Transcriptional networks in whole blood of asthmatics
Bibliographic record
Abstract
Allergen inhalation challenge causes significant changes in the blood transcriptomes of mild atopic asthmatic individuals [ 1 ]. Systems biology approaches have been used to identify transcriptional networks that reflect underlying disease processes. Such networks provide insights into the correlation patterns among genes and may identify specific molecular processes associated with asthmatic responses. Transcriptional networks can be identified using blood expression data and are associated with allergen-induced asthmatic responses. 14 participants (8 early responders and 6 dual responders) with mild, atopic asthma underwent a cat allergen inhalation challenge as part of the AllerGen Clinical Investigator Collaborative. The subjects’ whole blood samples were collected immediately prior to allergen challenge (pre-challenge) and 2 hours after the challenge (post-challenge). Whole blood transcriptional profiling was performed using Affymetrix GeneChip Human Gene 1.0 ST Arrays. The correlation networks (modules) were identified using weighted gene correlation network analysis (WGCNA) [ 2 ]. Pathway analysis was performed using GeneGo. 21,727 mRNA transcripts were profiled across 28 samples (14 pre and 14 post). Highly expressed mRNA transcripts (10,044, mean expression > log (base2) 6) were retained for WGCNA. WGCNA identified nine modules many of which were associated with various immune cell-types. A gene module consisting of 384 genes was significantly (p=0.0008) associated with the late phase asthmatic response and also significantly (p=1e-07) correlated with the compositional abundance of T cells. Pathways analysis of these genes indicated T cell receptor signaling pathway, TCR and CD28 co-stimulation in activation of NF-kβ and ICOS pathway in T-helper cells as the top significant pathways (FDR=10%). Transcriptional networks can be identified using whole blood expression data. Many transcriptional networks were associated with various cell-types frequencies, which may indicate the role of cell-specific gene expression in the development of asthmatic responses. Validation of these transcriptional networks will be performed using a larger asthma blood expression dataset.
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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 | 0.001 |
| 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".