ReviewFrontiers in pediatrics2019
Genomic Predictors of Asthma Phenotypes and Treatment Response.
Review in Frontiers in pediatrics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.
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.
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.
Who cites it
44 citing papers in PubMed, 94 citations in OpenAlex.
- Insights on inflammatory pathways and their cross-talk: a comprehensive review on asthma.Molecular biology reports · 2025Review
- Why Every Asthma Patient Tells a Different Story.Journal of clinical medicine · 2025Article
- Copy Number Variation in Asthma: An Integrative Review.Clinical reviews in allergy & immunology · 2025Review
- Evaluation of Polygenic Risk Score for Prediction of Childhood Onset and Severity of Asthma.International journal of molecular sciences · 2024Article
- Multifaceted roles of mitochondria in asthma.Cell biology and toxicology · 2024Review
- Asthma-Genomic Advances Toward Risk Prediction.Clinics in chest medicine · 2024Review
- Epigenomic partitioning of a polygenic risk score for asthma reveals distinct genetically driven disease pathways.The European respiratory journal · 2024Article
- Exosomes in asthma: Underappreciated contributors to the pathogenesis and novel therapeutic tools.Immunity, inflammation and disease · 2024Review
- Current Challenges in Pediatric Asthma.Children (Basel, Switzerland) · 2024Review
- Unraveling the Complexity of Asthma: Insights from Omics Approaches.Biomedicines · 2024Article
- Article
- Asthma exacerbations and eosinophilia in the UK Biobank: a genome-wide association study.ERJ open research · 2024Article
- Association of interleukin-13 gene single nucleotide polymorphism rs1800925 with allergic asthma in Asian population: A meta-analysis.Asia Pacific allergy · 2023Article
- Difficult-to-treat asthma patients from ethnic minority groups in central England are at an enhanced risk of house dust mite sensitisation.Clinical and translational allergy · 2023Article
- Genomics of Treatable Traits in Asthma.Genes · 2023Review
- Severe Asthma and Biological Therapies: Now and the Future.Journal of clinical medicine · 2023Review
- Gene-Smoking Interaction Analysis for the Identification of Novel Asthma-Associated Genetic Factors.International journal of molecular sciences · 2023Article
- Asthma Exacerbations: The Genes Behind the Scenes.Journal of investigational allergology & clinical immunology · 2023Review
- Epigenome-Wide Association Studies of the Fractional Exhaled Nitric Oxide and Bronchodilator Drug Response in Moderate-to-Severe Pediatric Asthma.Biomedicines · 2023Article
- Multi-ancestry meta-analysis of asthma identifies novel associations and highlights the value of increased power and diversity.Cell genomics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Asthma is a complex respiratory disease considered as the most common chronic condition in children. A large genetic contribution to asthma susceptibility is predicted by the clustering of asthma and allergy symptoms among relatives and the large disease heritability estimated from twin studies, ranging from 55 to 90%. Genetic basis of asthma has been extensively investigated in the past 40 years using linkage analysis and candidate-gene association studies. However, the development of dense arrays for polymorphism genotyping has enabled the transition toward genome-wide association studies (GWAS), which have led the discovery of several unanticipated asthma genes in the last 11 years. Despite this, currently known risk variants identified using many thousand samples from distinct ethnicities only explain a small proportion of asthma heritability. This review examines the main findings of the last 2 years in genomic studies of asthma using GWAS and admixture mapping studies, as well as the direction of studies fostering integrative perspectives involving omics data. Additionally, we discuss the need for assessing the whole spectrum of genetic variation in association studies of asthma susceptibility, severity, and treatment response in order to further improve our knowledge of asthma genes and predictive biomarkers. Leveraging the individual's genetic information will allow a better understanding of asthma pathogenesis and will facilitate the transition toward a more precise diagnosis and treatment.
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Registered trials
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.