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

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Selection, optimization and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse US populations. / Lennon, Niall J.; Kottyan, Leah C.; Kachulis, Christopher; Abul-Husn, Noura S.; Arias, Josh; Belbin, Gillian; Below, Jennifer E.; Berndt, Sonja I.; Chung, Wendy K.; Cimino, James J.; Clayton, Ellen Wright; Connolly, John J.; Crosslin, David R.; Dikilitas, Ozan; Velez Edwards, Digna R.; Feng, Qi Ping; Fisher, Marissa; Freimuth, Robert R.; Ge, Tian; Glessner, Joseph T.; Gordon, Adam S.; Patterson, Candace; Hakonarson, Hakon; Harden, Maegan; Harr, Margaret; Hirschhorn, Joel; Hoggart, Clive; Hsu, Li; Irvin, Marguerite R.; 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 A.; Martin, Lisa J.; McCarthy, Li; McNally, Elizabeth M.; Meigs, James B.; Mersha, Tesfaye B.; Mosley, Jonathan D.; Musick, Anjene; Namjou, Bahram; Pai, Nihal; Pesce, Lorenzo L.; Peters, Ulrike; Peterson, Josh F.; Prows, Cynthia A.; Puckelwartz, Megan J.; Rehm, Heidi L.; Roden, Dan M.; Rosenthal, Elisabeth A.; Rowley, Robb; Sawicki, Konrad Teodor; Schaid, Daniel J.; Smit, Roelof A.J.; Smith, Johanna L.; Smoller, Jordan W.; Thomas, Minta; Tiwari, Hemant; Toledo, Diana M.; Vaitinadin, Nataraja Sarma; Veenstra, David; Walunas, Theresa L.; Wang, Zhe; Wei, Wei Qi; Weng, Chunhua; Wiesner, Georgia L.; Yin, Xianyong; Kenny, Eimear E.; Berndt, Sonja; Hirschhorn, Joel.

In: Nature Medicine, Vol. 30, No. 2, 2024, p. 480-487.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Lennon, NJ, Kottyan, LC, Kachulis, C, Abul-Husn, NS, Arias, J, Belbin, G, Below, JE, Berndt, SI, Chung, WK, Cimino, JJ, Clayton, EW, Connolly, JJ, Crosslin, DR, Dikilitas, O, Velez Edwards, DR, Feng, QP, Fisher, M, Freimuth, RR, Ge, T, Glessner, JT, Gordon, AS, Patterson, C, Hakonarson, H, Harden, M, Harr, M, Hirschhorn, J, Hoggart, C, Hsu, L, Irvin, MR, Jarvik, GP, Karlson, EW, Khan, A, Khera, A, Kiryluk, K, Kullo, I, Larkin, K, Limdi, N, Linder, JE, Loos, R, Luo, Y, Malolepsza, E, Manolio, TA, Martin, LJ, McCarthy, L, McNally, EM, Meigs, JB, Mersha, TB, Mosley, JD, Musick, A, Namjou, B, Pai, N, Pesce, LL, Peters, U, Peterson, JF, Prows, CA, Puckelwartz, MJ, Rehm, HL, Roden, DM, Rosenthal, EA, Rowley, R, Sawicki, KT, Schaid, DJ, Smit, RAJ, Smith, JL, Smoller, JW, Thomas, M, Tiwari, H, Toledo, DM, Vaitinadin, NS, Veenstra, D, Walunas, TL, Wang, Z, Wei, WQ, Weng, C, Wiesner, GL, Yin, X, Kenny, EE, Berndt, S & Hirschhorn, J 2024, 'Selection, optimization and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse US populations', Nature Medicine, vol. 30, no. 2, pp. 480-487. https://doi.org/10.1038/s41591-024-02796-z

APA

Lennon, N. J., Kottyan, L. C., Kachulis, C., Abul-Husn, N. S., Arias, J., Belbin, G., Below, J. E., Berndt, S. I., Chung, W. K., Cimino, J. J., Clayton, E. W., Connolly, J. J., Crosslin, D. R., Dikilitas, O., Velez Edwards, D. R., Feng, Q. P., Fisher, M., Freimuth, R. R., Ge, T., ... Hirschhorn, J. (2024). Selection, optimization and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse US populations. Nature Medicine, 30(2), 480-487. https://doi.org/10.1038/s41591-024-02796-z

