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.

Figure 1.

Timeline and process for selection, evaluation, optimization, transfer, validation, and implementation of the clinical PRS test pipeline. Dotted lines represent pivotal moments in the progression of the project.

Figure 2.

Overview of the eMERGE PRS process. Participant DNA is genotyped using the Illumina Global Diversity Array which assesses 1.8M sites. Genotyping data is phased and imputed with a reference panel derived from the 1000 Genomes Project. Raw PRS scores are calculated for each condition. For each condition an ancestry calibration model is applied based on model parameters derived from the All of Us Research Program. Participants whose adjusted scores cross the pre-defined threshold for high PRS are identified and a pdf report is generated. The report is electronically signed after data review by a clinical laboratory director and delivered to the study portal for return to the clinical sites.

Figure 3.

Summary of the ten conditions that were implemented. “High-PRS Threshold” represents the percentile that is deemed to be the cut-off for a specific condition above which a high PRS result is reported for that condition. The Odds Ratios are the OR of the implemented scores, 95% confidence interval shown in the whiskers (with the exception of Obesity for which the OR will be published by the GIANT consortium). “Number of SNPs” represents the range of numbers or sites included in each score. “Age ranges for return” indicates the participant ages at which a PRS is calculated for a given condition. AFIB= Atrial fibrillation; BC = Breast Cancer; CKD = Chronic Kidney Disease; CHD = Coronary Heart Disease; HC = Hypercholesterolemia; PC = Prostate Cancer; T2D = Type 2 Diabetes; T1D = Type 1 Diabetes.

Figure 4 -. Summary of first 2500 clinical samples

Upper left - Principal component of ancestry indicating participants with a result of ‘high PRS’ for any condition (red dots) compared to participants who did not have a high PRS identified (gray dots). Lower Left - summary of number of high risk conditions found per participant. Left - Observed numbers of high risk PRS called per condition. Note not all participants get scored for every condition based on age and sex at birth filters. AFIB= Atrial fibrillation; BC = Breast Cancer; CKD = Chronic Kidney Disease; CHD = Coronary Heart Disease; HC = Hypercholesterolemia; PC = Prostate Cancer; T2D = Type 2 Diabetes; T1D = Type 1 Diabetes.