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Genetic landscape of Parkinson's disease in the Personalized Parkinson Project cohort

Lüth, T.; Klein, C.; Helmich, R. C.; Brüggemann, N.; Hrir, S.; Kuiperij, H. B.; Gorgogietas, V.; Gomes Fernandes, S. B.; Prasuhn, J.; May, P.; Outeiro, T. F.; Steidel, K.; Landoulsi, Z.; Kleinz, T.; Schaake, S.; Much, C.; Krüger, R.; Verbeek, M. M.; Bloem, B. R.; van de Warrenburg, B. P.; Trinh, J.

2026-03-23 neurology
10.64898/2026.03.16.26348127 medRxiv
Show abstract

BackgroundParkinsons disease (PD) is a multifactorial neurodegenerative disorder shaped by, amongst others, high-impact variants and common polygenic factors. The Personalized Parkinson Project (PPP) offers deep phenotyping and longitudinal follow-up of Dutch people with PD. Here, we characterize the genetic landscape and its interaction with lifestyle factors within PPP. MethodsWe utilized three complementary approaches in N=507 persons with PD: 1) short-read PD gene panel sequencing of eight PD genes, 2) genome-wide genotyping array, and 3) targeted long-read sequencing of the GBA1 gene. Additionally, we calculated the mitochondrial-function polygenic score (MGS). Associations between genetic factors, smoking status, and age at onset (AAO) were assessed using non-parametric tests, correlation analyses, and multiple regression models. ResultsGenetic screening of the participants revealed N=79 GBA1 ([~]15%), N=3 LRRK2, N=1 CHCHD2, N=1 SNCA variant carrier, and N=9 heterozygous PRKN/PINK1 variants. We also observed an interaction between MGS and smoking: MGS was associated with earlier AAO in non-smokers in persons with iPD (N=414, {beta}=-1.87, p=0.038). ConclusionOur findings corroborate previously reported frequencies of variants in PD-associated genes in European populations, and suggest a potential association between smoking and a mitochondrial dysfunction signature in PD. Thus, even in persons without rare variants (iPD subgroup), complex genetic contributions remained relevant. Our study supports future downstream stratification and personalized medicine approaches with high-impact variants and polygenic risk scores.

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