What question did this study set out to answer?

The study aims to uncover genetic factors related to programmed cell death that influence asthma, COPD, and lung function.

March 2, 2026International Journal of COPD0 citationsOpen Access

The Role of Programmed Cell Death–Related Genes in Asthma, Chronic Obstructive Pulmonary Disease, and Lung Function: A Multi-Omics Mendelian Randomization Study

TJTanao Ji YLYue Lv JGJun Gu

Key Points

The study aims to uncover genetic factors related to programmed cell death that influence asthma, COPD, and lung function.
Conducted a multi-omics analysis integrating GWAS, mQTL, eQTL, and pQTL data.
Applied Summary Data-Based Mendelian Randomization and colocalization analyses to determine causality.
Performed transcriptome-wide association studies and tissue-specific analyses for external validation.
Executed enrichment analysis to identify relevant biological pathways.
Conducted drug prediction and molecular docking analyses on candidate compounds.
Identified six programmed cell death-related genes associated with respiratory traits.
ERBB3, SFRP1, and FGFR1 showed strong links to COPD and lung function metrics in never-smokers.
HSPA1B and MAPK3 were associated with asthma risk and COPD risk, respectively.
IDUA was related to overall asthma, categorizing it as a potential biomarker.
Molecular docking analyses indicated stable binding interactions for selected candidate drugs.

Abstract

Purpose: Programmed cell death (PCD) has been linked to asthma, chronic obstructive pulmonary disease (COPD) and lung function, but the underlying genetic determinants remain unclear. Patients and Methods: A comprehensive multi-omics analysis was conducted by integrating genome-wide association studies (GWAS) with methylation quantitative trait loci (mQTL), expression quantitative trait loci (eQTL), and protein quantitative trait loci (pQTL) data. To determine the causality between exposures and respiratory traits, Summary Data-Based Mendelian Randomization (SMR) and colocalization analyses were applied. External validation was performed using replication cohorts, along with transcriptome-wide association studies (TWAS), gene-based analysis, and tissue-specific analysis. Additionally, enrichment analysis was carried out to identify biological pathways linked to respiratory traits. To explore potential therapeutic targets, drug prediction and molecular docking analyses were employed to assess the pharmacological feasibility of candidate compounds. Results: Through the integration of multi-omics analysis, we identified six PCD-related genes associated with respiratory traits. ERBB3, SFRP1, and FGFR1 demonstrated tier 1 evidence, linking them to COPD in never-smokers, forced expiratory volume in 1 second (FEV1), and FEV1/forced vital capacity (FVC), respectively. Additionally, HSPA1B and MAPK3 were classified as tier 2 genes, associated with non-allergic asthma risk and overall COPD risk, respectively. IDUA, categorized as a tier 3 gene, was related to overall asthma. These genes play critical roles in apoptotic signaling, mesenchymal development, and molecular binding processes, emphasizing their biological significance. Additionally, molecular docking demonstrated stable binding for candidate drugs and proteins encoded by identified genes. Conclusion: Our study offers critical insights into the genetic basis of asthma, COPD, and lung function by identifying six genes as potential biomarkers and therapeutic targets, contributing to the development of more effective interventions for these respiratory traits. Keywords: respiratory diseases, multi-omics, genetics, quantitative trait loci

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