Long-COVID Inducement Mechanism Based on the Path Module Correlation Coefficient

Ziqi Liu, Ziqiao Yin, Zhilong Mi and Binghui Guo ()
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Ziqi Liu: School of Mathematical Sciences, Beihang University, Beijing 100191, China
Ziqiao Yin: Key Laboratory of Mathematics, Informatics and Behavioral Semantics and State Key Laboratory of Software Development Environment, Beihang University, Beijing 100191, China
Zhilong Mi: Key Laboratory of Mathematics, Informatics and Behavioral Semantics and State Key Laboratory of Software Development Environment, Beihang University, Beijing 100191, China
Binghui Guo: Key Laboratory of Mathematics, Informatics and Behavioral Semantics and State Key Laboratory of Software Development Environment, Beihang University, Beijing 100191, China

Mathematics, 2023, vol. 11, issue 6, 1-14

Abstract: As the number of COVID-19 cases increases, the long-COVID symptoms become the focus of clinical attention. Based on the statistical analysis of long-COVID symptoms in European and Chinese populations, this study proposes the path module correlation coefficient, which can estimate the correlation between two modules in a network, to evaluate the correlation between SARS-CoV-2 infection and long-COVID symptoms, providing a theoretical support for analyzing the frequency of long-COVID symptoms in European and Chinese populations. The path module correlation coefficients between specific COVID-19-related genes in the European and Chinese populations and genes that may induce long-COVID symptoms were calculated. The results showed that the path module correlation coefficients were completely consistent with the frequency of long-COVID symptoms in the Chinese population, but slightly different in the European population. Furthermore, the cathepsin C (CTSC) gene was found to be a potential COVID-19-related gene by a path module correlation coefficient correction rate. Our study can help to explore other long-COVID symptoms that have not yet been discovered and provide a new perspective to research this syndrome. Meanwhile, the path module correlation coefficient correction rate can help to find more species-specific genes related to COVID-19 in the future.

Keywords: COVID-19; long COVID symptoms; path module correlation coefficient; path module correlation coefficient correction rate (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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