Mapping genetic modulators of amyloid plaque deposition in TgCRND8 transgenic mice
Bibliographic record
Abstract
Alzheimer's disease (AD) is a complex disorder for which various in vivo models exist. The TgCRND8 mouse, transgenic for the human amyloid precursor protein, is an aggressive early onset model of brain amyloid deposition. Preliminary studies revealed that when the transgene is expressed on an A/J genetic background, these mice not only survive longer but also deposit less parenchymal amyloid-beta (Abeta) peptides as compared to those on a C57BL/6 background. We performed a genome-wide study of an F2 intercross between TgCRND8 on an A/J background and C57BL/6 mice, to identify genetic modulators of amyloid accumulation and deposition. We identified four highly significant QTLs that together account for 55% of the phenotypic variance in the number of plaques (Thioflavin S). QTLs were found on the distal part of chromosome 4 with an LOD score of 8.1 at D4Mit251, on chromosome 11 with an LOD score of 5.5 at D11Mit242, on chromosome 9 with an LOD score of 5.0 at D9Mit336 and on the proximal part of chromosome 8 with an LOD score of 4.5 at D8Mit223. A/J alleles at these loci are protective and all decreased the amount of Abeta deposition. Interestingly, the QTL on chromosome 11 is also significantly linked to the levels of brain Abeta(42) and Abeta(40). Although these QTLs do not control the levels of plasmatic Abeta, other regions on chromosomes 1 and 6 show significant linkage. Further characterization of these QTL regions may lead to the identification of genes involved in the pathogenesis of AD.
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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".