Mosaic loss of chromosome Y in aged human microglia
Bibliographic record
Abstract
Abstract Mosaic loss of chromosome Y (LOY) is a particularly common acquired structural mutation in the leukocytes of aging men and it has been shown to correlate with several age-related diseases including Alzheimer’s disease (AD). To derive the molecular basis of LOY in brain cells, we create an integrated resource by aggregating data from 21 single-cell and single-nuclei RNA brain studies, yielding 763,410 cells to investigate the presence and cell-type specific burden of LOY. We created robust quantification metrics for assessing LOY, which were validated using a multi-modal dataset. Using this new resource and LOY-quantification approach, we found that LOY frequencies differed widely between CNS cell-types and individual donors. Among five common neural cell types, microglia were most affected by LOY (7.79%, n =41,949), while LOY in neurons was rare (0.48%, n =220,010). Differential gene expression analysis in microglia found 188 autosomal genes, 6 X-linked genes, and 11 pseudoautosomal genes, pointing to broad dysregulation in lipoprotein metabolism, inflammatory response, and antigen processing that coincides with loss of Y. To our knowledge, we provide the first evidence of LOY in the microglia, and highlight its potential roles in aging and the pathogenesis of neurodegenerative disorders such as AD.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".