Causal association between remnant cholesterol level and risk of cardiovascular diseases: a bidirectional two sample mendelian randomization study.
Serum lipids have been associated with an increased risk of various cardiovascular diseases (CVDs) in several observational studies, but the causal inference between the remnant cholesterol (RC) levels and several CVDs risk has not been established. The purpose of this study was to investigate whether there is a causal relationship between RC levels and risk of developing CVDs by a bidirectional two-sample Mendelian randomization (TSMR) analysis. One TSMR analysis was performed using the publicly released large-scale genome-wide association study (GWAS) data. Inverse variance weighted (IVW) method was chosen as the main analysis method, and MR-Egger, weighted median, simple mode, and weighted mode were used as supplementary methods. We conducted a series of sensitivity analyses to assess the robustness of the main results, including the Cochran's Q test, MR-Egger intercept test, leave-one-out sensitivity analysis, and funnel plot. The main IVW method revealed that genetically predicted serum level of RC is significantly associated with an increased risk of developing ischemic heart disease (OR = 1.409, 95%CI = 1.284-1.546, P value = 4.753E-13), unstable angina pectoris (OR = 1.621, 95%CI = 1.398-1.880, P value = 1.672E-10), myocardial infarction (OR = 1.526, 95%CI = 1.337-1.741, P value = 3.771E-10), cardiac arrest (OR = 1.595, 95%CI = 1.322-1.924, P value = 1.076E-06), heart failure (OR = 1.086, 95%CI = 1.009-1.169, P value = 0.028), hypertension (OR = 1.089, 95%CI = 1.043-1.136, P value = 9.458E-05), major coronary heart disease (CHD) events (OR = 1.515, 95%CI = 1.376-1.669, P value = 3.217E-17), coronary atherosclerosis (OR = 1.388, 95%CI = 1.231-1.564, P value = 7.739E-08), cardiac arrhythmias (OR = 1.067, 95%CI = 1.008-1.130, P value = 0.025), and atrial fibrillation and flutter (OR = 1.122, 95%CI = 1.039-1.211, P value = 0.003). Additionally, the causal associations between the RC levels and these CVDs remained significant after correcting for the false discovery rate (all P value < 0.05). However, this study did not find any significant association of RC with cardiomyopathy and pericarditis (both P value > 0.05). Heterogeneity existed in the IVs of RC and ischemic heart disease, unstable angina pectoris, myocardial infarction, heart failure, hypertension, major CHD events, cardiomyopathy, coronary atherosclerosis, cardiac arrhythmias and atrial fibrillation and flutter using the Cochran's Q test (all P value < 0.05). Moreover, there was no horizontal pleiotropy in this study (all P value > 0.05). The leave-one-out sensitivity analyses showed that the causal effects between RC level and CVDs (except for heart failure, cardiomyopathy, pericarditis and cardiac arrhythmias) are not driven by a single SNP. The funnel plots showed that there is no obvious potential bias in our study. In the replication analysis, the genetically predicted RC levels were positively associated with a 43.12% higher risk of coronary artery disease. This present study supported the causal link between RC and heightened the risk of CVDs, indicating that RC-lowering treatment might be effective in preventing CVDs.
Zhong L
，Xie B
，Wang HL
，Ji XW
... -
《Scientific Reports》
COVID-19 and the risk of acute cardiovascular diseases: a two-sample Mendelian randomization study.
Evidence suggests that coronavirus disease 2019 (COVID-19) is associated with the risk of cardiovascular diseases (CVDs). However, the results are inconsistent, and the causality remains to be established. We aimed to investigate the potential causal relationship between COVID-19 and CVDs by using two-sample Mendelian randomization (MR) analysis.
Summary-level data for COVID-19 and CVDs including myocarditis, heart failure (HF), acute myocardial infarction (AMI), arrhythmia and venous thromboembolism (VTE) were obtained from the IEU OpenGWAS project, a public genome-wide association study (GWAS). Single nucleotide polymorphisms (SNPs) were used as instrumental variables. Five complementary MR methods were performed, including inverse variance weighted (IVW), MR-Egger, weighted median, weighted mode and simple mode methods. IVW method was considered as the primary approach. Besides, sensitivity analyses, including Cochran's Q test, MR-Egger intercept test, and leave-one-out analysis, were performed to evaluate the robustness of the results.
According to the IVW results, our MR study indicated that genetically predicted COVID-19 was not causally connected with the risk of CVDs [myocarditis: odds ratio (OR) = 1.407, 95% confidence interval (CI) = 0.761-2.602, p-value = 0.277; HF: OR = 1.180, 95% CI = 0.980-1.420, p-value = 0.080; AMI: OR = 1.002, 95% CI = 0.998-1.005, p-value = 0.241; arrhythmia: OR = 0.865, 95% CI = 0.717-1.044, p-value = 0.132; VTE: OR = 1.013, 95% CI = 0.997-1.028, p-value = 0.115]. The supplementary MR methods showed similar results. Sensitivity analyses suggested that the causal estimates were robust.
This two-sample MR analysis did not provide sufficient evidence for a causal relationship between COVID-19 and the risk of acute CVDs, which may provide new insights into the prevention of acute CVDs in COVID-19 patients.
Li Y
，Yang D
，Kang J
，Cao Y
，Cui L
，Liu F
... -
《BMC Cardiovascular Disorders》
[Genetic Causation Analysis of Hyperandrogenemia Testing Indicators and Preeclampsia].
