The accuracy of polygenic score models for BMI and Type II diabetes in the Native Hawaiian population
Abstract Polygenic scores (PGS) are promising in stratifying individuals based on the genetic susceptibility to complex diseases or traits. However, the accuracy of PGS models, typically trained in European- or East Asian-ancestry populations, tend to perform poorly in other ethnic minority populati...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-04-01
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| Series: | Communications Biology |
| Online Access: | https://doi.org/10.1038/s42003-025-08050-7 |
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| author | Ying-Chu Lo He Tian Tsz Fung Chan Soyoung Jeon Kimberli Alatorre Bryan L. Dinh Gertraud Maskarinec Kekoa Taparra Nathan Nakatsuka Mingrui Yu Chia-Yen Chen Yen-Feng Lin Lynne R. Wilkens Loic Le Marchand Christopher A. Haiman Charleston W. K. Chiang |
| author_facet | Ying-Chu Lo He Tian Tsz Fung Chan Soyoung Jeon Kimberli Alatorre Bryan L. Dinh Gertraud Maskarinec Kekoa Taparra Nathan Nakatsuka Mingrui Yu Chia-Yen Chen Yen-Feng Lin Lynne R. Wilkens Loic Le Marchand Christopher A. Haiman Charleston W. K. Chiang |
| author_sort | Ying-Chu Lo |
| collection | DOAJ |
| description | Abstract Polygenic scores (PGS) are promising in stratifying individuals based on the genetic susceptibility to complex diseases or traits. However, the accuracy of PGS models, typically trained in European- or East Asian-ancestry populations, tend to perform poorly in other ethnic minority populations and their accuracies have not been evaluated for Native Hawaiians. In particular, for body mass index (BMI) and type-2 diabetes (T2D), Polynesian-ancestry individuals such as Native Hawaiians or Samoans exhibit varied distribution from other continental populations, but are understudied, particularly in the context of PGS. Using BMI and T2D as examples of metabolic traits of importance to Polynesian populations (along with height as a comparison of a similarly highly polygenic trait), here we examine the prediction accuracies of PGS models in a large Native Hawaiian sample from the Multiethnic Cohort with up to 5300 individuals. We find evidence of lowered prediction accuracies for the PGS models in some cases, particularly for height. We also find that using the Native Hawaiian samples as an optimization cohort during training does not consistently improve PGS performance. Moreover, even the best-performing PGS models among Native Hawaiians have lowered prediction accuracy among the subset of individuals most enriched with Polynesian ancestry. Our findings indicate that factors such as admixture histories, sample size, and diversity in GWAS can influence PGS performance for complex traits among Native Hawaiian samples. This study provides an initial survey of PGS performance among Native Hawaiians and exposes the current gaps and challenges associated with improving polygenic prediction models for underrepresented minority populations. |
| format | Article |
| id | doaj-art-bb222df9fc704bed87207912fcff3e55 |
| institution | Kabale University |
| issn | 2399-3642 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Biology |
| spelling | doaj-art-bb222df9fc704bed87207912fcff3e552025-08-20T03:53:32ZengNature PortfolioCommunications Biology2399-36422025-04-018111210.1038/s42003-025-08050-7The accuracy of polygenic score models for BMI and Type II diabetes in the Native Hawaiian populationYing-Chu Lo0He Tian1Tsz Fung Chan2Soyoung Jeon3Kimberli Alatorre4Bryan L. Dinh5Gertraud Maskarinec6Kekoa Taparra7Nathan Nakatsuka8Mingrui Yu9Chia-Yen Chen10Yen-Feng Lin11Lynne R. Wilkens12Loic Le Marchand13Christopher A. Haiman14Charleston W. K. Chiang15Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern CaliforniaCenter for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern CaliforniaCenter for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern CaliforniaCenter for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern CaliforniaCenter for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern CaliforniaCenter for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern CaliforniaEpidemiology Program, University of Hawai’i Cancer Center, University of Hawai’i, ManoaStandard Health Care, Department of Radiation OncologyNew York Genome CenterStanley Center for Psychiatric Research, Broad Institute of MIT and HarvardBiogenCenter for Neuropsychiatric Research, National Health Research InstitutesEpidemiology Program, University of Hawai’i Cancer Center, University of Hawai’i, ManoaEpidemiology Program, University of Hawai’i Cancer Center, University of Hawai’i, ManoaCenter for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern CaliforniaCenter for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern CaliforniaAbstract Polygenic scores (PGS) are promising in stratifying individuals based on the genetic susceptibility to complex diseases or traits. However, the accuracy of PGS models, typically trained in European- or East Asian-ancestry populations, tend to perform poorly in other ethnic minority populations and their accuracies have not been evaluated for Native Hawaiians. In particular, for body mass index (BMI) and type-2 diabetes (T2D), Polynesian-ancestry individuals such as Native Hawaiians or Samoans exhibit varied distribution from other continental populations, but are understudied, particularly in the context of PGS. Using BMI and T2D as examples of metabolic traits of importance to Polynesian populations (along with height as a comparison of a similarly highly polygenic trait), here we examine the prediction accuracies of PGS models in a large Native Hawaiian sample from the Multiethnic Cohort with up to 5300 individuals. We find evidence of lowered prediction accuracies for the PGS models in some cases, particularly for height. We also find that using the Native Hawaiian samples as an optimization cohort during training does not consistently improve PGS performance. Moreover, even the best-performing PGS models among Native Hawaiians have lowered prediction accuracy among the subset of individuals most enriched with Polynesian ancestry. Our findings indicate that factors such as admixture histories, sample size, and diversity in GWAS can influence PGS performance for complex traits among Native Hawaiian samples. This study provides an initial survey of PGS performance among Native Hawaiians and exposes the current gaps and challenges associated with improving polygenic prediction models for underrepresented minority populations.https://doi.org/10.1038/s42003-025-08050-7 |
| spellingShingle | Ying-Chu Lo He Tian Tsz Fung Chan Soyoung Jeon Kimberli Alatorre Bryan L. Dinh Gertraud Maskarinec Kekoa Taparra Nathan Nakatsuka Mingrui Yu Chia-Yen Chen Yen-Feng Lin Lynne R. Wilkens Loic Le Marchand Christopher A. Haiman Charleston W. K. Chiang The accuracy of polygenic score models for BMI and Type II diabetes in the Native Hawaiian population Communications Biology |
| title | The accuracy of polygenic score models for BMI and Type II diabetes in the Native Hawaiian population |
| title_full | The accuracy of polygenic score models for BMI and Type II diabetes in the Native Hawaiian population |
| title_fullStr | The accuracy of polygenic score models for BMI and Type II diabetes in the Native Hawaiian population |
| title_full_unstemmed | The accuracy of polygenic score models for BMI and Type II diabetes in the Native Hawaiian population |
| title_short | The accuracy of polygenic score models for BMI and Type II diabetes in the Native Hawaiian population |
| title_sort | accuracy of polygenic score models for bmi and type ii diabetes in the native hawaiian population |
| url | https://doi.org/10.1038/s42003-025-08050-7 |
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