This study investigates the association between metabolic syndrome (MetS) and epigenetic aging using two epigenetic clocks, GrimAge and DunedinPACE, in a Finnish population-based cohort. The study employs a twin design to control for genetic and familial confounding. Key findings include: 1. **Individual-Level Analysis**: Participants with MetS had significantly higher epigenetic aging measured by both GrimAge and DunedinPACE compared to those without MetS. Specifically, GrimAge age acceleration was 2.078 years higher in participants with MetS (p = 3.5E-5), and DunedinPACE estimated a 1.032 years/calendar year higher pace of aging (p = 4.8E-11). 2. **Within-Twin-Pair Analysis**: Within-twin-pair analyses suggested that genetics fully explains the association between MetS components and GrimAge, and partly explains the association with DunedinPACE. 3. **Replication Analysis**: Replication in two independent cohorts confirmed the association between MetS components and accelerated aging, independent of lifestyle factors. The within-twin-pair analyses in the replication cohorts further supported the role of genetics in mediating this association. 4. **Discussion**: The study demonstrates that MetS is associated with accelerated epigenetic aging, which may be explained by genetic factors. The findings highlight the importance of considering genetic confounding when studying the relationship between MetS and aging. 5. **Mechanisms**: The exact mechanisms by which MetS accelerates aging are not fully understood but are likely related to physiological responses to excess fat accumulation, such as increased oxidative stress and inflammation. 6. **Future Research**: Further research is needed to identify specific lifestyle factors that mediate or moderate the association between MetS and epigenetic aging, which could lead to interventions to slow down aging and prevent age-related diseases. The study's strengths include its use of a twin design to control for genetic and familial confounding, and its broad age range covering young adulthood to older individuals. However, the cross-sectional design limits the ability to draw causal conclusions.This study investigates the association between metabolic syndrome (MetS) and epigenetic aging using two epigenetic clocks, GrimAge and DunedinPACE, in a Finnish population-based cohort. The study employs a twin design to control for genetic and familial confounding. Key findings include: 1. **Individual-Level Analysis**: Participants with MetS had significantly higher epigenetic aging measured by both GrimAge and DunedinPACE compared to those without MetS. Specifically, GrimAge age acceleration was 2.078 years higher in participants with MetS (p = 3.5E-5), and DunedinPACE estimated a 1.032 years/calendar year higher pace of aging (p = 4.8E-11). 2. **Within-Twin-Pair Analysis**: Within-twin-pair analyses suggested that genetics fully explains the association between MetS components and GrimAge, and partly explains the association with DunedinPACE. 3. **Replication Analysis**: Replication in two independent cohorts confirmed the association between MetS components and accelerated aging, independent of lifestyle factors. The within-twin-pair analyses in the replication cohorts further supported the role of genetics in mediating this association. 4. **Discussion**: The study demonstrates that MetS is associated with accelerated epigenetic aging, which may be explained by genetic factors. The findings highlight the importance of considering genetic confounding when studying the relationship between MetS and aging. 5. **Mechanisms**: The exact mechanisms by which MetS accelerates aging are not fully understood but are likely related to physiological responses to excess fat accumulation, such as increased oxidative stress and inflammation. 6. **Future Research**: Further research is needed to identify specific lifestyle factors that mediate or moderate the association between MetS and epigenetic aging, which could lead to interventions to slow down aging and prevent age-related diseases. The study's strengths include its use of a twin design to control for genetic and familial confounding, and its broad age range covering young adulthood to older individuals. However, the cross-sectional design limits the ability to draw causal conclusions.