ABSTRACT
Polygenic risk scores (PRSs), which often aggregate results from genome-wide association studies, can bridge the gap between initial discovery efforts and clinical applications for the estimation of disease risk using genetics. However, there is notable heterogeneity in the application and reporting of these risk scores, which hinders the translation of PRSs into clinical care. Here, in a collaboration between the Clinical Genome Resource (ClinGen) Complex Disease Working Group and the Polygenic Score (PGS) Catalog, we present the Polygenic Risk Score Reporting Standards (PRS-RS), in which we update the Genetic Risk Prediction Studies (GRIPS) Statement to reflect the present state of the field. Drawing on the input of experts in epidemiology, statistics, disease-specific applications, implementation and policy, this comprehensive reporting framework defines the minimal information that is needed to interpret and evaluate PRSs, especially with respect to downstream clinical applications. Items span detailed descriptions of study populations, statistical methods for the development and validation of PRSs and considerations for the potential limitations of these scores. In addition, we emphasize the need for data availability and transparency, and we encourage researchers to deposit and share PRSs through the PGS Catalog to facilitate reproducibility and comparative benchmarking. By providing these criteria in a structured format that builds on existing standards and ontologies, the use of this framework in publishing PRSs will facilitate translation into clinical care and progress towards defining best practice.
Subject(s)
Genetic Predisposition to Disease , Genetics, Medical/standards , Multifactorial Inheritance/genetics , Humans , Reproducibility of Results , Risk Assessment/standardsABSTRACT
As large-scale genomic screening becomes increasingly prevalent, understanding the influence of actionable results on healthcare utilization is key to estimating the potential long-term clinical impact. The eMERGE network sequenced individuals for actionable genes in multiple genetic conditions and returned results to individuals, providers, and the electronic health record. Differences in recommended health services (laboratory, imaging, and procedural testing) delivered within 12 months of return were compared among individuals with pathogenic or likely pathogenic (P/LP) findings to matched individuals with negative findings before and after return of results. Of 16,218 adults, 477 unselected individuals were found to have a monogenic risk for arrhythmia (n = 95), breast cancer (n = 96), cardiomyopathy (n = 95), colorectal cancer (n = 105), or familial hypercholesterolemia (n = 86). Individuals with P/LP results more frequently received services after return (43.8%) compared to before return (25.6%) of results and compared to individuals with negative findings (24.9%; p < 0.0001). The annual cost of qualifying healthcare services increased from an average of $162 before return to $343 after return of results among the P/LP group (p < 0.0001); differences in the negative group were non-significant. The mean difference-in-differences was $149 (p < 0.0001), which describes the increased cost within the P/LP group corrected for cost changes in the negative group. When stratified by individual conditions, significant cost differences were observed for arrhythmia, breast cancer, and cardiomyopathy. In conclusion, less than half of individuals received billed health services after monogenic return, which modestly increased healthcare costs for payors in the year following return.
Subject(s)
Breast Neoplasms , Cardiomyopathies , Adult , Humans , Female , Prospective Studies , Patient Acceptance of Health Care , Arrhythmias, Cardiac , Breast Neoplasms/genetics , Cardiomyopathies/geneticsABSTRACT
Because polygenic risk scores (PRSs) for coronary heart disease (CHD) are derived from mainly European ancestry (EA) cohorts, their validity in African ancestry (AA) and Hispanic ethnicity (HE) individuals is unclear. We investigated associations of "restricted" and genome-wide PRSs with CHD in three major racial and ethnic groups in the U.S. The eMERGE cohort (mean age 48 ± 14 years, 58% female) included 45,645 EA, 7,597 AA, and 2,493 HE individuals. We assessed two restricted PRSs (PRSTikkanen and PRSTada; 28 and 50 variants, respectively) and two genome-wide PRSs (PRSmetaGRS and PRSLDPred; 1.7 M and 6.6 M variants, respectively) derived from EA cohorts. Over a median follow-up of 11.1 years, 2,652 incident CHD events occurred. Hazard and odds ratios for the association of PRSs with CHD were similar in EA and HE cohorts but lower in AA cohorts. Genome-wide PRSs were more strongly associated with CHD than restricted PRSs were. PRSmetaGRS, the best performing PRS, was associated with CHD in all three cohorts; hazard ratios (95% CI) per 1 SD increase were 1.53 (1.46-1.60), 1.53 (1.23-1.90), and 1.27 (1.13-1.43) for incident CHD in EA, HE, and AA individuals, respectively. The hazard ratios were comparable in the EA and HE cohorts (pinteraction = 0.77) but were significantly attenuated in AA individuals (pinteraction= 2.9 × 10-3). These results highlight the potential clinical utility of PRSs for CHD as well as the need to assemble diverse cohorts to generate ancestry- and ethnicity PRSs.