Vancouver

Lennon NJ, Kottyan LC, Kachulis C, Abul-Husn NS, Arias J, Belbin G et al. Selection, optimization and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse US populations. Nature Medicine. 2024;30(2):480-487. https://doi.org/10.1038/s41591-024-02796-z

Author

Lennon, Niall J. ; Kottyan, Leah C. ; Kachulis, Christopher ; Abul-Husn, Noura S. ; Arias, Josh ; Belbin, Gillian ; Below, Jennifer E. ; Berndt, Sonja I. ; Chung, Wendy K. ; Cimino, James J. ; Clayton, Ellen Wright ; Connolly, John J. ; Crosslin, David R. ; Dikilitas, Ozan ; Velez Edwards, Digna R. ; Feng, Qi Ping ; Fisher, Marissa ; Freimuth, Robert R. ; Ge, Tian ; Glessner, Joseph T. ; Gordon, Adam S. ; Patterson, Candace ; Hakonarson, Hakon ; Harden, Maegan ; Harr, Margaret ; Hirschhorn, Joel ; Hoggart, Clive ; Hsu, Li ; Irvin, Marguerite R. ; 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 A. ; Martin, Lisa J. ; McCarthy, Li ; McNally, Elizabeth M. ; Meigs, James B. ; Mersha, Tesfaye B. ; Mosley, Jonathan D. ; Musick, Anjene ; Namjou, Bahram ; Pai, Nihal ; Pesce, Lorenzo L. ; Peters, Ulrike ; Peterson, Josh F. ; Prows, Cynthia A. ; Puckelwartz, Megan J. ; Rehm, Heidi L. ; Roden, Dan M. ; Rosenthal, Elisabeth A. ; Rowley, Robb ; Sawicki, Konrad Teodor ; Schaid, Daniel J. ; Smit, Roelof A.J. ; Smith, Johanna L. ; Smoller, Jordan W. ; Thomas, Minta ; Tiwari, Hemant ; Toledo, Diana M. ; Vaitinadin, Nataraja Sarma ; Veenstra, David ; Walunas, Theresa L. ; Wang, Zhe ; Wei, Wei Qi ; Weng, Chunhua ; Wiesner, Georgia L. ; Yin, Xianyong ; Kenny, Eimear E. ; Berndt, Sonja ; Hirschhorn, Joel. / Selection, optimization and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse US populations. In: Nature Medicine. 2024 ; Vol. 30, No. 2. pp. 480-487.

