The association between telomere length and blood lipids: a bidirectional two-sample Mendelian randomization study.

Abstract

Observational studies suggest an association between telomere length (TL) and blood lipid (BL) levels. Nevertheless, the causal connections between these two traits remain unclear. We aimed to elucidate whether genetically predicted TL is associated with BL levels via Mendelian randomization (MR) and vice versa. We obtained genetic instruments associated with TL, triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A-1 (ApoA-1) and apolipoprotein B (ApoB) from large-scale genome-wide association studies (GWASs). The causal relationships between TL and BL were investigated via bidirectional MR, multivariable MR and mediation analysis methods. The inverse variance weighted (IVW) method was employed as the principal methodology, complemented by several other estimators to enhance the robustness of the analysis. In the forward MR analyses, we identified significant positive correlation between genetically predicted TL and the levels of TG (β=0.04, 95% confidence interval [CI]: 0.01 to 0.06, p = 0.003). In the reverse MR analysis, TG (β=0.02, 95% CI: 0.01 to 0.03, p = 0.004), LDL-C (β=0.03, 95% CI: 0.01 to 0.04, p = 0.001) and ApoB (β=0.03, 95% CI: 0.01 to 0.04, p = 9.71×10-5) were significantly positively associated with TL, although this relationship was not observed in the multivariate MR analysis. The mediation analysis via two-step MR showed no significant mediation effects acting through obesity-related phenotypes in analysis of TL with TG, while the effect of LDL-C on TL was partially mediated by body mass index (BMI) in the reverse direction, with mediated proportion of 12.83% (95% CI: 0.62% to 25.04%). Our study indicated that longer TL were associated with higher TG levels, while conversely, higher TG, LDL-C, and ApoB levels predicted longer TL, with BMI partially mediating these effects. Our findings present valuable insights into the development of preventive strategies and interventions that specifically target TL-related aging and age-related diseases.