Evidence map›Paper›PMID 30393374›Full record

ArticleThe pharmacogenomics journal2019

Iatrogenic hypertension: a bioinformatic analysis.

Alon Botzer, Yoram Finkelstein, Ehud Grossman, John Moult, Ron Unger

Abstract read
PubMed Publisher
In one paragraph

Article in The pharmacogenomics journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 34% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 2 countries.

Alon BotzerThe Mina & Everard Goodman Faculty of Life Sciences, Bar Ilan University, Ramat Gan, Israel.
Yoram FinkelsteinNeurology and Toxicology Service and Unit, Shaare Zedek Medical Center, Jerusalem, Israel.
Ehud GrossmanDepartment of Internal Medicine D and Hypertension Unit, The Chaim Sheba Medical Center, Tel-Hashomer, Ramat Gan, Israel.
John MoultInstitute for Bioscience and Biotechnology Research and Department of Cell Biology and Molecular Genetics, University of Maryland, Rockville, MD, USA.
Ron UngerThe Mina & Everard Goodman Faculty of Life Sciences, Bar Ilan University, Ramat Gan, Israel. ron@biomodel.os.biu.ac.il.
Bar-Ilan University · ILAdvanced Bioscience Laboratories (United States) · USShaare Zedek Medical Center · ILSheba Medical Center · IL

Funding

Mechanisms underlying complex trait human diseaseR01GM104436 · NIGMS · UNIV OF MARYLAND, COLLEGE PARK · PI MOULT, JOHN · 2013 to 2016
$1.1M
NIGMS NIH HHS R01 GM104436NIH HHS R01 GM1044367
6 · The paper itself

Abstract

It is well known that a myriad of medications and substances can induce side effects that are related to blood pressure (BP) regulation. This study aims to investigate why certain drugs tend to cause iatrogenic hypertension (HTN) and focus on drug targets that are implicated in these conditions.Databases and resources such as SIDER, DrugBank, and Genomatix were utilized in order to bioinformatically investigate HTN-associated drug target-genes for which HTN is a side effect. A tree-like map was created, representing interactions between 198 human genes that relate to the blood pressure system. 72 HTN indicated drugs and 160 HTN-inducing drugs were investigated. HTN-associated genes affected by these drugs were identified. HTN indicated drugs, which target nearly all branches of the interaction tree, were shown to exert an effect on most functional sub-systems of the BP regulatory system; and specifically, for the adrenergic and dopaminergic receptor pathways. High prevalence (25 genes) of shared targets between the HTN indicated and HTN-inducing drug categories was demonstrated. We focus on six drug families which are not indicated for HTN treatment, yet are reported as a major cause for blood pressure side effects. We show the molecular mechanisms that may lead to this iatrogenic effect. Such an analysis may have clinical implications that could allow for the development of tailored medicine with fewer side effects.

Indexed as

Antihypertensive AgentsBlood PressureComputational BiologyHumansHypertensionPrevalenceAntihypertensive Agents

Identifiers

PMID30393374
OpenAlexW2899503482

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.