Daniel J. Schaid

BACKGROUND: Performance and transferability of contemporary polygenic risk scores (PRS) for atherosclerotic cardiovascular disease phenotypes may vary across PRS methods, training data, and trait ascertainment. METHODS: We aimed to investigate the performance and transferability of contemporary PRS for atherosclerotic cardiovascular disease subtypes: coronary heart disease (CHD), abdominal aortic aneurysm (AAA), ischemic stroke (IS), and peripheral artery disease (PAD), using the All of Us Workbench, which consists of a large, diverse cohort with whole-genome sequence data. We also developed and evaluated a multi-trait PRS for each subtype. Performance of PRS for 4 atherosclerotic cardiovascular disease subtypes was compared across genetic similarity groups in 245 388 All of Us participants. Groups genetically similar to European, African, admixed American, and remaining groups (combined as other) were used to assess PRS for CHD, IS, AAA, PAD, and multi-trait. RESULTS: PRS for CHD and AAA performed better than IS and PAD. For CHD, CHD _PGS003725 performed the best (hazard ratio per SD increase [95% CI]), across genetic ancestry groups, European, and African (1.72 [1.67–1.78], 1.23 [1.17–1.29]), with CHD _PGS004696 being best for admixed American (1.91 [1.70–2.15]), and CHD _PGS003356 for other (1.75 [1.58–1.95]). The best performing PRS for AAA was AAA _Multi for European, other, and admixed American (1.71 [1.52–1.92], 1.59 [1.07–2.37], 1.50 [0.90–2.52]) and AAA _PGS003972 for African (1.39 [1.19–1.63]). For IS, IS _Multi performed best for other and European (1.49 [1.17–1.89], 1.33 [1.25–1.42]), and IS _PGS000039 performed best in admixed American and African (1.17 [1.07–1.27], 1.09 [1.04–1.15]). For PAD, PAD _Multi performed best for all groups (other, 1.51 [1.19–1.92]; European, 1.32 [1.24–1.41]; admixed American, 1.23 [1.05–1.45]; and African, 1.18 [1.04–1.34]). CONCLUSIONS: Multi-trait and multi-ancestry PRS performed better than individual trait and/or single ancestry PRS for each atherosclerotic cardiovascular disease phenotype across ancestrally diverse and admixed individuals, with minimal change including adjustment for conventional risk factors.

The recent report from the National Academies of Sciences, Engineering and Medicine emphasizes the importance of detailed and tailored use of population descriptors in genomic analyses, but specific guidance for genomic data analysts is still lacking. In this Perspective, we focus on polygenic risk score (PRS) development and demonstrate that population descriptors are explicitly or implicitly involved in every step of the process. Attention to this matter is both an analytical concern and an ethical concern, as each decision has an impact on PRS results and performance across diverse populations. Drawing from the experience of the Polygenic Risk Methods Development (PRIMED) Consortium, we offer recommendations for applying population descriptors throughout the entire process of PRS development, validation and application. We urge the research community, particularly data analysts, to critically evaluate and justify their choices when using these descriptors to ensure both scientific rigor and research integrity.

Background: Admixture mapping can be leveraged to identify genomic loci associated with disease traits in admixed individuals such as Hispanic Americans. Methods and Results: We characterized fine‐scale population structure of participants (n=105 108) in the multiethnic eMERGE‐III (electronic Medical Records and Genomics) cohort, using reference panels from the 1000 Genomes Project and a Native American cohort. We defined “genetically admixed Hispanic Americans” as those having ≥10% Native American genetic ancestry (n=5025), in addition to European (specifically, Iberian) and African genetic ancestry. This population descriptor was subsequently applied to 3 other cohorts: the MESA (Multi‐Ethnic Study of Atherosclerosis; n=1176), WHI (Women’s Health Initiative; n=2873), and the HCHS/SOL (Hispanic Community Health Study/Study of Latinos; n=7804). We inferred local ancestry along the genome in genetically admixed Hispanic Americans in each cohort using RFMix2 with phased haplotypes from SHAPEIT2. Local ancestry proportions were used for admixture mapping of lipid traits (low‐density lipoprotein cholesterol, high‐density lipoprotein cholesterol, total cholesterol, and triglycerides) using extended linear mixed models that incorporated multiple or single ancestries. After accounting for fixed‐effect covariates and random effects, ancestry proportions at the following loci were associated with lipid traits in the HCHS/SOL cohort: 11q12.2 ( P =6.8×10 ⁻⁷ ) with low‐density lipoprotein cholesterol, 2p23.3 ( P =5.2×10 ⁻⁷ ) with total cholesterol, and 11q23.3 ( P =7.3×10 ⁻¹² ) with triglycerides. The LDL cholesterol and triglyceride loci replicated in at least one independent cohort, whereas the total cholesterol locus showed suggestive evidence for replication in the eMERGE cohort ( P =0.073). Native American (NAMR) ancestry appeared to drive the LDL‐C association, whereas both NAMR and Iberian population in Spain (IBS) ancestries contributed to the triglyceride signal. Conclusions: Admixture mapping in genetically admixed Hispanic Americans identified genomic loci influencing lipid traits and the different ancestral origins driving these associations.

