Genetic determinants of polygenic prediction accuracy within a population

Genomic risk prediction is on the emerging path towards personalized medicine. However, the accuracy of polygenic prediction varies strongly in different individuals. In this study, based on up to 352,277 White British participants in the UK Biobank, we constructed polygenic risk scores for 15 physiological and biochemical quantitative traits after performing genome-wide association studies (GWASs). We identified 185 polygenic prediction variability quantitative trait loci (pvQTLs) for 11 traits by Levene’s test among 254,376 unrelated individuals. We validated the effects of pvQTLs using an independent test set of 58,927 individuals. A score aggregating 51 pvQTL SNPs for triglycerides had the strongest Spearman correlation of 0.185 (p-value < 1.0x10−300) with the squared prediction errors. We found a strong enrichment of complex genetic effects conferred by pvQTLs compared to risk loci identified in GWASs, including 89 pvQTLs exhibiting dominance effects. Incorporation of dominance effects into polygenic risk scores significantly improved polygenic prediction for triglycerides, low-density lipoprotein cholesterol, vitamin D, and platelet. After including 87 dominance effects for triglycerides, the adjusted R2 for the polygenic risk score had an 8.1% increase on the test set. In addition, 108 pvQTLs had significant interaction effects with measured environmental or lifestyle exposures. In conclusion, we have discovered and validated genetic determinants of polygenic prediction variability for 11 quantitative biomarkers, and partially profiled the underlying complex genetic effects. These findings may assist interpretation of genomic risk prediction in various contexts, and encourage novel approaches for constructing polygenic risk scores with complex genetic effects.

Integration of Genomic Risk Scores to Improve the Prediction of Childhood Asthma Diagnosis

Genome-wide and epigenome-wide association studies have identified genetic variants and differentially methylated nucleotides associated with childhood asthma. Incorporation of such genomic data may improve performance of childhood asthma prediction models which use phenotypic and environmental data. Using genome-wide genotype and methylation data at birth from the Isle of Wight Birth Cohort (n = 1456), a polygenic risk score (PRS), and newborn (nMRS) and childhood (cMRS) methylation risk scores, were developed to predict childhood asthma diagnosis. Each risk score was integrated with two previously published childhood asthma prediction models (CAPE and CAPP) and were validated in the Manchester Asthma and Allergy Study. Individually, the genomic risk scores demonstrated modest-to-moderate discriminative performance (area under the receiver operating characteristic curve, AUC: PRS = 0.64, nMRS = 0.55, cMRS = 0.54), and their integration only marginally improved the performance of the CAPE (AUC: 0.75 vs. 0.71) and CAPP models (AUC: 0.84 vs. 0.82). The limited predictive performance of each genomic risk score individually and their inability to substantially improve upon the performance of the CAPE and CAPP models suggests that genetic and epigenetic predictors of the broad phenotype of asthma are unlikely to have clinical utility. Hence, further studies predicting specific asthma endotypes are warranted.

Prognostic Value of a Polygenic Risk Score for Coronary Heart Disease in Individuals Aged 70 Years and Older

Background: The use of a polygenic risk score (PRS) to improve risk prediction of coronary heart disease (CHD) events has been demonstrated to have clinical utility in the general adult population. However, the prognostic value of a PRS for CHD has not been examined specifically in older populations of individuals aged ≥70 years, who comprise a distinct high-risk subgroup. The objective of this study was to evaluate the predictive value of a PRS for incident CHD events in a prospective cohort of older individuals without a history of cardiovascular events. Methods: We used data from 12 792 genotyped, healthy older individuals enrolled into the ASPREE trial (Aspirin in Reducing Events in the Elderly), a randomized double-blind placebo-controlled clinical trial investigating the effect of daily 100 mg aspirin on disability-free survival. Participants had no previous history of diagnosed atherothrombotic cardiovascular events, dementia, or persistent physical disability at enrollment. We calculated a PRS (meta-genomic risk score) consisting of 1.7 million genetic variants. The primary outcome was a composite of incident myocardial infarction or CHD death over 5 years. Results: At baseline, the median population age was 73.9 years, and 54.9% were female. In total, 254 incident CHD events occurred. When the PRS was added to conventional risk factors, it was independently associated with CHD (hazard ratio, 1.24 [95% CI, 1.08–1.42], P =0.002). The area under the curve of the conventional model was 70.53 (95% CI, 67.00–74.06), and after inclusion of the PRS increased to 71.78 (95% CI, 68.32–75.24, P =0.019), demonstrating improved prediction. Reclassification was also improved, as the continuous net reclassification index after adding PRS to the conventional model was 0.25 (95% CI, 0.15–0.28). Conclusion: A PRS for CHD performs well in older people and improves prediction over conventional cardiovascular risk factors. Our study provides evidence that genomic risk prediction for CHD has clinical utility in individuals aged 70 years and older. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01038583

