Li-Ching Chang

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

The Taiwan Precision Medicine Initiative (TPMI) recruits a large cohort for genetic and electronic medical record studies to advance precision medicine.

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.

This study identifies 12,111 SNPs associated with height from 5.4 million individuals, explaining most common SNP-based heritability and showing ancestry-specific prediction accuracy.

This study identifies 277 T2D loci using diverse populations and improves fine-mapping to assess causal genes and mechanisms, enhancing clinical translation.

This study identifies 242 genetic loci for glycaemic traits using trans-ancestry meta-analysis, finding 99 novel loci and improved fine-mapping resolution compared to single-ancestry analyses.

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