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

ABSTRACT: 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.

SUBMITTER: Lennon NJ

PROVIDER: S-EPMC10275001 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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

Lennon Niall J NJ Kottyan Leah C LC Kachulis Christopher C Abul-Husn Noura N Arias Josh J Belbin Gillian G Below Jennifer E JE Berndt Sonja S Chung Wendy W Cimino James J JJ Clayton Ellen Wright EW Connolly John J JJ Crosslin David D Dikilitas Ozan O Velez Edwards Digna R DR Feng QiPing Q Fisher Marissa M Freimuth Robert R Ge Tian T Glessner Joseph T JT Gordon Adam A Guiducci Candace C Hakonarson Hakon H Harden Maegan M Harr Margaret M Hirschhorn Joel J Hoggart Clive C Hsu Li L Irvin Ryan R 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 R Luo Yuan Y Malolepsza Edyta E Manolio Teri T Martin Lisa J LJ McCarthy Li L Meigs James B JB Mersha Tesfaye B TB Mosley Jonathan J Namjou Bahram B Pai Nihal N Pesce Lorenzo L LL Peters Ulrike U Peterson Josh J Prows Cynthia A CA Puckelwartz Megan J MJ Rehm Heidi H Roden Dan D Rosenthal Elisabeth A EA Rowley Robb R Sawicki Konrad Teodor KT Schaid Dan D Schmidlen Tara T Smit Roelof R Smith Johanna J Smoller Jordan W JW Thomas Minta M Tiwari Hemant H Toledo Diana D Vaitinadin Nataraja Sarma NS Veenstra David D Walunas Theresa T Wang Zhe Z Wei Wei-Qi WQ Weng Chunhua C Wiesner Georgia G Xianyong Yin Y Kenny Eimear E

medRxiv : the preprint server for health sciences 20230605

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 ...[more]

PMID: 37333246

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Project description:BackgroundType 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.MethodsWe 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.ResultsThe 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.ConclusionsBy 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.

Dataset Information

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

Publications

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

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