Nature Communications (Mar 2020)
Dimensionality reduction reveals fine-scale structure in the Japanese population with consequences for polygenic risk prediction
- Saori Sakaue,
- Jun Hirata,
- Masahiro Kanai,
- Ken Suzuki,
- Masato Akiyama,
- Chun Lai Too,
- Thurayya Arayssi,
- Mohammed Hammoudeh,
- Samar Al Emadi,
- Basel K. Masri,
- Hussein Halabi,
- Humeira Badsha,
- Imad W. Uthman,
- Richa Saxena,
- Leonid Padyukov,
- Makoto Hirata,
- Koichi Matsuda,
- Yoshinori Murakami,
- Yoichiro Kamatani,
- Yukinori Okada
Affiliations
- Saori Sakaue
- Department of Statistical Genetics, Osaka University Graduate School of Medicine
- Jun Hirata
- Department of Statistical Genetics, Osaka University Graduate School of Medicine
- Masahiro Kanai
- Department of Statistical Genetics, Osaka University Graduate School of Medicine
- Ken Suzuki
- Department of Statistical Genetics, Osaka University Graduate School of Medicine
- Masato Akiyama
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences
- Chun Lai Too
- Allergy and Immunology Research Center, Institute for Medical Research, Ministry of Health Malaysia
- Thurayya Arayssi
- Department of Internal Medicine, Weill Cornell Medicine-Qatar, Education City
- Mohammed Hammoudeh
- Department of Internal Medicine, Hamad Medical Corporation
- Samar Al Emadi
- Department of Internal Medicine, Hamad Medical Corporation
- Basel K. Masri
- Department of Internal Medicine, Jordan Hospital
- Hussein Halabi
- Rheumatology Division, Department of Internal Medicine, King Faisal Specialist Hospital and Research Center
- Humeira Badsha
- Dr. Humeira Badsha Medical Center, Emirates Hospital
- Imad W. Uthman
- Department of Rheumatology, American University of Beirut
- Richa Saxena
- Center for Genomic Medicine, Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School
- Leonid Padyukov
- Division of Rheumatology, Department of Medicine, Karolinska Institutet and Karolinska University Hospital
- Makoto Hirata
- Laboratory of Genome Technology, Institute of Medical Science, the University of Tokyo
- Koichi Matsuda
- Department of Computational Biology and Medical Sciences, Graduate school of Frontier Sciences, the University of Tokyo
- Yoshinori Murakami
- Division of Molecular Pathology, Institute of Medical Science, the University of Tokyo
- Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences
- Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine
- DOI
- https://doi.org/10.1038/s41467-020-15194-z
- Journal volume & issue
-
Vol. 11,
no. 1
pp. 1 – 11
Abstract
Population structure, even subtle differences within seemingly homogenous populations, can have an impact on the accuracy of polygenic prediction. Here, Sakaue et al. use dimensionality reduction methods to reveal fine-scale structure in the Biobank Japan cohort and explore the performance of polygenic risk scores.
