<scp>COVID</scp>‐19 Induces Neuroinflammation and Suppresses Peroxisomes in the Brain
Bibliographic record
Abstract
OBJECTIVE: Peroxisome injury occurs in the central nervous system (CNS) during multiple virus infections that result in neurological disabilities. We investigated host neuroimmune responses and peroxisome biogenesis factors during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using a multiplatform strategy. METHODS: Brain tissues from coronavirus disease 2019 (COVID-19) (n = 12) and other disease control (ODC) (n = 12) patients, as well as primary human neural cells and Syrian hamsters, infected with a clinical variant of SARS-CoV-2, were investigated by droplet digital polymerase chain reaction (ddPCR), quantitative reverse transcriptase PCR (RT-qPCR), and immunodetection methods. RESULTS: SARS-CoV-2 RNA was detected in the CNS of 4 patients with COVID-19 with viral protein (NSP3 and spike) immunodetection in the brainstem. Olfactory bulb, brainstem, and cerebrum from patients with COVID-19 showed induction of pro-inflammatory transcripts (IL8, IL18, CXCL10, NOD2) and cytokines (GM-CSF and IL-18) compared to CNS tissues from ODC patients (p < 0.05). Peroxisome biogenesis factor transcripts (PEX3, PEX5L, PEX11β, and PEX14) and proteins (PEX3, PEX14, PMP70) were suppressed in the CNS of COVID-19 compared to ODC patients (p < 0.05). SARS-CoV-2 infection of hamsters revealed viral RNA detection in the olfactory bulb at days 4 and 7 post-infection while inflammatory gene expression was upregulated in the cerebrum of infected animals by day 14 post-infection (p < 0.05). Pex3 transcript levels together with catalase and PMP70 immunoreactivity were suppressed in the cerebrum of SARS-CoV-2 infected animals (p < 0.05). INTERPRETATION: COVID-19 induced sustained neuroinflammatory responses with peroxisome biogenesis factor suppression despite limited brainstem SARS-CoV-2 neurotropism in humans. These observations offer insights into developing biomarkers and therapies, while also implicating persistent peroxisome dysfunction as a contributor to the neurological post-acute sequelae of COVID-19. ANN NEUROL 2023;94:531-546.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".