Method to identify genetic variations linked to asthma onset developed by University of Chicago

UChicago study combines genetic data with computational models to pinpoint likely genetic variations which cause asthma onset in both children and adults

Genome wide association studies (GWAS) have identified a large number of genome regions containing many thousands of genetic variations that have been linked to asthma. However, it remains unclear which variants have any causal link to the condition.

The ‘variant-to-function’ gap continues to be a significant challenge to the practical application and usefulness of genomic studies. Consequently, researchers have worked to develop tools that can make more sense of the results produced by GWAS.

A research team from the University of Chicago (UChicago) have combined empirical genetic information with computational models to examine the GWAS data for asthma onset in both adults and children.

Many genetic variants were identified in the study that had a high likelihood of causal link with both types of asthma, with the research also finding significant differences in the sets of genes that could be associated with adult-onset vs childhood-onset of asthma, showing relatively little commonality between the two sets.

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“The real uniqueness of our study is that the differences between childhood- and adult-onset asthma were evident at every level that we looked at,” said Professor Carole Ober, PhD, the Blum-Riese distinguished service professor and chair of human genetics at UChicago, who was also a co-senior author for the article.

GWAS is used in research to allow for the comparison of genomic sequences from a large group of people who have a disease with other sets of sequences from healthy individuals. Genetic differences seen in the disease group could indicate a risk increase for that disease to be examined further.

“You find out it's actually different variants that are contributing to asthma. Even when the GWAS locus looks the same, the genes functionally linked to these variants are also different. So, they're really quite different diseases,” Professor Ober added.

Most human diseases – including asthma – are not directly caused by a single genetic variant. They result from complex interactions among multiple genes, moderated by environmental factors and many other variables. Consequently, GWAS studies often produce too many variants across the genome to be of immediate use and need refinement.

Importantly, GWAS is indicative of association only, and not causality. In a given genomic region, variants will be highly correlated, because of a phenomenon called ‘linkage disequilibrium’.

Here DNA passes from one generation to the next in entire blocks, rather than as discrete variations. Therefore, variants nearby to each other tend to be correlated. Additionally, most of the genetic variants associated with diseases are located in non-coding regions of the genome, making their effects difficult to interpret.

In the study the team wanted to bridge the gap between variant-and-function in order to have more definitive insights into the biology that formed different data sets for asthma GWAS. A graduate researcher, Ethan Zhong, accessed UK Biobank data – a large-scale biomedical database and resource which contains anonymised genetic data from nearly half a million people in the UK – and applied a statistical methodology called ‘fine mapping’.

This approach was able to give an estimate of probability that a given genetic variant had a causal relationship with asthma.

These estimates included data on the accessibility of chromatin, the DNA and protein bundle that makes up chromosomes. A region’s involvement in regulation of gene expression will become more accessible and the chromatin is seen to ‘open’. Measurements of open chromatin can be used to indicate whether there is involvement of that region in regulatory activity. In combination with the probabilistic statistics a stronger case can be built to link a variant causally with asthma.

“GWAS association provides sets of variants associated with disease,” Zhong said.

“So, when those variants overlap with open chromatin regions in cell types that are relevant to asthma pathogenesis like lung epithelial cells, we think that they are more likely to be causal to these asthma phenotypes,” he said.

By also including data on expression quantitative trait loci (eQTLs), with genetic variants associated with differences in gene expression, and chromatin interactions from blood and lung cell types, Zhong was able to link fine-mapped variants to target genes and so build a list of genes which were a probable cause in the disease.

Fine-mapping analysis found 21 independent sets of variants – called ‘credible sets’ – in adults and 67 in children. Only 16% was shared between both. Zhong also looked for cis-regulatory elements (CREs) – short DNA sequences that control expression of nearby genes – that link to asthma. He found 62 candidate genes for adult-onset and 169 for childhood-onset. Open chromatin in different cell types was found in excess of 60%, along with genes indicated to immune and inflammatory responses.

The team, which included Associate Professor Xin He, PhD, a professor of human genetics and another co-senior author of the paper, selected six candidate CREs to test in bronchial epithelial cells to determine whether there was a regulatory effect with these variants. Four out of the six did so, indicating the work was getting closer to developing a process which could identify those cells involved in asthma.

The study was supported in part by a US National Institutes of Health grant to discover genes in asthma and allergy, in collaboration with Dr Marcelo Nobrega, A.N. Pritzker Professor of Human Genetics at UChicago; Dr. Nathan Schoettler, Assistant Professor of Medicine; and Dr. Anne Sperling, formerly of UChicago and now Professor of Medicine at the University of Virginia. Additional authors include Robert Mitchell, Christine Billstrand, Emma Thompson, Noboru J. Sakabe, Ivy Aneas, Isabella M. Salamone and Jing Gu.

For further reading please visit: 10.1186/s13073-025-01459-z