Phenome-wide analysis of Taiwan Biobank reveals novel glycemia-related loci and genetic risks for diabetes

To explore the complex genetic architecture of common diseases and traits, we conducted comprehensive PheWAS of ten diseases and 34 quantitative traits in the community-based Taiwan Biobank (TWB). We identified 995 significantly associated loci with 135 novel loci specific to Taiwanese population. Further analyses highlighted the genetic pleiotropy of loci related to complex disease and associated quantitative traits. Extensive analysis on glycaemic phenotypes (T2D, fasting glucose and HbA(1c)) was performed and identified 115 significant loci with four novel genetic variants (HACL1, RAD21, ASH1L and GAK). Transcriptomics data also strengthen the relevancy of the findings to metabolic disorders, thus contributing to better understanding of pathogenesis. In addition, genetic risk scores are constructed and validated for absolute risks prediction of T2D in Taiwanese population. In conclusion, our data-driven approach without a priori hypothesis is useful for novel gene discovery and validation on top of disease risk prediction for unique non-European population. A phenome-wide association study and polygenic risk score analysis identifies several loci linked to metabolic disease and type 2 diabetes in the Taiwanese population.

Automated summary

This study conducted a comprehensive PheWAS to identify genetic loci associated with specific diseases and traits in the Taiwanese population, contributing to a better understanding of complex diseases and genetic pleiotropy. The findings were further supported by transcriptomics data, enhancing the relevance to metabolic disorders. Additionally, genetic risk scores were developed for predicting the absolute risk of type 2 diabetes in the Taiwanese population.