Lower estimated glomerular filtration rate relates to cognitive impairment and brain alterations
Bibliographic record
Abstract
INTRODUCTION: Chronic kidney disease (CKD) is associated with cognitive decline and changes in brain structure. However, their associations remain unclear, particularly the selective vulnerability characteristics that make some brain regions more vulnerable. METHODS: We investigated the baseline association between estimated glomerular filtration rates (eGFR) and cognitive function in 15,897 individuals from the CARTaGENE cohort. We performed vertex-based magnetic resonance imaging (MRI) analyses between eGFR and longitudinal cortical thickness in the 1397 participants who underwent brain MRI after 6 years. Imaging transcriptomics was used to characterize the gene expression and neurodegenerative features associated with this association. RESULTS: Lower eGFR correlated with reduced cognitive performance and brain structure. Brain regions associated with eGFR were enriched for mitochondrial and inflammatory-related genes. These associations occurred independently from age, sex, education, and body mass index (BMI), Framingham risk score, and white matter lesion volume. DISCUSSION: This study highlights the link between reduced eGFR, cognitive impairment, and brain structure, revealing some of the kidney-brain axis mechanisms. Highlights: Lower eGFR is associated with reduced cognitive abilities.Structural brain changes are mediated by eGFR levels.Specific gene expression patterns correlate with lower eGFR and brain changes.Mitochondrial and inflammation-related genes were enriched in these patterns.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".