Evidence map›Paper›PMID 35434004›Full record

ReviewAnnals of translational medicine2022

Recent advances in pharmacogenomics research of anti-asthmatic drugs: a narrative review.

Jie Li, Chen Qiu

Open access · diamondAbstract readReview
In one paragraph

Review in Annals of translational medicine, 2022. 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
0.4field-weighted citation impact, top 43% 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, 3 citations in OpenAlex.

  1. Future directions in asthma pharmacogenomics.Annals of translational medicine · 2022
    Article
  2. Towards precision drug therapy in asthma.Annals of translational medicine · 2022
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Jie LiKey Laboratory of Shenzhen Respiratory Disease, Shenzhen Institute of Respiratory Disease, Shenzhen People's Hospital (The First Affiliated Hospital of Southern University of Science and Technology, The Second Clinical Medical College of Jinan University), Shenzhen, China.
Chen QiuKey Laboratory of Shenzhen Respiratory Disease, Shenzhen Institute of Respiratory Disease, Shenzhen People's Hospital (The First Affiliated Hospital of Southern University of Science and Technology, The Second Clinical Medical College of Jinan University), Shenzhen, China.
Southern University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objective: Bronchial asthma, a common respiratory disease in children and young adults, is characterized by hyperresponsiveness and reversible narrowing of the airways which manifest clinically as shortness of breath, cough, and/or wheezing. Although its pathogenic mechanism remains unknown, it's known that asthma patients have substantial interindividual variability in drug responsiveness, among which genetic factors play key roles. For improving the understanding of the biological mechanism of asthma and useful recognition of diagnostic and therapeutic targets, and the main purpose of this article is to optimize drug selection by analyzing genes associated with different drug responsiveness in asthmatic patients through the use of genomic techniques. Methods: β2-agonists, inhaled corticosteroids (ICS), and leukotriene modulators are the most commonly used to treat asthma, and major genetic variations associated with differential response to these three drugs were identified via candidate gene association analysis, genome-wide association study (GWAS), and RNA sequencing. Key Content and Findings: Genomics focuses on the effects of genetic variations in a group of genes. Most current studies have focused on the effect of single gene polymorphisms on drug efficacy, but the pharmacogenomics of asthma is inherently complex, with each factor having a small effect on drug responsiveness, and no single locus has yet been able to predict the variability in drug responsiveness. Conclusions: According to epidemiological researches, a worldwide increase in the prevalence of bronchial asthma over the past four decades was shown. Genomic approaches can be used to screen for genetic variants associated with drug response. Stratifying patients prior to treatment helps to optimize drug selection, maximize the effectiveness of individual treatment, and improve clinical outcomes.

Indexed as

Bronchial asthmagenetic variantsgenomicssingle nucleotide polymorphisms

Identifiers

PMID35434004
PMCPMC9011285
OpenAlexW4224275402

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.