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

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Tác giả: Sze Ling Celine Chui, Esther Chan, Shirely Li, Hao Luo, Lue Tian, Eric Wan, Ian C K Wong, Qingpeng Zhang

Ngôn ngữ: eng

Ký hiệu phân loại: 629.4092 Astronautics

Thông tin xuất bản: United States : Chaos (Woodbury, N.Y.) , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 220082

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.
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