Comparisons of the immunological landscape of COVID-19 patients based on sex and disease severity by multi-omics analysis

Abstract

Objective To determine the differences in the immune response against SARS-CoV-2 infection of patients based on sex and disease severity. Methods We used an analytical framework of 382 transcriptional modules and multi-omics analyses to discriminate COVID-19 patients based on sex and disease severity. Results Male and female patients overexpressed modules related to the innate immune response. The expression of modules related to the adaptive immune response showed lower enrichment levels in males than females. Inflammation modules showed ascending overexpression in male and female patients, while a higher level was observed in severe female patients. Moderate female patients demonstrated significant overexpression to interferon, cytolytic lymphocyte, T & B cells, and erythrocytes modules. Moderate female patients showed a higher adaptive immune response than males matched group. Pathways involved in metabolism dysregulation and Hippo signaling were upregulated in females than in male patients. Females and moderate cases showed higher levels of metabolic dysregulation. Conclusions The immune landscape in COVID-19 patients was noticeably different between the sexes, and these differences may highlight disease vulnerability in males. This study suggested that certain treatments that increase or decrease the immune responses to SARS-CoV-2 might be necessary for male and female patients at certain disease stages.

HYGIEIA: HYpothesizing the Genesis of Infectious Diseases and Epidemics through an Integrated Systems Biology Approach

“…In consequence, there is an urgent need to identify and thoroughly map disease pathways at all levels: from the genome and metagenome, to the transcriptome, proteome, and metabolome, in order to elucidate SARS-CoV-2 specific therapeutic targets and biomarkers. Despite the global research effort into COVID-19 pathogenesis, most research tends to focus on single-omic datasets, such as the genome or proteome; even the few articles that have adopted a multi-omic design tend to only investigate two [ 26 , 27 , 28 ] or three [ 29 , 30 , 31 ] omic-levels. This has led to many gaps in our knowledge of COVID-19 pathogenic pathways, whereby parts of a pathway have been identified, but upstream and downstream consequences are still unknown.…”