Distinct brain atrophy progression subtypes underlie phenoconversion in isolated REM sleep behaviour disorder
Authors: Joza Stephen , Delva Aline , Tremblay Christina , Vo Andrew , Filiatrault Marie , Tweedale Max , Taylor John-Paul , O’Brien John T. , Firbank Michael , Thomas Alan , Donaghy Paul C. , Klein Johannes , Hu Michele , Dusek Petr , Marecek Stanislav , Varga Zsoka , Lehericy Stephane , Arnulf Isabelle , Vidailhet Marie , Corvol Jean-Christophe , Gagnon Jean-François , Postuma Ronald B. , Dagher Alain , Camicioli Richard , Chertkow Howard , Lewis Simon , Matar Elie , Ehgoetz Martens Kaylena A. , Churchill Lachlan , Sommerauer Michael , Röttgen Sinah , Borghammer Per , Knudsen Karoline , Hansen Allan K. , Arnaldi Dario , Orso Beatrice , Mattioli Pietro , Roccatagliata Luca , Monchi Oury , Rahayel Shady 
Published: September 2024

Background

Synucleinopathies manifest as a spectrum of disorders that vary in features and severity, including idiopathic/isolated REM sleep behaviour disorder (iRBD) and dementia with Lewy bodies. Patterns of brain atrophy in iRBD are already reminiscent of what is later seen in overt disease and are related to cognitive impairment, being associated with the development of dementia with Lewy bodies. However, how brain atrophy begins and progresses remains unclear.

Methods

A multicentric cohort of 1,134 participants, including 538 patients with synucleinopathies (451 with polysomnography-confirmed iRBD and 87 with dementia with Lewy bodies) and 596 healthy controls, was recruited from 11 international study centres and underwent T1-weighted MRI imaging and longitudinal clinical assessment. Scans underwent vertex-based cortical surface reconstruction and volumetric segmentation to quantify brain atrophy, followed by parcellation, ComBAT scan harmonization, and piecewise linear z-scoring for age and sex. We applied the unsupervised machine learning algorithm, Subtype and Stage Inference (SuStaIn), to reconstruct spatiotemporal patterns of brain atrophy progression and correlated the distinct subtypes with clinical markers of disease progression.

Results

SuStaIn identified two unique subtypes of brain atrophy progression: 1) a “cortical-first” progression subtype characterized by atrophy beginning in the frontal lobes followed by the temporal and parietal areas and remaining cortical areas, with the involvement of subcortical structures at later stages; and 2) a “subcortical-first” progression subtype, which involved atrophy beginning in the limbic areas, then basal ganglia, and only involving cortical structures at late stages. Patients classified to either subtype had higher motor and cognitive disease burden and were more likely to phenoconvert to overt disease compared with those that were not classifiable. Of the 84 iRBD patients who developed overt disease during follow-up, those with a subcortical-first pattern of atrophy were more likely to phenoconvert at earlier SuStaIn stages, particularly to a parkinsonism phenotype. Conversely, later disease stages in both subtypes were associated with more imminent phenoconversion to a dementia phenotype.

Conclusions

Patients with synucleinopathy can be classified into distinct patterns of atrophy that correlate with disease burden. This demonstrates insights into underlying disease biology and the potential value of categorizing patients in clinical trials.