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<p>Parkinson’s disease (PD) exhibits significant variability in disease progression, making individual trajectory prediction challenging. Previously, we defined motor progression phenotypes based on longitudinal OFF-medication changes in the Movement Disorder Society–Unified Parkinson’s Disease Rating Scale Part III (MDS-UPDRS-III) and demonstrated their predictability at baseline using MRI-informed machine learning. OFF-medication assessments are rare in routine care. Therefore, this study evaluated whether these phenotypes correspond to standard clinical outcomes. Eighty-eight early PD patients from the Parkinson’s Progression Markers Initiative were classified as “faster” or “slower” progressors based on 48-month OFF-medication ΔMDS-UPDRS-III scores. A support vector machine incorporating baseline structural MRI and clinical features classified these phenotypes with 89% accuracy. Phenotypes were compared across independent 48-month outcomes, including MDS-UPDRS Part II, Schwab &amp; England Activities of Daily Living (S&amp;E ADL), levodopa equivalent daily dose (LEDD), and Hoehn &amp; Yahr (HY) staging. Faster progressors exhibited significantly greater functional declines in MDS-UPDRS Part II and S&amp;E ADL scores and higher LEDD requirements at 48&#xa0;months. Clinically meaningful deterioration consistent with published thresholds occurred more frequently among faster progressors for MDS-UPDRS Part II and HY staging. These findings validate the clinical relevance of MRI-informed progression phenotyping for prognostic stratification in early PD, highlighting its potential to identify biologically distinct trajectories.</p>

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Clinical relevance of MRI-informed motor progression phenotypes in early Parkinson’s disease

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月28日

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  • Anupa A. Vijayakumari,
  • Daniel Teixeira-Dos-Santos,
  • Hubert H. Fernandez,
  • Benjamin L. Walter

摘要

Parkinson’s disease (PD) exhibits significant variability in disease progression, making individual trajectory prediction challenging. Previously, we defined motor progression phenotypes based on longitudinal OFF-medication changes in the Movement Disorder Society–Unified Parkinson’s Disease Rating Scale Part III (MDS-UPDRS-III) and demonstrated their predictability at baseline using MRI-informed machine learning. OFF-medication assessments are rare in routine care. Therefore, this study evaluated whether these phenotypes correspond to standard clinical outcomes. Eighty-eight early PD patients from the Parkinson’s Progression Markers Initiative were classified as “faster” or “slower” progressors based on 48-month OFF-medication ΔMDS-UPDRS-III scores. A support vector machine incorporating baseline structural MRI and clinical features classified these phenotypes with 89% accuracy. Phenotypes were compared across independent 48-month outcomes, including MDS-UPDRS Part II, Schwab & England Activities of Daily Living (S&E ADL), levodopa equivalent daily dose (LEDD), and Hoehn & Yahr (HY) staging. Faster progressors exhibited significantly greater functional declines in MDS-UPDRS Part II and S&E ADL scores and higher LEDD requirements at 48 months. Clinically meaningful deterioration consistent with published thresholds occurred more frequently among faster progressors for MDS-UPDRS Part II and HY staging. These findings validate the clinical relevance of MRI-informed progression phenotyping for prognostic stratification in early PD, highlighting its potential to identify biologically distinct trajectories.