A LARGE cohort study using data from the UK Biobank has found that metabolic syndrome (MetS) is associated with an increased risk of developing Parkinson’s disease (PD), particularly in individuals with a high genetic predisposition. MetS is known to lead to a range of chronic diseases, including cardiovascular disease, cancer, and diabetes; however, previous research on MetS’s role in PD has yielded mixed results.
MetS was defined as the presence of three or more of the following symptoms: elevated waist circumference (≥102 cm for men; ≥88 cm for women), hypertension (systolic blood pressure ≥130 mmHg, diastolic blood pressure ≥85 mmHg, or use of antihypertensive medication), dyslipidaemia (high-density lipoprotein cholesterol <1.04 mmol/L for men, <1.30 mmol/L for women, or use of lipid-lowering medication), hypertriglyceridaemia (triglycerides ≥1.70 mmol/L or use of lipid-lowering medication), and hyperglycaemia (HbA1c ≥5.7%). PD diagnoses were identified through medical records.
A total of 467,200 PD-free adults aged 37–73 years were included in the study, 37.97% of whom had MetS. During follow-up, 3,222 individuals developed PD. The hazard ratio of PD of 1.39 for those with MetS, compared to those who were MetS-free. A dose–response relationship was observed, with risk increasing as the number of MetS components rose (HR: 1.14; 95% CI: 1.05–1.24; p for trend=0.001). Importantly, genetic susceptibility modified this association, as participants with both MetS and a high polygenic risk score for PD had the highest risk of developing PD (HR: 2.58; 95% CI: 2.12–3.14; p for interaction=0.002).
The authors concluded that MetS is a potentially modifiable risk factor for PD, particularly in genetically susceptible individuals. These results highlight the importance of early cardiometabolic risk management, not only for cardiovascular and metabolic health, but also for potentially reducing the future burden of neurological disease.
Reference
Zhang X et al. Metabolic syndrome and incidence of Parkinson disease: a community-based longitudinal study and meta-analysis. Neurology. 2025;105(6):e214033.
