Unraveling the Relationship Between Metabolic Syndrome and Epigenetic Aging: Evidence from NHANES 1999-2002 and Mendelian Randomization Study

Abstract Background Epigenetic age acceleration (EAA), reflecting the difference between biological and chronological age, serves as a novel biomarker for biological aging. Evidence shows metabolic syndrome (MetS) affects aging-related physiology, but the relationship between MetS and EAA remains unclear and warrants further investigation. Methods We analyzed data from 1,972 individuals in the National Health and Nutrition Examination Survey (NHANES) 1999-2002. EAAs were determined from the residuals of 13 epigenetic clocks regressed on chronological age. Weighted logistic regression, linear regression, and restricted cubic spline (RCS) models were utilized to investigate correlations between EAAs and MetS. Genetic correlation and two-sample Mendelian randomization (MR) analyses were performed to assess causal associations, complemented by summary-data-based MR (SMR) and bioinformatics analyses to explore gene regulation related to these associations. Results Participants with MetS exhibited significantly higher levels of EAAs, with DNA methylation PhenoAge acceleration (PhenoAgeAccel) increasing by 0.84 years (95% CI: 0.04-1.64), DNA methylation GrimAge acceleration (GrimAgeAccel) increasing by 0.83 years (95% CI: 0.32-1.34), and DNA methylation Grim2Age acceleration (GrimAge2Accel) increasing by 1.33 years (95% CI: 0.77-1.89). Elevated EAAs were significantly associated with increased risks of MetS, a correlation further substantiated by RCS models. Genetic correlation and MR analyses revealed significant associations between MetS and GrimAgeAccel. SMR identified shared risk genes between MetS and GrimAgeAccel. Subsequent bioinformatics analyses showed that these genes were associated with phenotypes such as glucose-dependent proinsulinotropic peptide levels. Conclusion We established a causal relationship between MetS and EAAs, indicating that MetS may provide new strategies for personalized aging prevention and intervention.