Longitudinal Assessment of DNA Repair Signature Trajectory in Prodromal versus Established Parkinson’s Disease

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by motor and non-motor symptoms. DNA repair dysfunction and integrated stress response (ISR) dysregulation have been suggested to be relevant in PD pathophysiology, but their role during the prodromal phase, before motor symptoms manifest, remains unclear. In this study, we analyzed longitudinal blood transcriptomic data from the Parkinson’s Progression Markers Initiative (PPMI) to investigate how DNA repair and ISR gene expression differ across healthy individuals, prodromal PD patients, and individuals with established PD. Using logistic regression classifiers, a type of supervised machine learning model, we found that DNA repair and ISR gene expression effectively distinguished prodromal PD from healthy individuals, with classification accuracy increasing over time and peaking at later prodromal stages. In contrast, these pathways failed to differentiate established PD from healthy controls, suggesting that DNA repair and ISR dysregulation play a more distinct role early in disease progression. Gene expression variability was high in prodromal PD at baseline but reduced over time, indicating a convergence in gene expression patterns as the disease advances. Notably, 50% of DNA repair genes and 74% of ISR genes exhibited nonlinear expression patterns, with an initial increase followed by a decline. This suggests a transient adaptive response that fades out as PD progresses. Feature importance analysis identified key genes, including ERCC6, PRIMPOL, NEIL2, and NTHL1, as important predictors of prodromal PD. These findings suggest that DNA repair and ISR dysregulation contribute to early-stage PD pathology and may serve as biomarkers for early disease detection and possible treatment avenues during the prodromal phase. This study highlights the role of DNA repair and ISR pathways in the prodromal phase of PD, demonstrating their potential as early molecular indicators of disease onset. Future research should validate these findings in larger cohorts and explore their relevance for early diagnostics and intervention strategies.