Background Coronary artery disease (CAD) remains the leading cause of mortality worldwide despite enormous efforts devoted to its prevention and treatment. While many genetic loci have been identified to associate with CAD, the intermediate causal risk factors and etiology have not been fully understood. This study assesses the causal effects of 37 heritable clinical factors on CAD in East Asian and European populations. Methods We collected genome-wide association summary statistics of 37 clinical factors from the Biobank Japan (42,793 to 191,764 participants) and the UK Biobank (314,658 to 442,817 participants), paired with summary statistics of CAD from East Asians (29,319 cases and 183,134 controls) and Europeans (91,753 cases and 311,344 controls). These clinical factors covered 12 cardiometabolic traits, 13 hematological indices, 7 hepatological and 3 renal function indices, and 2 serum electrolyte indices. We performed univariable and multivariable Mendelian randomization (MR) analyses in East Asians and Europeans separately, followed by meta-analysis. Results Univariable MR analyses identified reliable causal evidence (P < 0.05/37) of 10 cardiometabolic traits (height, body mass index [BMI], blood pressure, glycemic and lipid traits) and 4 other clinical factors related to red blood cells (red blood cell count [RBC], hemoglobin, hematocrit) and uric acid (UA). Interestingly, while generally consistent, we identified population heterogeneity in the causal effects of BMI and UA, with higher effect sizes in East Asians than those in Europeans. After adjusting for cardiometabolic factors in multivariable MR analysis, red blood cell traits (RBC, meta-analysis odds ratio 1.07 per standard deviation increase, 95% confidence interval 1.02–1.13; hemoglobin, 1.10, 1.03–1.16; hematocrit, 1.10, 1.04–1.17) remained significant (P < 0.05), while UA showed an independent causal effect in East Asians only (1.12, 1.06–1.19, P = 3.26×10−5). Conclusions We confirmed the causal effects of 10 cardiometabolic traits on CAD and identified causal risk effects of RBC, hemoglobin, hematocrit, and UA independent of traditional cardiometabolic factors. We found no causal effects for 23 clinical factors, despite their reported epidemiological associations. Our findings suggest the physiology of red blood cells and the level of UA as potential intervention targets for the prevention of CAD.

We systematically investigated the bidirectional causality between high-densitylipoprotein cholesterol (HDL-C), low-density-lipoprotein cholesterol (LDL-C), triglycerides (TG), fasting insulin (FI), and glycated hemoglobin A1c (HbA1c) based on genome-wide association summary statistics of Europeans (sample size n = 1,320,016 for lipids, 151,013 for FI, and 344,182 for HbA1c). We applied multivariable Mendelian randomization (MR) to account for the correlation between different traits, and constructed a causal graph with 13 significant causal effects after adjusting for multiple testing (P &lt; 0.05/20). Remarkably, we found the effects of lipids on glycemic traits were through FI from TG (β = 0.06 [95% CI: 0.03, 0.08] in unit of 1-SD for each trait) and HDL-C (β = -0.02 [-0.03, -0.01]). On the other hand, FI had strong a negative effect on HDL-C (β = -0.15 [-0.21, -0.09]) and positive effects on TG (β = 0.22 [0.14, 0.31]) and HbA1c (β = 0.15 [0.12, 0.19]), while HbA1c could raise LDL-C (β = 0.06 [0.03, 0.08]) and TG (β = 0.08 [0.06, 0.10]). These estimates derived from the inversevariance weighting method were robust when using different MR methods. Our results suggested that elevated FI was a strong causal factor of high TG and low HDL-C, which in turn would further increase FI. Therefore, early control of insulin resistance is critical to reduce the risk of type 2 diabetes, dyslipidemia, and cardiovascular complications.

Background: Pain often occurs in parallel with many neuropsychiatric disorders.However, the underlying mechanisms and potential causality have not been well studied. Methods:We collected the genome-wide association study (GWAS) summary statistics of 26 common pain and neuropsychiatric disorders with sample size ranging from 17,310 to 482,730 in European population. The genetic correlation between pair of pain and neuropsychiatric disorders, as well as the relevant cell types were investigated by linkage disequilibrium (LD) score regression analyses. Then transcriptome-wide association study (TWAS) was applied to identify the potential shared genes by integrating the gene expression information and GWAS. In addition, Mendelian randomization (MR) analyses were conducted to infer the potential causality between pain and neuropsychiatric disorders.Results: Among the 169 pairwise pain and neuropsychiatric disorders, 55 pairs showed significant (P < 1.54×10 −4 ) positive correlations (median rg = 0.43) and 9 pairs showed negative correlations (median rg = −0.31). MR analyses identified 26 significant (P < 1.48×10 −4 ) likely causal associations, for instance, neuroticism and insomnia were risk 2 / 29 factors for most of short-term pain, multisite chronic pain was risk factor for neuroticism, insomnia, major depressive disorder and attention deficit/hyperactivity disorder, and vice versa. The signals of pain and neuropsychiatric disorders tended to be enriched in the functional regions of cell types from central nervous system (CNS).A total of 19 genes shared in at least one pain and neuropsychiatric disorder pair were identified by TWAS integrating the gene expression information of CNS. The shared genes included AMT, NCOA6 and UNC45A which involved in glycine degradation, insulin secretion and cell proliferation, respectively, suggesting pain and neuropsychiatric disorders might share neuronal signaling-related, metabolism-related and proliferation-related pathogenic mechanisms. Conclusion:Our findings provided the evidence of shared genetic structure, causality and potential shared pathogenic mechanisms between pain and neuropsychiatric disorders, and enhanced our understanding of the comorbidities of pain and neuropsychiatric disorders.

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Background Although immune cells are involved in acute coronary syndrome (ACS), few studies have explored the association of incident ACS with the relative immune cell proportions. We aimed to investigate the association of immune cell proportions with the incidence and risk factors of ACS in the Dongfeng–Tongji cohort. Methods We conducted the analyses with 38,295 subjects from the first follow-up of the Dongfeng–Tongji cohort, including DNA methylation profiles for 1570 individuals. The proportions of immune cell types were observed from routine blood tests or estimated from DNA methylation profiles. For both observed and estimated immune cell proportions, we tested their associations with risk factors of ACS by multivariable linear regression models. In addition, the association of each immune cell proportion with incident ACS was assessed by the Cox regression model and conditional logistic regression model, respectively, adjusting for the risk factors of ACS. Findings The proportions of lymphocytes, monocytes, and neutrophils showed strong associations with sex, followed by diabetes. Moreover, sex and current smoking were the two factors with strongest association with the proportions of lymphocyte subtypes. The hazard ratio (HR) and 95% confidence interval (CI) of incident ACS per standard deviation (SD) increase in proportions of lymphocytes and neutrophils were 0.91 (0.85–0.96) and 1.10 (1.03–1.16), respectively. Furthermore, the OR (95% CI) of incident ACS per SD increase in proportions of NK cells, CD4+ T cells, and B cells were 0.88 (0.78–0.99), 1.15 (1.03–1.30), and 1.13 (1.00–1.26), respectively. Interpretation The proportions of immune cells were associated with several risk factors of ACS, including sex, diabetes, and current smoking. In addition, proportion of neutrophils had a risk effect, while proportion of lymphocytes had a protective effect on the incidence of ACS. The protective effect of lymphocytes was probably driven by NK cells.