MIR-338-3P DOWN-REGULATION IN SMALL ARTERIES OF HYPERTENSIVE PATIENTS WITH CHRONIC KIDNEY DISEASE MAY ACT VIA UP-REGULATION OF ALKALINE CERAMIDASE 2 AND GLUTATHIONE PEROXIDASE 3
Bibliographic record
Abstract
Objective: Hypertension (HTN) is associated with vascular damage characterized by vascular remodeling and stiffening and endothelial dysfunction, which is a cause of end-organ damage such as chronic kidney disease (CKD). microRNAs are small non-coding RNA that regulate gene expression by binding to their target messenger RNAs (mRNAs), leading to mRNA degradation or translational repression. Their participation in mechanisms leading to vascular injury remains unclear. We aimed to identify differentially expressed (DE) microRNAs in small arteries of human subjects with HTN associated or not with CKD to gain insight into pathophysiological molecular mechanisms in these conditions. Design and method: Normotensive subjects and patients with HTN associated or not with CKD grades 3-4 were studied (n = 15-16). Blood pressure was determined by automated office measurement (AOBP). Small arteries were isolated from subcutaneous gluteal biopsies and RNA extracted for small and total RNA sequencing using Illumina HiSeq-2500. Differentially expressed (DE) genes were identified with a P < 0.05. The selected DE miRNAs were confirmed by reverse transcription-quantitative PCR (RT-qPCR). Putative microRNA targets were validated using gain- and loss-of-function in human aortic vascular cells by RT-qPCR and luciferase reporter assay. Results: Small RNA sequencing identified DE microRNAs uniquely associated with HTN (3 up and 6 down), CKD (42 up and 39 down) or both groups (2 up). One of 14 tested DE microRNAs was validated. RT-qPCR showed that miR-338-3p was decreased by 59% in CKD (P < 0.05). miR-338-3p and three of its predicted targets were highly expressed in human aortic endothelial cells (HAECs). Two of them, alkaline ceramidase 2 (ACER2) and glutathione peroxidase 3 (GPX3), were up-regulated by 48% and 90% in human aortic endothelial cells (HAECs) transfected with anti-miR-338-3p, respectively (P < 0.05). miR-338-3p mimic co-transfection in HAECs decreased respectively by 13% and 24% luciferase activity of reporter vectors containing the conserved wild-type but not mutated ACER2 or GPX3 3’ untranslated transcribed region miR-338-3p-5p binding sites (P < 0.05). Conclusions: miR-338-3p down-regulation in small arteries may act via mRNA up-regulation of alkaline ceramidase 2 and glutathione peroxidase 3 to play a role in vascular injury in hypertensive patients with chronic kidney disease.
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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) | 0.001 | 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".