One of the most important goals of studying genetics is to find genes that are involved with diseases. The problem is that most diseases aren’t caused by a single gene or mutation. They’re the result of complex interactions among dozens, if not hundreds or thousands of genes, plus environmental factors, lifestyle, and a host of other variables. That flood of genes creates a needle-in-a-haystack problem.
A growing view among geneticists holds that nearly every gene active in the relevant tissue plays some part in a disease, but the vast majority act only indirectly and from a distance, nudging a much smaller set of "central" genes that sit at the heart of the disease. Those central genes are the ones that directly drive the biology and therefore are the ones most worth targeting with drugs. Until now, though, scientists had no reliable way to pick them out of the crowd and experimentally test them.
An interdisciplinary team of researchers at UChicago and Columbia University developed a new computational tool that could make the challenge of finding genes most directly related to disease much easier. In a paper published in Cell, they showed how this tool was able to identify 21 genes related to asthma, most of which hadn’t been discovered by other methods. The researchers also used both CRISPR gene-editing screens and mouse models to validate that these genes lead to asthma phenotypes and demonstrated that two of the genes are in the same pathway involved in fatty acid metabolism and protein palmitoylation, which hasn’t yet been studied for asthma.
The study, “Trans-regulatory gene mapping prioritizes disease drivers in asthma,” was primarily supported by the National Institutes of Health. Additional authors include Peixin Tian from the First Affiliated Hospital of Kunming Medical University, China; Zining Qi, Jiaqi Zhao, Li Zhang, Qilong Tan, Jinghui Li, Alexis G. Thornburg, Noboru J. Sakabe, Mark Minogue, Zachary T. Weber, Bohao Chen, Cezary Ciszewski, Xin He, Hardik Shah, and Carole Ober from UChicago; Ashley N. Michael and Donata Vercelli from the University of Arizona; and co-senior author Zhonghua Liu from Columbia University.
By Matt Wood, originally published August 17, 2026