
Combined Risk Factors Associated With Greater Risk of Late-Onset Parkinson Disease
An analysis of more than 311,000 UK Biobank participants identified 13 pairs and 14 triplets of risk factors with significant additive interactions for late-onset Parkinson disease, with several potentially modifiable factors emerging as targets for prevention.
Combinations of clinical, genetic, lifestyle, and other risk factors were associated with substantially greater risk of incident late-onset Parkinson disease (LOPD) than individual factors alone, according to findings from a prospective cohort study published in Movement Disorders. All told, investigators identified 13 pairs and 14 triplets of risk factors with significant positive additive interactions, with the magnitude of association increasing with the number of co-occurring exposures.1
Using data from the UK Biobank, researchers evaluated 311,261 participants aged 50 years or older who were free of PD at baseline. Participants were followed for up to 15 years, during which 2,769 individuals developed incident LOPD. Investigators initially assessed 65 candidate risk factors using multivariable Cox proportional hazards models, identifying 18 factors independently associated with LOPD that were subsequently evaluated in combinations of 2 or 3 exposures.
Study author Andrea Quattrone, MD, PhD, professor of neurology at Magna Graecia University in Catanzaro, Italy, and colleagues sought to address limitations of traditional risk-factor analyses, which generally examine exposures individually. Because multiple environmental, clinical, genetic, and lifestyle factors can coexist in an individual, the study assessed whether combinations of these exposures could produce effects beyond those expected from their individual associations with PD risk.
Combined Exposures Show Greater Risk
Across the 18 independently associated risk factors, the mean hazard ratio (HR) for individual exposures was 1.43. When evaluated jointly, 13 pairs demonstrated significant positive additive interaction, with a mean HR of 2.00, while 14 triplets showed significant positive additive interaction, with a mean HR of 4.21.1
The findings indicated that the increased risk associated with multiple exposures was not simply equivalent to the effects of each individual factor considered separately. Instead, several combinations produced an excess risk consistent with additive interaction, suggesting that the presence of one exposure may amplify the effect of another.
The association also increased according to the number of coexisting risk factors. Across the identified exposure combinations, the mean incidence rate of LOPD increased from 90.4 cases per 100,000 person-years among individuals exposed to individual risk factors to 118.8 cases per 100,000 person-years among those exposed to additive pairs and 247.3 cases per 100,000 person-years among those exposed to additive triplets.
Although some combinations were relatively uncommon, the number of individuals exposed to these profiles remained substantial, with approximately 19,400 individuals represented across additive pairs and 3,536 across triplets. Investigators said these findings suggest that clinically relevant combinations of risk factors are not rare in the general population.
Modifiable Factors Emerge as Potential Prevention Targets
The study also examined the contribution of potentially modifiable exposures within the higher-risk combinations. Several factors were associated with particularly elevated risk when occurring alongside other clinical, cognitive, or genetic exposures.1
Among the highest-risk combinations, loneliness was represented in the highest-risk pairs, while low handgrip strength, epilepsy, hearing loss, and diabetes were represented in the highest-risk triplets. Three pairs had HRs of at least 2.53, while 4 triplets had HRs of at least 5.28.
The investigators further examined what happened when potentially modifiable exposures were removed from these combinations. Removing modifiable factors was associated with a 30% reduction in mean HRs for additive pairs and a 49% reduction for additive triplets (P = .001). At the population level, removal of modifiable risk factors was estimated to correspond to a 34.4% reduction in LOPD incidence.
These findings suggested that certain modifiable exposures may contribute disproportionately to PD risk when they occur alongside other susceptibility factors. The authors emphasized that identifying such combinations could help move risk assessment beyond isolated exposures and toward more individualized prevention strategies.
Implications for PD Risk Stratification
The findings support a multifactorial model of LOPD in which genetic susceptibility and potentially modifiable exposures may interact to influence disease risk. Investigators noted that most individual risk factors had relatively modest effect sizes, with HRs generally below 1.50, potentially explaining why analyses limited to individual exposures may not fully capture real-world risk.1
The study's additive interaction approach may therefore provide a framework for identifying individuals with clusters of exposures that place them at substantially higher risk. Such profiles could ultimately help inform targeted prevention strategies, particularly when they contain factors that may be modified.
However, the authors cautioned that the specific composition and prevalence of these combinations may differ across populations. External validation and population-specific calibration will be necessary before these risk profiles can be applied broadly in clinical practice.
The study also had limitations inherent to its observational design and use of UK Biobank data. The findings demonstrate associations between combinations of exposures and incident LOPD but do not establish causality. In addition, differences in the prevalence of genetic, clinical, and environmental factors across populations may limit generalizability.
Overall, the findings suggest that evaluating combinations of risk factors may improve understanding of LOPD risk beyond traditional single-factor models. The investigators concluded that integrating individual risk factors with high-risk additive exposure profiles could improve risk stratification and help identify potentially actionable targets for PD prevention.

















