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

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  • Niall J. Lennon
  • Leah C. Kottyan
  • Christopher Kachulis
  • Noura S. Abul-Husn
  • Josh Arias
  • Gillian Belbin
  • Jennifer E. Below
  • Sonja I. Berndt
  • Wendy K. Chung
  • James J. Cimino
  • Ellen Wright Clayton
  • John J. Connolly
  • David R. Crosslin
  • Ozan Dikilitas
  • Digna R. Velez Edwards
  • Qi Ping Feng
  • Marissa Fisher
  • Robert R. Freimuth
  • Tian Ge
  • Joseph T. Glessner
  • Adam S. Gordon
  • Candace Patterson
  • Hakon Hakonarson
  • Maegan Harden
  • Margaret Harr
  • Joel Hirschhorn
  • Clive Hoggart
  • Li Hsu
  • Marguerite R. Irvin
  • Gail P. Jarvik
  • Elizabeth W. Karlson
  • Atlas Khan
  • Amit Khera
  • Krzysztof Kiryluk
  • Iftikhar Kullo
  • Katie Larkin
  • Nita Limdi
  • Jodell E. Linder
  • Yuan Luo
  • Edyta Malolepsza
  • Teri A. Manolio
  • Lisa J. Martin
  • Li McCarthy
  • Elizabeth M. McNally
  • James B. Meigs
  • Tesfaye B. Mersha
  • Jonathan D. Mosley
  • Anjene Musick
  • Bahram Namjou
  • Nihal Pai
  • Lorenzo L. Pesce
  • Ulrike Peters
  • Josh F. Peterson
  • Cynthia A. Prows
  • Megan J. Puckelwartz
  • Heidi L. Rehm
  • Dan M. Roden
  • Elisabeth A. Rosenthal
  • Robb Rowley
  • Konrad Teodor Sawicki
  • Daniel J. Schaid
  • Johanna L. Smith
  • Jordan W. Smoller
  • Minta Thomas
  • Hemant Tiwari
  • Diana M. Toledo
  • Nataraja Sarma Vaitinadin
  • David Veenstra
  • Theresa L. Walunas
  • Zhe Wang
  • Wei Qi Wei
  • Chunhua Weng
  • Georgia L. Wiesner
  • Xianyong Yin
  • Eimear E. Kenny
  • Sonja Berndt
  • Joel Hirschhorn

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.

Original languageEnglish
JournalNature Medicine
Volume30
Issue number2
Pages (from-to)480-487
Number of pages8
ISSN1078-8956
DOIs
Publication statusPublished - 2024

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© The Author(s) 2024.

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