Abstract
BACKGROUND: Numerous observational studies have reported an association between frailty and atherosclerosis. However, the causal relationship between frailty and the occurrence of atherosclerosis in different anatomical sites remains unclear. we conducted a bidirectional Mendelian randomization (MR) study to evaluate the causal relationship between the frailty index (FI), and both systemic atherosclerosis and lipids. METHODS: We obtained summary statistics from large-scale genome-wide association studies (GWAS) of various phenotypes, including frailty (n = 175,226), coronary atherosclerosis (n = 56,685), cerebral atherosclerosis (n = 150,765), peripheral arterial disease (PAD) (n = 361,194), atherosclerosis at other sites (n = 17,832), LDL-C (n = 201,678), HDL-C (n = 77,409), and triglycerides (n = 78,700). The primary MR analysis employed the inverse variance weighted (IVW) method. Furthermore, to assess reverse causality, we employed inverse MR and multivariate MR analysis. RESULTS: Genetically predicted FI showed positive associations with the risk of coronary atherosclerosis (OR = 1.47, 95% CI 1.12-1.93) and cerebral atherosclerosis (OR = 1.99, 95% CI 1.05-3.78), with no significant association (p >0.05) applied to peripheral arterial disease and atherosclerosis at other sites. Genetically predicted FI was positively associated with the risk of triglycerides (OR = 1.31, 95% CI 1.08-1.59), negatively associated with the risk of LDL-C (OR = 0.87, 95% CI 0.78-0.97), and showed no significant association with the risk of HDL-C (p >0.05). Furthermore, both reverse MR and multivariate MR analyses demonstrated a correlation between systemic atherosclerosis, lipids, and increased FI. CONCLUSION: Our study elucidated that genetically predicted FI is associated with the risk of coronary atherosclerosis and cerebral atherosclerosis by the MR analysis method, and they have a bidirectional causal relationship. Moreover, genetically predicted FI was causally associated with triglyceride and LDL-C levels. Further understanding of this association is crucial for optimizing medical practice and care models specifically tailored to frail populations.