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Selection, optimization, and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse populations

Polygenic risk scores (PRS) have improved in predictive performance supporting their use in clinical practice. Reduced predictive performance of PRS in diverse populations can exacerbate existing health disparities. The NHGRI-funded eMERGE Network is returning a PRS-based genome-informed risk assess...

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Autores principales: Lennon, Niall J, Kottyan, Leah C, Kachulis, Christopher, Abul-Husn, Noura, Arias, Josh, Belbin, Gillian, Below, Jennifer E, Berndt, Sonja, Chung, Wendy, Cimino, James J., Clayton, Ellen Wright, Connolly, John J., Crosslin, David, Dikilitas, Ozan, Velez Edwards, Digna R., Feng, QiPing, Fisher, Marissa, Freimuth, Robert, Ge, Tian, Glessner, Joseph T., Gordon, Adam, Guiducci, Candace, Hakonarson, Hakon, Harden, Maegan, Harr, Margaret, Hirschhorn, Joel, Hoggart, Clive, Hsu, Li, Irvin, Ryan, Jarvik, Gail P., Karlson, Elizabeth W., Khan, Atlas, Khera, Amit, Kiryluk, Krzysztof, Kullo, Iftikhar, Larkin, Katie, Limdi, Nita, Linder, Jodell E., Loos, Ruth, Luo, Yuan, Malolepsza, Edyta, Manolio, Teri, Martin, Lisa J., McCarthy, Li, Meigs, James B, Mersha, Tesfaye B., Mosley, Jonathan, Namjou, Bahram, Pai, Nihal, Pesce, Lorenzo L., Peters, Ulrike, Peterson, Josh, Prows, Cynthia A., Puckelwartz, Megan J., Rehm, Heidi, Roden, Dan, Rosenthal, Elisabeth A., Rowley, Robb, Sawicki, Konrad Teodor, Schaid, Dan, Schmidlen, Tara, Smit, Roelof, Smith, Johanna, Smoller, Jordan W., Thomas, Minta, Tiwari, Hemant, Toledo, Diana, Vaitinadin, Nataraja Sarma, Veenstra, David, Walunas, Theresa, Wang, Zhe, Wei, Wei-Qi, Weng, Chunhua, Wiesner, Georgia, Xianyong, Yin, Kenny, Eimear
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10275001/
https://www.ncbi.nlm.nih.gov/pubmed/37333246
http://dx.doi.org/10.1101/2023.05.25.23290535
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author Lennon, Niall J
Kottyan, Leah C
Kachulis, Christopher
Abul-Husn, Noura
Arias, Josh
Belbin, Gillian
Below, Jennifer E
Berndt, Sonja
Chung, Wendy
Cimino, James J.
Clayton, Ellen Wright
Connolly, John J.
Crosslin, David
Dikilitas, Ozan
Velez Edwards, Digna R.
Feng, QiPing
Fisher, Marissa
Freimuth, Robert
Ge, Tian
Glessner, Joseph T.
Gordon, Adam
Guiducci, Candace
Hakonarson, Hakon
Harden, Maegan
Harr, Margaret
Hirschhorn, Joel
Hoggart, Clive
Hsu, Li
Irvin, Ryan
Jarvik, Gail P.
Karlson, Elizabeth W.
Khan, Atlas
Khera, Amit
Kiryluk, Krzysztof
Kullo, Iftikhar
Larkin, Katie
Limdi, Nita
Linder, Jodell E.
Loos, Ruth
Luo, Yuan
Malolepsza, Edyta
Manolio, Teri
Martin, Lisa J.
McCarthy, Li
Meigs, James B
Mersha, Tesfaye B.
Mosley, Jonathan
Namjou, Bahram
Pai, Nihal
Pesce, Lorenzo L.
Peters, Ulrike
Peterson, Josh
Prows, Cynthia A.
Puckelwartz, Megan J.
Rehm, Heidi
Roden, Dan
Rosenthal, Elisabeth A.
Rowley, Robb
Sawicki, Konrad Teodor
Schaid, Dan
Schmidlen, Tara
Smit, Roelof
Smith, Johanna
Smoller, Jordan W.
