<i>HLA’s</i> hidden hand in Alzheimer’s disease—five research questions en route to an answer
Bibliographic record
Abstract
Abstract The association of genetic variants in the Human Leukocyte Antigen (HLA) locus with late-onset Alzheimer’s disease has been stringently replicated across several, powerful genome-wide association studies. However, no clear picture has yet emerged of the mechanistic relationship between Alzheimer’s disease and this top genetic hit, despite the fact that the HLA locus is one of the most influential gene loci of the immune system, known to influence antigen presentation, T cell responses and brain plasticity. In this review, we explore this association by outlining five research questions, namely: (i) the association of HLA Class I and Class II genes with Alzheimer’s disease at the allelic and haplotypic levels, (ii) the unconventional role of HLA Class I in the brain, (iii) the infection hypothesis of Alzheimer’s disease in the context of the known role HLA proteins play in immunity, (iv) the possible antigen presentation of Alzheimer’s disease relevant self-antigens and in turn (v) the possibility of T cells existing that are specific for these antigens. Identifying the functional mechanisms underlying this important genetic association with Alzheimer’s disease may hold the key to unravelling new avenues of Alzheimer’s disease immunotherapeutics.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".