Circulating metabolites and coronary heart disease: a bidirectional Mendelian randomization.
Numerous studies have established a link between coronary heart disease and metabolic disorders. Yet, causal evidence connecting metabolites and Coronary Heart Disease (CHD) remains scarce. To address this, we performed a bidirectional Mendelian Randomization (MR) analysis investigating the causal relationship between blood metabolites and CHD.
Data were extracted from published genome-wide association studies (GWASs) on metabolite levels, focusing on 1,400 metabolite summary data as exposure measures. Primary analyses utilized the GWAS catalog database GCST90199698 (60,801 cases and 123,504 controls) and the FinnGen cohort (43,518 cases and 333,759 controls). The primary method used for causality analysis was random inverse variance weighting (IVW). Supplementary analyses included MR-Egger, weighted mode, and weighted median methods. Sensitivity analyses were conducted to evaluate heterogeneity and pleiotropy. Reverse MR analysis was employed to evaluate the direct impact of metabolites on coronary heart disease. Additionally, replication and meta-analysis were performed. We further conducted the Steiger test and colocalization analysis to reflect the causality deeply.
This study identified eight metabolites associated with lipids, amino acids and metabolite ratios that may influence CHD risk. Findings include: 1-oleoyl-2-arachidonoyl-GPE (18:1/20:4) levels: OR = 1.08; 95% CI 1.04-1.12; P = 8.21E-06; 1-palmitoyl-2-arachidonoyl-GPE (16:0/20:4) levels: OR = 1.07; 95% CI 1.04-1.11; P = 9.01E-05; Linoleoyl-arachidonoyl-glycerol (18:2/20:4): OR = 1.08; 95% CI 1.04-1.22; P = 0.0001; Glycocholenate sulfate: OR = 0.93; 95% CI 0.90-0.97; P = 0.0002; 1-stearoyl-2-arachidonoyl-GPE (OR = 1.07; 95% CI 1.03-1.11; P = 0.0002); N-acetylasparagine (OR = 1.04; 95% CI 1.02-1.07; P = 0.0030); Octadecenedioate (C18:1-DC) (OR = 0.93; 95% CI 0.90-0.97; P = 0.0004); Phosphate to linoleoyl-arachidonoyl-glycerol (18:2-20:4) (1) ratio (OR = 0.92; 95% CI 0.88-0.97; P = 0.0005).
The integration of genomics and metabolomics offers novel insights into the pathogenesis of CHD and holds significant importance for the screening and prevention of CHD.
Chen H
，Huang Y
，Wan G
，Zou X
... -
《Frontiers in Cardiovascular Medicine》
Assessing the causal relationship between metabolic biomarkers and coronary artery disease by Mendelian randomization studies.
The development of coronary artery disease (CAD) is significantly affected by impaired endocrine and metabolic status. Under this circumstance, improved prevention and treatment of CAD may result from knowing the connection between metabolites and CAD. This study aims to delve into the causal relationship between human metabolic biomarkers and CAD by using two-sample Mendelian randomization (MR). Utilizing two-sample bidirectional MR analysis, we assessed the correlation between 1400 blood metabolites and CAD, and the metabolites data from the CLSA, encompassing 8299 participants. Metabolite analysis identified 1091 plasma metabolites and 309 ratios as instrumental variables. To evaluate the causal link between metabolites and CAD, we analyzed three datasets: ebi-a-GCST005195 (547,261 European & East Asian samples), bbj-a-159 (29,319 East Asian CAD cases & 183,134 East Asian controls), and ebi-a-GCST005194 (296,525 European & East Asian samples). To estimate causal links, we utilized the IVW method. To conduct sensitivity analysis, we used MR-Egger, Weighted Median, and MR-PRESSO. Additionally, we employed MR-Egger interception and Cochran's Q statistic to assess potential heterogeneity and pleiotropy. What's more, replication and reverse analyses were performed to verify the reliability of the results and the causal order between metabolites and disease. Furthermore, we conducted a pathway analysis to identify potential metabolic pathways. 59 blood metabolites and 27 metabolite ratios nominally associated with CAD (P < 0.05) were identified by IVW analysis method. A total of four known blood metabolites, namely beta-hydroxyisovaleroylcarnitine (OR 1.06, 95% CI 1.027-1.094, FDR 0.07), 1-palmitoyl-2-arachidonoyl (OR 1.07, 95% CI 1.029-1.110, FDR 0.09), 1-stearoyl-2- docosahexaenoyl (OR 1.07, 95% CI 1.034-1.113, FDR 0.07) and Linoleoyl-arachidonoyl-glycerol, (OR 1.07, 95% CI 1.036-1.105, FDR 0.05), and two metabolite ratios, namely spermidine to N-acetylputrescine ratio (OR 0.94, 95% CI 0.903-0.972, FDR 0.09) and benzoate to linoleoyl-arachidonoyl-glycerol ratio (OR 0.87, 95% CI 0.879-0.962, FDR 0.07), were confirmed as having a significant causal relationship with CAD, after correcting for the FDR method (p < 0. 1). A causal relationship was found to be established between beta -hydroxyisovalerylcarnitine and CAD with the validation in other two datasets. Moreover, multiple metabolic pathways were discovered to be associated with CAD. Our study supports the hypothesis that metabolites have an impact on CAD by demonstrating a causal relationship between human metabolites and CAD. This study is important for new strategies for the prevention and treatment of CAD.
