The association of NLRP3 polymorphisms and its downstream interaction in mild cognitive impairment
Bibliographic record
Abstract
Abstract Background Nucleotide-binding domain and leucine-rich repeat (LRR)-containing family protein 3 (NLRP3) has been widely studied in the pathogenesis of mild cognitive impairments (MCI) and Alzheimer’s Disease (AD). Single nucleotide polymorphisms (SNPs) of NLRP3 gene are associated with various diseases, however the association between NLRP3 SNPs and downstream pathway is unclear. Methods 12 intron SNPs and 2 exon SNPs were genotyped in 235 normal controls and 331 MCI older adults. NLRP3 and other inflammation-related genes expression were quantified in peripheral blood mononuclear cells (PBMC) from the older adults by quantitative PCR (qPCR). Functional studies of selected mutations were performed by luciferase assay. The older adults were followed up for 2 years to investigate the relationship between NLRP3 SNPs and risk of cognitive decline. Results Our study showed rs10754558 and rs7525979 were associated with an increased risk of MCI. The T allele of rs12564791 was associated with higher gene expression level of NLRP3, interleukin-18 (IL-18), PYCARD, and CASP1. rs12048215, rs10754555, and rs7525979 were associated with cognitive decline as shown by the reduction of Montreal Cognitive Assessment (MoCA) score. Functional studies showed that both rs10754558 and rs10754555 G to C mutation affected enhancer activity of transcription. rs10754558 G to C mutation also disturbed the interaction between NLRP3 3’UTR and miR-425-5p. Plasma miR-425-5p expression was negatively correlated with MoCA score. Conclusions Our study suggested that genetic variations of NLRP3 were associated with the cognitive decline by affecting the gene expression of inflammation-related genes and its interactions to miRNAs.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".