Mediation Effects of IL-1β and IL-18 on the Association Between Vitamin D Levels and Mild Cognitive Impairment Among Chinese Older Adults: A Case–Control Study in Taiyuan, China
Bibliographic record
Abstract
Objective Mild cognitive impairment (MCI) is a common, chronic, and complex disease in the elderly, which is often influenced by a variety of factors that include nutrition and inflammation. This study was undertaken to evaluate the mediation effects of inflammation on the association between vitamin D levels and MCI. Methods We explored the associations of inflammation and cognitive impairment related to 25(OH)D3 deficiency among 360 older people from the communities in China. Demographic characteristics, lifestyle, and health status were investigated by questionnaire, cognitive function was detected by MoCA, and plasma 25(OH)D3, interleukin-1β (IL-1β), and interleukin-18 (IL-18) were measured by ELISA. Spearman’s correlation analysis and logistic regression analysis were used to analyze the relationship among 25(OH)D3, IL-1β, and IL-18 in the MCI group and the control group and further to analyze the relationship between 25(OH)D3 and inflammatory factors in the MCI group. Finally, mediation analysis was performed to evaluate whether inflammation mediated the effect of 25(OH)D3 deficiency on cognitive impairment. Results There were lower plasma 25(OH)D3 concentration and higher IL-1β and IL-18 levels in the MCI group compared with the controls. The levels of 25(OH)D3 were positively correlated with the MoCA scores and scores of different domains; the levels of IL-1β and IL-18 were negatively correlated with them (p < 0.05). In multivariate logistic analysis, there were significant associations among 25(OH)D3, IL-1β, IL-18, and MCI after adjusted. Further analysis revealed the significant association between the subjects with VD deficiency and the highest quartile of IL-18 in MCI (OR = 4.066), not with IL-1β after adjusting the confounding variables in MCI group. Ultimately, mediation analysis suggested that IL-1β and IL-18 could explain 25.4 and 17.5% of effect of the risk of cognitive impairment related to 25(OH)D3 deficiency. Conclusion Our findings suggested that 25(OH)D3 deficiency could increase the risk of cognitive impairment by a mechanism partly involving inflammation. Therefore, vitamin D supplementation may improve or delay the decline in cognitive function caused by inflammation in the elderly.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".