COVID-19 is a severe respiratory disease caused by SARS-CoV-2, a novel human coronavirus. The host response to SARS-CoV-2 infection is not clearly understood. Patients infected with SARS-CoV-2 exhibit heterogeneous intensity of symptoms, i.e., asymptomatic, mild, and severe. Moreover, effects on organs also vary from person to person. These heterogeneous responses pose pragmatic hurdles for implementing appropriate therapy and management of COVID-19 patients. Post-COVID complications pose another major challenge in managing the health of these patients. Thus, understanding the impact of disease severity at the molecular level is vital to delineate the precise host response and management. In the current study, we performed a comprehensive transcriptomics analysis of publicly available seven asymptomatic and eight severe COVID-19 patients. Exploratory data analysis using Principal Component Analysis (PCA) showed the distinct clusters of asymptomatic and severe patients. Subsequently, the differential gene expression analysis using DESeq2 identified 1,224 significantly upregulated genes (logFC>= 1.5, p-adjusted value <0.05) and 268 significantly downregulated genes (logFC<= -1.5, p-adjusted value <0.05) in severe samples in comparison to asymptomatic samples. Eventually, Gene Set Enrichment Analysis (GSEA) of upregulated genes revealed significant enrichment of terms, i.e., anti-viral and anti-inflammatory pathways, secondary infections, Iron homeostasis, anemia, cardiac-related, etc. Gene set enrichment analysis of downregulated genes indicates lipid metabolism, adaptive immune response, translation, recurrent respiratory infections, heme-biosynthetic pathways, etc. In summary, severe COVID-19 patients are more susceptible to other health issues/concerns, non-viral pathogenic infections, atherosclerosis, autoinflammatory diseases, anemia, male infertility, etc. And eventually, these findings provide insight into the precise therapeutic management of severe COVID-19 patients and efficient disease management.