The accelerated aging model reveals critical mechanisms of late-onset Parkinson's disease

Shiyan Li; Hongxin Liu; Shiyu Bian; Xianzheng Sha; Yixue Li; Yin Wang

doi:10.1186/s13040-020-00215-w

The accelerated aging model reveals critical mechanisms of late-onset Parkinson's disease

BioData Min. 2020 Jun 10:13:4. doi: 10.1186/s13040-020-00215-w. eCollection 2020.

Authors

Shiyan Li¹, Hongxin Liu¹, Shiyu Bian², Xianzheng Sha¹, Yixue Li^{3

4

5

6}, Yin Wang^{1

7}

Affiliations

¹ Department of Biomedical Engineering, School of Fundamental Sciences, China Medical University, Shenyang, 110122 Liaoning Province China.
² China Medical University, The Queen's University of Belfast Joint College, China Medical University, Shenyang, 110122 Liaoning Province China.
³ Bio-Med Big Data Center, Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Science, Shanghai, 200031 China.
⁴ School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240 China.
⁵ Collaborative Innovation Center of Genetics and Development, Fudan University, Shanghai, 200433 China.
⁶ Shanghai Center for Bioinformation Technology, Shanghai Academy of Science and Technology, Shanghai, 201203 China.
⁷ Tumor Etiology and Screening Department of Cancer Institute and General Surgery, The First Affiliated Hospital of China Medical University, 155# North Nanjing Street, Heping District, Shenyang City, 110001 Liaoning Province China.

Abstract

Background: Late-onset Parkinson's disease (LOPD) is a common neurodegenerative disorder and lacks disease-modifying treatments, attracting major attentions as the aggravating trend of aging population. There were numerous evidences supported that accelerated aging was the primary risk factor for LOPD, thus pointed out that the mechanisms of PD should be revealed thoroughly based on aging acceleration. However, how PD was triggered by accelerated aging remained unclear and the systematic prediction model was needed to study the mechanisms of PD.

Results: In this paper, an improved PD predictor was presented by comparing with the normal aging process, and both aging and PD markers were identified herein using machine learning methods. Based on the aging scores, the aging acceleration network was constructed thereby, where the enrichment analysis shed light on key characteristics of LOPD. As a result, dysregulated energy metabolisms, the cell apoptosis, neuroinflammation and the ion imbalances were identified as crucial factors linking accelerated aging and PD coordinately, along with dysfunctions in the immune system.

Conclusions: In short, mechanisms between aging and LOPD were integrated by our computational pipeline.

Keywords: Aging acceleration; Late-onset Parkinson’s disease; Network analysis.