Wearables-derived risk score for unintrusive detection of α-synuclein aggregation or dopaminergic deficit

Schalkamp, Ann-Kathrin, Peall, Kathryn J. ORCID: https://orcid.org/0000-0003-4749-4944, Harrison, Neil A. ORCID: https://orcid.org/0000-0002-9584-3769, Escott-Price, Valentina ORCID: https://orcid.org/0000-0003-1784-5483, Barnaghi, Payam and Sandor, Cynthia ORCID: https://orcid.org/0000-0002-8905-1052 2025. Wearables-derived risk score for unintrusive detection of α-synuclein aggregation or dopaminergic deficit. EBioMedicine 117 , 105782. 10.1016/j.ebiom.2025.105782

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Abstract

Background Smartwatch data has been found to identify Parkinson's disease (PD) several years before the clinical diagnosis. However, it has not been assessed against the gold standard but costly and invasive biological and pathological markers for PD. These include dopaminergic imaging (DaTscan) and cerebrospinal fluid alpha-synuclein seed amplification assay (SAA), which are being studied as markers thought to represent the onset of PD pathology. Methods Here, we combined clinical and biological data from the Parkinson's Progression Marker Initiative (PPMI) cohort with long-term (mean: 485 days) at-home digital monitoring data collected using the Verily Study Watch. We derived a digital risk score based on sleep, vital signs, and physical activity features to distinguish between PD (N = 143) and healthy controls (N = 34), achieving an area under precision-recall curve of 0.96 ± 0.01. We compared it with the Movement Disorder Society (MDS) research criteria for prodromal PD to detect dopaminergic deficit or α-synuclein aggregation in an at-risk cohort consisting of people with genetic markers or prodromal symptoms without a diagnosis of PD (N = 109, mean age = 64.62 ± 6.86, 40 men and 69 women). Findings The digital risk correlated with the MDS research criteria (r = 0.36, p-value = 1.46 × 10−4) and was increased in individuals with subthreshold Parkinsonism (p-value = 4.99 × 10−6) and hyposmia (p-value = 3.77 × 10−2). The digital risk was correlated to a stronger degree with DaTscan putamen binding ratio (r = −0.32, p-value = 6.64 × 10−4) than the MDS criteria (r = −0.19, p-value = 6.81 × 10−3) but to a weaker degree with SAA (r = 0.2, p-value = 3.9 × 10−2) than the MDS (r = 0.43, p-value = 1.3 × 10−5). The digital risk score achieved higher sensitivity in identifying synucleinopathy or neurodegeneration (0.59) than the MDS score (0.35) but performed on-par with hyposmia (0.59) with a combination of hyposmia and digital risk score achieving the highest sensitivity (0.71). The digital risk score showed lower precision (0.18) than other models. Interpretation A digital risk score from smartwatch data should be further explored as a possible first sensitive screening tool for presence of α-synuclein aggregation or dopaminergic deficit followed by subsequent more specific tests to reduce false positives. Funding This project is funded by Welsh Government through Health and Care Research Wales, Medical Research Council (MRC), Higher Education Funding Council for Wales, UK Dementia Research Institute, Alzheimer's Society and Alzheimer's Research UK, Dementia Platforms UK, UKRI Engineering and Physical Sciences Research Council (EPSRC), NIHR Imperial Biomedical Research Centre (BRC), Great Ormond Street Hospital and the Royal Academy of Engineering, Edmond J. Safra Foundation, Ser Cymru II programme, and the European Regional Development Fund.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Schools > Medicine ?? NMHII ?? Research Institutes & Centres > Cardiff University Brain Research Imaging Centre (CUBRIC)
Additional Information:	License information from Publisher: LICENSE 1: URL: http://creativecommons.org/licenses/by/4.0/, Start Date: 2025-05-16
Publisher:	Elsevier
ISSN:	2352-3964
Date of First Compliant Deposit:	18 June 2025
Date of Acceptance:	16 May 2025
Last Modified:	18 Jun 2025 09:46
URI:	https://orca.cardiff.ac.uk/id/eprint/179151

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