Yang K
，Li J
，Hui X
，Wang W
，Liu Y
... -
《Scientific Reports》
Causal relationships between gut microbiota, plasma metabolites, and HIV infection: insights from Mendelian randomization and mediation analysis.
Gut dysbiosis and metabolic abnormalities have been implicated in HIV infection. However, the exact causal relationships among the gut microbiota, metabolites, and HIV infection remain poorly understood. Our study involving Mendelian randomization (MR) and mediation analysis aims to unveil these causalities.
Genetic instrumental variables for the gut microbiota were retrieved from MiBioGen consortium (n = 18,340). Metabolism-related genetic variants were sourced from the CLSA cohort (n = 8299). GWAS summary statistics for symptomatic HIV infection were derived from the FinnGen study (n = 309,154), and the UK Biobank (n = 208,808). We performed the bidirectional two-sample MR to assess causalities with the inverse-variance weighted (IVW) method as the primary analysis. Moreover, we executed a mediation analysis using two-step MR methods.
Compared to the causal effects of HIV infection on gut microbiota (or metabolites), those of gut microbiota (or plasma metabolites) on the risk of HIV infection were more substantial. Phylum Proteobacteria (OR: 2.114, 95% CI 1.042-4.288, P = 0.038), and genus Ruminococcaceae UCG013 (OR: 2.127, 95% CI 1.080-4.191, P = 0.029) exhibited an adverse causal effect on HIV infection, whereas genus Clostridium sensu stricto 1(OR: 0.491, 95% CI 0.252-0.956, P = 0.036) and family Erysipelotrichaceae (OR: 0.399, 95% CI 0.193-0.827, P = 0.013) acted as significant protective factors for HIV. The salicyluric glucuronide level (OR = 2.233, 95% CI 1.120-4.453, P = 0.023) exhibited a considerably adverse causal effect on HIV infection. Conversely, the salicylate-to-citrate ratio (OR: 0.417, 95% CI 0.253-0.688, P = 0.001) was identified as a protective factor for HIV. We identified only one bidirectional causality between 1-palmitoyl-GPI and HIV infection. Mechanistically, genus Haemophilus mediated the causal effects of three phospholipids on HIV infection risk: 1-palmitoyl-GPI (mediation proportion = 33.7%, P = 0.018), 1-palmitoyl-2-arachidonoyl-GPI (mediation proportion = 18.3%, P = 0.019), and 1-linoleoyl-2-linolenoyl-GPC (mediation proportion = 20.3%, P = 0.0216). Additionally, 5-Dodecenoylcarnitine (C12:1) mediated the causal effect of genus Sellimonas on the risk of HIV infection (mediation proportion = 13.7%, P = 0.0348).
Our study revealed that gut microbiota and metabolites causally influence HIV infection risk more substantially than the reverse. We identified the bidirectional causality between 1-palmitoyl-GPI (16:0) and HIV infection, and elucidated four mediation relationships. These findings provide genetic insights into prediction, prevention, and personalized medicine of HIV infection.
Hu J
，Hu J
，Han D
《Virology Journal》
ResearchGate
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钛学术
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