Bibtex

@article{fb5accef948145fb9cc91a0e23e440c9,
title = "Selection, optimization and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse US populations",
abstract = "Polygenic risk scores (PRSs) have improved in predictive performance, but several challenges remain to be addressed before PRSs can be implemented in the clinic, including reduced predictive performance of PRSs in diverse populations, and the interpretation and communication of genetic results to both providers and patients. To address these challenges, the National Human Genome Research Institute-funded Electronic Medical Records and Genomics (eMERGE) Network has developed a framework and pipeline for return of a PRS-based genome-informed risk assessment to 25,000 diverse adults and children as part of a clinical study. From an initial list of 23 conditions, ten were selected for implementation based on PRS performance, medical actionability and potential clinical utility, including cardiometabolic diseases and cancer. Standardized metrics were considered in the selection process, with additional consideration given to strength of evidence in African and Hispanic populations. We then developed a pipeline for clinical PRS implementation (score transfer to a clinical laboratory, validation and verification of score performance), and used genetic ancestry to calibrate PRS mean and variance, utilizing genetically diverse data from 13,475 participants of the All of Us Research Program cohort to train and test model parameters. Finally, we created a framework for regulatory compliance and developed a PRS clinical report for return to providers and for inclusion in an additional genome-informed risk assessment. The initial experience from eMERGE can inform the approach needed to implement PRS-based testing in diverse clinical settings.",
author = "Lennon, {Niall J.} and Kottyan, {Leah C.} and Christopher Kachulis and Abul-Husn, {Noura S.} and Josh Arias and Gillian Belbin and Below, {Jennifer E.} and Berndt, {Sonja I.} and Chung, {Wendy K.} and Cimino, {James J.} and Clayton, {Ellen Wright} and Connolly, {John J.} and Crosslin, {David R.} and Ozan Dikilitas and {Velez Edwards}, {Digna R.} and Feng, {Qi Ping} and Marissa Fisher and Freimuth, {Robert R.} and Tian Ge and Glessner, {Joseph T.} and Gordon, {Adam S.} and Candace Patterson and Hakon Hakonarson and Maegan Harden and Margaret Harr and Joel Hirschhorn and Clive Hoggart and Li Hsu and Irvin, {Marguerite R.} and Jarvik, {Gail P.} and Karlson, {Elizabeth W.} and Atlas Khan and Amit Khera and Krzysztof Kiryluk and Iftikhar Kullo and Katie Larkin and Nita Limdi and Linder, {Jodell E.} and Ruth Loos and Yuan Luo and Edyta Malolepsza and Manolio, {Teri A.} and Martin, {Lisa J.} and Li McCarthy and McNally, {Elizabeth M.} and Meigs, {James B.} and Mersha, {Tesfaye B.} and Mosley, {Jonathan D.} and Anjene Musick and Bahram Namjou and Nihal Pai and Pesce, {Lorenzo L.} and Ulrike Peters and Peterson, {Josh F.} and Prows, {Cynthia A.} and Puckelwartz, {Megan J.} and Rehm, {Heidi L.} and Roden, {Dan M.} and Rosenthal, {Elisabeth A.} and Robb Rowley and Sawicki, {Konrad Teodor} and Schaid, {Daniel J.} and Smit, {Roelof A.J.} and Smith, {Johanna L.} and Smoller, {Jordan W.} and Minta Thomas and Hemant Tiwari and Toledo, {Diana M.} and Vaitinadin, {Nataraja Sarma} and David Veenstra and Walunas, {Theresa L.} and Zhe Wang and Wei, {Wei Qi} and Chunhua Weng and Wiesner, {Georgia L.} and Xianyong Yin and Kenny, {Eimear E.} and Sonja Berndt and Joel Hirschhorn",
note = "Publisher Copyright: {\textcopyright} The Author(s) 2024.",
year = "2024",
doi = "10.1038/s41591-024-02796-z",
language = "English",
volume = "30",
pages = "480--487",
journal = "Nature Medicine",
issn = "1078-8956",
publisher = "nature publishing group",
number = "2",

}

RIS

TY - JOUR

T1 - Selection, optimization and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse US populations

AU - Lennon, Niall J.

AU - Kottyan, Leah C.

AU - Kachulis, Christopher

AU - Abul-Husn, Noura S.

AU - Arias, Josh

AU - Belbin, Gillian

AU - Below, Jennifer E.

AU - Berndt, Sonja I.

AU - Chung, Wendy K.

AU - Cimino, James J.

AU - Clayton, Ellen Wright

AU - Connolly, John J.

AU - Crosslin, David R.

AU - Dikilitas, Ozan

AU - Velez Edwards, Digna R.

AU - Feng, Qi Ping

AU - Fisher, Marissa

AU - Freimuth, Robert R.

AU - Ge, Tian

AU - Glessner, Joseph T.

AU - Gordon, Adam S.

AU - Patterson, Candace

AU - Hakonarson, Hakon

AU - Harden, Maegan

AU - Harr, Margaret

AU - Hirschhorn, Joel

AU - Hoggart, Clive

AU - Hsu, Li

AU - Irvin, Marguerite R.

AU - Jarvik, Gail P.

AU - Karlson, Elizabeth W.

AU - Khan, Atlas

AU - Khera, Amit

AU - Kiryluk, Krzysztof

AU - Kullo, Iftikhar

AU - Larkin, Katie

AU - Limdi, Nita

AU - Linder, Jodell E.

AU - Loos, Ruth

AU - Luo, Yuan

AU - Malolepsza, Edyta

AU - Manolio, Teri A.

AU - Martin, Lisa J.

AU - McCarthy, Li

AU - McNally, Elizabeth M.

AU - Meigs, James B.

