Staged Screening Identifies People with Biomarkers Related to Neuronal Alpha-Synuclein Disease.

Brown, Ethan G; Chahine, Lana M; Siderowf, Andrew; Gochanour, Caroline; Kurth, Ryan; Marshall, Micah J; Caspell-Garcia, Chelsea; Brumm, Michael C et al. · Ann Neurol · 2025

prospective_cohort · Level II

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Abstract

Remote identification of individuals with severe hyposmia may enable scalable recruitment of participants with underlying alpha-synuclein aggregation. We evaluated the performance of a staged screening paradigm using remote smell testing to enrich for abnormal dopamine transporter single-photon emission computed tomography imaging (DAT-SPECT) and alpha-synuclein aggregation. The Parkinson's Progression Markers Initiative (PPMI) recruited participants for the prodromal cohort who were 60-years and older without a Parkinson's disease diagnosis. Participants were invited to complete a University of Pennsylvania Smell Identification Test (UPSIT) independently through an online portal. Hyposmic participants were invited to complete DAT-SPECT, which determined eligibility for enrollment in longitudinal assessments and further biomarker evaluation including cerebrospinal fluid alpha-synuclein seed amplification assay (aSynSAA). As of January 29, 2024, 49,843 participants were sent an UPSIT and 31,293 (63%) completed it. Of UPSIT completers, 8,301 (27%) scored <15th percentile. Of 1,546 who completed DAT-SPECT, 1,060 (69%) had DAT-SPECT binding <100% expected for age and sex. Participants with an UPSIT <10th percentile (n = 1,221) had greater likelihood of low DAT-SPECT binding compared to participants with an UPSIT in the 10th to 15th percentile (odds ratio, 3.01; 95% confidence interval, 1.85-4.91). Overall, 55% (198/363) of cases with UPSIT <15th percentile and DAT-SPECT <100% had positive aSynSAA, which increased to 70% (182/260) when selecting for more severe hyposmia (UPSIT <10th percentile). Remote screening for hyposmia and reduced DAT-SPECT binding identifies participants with a high proportion positive aSynSAA. Longitudinal data will be essential to define progression patterns in these individuals to ultimately inform recruitment into disease modification clinical trials. ANN NEUROL 2025;97:730-740.

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