Haploinsufficiency of ITSN1 is associated with Parkinson's disease

Background Despite its significant heritability, the genetic underpinnings of Parkinson disease (PD) remain incompletely understood, particularly the role of rare variants. Advances in population-scale sequencing now provide an unprecedented opportunity to uncover additional large-effect rare genetic risk factors and expand our understanding of disease mechanisms. Methods We leveraged whole-genome sequence data with linked electronic health records from 490,560 UK Biobank participants, identifying 3,809 PD cases and 247,101 controls without a neurological disorder. We performed both variant- and gene-level association analyses to identify novel genetic associations with PD. We analyzed two additional independent case-control cohorts for replication (totaling 3,739 cases and 58,156 controls). Additionally, we performed functional validation of a novel PD association in a human synuclein-expressing Drosophila model. Findings In the UK Biobank, we replicated associations in well-established loci including GBA1 and LRRK2. We also identified a novel association between protein-truncating variants (PTVs) in ITSN1 and an increased risk of PD, with an effect size exceeding those of established loci (Fisher's Exact Test: p=6.1x10-7; Odds ratio [95% confidence interval] = 10.53 [5.20, 21.34]). We replicated the ITSN1 risk signal in a meta-analysis across all cohorts (Cochran-Mantel-Haenszel test p=5.7x10-9; Odds ratio [95% confidence interval] = 9.20 [4.66, 16.70]). In Drosophila, haploinsufficiency of the ITSN1 ortholog (Dap160) exacerbated α-synuclein-induced compound eye degeneration and motor deficits. Interpretation We establish ITSN1 as a novel risk gene for PD, with PTVs substantially increasing disease risk. ITSN1 encodes a scaffold protein involved in synaptic vesicle endocytosis, a critical pathway increasingly recognized in PD pathogenesis. Our findings highlight the power of large-scale sequencing coupled with preclinical functional modeling to identify rare variant associations and elucidate disease mechanisms.