AU - Mersha, Tesfaye B.

AU - Mosley, Jonathan D.

AU - Musick, Anjene

AU - Namjou, Bahram

AU - Pai, Nihal

AU - Pesce, Lorenzo L.

AU - Peters, Ulrike

AU - Peterson, Josh F.

AU - Prows, Cynthia A.

AU - Puckelwartz, Megan J.

AU - Rehm, Heidi L.

AU - Roden, Dan M.

AU - Rosenthal, Elisabeth A.

AU - Rowley, Robb

AU - Sawicki, Konrad Teodor

AU - Schaid, Daniel J.

AU - Smit, Roelof A.J.

AU - Smith, Johanna L.

AU - Smoller, Jordan W.

AU - Thomas, Minta

AU - Tiwari, Hemant

AU - Toledo, Diana M.

AU - Vaitinadin, Nataraja Sarma

AU - Veenstra, David

AU - Walunas, Theresa L.

AU - Wang, Zhe

AU - Wei, Wei Qi

AU - Weng, Chunhua

AU - Wiesner, Georgia L.

AU - Yin, Xianyong

AU - Kenny, Eimear E.

AU - Berndt, Sonja

AU - Hirschhorn, Joel

N1 - Publisher Copyright: © The Author(s) 2024.

PY - 2024

Y1 - 2024

N2 - Polygenic risk scores (PRSs) have improved in predictive performance, but several challenges remain to be addressed before PRSs can be implemented in the clinic, including reduced predictive performance of PRSs in diverse populations, and the interpretation and communication of genetic results to both providers and patients. To address these challenges, the National Human Genome Research Institute-funded Electronic Medical Records and Genomics (eMERGE) Network has developed a framework and pipeline for return of a PRS-based genome-informed risk assessment to 25,000 diverse adults and children as part of a clinical study. From an initial list of 23 conditions, ten were selected for implementation based on PRS performance, medical actionability and potential clinical utility, including cardiometabolic diseases and cancer. Standardized metrics were considered in the selection process, with additional consideration given to strength of evidence in African and Hispanic populations. We then developed a pipeline for clinical PRS implementation (score transfer to a clinical laboratory, validation and verification of score performance), and used genetic ancestry to calibrate PRS mean and variance, utilizing genetically diverse data from 13,475 participants of the All of Us Research Program cohort to train and test model parameters. Finally, we created a framework for regulatory compliance and developed a PRS clinical report for return to providers and for inclusion in an additional genome-informed risk assessment. The initial experience from eMERGE can inform the approach needed to implement PRS-based testing in diverse clinical settings.

AB - Polygenic risk scores (PRSs) have improved in predictive performance, but several challenges remain to be addressed before PRSs can be implemented in the clinic, including reduced predictive performance of PRSs in diverse populations, and the interpretation and communication of genetic results to both providers and patients. To address these challenges, the National Human Genome Research Institute-funded Electronic Medical Records and Genomics (eMERGE) Network has developed a framework and pipeline for return of a PRS-based genome-informed risk assessment to 25,000 diverse adults and children as part of a clinical study. From an initial list of 23 conditions, ten were selected for implementation based on PRS performance, medical actionability and potential clinical utility, including cardiometabolic diseases and cancer. Standardized metrics were considered in the selection process, with additional consideration given to strength of evidence in African and Hispanic populations. We then developed a pipeline for clinical PRS implementation (score transfer to a clinical laboratory, validation and verification of score performance), and used genetic ancestry to calibrate PRS mean and variance, utilizing genetically diverse data from 13,475 participants of the All of Us Research Program cohort to train and test model parameters. Finally, we created a framework for regulatory compliance and developed a PRS clinical report for return to providers and for inclusion in an additional genome-informed risk assessment. The initial experience from eMERGE can inform the approach needed to implement PRS-based testing in diverse clinical settings.

U2 - 10.1038/s41591-024-02796-z

DO - 10.1038/s41591-024-02796-z

M3 - Journal article

C2 - 38374346

AN - SCOPUS:85185323827

VL - 30

SP - 480

EP - 487

JO - Nature Medicine

JF - Nature Medicine

SN - 1078-8956

IS - 2

ER -

ID: 385588190