ArticleBMC medical genomics2020
Integrative genomics analysis of various omics data and networks identify risk genes and variants vulnerable to childhood-onset asthma.
Article in BMC medical genomics, 2020. 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, 29 citations in OpenAlex.
- Mendelian randomization study shows a causal effect of asthma on epilepsy risk.Frontiers in immunology · 2023Pooled it
- Plasma metabolite association profiles for type 2 diabetes genetic clusters in Finnish men.Diabetologia · 2026Article
- The Ubiquitin-Proteasome System in Asthma: Mechanisms and Therapeutic Possibilities.Clinical reviews in allergy & immunology · 2025Review
- Genomics and multiomics in the age of precision medicine.Pediatric research · 2025Review
- Systematic dissection of pleiotropic loci and critical regulons in excitatory neurons and microglia relevant to neuropsychiatric and ocular diseases.Translational psychiatry · 2025Article
- Association of rs7216389 Polymorphism in Gasdermin B (GSDMB) With Childhood Asthma: A Case-Control Study.Cureus · 2025Article
- Asthma-Genomic Advances Toward Risk Prediction.Clinics in chest medicine · 2024Review
- Integration of human organoids single-cell transcriptomic profiles and human genetics repurposes critical cell type-specific drug targets for severe COVID-19.Cell proliferation · 2024Article
- Unspecified asthma, childhood-onset, and adult-onset asthma have different causal genes: a Mendelian randomization analysis.Frontiers in immunology · 2024Article
- Bioinformatics analysis of key biomarkers for bladder cancer.Biomedical reports · 2023Article
- Variants inFrontiers in genetics · 2023Article
- Identification ofComputational and structural biotechnology journal · 2023Article
- Integrating single-cell sequencing data with GWAS summary statistics reveals CD16+monocytes and memory CD8+T cells involved in severe COVID-19.Genome medicine · 2022Article
- Single cell sequencing analysis identifies genetics-modulated ORMDL3Journal of nanobiotechnology · 2021Article
- Leveraging auxiliary data from arbitrary distributions to boost GWAS discovery with Flexible cFDR.PLoS genetics · 2021Article
- Integrative genomics analysis reveals a 21q22.11 locus contributing risk to COVID-19.Human molecular genetics · 2021Article
- Genetic and Pathological Insights into the rs7216389 Polymorphism in Gasdermin B and Its Association with Childhood Asthma.Discoveries (Craiova, Romania)Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundChildhood-onset asthma is highly affected by genetic components. In recent years, many genome-wide association studies (GWAS) have reported a large group of genetic variants and susceptible genes associated with asthma-related phenotypes including childhood-onset asthma. However, the regulatory mechanisms of these genetic variants for childhood-onset asthma susceptibility remain largely unknown.
methodsIn the current investigation, we conducted a two-stage designed Sherlock-based integrative genomics analysis to explore the cis- and/or trans-regulatory effects of genome-wide SNPs on gene expression as well as childhood-onset asthma risk through incorporating a large-scale GWAS data (N = 314,633) and two independent expression quantitative trait loci (eQTL) datasets (N = 1890). Furthermore, we applied various bioinformatics analyses, including MAGMA gene-based analysis, pathway enrichment analysis, drug/disease-based enrichment analysis, computer-based permutation analysis, PPI network analysis, gene co-expression analysis and differential gene expression analysis, to prioritize susceptible genes associated with childhood-onset asthma.
resultsBased on comprehensive genomics analyses, we found 31 genes with multiple eSNPs to be convincing candidates for childhood-onset asthma risk; such as, PSMB9 (cis-rs4148882 and cis-rs2071534) and TAP2 (cis-rs9267798, cis-rs4148882, cis-rs241456, and trans-10,447,456). These 31 genes were functionally interacted with each other in our PPI network analysis. Our pathway enrichment analysis showed that numerous KEGG pathways including antigen processing and presentation, type I diabetes mellitus, and asthma were significantly enriched to involve in childhood-onset asthma risk. The co-expression patterns among 31 genes were remarkably altered according to asthma status, and 25 of 31 genes (25/31 = 80.65%) showed significantly or suggestively differential expression between asthma group and control group.
conclusionsWe provide strong evidence to highlight 31 candidate genes for childhood-onset asthma risk, and offer a new insight into the genetic pathogenesis of childhood-onset asthma.
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.