Two-stage association study of mitochondrial DNA variants in allergic rhinitis
Bibliographic record
Abstract
BACKGROUND: Correlations between mitochondrial DNA (mtDNA) and allergic rhinitis (AR) have not been reported before. This study aimed to better understand the mitochondrial genome profile with AR and to investigate the associations between AR in China and the mitochondrial genome at a single variant and gene level. METHODS: Mitochondrial sequencing was conducted on a total of 134 unrelated individual subjects (68 patients with AR, 66 healthy controls) at discovery stage. Heteroplasmy was analyzed using the Mann-Whitney U test. Sequence kernel association tests (SKAT) were conducted to study the association between mitochondrial genes and AR. Single-variant analysis was performed using logistic regression analysis and further validated in 120 subjects (69 patients with AR, 51 healthy controls). Candidate genes were further explored based on differences in mRNA and protein abundance in nasal mucosal tissue. RESULTS: In the discovery stage, 886 variants, including 836 SNV and 50 indels, were identified with mitochondrial sequencing. No statistically significant differences were identified for the mitochondrial heteroplasmy or SKAT analysis between these two groups after applying a Boferroni correction. One nonsynonymous variants, rs3135028 (MT8584.G/A) in ATP6, was related to a reduced risk of AR in both the discovery and validation cohorts. Furthermore, mRNA levels of MT-ATP6 in nasal mucosal tissue were significantly lower in AR individuals than in controls (P < 0.05). CONCLUSIONS: In a two-stage analysis of associations between AR and mtDNA variations, mitochondrial gene maps of Chinese patients with AR indicated that the ATP6 gene was probably associated with AR at the single-variant level.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".