Haploinsufficiency of ITSN1 is associated with Parkinson’s disease
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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.