Subject(s)
Black or African American/genetics , Coronary Disease/genetics , Genetic Predisposition to Disease , Hispanic or Latino/genetics , Multifactorial Inheritance/genetics , White People/genetics , Cohort Studies , Female , Humans , Male , Middle Aged , Odds RatioABSTRACT
PURPOSE: Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk. METHODS: To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report and will assess uptake of care recommendations after return of results. RESULTS: GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022. CONCLUSION: Return of a novel report for communicating monogenic, polygenic, and family history-based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.
Subject(s)
Genome , Genomics , Humans , Prospective Studies , Genomics/methods , Risk Factors , Risk AssessmentABSTRACT
Despite the increasing numbers of genetic assistants (GAs) in the genomics workforce, their training needs and how to best prepare GAs for their role have not been well defined. We sought to identify the current educational status of GAs, opinions on their training needs, and attitudes about GA training programs (GATPs). Survey links were emailed to NSGC members, 17 state genetic counseling (GC) professional organizations, and genomic medicine researchers. Respondents (n = 411) included GCs (n = 231) and GAs (n = 136). Like other studies, we found that the GA position is filled by a range of education levels and career aspirations. Most respondents supported the creation of GATPs, with 63% endorsing that GATPs would be helpful and half endorsing a short-term (3 months or less) program. Most believed GATPs should focus on general knowledge, with almost all practical skills learned on-the-job. If more GATPs are created, our survey provides evidence that graduates would be hired. Indeed, of those whose work setting required a bachelor's degree, the number of respondents who favored keeping that requirement was similar to the number who favored hiring a GA without a degree if they attended a GATP. However, there were concerns about GATPs. Many (44%) believed creating GATPs could discourage candidates from becoming GAs. We observed that there are two types of GAs: entry-level and bachelor's-level, with the entry-level being those who do not have and are not working to obtain a bachelor's degree and the bachelor's-level being those who do/are. GATPs could focus on the education of entry-level GAs, while gaps in the knowledge base of bachelor's-level GAs could be addressed by augmenting bachelor's curriculum or providing additional training after hire. Further research on the training needs of GAs and hiring practices of institutions will be vital to understanding their training needs and designing and implementing effective GATPs.
ABSTRACT
Advances in technologies for assessing genomic variation and an increasing understanding of the effects of genomic variants on health and disease are driving the transition of genomics from the research laboratory into clinical care. Genomic medicine, or the use of an individual's genomic information as part of their clinical care, is increasingly gaining acceptance in routine practice, including in assessing disease risk in individuals and their families, diagnosing rare and undiagnosed diseases, and improving drug safety and efficacy. We describe the major types and measurement tools of genomic variation that are currently of clinical importance, review approaches to interpreting genomic sequence variants, identify publicly available tools and resources for genomic test interpretation, and discuss several key barriers in using genomic information in routine clinical practice.
Subject(s)
Genomics/methods , Precision Medicine/methods , Genetic Predisposition to Disease , Humans , Pharmacogenomic VariantsABSTRACT
INTRODUCTION: Phenotyping algorithms enable the interpretation of complex health data and definition of clinically relevant phenotypes; they have become crucial in biomedical research. However, the lack of standardization and transparency inhibits the cross-comparison of findings among different studies, limits large scale meta-analyses, confuses the research community, and prevents the reuse of algorithms, which results in duplication of efforts and the waste of valuable resources. RECOMMENDATIONS: Here, we propose five independent fundamental dimensions of phenotyping algorithms-complexity, performance, efficiency, implementability, and maintenance-through which researchers can describe, measure, and deploy any algorithms efficiently and effectively. These dimensions must be considered in the context of explicit use cases and transparent methods to ensure that they do not reflect unexpected biases or exacerbate inequities.
