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

被引:0
|
作者
Tian, Lue [1 ]
Wan, Eric [2 ,3 ]
Chui, Sze Ling Celine [4 ,5 ,6 ]
Li, Shirely [2 ,4 ,7 ]
Chan, Esther [2 ,4 ]
Luo, Hao [8 ,9 ]
Wong, Ian C. K. [2 ,4 ,10 ]
Zhang, Qingpeng [2 ,4 ,11 ]
机构
[1] City Univ Hong Kong, Sch Data Sci, Hong Kong, Peoples R China
[2] Univ Hong Kong, LKS Fac Med, Dept Pharmacol & Pharm, Hong Kong, Peoples R China
[3] Univ Hong Kong, LKS Fac Med, Sch Clin Med, Dept Family Med & Primary Care, Hong Kong, Peoples R China
[4] Lab Data Discovery Hlth, Hong Kong, Peoples R China
[5] Univ Hong Kong, LKS Fac Med, Sch Nursing, Hong Kong, Peoples R China
[6] Univ Hong Kong, LKS Fac Med, Sch Publ Hlth, Hong Kong, Peoples R China
[7] Univ Hong Kong, LKS Fac Med, Sch Clin Med, Dept Med, Hong Kong, Peoples R China
[8] Univ Hong Kong, Dept Social Work & Social Adm, Hong Kong, Peoples R China
[9] Univ Waterloo, Sch Publ Hlth Sci, Waterloo, ON N2L3G1, Canada
[10] Aston Univ, Aston Pharm Sch, Birmingham B4 7ET, England
[11] Univ Hong Kong, Musketeers Fdn Inst Data Sci, Hong Kong, Peoples R China
关键词
ONLINE MENDELIAN INHERITANCE; HUMAN GENES; R PACKAGE; INFECTION;
D O I
10.1063/5.0250923
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
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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页数:13
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