 8 (OR = 0.65, 95%CI = 0.50-0.85, p = .001). The ELISA analysis demonstrated elevated levels of FGF-21 and decreased levels of IL-10 and Caspase-8 in the plasma of patients with PE. These findings reveal that immunophenotypes and circulating inflammatory proteins may induce PE, confirming the importance of peripheral Immunity-Inflammation in PE. The discovery has the potential to lead to earlier detection and more effective treatment techniques.