Elucidating Molecular Networks Underpinning Heterogeneity in Parkinson's Disease Progression Across Clinical Manifestation Spectrum

In this study, we applied statistical and machine learning techniques to identify molecular mechanisms underlying the heterogeneity in individual Parkinson's Disease (PD) progression. Leveraging data from the Parkinson's Progression Markers Initiative (PPMI) cohort, we analyzed genetic and clinical data for patients with PD, focusing on traits including motor symptoms, non-motor symptoms, and biomarkers. Our method identified significant single-nucleotide polymorphisms (SNPs) associated with each PD trait, revealing key genetic factors and their impact on disease progression. Furthermore, through network medicine approaches, we delineated disease modules, uncovering unique gene clusters and their roles in PD pathology. The integration of pathway enrichment analysis further enhanced our understanding of the functional implications of these genetic variations, notably highlighting the significance of cellular stress response and protein aggregation pathways in PD. Overall, our findings offer a comprehensive view of the genetic landscape of PD progression, highlighting the potential of personalized medicine in managing this complex disease. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was funded by Michael J. Fox Foundation, MJFF-023081. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: www.ppmi-info.org I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available from the PPMI study - https://www.ppmi-info.org/access-data-specimens/download-data