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

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