Decoding the genetic predisposition to asthma using epigenomics

Introduction: Asthma, an inflammatory airway disease, results from intricate interactions between genetics and environmental factors. High medical costs are mostly incurred by the 5-10% of patients requiring intensive treatment due to poor symptom control. Aims and objectives: We aim to highlight targets for phenotype-specific and personalized treatment of (severe) asthma by studying the genetic variants underlying asthma predisposition. Methods: We use the results of genome-wide association studies that analyze genotypes of large cohorts of asthma patients. These studies identify up to 179 asthma-associated loci in which ~99% of genetic variants reside in non-coding genomic regions—thereby largely obscuring direct links to susceptibility genes. To find cell-type specific links between genetic variants and genes, we use an integrated epigenomics approach based on active chromatin signatures (ATAC-seq/ChIP-seq data), 3D chromatin folding (Hi-C data) and gene expression patterns (RNA-seq data). Results: Systematically intersecting asthma-associated genetic variants with features of gene regulatory activity of 47 cell types revealed clusters of genetic loci linked to disease-relevant cell types. These included well-known gene-cell type pairs, e.g. the interleukin 33 locus and epithelial cells, and new associations involving mast cells, B or T cells, and even early blood cell precursors. We could also link genetic variants in large gene deserts to GATA3, which encodes a transcription factor driving inflammatory cytokine production in T helper 2 cells. Conclusions: We present a systematic way to translate genetic associations into tractable hypotheses, uncovering potentially new biological mechanisms relevant for asthma pathogenesis.