DIFFERENTIALLY EXPRESSED MICRORNAS AND THEIR TARGETS WERE IDENTIFIED IN PERIPHERAL BLOOD MONONUCLEAR CELLS OF PATIENTS WITH HYPERTENSION ASSOCIATED OR NOT WITH TARGET ORGAN DAMAGE
Bibliographic record
Abstract
Objective: Hypertension is associated with subclinical target organ damage including cardiac, vascular and kidney injury. The immune system plays a role in HTN and target organ damage in animal models. Activation of T cells has been reported among peripheral blood mononuclear cells (PBMCs) of patients with HTN. MicroRNAs are crucial post-transcriptional regulators of immune cells. Whether microRNAs play a role in the activation of immune cells in HTN complicated by target organ damage in humans remains unknown. We aimed to address this question by identifying differentially expressed (DE) microRNAs and their mRNA and non-coding RNA (ncRNA) targets in PBMCs of patients with HTN complicated or not with target organ damage. mRNA targets of DE microRNAs were predicted with TargetScan using the inversely related DE mRNAs as a filter to improve prediction efficiency. Design and method: Normotensive (NTN), hypertensive patients (HTN) and patients with HTN associated with at least 2 other features of the metabolic syndrome (MetS) or with chronic kidney disease (CKD) grades 3-4 were studied (n = 15-16 in each group). PBMCs were isolated from blood, RNA extracted for RNA sequencing (RNA-seq) using Illumina HiSeq-2500 and data were analyzed using a systems biology approach. DE genes microRNAs and mRNAs were identified with fold change (FC) >1.5 and P < 0.005. DE miRNAs with FC >2 and RNA-seq count number (CM) >500, and with predicted targets with CM >300 were validated by reverse transcription-quantitative PCR (RT-qPCR). Results: DE microRNAs, mRNAs and other ncRNAs were identified by RNA-seq in HTN (22, 19 and 0), MetS (57, 401 and 11) and CKD (6, 26 and 2) compared to NTN. TargetScan predicted that 7 microRNAs target 3 mRNAs in NTN, 57 microRNAs target 55 mRNAs in MetS and 3 microRNA target 2 mRNAs in CKD. Three of 14 selected miRNAs were validated by RT-qPCR: miR-409-5p (46% down, P < 0.05) and miR-411-5p (60% down, P < 0.001) and novel miR-pl-86 (2-fold up, P < 0.05) in MetS vs NTN. Conclusions: RNA-seq and RT-qPCR validation showed that DE miR-409-5p, miR-411-5p and the novel miR-pl-86 may play a role in HTN associated with MetS.
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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 | 0.000 | 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) | 0.001 | 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".