Human genomics · 2025
Genome-wide association study of lung function decline using elastic-net regression: a prospective analysis in Korean cohort.
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Bae Eunhye, Oh Sohee, Lee Jung-Kyu, Heo Eun Young, Kim Deog Kyeom, Lee Hyun Woo
Аннотация
BACKGROUND: A rapid decline in forced expiratory volume in one second (FEV1) can lead to chronic airway disease and is associated with poor prognosis. This study aims to identify single nucleotide polymorphisms (SNPs) associated with the annual rate of FEV1 decline, investigate the differential effects based on various phenotypes, and develop a genetic risk score (GRS) for predicting rapid FEV1 decline.
METHODS: We conducted a genome-wide association study (GWAS) within the prospective Korean Genome and Epidemiology Study (KoGES) cohort. The association of each SNP with the annual decline rate of FEV1 was assessed using a linear regression model. We employed elastic-net regression analysis to identify SNPs associated with FEV1 decline and developed a GRS.
RESULTS: In 7,357 participants, we identified 21 SNPs associated with rapid FEV1 decline. Elastic-net regression model highlighted 12 SNPs with high likelihood of replication. Subgroup analyses revealed SNPs with different effects on FEV1 decline based on sex, age, and smoking history. The GRS, derived from the top 1,000 SNPs, was significant associated with annual FEV1 change (adjusted R² = 0.308). A GRS below - 17 indicated an accelerated decline in FEV1.
CONCLUSION: Our study identified novel SNPs associated with FEV1 decline and developed a GRS that could help predict individuals at higher risk of rapid FEV1 decline. The influence of genetic factors on the annual rate of decline in FEV1 may vary depending on phenotypic characteristics.
METHODS: We conducted a genome-wide association study (GWAS) within the prospective Korean Genome and Epidemiology Study (KoGES) cohort. The association of each SNP with the annual decline rate of FEV1 was assessed using a linear regression model. We employed elastic-net regression analysis to identify SNPs associated with FEV1 decline and developed a GRS.
RESULTS: In 7,357 participants, we identified 21 SNPs associated with rapid FEV1 decline. Elastic-net regression model highlighted 12 SNPs with high likelihood of replication. Subgroup analyses revealed SNPs with different effects on FEV1 decline based on sex, age, and smoking history. The GRS, derived from the top 1,000 SNPs, was significant associated with annual FEV1 change (adjusted R² = 0.308). A GRS below - 17 indicated an accelerated decline in FEV1.
CONCLUSION: Our study identified novel SNPs associated with FEV1 decline and developed a GRS that could help predict individuals at higher risk of rapid FEV1 decline. The influence of genetic factors on the annual rate of decline in FEV1 may vary depending on phenotypic characteristics.