This study explored the association between PRSMetS and the risk of MetS and investigated the impact of lifestyle risk factors on MetS risk in the Korean general population. The main findings were as follows: (i) individuals with high PRSMetS had a 1.31-fold increased risk of MetS; (ii) regardless of PRSMetS level, those with poorer lifestyles showed a higher prevalence of MetS in a dose-dependent manner; and (iii) individuals with high PRSMetS who maintained ideal or intermediate lifestyles had a lower MetS risk compared to those with low PRSMetS and poor lifestyles. These results highlight the significant impact of both genetic predisposition and lifestyle on MetS risk, underscoring the importance of maintaining an ideal lifestyle for MetS prevention, even in those with high genetic susceptibility among Korean adults.
MetS is a complex metabolic disorder characterised by interrelated physiological, biochemical, and clinical factors, such as insulin resistance, visceral fat accumulation, endothelial dysfunction, and dyslipidaemia32. The prevalence of MetS has risen from 27.1% in 2001 to 33.2% in 202033. This has been attributed to a combination of clinical factors and lifestyle changes34. A study in Australian adults linked a Western dietary pattern (rich in meat, refined grains, and processed foods) to higher MetS risk, insulin resistance, abnormal β-cell function, and reduced insulin sensitivity. In contrast, a healthy dietary pattern (rich in fruits, vegetables, and whole grains) showed protective effects35. The Western diet al.so promotes pro-inflammatory cytokines36causing inflammation that leads to LDL accumulation in arterial walls and endothelial dysfunction, a major factor in cardiovascular diseases37. Alcohol intake also exacerbates MetS by raising triglycerides and blood pressure38. Conversely, PA has demonstrated a protective effect against MetS. Korean adults who engaged in moderate PA, walking, or flexibility exercises had significantly lower MetS prevalence than those who were inactive39. Regular exercise reduces body fat, increases muscle mass, and improves insulin sensitivity, metabolic health, and vascular function; thus, lowering the risks of cardiovascular and cerebrovascular diseases40. Overall, the roles of lifestyle factors, including diet, alcohol, and PA, are crucial in the risk of developing MetS.
Evidence underscores the importance of adopting healthy lifestyle habits to lower mortality rates and enhance metabolic and cardiovascular health outcomes. Among patients with ischemic heart disease, smoking was associated with elevated mortality rates, whereas vigorous PA significantly reduced mortality risk. Adherence to the AHA Step 2 diet was associated with lower mortality rates41. In this regard, the AHA proposed LS7 in 2010, defining ideal cardiovascular health based on seven modifiable risk factors through lifestyle changes23,42. This framework was continuously refined and, in 2022, expanded into Life’s Essential 8, comprising diet, PA, nicotine exposure, sleep health, BMI, blood lipids, blood glucose, and BP43. Several studies have confirmed a strong and stepwise inverse association between these metrics and total cardiovascular disease, cardiovascular mortality, and all-cause mortality43. Assessing cardiovascular risks, including MetS, and implementing active management strategies in adults remain essential, as lifestyle modifications significantly influence the prevention and management of MetS and cardiovascular diseases.
PRS, derived from the genome-wide association study data, evaluates disease risk based on genetic variants within an individual’s genome44. Higher scores generally indicate an elevated risk44. For coronary artery disease, combining multiple genomic risk scores (GRS) into a metaGRS significantly enhances risk prediction compared to individual GRS45,46. The metaGRS also achieved a superior predictive ability compared to traditional risk factors like BMI, diabetes, hypertension, smoking, family history of heart disease, and high cholesterol46. These findings highlight the value of integrating metaGRS with traditional risk factors for improved prediction. Building on this concept, the present study utilised the PRSMetS that incorporates individual components of the genetic predisposition to various metabolic diseases.
Recent studies have reported the utility of integrating genetic risk with lifestyle interventions. In American adults, individuals with high PRS and ideal LS7 scores lived 20.2 years longer without coronary heart disease than those with low LS7 scores28. Khera et al. demonstrated that low genetic risk paired with unhealthy lifestyles led to higher coronary event rates than healthy lifestyles17. Consistent with these findings, our study showed that among individuals with high PRSMetS, lifestyle factors substantially modified the risk of metabolic syndrome. Specifically, individuals with a poor lifestyle in the high PRSMetS group had a 4.52-fold higher risk of MetS (95% CI: 1.66–12.29) compared to those with an ideal lifestyle in the same genetic risk group. Notably, in the low PRSMetS group, poor lifestyle habits were also associated with a 7.52-fold increased risk of MetS (95% CI: 5.89–9.61). These findings highlight that lifestyle factors can strongly influence MetS risk, regardless of an individual’s genetic risk level.
Our study used the PRSMetS for eight individual metabolic phenotypes, designed to optimally predict ASCVD31. Individuals with high PRSMetS had a 1.31-fold increased risk of MetS (95% CI: 1.03–1.66), consistent with previous reports showing hazard ratios of approximately 1.10–1.20 per standard deviation increase in PRSMetS28. Importantly, an ideal or intermediate lifestyle in the high PRSMetS group reduced MetS risk by 75% and 43%, respectively, compared to having a poor lifestyle with low PRSMetS. This suggests that, while genetic risk contributes to MetS susceptibility, its effects can be substantially mitigated by maintaining healthy lifestyle habits. Using PRSMetS to assess genetic risk, alongside promoting regular PA, smoking cessation, and healthy eating, is expected to reduce both MetS and ASCVD risks. These findings underscore the importance of integrating genetic risk assessments with lifestyle interventions in clinical and public health strategies for MetS prevention, providing valuable insights for personalised health strategies and public health policy development. It also suggests that while genetic risk is an important consideration, public health interventions should prioritize modifiable lifestyle factors to reduce MetS risk. Clinicians should emphasize dietary counseling, increased physical activity, and smoking cessation, even in individuals with high genetic risk.
This study had several limitations. Firstly, the data from the GENIE cohort were collected through a cross-sectional study conducted within a limited time frame. Although associations were identified, determining causal relationships was not possible. Secondly, this study relied on self-reported data, which could have introduced inaccuracies in measuring lifestyle risk factors. Thirdly, the thresholds for lifestyle risk factors were based on the criteria adopted by the GENIE cohort, potentially limiting the generalisability of the findings to other settings or populations. Fourthly, although the present study was conducted in a general population setting, our cohort included individuals with at least one ASCVD risk factor. Therefore, caution is warranted when extrapolating these findings to populations without ASCVD risk factors or younger age groups. Fifthly, a potential collider bias could have been introduced by selecting individuals with ASCVD risk factors. Therefore, our findings should be validated in future studies using general population cohorts without ASCVD risk factors to confirm the robustness and generalizability of our results. Finally, certain indicators were difficult to measure as continuous values. Given the nonlinear relationship between some indicators and health, applying a ranking score system for each indicator, such as a scoring method ranging from 0 to 9 with categories like ideal, intermediate, and poor, would be more appropriate43. Although somewhat subjective, this method is considered effective for capturing individual differences and tracking changes in cardiovascular health over time43.
In conclusion, this cohort study of Korean adults suggested that individuals with high PRSMetS were associated with an increased risk of MetS. However, maintaining healthy lifestyle habits, including regular PA, a healthy diet, and smoking cessation, reduced the risk of MetS, even among individuals with high PRSMetS. These findings highlight the need for personalised health strategies that utilise PRSMetS to identify high-risk groups for MetS and alleviate the impact of genetic predisposition on MetS development.