MicroRNA-132-3p, Downregulated in Myeloid Angiogenic Cells from Hereditary Hemorrhagic Telangiectasia Patients, Is Enriched in the TGFβ and PI3K/AKT Signalling Pathways
Bibliographic record
Abstract
Background. Hereditary hemorrhagic telangiectasia (HHT) is a rare, autosomal dominant genetic disorder characterized by life-threatening vascular dysplasia. Myeloid angiogenic cells (MACs), alternatively called early endothelial progenitor cells or circulating angiogenic cells, do not directly incorporate into developing blood vessels, but augment angiogenesis in a paracrine manner. MAC dysfunction has been reported in HHT. MicroRNAs (miRNAs) regulate cellular function by modulating gene expression post-transcriptionally. To date, the role of miRNAs in HHT MAC dysfunction has not been documented. Objective. The goal of this study was to comparatively profile miRNAs in HHT patient and control MACs to identify dysregulated miRNAs that may be responsible for the observed MAC dysfunction in HHT. Methodology/Results. Twenty-three dysregulated miRNAs (twenty-one upregulated and two downregulated) in HHT MACs were identified with a TaqMan miRNA microarray. Pathway enrichment analysis showed that the dysregulated miRNAs were significantly enriched in pathways involved in HHT pathogenesis, such as the transforming growth factor β (TGFβ), phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT), and Hippo signalling pathways. Furthermore, miR-132-3p was determined to be significantly reduced in HHT MACs compared with controls by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Bioinformatic analysis revealed that miR-132-3p is significantly enriched in the TGFβ and PI3K/AKT signalling pathways, targeting SMAD4, an effector of the TGFβ signalling pathway and RASA1, a negative regulator of the PI3K/AKT signalling pathway, respectively. Conclusion. MiRNA dysregulation, specifically reduced expression of miR-132-3p, in HHT MACs was identified. The dysregulated miRNAs are significantly enriched in the TGFβ, PI3K/AKT, and Hippo signalling pathways. These data suggest that alteration in miRNA expression may impair these pathways and contribute to MAC dysfunction in HHT.
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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 | 0.000 | 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 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".