Evidence map›Paper›PMID 26126791›Full record

ArticlePhysiological genomics2015

MicroRNA network changes in the brain stem underlie the development of hypertension.

Danielle DeCicco, Haisun Zhu, Anthony Brureau, James S Schwaber, Rajanikanth Vadigepalli

Open access · greenAbstract read
In one paragraph

Article in Physiological genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.3field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Review
  8. Review
  9. Noncoding RNAs in Hypertension.Hypertension (Dallas, Tex. : 1979) · 2019
    Review
  10. Review
  11. Rostral Ventrolateral Medulla and Hypertension.Hypertension (Dallas, Tex. : 1979) · 2018
    Review
  12. Article
  13. Article
  14. Systemic leukotriene BThe Journal of physiology · 2016
    Article
  15. Article
  16. Review
  17. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Danielle DeCiccoDepartment of Pathology, Anatomy and Cell Biology, Daniel Baugh Institute for Functional Genomics/Computational Biology, Thomas Jefferson University, Philadelphia, Pennsylvania.
Haisun ZhuDepartment of Pathology, Anatomy and Cell Biology, Daniel Baugh Institute for Functional Genomics/Computational Biology, Thomas Jefferson University, Philadelphia, Pennsylvania.
Anthony BrureauDepartment of Pathology, Anatomy and Cell Biology, Daniel Baugh Institute for Functional Genomics/Computational Biology, Thomas Jefferson University, Philadelphia, Pennsylvania.
James S SchwaberDepartment of Pathology, Anatomy and Cell Biology, Daniel Baugh Institute for Functional Genomics/Computational Biology, Thomas Jefferson University, Philadelphia, Pennsylvania.
Rajanikanth VadigepalliDepartment of Pathology, Anatomy and Cell Biology, Daniel Baugh Institute for Functional Genomics/Computational Biology, Thomas Jefferson University, Philadelphia, Pennsylvania rajanikanth.vadigepalli@jefferson.edu.
Thomas Jefferson University · US

Funding

Modeling Central Autonomic Regulatory Network Adaptation to HypertensionR01HL111621 · NHLBI · THOMAS JEFFERSON UNIVERSITY · PI SCHWABER, JAMES, VADIGEPALLI, RAJANIKANTH · 2012 to 2015
$2.4M
Integrated Modeling of Adaptive Neuronal RegulationR01GM083108 · NIGMS · THOMAS JEFFERSON UNIVERSITY · PI SCHWABER, JAMES, VADIGEPALLI, RAJANIKANTH · 2009 to 2012
$1.5M
NHLBI NIH HHS R01 HL111621NHLBI NIH HHS R01HL-111621NIGMS NIH HHS R01 GM-083108
6 · The paper itself

Abstract

Hypertension is a major chronic disease whose molecular mechanisms remain poorly understood. We compared neuroanatomical patterns of microRNAs in the brain stem of the spontaneous hypertensive rat (SHR) to the Wistar Kyoto rat (WKY, control). We quantified 419 well-annotated microRNAs in the nucleus of the solitary tract (NTS) and rostral ventrolateral medulla (RVLM), from SHR and WKY rats, during three main stages of hypertension development. Changes in microRNA expression were stage- and region-dependent, with a majority of SHR vs. WKY differential expression occurring at the hypertension onset stage in NTS versus at the prehypertension stage in RVLM. Our analysis identified 24 microRNAs showing time-dependent differential expression in SHR compared with WKY in at least one brain region. We predicted potential gene regulatory targets corresponding to catecholaminergic processes, neuroinflammation, and neuromodulation using the miRWALK and RNA22 databases, and we tested those bioinformatics predictions using high-throughput quantitative PCR to evaluate correlations of differential expression between the microRNAs and their predicted gene targets. We found a novel regulatory network motif consisting of microRNAs likely downregulating a negative regulator of prohypertensive processes such as angiotensin II signaling and leukotriene-based inflammation. Our results provide new evidence on the dynamics of microRNA expression in the development of hypertension and predictions of microRNA-mediated regulatory networks playing a region-dependent role in potentially altering brain-stem cardiovascular control circuit function leading to the development of hypertension.

Indexed as

MicroRNAsAnimalsBrain StemGene Expression RegulationGene Regulatory NetworksHigh-Throughput Nucleotide SequencingHypertensionMaleRats, Inbred SHRRats, Inbred WKYMicroRNAsangiotensin IIbrain stemhypertensionmicroRNAneuroinflammation

Identifiers

PMID26126791
PMCPMC4556940
OpenAlexW2172540214

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.