Clinical correlates of data-driven subtypes of deep gray matter atrophy and dopamine availability in early Parkinson's disease.

Journal: NPJ Parkinson's disease
Published Date: Jun 12, 2025

Abstract

Recent machine-learning techniques may be useful to identify subtypes with distinct spatial patterns of biomarker abnormality in the various neurodegenerative diseases. Using the Subtype and Stage Inference (SuStaIn) technique, we categorized data-driven subtypes of PD by examining the deep gray matter volume and dopamine availability and compared cardiac denervation, cognition, and motor symptoms between these subtypes. The SuStaIn algorithm revealed two distinctive subtypes, which were well replicated in an external dataset. Subtype 1 was characterized by lower dopamine availability apparent at early inferred stages, severe cardiac denervation, mild cognitive dysfunction in the early stage, and patterns suggesting accelerated motor and cognitive dysfunction associated with later stages. In contrast, subtype 2 showed patterns indicative of earlier brain atrophy, mild cardiac denervation, and severe cognitive dysfunction apparent at early inferred stages, with no significant correlation between motor and cognitive status and SuStaIn stage. These findings suggest that the machine-learning model can identify heterogeneity in PD biomarker profiles, offering insights into potential region and stage-specific patterns of biomarker abnormality and their clinical implications.

Authors

  • Yoonsang Oh
    Department of Neurology, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
  • Joong-Seok Kim
    Department of Neurology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
  • Gilsoon Park
    Department of Biomedical Engineering, Hanyang University, Seoul, South Korea.
  • Sang-Won Yoo
    Department of Neurology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
  • Dong-Woo Ryu
    Department of Neurology, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
  • Hosung Kim
    Laboratory of Neuro Imaging, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA. Electronic address: hosung.kim@loni.usc.edu.

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