Molecular signature of postmortem lung tissue from COVID-19 patients suggests distinct trajectories driving mortality
Author(s) -
Anshul Budhraja,
Anubhav Basu,
Atish Gheware,
Dasari Abhilash,
Seesandra V. Rajagopala,
Suman Pakala,
Madhuresh Sumit,
Animesh Ray,
Arulselvi Subramaniam,
Purva Mathur,
Arumbirajan,
Sachin Kumar,
Ritu Gupta,
Naveet Wig,
Anjan Trikha,
Randeep Guleria,
Chitra Sarkar,
Ishaan Gupta,
Deepali Jain
Publication year - 2022
Publication title -
disease models and mechanisms
Language(s) - English
Resource type - Journals
eISSN - 1754-8411
pISSN - 1754-8403
DOI - 10.1242/dmm.049572
Subject(s) - covid-19 , biology , lung , signature (topology) , pathology , evolutionary biology , medicine , virology , outbreak , disease , mathematics , infectious disease (medical specialty) , geometry
To elucidate the molecular mechanisms manifesting lung abnormalities during severe SARS-CoV-2 infections, we performed whole transcriptome sequencing of lung autopsies from 31 patients with severe COVID-19 and 10 uninfected controls. Using metatranscriptomics, we identified the existence of two distinct molecular signatures of lethal COVID-19. The dominant “classical” signature (n=23) showed upregulation of unfolded protein response, steroid biosynthesis and complement activation supported by massive metabolic reprogramming leading to characteristic lung damage. The rarer signature (n=8) potentially representing “Cytokine Release Syndrome” (CRS) showed upregulation of cytokines such IL1 and CCL19 but absence of complement activation. We found that a majority of patients cleared SARS-CoV-2 infection, but they suffered from acute dysbiosis with characteristic enrichment of opportunistic pathogens such as Staphylococcus cohnii in “classical” patients and Pasteurella multocida in CRS patients. Our results suggest two distinct models of lung pathology in severe COVID-19 patients that can be identified through complement activation, presence of specific cytokines and characteristic microbiome that may be used to design personalized therapy using in-silico identified drug molecules or in mitigating specific secondary infections.
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