Integration of cross-species multi-omics with in vivo experimental validation identifies Parkinson's disease therapeutic targets and novel risk factors within endolysosomal pathway subnetworks.

Abstract

Parkinson's disease (PD), the most common neurodegenerative movement disorder, imposes a growing healthcare and socioeconomic burden worldwide. A defining hallmark of PD is the accumulation of α-synuclein (αSyn) within intracellular inclusions such as Lewy bodies and Lewy neurites. Genomic studies have identified numerous PD risk factors within the endolysosomal pathway (ELP), an essential cellular system for protein and membrane recycling. Concordantly, recurrent transcriptomic and proteomic alterations in ELP components implicate broad ELP dysfunction as a causal contributor to PD and suggest that additional, uncharacterized ELP genes may cooperate in polygenic disease mechanisms. A promising but underexplored therapeutic concept is that targeted manipulation of specific ELP genes may confer protection against αSyn-induced pathology. Distinguishing pathogenic from compensatory ELP alterations could therefore reveal strategies to enhance endogenous protective responses or counteract deleterious ones. Using an integrative multi-omic network approach, we identified high-weight subnetworks of dysregulated ELP genes that converge on known PD risk factors and potential therapeutic nodes. Experimental validation in a Drosophila model demonstrates subnetworks playing a causal role in disease progression. Notably, Endosomal Sorting Complex Required for Transport (ESCRT) and phosphatidylinositol cycle subnetworks contain multiple genes whose perturbation either worsens or mitigates PD-relevant phenotypes. Among these, manipulation of STAM1/2, INPP4A/B, and TMEM55A/B ameliorates behavioral deficits, reduces neurodegeneration, and protects dopaminergic neurons. Collectively, these findings provide new mechanistic insight into the contribution of ELP dysfunction to PD, nominate previously unrecognized therapeutic targets and risk factors, and illustrate a generalizable strategy for identifying interventions capable of reprogramming maladaptive ELP responses in neurodegeneration.