IMR Press / FBL / Volume 27 / Issue 7 / DOI: 10.31083/j.fbl2707204
Open Access Original Research
Identification of DNA Methylation Signature and Rules for SARS-CoV-2 Associated with Age
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1 School of Life Sciences, Shanghai University, 200444 Shanghai, China
2 College of Information Engineering, Shanghai Maritime University, 201306 Shanghai, China
3 Ophthalmology & Optometry Medical School, Shandong University of Traditional Chinese Medicine, 250002 Jinan, Shandong, China
4 School of Electrical Engineering, Shaoyang University, 422000 Shaoyang, Hunan, China
5 Key Laboratory of Stem Cell Biology, Shanghai Jiao Tong University School of Medicine (SJTUSM) & Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS), 200031 Shanghai, China
6 Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 200031 Shanghai, China
7 CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 200031 Shanghai, China
*Correspondence: tohuangtao@126.com (Tao Huang); cai_yud@126.com (Yu-Dong Cai)
These authors contributed equally.
Academic Editor: Alika K. Maunakea
Front. Biosci. (Landmark Ed) 2022, 27(7), 204; https://doi.org/10.31083/j.fbl2707204
Submitted: 17 March 2022 | Revised: 26 May 2022 | Accepted: 26 May 2022 | Published: 27 June 2022
Copyright: © 2022 The Author(s). Published by IMR Press.
This is an open access article under the CC BY 4.0 license.
Abstract

Background: COVID-19 displays an increased mortality rate and higher risk of severe symptoms with increasing age, which is thought to be a result of the compromised immunity of elderly patients. However, the underlying mechanisms of aging-associated immunodeficiency against Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains unclear. Epigenetic modifications show considerable changes with age, causing altered gene regulations and cell functions during the aging process. The DNA methylation patterns among patients with coronavirus 2019 disease (COVID-19) who had different ages were compared to explore the effect of aging-associated methylation modifications in SARS-CoV-2 infection. Methods: Patients with COVID-19 were divided into three groups according to age. Boruta was used on the DNA methylation profiles of the patients to remove irrelevant features and retain essential signature sites to identify substantial aging-associated DNA methylation changes in COVID-19. Next, these features were ranked using the minimum redundancy maximum relevance (mRMR) method, and the feature list generated by mRMR was processed into the incremental feature selection method with decision tree (DT), random forest, k-nearest neighbor, and support vector machine to obtain the key methylation sites, optimal classifier, and decision rules. Results: Several key methylation sites that showed distinct patterns among the patients with COVID-19 who had different ages were identified, and these methylation modifications may play crucial roles in regulating immune cell functions. An optimal classifier was built based on selected methylation signatures, which can be useful to predict the aging-associated disease risk of COVID-19. Conclusions: Existing works and our predictions suggest that the methylation modifications of genes, such as NHLH2, ZEB2, NWD1, ELOVL2, FGGY, and FHL2, are closely associated with age in patients with COVID-19, and the 39 decision rules extracted with the optimal DT classifier provides quantitative context to the methylation modifications in elderly patients with COVID-19. Our findings contribute to the understanding of the epigenetic regulations of aging-associated COVID-19 symptoms and provide the potential methylation targets for intervention strategies in elderly patients.

Keywords
SARS-CoV-2
DNA methylation signature
age
feature selection
classification algorithm
Funding
XDB38050200/Strategic Priority Research Program of Chinese Academy of Sciences
XDA26040304/Strategic Priority Research Program of Chinese Academy of Sciences
2018YFC0910403/National Key R&D Program of China
202002/Fund of the Key Laboratory of Tissue Microenvironment and Tumor of Chinese Academy of Sciences
Figures
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