The causal relationship between immune cells and heart failure risk and the mediating role of serum metabolites: A Mendelian randomization study
- VernacularTitle:免疫细胞与心力衰竭风险的因果关系及血清代谢物中介作用的孟德尔随机化研究
- Author:
Yun ZHU
1
,
2
;
Jiaming WEI
2
;
Ruifang LIN
2
;
Yongjun LIU
2
;
Yue LIU
2
;
Guohua ZHANG
3
;
Zhihua GUO
2
,
3
,
4
,
5
Author Information
1. The Second People's Hospital of Yichang, Yichang, 443000, Hubei, P. R. China
2. School of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, 410208, P. R. China
3. First Clinical College of Chinese Medicine, Hunan University of Chinese Medicine, Changsha, 410208, P. R. China
4. Hunan Key Laboratory of Colleges and Universities of Intelligent Traditional Chinese Medicine Diagnosis and Preventive Treatment of Chronic Diseases of Hunan Universities of Chinese Medicine, Changsha, 410208, P. R. China
5. Internet+TCM Diagnosis and Treatment of Chronic Diseases and Intelligent Application of Health Care Joint Postgraduate Training Base, Changsha, 410208, P. R. China
- Publication Type:Journal Article
- Keywords:
Immune cells;
serum metabolites;
heart failure;
Mendelian randomization;
mediating role;
causal relationship
- From:
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery
2026;33(01):115-121
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the causal relationship between immune cells and heart failure (HF), and the mediating role of serum metabolites, in order to identify potential biomarkers and therapeutic targets. Methods We employed a two-sample Mendelian randomization (MR) analysis method based on genome-wide association study (GWAS) data, analyzing the direct and indirect effects of 731 types of immune cells and 1 400 metabolites on HF. We selected valid instrumental variables and conducted statistical analyses using R software. The primary analysis was performed using the inverse variance weighted method, supplemented by MR-Egger analysis and weighted median method. The stability of the results was assessed through tests such as Cochran’s Q test. Results Our research found a negative causal relationship between PD-L1 on CD14−CD16+ and HF. Sensitivity analysis supported this result. The reverse MR analysis did not find an effect of HF on PD-L1 on CD14−CD16+, indicating that PD-L1 on CD14−CD16+ might play a unidirectional role in reducing the risk of HF. Further mediation MR analysis showed that PD-L1 on CD14−CD16+ might influence the risk of HF onset by regulating the levels of sphingomyelin (d17:1/14:0, d16:1/15:0), with a mediation effect ratio of 6.7%. Conclusion PD-L1 on CD14−CD16+ may reduce the risk of HF by elevating the levels of sphingomyelin (d17:1/14:0, d16:1/15:0), which provides a new perspective for understanding the pathogenesis of HF.
