Identifying key genes in COPD risk via multiple population data integration and gene prioritization

Area of Science:

• Genetics
• Pulmonology
• Bioinformatics

Background:

• Chronic obstructive pulmonary disease (COPD) is a major global health concern with high prevalence and mortality.
• Genome-wide association studies (GWAS) have identified COPD-associated genetic loci, but challenges exist in multi-population analyses due to differing ancestral genetic compositions.
• Lung function measurements serve as key indicators for COPD risk prediction.

Purpose of the Study:

• To identify protein-coding genes associated with COPD using a multi-population gene prioritization approach.
• To re-evaluate lung function GWAS data from Japanese and European populations by prioritizing genes within each cohort.
• To compare gene prioritization with standard meta-analysis for detecting COPD-associated genetic variants.

Main Methods:

• Utilized lung function GWAS data from Japanese and European populations.
• Applied a multi-population gene prioritization approach to analyze GWAS data separately for each population.
• Compared results with a standard meta-analysis to assess the effectiveness of the prioritization method.

Main Results:

• Identified significant single nucleotide variants (SNPs) in both Japanese (9 significant SNPs, 4 lead SNPs in 3 loci) and European (17 independent significant SNPs, 5 lead SNPs in 21 loci) populations.
• The gene prioritization approach identified 28 common genes between the Japanese and European prioritized gene lists.
• A standard meta-analysis identified 18 common genes, indicating the prioritization method detected additional associations.

Conclusions:

• The gene prioritization approach using trans-ethnic linkage disequilibrium (LD) can detect novel COPD-associated genes missed by standard meta-analyses, especially in diverse populations.
• This method is a feasible strategy for identifying new genetic associations in multi-population GWAS data with genetic diversity.
• Findings suggest potential for developing generalized and population-specific diagnostic and treatment strategies for COPD.