Derangement of cell cycle markers in peripheral blood mononuclear cells of asthmatic patients as a reliable biomarker for asthma control
Bibliographic record
Abstract
In asthma, most of the identified biomarkers pertain to the Th2 phenotype and no known biomarkers have been verified for severe asthmatics. Therefore, identifying biomarkers using the integrative phenotype-genotype approach in severe asthma is needed. The study aims to identify novel biomarkers as genes or pathways representing the core drivers in asthma development, progression to the severe form, resistance to therapy, and tissue remodeling regardless of the sample cells or tissues examined. Comprehensive reanalysis of publicly available transcriptomic data that later was validated in vitro, and locally recruited patients were used to decipher the molecular basis of asthma. Our in-silicoanalysis revealed a total of 10 genes (GPRC5A, SFN, ABCA1, KRT8, TOP2A, SERPINE1, ANLN, MKI67, NEK2, and RRM2) related to cell cycle and proliferation to be deranged in the severe asthmatic bronchial epithelium and fibroblasts compared to their healthy counterparts. In vitro, RT qPCR results showed that (SERPINE1 and RRM2) were upregulated in severe asthmatic bronchial epithelium and fibroblasts, (SFN, ABCA1, TOP2A, SERPINE1, MKI67, and NEK2) were upregulated in asthmatic bronchial epithelium while (GPRC5A and KRT8) were upregulated only in asthmatic bronchial fibroblasts. Furthermore, MKI76, RRM2, and TOP2A were upregulated in Th2 high epithelium while GPRC5A, SFN, ABCA1 were upregulated in the blood of asthmatic patients. SFN, ABCA1 were higher, while MKI67 was lower in severe asthmatic with wheeze compared to nonasthmatics with wheezes. SERPINE1 and GPRC5A were downregulated in the blood of eosinophilic asthmatics, while RRM2 was upregulated in an acute attack of asthma. Validation of the gene expression in PBMC of locally recruited asthma patients showed that SERPINE1, GPRC5A, SFN, ABCA1, MKI67, and RRM2 were downregulated in severe uncontrolled asthma. We have identified a set of biologically crucial genes to the homeostasis of the lung and in asthma development and progression. This study can help us further understand the complex interplay between the transcriptomic data and the external factors which may deviate our understanding of asthma heterogeneity.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".