Data-driven trajectories of atrophy explain clinical heterogeneity across Lewy body diseases.

Konuri A., Leal GC., Zebarjadi N., Habich A., Castellanos-Perilla N., Gonzalez MC., Taylor J-P., Firbank M., Alcolea D., Bejanin A., Segers K., Benoit F., Isik AT., Samanci B., Cháfer-Pericás C., Wade-Martins R., Hu MTM., Bhome R., Dobreva I., Walker Z., Aarsland D., Westman E., Ferreira D., Halliday G., Lewis SJG., Weil RS., Landin-Romero R., Lambert C., Oxtoby NP., Matar E.

BACKGROUND: Lewy body diseases (LBD) collectively share α-synuclein Lewy pathology, yet present wide clinical heterogeneity, with overlapping motor and non-motor features and progression patterns that challenge traditional diagnostic boundaries. METHODS: To resolve this spatiotemporal heterogeneity at the biological level, we applied a data-driven atrophy progression framework to MRI data from 833 individuals across Parkinson's disease, dementia with Lewy bodies, and prodromal isolated REM sleep behaviour disorder using the Subtype and Stage Inference algorithm. FINDINGS: Four transdiagnostic subtypes (A: Early cortico-limbic/late basal ganglia, B: Early basal ganglia/late limbic, C: Early temporo-limbic/late basal ganglia, and D: Early basal ganglia-cingulate/late cortex) emerged, each defined by a distinct spatiotemporal progression of atrophy that explained cognitive, motor, and psychiatric variability. An early cortico-limbic/late basal ganglia subtype represented a dementia-prone subtype across clinical diagnoses, with limbic involvement associating with the emergence of visual hallucinations. INTERPRETATION: These biologically relevant spatiotemporal atrophy subtypes provide an interpretable stratification of patients with LBD, with the potential to refine prognosis, improve clinical trial stratification, and guide precision therapeutic approaches. FUNDING: This work was made possible by an Ignition grant from the University of Sydney and University College London (Global Engagement Fund).

DOI

10.1016/j.ebiom.2026.106400

Type

Journal article

Publication Date

2026-08-05T00:00:00+00:00

Volume

131

Keywords

Dementia, Heterogeneity, Lewy body diseases, Machine learning, Neurodegeneration, Subtypes

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