Suzuki Ken

This paper develops and validates multi-ancestry polygenic risk scores for type 2 diabetes prediction and complications across diverse populations.

This study examines how genetic and lifestyle factors together influence the risk of developing type 2 diabetes in the UK Biobank population.

This study uses Mendelian randomization to show that higher glycemic traits are inversely associated with thoracic aortic diameters and reduced risk of aneurysm and dissection.

This study investigates causal links between T2D genetic clusters and non-cardiovascular comorbidities, identifying potential drug repurposing opportunities.

This study integrates multi-omics data to identify genetic variants and molecular mechanisms associated with type 2 diabetes and highlights potential drug targets.

This study identifies 1,289 genetic signals for type 2 diabetes in 2.5 million individuals, revealing distinct clusters linked to vascular complications and highlighting ancestry-specific genetic risk factors.

Cross-population GWAS of 220 phenotypes in BioBank Japan, UK Biobank, and FinnGen (n=628,000) identifies 5,343 previously unreported loci and decomposes summary statistics into latent genetic components for disease subtyping.

The paper reports in silico structural analysis of ethnic-specific PAX4 variants associated with type 2 diabetes in a Japanese population.

DEEP*HLA improves HLA allelic imputation for low-frequency alleles, enabling trans-ethnic MHC fine-mapping of type 1 diabetes with high accuracy.

A large-scale GWAS in 212,453 Japanese individuals identified 45 novel susceptibility loci for 22 diseases, highlighting the importance of non-European population studies.

This paper identifies 56 new type 2 diabetes loci in 433,540 East Asian individuals through a meta-analysis of GWAS data.