Bronchoalveolar lavage single-cell transcriptomics reveals immune dysregulations driving COVID-19 severity
Bibliographic record
Abstract
The continuous threats posed by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19, including the emergence of potentially more infectious and deadly variants, necessitate ongoing studies to uncover novel and detailed mechanisms driving disease severity. Using single-cell transcriptomics, we conducted a secondary data analysis of bronchoalveolar lavage fluid (BALF) from COVID-19 patients of varying severities and healthy controls to comprehensively examine immune responses. We observed significant immune cell alterations correlating with disease severity. In severe cases, macrophages showed upregulation of pro-inflammatory genes TNFα and IL1β, contributing to severe inflammation and tissue damage. Neutrophils exhibited increased activation, marked by S100A8, CXCL8, and IL1β expression, with extended viability and reduced phagocytosis. Genes such as MCL1 and HIF1α supported extended viability, while MSR1 and MRC1 indicated reduced phagocytosis. Enhanced formation of neutrophil extracellular traps (NETs) and reduced clearance, indicated by NET-associated markers, were linked to thrombo-inflammation and organ damage. Both macrophages and neutrophils in severe cases showed impaired efferocytosis, indicated by decreased expression of MSR1 and TREM2 in macrophages and downregulation of FCGR3B in neutrophils, leading to the accumulation of apoptotic cells and exacerbating inflammation. Severe cases were characterized by M1 macrophages with high TNFα and IL1β, while milder cases had M2 macrophages with elevated PPARγ. Dendritic cells (DCs) in severe cases exhibited reduced proportions and attenuated expression of MHC class I genes (HLA-A, HLA-B, HLA-C) and co-stimulatory molecules (CD80, CD86), alongside increased cytochrome c expression, indicating impaired antigen presentation and enhanced apoptosis. NK and T cells in severe cases demonstrated altered receptor and gene expression, with increased activation markers IFNγ and ISG15, suggesting a paradoxical state of activation and exhaustion. This analysis highlights the critical role of dysregulated neutrophil, macrophage, dendritic cell, NK, and T cell responses in severe COVID-19, identifying potential therapeutic targets and providing novel insights into the disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".