Jinyoung Byun

This paper develops a polygenic score for smoking persistence and finds it is associated with earlier or later cessation ages across diverse populations.

The paper introduces a machine learning framework to detect high-order genetic interactions in GWAS by encoding decision paths from classification trees as features, improving model accuracy and interpretability.

The paper presents an isoform-level lung cell atlas using single-cell long-read RNA-sequencing, revealing genetic effects on isoform regulation that improve cell-type classification and identify novel variants associated with lung cancer risk.

The paper constructs a single-cell eQTL dataset from Asian never-smokers, identifying alveolar cell-specific genes linked to lung cancer susceptibility.

This study identifies smoking-associated natural killer cell subsets in NSCLC that correlate with survival and response to neoadjuvant chemoimmunotherapy, suggesting their use in therapeutic stratification.

This paper improves genetic discovery and polygenic risk prediction for respiratory diseases by analyzing multiple traits and ancestries, identifying novel loci and developing a new polygenic risk score method.

This paper introduces a formal statistical replication analysis to reduce false positives in lung cancer GWAS, finding it significantly lowers false discovery rate and improves polygenic risk score efficiency.

The paper develops polygenic risk scores to stratify lung cancer and smoking cessation risk, showing significant odds ratios in diverse populations and planning clinical trials to evaluate interventions.

The paper identifies twelve novel genetic risk loci for lung cancer subtypes through multi-ancestry GWAS and shows smoking-independent genetic risk.

The paper identifies cell-type specific lung cancer susceptibility genes by integrating single-cell multi-omics data with GWAS loci.

This study identifies 13 genome-wide significant loci associated with SARS-CoV-2 infection or severe COVID-19 through a global meta-analysis of 49,562 patients.