Radiological signature of levodopa responsiveness in Parkinson's disease: A data driven approach in a deep brain stimulation cohort
Abstract
Background: Levodopa is the gold-standard therapy for motor symptoms in Parkinson's disease (PD). However, individual responses vary substantially among patients, and the biological mechanisms underlying this heterogeneity remain incompletely understood. Objective: This study aimed to investigate the neural substrates associated with variability in levodopa responsiveness using multimodal magnetic resonance imaging (MRI). Methods: Data were retrieved for this ancillary study from the PREDISTIM cohort, that aims to define predictors for deep brain stimulation outcomes. Patients were stratified through a data-driven clustering approach according to their dopa responsiveness and disease duration. MRI analyses included T1-weighted imaging and multi-echo fast gradient-echo sequences. Structural and iron-sensitive MRI measures were compared across clusters within key regions. Results: A three-phenotype response pattern previously reported in the Parkinson's Progression Markers Initiative dataset was identified, extending beyond the conventional binary classification of good (C3) and poor responders (C1). An intermediate phenotype (C2) showed preserved pharmacological responsiveness despite longer disease duration. Structural MRI revealed significant putaminal atrophy in this cluster. In contrast, patients in cluster C1 exhibited reduced grey matter in the temporo-parietal operculum and inferior frontal cortex as well as an increased iron deposition in the substantia nigra and globus pallidus internus. Conclusion: These findings, that should be validated in other populations, suggest that variability in levodopa responsiveness reflects distinct neurobiological substrates rather than a simple continuum of disease severity. Integrating markers of structural degeneration and iron-related microenvironmental changes within basal ganglia-cortical circuits may improve phenotypic stratification and support the development of precision therapeutic strategies in PD.
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BibTeX
@article{betrouni2026radiological,
title = {{Radiological signature of levodopa responsiveness in Parkinson's disease: A data driven approach in a deep brain stimulation cohort}},
author = {Nacim Betrouni and Maia Ketelers and Romain Viard and Camille Naïdji and Anne-Sophie Rolland and Charlotte Laloux and Caroline Moreau and Grégory Kuchcinski and Alexandre Eusebio and Stéphane Thobois and Elodie Hainque and Jean-Philippe Brandel and Olivier Rascol and Christine Brefel-Courbon and Sophie Drapier and Caroline Giordana and Ana Marques and David Maltête and Dominique Guehl and Lucie Hopes and Tiphaine Rouaud and Bechir Jarraya and Isabelle Benatru and Thomas Wirth and Melissa Tir and Marie Chupin and Jean-Christophe Corvol and David Devos},
journal = {Neurobiology of Disease},
year = {2026},
month = sep,
doi = {10.1016/j.nbd.2026.107599},
url = {https://u-picardie.hal.science/hal-05745752v1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Radiological signature of levodopa responsiveness in Parkinson's disease: A data driven approach in a deep brain stimulation cohort
AU - Nacim Betrouni
AU - Maia Ketelers
AU - Romain Viard
AU - Camille Naïdji
AU - Anne-Sophie Rolland
AU - Charlotte Laloux
AU - Caroline Moreau
AU - Grégory Kuchcinski
AU - Alexandre Eusebio
AU - Stéphane Thobois
AU - Elodie Hainque
AU - Jean-Philippe Brandel
AU - Olivier Rascol
AU - Christine Brefel-Courbon
AU - Sophie Drapier
AU - Caroline Giordana
AU - Ana Marques
AU - David Maltête
AU - Dominique Guehl
AU - Lucie Hopes
AU - Tiphaine Rouaud
AU - Bechir Jarraya
AU - Isabelle Benatru
AU - Thomas Wirth
AU - Melissa Tir
AU - Marie Chupin
AU - Jean-Christophe Corvol
AU - David Devos
PY - 2026
DA - 2026/09/07
JO - Neurobiology of Disease
DO - 10.1016/j.nbd.2026.107599
UR - https://u-picardie.hal.science/hal-05745752v1
AB - Background: Levodopa is the gold-standard therapy for motor symptoms in Parkinson's disease (PD). However, individual responses vary substantially among patients, and the biological mechanisms underlying this heterogeneity remain incompletely understood. Objective: This study aimed to investigate the neural substrates associated with variability in levodopa responsiveness using multimodal magnetic resonance imaging (MRI). Methods: Data were retrieved for this ancillary study from the PREDISTIM cohort, that aims to define predictors for deep brain stimulation outcomes. Patients were stratified through a data-driven clustering approach according to their dopa responsiveness and disease duration. MRI analyses included T1-weighted imaging and multi-echo fast gradient-echo sequences. Structural and iron-sensitive MRI measures were compared across clusters within key regions. Results: A three-phenotype response pattern previously reported in the Parkinson's Progression Markers Initiative dataset was identified, extending beyond the conventional binary classification of good (C3) and poor responders (C1). An intermediate phenotype (C2) showed preserved pharmacological responsiveness despite longer disease duration. Structural MRI revealed significant putaminal atrophy in this cluster. In contrast, patients in cluster C1 exhibited reduced grey matter in the temporo-parietal operculum and inferior frontal cortex as well as an increased iron deposition in the substantia nigra and globus pallidus internus. Conclusion: These findings, that should be validated in other populations, suggest that variability in levodopa responsiveness reflects distinct neurobiological substrates rather than a simple continuum of disease severity. Integrating markers of structural degeneration and iron-related microenvironmental changes within basal ganglia-cortical circuits may improve phenotypic stratification and support the development of precision therapeutic strategies in PD.
SN - 0969-9961
SN - 1095-953X
ER -