Identifying cross-tissue molecular targets of lung function by multi-omics integration analysis from DNA methylation and gene expression of diverse human tissues

• Published in: BMC genomics Vol. 26; no. 1; pp. 289 - 15
• Main Authors: Peng, Shisheng, Fang, Jinlong, Mo, Weiliang, Hu, Guodong, Wu, Senquan
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 24.03.2025; BioMed Central; BMC
• Subjects: Bayesian analysis; Biological analysis; Blood; Blood cells; CD46 antigen; Chronic obstructive pulmonary disease; Cross-tissue targets; Datasets; Deoxyribonucleic acid; DNA; DNA Methylation; Epigenetics; Gene expression; Gene Expression Profiling; Gene Expression Regulation; Gene loci; Gene mapping; Genes; Genetic analysis; Genetic aspects; Genetic research; Genome-wide association studies; Genome-Wide Association Study; Genomes; Human tissues; Humans; Lung - metabolism; Lung - physiology; Lung diseases; Lung function; Lungs; Methylation; Multi-omics analysis; Multiomics; Organ Specificity - genetics; Phenotypes; Physiological aspects; Protein expression; Proteins; Quantitative Trait Loci; Respiratory function; Tissues; China; DNA methylation; Lung function; Cross-tissue targets; Gene expression; Multi-omics analysis
• ISSN: 1471-2164; 1471-2164
• DOI: 10.1186/s12864-025-11476-2

Previous studies have reported several genetic loci associated with lung function. However, the mediating mechanism between these genetic loci and lung function phenotype is rarely explored. In this research, we used a cross-tissue multi-omics post-GWAS analysis to explain the associations between DNA methylation, gene expression, and lung function. We conducted integration analyses of lung function traits using genome-wide association study (GWAS) summary data alongside expression quantitative trait loci (eQTLs) and DNA methylation quantitative trait loci (mQTLs) derived from whole blood, utilizing multi-omics SMR and Bayesian colocalization analysis. Considering the genetic differences of tissues, we replicated the shared causal signals of eQTLs and lung function in 48 diverse tissues and the shared causal signals of mQTLs and lung function in 8 diverse tissues. Multi-trait colocalization analyses were utilized to identify the causal signals between gene expression in blood, blood cell traits, and lung function, as well as between cross-tissue gene expression in diverse tissues and lung function. Eight genes from blood tissue were prioritized as FEV1 causal genes using multi-omics SMR analysis and COLOC colocalization analysis: EML3, UBXN2A, ROM1, ZBTB38, RASGRP3, FAIM, PABPC4, and SNIP1. Equally, five genes (CD46, EML3, UBXN2A, ZBTB38, and LMCD1) were prioritized as FVC causal genes and one gene (LMCD1) was prioritized as FEV1/FVC causal genes. The causal signals between 8 genes (EML3, ROM1, UBXN2A, ZBTB38, RASGRP3, FAIM, PABPC4, and CD46) and lung function were successfully replicated in diverse tissues. More importantly, MOLCO colocalization analysis showed that 3 genes (CD46, LMCD1, and ZBTB38) expression in blood, blood cell traits, and lung function traits shared the same causal signals. Finally, through cross-tissue colocalization analysis of multiple traits, we found that the heart-lung axis EML3 expressions and lung function mediate the same causal signal. This study identified potential cross-tissue molecular targets associated with lung function traits from DNA methylation and gene expression of diverse tissues and explored the probable regulation mechanism of these molecular targets. This provides multi-omics and cross-tissue evidence for the molecular regulation mechanism of lung function and may provide new insight into the influence of crosstalk between organs and tissues on lung function.