Deciphering the molecular mechanism of post-acute sequelae of COVID-19 through comorbidity network analysis

Abstract

The post-acute sequelae of COVID-19 (PASC) poses a significant health challenge in the post-pandemic world. However, the underlying biological mechanisms of PASC remain intricate and elusive. Network-based methods can leverage electronic health record data and biological knowledge to investigate the impact of COVID-19 on PASC and uncover the underlying biological mechanisms. This study analyzed territory-wide longitudinal electronic health records (from January 1, 2020 to August 31, 2022) of 50 296 COVID-19 patients and a healthy non-exposed group of 100 592 individuals to determine the impact of COVID-19 on disease progression, provide molecular insights, and identify associated biomarkers. We constructed a comorbidity network and performed disease-protein mapping and protein–protein interaction network analysis to reveal the impact of COVID-19 on disease trajectories. Results showed disparities in prevalent disease comorbidity patterns, with certain patterns exhibiting a more pronounced influence by COVID-19. Overlapping proteins elucidate the biological mechanisms of COVID-19's impact on each comorbidity pattern, and essential proteins can be identified based on their weights. Our findings can help clarify the biological mechanisms of COVID-19, discover intervention methods, and decode the molecular basis of comorbidity associations, while also yielding potential biomarkers and corresponding treatments for specific disease progression patterns.

Publication DOI: https://doi.org/10.1063/5.0250923
Divisions: College of Health & Life Sciences > Aston Pharmacy School
College of Health & Life Sciences
Aston University (General)
Funding Information: This work was supported by the Collaborative Research Grant of the Research Grant Council of Hong Kong (No. C7154-20GF).
Additional Information: Copyright © 2025 Author(s). Published under an exclusive license by AIP Publishing. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. The following article appeared in Lue Tian, Eric Wan, Sze Ling Celine Chui, Shirely Li, Esther Chan, Hao Luo, Ian C. K. Wong, Qingpeng Zhang; Deciphering the molecular mechanism of post-acute sequelae of COVID-19 through comorbidity network analysis. Chaos 1 February 2025; 35 (2): 021102. and may be found at https://doi.org/10.1063/5.0250923
Publication ISSN: 1089-7682
Last Modified: 27 Mar 2025 17:42
Date Deposited: 07 Mar 2025 11:10
Full Text Link:
Related URLs: https://pubs.ai ... m-of-post-acute (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2025-02
Published Online Date: 2025-02-20
Accepted Date: 2025-01-11
Authors: Tian, Lue
Wan, Eric
Celine Chui, Sze Ling
Li, Shirely
Chan, Esther
Luo, Hao
Wong, Ian C. K. (ORCID Profile 0000-0001-8242-0014)
Zhang, Qingpeng

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