Background: Performance and portability of contemporary polygenic risk scores (PRS) for atherosclerotic cardiovascular disease (ASCVD) phenotypes vary based on different methods, training data, and trait ascertainment. Objectives: We aimed to investigate performance and portability of contemporary PRS for ASCVD subtypes: coronary heart disease (CHD), abdominal aortic aneurysm (AAA), ischemic stroke (IS), and peripheral artery disease (PAD), using the All of Us Workbench which provides access to a large diverse cohort with phenotype and whole genome sequence data. We also developed and evaluated a multi-trait PRS for each subtype. Methods: Performance of PRS for 4 ASCVD traits and related risk factors was compared across genetic ancestry groups in 245,388 All of Us participants. Genetic EUR, African (AFR), Admixed American (AMR), and remaining ancestry groups (combined as Other, OTH) were defined by All of Us based on principal components. PRS for CHD, IS, AAA, PAD, and multi-trait (combining PRS for the 4 traits as well as PRS for ASCVD risk factors) were assessed for portability across genetic ancestry groups using hazard ratios (HR) per SD increase. Results: For CHD, CHD _PGS003725 performed the best (HR for 1 SD increase [95% CI]), across 4 genetic ancestry groups (EUR: 1.72[1.67-1.78], AFR: 1.24[1.18-1.31], AMR: 1.48[1.37-1.59], OTH: 1.65[1.52-1.79]). The best performing PRS for AAA was AAA _PGS003972 (EUR: 1.68[1.59-1.78], AFR: 1.29[1.13-1.48], AMR: 1.30[1.06-1.60], OTH: 1.45[1.20-1.75]). The best performing IS PRS was IS _PGS000039 in AFR (1.12[1.06-1.17]), AMR (1.11[1.04-1.19]), and OTH (1.23[1.09-1.38]), and IS _PGS004939 in EUR (1.16[1.12-1.20]). For PAD, PAD _PGS004940 performed best in EUR (1.26[1.22-1.30]), AFR (1.11[1.05-1.18]), AMR (1.08[1.01-1.16]), and OTH (1.13[1.04-1.22]). Multi-trait PRS performed better than individual trait PRS for each ASCVD phenotype. Also, PRS derived from multi-ancestry cohorts performed better than those derived from single ancestry. Conclusions: PRS for ASCVD developed from multi-ancestry cohorts and multiple related traits performed best across ancestrally diverse and admixed individuals. PRS for CHD and AAA performed better than those for IS and PAD.

BACKGROUND: Coronary atherosclerotic burden and adverse coronary heart disease events are related phenotypes with likely shared genetic cause. METHODS: We analyzed 6021 patients with available coronary angiography, genotyping, and exome sequencing data. We tested for associations of polygenic risk scores for coronary heart disease (PRS _CHD ) with multiple measures of coronary artery disease (CAD) severity. We assessed the joint associations of PRS _CHD and pathogenic/likely pathogenic variants in 3 familial hypercholesterolemia genes, with CAD severity. We performed mediation analyses to explore whether CAD severity mediated the association of PRS _CHD with prevalent coronary heart disease and incident myocardial infarction. RESULTS: A 1-SD increase in PRS _CHD was associated with multiple measures of CAD severity, including the log Gensini score (β, 0.31 [95% CI, 0.28–0.33]). Carrying a pathogenic/likely pathogenic familial hypercholesterolemia variant was associated with a higher log Gensini score after adjustment for PRS _CHD (β, 0.21 [95% CI, 0.03–0.38]). A 1-SD increase in PRS _CHD was associated with incident myocardial infarction over a mean follow-up of 9.2 years (hazard ratio, 1.20 [95% CI, 1.13–1.27]; P =5×10 ^{− 10} ), and the Gensini score mediated 90% of this association. CONCLUSIONS: PRS _CHD was associated with multiple measures of CAD severity. The association of PRS _CHD with incident myocardial infarction was almost fully mediated by CAD severity, indicating a considerable genetic overlap between the 2 phenotypes.

