Association of specific biotypes in patients with Parkinson's disease and disease progression
Wang, Linbo et al. (2021), Association of specific biotypes in patients with Parkinson's disease and disease progression, Dryad, Dataset, https://doi.org/10.5061/dryad.xsj3tx9bf
To identify biotypes in newly diagnosed Parkinson’s disease patients and test whether these biotypes could explain inter-individual differences in longitudinal progression.
In this longitudinal analysis, we use a data-driven approach clustering PD patients from the Parkinson’s Progression Markers Initiative (PPMI) (n = 314, age = 61.0 ± 9.5, 34.1% female, 5 years follow-up). Voxel-level neuroanatomical features were estimated using deformation-based morphometry (DBM) of T1-weighted MRI. Voxels whose deformation values were significantly correlated (P < 0.01) with clinical scores (MDS-UPDRS-Parts I-III, MDS-UPDRS-total, tremor score, and postural instability and gait difficulty score) at baseline were selected. Then, these neuroanatomical features were subjected to hierarchical cluster analysis. Changes in the longitudinal progression and neuroanatomical pattern were compared between different biotypes.
Two neuroanatomical biotypes were identified: (i) biotype 1 (n = 114) with subcortical brain volume as smaller than heathy controls; (ii) biotype 2 (n = 200) with subcortical brain volumes larger than heathy controls. Biotype 1 had more severe motor impairment, autonomic dysfunction, and very much worse REM sleep behavior disorder than biotype 2 at baseline. Although disease duration at initial visit and follow-up were similar between biotypes, PD patients with smaller subcortical brain volume had poorer prognosis, with more rapid decline in several clinical domains and in dopamine functional neuroimaging over an average of five years.
Robust neuroanatomical biotypes exist in PD with distinct clinical and neuroanatomical pattern. These biotypes can be detected at diagnosis, and predict the course of longitudinal progression, which should benefit trial design and evaluation.
All deidentified clinical and imaging data are available on the PPMI website (http://www.ppmi-info.org) and from the corresponding author on reasonable request.