C-Reactive protein and cognition: Mediation analyses with brain morphology in the UK Biobank
Bibliographic record
Abstract
Cognitive impairments and abnormal immune activity are both associated with various clinical disorders. The association between C-Reactive protein (CRP), a marker associated with inflammation, and cognitive performance remains unclear. Further, mechanisms potentially linking CRP to cognition are not yet established. Brain structure may well mediate this relationship: immune processes play crucial roles in shaping and maintaining brain structure, with brain structure and function driving cognition. The UK Biobank is a large cohort study with extensive assessments, including high-sensitivity serum CRP levels, brain imaging, and various cognitive tasks. With data from 39,200 UK Biobank participants, we aimed first to determine the relationship between CRP and cognitive performance, and second, to assess metrics of brain morphology as potential mediators in this relationship. Participants were aged 40 to 70 at initial assessment and were mostly Caucasian. After accounting for potential covariates (e.g., age, sex, medical diagnoses, use of selective-serotonin reuptake inhibitors), we found CRP levels to have small, negative associations with fluid intelligence (b = −0.03, 95%CI[-0.05,-0.02], t(14381) = −3.62, pcor = .004), and numeric memory (b = −0.03, 95%CI[-0.05,-0.01], t(14366) = −3.31, pcor = .007). We found no evidence of brain morphology mediating these relationships (all |ab| < 0.001, all pcor > .55). Our findings from this large sample suggest that serum-assessed CRP is of marginal importance for cognitive performance in mid-to-late aged Caucasians; the small effect sizes of statistically significant associations provide context to previous inconsistent results. The seeming lack of involvement of brain morphology suggests that other brain metrics (e.g., connectivity, functional activation) may be more pertinent to this relationship. Future work should also consider CRP levels measured in the central nervous system and/or other cytokines that may better predict cognitive performance in this population.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".