Isabella M Salamone, Peixin Tian, Zining Qi, Jiaqi Zhao, Li Zhang, Qilong Tan, Jinghui Li, Ashley N Michael, Alexis G Thornburg, Noboru J Sakabe, Mark Minogue, Zachary T Weber, Bohao Chen, Cezary Ciszewski, Xin He, Hardik Shah, Donata Vercelli, Carole Ober, Hening Lin, Zhonghua Liu, Marcelo A Nóbrega, Xuanyao Liu
Deciphering which genes are most important to disease etiology is a central challenge in human genetics. While genome-wide association studies have cataloged thousands of variants, it's been proposed that most are indirect regulators of a limited, currently unidentified set of central disease-driving genes, defined here as disease-proximal genes (DPGs). Here, we introduce DANDELION, a mediation-inspired statistical framework that prioritizes DPGs by integrating trans-regulatory effects from disease-relevant tissues with gene-level burden from whole-exome sequencing. Applying DANDELION to asthma uncovers novel DPGs that escape detection by conventional methods. CRISPR screens in epithelial and T cells find that most DPGs regulate key asthma-related cellular phenotypes. We also demonstrate that loss of two DPGs, SLC27A3 and SCD, affects inflammation and airway remodeling in a mouse model of allergic asthma. Our study establishes DANDELION as a powerful framework for prioritizing novel, therapeutically actionable genes and pathways underlying disease pathogenesis.