Abstract

Parkinson's disease (PD) is a highly age-related disorder, where common genetic risk variants affect both disease risk and age at onset. A statistical approach that integrates these effects across all common variants may be clinically useful for individual risk stratification. A polygenic hazard score methodology, leveraging a time-to-event framework, has recently been successfully applied in other age-related disorders. We aimed to develop and validate a polygenic hazard score model in sporadic PD. Using a Cox regression framework, we modeled the polygenic hazard score in a training data set of 11,693 PD patients and 9841 controls. The score was then validated in an independent test data set of 5112 PD patients and 5372 controls and a small single-study sample of 360 patients and 160 controls. A polygenic hazard score predicts the onset of PD with a hazard ratio of 3.78 (95% confidence interval 3.49-4.10) when comparing the highest to the lowest risk decile. Combined with epidemiological data on incidence rate, we apply the score to estimate genetically stratified instantaneous PD risk across age groups. We demonstrate the feasibility of a polygenic hazard approach in PD, integrating the genetic effects on disease risk and age at onset in a single model. In combination with other predictive biomarkers, the approach may hold promise for risk stratification in future clinical trials of disease-modifying therapies, which aim at postponing the onset of PD. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Highlights

  • We have shown that a polygenic hazard score (PHS) generated by our Cox regression method can be improved by the incorporation of genome-wide association studies (GWAS)-nominated single-nucleotide polymorphisms (SNPs) in an additional step where the optimal SNP set is selected using least absolute shrinkage and selection operator (LASSO)-regularized regression.[22]

  • We show for the first time that the PHS method can be used to estimate PHS-adjusted Parkinson’s disease (PD) risk

  • We focused our analysis on the age range from 40 to 75, demonstrating that a 71 SNP PHS model trained on the reference data set successfully predicts empirical age at PD onset in the independent test data

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Summary

Objectives

We aimed to develop and validate a polygenic hazard score model in sporadic PD

Methods
Results
Conclusion
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