Polygenic Scores and Parental Predictors: An Adult Height Study Based on the United Kingdom Biobank and the Framingham Heart Study
Human height is a polygenic trait, influenced by a large number of genomic loci. In the pre-genomic era, height prediction was based largely on parental height. More recent predictions of human height have made great strides by integrating genotypic data from large biobanks with improved statistical...
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Frontiers Media S.A.
2021-05-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2021.669441/full |
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| author | Chong You Zhenwei Zhou Jia Wen Yun Li Cheng Heng Pang Haoyang Du Ziwen Wang Xiao-Hua Zhou Daniel A. King Ching-Ti Liu Jie Huang Jie Huang |
| author_facet | Chong You Zhenwei Zhou Jia Wen Yun Li Cheng Heng Pang Haoyang Du Ziwen Wang Xiao-Hua Zhou Daniel A. King Ching-Ti Liu Jie Huang Jie Huang |
| author_sort | Chong You |
| collection | DOAJ |
| description | Human height is a polygenic trait, influenced by a large number of genomic loci. In the pre-genomic era, height prediction was based largely on parental height. More recent predictions of human height have made great strides by integrating genotypic data from large biobanks with improved statistical techniques. Nevertheless, recent studies have not leveraged parental height, an added feature that we hypothesized would offer complementary predictive value. In this study, we assessed the predictive power of polygenic risk scores (PRS) combined with the traditional parental height predictors. Our study analyzed genotypic data and parental height from 1,071 trios from the United Kingdom Biobank and 444 trios from the Framingham Heart Study. We explored a series of statistical models to fully evaluate the performance of several PRS constructed together with parental information and proposed a model we call PRS++ that includes gender, parental height, and PRSs of parents and proband. Our estimate of height with an R2 of ∼0.82 is, to our knowledge, the most accurate estimate yet achieved for predicting human adult height. Without parental information, the R2 from the best PRS-driven model is ∼0.73. In summary, using adult height prediction as an example, we demonstrated that traditional predictors still play important roles and merit integration into the current trends of intensive PRS approaches. |
| first_indexed | 2024-12-14T21:48:10Z |
| format | Article |
| id | doaj.art-9931588061cc411fb901c4e1bb321100 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-12-14T21:48:10Z |
| publishDate | 2021-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-9931588061cc411fb901c4e1bb3211002022-12-21T22:46:18ZengFrontiers Media S.A.Frontiers in Genetics1664-80212021-05-011210.3389/fgene.2021.669441669441Polygenic Scores and Parental Predictors: An Adult Height Study Based on the United Kingdom Biobank and the Framingham Heart StudyChong You0Zhenwei Zhou1Jia Wen2Yun Li3Cheng Heng Pang4Haoyang Du5Ziwen Wang6Xiao-Hua Zhou7Daniel A. King8Ching-Ti Liu9Jie Huang10Jie Huang11Department of Biostatistics, School of Public Health, Peking University, Beijing, ChinaDepartment of Biostatistics, Boston University, Boston, MA, United StatesDepartment of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United StatesDepartment of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United StatesFaculty of Science and Engineering, University of Nottingham Ningbo, Ningbo, ChinaDepartment of Computer Science, School of Art and Science, Wake Forest University, Wake Forest, NC, United StatesDepartment of Bioengineering, School of Engineering, Rice University, Houston, TX, United StatesDepartment of Biostatistics, School of Public Health, Peking University, Beijing, ChinaDepartment of Medicine, Stanford University, Palo Alto, CA, United StatesDepartment of Biostatistics, Boston University, Boston, MA, United StatesDepartment of Global Health, School of Public Health, Peking University, Beijing, China0Institute for Global Health and Development, Peking University, Peking, ChinaHuman height is a polygenic trait, influenced by a large number of genomic loci. In the pre-genomic era, height prediction was based largely on parental height. More recent predictions of human height have made great strides by integrating genotypic data from large biobanks with improved statistical techniques. Nevertheless, recent studies have not leveraged parental height, an added feature that we hypothesized would offer complementary predictive value. In this study, we assessed the predictive power of polygenic risk scores (PRS) combined with the traditional parental height predictors. Our study analyzed genotypic data and parental height from 1,071 trios from the United Kingdom Biobank and 444 trios from the Framingham Heart Study. We explored a series of statistical models to fully evaluate the performance of several PRS constructed together with parental information and proposed a model we call PRS++ that includes gender, parental height, and PRSs of parents and proband. Our estimate of height with an R2 of ∼0.82 is, to our knowledge, the most accurate estimate yet achieved for predicting human adult height. Without parental information, the R2 from the best PRS-driven model is ∼0.73. In summary, using adult height prediction as an example, we demonstrated that traditional predictors still play important roles and merit integration into the current trends of intensive PRS approaches.https://www.frontiersin.org/articles/10.3389/fgene.2021.669441/fulladult heightpredictionpolygenic scoreparental heightmodel selection |
| spellingShingle | Chong You Zhenwei Zhou Jia Wen Yun Li Cheng Heng Pang Haoyang Du Ziwen Wang Xiao-Hua Zhou Daniel A. King Ching-Ti Liu Jie Huang Jie Huang Polygenic Scores and Parental Predictors: An Adult Height Study Based on the United Kingdom Biobank and the Framingham Heart Study Frontiers in Genetics adult height prediction polygenic score parental height model selection |
| title | Polygenic Scores and Parental Predictors: An Adult Height Study Based on the United Kingdom Biobank and the Framingham Heart Study |
| title_full | Polygenic Scores and Parental Predictors: An Adult Height Study Based on the United Kingdom Biobank and the Framingham Heart Study |
| title_fullStr | Polygenic Scores and Parental Predictors: An Adult Height Study Based on the United Kingdom Biobank and the Framingham Heart Study |
| title_full_unstemmed | Polygenic Scores and Parental Predictors: An Adult Height Study Based on the United Kingdom Biobank and the Framingham Heart Study |
| title_short | Polygenic Scores and Parental Predictors: An Adult Height Study Based on the United Kingdom Biobank and the Framingham Heart Study |
| title_sort | polygenic scores and parental predictors an adult height study based on the united kingdom biobank and the framingham heart study |
| topic | adult height prediction polygenic score parental height model selection |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2021.669441/full |
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