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Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations

BACKGROUND: Type 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement e...

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Autores principales: Ge, Tian, Irvin, Marguerite R., Patki, Amit, Srinivasasainagendra, Vinodh, Lin, Yen-Feng, Tiwari, Hemant K., Armstrong, Nicole D., Benoit, Barbara, Chen, Chia-Yen, Choi, Karmel W., Cimino, James J., Davis, Brittney H., Dikilitas, Ozan, Etheridge, Bethany, Feng, Yen-Chen Anne, Gainer, Vivian, Huang, Hailiang, Jarvik, Gail P., Kachulis, Christopher, Kenny, Eimear E., Khan, Atlas, Kiryluk, Krzysztof, Kottyan, Leah, Kullo, Iftikhar J., Lange, Christoph, Lennon, Niall, Leong, Aaron, Malolepsza, Edyta, Miles, Ayme D., Murphy, Shawn, Namjou, Bahram, Narayan, Renuka, O’Connor, Mark J., Pacheco, Jennifer A., Perez, Emma, Rasmussen-Torvik, Laura J., Rosenthal, Elisabeth A., Schaid, Daniel, Stamou, Maria, Udler, Miriam S., Wei, Wei-Qi, Weiss, Scott T., Ng, Maggie C. Y., Smoller, Jordan W., Lebo, Matthew S., Meigs, James B., Limdi, Nita A., Karlson, Elizabeth W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9241245/
https://www.ncbi.nlm.nih.gov/pubmed/35765100
http://dx.doi.org/10.1186/s13073-022-01074-2
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author Ge, Tian
Irvin, Marguerite R.
Patki, Amit
Srinivasasainagendra, Vinodh
Lin, Yen-Feng
Tiwari, Hemant K.
Armstrong, Nicole D.
Benoit, Barbara
Chen, Chia-Yen
Choi, Karmel W.
Cimino, James J.
Davis, Brittney H.
Dikilitas, Ozan
Etheridge, Bethany
Feng, Yen-Chen Anne
Gainer, Vivian
Huang, Hailiang
Jarvik, Gail P.
Kachulis, Christopher
Kenny, Eimear E.
Khan, Atlas
Kiryluk, Krzysztof
Kottyan, Leah
Kullo, Iftikhar J.
Lange, Christoph
Lennon, Niall
Leong, Aaron
Malolepsza, Edyta
Miles, Ayme D.
Murphy, Shawn
Namjou, Bahram
Narayan, Renuka
O’Connor, Mark J.
Pacheco, Jennifer A.
Perez, Emma
Rasmussen-Torvik, Laura J.
Rosenthal, Elisabeth A.
Schaid, Daniel
Stamou, Maria
Udler, Miriam S.
Wei, Wei-Qi
Weiss, Scott T.
Ng, Maggie C. Y.
Smoller, Jordan W.
Lebo, Matthew S.
Meigs, James B.
Limdi, Nita A.
Karlson, Elizabeth W.
author_facet Ge, Tian
Irvin, Marguerite R.
Patki, Amit
Srinivasasainagendra, Vinodh
Lin, Yen-Feng
Tiwari, Hemant K.
Armstrong, Nicole D.
Benoit, Barbara
Chen, Chia-Yen
Choi, Karmel W.
Cimino, James J.
Davis, Brittney H.
Dikilitas, Ozan
Etheridge, Bethany
Feng, Yen-Chen Anne
Gainer, Vivian
Huang, Hailiang
Jarvik, Gail P.
Kachulis, Christopher
Kenny, Eimear E.
Khan, Atlas
Kiryluk, Krzysztof
Kottyan, Leah
Kullo, Iftikhar J.
Lange, Christoph
Lennon, Niall
Leong, Aaron
Malolepsza, Edyta
Miles, Ayme D.
Murphy, Shawn
Namjou, Bahram
Narayan, Renuka
O’Connor, Mark J.
Pacheco, Jennifer A.
Perez, Emma
Rasmussen-Torvik, Laura J.
Rosenthal, Elisabeth A.
Schaid, Daniel
Stamou, Maria
Udler, Miriam S.
Wei, Wei-Qi
Weiss, Scott T.
Ng, Maggie C. Y.
Smoller, Jordan W.
Lebo, Matthew S.
Meigs, James B.
Limdi, Nita A.