Thomas, Minta
Tiwari, Hemant
Toledo, Diana
Vaitinadin, Nataraja Sarma
Veenstra, David
Walunas, Theresa
Wang, Zhe
Wei, Wei-Qi
Weng, Chunhua
Wiesner, Georgia
Xianyong, Yin
Kenny, Eimear
author_facet Lennon, Niall J
Kottyan, Leah C
Kachulis, Christopher
Abul-Husn, Noura
Arias, Josh
Belbin, Gillian
Below, Jennifer E
Berndt, Sonja
Chung, Wendy
Cimino, James J.
Clayton, Ellen Wright
Connolly, John J.
Crosslin, David
Dikilitas, Ozan
Velez Edwards, Digna R.
Feng, QiPing
Fisher, Marissa
Freimuth, Robert
Ge, Tian
Glessner, Joseph T.
Gordon, Adam
Guiducci, Candace
Hakonarson, Hakon
Harden, Maegan
Harr, Margaret
Hirschhorn, Joel
Hoggart, Clive
Hsu, Li
Irvin, Ryan
Jarvik, Gail P.
Karlson, Elizabeth W.
Khan, Atlas
Khera, Amit
Kiryluk, Krzysztof
Kullo, Iftikhar
Larkin, Katie
Limdi, Nita
Linder, Jodell E.
Loos, Ruth
Luo, Yuan
Malolepsza, Edyta
Manolio, Teri
Martin, Lisa J.
McCarthy, Li
Meigs, James B
Mersha, Tesfaye B.
Mosley, Jonathan
Namjou, Bahram
Pai, Nihal
Pesce, Lorenzo L.
Peters, Ulrike
Peterson, Josh
Prows, Cynthia A.
Puckelwartz, Megan J.
Rehm, Heidi
Roden, Dan
Rosenthal, Elisabeth A.
Rowley, Robb
Sawicki, Konrad Teodor
Schaid, Dan
Schmidlen, Tara
Smit, Roelof
Smith, Johanna
Smoller, Jordan W.
Thomas, Minta
Tiwari, Hemant
Toledo, Diana
Vaitinadin, Nataraja Sarma
Veenstra, David
Walunas, Theresa
Wang, Zhe
Wei, Wei-Qi
Weng, Chunhua
Wiesner, Georgia
Xianyong, Yin
Kenny, Eimear
author_sort Lennon, Niall J
collection PubMed
description Polygenic risk scores (PRS) have improved in predictive performance supporting their use in clinical practice. Reduced predictive performance of PRS in diverse populations can exacerbate existing health disparities. The NHGRI-funded eMERGE Network is returning a PRS-based genome-informed risk assessment to 25,000 diverse adults and children. We assessed PRS performance, medical actionability, and potential clinical utility for 23 conditions. Standardized metrics were considered in the selection process with additional consideration given to strength of evidence in African and Hispanic populations. Ten conditions were selected with a range of high-risk thresholds: atrial fibrillation, breast cancer, chronic kidney disease, coronary heart disease, hypercholesterolemia, prostate cancer, asthma, type 1 diabetes, obesity, and type 2 diabetes. We developed a pipeline for clinical PRS implementation, used genetic ancestry to calibrate PRS mean and variance, created a framework for regulatory compliance, and developed a PRS clinical report. eMERGE’s experience informs the infrastructure needed to implement PRS-based implementation in diverse clinical settings.
