Schaid, Daniel J.

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.

Background Measles remains a public health threat in the United States with over 50,000 cases being reported from 1989 through 1991 with continued smaller outbreaks. Measles vaccine failure is in part to blame for these large-scale outbreaks. The human leukocyte antigen (HLA) genes are important determinants of immune response to measles virus and vaccine. To examine the influence that HLA polymorphisms may have on measles vaccine antibody response, we compared the distribution of HLA-DRB1 alleles between measles vaccine nonresponders and hyper-responders. Methods We determined the seroprevalence of measles antibody in 881 school children immunized with measles-mumps-rubella-II at age 15 months using a whole virus IgG EIA. We performed class II HLA-DR typing by PCR with sequence specific primers (PCR-SSP) on 81 nonresponders (IgG seronegative) and 65 hyper-responders (from the upper 10th percentile of IgG levels of all subjects). We then compared the distribution of alleles between nonresponders and hyper-responders. Results The distribution of HLA-DRB1 alleles among nonresponders compared to hyper-responders was significantly different ( p = 0.014). Nonresponders were significantly less likely to carry the HLA-DRB1*13 alleles than were hyper-responders (7.4% vs 16.2%; p = 0.02). Nonresponders also had an excess of HLA-DRB1*07 alleles (15.4% vs 6.2%; p = 0.015). Conclusions The absence of HLA-DRB1*13 alleles is associated with measles vaccine nonresponse. The absence of this allele has also been associated with susceptibility to other infectious diseases. The role of this gene in the immunogenetic response to infectious diseases requires further study.

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.

10544 Background: Incorporation of Polygenic Risk Scores (PRS) can refine traditional breast cancer risk assessment models to provide precise estimates of breast cancer risk. However, the impact of such an integrated model on clinical decision-making related to breast cancer surveillance and preventive strategies is not fully understood. Methods: The GENRE-2 is a prospective single-arm multisite clinical trial (NCT04474834) incorporating PRS into standard breast cancer risk assessment models to determine the impact of PRS on clinical decisions on breast cancer prevention and surveillance. Women at high risk of breast cancer due to NCI-BCRAT 5-year risk of ≥ 3%, or IBIS (Tyrer-Cuzik) 10-year breast cancer risk of ≥5%, biopsy-proven high-risk breast lesion, or a pathogenic variant (PV) in ATM , BRCA1, BRCA2, CHEK2 or PALB2 , were enrolled from five sites in the United States. All women were invited to complete surveys on their breast surveillance and cancer prevention decisions based on pre-PRS standard risk models and post-PRS risk estimation, and further annual surveys are planned for 10 years. Results: Among 902 women enrolled in the study, 605 (median age: 52 years) received PRS results and completed a survey to date. Of those who received PRS results,195 (32.2%) were PV carriers. Among non-carriers, the median 10-year and lifetime pre-PRS IBIS-based risk was 10.0% and 28.7%, respectively. Among PV carriers, the CanRisk-based 10-year and lifetime pre-PRS risk estimates were 6.3% and 25.2% for ATM , 22.3% and 77.6% for BRCA1 , 18.5% and 77.7% for BRCA2 , 7.1% and 25.7% for CHEK2 , and 16.8% and 38.0% for PALB2 PV carriers, respectively. After the incorporation of PRS, the lifetime risk of breast cancer increased by at least 10% in 31% of non-carriers and 7.7% of PV carriers and decreased by at least 10% in 10.7% of non-carriers and 7.7% of PV carriers. The proportion of non-carriers with lifetime risk < 20% or > 40% changed from 17.3% and 22.0%, respectively, in the pre-PRS evaluation to 24.4% and 32.9%, in the post-PRS evaluation. A higher lifetime post-PRS score was associated with intent to take preventive action (surgery or endocrine agents). In non-carriers, the proportion of women with a lifetime risk < 20% with intent to take preventive action was 11%, compared to 36.8% of those with a lifetime risk > 40% (p < 0.001). Similarly, in PV carriers, the proportion of women with lifetime risk < 20% with intent to take preventive action was 20.8% compared to 41.1% of those with lifetime risk > 40% (p = 0.015). Conclusions: The GENRE-2 trial demonstrates that the incorporation of PRS into breast cancer risk assessment models in high-risk women is feasible and leads to clinically meaningful changes in breast cancer risk estimates and decision-making regarding preventive strategies. Evaluation of the implementation of breast cancer risk management strategies in study participants is ongoing and will be reported. Clinical trial information: NCT04474834 .

Introduction: The overall amount and the distribution of body fat, proxied by body-mass index (BMI) and waist-to-hip ratio (WHR), are two important measures of obesity and have significant polygenic heritability. We aimed to investigate whether polygenic scores (PGS) for these traits have additional predictive utility, beyond phenotypic characterization of obesity, for cardiovascular-kidney-metabolic (CKM) health. Methods: We derived PGS for BMI (PGS BMI ) and WHR adjusted for BMI (PGS WHRadjBMI ) using PRS-CS-auto on summary statistics from ~700k individuals of European ancestry (EA) in the GIANT consortium and selecting ~1M common variants for each score. We conducted association analyses in the Atherosclerosis Risk in Communities study, a prospective cohort including 8,631 EA individuals with ascertainment of incident diabetes, hypertension, chronic kidney disease, atrial fibrillation, coronary heart disease, ischemic stroke, and heart failure. We used nested Cox models to measure the added predictive utility of PGS to BMI and WHR for incident CKM phenotypes. Results: The study cohort (age 54.4±5.7 years, 52.4% women, follow-up 24.5±7.6 years) had a baseline BMI of 26.4 kg/m 2 (median [IQR]; 21.6-29.6) and WHR of 0.94 (0.88-0.98). PGS BMI and PGS WHRadjBMI were associated with their phenotypes (partial R 2 ; BMI 0.11 and WHR 0.04, p <0.001), although with a large phenotypic variability across the distribution of PGS (IQR for 1 st and 10 th deciles of PGS; BMI 19.6-28.3 and 22.6-35.9, WHR 0.79-1.03 and 0.87-1.05). Anthropometric measures of obesity were associated with a wider gradient of risk compared to PGS for obesity–most notable for diabetes and cardiovascular phenotypes (Table 1a). Addition of PGS BMI and PGS WHRadjBMI to BMI and WHR resulted in limited improvement in risk discrimination across incident CKM phenotypes (Table 1b). Conclusions: Observed anthropometric measures of obesity are sufficient, and for certain conditions far superior, to capture the risk of incident CKM phenotypes. These findings suggest PGS for adiposity traits likely have limited clinical utility to refine risk stratification for CKM syndrome among middle aged adults.

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 .

Abstract 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.