Despite vaccine development, severe cases of COVID-19 still arise in patients who are unvaccinated, elderly and/or have major comorbidities; therefore, the need to accurately prognose these patients remains. There has also been worldwide disparity in COVID-19 mortality rates. India has been one of the worst affected countries, with over 500,000 COVID-19 mortalities. Not only do we need to deepen our understanding of the mechanisms of severe COVID-19 to improve treatments, but we also need to expand the diversity of populations studied in this context to ensure inclusive benefit to patients.
To help address this, Gupta and colleagues conducted the first study of lung transcriptomes from severe COVID-19 patients in an Indian population. They compared transcriptomes of post-mortem lung tissue from 31 patients that had severe COVID-19 to non-cancerous lung tissue from ten control patients who had cancer but were not infected with SARS-CoV-2. Transcriptome data revealed vast differences in host gene expression, cell type composition and microbial signatures between lung tissue samples from patients with severe COVID-19 and control patients.
Two distinct molecular signatures within the COVID-19 patient group also emerged. The ‘dominant’ signature found in 23 samples included upregulation of the complement system, causing neutrophil activation and hyperinflammation. The ‘rarer’ molecular signature found in eight COVID-19 patients showed less deviation from the control group, but was indicative of cytokine release syndrome due to excessive production of IL1 and CCL19, and high proliferation of natural killer T cells. Lung transcriptomes from both groups indicated that COVID-19 patients were unable to mount an effective adaptive immune response due to lymphopenia and displayed lung damage. All patients in the COVID-19 cohort were also administered broad-spectrum antibiotics, causing reduced microbial diversity compared to controls, but there were distinct microbial signatures between the ‘dominant’ and ‘rarer’ groups. Microbial dysbiosis could play a role in determining the transcriptomic signatures and should be investigated further.
Based on the molecular signatures of the COVID-19 patient samples, in silico drug screening identified roughly 2000 potential therapeutic agents, and interestingly, the top hits were distinct between the ‘dominant’ and ‘rarer’ groups. The diversity in molecular signature, proportion of cell types and microbiome between the COVID-19 groups supports stratifying patients to better inform prognosis and treatment based on circulating molecules such as cytokines or those involved in complement activation. Unravelling the lung pathophysiology of patients affected by severe COVID-19 will help to overcome the devastating effects of this ongoing pandemic, but only if we continue to investigate it in worldwide populations.
