Mitochondrial DNA somatic mutation burden and heteroplasmy are associated with chronological age, smoking, and HIV infection
Bibliographic record
Abstract
The gradual accumulation of mitochondrial DNA (mtDNA) mutations is implicated in aging and may contribute to the accelerated aging phenotype seen with tobacco smoking and HIV infection. mtDNA mutations are thought to arise from oxidative damage; however, recent reports implicate polymerase γ errors during mtDNA replication. Investigations of somatic mtDNA mutations have been hampered by technical challenges in measuring low-frequency mutations. We use primer ID-based next-generation sequencing to quantify both somatic and heteroplasmic blood mtDNA point mutations within the D-loop, in 164 women and girls aged 2-72 years, of whom 35% were smokers and 56% were HIV-positive. Somatic mutations and the occurrence of heteroplasmic mutations increased with age. While transitions are theorized to result from polymerase γ errors, transversions are believed to arise from DNA oxidative damage. In our study, both transition and transversion mutations were associated with age. However, transition somatic mutations were more prevalent than transversions, and no heteroplasmic transversions were observed. We also measured elevated somatic mutations, but not heteroplasmy, in association with high peak HIV viremia. Conversely, heteroplasmy was higher among smokers, but somatic mutations were not, suggesting that smoking promotes the expansion of preexisting mutations rather than de novo mutations. Taken together, our results are consistent with blood mtDNA mutations increasing with age, inferring a greater contribution of polymerase γ errors in mtDNA mutagenesis. We further suggest that smoking and HIV infection both contribute to the accumulation of mtDNA mutations, though in different ways.
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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 | 0.002 |
| 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".