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Body mass index stratification optimizes polygenic prediction of type 2 diabetes in cross-biobank analyses (Okada G, in Nat Gen.)


Genomic information is used to predict the risk of developing type 2 diabetes. However, the scarcity of genomic information from Japanese subjects compared to Westerners is concerning to researchers. This scarcity of data may potentially lead to reduced accuracy in predicting the risk of type 2 diabetes and could contribute to a decline in the future of genomic medicine in Japan.

Despite the limited data, the research group led by Yukinori Okada (WPI-IFReC/Graduate School of Medicine, Osaka University/Graduate School of Medicine, The University of Tokyo/RIKEN) succeeded in improving the predictive accuracy by incorporating body mass index (BMI) into the genomic information. Their approach improves the ability to determine whether an individual is likely to develop type 2 diabetes.

(online publishing in Nature Genetics on June 11, 2024)


Prof. Yukinori Okada

Statistical Immunology