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Record W7116875450 · doi:10.1002/alz70861_108935

SARS‐CoV‐2 symptoms are negatively associated with myelin content in older individuals: Results from the Canadian Longitudinal Study on Aging COVID‐19 Brain Health Study

2025· article· en· W7116875450 on OpenAlexaffabout
Narlon C. Boa Sorte Silva, Ryan G Stein, Yi Gu, Chun Liang Hsu, Roger Tam, Marina Salluzzi, Cheryl R. McCreary, Walid A. Alkeridy, K W Lam, A. MacKay, Shannon Kolind, Benoît Cossette, L. Griffith, David B. Hogan, Jacqueline M. McMillan, P Raina, Eric E. Smith, Teresa Liu‐Ambrose

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsMcMaster UniversityUniversity of British ColumbiaUniversité de SherbrookeUniversity of CalgaryConcordia University
Fundersnot available
KeywordsLongitudinal studyIncidence (geometry)MyelinAgeingCohort studyEpidemiologyBrain agingAging brain

Abstract

fetched live from OpenAlex

Abstract Background Severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) is the causative agent of COVID‐19 and has infected >700 million persons worldwide. Individuals infected with SARS‐CoV‐2 are at risk for cognitive decline and at higher risk of dementia compared with those diagnosed with other respiratory tract infections. Data from animal models suggest that SARS‐CoV‐2 infection triggers an overaggressive neuroinflammatory response resulting in myelin loss. Whether SARS‐CoV‐2 is associated with myelin loss in older individuals remains unknown. Methods We investigated the impact of SARS‐CoV‐2 on myelin in older individuals from the Canadian Longitudinal Study on Aging COVID‐19 Brain Health Study who underwent brain MRIs. We included SARS‐CoV‐2 confirmed cases at baseline (2021‐2022) via positive serological testing or health care provider diagnosis. Non‐infected controls had negative serological testing and reported no COVID‐19 diagnosis. Myelin data were acquired via myelin water imaging using a 3D MRI gradient and spin echo sequence for T2 measurement. Myelin content was extracted from 16 regions‐of‐interest within the cerebral white matter. 3D T1‐weighted scans were acquired for registrations and to estimate intracranial volume. T2‐ and PD‐weighted scans were acquired for segmentation of white matter lesions. We performed cross‐sectional comparisons via analysis of covariance. Exploratory analyses were conducted to assess the association of SARS‐CoV‐2‐related symptom incidence and severity with myelin content by group. All models were adjusted for age, age 2 , sex, ethnicity, white matter lesion burden, intracranial volume, and study site. Results We included 352 community‐dwelling individuals (SARS‐CoV‐cases, n= 64; controls, n=288). Their mean [SD] age was 65.26 (8.35) years, and 50.3% were female. There were no differences between SARS‐CoV‐2 cases and controls on myelin content across all regions‐of‐interest. Cases showed greater incidence ( p <0.001) and severity ( p <0.001) of symptoms compared with controls (Figure 1). Exploratory analysis revealed significant interactions between symptom incidence and severity with group after correcting for multiple comparisons (Table 1, p corrected < 0.05). Post hoc analysis showed that symptom incidence and severity were inversely associated with myelin in SARS‐CoV‐2 cases but not in controls across multiple regions‐of‐interest (Figure 2). Conclusions Myelin loss may occur in older individuals who experienced greater incidence and severity of SARS‐CoV‐2 infection symptoms.

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 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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.262

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.093
GPT teacher head0.371
Teacher spread0.278 · 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 designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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