Plasma metabolome mediates the causal relationship between immune cells and heart failure: a two-step bidirectional Mendelian randomization study - Li, Tan; Liu, Yanwei; Fu, Juncong; Huang, Langlang; Liu, Zhongyong (Frontiers in Cardiovascular Medicine, 2024)
Background Prior research has established a correlation between immune cell activity and heart failure (HF), but the causal nature of this relationship remains unclear. Furthermore, the potential influence of metabolite levels on this interaction has not been comprehensively explored. To address these gaps, we employed a bidirectional Mendelian randomization (MR) approach in two stages to examine whether metabolite levels can mediate the causal relationship between immune cells and HF. Methods Genetic information was extracted from summary data of genome-wide association studies. By applying a two-sample, two-step MR approach, we investigated the causal relationships among immune cells, metabolite levels, and HF, with a specific focus on the mediating effects of metabolites. Sensitivity analysis techniques were implemented to ensure the robustness of our findings. Results MR analysis revealed significant causal associations between HF and eight specific immune cells and five metabolites. Mediation analysis further identified three mediated relationships. Particularly, hexadecenedioate (C16:1-DC) mediated the influence of both the CD28- CD127- CD25++ CD8br%CD8br (mediation proportion: 19.2%) and CD28+ CD45RA + CD8br%T cells (mediation proportion: 11.9%) on HF. Additionally, the relationship between IgD + CD38br AC cells and HF appeared to be mediated by the phosphate to alanine ratio (mediation proportion: 16.3%). Sensitivity analyses validated that the used instrumental variables were free from pleiotropy and heterogeneity. Conclusion This study provides evidence that certain immune cell levels are associated with the risk of HF and that metabolite levels may mediate these relationships. However, to strengthen these findings, further validation using MR analyses with larger sample sizes is essential.