Some epidemiological studies have shown that pregnant women who develop preeclampsia (PE) have elevated levels of testosterone in their maternal plasma compared to women with normal blood pressure during pregnancy, revealing a potential association between hyperandrogenism in women and PE. To explore the causal relationship between hyperandrogenism and PE, this study selected total testosterone (TT), bioavailable testosterone (BIOT), and sex hormone binding globulin (SHBG) as exposure factors and PE and chronic hypertension with superimposed PE as disease outcomes. Two-sample Mendelian randomization (MR) analyses were used to genetically dissect the causal relationships between the three exposure factors (TT, BIOT, and SHBG) and the outcomes of PE and chronic hypertension with superimposed PE.
Two independent genome-wide association study (GWAS) databases were used for the two-sample MR analysis. In the GWAS data of female participants from the UK Biobank cohort, single nucleotide polymorphisms (SNPs) associated with TT, BIOT, and SHBG were analyzed, involving 230454, 188507, and 188908 samples, respectively. GWAS data on PE and chronic hypertension with superimposed PE from the Finnish database were used to calculate SNP, involving 3556 PE cases and 114735 controls, as well as 38 cases of chronic hypertension with superimposed PE and 114735 controls. To meet the assumptions of instrumental relevance and independence in MR analysis, SNPs associated with exposure were identified at the genome-wide level (P<5.0×10-8), and those in linkage disequilibrium interference were excluded based on clustering thresholds of R 2<0.001 and an allele distance greater than 10000 kb. Known confounding factors, including previous PE, chronic kidney disease, chronic hypertension, diabetes, systemic lupus erythematosus, or antiphospholipid syndrome, were also identified and the relevant SNPs were removed. Finally, we extracted the outcome data based on the exposure-related SNPs in the outcome GWAS, integrating exposure and outcome data, and removing palindromic sequences. Five genetic causal analysis methods, including inverse variance-weighted method (IVW), MR-Egger regression, weighted median method, simple mode method, and weighted mode method, were used to infer causal relationships. In the IVW, it was assumed that the selected SNPs satisfied the three assumptions and provided the most ideal estimate of the effect. IVW was consequently used as the primary analysis method in this study. Considering the potential heterogeneity among the instrumental variables, random-effects IVW was used for MR analysis. The results were interpreted using odds ratios (OR) and the corresponding 95% confidence interval (CI) to explain the impact of exposure factors on PE and chronic hypertension with superimposed PE. If the CI did not include 1 and had a P value less than 0.05, the difference was considered statistically significant. Sensitivity analysis was conducted to assess heterogeneity and pleiotropy. Heterogeneity was examined using Cochran's Q test, and pleiotropy was assessed using MR-Egger intercept analysis. Additionally, leave-one-out analysis was conducted to examine whether individual SNPs were driving the causal associations. To further validate the findings, MR analyses were performed using the same methods and outcome variables, but with different exposure factors, including waist-to-hip ratio adjusted for BMI (WHRadjBMI) and 25-hydroxyvitamin D levels, with MR results for WHRadjBMI and PE serving as the positive controls and MR results for 25-hydroxyvitamin D levels and PE as the negative controls.
According to the criteria for selecting genetic instrumental variables, 186, 127, and 262 SNPs were identified as genetic instrumental variables significantly associated with testosterone indicators TT, BIOT, and SHBG. MR analysis did not find a causal relationship between the TT, BIOT, and SHBG levels and the risk of developing PE and chronic hypertension with superimposed PE. The IVW method predicted that genetically predicted TT (OR [95% CI]=1.018 [0.897-1.156], P=0.78), BIOT (OR [95% CI]=1.11 [0.874-1.408], P=0.392), and SHBG (OR [95% CI]=0.855 [0.659-1.109], P=0.239) were not associated with PE. Similarly, genetically predicted TT (OR [95% CI]=1.222 [0.548-2.722], P=0.624), BIOT (OR [95% CI]=1.066 [0.242-4.695], P=0.933), and SHBG (OR [95% CI]=0.529 [0.119-2.343], P=0.402) were not significantly associated with chronic hypertension with superimposed PE. Additionally, MR analysis using the MR-Egger method, weighted median method, simple mode method, and weighted mode method yielded consistent results, indicating no significant causal relationship between elevated testosterone levels and PE or chronic hypertension with superimposed PE. Heterogeneity was observed for SHBG in the analysis with PE (Cochran's Q test, P=0.01), and pleiotropy was detected for BIOT in the analysis with PE (MR-Egger intercept analysis, P=0.014), suggesting that the instrumental variables did not affect PE through BIOT. Other instrumental variables did not show significant heterogeneity or pleiotropy. Leave-one-out analysis confirmed that the results of the MR analysis were not driven by individual instrumental variables. Consistent with previous MR studies, the results of the control MR analyses using WHRadjBMI and 25-hydroxyvitamin D levels supported the accuracy of the MR analysis approach and the methods used in this study.
The MR analysis results suggest that current genetic evidence does not support a causal relationship between TT, BIOT, and SHBG levels and the development of PE and chronic hypertension with superimposed PE. This study suggests that elevated testosterone may be a risk factor for PE but not a direct cause.
Lin C
，Chen J
，Zhao X
《-》
ResearchGate
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钛学术
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