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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.

SUBMITTER: Lennon NJ 

PROVIDER: S-EPMC10878968 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

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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 NJ   Kottyan Leah C LC   Kachulis Christopher C   Abul-Husn Noura S NS   Arias Josh J   Belbin Gillian G   Below Jennifer E JE   Berndt Sonja I SI   Chung Wendy K WK   Cimino James J JJ   Clayton Ellen Wright EW   Connolly John J JJ   Crosslin David R DR   Dikilitas Ozan O   Velez Edwards Digna R DR   Feng QiPing Q   Fisher Marissa M   Freimuth Robert R RR   Ge Tian T   Glessner Joseph T JT   Gordon Adam S AS   Patterson Candace C   Hakonarson Hakon H   Harden Maegan M   Harr Margaret M   Hirschhorn Joel N JN   Hoggart Clive C   Hsu Li L   Irvin Marguerite R MR   Jarvik Gail P GP   Karlson Elizabeth W EW   Khan Atlas A   Khera Amit A   Kiryluk Krzysztof K   Kullo Iftikhar I   Larkin Katie K   Limdi Nita N   Linder Jodell E JE   Loos Ruth J F RJF   Luo Yuan Y   Malolepsza Edyta E   Manolio Teri A TA   Martin Lisa J LJ   McCarthy Li L   McNally Elizabeth M EM   Meigs James B JB   Mersha Tesfaye B TB   Mosley Jonathan D JD   Musick Anjene A   Namjou Bahram B   Pai Nihal N   Pesce Lorenzo L LL   Peters Ulrike U   Peterson Josh F JF   Prows Cynthia A CA   Puckelwartz Megan J MJ   Rehm Heidi L HL   Roden Dan M DM   Rosenthal Elisabeth A EA   Rowley Robb R   Sawicki Konrad Teodor KT   Schaid Daniel J DJ   Smit Roelof A J RAJ   Smith Johanna L JL   Smoller Jordan W JW   Thomas Minta M   Tiwari Hemant H   Toledo Diana M DM   Vaitinadin Nataraja Sarma NS   Veenstra David D   Walunas Theresa L TL   Wang Zhe Z   Wei Wei-Qi WQ   Weng Chunhua C   Wiesner Georgia L GL   Yin Xianyong X   Kenny Eimear E EE  

Nature medicine 20240219 2


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 pipel  ...[more]

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