We defined 220 disease endpoints in Biobank Japan by mining the datasets in electronic health record and performed GWAS meta-analysis with the corresponding phenotypes in European populations, UK Biobank and FinnGen.
Using a set of GWAS summary statistics of diseases characterized from both European (UK Biobank and FinnGen) and East Asian (Biobank Japan) populations, we dissected latent DeGAs components of multi-ethnic association summary statistics. We annotated each component by pathway and cell-type enrichment as well as projection of metabolomic and biomarker summary statistics. We demonstrate how can we use such trans-ethnic annotated latent components to classify diseases based on their genetic basis.
This paper was highlighted in the cover of the journal. Huge congratulations to Saori, Masa, and the team!
Citation: S. Sakaue*, M. Kanai*, Y. Tanigawa, J. Karjalainen, M. Kurki, S. Koshiba, A. Narita, T. Konuma, K. Yamamoto, M. Akiyama, K. Ishigaki, A. Suzuki, K. Suzuki, W. Obara, K. Yamaji, K. Takahashi, S. Asai, Y. Takahashi, T. Suzuki, N. Sinozaki, H. Yamaguchi, S. Minami, S. Murayama, K. Yoshimori, S. Nagayama, D. Obata, M. Higashiyama, A. Masumoto, Y. Koretsune, F. Gen, K. Ito, C. Terao, T. Yamauchi, I. Komuro, T. Kadowaki, G. Tamiya, M. Yamamoto, Y. Nakamura, M. Kubo, Y. Murakami, K. Yamamoto, Y. Kamatani, A. Palotie, M. A. Rivas, M. Daly, K. Matsuda, Y. Okada, A cross-population atlas of genetic associations for 220 human phenotypes. Nat Gen. 53(10), 1415-1424 (2021). https://doi.org/10.1038/s41588-021-00931-x