Trial reportThe Journal of allergy and clinical immunology2018
Differential connectivity of gene regulatory networks distinguishes corticosteroid response in asthma.
Trial report in The Journal of allergy and clinical immunology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled 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.
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
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.
- Systematic Literature Review of Systemic Corticosteroid Use for Asthma Management.American journal of respiratory and critical care medicine · 2020Pooled it
- Severe Asthma and Biological Therapies: Now and the Future.Journal of clinical medicine · 2023Review
- Heterogeneity of Treatment Response to Asthma.Advances in experimental medicine and biology · 2023Article
- Connections for Matters of the Heart: Network Medicine in Cardiovascular Diseases.Frontiers in cardiovascular medicine · 2022Review
- Constructing gene regulatory networks using epigenetic data.NPJ systems biology and applications · 2021Article
- Network and co-expression analysis of airway smooth muscle cell transcriptome delineates potential gene signatures in asthma.Scientific reports · 2021Article
- Drug Repurposing to Treat Glucocorticoid Resistance in Asthma.Journal of personalized medicine · 2021Article
- Gene regulatory network inference as relaxed graph matching.Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence · 2021Article
- Gene Targeting in Disease Networks.Frontiers in genetics · 2021Article
- Different Biological Pathways Between Good and Poor Inhaled Corticosteroid Responses in Asthma.Frontiers in medicine · 2021Article
- Molecular networks in Network Medicine: Development and applications.Wiley interdisciplinary reviews. Systems biology and medicine · 2020Review
- Understanding the Molecular Mechanisms of Asthma through Transcriptomics.Allergy, asthma & immunology research · 2020Review
- Precision Medicine in Childhood Asthma: Omic Studies of Treatment Response.International journal of molecular sciences · 2020Review
- Childhood asthma in the new omics era: challenges and perspectives.Current opinion in allergy and clinical immunology · 2020Review
- Network Medicine in the Age of Biomedical Big Data.Frontiers in genetics · 2019Review
- Genomic Predictors of Asthma Phenotypes and Treatment Response.Frontiers in pediatrics · 2019Review
- From systems biology to P4 medicine: applications in respiratory medicine.European respiratory review : an official journal of the European Respiratory Society · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundVariations in drug response between individuals have prevented us from achieving high drug efficacy in treating many complex diseases, including asthma. Genetics plays an important role in accounting for such interindividual variations in drug response. However, systematic approaches for addressing how genetic factors and their regulators determine variations in drug response in asthma treatment are lacking.
objectiveWe sought to identify key transcriptional regulators of corticosteroid response in asthma using a novel systems biology approach.
methodsWe used Passing Attributes between Networks for Data Assimilations (PANDA) to construct the gene regulatory networks associated with good responders and poor responders to inhaled corticosteroids based on a subset of 145 white children with asthma who participated in the Childhood Asthma Management Cohort. PANDA uses gene expression profiles and published relationships among genes, transcription factors (TFs), and proteins to construct the directed networks of TFs and genes. We assessed the differential connectivity between the gene regulatory network of good responders versus that of poor responders.
resultsWhen compared with poor responders, the network of good responders has differential connectivity and distinct ontologies (eg, proapoptosis enriched in network of good responders and antiapoptosis enriched in network of poor responders). Many of the key hubs identified in conjunction with clinical response are also cellular response hubs. Functional validation demonstrated abrogation of differences in corticosteroid-treated cell viability following siRNA knockdown of 2 TFs and differential downstream expression between good responders and poor responders.
conclusionsWe have identified and validated multiple TFs influencing asthma treatment response. Our results show that differential connectivity analysis can provide new insights into the heterogeneity of drug treatment effects.
Indexed as
Identifiers
What OpenQuestion holds
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.