Psychosocial Well-being and Genetic Predisposition Shape Responsiveness to Lifestyle Coaching: Insights from a Risk-Stratified Intervention Trial

Background: Lifestyle modifications are known to improve cardiometabolic outcomes, however, their effectiveness in modulating metabolic signatures and interacting with genetic susceptibility and behavioral determinants of health remains incompletely understood. Psychosocial well-being may both reflect underlying genetic predisposition and influence responsiveness to lifestyle interventions, yet this interplay remains underexplored, thus elucidating these relationships is essential for advancing personalized and precision health approaches. Methods: This 10-week randomized controlled trial (RCT) assessed the impact of lifestyle coaching on cardiometabolic health among working-age adults at elevated risk (N = 709 screened). Risk stratification was based on apolipoprotein B to apolipoprotein A1 (ApoB/ApoA1) ratio. Participants in the highest risk category (~15%, n = 104) were randomized to either personal coaching (intervention: n = 53; control: n = 51), while those at medium risk (~30%, n = 213) were randomized to group coaching (intervention: n = 107; control: n = 106) branch. Low-risk individuals (n = 394) were excluded after baseline. Interventions followed a standardized curriculum and included personalized or group-based behavioral guidance targeting diet, physical activity, and stress management. Statistical analyses were performed using generalized estimation equations (GEE) for primary analyses. Results: At baseline, higher polygenic risk scores (PRS) for body mass index (BMI) associated with greater psychosocial burden, higher adiposity, and more adverse metabolic profiles (FDR < 0.05), including elevated high-sensitivity C-reactive protein (hs-CRP), uric acid, and alanine aminotransferase (ALT) levels. The 10-week lifestyle intervention did not yield major differential effects on cardiometabolic status between coaching modalities within different risk strata but did result in incremental improvements (FDR < 0.05) in psychosocial well-being. Participants with multidomain challenges showed the least responsiveness (FDR < 0.05) in adiposity and metabolic signatures compared with those with more favorable psychosocial profiles. In addition to psychosocial well-being, baseline cardiometabolic status (i.e., adiposity, blood pressure, biomarker profile) and polygenic risk predisposition for BMI and coronary heart disease (CHD) shaped (FDR < 0.05) intervention responsiveness, influencing adiposity and metabolic signature trajectories. Conclusions: These findings underscore the importance of personalized, multidimensional approaches to cardiometabolic health. Genetic risk together with psychosocial well-being shape both baseline status and potential for change and intervention responsiveness. Integrating and accounting both factors is essential for optimizing prevention strategies. Trial registration: ClinicalTrials.gov NCT04633876. Registration date: 18/11/2020.