PS-B11-8: ONE NOVEL MIRNA WITH 4 MRNA TARGETS WAS IDENTIFIED IN PERIPHERAL BLOOD MONONUCLEAR CELLS OF HYPERTENSIVE PATIENTS WITH METABOLIC SYNDROME
Bibliographic record
Abstract
Objective: Hypertension (HTN), metabolic syndrome (MetS) and chronic kidney disease (CKD) are global health disorders that are epidemiologically associated. The immune system plays a role in hypertension and target organ damage. MicroRNAs are crucial post-transcriptional regulators of immune cell development and function. We hypothesized that microRNAs play a role in activation of immune cells in hypertension with target organ damage in humans. Design and method: Normotensive subjects (NTN) and patients with HTN associated or not with at least 2 other features of the MetS or with CKD were studied (n = 15–16). Peripheral blood mononuclear cells (PBMCs) were isolated, RNA extracted, small and total RNA sequencing (RNA-seq) done using Illumina HiSeq-2500 and data analyzed using a systems biology approach. Differentially expressed (DE) microRNAs and mRNAs were identified with fold change (FC) > 2 and > 1.5, respectively, and P < 0.005. The most representative DE miRNA isoforms with RNA-seq count number (CN) > 500, and with predicted targets by TargetScan with CN> 300 were validated by reverse transcription-quantitative PCR (RT-qPCR) in PBMCs. Results: RNA-seq identified DE microRNAs and mRNAs in HTN (22 and 19), MetS (57 and 401) and CKD (6 and 26) compared to NTN. Three of 14 selected miRNAs were validated by RT-qPCR. miR-409–5p and miR-411–5p were decreased respectively by 46% (P < 0.05) and 60% (P < 0.001), whereas the novel miR-pl-86 was increased 2-fold (P < 0.05) in MetS vs NTN. RT-qPCR data showed that tubulin alpha 1a (TUBA1A) predicted as mRNA target for miR-409–5p and miR-411–5p was increased 1.9-fold in MetS vs NTN group (P < 0.05). However, there was no correlation between RT-qPCR and RNA-seq data for TUBA1A. RT-qPCR data validated the decrease of 4 predicted miR-pl-86 targets. WD repeat domain 89 (WDR89), Dmx like 1 (DMXL1), zinc finger protein 600 (ZNF600) and NOC3-like DNA replication regulator (NOC3L) were decreased by ≧ 50% in MetS vs NTN (P < 0.05). RT-qPCR data demonstrated a correlation with RNA-seq data for miR-pl-86 (R2 = 0.37, P < 5.5E-07, n = 56), WDR89 (R2 = 0.29, P < 1.4E-05, n = 57), DMXL1 (R2 = 0.33, P < 2.7E-06, n = 57), ZNF600 (R2 = 0.25, P < 7.9E-05, n = 57), and NOC3L (R2 = 0.27, P < 3.5E-05, n = 57). Conclusion: This study identified one up-regulated novel microRNA and 4 down-regulated mRNA targets in PBMCs of patients with HTN and MetS. The role of this miRNA and mRNAs in immune cells of HTN patients with MetS needs to be determined.
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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 | 0.000 |
| 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) | 0.002 | 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".