Genome-wide transcriptional profiling linked to social class in asthma
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: Low socioeconomic status (SES) is one of the most robust social factors associated with disease morbidity, including more severe asthma in childhood. However, our understanding of the biological processes that explain this link is limited. This study tested whether the social environment could get "under the skin" to alter genomic activity in children with asthma. DESIGN AND PARTICIPANTS: Two group design of children with physician diagnosed asthma who came from low or high SES families. OUTCOMES: Genome-wide transcriptional profiles from T lymphocytes of children with asthma. RESULTS: Children with asthma from a low SES background showed overexpression of genes regulating inflammatory processes, including those involved in chemokine activity, stress responses and wound responses, compared with children with asthma from a high SES background. Bioinformatic analysis suggested that decreased activity of cyclic AMP response element binding protein and nuclear factor Y and increased nuclear factor kappaB transcriptional signalling mediated these effects. These pathways are known to regulate catecholamine and inflammatory signalling in immune cells. CONCLUSIONS: This study provides the first evidence in a sample of paediatric patients diagnosed with asthma that the larger social environment can affect processes at the genomic level. Specifically, gene transcription control pathways that regulate inflammation and catecholamine signalling were found to vary by SES in children with asthma. Because these pathways are the primary targets of many asthma medications, these findings suggest that the larger social environment may alter molecular mechanisms that have implications for the efficacy of asthma therapeutics.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it