A nomogram for predicting probability of low risk of MammaPrint results in women with clinically high-risk breast cancer

We aimed to develop a prediction MammaPrint (MMP) genomic risk assessment nomogram model for hormone-receptor positive (HR+) and human epidermal growth factor receptor-2 negative (HER2–) breast cancer and minimal axillary burden (N0-1) tumors using clinicopathological factors of patients who underwent an MMP test for decision making regarding adjuvant chemotherapy. A total of 409 T1-3 N0-1 M0 HR + and HER2– breast cancer patients whose MMP genomic risk results and clinicopathological factors were available from 2017 to 2020 were analyzed. With randomly selected 306 patients, we developed a nomogram for predicting a low-risk subgroup of MMP results and externally validated with remaining patients (n = 103). Multivariate analysis revealed that the age at diagnosis, progesterone receptor (PR) score, nuclear grade, and Ki-67 were significantly associated with MMP risk results. We developed an MMP low-risk predictive nomogram. With a cut off value at 5% and 95% probability of low-risk MMP, the nomogram accurately predicted the results with 100% positive predictive value (PPV) and negative predictive value respectively. When applied to cut-off value at 35%, the specificity and PPV was 95% and 86% respectively. The area under the receiver operating characteristic curve was 0.82 (95% confidence interval [CI] 0.77 to 0.87). When applied to the validation group, the nomogram was accurate with an area under the curve of 0.77 (95% CI 0.68 to 0.86). Our nomogram, which incorporates four traditional prognostic factors, i.e., age, PR, nuclear grade, and Ki-67, could predict the probability of obtaining a low MMP risk in a cohort of high clinical risk patients. This nomogram can aid the prompt selection of patients who does not need additional MMP testing.

The incidence of discordant clinical and genomic risk in patients with invasive lobular or ductal carcinoma of the breast: a National Cancer Database Study

When molecular testing classifies breast tumors as low risk but clinical risk is high, the optimal management strategy is unknown. One group of patients who may be more likely to have such discordant risk are those with invasive lobular carcinoma of the breast. We sought to examine whether patients with invasive lobular carcinoma are more likely to have clinical high/genomic low-risk tumors compared to those with invasive ductal carcinoma, and to evaluate the impact on receipt of chemotherapy and overall survival. We conducted a cohort study using the National Cancer Database from 2010–2016. Patients with hormone receptor positive, HER2 negative, stage I-III breast cancer who underwent 70-gene signature testing were included. We evaluated the proportion of patients with discordant clinical and genomic risk by histology using Kaplan-Meier plots, log-rank tests, and Cox proportional hazards models with and without propensity score matching. A total of 7399 patients (1497 with invasive lobular carcinoma [20.2%]) were identified. Patients with invasive lobular carcinoma were significantly more likely to fall into a discordant risk category compared to those with invasive ductal carcinoma (46.8% versus 37.1%, p < 0.001), especially in the clinical high/genomic low risk subgroup (35.6% versus 19.2%, p < 0.001). In unadjusted analysis of the clinical high/genomic low-risk cohort who received chemotherapy, invasive ductal carcinoma patients had significantly improved overall survival compared to those with invasive lobular carcinoma (p = 0.02). These findings suggest that current tools for stratifying clinical and genomic risk could be improved for those with invasive lobular carcinoma to better tailor treatment selection.

