ABSTRACT
Hyper-transmissibility with decreased disease severity are typical characteristics of Omicron variant. To understand this phenomenon, we used various bioinformatics approaches to analyze randomly selected genome sequences (one each) of the Gamma, Delta, and Omicron variants submitted to NCBI from 15 to 31 December 2021. We show that: (i) Pathogenicity of SARS-CoV-2 variants decreases in the order: Wuhan > Gamma > Delta > Omicron; however, the antigenic property follows the order: Omicron > Gamma > Wuhan > Delta. (ii) Omicron Spike RBD has lower pathogenicity but higher antigenicity than other variants. (iii) Decreased disease severity by Omicron variant may be due to its decreased pro-inflammatory and IL-6 stimulation and increased IFN-{gamma} and IL-4 induction efficacy. (iv) Mutations in N protein are associated with decreased IL-6 induction and human DDX21-mediated increased IL-4 production in Omicron. (v) Due to mutations, the stability of S, M, N, and E proteins decreases in the order: Omicron > Gamma > Delta > Wuhan. (vi) Stronger Spike RBD-hACE2 binding in Omicron is associated with increased transmissibility. However, the lowest stability of the Omicron Spike protein makes Spike RBD-hACE2 interaction weak for systemic infection and for causing severe disease. Finally (vii), the highest instability of Omicron E protein may also be associated with decreased viral maturation and low viral load leading to less severe disease and faster recovery. Our method may be used for other similar viruses, and these findings will contribute to the understanding of the dynamics of SARS-CoV-2 variants and the management of emerging variants.
ABSTRACT
Till date the comprehensive clinical pictures, comorbid conditions, and long-term complications of COVID-19 are not known. Recently using a multi-omics-based strategy, we have predicted the drugs for COVID-19 management with [~]70% accuracy. Here, using a similar multi-omics-based bioinformatics approach and three-ways of analysis, we identified the symptoms, comorbid conditions, and short, mid and possible long-term complications of COVID-19 with [~]90% precision. In our analysis (i) we identified 27 parent, 170 child, and 403 specific conditions associated with COVID-19. (ii) Among the specific conditions, 36 are viral and 53 short-term, 62 short to mid to long-term, 194 mid to long-term, and 57 are congenital conditions. (iii) At a cut off "count of occurrence" of 4, we found [~] 90% of the enriched conditions are associated with COVID-19. (iv) Except the dry cough and loss of taste, all other COVID-19 associated mild and severe symptoms are enriched. (v) Cardiovascular, pulmonary, metabolic, musculoskeletal, neuropsychiatric, kidney, liver, and immune system disorders are found as top comorbid conditions. (vi) Specific diseases such as myocardial infarction, hypertension, COPD, lung injury, diabetes, cirrhosis, mood disorders, dementia, macular degeneration, chronic kidney disease, lupus, arthritis etc. along with several other diseases are also enriched as top candidates. (vii) Interestingly, many cancers and congenital disorders associated with COVID-19 severity are also identified. (viii) Arthritis, dermatomyositis, glioma, diabetes, psychiatric disorder, cardiovascular diseases having bidirectional relationship with COVID-19 are also found as top ranked conditions. Based on the accuracy ([~]90%) of this analysis, long presence of SARS-CoV-2 RNA in human, and our previously proposed "genetic remittance" assumption, we hypothesize that all the identified comorbid conditions including the short-long-mid and mid-long non-communicable diseases (NCDs) could also be long-term consequences in COVID-19 survivors and warrants long-term observational studies.
