Parkinson's Disease Subtyping Using Clinical Features and Biomarkers: Literature Review and Preliminary Study of Subtype Clustering.

Seung Hyun Lee,Mi-Kyung Lee,Sang-Min Park,Sang Seok Yeo,Jung-Hee Jang,Eun Kyoung Ahn,Ojin Kwon,Jae Young Jang,Horyong Yoo

doi:10.3390/diagnostics12010112

Abstract

The second most common progressive neurodegenerative disorder, Parkinson’s disease (PD), is characterized by a broad spectrum of symptoms that are associated with its progression. Several studies have attempted to classify PD according to its clinical manifestations and establish objective biomarkers for early diagnosis and for predicting the prognosis of the disease. Recent comprehensive research on the classification of PD using clinical phenotypes has included factors such as dominance, severity, and prognosis of motor and non-motor symptoms and biomarkers. Additionally, neuroimaging studies have attempted to reveal the pathological substrate for motor symptoms. Genetic and transcriptomic studies have contributed to our understanding of the underlying molecular pathogenic mechanisms and provided a basis for classifying PD. Moreover, an understanding of the heterogeneity of clinical manifestations in PD is required for a personalized medicine approach. Herein, we discuss the possible subtypes of PD based on clinical features, neuroimaging, and biomarkers for developing personalized medicine for PD. In addition, we conduct a preliminary clustering using gait features for subtyping PD. We believe that subtyping may facilitate the development of therapeutic strategies for PD.

Highlights

Parkinson’s disease (PD) is associated with a broad spectrum of clinical symptoms, including motor and non-motor symptoms [1,3]
Dimension reduction of the data was performed to reduce all features to three principal components, which were representative of all features
Considering the clinical heterogeneity of PD, here, we summarized its subtypes using the clinical symptoms, neuroimaging, and molecular markers from previous studies for improving treatment efficiency through personalized medicine

Summary

Introduction

Parkinson’s disease (PD), a common chronic progressive neurodegenerative disorder, is characterized by α-synuclein aggregations and neuronal loss in the substantia nigra, which results in striatal dopamine deficiency [1]. The pathophysiology of PD involves multiple neurotransmitter deficiencies resulting in multisystem neurodegeneration, contributing to a clinical phenotyping variability [2,3]. PD is associated with a broad spectrum of clinical symptoms, including motor and non-motor symptoms [1,3]. These multiple clinical symptoms are associated with the progression of PD. The progression of PD is driven by the combination of increasing severity of non-motor and motor symptoms, complications, and poor response to standard therapy [1]. The clinical manifestations, course of progression, and biomarker profiles in PD vary widely from person to person [4]

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