Chicago, IL — A groundbreaking study by researchers at the University of Chicago is shedding new light on the genetic roots of asthma, narrowing the gap between statistical associations and functional genetic causes of the disease.
While genome-wide association studies (GWAS) have previously identified hundreds of genomic regions linked to asthma, pinpointing which specific genetic variants actually cause the disease has remained elusive. This challenge — known as the “variant-to-function” gap — has limited the clinical utility of GWAS findings. Now, researchers have developed advanced computational tools to better identify which variants likely contribute to asthma and how they function biologically.
Published in Genome Medicine, the study reveals significant distinctions between the genetic mechanisms behind adult-onset and childhood-onset asthma, highlighting that the two may be driven by largely separate sets of genes. “The real uniqueness of our study is that the differences between childhood- and adult-onset asthma were evident at every level we looked at,” said co-senior author Carole Ober, PhD, Chair of Human Genetics at UChicago. “Even when the genomic region is the same, the actual variants and genes involved are often completely different.”
From Genetic Signals to Causal Insights
GWAS typically work by comparing the DNA of people with a disease to those without it, identifying differences that may point to disease risk. However, because many genetic variants are inherited together in blocks, determining which individual variant is causal is difficult. This challenge is compounded by the fact that most of these variants lie in non-coding regions of the genome, making their function hard to interpret.
To overcome these hurdles, graduate student Ethan Zhong, under the supervision of Ober and co-senior author Xin He, PhD, used “fine-mapping” — a statistical approach to estimate the likelihood that a given variant actually causes disease. Using data from the UK Biobank, a massive genetic repository of nearly 500,000 participants, Zhong applied this method to GWAS datasets for both types of asthma.
The team incorporated chromatin accessibility data — which reveals how open or “active” certain DNA regions are — to better assess which variants are likely regulating nearby genes. Open chromatin regions are often key to gene regulation, and variants within them are more likely to have functional consequences.
“When GWAS variants overlap with open chromatin in asthma-relevant cell types like lung epithelial cells, we have stronger evidence that these variants are biologically meaningful,” Zhong explained.
Linking Variants to Genes
Beyond chromatin data, the study also included expression quantitative trait loci (eQTLs), which connect genetic variants to gene expression levels, and chromatin interaction data from blood and lung cells. This comprehensive approach allowed researchers to link fine-mapped variants to their likely target genes.
The analysis identified 21 independent variant sets, or “credible sets,” for adult-onset asthma and 67 for childhood-onset asthma, with only 16% overlapping. This further supports the idea that adult and childhood asthma are largely genetically distinct conditions.
Researchers also identified cis-regulatory elements (CREs) — short DNA sequences that regulate nearby genes — tied to asthma: 62 for adult-onset and 169 for childhood-onset. Many of these were located in regions of open chromatin and were associated with immune and inflammatory responses, key pathways in asthma development.
To validate their findings, the team selected six candidate CREs and tested their regulatory effects in bronchial epithelial cells. Four showed a significant impact on gene expression, providing functional confirmation of their role in asthma.
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