Non-cancer-related pathogenic germline variants and expression consequences in ten-thousand cancer genomes

Background DNA sequencing is increasingly incorporated into the routine care of cancer patients, many of whom also carry inherited, moderate/high-penetrance variants associated with other diseases. Yet, the prevalence and consequence of such variants remain unclear. Methods We analyzed the germline genomes of 10,389 adult cancer cases in the TCGA cohort, identifying pathogenic/likely pathogenic variants in autosomal-dominant genes, autosomal-recessive genes, and 59 medically actionable genes curated by the American College of Molecular Genetics (i.e., the ACMG 59 genes). We also analyzed variant- and gene-level expression consequences in carriers. Results The affected genes exhibited varying pan-ancestry and population-specific patterns, and overall, the European population showed the highest frequency of pathogenic/likely pathogenic variants. We further identified genes showing expression consequence supporting variant functionality, including altered gene expression, allelic specific expression, and mis-splicing determined by a massively parallel splicing assay. Conclusions Our results demonstrate that expression-altering variants are found in a substantial fraction of cases and illustrate the yield of genomic risk assessments for a wide range of diseases across diverse populations.

A Nomogram for Predicting Mammaprint Results in Women with T1-3N0-1M0 Hormone Receptor-Positive and Human Epidermal Growth Factor Receptor-2-Negative Breast Cancer

PurposeWe aimed to develop a prediction MammaPrint (MMP) genomic risk assessment nomogram model for hormone-receptor-positive and human epidermal growth factor receptor-2 (HER2)-negative breast cancer and minimal axillary burden (N0-1) tumors using clinicopathological factors of patients who underwent an MMP test for decision making regarding adjuvant chemotherapy.MethodsA total of 409 T1-3 N0-1 M0 hormone receptor-positive and HER2-negative breast cancer patients whose MMP genomic risk results were available at Asan Medical Center from 2017 to 2020 were enrolled. Patients were randomly assigned to training and validation subsets and logistic regression was performed. ResultsThe primary cohort (n = 409) included 216 (53.1%) T2-3 and 388 (94.8%) N1 patients. No patients were estrogen-receptor-negative or -weak, 175 (42.7%) had a high proliferation index (Ki-67 ≥ 20%), and 225 (55.0%) were premenopausal. Multivariate analysis revealed that the age at diagnosis, progesterone receptor (PR) score, nuclear grade, and Ki-67 were significantly associated with MMP risk results. We developed an MMP low-risk predictive nomogram. The area under the receiver operating characteristic curve was 0.82 (95% confidence interval [CI], 0.77 to 0.87). When applied to the validation group, the nomogram was accurate with an area under the curve of 0.77 (95% CI, 0.68 to 0.86).Conclusion Our nomogram, which incorporates four traditional prognostic factors, i.e., age, PR, nuclear grade, and Ki-67, could predict the probability of obtaining a low MMP risk in a cohort of intermediate clinical risk patients. This nomogram can aid the selection of patients who need additional MMP testing.

Impact of personal genomic risk information on melanoma prevention behaviors and psychological outcomes: a randomized controlled trial

Purpose We evaluated the impact of personal melanoma genomic risk information on sun-related behaviors and psychological outcomes. Methods In this parallel group, open, randomized controlled trial, 1,025 Australians of European ancestry without melanoma and aged 18–69 years were recruited via the Medicare database (3% consent). Participants were randomized to the intervention (n = 513; saliva sample for genetic testing, personalized melanoma risk booklet based on a 40-variant polygenic risk score, telephone-based genetic counseling, educational booklet) or control (n = 512; educational booklet). Wrist-worn ultraviolet (UV) radiation dosimeters (10-day wear) and questionnaires were administered at baseline, 1 month postintervention, and 12 months postbaseline. Results At 12 months, 948 (92%) participants completed dosimetry and 973 (95%) the questionnaire. For the primary outcome, there was no effect of the genomic risk intervention on objectively measured UV exposure at 12 months, irrespective of traditional risk factors. For secondary outcomes at 12 months, the intervention reduced sunburns (risk ratio: 0.72, 95% confidence interval: 0.54–0.96), and increased skin examinations among women. Melanoma-related worry was reduced. There was no overall impact on general psychological distress. Conclusion Personalized genomic risk information did not influence sun exposure patterns but did improve some skin cancer prevention and early detection behaviors, suggesting it may be useful for precision prevention. There was no evidence of psychological harm.