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Neuroinflammation After COVID-19 With Persistent Depressive and Cognitive Symptoms

2023· letter· en· W4378781930 on OpenAlexafffundabout
Joeffre Braga, Mariel Lepra, Stephen J. Kish, Pablo Rusjan, Zahra Nasser, Natasha Verhoeff, Neil Vasdev, Michael Bagby, Isabelle Boileau, Muhammad Ishrat Husain, Nathan J. Kolla, Armando García, Thomas Chao, Romina Mizrahi, Khunsa Faiz, Érica Leandro Marciano Vieira, Jeffrey H. Meyer

Bibliographic record

VenueJAMA Psychiatry · 2023
Typeletter
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsMcMaster UniversityUniversity of British ColumbiaMcGill UniversityHamilton Health SciencesUniversity of TorontoBC Mental Health & Substance Use ServicesWaypoint Centre for Mental Health CareCentre for Addiction and Mental Health
FundersCanadian Institutes of Health Research
KeywordsCoronavirus disease 2019 (COVID-19)Neuroinflammation2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)CognitionDepressive symptomsMedicinePsychologyDepression (economics)PsychiatryClinical psychologyInternal medicineVirologyInflammation

Abstract

fetched live from OpenAlex

Importance: Persistent depressive symptoms, often accompanied by cognitive symptoms, commonly occur after COVID-19 illness (hereinafter termed COVID-DC, DC for depressive and/or cognitive symptoms). In patients with COVID-DC, gliosis, an inflammatory change, was suspected, but measurements of gliosis had not been studied in the brain for this condition. Objective: To determine whether translocator protein total distribution volume (TSPO VT), a marker of gliosis that is quantifiable with positron emission tomography (PET), is elevated in the dorsal putamen, ventral striatum, prefrontal cortex, anterior cingulate cortex, and hippocampus of persons with COVID-DC. Design, Setting, and Participants: This case-control study conducted at a tertiary care psychiatric hospital in Canada from April 1, 2021, to June 30, 2022, compared TSPO VT of specific brain regions in 20 participants with COVID-DC with that in 20 healthy controls. The TSPO VT was measured with fluorine F 18-labeled N-(2-(2-fluoroethoxy)benzyl)-N-(4-phenoxypyridin-3-yl)acetamide ([18F]FEPPA) PET. Main Outcomes and Measures: The TSPO VT was measured in the dorsal putamen, ventral striatum, prefrontal cortex, anterior cingulate cortex, and hippocampus. Symptoms were measured with neuropsychological and psychological tests, prioritizing outcomes related to striatal function. Results: The study population included 40 participants (mean [SD] age, 32.9 [12.3] years). The TSPO VT across the regions of interest was greater in persons with COVID-DC (mean [SD] age, 32.7 [11.4] years; 12 [60%] women) compared with healthy control participants (mean [SD] age, 33.3 [13.9] years; 11 [55%] women): mean (SD) difference, 1.51 (4.47); 95% CI, 0.04-2.98; 1.51 divided by 9.20 (17%). The difference was most prominent in the ventral striatum (mean [SD] difference, 1.97 [4.88]; 95% CI, 0.36-3.58; 1.97 divided by 8.87 [22%]) and dorsal putamen (mean difference, 1.70 [4.25]; 95% CI, 0.34-3.06; 1.70 divided by 8.37 [20%]). Motor speed on the finger-tapping test negatively correlated with dorsal putamen TSPO VT (r, -0.53; 95% CI, -0.79 to -0.09), and the 10 persons with the slowest speed among those with COVID-DC had higher dorsal putamen TSPO VT than healthy persons by 2.3 (2.30 divided by 8.37 [27%]; SD, 2.46; 95% CI, 0.92-3.68). Conclusions and Relevance: In this case-control study, TSPO VT was higher in patients with COVID-DC. Greater TSPO VT is evidence for an inflammatory change of elevated gliosis in the brain of an individual with COVID-DC. Gliosis may be consequent to inflammation, injury, or both, particularly in the ventral striatum and dorsal putamen, which may explain some persistent depressive and cognitive symptoms, including slowed motor speed, low motivation or energy, and anhedonia, after initially mild to moderate COVID-19 illness.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.018
GPT teacher head0.253
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

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Citations144
Published2023
Admission routes3
Has abstractyes

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