Extended Kindred With Recessive Late-Onset Alzheimer Disease Maps to Locus 8p22-p21.2
Bibliographic record
Abstract
Late-onset Alzheimer disease (LOAD) is a complex genetic disorder. Although genes involved in early-onset forms were discovered more than a decade ago, LOAD research has only been able to point out small effect loci, with the exception of APOE. We mapped the gene predisposing to LOAD in an extended inbred family coming from a genetically isolated region (24 sampled individuals, 12 of whom are affected), completing a genome-wide screen with an Affymetrix10 K single nucleotide polymorphism microarray. Genotyping results were evaluated under model-dependent (dominant and recessive) and model-free analysis. We obtained a maximum nonparametric linkage score of 3.24 (P=0.00006) on chromosome 8p22-p21.2. The same genomic position also yielded the highest multipoint heterogeneity LOD (HLOD) under a recessive model (HLOD=3.04). When we compared the results of the model-dependent analysis, a higher score was obtained in the recessive model (3.04) than in the dominant model (1.0). This is a new locus identified in LOAD, in chromosome 8p22-p21.2 and encompassing several candidate genes, among them CLU and PPP3CC that were excluded by sequencing. The finding of a recessive model of inheritance, consistent with the assumption of inbreeding as a morbidity factor in this population, supports the notion of a role of recessive genes in LOAD.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".