Evidence map›Paper›PMID 34132494›Full record

ArticleCPT: pharmacometrics & systems pharmacology2021

Network module-based drug repositioning for pulmonary arterial hypertension.

Rui-Sheng Wang, Joseph Loscalzo

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in CPT: pharmacometrics & systems pharmacology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.5field-weighted citation impact, top 10% 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

16 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
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  8. Disease gene prioritization with quantum walks.Bioinformatics (Oxford, England) · 2024
    Article
  9. Article
  10. Review
  11. Article
  12. Association Between Circulating CD4Journal of cardiovascular translational research · 2023
    Article
  13. Article
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  15. Review
  16. Network module-based drug repositioning for pulmonary arterial hypertension.CPT: pharmacometrics & systems pharmacology · 2021
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Rui-Sheng WangDepartment of Medicine, Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0003-4920-4357
Joseph LoscalzoDepartment of Medicine, Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0002-1153-8047
Brigham and Women's Hospital · US

Funding

Boston Biomedical Innovation CenterU54HL119145 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI GOLAN, DAVID E., LOSCALZO, JOSEPH · 2013 to 2021
$18.8M
Center for Integrated Approaches to Undiagnosed DiseasesU01HG007690 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI LOSCALZO, JOSEPH · 2014 to 2022
$10.4M
L-2-Hydroxyglutarate and Metabolic Remodeling in HypoxiaR01HL155107 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI Joseph Loscalzo · 2021 to 2026
$4.1M
NHGRI NIH HHS U01 HG007690NHLBI NIH HHS R01 HL155107NHLBI NIH HHS U54 HL119145
6 · The paper itself

Abstract

Pulmonary arterial hypertension (PAH) is a progressive disorder characterized by pulmonary vascular remodeling leading to increased pulmonary vascular resistance and pulmonary arterial pressure. PAH is a highly morbid cardiopulmonary disease adversely affecting lifespan and quality of life. Despite increased awareness and advances of medical therapies in recent decades, long-term prognosis and survival remain poor for patients with PAH. Novel therapies that can target the underlying pathobiology of PAH and reverse pulmonary vascular remodeling are clearly needed. In this study, we develop a network module-based framework to examine potential drug repositioning for PAH. The rationale for this approach is that in order to have therapeutic effects, the targets of potential drugs must be significantly proximate to the disease module of interest in the human protein-protein interactome. Based on 15 existing drugs for treating PAH, our framework integrates drug-drug interactions, drug-drug chemical similarity, drug targets, and PAH disease proteins into the human interactome, and prioritizes candidate drugs for PAH. We identified 53 drugs that could potentially be repurposed for PAH. Many of these candidates have strong literature support. Compared to black-box-like machine learning models, network module-based drug repositioning can provide mechanistic insights into how repositioned drugs can target the underlying pathobiological mechanisms of PAH.

Indexed as

Drug InteractionsDrug RepositioningHumansMachine LearningPulmonary Arterial Hypertension

Identifiers

PMID34132494
PMCPMC8452304
OpenAlexW3172563354

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.