New computational tool identifies hidden genes driving asthma

Researchers at Columbia University Mailman School of Public Health, in collaboration with investigators at the University of Chicago, have developed a new computational framework that helps scientists identify genes that play central roles in diseases such as asthma but are often overlooked by existing genetic analysis methods. The framework, called DANDELION, is a mediation-inspired computational approach that identifies disease-driving genes, providing a new way to uncover therapeutic targets. The study findings are published in the journal Cell.

One of the biggest challenges in genetics is determining which genes actually drive disease rather than simply being associated with it. DANDELION was designed to address that challenge by identifying genes that contribute directly to disease but are often missed by existing methods.

In a study of asthma, the researchers used DANDELION to identify a previously unrecognized biological process that appears to play a key role in driving the disease, revealing a potential new target for future treatments.

The study was co-led by Zhonghua Liu, ScD, assistant professor of Biostatistics at Columbia University Mailman School of Public Health; Marcelo A. Nóbrega, MD, PhD, professor in the Department of Human Genetics at the University of Chicago; and Xuanyao Liu, PhD, assistant professor in the Departments of Medicine and Human Genetics at the University of Chicago. The three investigators are equal-contributing senior authors of the study.

Current genetic approaches and large-scale studies often identify hundreds of DNA changes linked to disease risk but it can be difficult to determine which genes are actually causing the disease rather than simply being associated with it. DANDELION gives researchers a more effective way to pinpoint those genes and the biological pathways they control."

 Zhonghua Liu, ScD, Assistant Professor of Biostatistics, Columbia Mailman School

Genetic discoveries have become one of the strongest starting points for developing successful new medicines, according to Liu and colleagues. "The challenge is separating the genes that truly drive disease from the many genetic associations that are detected in large studies."

DANDELION integrates large-scale genetic data with trans-gene regulatory information from disease-relevant tissues to identify disease-driving genes overlooked by conventional approaches.

"This computational framework gives researchers a new way to uncover biological pathways that could become targets for future therapies," said Liu.

The researchers then applied DANDELION to asthma and combined the results with single-cell gene expression data from the Human Lung Cell Atlas to identify the lung cell types where the newly identified genes are most active.

The newly identified pathway involves protein palmitoylation, a cellular process that regulates how proteins function and where they are located within cells. Laboratory experiments showed that enzymes involved in this process influence asthma-related inflammation, suggesting they may represent promising targets for future therapies.

The researchers say DANDELION is designed to work beyond asthma. "Our findings suggest DANDELION can reveal clinically meaningful disease mechanisms that other approaches miss," Liu said. "We anticipate it will help researchers identify new therapeutic targets across many complex diseases."

The DANDELION software package and analysis code are publicly available at: https://www.github.com/mxxptian/DANDELION.