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Comprehensive subtyping of Parkinson's disease patients with similarity fusion: a case study with BioFIND data.
Brendel, Matthew; Su, Chang; Hou, Yu; Henchcliffe, Claire; Wang, Fei.
Afiliação
  • Brendel M; Institute for Computational Biomedicine, Department of Physiology and Biophysics, Weill Cornell Medicine of Cornell University, New York, NY, 10065, USA.
  • Su C; Department of Health Service Administration and Policy, Temple University, Philadelphia, PA, 19122, USA.
  • Hou Y; Department of Population Health Sciences, Weill Cornell Medical College, New York, NY, 10065, USA.
  • Henchcliffe C; Department of Neurology, University of California Irvine, Irvine, CA, 92697, USA.
  • Wang F; Department of Population Health Sciences, Weill Cornell Medical College, New York, NY, 10065, USA. few2001@med.cornell.edu.
NPJ Parkinsons Dis ; 7(1): 83, 2021 Sep 17.
Article em En | MEDLINE | ID: mdl-34535682
Parkinson's disease (PD) is a complex neurodegenerative disorder with diverse clinical manifestations. To better understand this disease, research has been done to categorize, or subtype, patients, using an array of criteria derived from clinical assessments and biospecimen analyses. In this study, using data from the BioFIND cohort, we aimed at identifying subtypes of moderate-to-advanced PD via comprehensively considering motor and non-motor manifestations. A total of 103 patients were included for analysis. Through the use of a patient-wise similarity matrix fusion technique and hierarchical agglomerative clustering analysis, three unique subtypes emerged from the clustering results. Subtype I, comprised of 60 patients (~58.3%), was characterized by mild symptoms, both motor and non-motor. Subtype II, comprised of 20 (~19.4%) patients, was characterized by an intermediate severity, with a high tremor score and mild non-motor symptoms. Subtype III, comprised of 23 (~22.3%) patients, was characterized by more severe motor and non-motor symptoms. These subtypes show statistically significant differences when looking at motor (on and off medication) clinical features and non-motor clinical features, while there was no clear difference in demographics, biomarker levels, and genetic risk scores.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article