Potential contribution of the neurodegenerative disorders risk loci to cognitive performance in an elderly male gout population
Bibliographic record
Abstract
Cognitive impairment has been described in elderly subjects with high normal concentrations of serum uric acid. However, it remains unclear if gout confers an increased poorer cognition than those in individuals with asymptomatic hyperuricemia. The present study aimed at evaluating cognitive function in patients suffering from gout in an elderly male population, and further investigating the genetic contributions to the risk of cognitive function.This study examined the cognitive function as assessed by Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) in 205 male gout patients and 204 controls. The genetic basis of these cognitive measures was evaluated by genome-wide association study (GWAS) data in 102 male gout patients. Furthermore, 7 loci associated with cognition in GWAS were studied for correlation with gout in 1179 male gout patients and 1848 healthy male controls.Compared with controls, gout patients had significantly lower MoCA scores [22.78 ± 3.01 vs 23.42 ± 2.95, P = .023, adjusted by age, body mass index (BMI), education, and emotional disorder]. GWAS revealed 7 single-nucleotide polymorphisms (SNPs) associations with MoCA test at a level of conventional genome-wide significance (P < 9.6 × 10). The most significant association was observed between rs12895072 and rs12434554 within the KTN1 gene (Padjusted = 4.2 × 10, Padjusted = 4.7 × 10) at 14q22. The next best signal was in RELN gene (rs155333, Padjusted = 1.3 × 10) at 7q22, while the other variants at rs17458357 (Padjusted = 3.98 × 10), rs2572683 (Padjusted = 8.9 × 10), rs12555895 (Padjusted = 2.6 × 10), and rs3764030 (Padjusted = 9.4 × 10) were also statistically significant. The 7 SNPs were not associated with gout in further analysis (all P > .05).Elderly male subjects with gout exhibit accelerated decline in cognition performance. Several neurodegenerative disorders risk loci were identified for genetic contributors to cognitive performance in our Chinese elderly male gout population. Larger prospective studies of the cognitive performance and genetic analysis in gout subjects are recommended.
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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 | 0.001 |
| 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) | 0.001 | 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".