Exome Sequencing Reveals Immune Genes as Susceptibility Modifiers in Individuals with α1-Antitrypsin Deficiency
Bibliographic record
Abstract
Alpha-1 antitrypsin deficiency (AATD) is a genetic disorder associated to early onset emphysema, mainly imputable to Pi*ZZ genotype. In spite of the serious potential effects, many AATD individuals do not develop emphysema. To identify genes/variants potentially involved in emphysema development we studied 4 AATD families. Each family had at least one affected sibling with emphysema and one non-affected. Whole Exome Sequencing (WES) was performed on genomic DNA isolated from 9 individuals with AATD (4 affected/5 non-affected). Genetic variants confirmed at least in three families were prioritized using QueryOR and network analysis was used to verify enriched pathways. In affected subjects: 14 genes (57% immune-related) segregated in a recessive model and 21 (29% immune-related) in a dominant model. In non-affected subjects: 21 genes (43% immune-related) segregated in a recessive model and 50 (24% immune-related) in a dominant model. In affected siblings immune genes had an activating function, while where immune-suppressing in non-affected siblings involving antigen processing, MHC-I presentation, TCR and PD-1 signalling. This study describes possible genetic susceptibility factors for emphysema development in AATD, and suggests that gene variants involved in regulation of immune homeostasis and maintenance of self-tolerance contribute to the development or suppression of the disease.
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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 | 0.000 |
| 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".