Genetic and epigenetic study of an Alzheimer’s disease family with monozygotic triplets
Bibliographic record
Abstract
Age at onset of Alzheimer's disease is highly variable, and its modifiers (genetic or environmental) could act through epigenetic changes, such as DNA methylation at CpG sites. DNA methylation is also linked to ageing-the strongest Alzheimer's disease risk factor. DNA methylation age can be calculated using age-related CpGs and might reflect biological ageing. We conducted a clinical, genetic and epigenetic investigation of a unique Ashkenazi Jewish family with monozygotic triplets, two of whom developed Alzheimer's disease at ages 73 and 76, while the third at age 85 has no cognitive complaints or deficits in daily activities. One of their offspring developed Alzheimer's disease at age 50. Targeted sequencing of 80 genes associated with neurodegeneration revealed that the triplets and the affected offspring are heterozygous carriers of the risk APOE ε4 allele, as well as rare substitutions in APP (p.S198P), NOTCH3 (p.H1235L) and SORL1 (p.W1563C). In addition, we catalogued 52 possibly damaging rare variants detected by NeuroX array in affected individuals. Analysis of family members on a genome-wide DNA methylation chip revealed that the DNA methylation age of the triplets was 6-10 years younger than chronological age, while it was 9 years older in the offspring with early-onset Alzheimer's disease, suggesting accelerated ageing.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".