DANDELION Tool | How New Asthma Genes Were Identified

Tracking Asthma Drivers With DANDELION

Geneticists long suspected that only a small group of central genes directly dictate disease, while the vast majority act as distant, indirect observers. Scientists at the University of Chicago and Columbia University created a computational tool named DANDELION to bridge this gap. Their findings appeared in a report published in Cell on August 21, 2026. This tool isolates disease-proximal genes that exist within complex regulatory networks, moving beyond the limitations of traditional genome-wide association studies.

Traditional methods like GWAS focus on variants with small effect sizes, often missing the core drivers of illness. DANDELION functions differently by mapping trans-regulatory networks where genetic effects cascade across chromosomes. Xuanyao Liu, assistant professor of medicine and human genetics, designed the tool to pinpoint genes that receive these distal signals. By analyzing data from the UK Biobank and human transcriptomes, the team identified 21 potential asthma genes. Nineteen of these candidates were previously unknown to researchers.

Experimental Validation of Candidate Genes

To prove the computational predictions held weight, the team turned to Marcelo Nóbrega at the University of Chicago. His laboratory uses experimental platforms to alter gene expression in asthma-relevant cells, including inflammatory cells and airway epithelial cells. Postdoctoral scholar Isabella Salamone led the wet-lab testing phase. When she evaluated the list generated by DANDELION, the results showed a measurable impact on cellular function that far exceeded expectations for distal genetic associations.

Two specific genes, SLC27A3 and SCD, displayed significant influence with opposing effects. Knocking out SLC27A3 provided protection against asthma-like phenotypes in both human cells and mouse models. Conversely, knocking out SCD increased susceptibility to inflammation. Human patient data mirrored these lab results, as patients with severe asthma showed increased SLC27A3 expression in their lung cells, while SCD expression remained lower.

Broad Implications for Future Drug Targets

Chemical biologist Hening Lin investigated why these two genes produced such clear results. His team discovered both genes participate in protein palmitoylation, a process involving the addition of fatty acid groups to proteins. This pathway is essential for immune signaling. By identifying this specific mechanism, the researchers established a direct link between lipid metabolism and asthma severity. The discovery offers a new angle for pharmaceutical intervention, potentially moving toward drugs that target SLC27A3 or modulate palmitoylation.

The research demonstrates how closing the gap between computational prediction and bench-top experiment yields tangible results. Liu intends to apply DANDELION to other chronic conditions like type 2 diabetes and inflammatory bowel disease. While GWAS provided a massive amount of raw data over the past two decades, the field struggled to find the specific protein targets needed for effective treatment. DANDELION addresses this by refining the search to genes that actually drive disease pathology rather than those that simply sit near a variant. The success of this study confirms that the future of genetic medicine relies on integrating diverse expertise across computing, molecular biology, and clinical chemistry.