MINI REVIEW article
Front. Neurol.
Sec. Neurological Biomarkers
Volume 16 - 2025 | doi: 10.3389/fneur.2025.1652378
This article is part of the Research TopicIdentification of Neurological Biomarkers for Neurodegenerative DisordersView all articles
Research Progress of Multimodal Biomarkers in the Early Diagnosis of Mild Cognitive Impairment in Parkinson's Disease
Provisionally accepted
- Henan University of Chinese Medicine, Zhengzhou, China
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Parkinson's disease (PD), as a common neurodegenerative disorder, its associated mild cognitive impairment (PD-mild cognitive impairment, PD-MCI) is a key prodromal stage in the progression to PD-dementia (PDD). Cognitive dysfunction seriously affects the quality of life of patients. Early diagnosis of PD-MCI is crucial for the prognosis of the disease. At present, traditional clinical diagnosis mainly relies on neuropsychological tests, but it has limitations such as low sensitivity and being easily interfered by subjective factors. It is difficult to achieve early and accurate identification of PD-MCI, which greatly affects the intervention timing and prognosis of the disease. This article summarizes the research progress of multimodal biomarkers in the early diagnosis of PD-MCI, mainly including the comprehensive application of neuroimaging biomarkers, humoral biomarkers, genetic and molecular biomarkers, digital biomarkers, and clinical assessment, providing new theoretical basis and technical paths for promoting the early diagnosis of PD-MCI. It is of great clinical significance and social value to assist in the formulation of individualized intervention strategies, delay the progression of diseases to dementia, improve the quality of life of patients, and reduce the medical burden on families and society.
Keywords: Parkinson's disease-mild cognitive impairment, multimodal, biomarkers, early diagnosis, Machine learning algorithm
Received: 23 Jun 2025; Accepted: 01 Aug 2025.
Copyright: © 2025 Guo, Shen, Lv, Zhou, Chen, Xing and Xie. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: ming Xiao Shen, Henan University of Chinese Medicine, Zhengzhou, China
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