Immune Response Is Key to Genetic Mechanisms of SARS-CoV-2 Infection With Psychiatric Disorders Based on Differential Gene Expression Pattern Analysis

Abstract

Existing evidence demonstrates that coronavirus disease 2019 (COVID-19) leads to psychiatric illness, despite its main clinical manifestations affecting the respiratory system. People with mental disorders are more susceptible to COVID-19 than individuals without coexisting mental health disorders, with significantly higher rates of severe illness and mortality in this population. The incidence of new psychiatric diagnoses after infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is also remarkably high. SARS-CoV-2 has been reported to use angiotensin-converting enzyme-2 (ACE2) as a receptor for infecting susceptible cells and is expressed in various tissues, including brain tissue. Thus, there is an urgent need to investigate the mechanism linking psychiatric disorders to COVID-19. Using a data set of peripheral blood cells from patients with COVID-19, we compared this to data sets of whole blood collected from patients with psychiatric disorders and used bioinformatics and systems biology approaches to identify genetic links. We found a large number of overlapping immune-related genes between patients infected with SARS-CoV-2 and differentially expressed genes of bipolar disorder (BD), schizophrenia (SZ), and late-onset major depressive disorder (LOD). Many pathways closely related to inflammatory responses, such as MAPK, PPAR, and TGF-β signaling pathways, were observed by enrichment analysis of common differentially expressed genes (DEGs). We also performed a comprehensive analysis of protein-protein interaction network and gene regulation networks. Chemical-protein interaction networks and drug prediction were used to screen potential pharmacologic therapies. We hope that by elucidating the relationship between the pathogenetic processes and genetic mechanisms of infection with SARS-CoV-2 with psychiatric disorders, it will lead to innovative strategies for future research and treatment of psychiatric disorders linked to COVID-19.

Keywords: COVID-19; SARS-CoV-2; differentially expressed gene; functional enrichment; psychiatric illness.

Graphical Abstract

Figure 1

Volcano plots indicate differentially expressed genes (DEGs) of (A) bipolar disorder (BD), (B) schizophrenia (SZ), and (C) late-onset major depressive disorder (LOD), with genes harboring log fold-change of at least 1 and adjusted P-value <0.05. The Venn diagram depicts the shared DEGs among coronavirus disease 2019 (COVID-19) and (D) BD, SZ, and LOD.

Figure 2

(A) The Venn diagram illustrates the common DEGs in COVID-19 immune system and BD, SZ, and LOD. Heatmaps demonstrate the associations of DEGs based on (B) adjusted P-value and (C) log fold-change for all immune data sets.

Figure 3

Top 25 cascades between COVID-19 and psychiatric diseases. Cascades were determined using DEGs for each condition and COVID-19 whole blood and immune samples. Panel (A) shows cascades for BD. Panels (B, C) show pathways for SZ and LOD, respectively. The higher the log adj P, the more significant the enrichment.

Figure 4

Top 25 gene ontology between COVID-19 and mental disorders. The ontology cascades were determined using the DEGs for each of the condition and the combined genes of COVID-19 whole blood and immune samples. Panel (A) exhibits the ontology for BD. Panels (B, C) exhibit ontology cascades for SZ and LOD, respectively.

Figure 5

(A) The detailed PPI network of shared DEGs in COVID-19 and psychiatric disorders. The purple circles illustrate the proteins common in COVID-19 and corresponding diseases. Nodes designate proteins and edges exhibit cross talk between two proteins. Proteins having multiple edges are overexpressed. (B) Hub protein network exhibits eight hub proteins based on the degree of cross talk. EGF has the highest cross talk with other proteins.

Figure 6

Regulatory gene networks of COVID-19 with psychiatric disorders. Panels (A–C) designate the DEG–miRNA networks of COVID-19 with BD, SZ, and LOD, respectively. Circles designate DEGs and diamonds designate miRNAs. The results of the DEG–TF networks of (D) BD–COVID-19, (E) SZ–COVID-19, and (F) LOD–COVID-19. Circles illustrate DEGs, and triangles represent TFs. Overexpressed DEGs, miRNAs, and TFs are designated by larger size and darker color.

Figure 7

Relationship of COVID-19 and psychiatric disorders with regard to chemical and protein agents. Panels (A–C) illustrate the chemical–protein networks of COVID-19 with BD, SZ, and LOD, respectively. Circles designate proteins and squares designate chemical compounds. Overexpressed proteins and chemicals are designated by larger size and darker color. Squares having multiple edges are the most overexpressed chemical agents.