Karlson, Elizabeth W.
author_sort Ge, Tian
collection PubMed
description BACKGROUND: Type 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for equitable deployment of PRS to clinical practice that benefits global populations. METHODS: We integrated T2D GWAS in European, African, and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and assessed the prediction accuracy of the PRS in the multi-ethnic Electronic Medical Records and Genomics (eMERGE) study (11,945 cases; 57,694 controls), four Black cohorts (5137 cases; 9657 controls), and the Taiwan Biobank (4570 cases; 84,996 controls). We additionally evaluated a post hoc ancestry adjustment method that can express the polygenic risk on the same scale across ancestrally diverse individuals and facilitate the clinical implementation of the PRS in prospective cohorts. RESULTS: The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined. The top 2% of the PRS distribution can identify individuals with an approximately 2.5–4.5-fold of increase in T2D risk, which corresponds to the increased risk of T2D for first-degree relatives. The post hoc ancestry adjustment method eliminated major distributional differences in the PRS across ancestries without compromising its predictive performance. CONCLUSIONS: By integrating T2D GWAS from multiple populations, we developed and validated a trans-ancestry PRS, and demonstrated its potential as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13073-022-01074-2.
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spelling pubmed-92412452022-06-30 Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations Ge, Tian Irvin, Marguerite R. Patki, Amit Srinivasasainagendra, Vinodh Lin, Yen-Feng Tiwari, Hemant K. Armstrong, Nicole D. Benoit, Barbara Chen, Chia-Yen Choi, Karmel W. Cimino, James J. Davis, Brittney H. Dikilitas, Ozan Etheridge, Bethany Feng, Yen-Chen Anne Gainer, Vivian Huang, Hailiang Jarvik, Gail P. Kachulis, Christopher Kenny, Eimear E. Khan, Atlas Kiryluk, Krzysztof Kottyan, Leah Kullo, Iftikhar J. Lange, Christoph Lennon, Niall Leong, Aaron Malolepsza, Edyta Miles, Ayme D. Murphy, Shawn Namjou, Bahram Narayan, Renuka O’Connor, Mark J. Pacheco, Jennifer A. Perez, Emma Rasmussen-Torvik, Laura J. Rosenthal, Elisabeth A. Schaid, Daniel Stamou, Maria Udler, Miriam S. Wei, Wei-Qi Weiss, Scott T. Ng, Maggie C. Y. Smoller, Jordan W. Lebo, Matthew S. Meigs, James B. Limdi, Nita A. Karlson, Elizabeth W. Genome Med Research BACKGROUND: Type 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for equitable deployment of PRS to clinical practice that benefits global populations. METHODS: We integrated T2D GWAS in European, African, and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and assessed the prediction accuracy of the PRS in the multi-ethnic Electronic Medical Records and Genomics (eMERGE) study (11,945 cases; 57,694 controls), four Black cohorts (5137 cases; 9657 controls), and the Taiwan Biobank (4570 cases; 84,996 controls). We additionally evaluated a post hoc ancestry adjustment method that can express the polygenic risk on the same scale across ancestrally diverse individuals and facilitate the clinical implementation of the PRS in prospective cohorts. RESULTS: The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined. The top 2% of the PRS distribution can identify individuals with an approximately 2.5–4.5-fold of increase in T2D risk, which corresponds to the increased risk of T2D for first-degree relatives. The post hoc ancestry adjustment method eliminated major distributional differences in the PRS across ancestries without compromising its predictive performance. CONCLUSIONS: By integrating T2D GWAS from multiple populations, we developed and validated a trans-ancestry PRS, and demonstrated its potential as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13073-022-01074-2. BioMed Central 2022-06-29 /pmc/articles/PMC9241245/ /pubmed/35765100 http://dx.doi.org/10.1186/s13073-022-01074-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Ge, Tian
Irvin, Marguerite R.
Patki, Amit
Srinivasasainagendra, Vinodh
Lin, Yen-Feng
Tiwari, Hemant K.
Armstrong, Nicole D.
Benoit, Barbara
Chen, Chia-Yen
Choi, Karmel W.
Cimino, James J.
Davis, Brittney H.
Dikilitas, Ozan
Etheridge, Bethany
Feng, Yen-Chen Anne
Gainer, Vivian
Huang, Hailiang
Jarvik, Gail P.
Kachulis, Christopher
Kenny, Eimear E.
Khan, Atlas
Kiryluk, Krzysztof
Kottyan, Leah
Kullo, Iftikhar J.
Lange, Christoph
Lennon, Niall
Leong, Aaron
Malolepsza, Edyta
Miles, Ayme D.
Murphy, Shawn
Namjou, Bahram
Narayan, Renuka
O’Connor, Mark J.
Pacheco, Jennifer A.
Perez, Emma
Rasmussen-Torvik, Laura J.
Rosenthal, Elisabeth A.
Schaid, Daniel
Stamou, Maria
Udler, Miriam S.
Wei, Wei-Qi
Weiss, Scott T.
Ng, Maggie C. Y.
Smoller, Jordan W.
Lebo, Matthew S.
Meigs, James B.
Limdi, Nita A.
Karlson, Elizabeth W.
Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations
title Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations
title_full Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations
title_fullStr Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations
title_full_unstemmed Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations
title_short Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations
title_sort development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9241245/
https://www.ncbi.nlm.nih.gov/pubmed/35765100
http://dx.doi.org/10.1186/s13073-022-01074-2
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