Association of alleles carried at TNFA -850 and BAT1-22 with Alzheimer's disease
Bibliographic record
Abstract
BACKGROUND: Inflammatory changes are a prominent feature of brains affected by Alzheimer's disease (AD). Activated glial cells release inflammatory cytokines which modulate the neurodegenerative process. These cytokines are encoded by genes representing several interleukins and TNFA, which are associated with AD. The gene coding for HLA-B associated transcript 1 (BAT1) lies adjacent to TNFA in the central major histocompatibility complex (MHC). BAT1, a member of the DEAD-box family of RNA helicases, appears to regulate the production of inflammatory cytokines associated with AD pathology. In the current study TNFA and BAT1 promoter polymorphisms were analysed in AD and control cases and BAT1 mRNA levels were investigated in brain tissue from AD and control cases. METHODS: Genotyping was performed for polymorphisms at positions -850 and -308 in the proximal promoter of TNFA and position -22 in the promoter of BAT1. These were investigated singly or in haplotypic association in a cohort of Australian AD patients with AD stratified on the basis of their APOE epsilon4 genotype. Semi-quantitative RT-PCR was also performed for BAT1 from RNA isolated from brain tissue from AD and control cases. RESULTS: APOE epsilon4 was associated with an independent increase in risk for AD in individuals with TNFA -850*2, while carriage of BAT1 -22*2 reduced the risk for AD, independent of APOE epsilon4 genotype. Semi-quantitative mRNA analysis in human brain tissue showed elevated levels of BAT1 mRNA in frontal cortex of AD cases. CONCLUSION: These findings lend support to the application of TNFA and BAT1 polymorphisms in early diagnosis or risk assessment strategies for AD and suggest a potential role for BAT1 in the regulation of inflammatory reactions in AD pathology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".