Common genetic variation influencing the human lung imaging phenotypes

作者：Meng Zhu, Lingbin Du, Lei Shi, Ji Chen, Chen Zhu, Ci Song, Lili Wu, Lingying Zhu, Jing Lü, Qun Zhang, Fei‐Yun Wu, Chen Jin, Yuanlin Mou, Qiao Li, Jiahao Zhang, Mingxuan Zhu, Jiaying Cai, Caochen Zhang, Yating Fu, Linnan Gong, Dong Hang, Juncheng Dai, Yue Jiang, Guangfu Jin, Zhibin Hu, Hongxia Ma, Xiangdong Cheng, Hongbing Shen · 发表于：Nature Communications · 年份：2025 · DOI：10.1038/s41467-025-64571-z · 被引用次数：3 · 研究领域：Congenital Diaphragmatic Hernia Studies、Congenital heart defects research、Radiomics and Machine Learning in Medical Imaging

Lung structures are critical for gas exchange and contribute to the pathogenesis of respiratory diseases, exhibiting notable lobe-specific heterogeneity. To investigate their genetic basis, we apply a deep-learning AI system and Pyradiomics to define lobe-specific lung CT imaging phenotypes, conducting genome-wide analyses in 35,469 participants from the Lung Imaging Genomics Initiative in China. We identify 36 loci associated with voxel intensities and 138 loci linked to three-dimensional shape. Functional annotation reveals significant enrichment of relevant genes in pathways regulating early fetal lung development and loci enriched in fetal lung regulatory elements. Genetic correlations are identified between lung structures and chronic respiratory diseases as well as lung function, with a number of loci showing colocalization. Mendelian randomization analyses suggest a causal role of lung structures in chronic lung diseases and extrapulmonary traits. This study provides new insights into the genetic architecture of lung structures and their links to diverse clinical outcomes. Lung structure contributes to respiratory disease risk and shows strong genetic regulation. Here, the authors identify genetic loci linked to lobe-specific lung CT features, revealing developmental pathways and causal links to chronic lung disease.