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
Bibliographic record
Abstract
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.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".