Mitonuclear interactions influence Alzheimer's disease risk
Bibliographic record
Abstract
We examined the associations between mitochondrial DNA haplogroups (MT-hgs; mitochondrial haplotype groups defined by a specific combination of single nucleotide polymorphisms labeled as letters running from A to Z) and their interactions with a polygenic risk score composed of nuclear-encoded mitochondrial genes (nMT-PRS) with risk of dementia and age of onset (AOO) of dementia. MT-hg K (Odds ratio [OR]: 2.03 [95% CI: 1.04, 3.97]) and a 1 SD larger nMT-PRS (OR: 2.2 [95% CI: 1.68, 2.86]) were associated with elevated odds of dementia. Significant antagonistic interactions between the nMT-PRS and MT-hg K (OR: 0.45 [95% CI: 0.22, 0.9]) and MT-hg T (OR: 0.22 [95% CI: 0.1, 0.49]) were observed. Individual MT-hgs were not associated with AOO; however, a significant antagonistic interactions was observed between the nMT-PRS and MT-hg T (Hazard ratio: 0.62 [95% CI: 0.42, 0.91]) and a synergistic interaction between the nMT-PRS and MT-hg V (Hazard ratio: 2.28 [95% CI: 1.19, 4.35]). These results suggest that MT-hgs influence dementia risk and that variants in the nuclear and mitochondrial genome interact to influence the AOO of dementia.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".