BACKGROUND: Predictive performance of polygenic risk scores (PRS) varies across populations. To facilitate equitable clinical use, we developed PRS for coronary heart disease (CHD; PRS _CHD ) for 5 genetic ancestry groups. METHODS: We derived ancestry-specific and multi-ancestry PRS _CHD based on pruning and thresholding (PRS _PT ) and ancestry-based continuous shrinkage priors (PRS _CSx ) applied to summary statistics from the largest multi-ancestry genome-wide association study meta-analysis for CHD to date, including 1.1 million participants from 5 major genetic ancestry groups. Following training and optimization in the Million Veteran Program, we evaluated the best-performing PRS _CHD in 176,988 individuals across 9 diverse cohorts. RESULTS: Multi-ancestry PRS _PT and PRS _CSx outperformed ancestry-specific PRS _PT and PRS _CSx across a range of tuning values. Two best-performing multi-ancestry PRS _CHD (ie, PRS _PTmult and PRS _CSxmult ) and 1 ancestry-specific (PRS _CSxEUR ) were taken forward for validation. PRS _PTmult demonstrated the strongest association with CHD in individuals of South Asian ancestry and European ancestry (odds ratio per 1 SD [95% CI, 2.75 [2.41–3.14], 1.65 [1.59–1.72]), followed by East Asian ancestry (1.56 [1.50–1.61]), Hispanic/Latino ancestry (1.38 [1.24–1.54]), and African ancestry (1.16 [1.11–1.21]). PRS _CSxmult showed the strongest associations in South Asian ancestry (2.67 [2.38–3.00]) and European ancestry (1.65 [1.59–1.71]), lower in East Asian ancestry (1.59 [1.54–1.64]), Hispanic/Latino ancestry (1.51 [1.35–1.69]), and the lowest in African ancestry (1.20 [1.15–1.26]). CONCLUSIONS: The use of summary statistics from a large multi-ancestry genome-wide meta-analysis improved the performance of PRS _CHD in most ancestry groups compared with single-ancestry methods. Despite the use of one of the largest and most diverse sets of training and validation cohorts to date, improvement of predictive performance was limited in African ancestry. This highlights the need for larger genome-wide association study datasets of underrepresented populations to enhance the performance of PRS _CHD .

Refinement of breast cancer risk estimates with a polygenic-risk score (PRS) may improve uptake of risk-reducing endocrine therapy (ET). A previous clinical trial assessed the influence of adding a PRS to traditional risk estimates on ET use. We stratified participants according to PRS-refined breast cancer risk and evaluated ET use and ET-related quality of life (QOL) at 1-year (previously reported) and 2-year follow-ups. Of 151 participants, 58 (38.4%) initiated ET, and 22 (14.6%) discontinued ET by 2 years; 42 (27.8%) and 36 (23.8%) participants were using ET at 1- and 2-year follow-ups, respectively. At the 2-year follow-up, 39% of participants with a lifetime breast cancer risk of 40.1% to 100.0%, 18% with a 20.1% to 40.0% risk, and 16% with a 0.0% to 20.0% risk were taking ET (overall P = 0.01). Moreover, 40% of participants whose breast cancer risk increased by 10% or greater with addition of the PRS to a traditional breast cancer-risk model were taking ET versus 0% whose risk decreased by 10% or greater (P = 0.004). QOL was similar for participants taking or not taking ET at 1- and 2-year follow-ups, although most who discontinued ET did so because of adverse effects. However, these QOL results may have been skewed by the long interval between QOL surveys and lack of baseline QOL data. PRS-informed breast cancer prevention counseling has a lasting, but waning, effect over time. Additional follow-up studies are needed to address the effect of PRS on ET adherence, ET-related QOL, supplemental breast cancer screening, and other risk-reducing behaviors.Prevention Relevance:Risk-reducing medications for breast cancer are considerably underused. Informing women at risk with precise and individualized risk assessment tools may substantially affect the incidence of breast cancer. In our study, a risk assessment tool (IBIS-polygenic-risk score) yielded promising results, with 39% of women at highest risk starting preventive medication.

Refinement of breast cancer risk estimates with a polygenic-risk score (PRS) may improve uptake of risk-reducing endocrine therapy (ET). A previous clinical trial assessed the influence of adding a PRS to traditional risk estimates on ET use. We stratified participants according to PRS-refined breast cancer risk and evaluated ET use and ET-related quality of life (QOL) at 1-year (previously reported) and 2-year follow-ups. Of 151 participants, 58 (38.4%) initiated ET, and 22 (14.6%) discontinued ET by 2 years; 42 (27.8%) and 36 (23.8%) participants were using ET at 1- and 2-year follow-ups, respectively. At the 2-year follow-up, 39% of participants with a lifetime breast cancer risk of 40.1% to 100.0%, 18% with a 20.1% to 40.0% risk, and 16% with a 0.0% to 20.0% risk were taking ET (overall P = 0.01). Moreover, 40% of participants whose breast cancer risk increased by 10% or greater with addition of the PRS to a traditional breast cancer-risk model were taking ET versus 0% whose risk decreased by 10% or greater (P = 0.004). QOL was similar for participants taking or not taking ET at 1- and 2-year follow-ups, although most who discontinued ET did so because of adverse effects. However, these QOL results may have been skewed by the long interval between QOL surveys and lack of baseline QOL data. PRS-informed breast cancer prevention counseling has a lasting, but waning, effect over time. Additional follow-up studies are needed to address the effect of PRS on ET adherence, ET-related QOL, supplemental breast cancer screening, and other risk-reducing behaviors.Prevention Relevance:Risk-reducing medications for breast cancer are considerably underused. Informing women at risk with precise and individualized risk assessment tools may substantially affect the incidence of breast cancer. In our study, a risk assessment tool (IBIS-polygenic-risk score) yielded promising results, with 39% of women at highest risk starting preventive medication.

The Supplemental Materials and Methods file depicts a representative graphical report provided to participants at Visits 1 and 2 that illustrates the participant’s estimated 5-year, 10-year, and remaining lifetime breast cancer risk (determined by NCI-BCRAT and IBIS with and without PRS).