Year: 2025
Type: article
Study design: Observational Study
Abstract: Human height prediction based on genetic factors alone shows positive correlation, but predictors developed for one population perform less well when applied to population of different ancestries. In this study, we evaluated the utility of incorporating non-genetic factors in height predictors for the Han Chinese population in Taiwan. We analyzed data from 78,719 Taiwan Biobank (TWB) participants and 40,641 Taiwan Precision Medicine Initiative (TPMI) participants using genome-wide association study and multivariable linear regression least absolute shrinkage and selection operator (LASSO) methods to incorporate genetic and non-genetic factors for height prediction. Our findings establish that combining birth year (as a surrogate for nutritional status), age at measurement (to account for age-associated effects on height), and genetic profile data improves the accuracy of height prediction. This method enhances the correlation between predicted and actual height and significantly reduces the discrepancies between predicted and actual height in both males and females.
Source: npj Genomic Medicine
Authors: Chih-Hao Chang, Che-Yu Chou, Timothy G. Raben, Shih-Ann Chen, Yuh-Jyh Jong, Jeng-Yih Wu, Shun-Fa Yang, Hsiang-Cheng Chen, Yen-Lin Chen, Ming Chen, Gwo-Chin Ma, Chih-Yang Huang, Tso-Fu Wang, Sing-Lian Lee, Chen-Fang Hung, See-Tong Pang, Erik Widen, Yao-Ming Chang, Erh-Chan Yeh, Chun-Yu Wei, Chien-Hsiun Chen, Stephen D. H. Hsu, Pui-Yan Kwok
Institutions: University of California, San Francisco, Institute of Biomedical Sciences, Academia Sinica, Academia Sinica, Michigan State University, National Chung Hsing University, Taipei Veterans General Hospital, Taichung Veterans General Hospital, Kaohsiung Medical University, Kaohsiung Medical University Chung-Ho Memorial Hospital, Chung Shan Medical University Hospital, Chung Shan Medical University, Tri-Service General Hospital, National Defense Medical Center, Changhua Christian Hospital, China Medical University, Tzu Chi University, Tzu Chi Foundation, China Medical University Hospital, Koo Foundation Sun Yat-Sen Cancer Center, Chang Gung University, Chang Gung Memorial Hospital, Linkou Chang Gung Memorial Hospital, Genomic Prediction (United States)
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $4,190
Award: G967206143
OpenAlex ID: W4407151104