Systematic analysis of relationships between plasma branched-chain amino acid concentrations and cardiometabolic parameters: an association and Mendelian randomization study

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.

The Application of Mendelian Randomization in Cardiovascular Disease Risk Prediction: Current Status and Future Prospects

Cardiovascular disease (CVD), a leading cause of death and disability worldwide, and is associated with a wide range of risk factors, and genetically associated conditions. While many CVDs are preventable and early detection alongside treatment can significantly mitigate complication risks, current prediction models for CVDs need enhancements for better accuracy. Mendelian randomization (MR) offers a novel approach for estimating the causal relationship between exposure and outcome by using genetic variation in quasi-experimental data. This method minimizes the impact of confounding variables by leveraging the random allocation of genes during gamete formation, thereby facilitating the integration of new predictors into risk prediction models to refine the accuracy of prediction. In this review, we delve into the theory behind MR, as well as the strengths, applications, and limitations behind this emerging technology. A particular focus will be placed on MR application to CVD, and integration into CVD prediction frameworks. We conclude by discussing the inclusion of various populations and by offering insights into potential areas for future research and refinement.

Duality of Branched-Chain Amino Acids in Chronic Cardiovascular Disease: Potential Biomarkers versus Active Pathophysiological Promoters

Branched-chain amino acids (BCAAs), comprising leucine (Leu), isoleucine (Ile), and valine (Val), are essential nutrients vital for protein synthesis and metabolic regulation via specialized signaling networks. Their association with cardiovascular diseases (CVDs) has become a focal point of scientific debate, with emerging evidence suggesting both beneficial and detrimental roles. This review aims to dissect the multifaceted relationship between BCAAs and cardiovascular health, exploring the molecular mechanisms and clinical implications. Elevated BCAA levels have also been linked to insulin resistance (IR), type 2 diabetes mellitus (T2DM), inflammation, and dyslipidemia, which are well-established risk factors for CVD. Central to these processes are key pathways such as mammalian target of rapamycin (mTOR) signaling, nuclear factor kappa-light-chain-enhancer of activate B cells (NF-κB)-mediated inflammation, and oxidative stress. Additionally, the interplay between BCAA metabolism and gut microbiota, particularly the production of metabolites like trimethylamine-N-oxide (TMAO), adds another layer of complexity. Contrarily, some studies propose that BCAAs may have cardioprotective effects under certain conditions, contributing to muscle maintenance and metabolic health. This review critically evaluates the evidence, addressing the biological basis and signal transduction mechanism, and also discusses the potential for BCAAs to act as biomarkers versus active mediators of cardiovascular pathology. By presenting a balanced analysis, this review seeks to clarify the contentious roles of BCAAs in CVD, providing a foundation for future research and therapeutic strategies required because of the rising prevalence, incidence, and total burden of CVDs.

Branched-chain amino acids and type 2 diabetes: a bidirectional Mendelian randomization analysis

OBJECTIVE

Genetic studies have suggested that the branched-chain amino acids (BCAAs) valine, leucine, and isoleucine have a causal association with type 2 diabetes (T2D). However, inferences are based on a limited number of genetic loci associated with BCAAs.

METHODS

Instrumental variables (IVs) for each BCAA were constructed and validated using large well-powered data sets and their association with T2D was tested using a two-sample inverse-variance weighted Mendelian randomization approach. Sensitivity analyses were performed to ensure the accuracy of the findings. A reverse association was assessed using instrumental variables for T2D.

RESULTS

Estimated effect sizes between BCAA IVs and T2D, excluding outliers, were as follows: valine (β = 0.14 change in log-odds per SD change in valine, 95% CI: -0.06 to 0.33, p = 0.17), leucine (β = 0.15, 95% CI: -0.02 to 0.32, p = 0.09), and isoleucine (β = 0.13, 95% CI: -0.08 to 0.34, p = 0.24). In contrast, T2D IVs were positively associated with each BCAA, i.e., valine (β = 0.08 per SD change in levels per log-odds change in T2D, 95% CI: 0.05 to 0.10, p = 1.8 × 10-9 ), leucine (β = 0.06, 95% CI: 0.04 to 0.09, p = 4.5 × 10-8 ), and isoleucine (β = 0.06, 95% CI: 0.04 to 0.08, p = 2.8 × 10-8 ).

CONCLUSIONS

These data suggest that the BCAAs are not mediators of T2D risk but are biomarkers of diabetes.

Effect of genetically determined BCAA levels on cardiovascular diseases and their risk factors: A Mendelian randomization study

BACKGROUND AND AIMS

Observational studies have demonstrated that serum branched-chain amino acids (BCAAs) are associated with the risk of various cardiovascular diseases (CVDs) and their risk factors. However, the causal effect is unclear. The aim of this study was to investigate the effect of genetically determined BCAA levels on CVDs and their risk factors using Mendelian randomization (MR).

METHODS AND RESULTS

We performed univariable and multivariable MR analyses using summary-level data from multiple GWASs and the FinnGen consortium to investigate the association between BCAA levels and the risk of CVDs (myocardial infarction, ischemic stroke, and intracerebral hemorrhage) and their risk factors (atrial fibrillation, hypertension, heart failure, and valvular heart disease). We used the random-effects IVW approach as the primary statistical method and incorporated MR estimates from different data sources using the fixed-effects model. We found genetically determined total and individual BCAA levels and a high risk of hypertension. However, there is no evidence of a causal relationship between BCAA levels and 3 cardiovascular diseases and other their risk factors. The odds of hypertension increased per 1-SD increase in BCAA levels (OR = 1.02 95% CI: 1.01, 1.04; P = 0.005), valine (OR = 1.02 95% CI: 1.01, 1.03; P<0.0001), leucine (OR = 1.02 95% CI: 1.01, 1.04; P＜0.01), and isoleucine (OR = 1.02 95% CI: 1.01, 1.03; P < 0.0001). This result was also significant in the multivariable MR.

CONCLUSIONS

This MR study suggests that total and individual BCAA levels could be associated with a high risk of hypertension.