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spelling pubmed-102750012023-06-17 Selection, optimization, and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse populations Lennon, Niall J Kottyan, Leah C Kachulis, Christopher Abul-Husn, Noura Arias, Josh Belbin, Gillian Below, Jennifer E Berndt, Sonja Chung, Wendy Cimino, James J. Clayton, Ellen Wright Connolly, John J. Crosslin, David Dikilitas, Ozan Velez Edwards, Digna R. Feng, QiPing Fisher, Marissa Freimuth, Robert Ge, Tian Glessner, Joseph T. Gordon, Adam Guiducci, Candace Hakonarson, Hakon Harden, Maegan Harr, Margaret Hirschhorn, Joel Hoggart, Clive Hsu, Li Irvin, Ryan Jarvik, Gail P. Karlson, Elizabeth W. Khan, Atlas Khera, Amit Kiryluk, Krzysztof Kullo, Iftikhar Larkin, Katie Limdi, Nita Linder, Jodell E. Loos, Ruth Luo, Yuan Malolepsza, Edyta Manolio, Teri Martin, Lisa J. McCarthy, Li Meigs, James B Mersha, Tesfaye B. Mosley, Jonathan Namjou, Bahram Pai, Nihal Pesce, Lorenzo L. Peters, Ulrike Peterson, Josh Prows, Cynthia A. Puckelwartz, Megan J. Rehm, Heidi Roden, Dan Rosenthal, Elisabeth A. Rowley, Robb Sawicki, Konrad Teodor Schaid, Dan Schmidlen, Tara Smit, Roelof Smith, Johanna Smoller, Jordan W. Thomas, Minta Tiwari, Hemant Toledo, Diana Vaitinadin, Nataraja Sarma Veenstra, David Walunas, Theresa Wang, Zhe Wei, Wei-Qi Weng, Chunhua Wiesner, Georgia Xianyong, Yin Kenny, Eimear medRxiv Article Polygenic risk scores (PRS) have improved in predictive performance supporting their use in clinical practice. Reduced predictive performance of PRS in diverse populations can exacerbate existing health disparities. The NHGRI-funded eMERGE Network is returning a PRS-based genome-informed risk assessment to 25,000 diverse adults and children. We assessed PRS performance, medical actionability, and potential clinical utility for 23 conditions. Standardized metrics were considered in the selection process with additional consideration given to strength of evidence in African and Hispanic populations. Ten conditions were selected with a range of high-risk thresholds: atrial fibrillation, breast cancer, chronic kidney disease, coronary heart disease, hypercholesterolemia, prostate cancer, asthma, type 1 diabetes, obesity, and type 2 diabetes. We developed a pipeline for clinical PRS implementation, used genetic ancestry to calibrate PRS mean and variance, created a framework for regulatory compliance, and developed a PRS clinical report. eMERGE’s experience informs the infrastructure needed to implement PRS-based implementation in diverse clinical settings. Cold Spring Harbor Laboratory 2023-06-05 /pmc/articles/PMC10275001/ /pubmed/37333246 http://dx.doi.org/10.1101/2023.05.25.23290535 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Lennon, Niall J
Kottyan, Leah C
Kachulis, Christopher
Abul-Husn, Noura
Arias, Josh
Belbin, Gillian
Below, Jennifer E
Berndt, Sonja
Chung, Wendy
Cimino, James J.
Clayton, Ellen Wright
Connolly, John J.
Crosslin, David
Dikilitas, Ozan
Velez Edwards, Digna R.
Feng, QiPing
Fisher, Marissa
Freimuth, Robert
Ge, Tian
Glessner, Joseph T.
Gordon, Adam
Guiducci, Candace
Hakonarson, Hakon
Harden, Maegan
Harr, Margaret
Hirschhorn, Joel
Hoggart, Clive
Hsu, Li
Irvin, Ryan
Jarvik, Gail P.
Karlson, Elizabeth W.
Khan, Atlas
Khera, Amit
Kiryluk, Krzysztof
Kullo, Iftikhar
Larkin, Katie
Limdi, Nita
Linder, Jodell E.
Loos, Ruth
Luo, Yuan
Malolepsza, Edyta
Manolio, Teri
Martin, Lisa J.
McCarthy, Li
Meigs, James B
Mersha, Tesfaye B.
Mosley, Jonathan
Namjou, Bahram
Pai, Nihal
Pesce, Lorenzo L.
Peters, Ulrike
Peterson, Josh
Prows, Cynthia A.
Puckelwartz, Megan J.
Rehm, Heidi
Roden, Dan
Rosenthal, Elisabeth A.
Rowley, Robb
Sawicki, Konrad Teodor
Schaid, Dan
Schmidlen, Tara
Smit, Roelof
Smith, Johanna
Smoller, Jordan W.
Thomas, Minta
Tiwari, Hemant
Toledo, Diana
Vaitinadin, Nataraja Sarma
Veenstra, David
Walunas, Theresa
Wang, Zhe
Wei, Wei-Qi
Weng, Chunhua
Wiesner, Georgia
Xianyong, Yin
Kenny, Eimear
Selection, optimization, and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse populations
title Selection, optimization, and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse populations
title_full Selection, optimization, and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse populations
title_fullStr Selection, optimization, and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse populations
title_full_unstemmed Selection, optimization, and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse populations
title_short Selection, optimization, and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse populations
title_sort selection, optimization, and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse populations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10275001/
https://www.ncbi.nlm.nih.gov/pubmed/37333246
http://dx.doi.org/10.1101/2023.05.25.23290535
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