Integrative genomics analysis of various omics data and networks identify risk genes and variants vulnerable to childhood-onset asthma

BMC Med Genomics. 2020 Aug 31;13(1):123. doi: 10.1186/s12920-020-00768-z.

Abstract

Background: Childhood-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.

Methods: In 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.

Results: Based 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.

Conclusions: We 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.

Keywords: Asthma; GWAS; Gene expression; Genetic variants; Risk genes.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age of Onset
  • Asthma / genetics*
  • Asthma / pathology*
  • Biomarkers / analysis*
  • Case-Control Studies
  • Child
  • Computational Biology / methods*
  • Gene Expression Profiling
  • Gene Regulatory Networks*
  • Genome-Wide Association Study
  • Humans
  • Phenotype
  • Polymorphism, Single Nucleotide*
  • Quantitative Trait Loci
  • Risk Factors
  • Transcriptome*

Substances

  • Biomarkers