13073_2021_831_MOESM1_ESM.docx (1.05 MB)
Additional file 1 of Development of genome-wide polygenic risk scores for lipid traits and clinical applications for dyslipidemia, subclinical atherosclerosis, and diabetes cardiovascular complications among East Asians
journal contribution
posted on 2021-02-20, 04:40 authored by Claudia H. T. Tam, Cadmon K. P. Lim, Andrea O. Y. Luk, Alex C. W. Ng, Heung-man Lee, Guozhi Jiang, Eric S. H. Lau, Baoqi Fan, Raymond Wan, Alice P. S. Kong, Wing-hung Tam, Risa Ozaki, Elaine Y. K. Chow, Ka-fai Lee, Shing-chung Siu, Grace Hui, Chiu-chi Tsang, Kam-piu Lau, Jenny Y. Y. Leung, Man-wo Tsang, Grace Kam, Ip-tim Lau, June K. Y. Li, Vincent T. F. Yeung, Emmy Lau, Stanley Lo, Samuel Fung, Yuk-lun Cheng, Chun-chung Chow, Miao Hu, Weichuan Yu, Stephen K. W. Tsui, Yu Huang, Huiyao Lan, Cheuk-chun Szeto, Nelson L. S. Tang, Maggie C. Y. Ng, Wing-yee So, Brian Tomlinson, Juliana C. N. Chan, Ronald C. W. MaAdditional file 1: Supplementary methods: 1) Hong Kong Diabetes Register TRS Study Group Members; 2) Hong Kong Diabetes Biobank Study Group Members; and 3) Cohort descriptions. Figure S1. Principal component analysis (PCA). Figure S2. Pooled correlations of each candidate polygenic risk scores with measured lipid traits. Figure S3. Proportion of phenotypic variance in lipid traits explained by each candidate polygenic risk scores. Figure S4. Geometric means of measured lipid traits stratified by the quintile of polygenic risk score with the best performance. Figure S5. Geometric means of measured lipid traits at baseline and follow-up, and three-year changes in lipid traits stratified by quintile of polygenic risk scores in adolescents.