Subject(s)
Biomedical Research , Electronic Health Records , Algorithms , Phenotype , Reference StandardsABSTRACT
OBJECTIVE: Data from DNA genotyping via a 96-SNP panel in a study of 25,015 clinical samples were utilized for quality control and tracking of sample identity in a clinical sequencing network. The study aimed to demonstrate the value of both the precise SNP tracking and the utility of the panel for predicting the sex-by-genotype of the participants, to identify possible sample mix-ups. RESULTS: Precise SNP tracking showed no sample swap errors within the clinical testing laboratories. In contrast, when comparing predicted sex-by-genotype to the provided sex on the test requisition, we identified 110 inconsistencies from 25,015 clinical samples (0.44%), that had occurred during sample collection or accessioning. The genetic sex predictions were confirmed using additional SNP sites in the sequencing data or high-density genotyping arrays. It was determined that discrepancies resulted from clerical errors (49.09%), samples from transgender participants (3.64%) and stem cell or bone marrow transplant patients (7.27%) along with undetermined sample mix-ups (40%) for which sample swaps occurred prior to arrival at genome centers, however the exact cause of the events at the sampling sites resulting in the mix-ups were not able to be determined.
Subject(s)
Clinical Laboratory Services , High-Throughput Nucleotide Sequencing , Humans , Bone Marrow Transplantation , Genotype , LaboratoriesABSTRACT
The fields of genetics and genomics have greatly expanded across medicine through the development of new technologies that have revealed genetic contributions to a wide array of traits and diseases. Thus, the development of widely available educational resources for all healthcare providers is essential to ensure the timely and appropriate utilization of genetics and genomics patient care. In 2020, the National Human Genome Research Institute released a call for new proposals to develop accessible, sustainable online education for health providers. This paper describes the efforts of the six teams awarded to reach the goal of providing genetic and genomic training modules that are broadly available for busy clinicians.
Subject(s)
Education, Distance , Medicine , Humans , Genomic Medicine , Genomics/education , Health Personnel/educationABSTRACT
BACKGROUND: The implications of secondary findings detected in large-scale sequencing projects remain uncertain. We assessed prevalence and penetrance of pathogenic familial hypercholesterolemia (FH) variants, their association with coronary heart disease (CHD), and 1-year outcomes following return of results in phase III of the electronic medical records and genomics network. METHODS: Adult participants (n=18 544) at 7 sites were enrolled in a prospective cohort study to assess the clinical impact of returning results from targeted sequencing of 68 actionable genes, including LDLR, APOB, and PCSK9. FH variant prevalence and penetrance (defined as low-density lipoprotein cholesterol >155 mg/dL) were estimated after excluding participants enrolled on the basis of hypercholesterolemia. Multivariable logistic regression was used to estimate the odds of CHD compared to age- and sex-matched controls without FH-associated variants. Process (eg, referral to a specialist or ordering new tests), intermediate (eg, new diagnosis of FH), and clinical (eg, treatment modification) outcomes within 1 year after return of results were ascertained by electronic health record review. RESULTS: The prevalence of FH-associated pathogenic variants was 1 in 188 (69 of 13,019 unselected participants). Penetrance was 87.5%. The presence of an FH variant was associated with CHD (odds ratio, 3.02 [2.00-4.53]) and premature CHD (odds ratio, 3.68 [2.34-5.78]). At least 1 outcome occurred in 92% of participants; 44% received a new diagnosis of FH and 26% had treatment modified following return of results. CONCLUSIONS: In a multisite cohort of electronic health record-linked biobanks, monogenic FH was prevalent, penetrant, and associated with presence of CHD. Nearly half of participants with an FH-associated variant received a new diagnosis of FH and a quarter had treatment modified after return of results. These results highlight the potential utility of sequencing electronic health record-linked biobanks to detect FH.
Subject(s)
Cardiovascular Diseases , Coronary Artery Disease , Hyperlipoproteinemia Type II , Adult , Humans , Proprotein Convertase 9/genetics , Electronic Health Records , Penetrance , Prevalence , Prospective Studies , Risk Factors , Hyperlipoproteinemia Type II/diagnosis , Hyperlipoproteinemia Type II/epidemiology , Hyperlipoproteinemia Type II/genetics , Coronary Artery Disease/genetics , Heart Disease Risk Factors , GenomicsABSTRACT
Clostridioides difficile (C. diff.) infection (CDI) is a leading cause of hospital acquired diarrhea in North America and Europe and a major cause of morbidity and mortality. Known risk factors do not fully explain CDI susceptibility, and genetic susceptibility is suggested by the fact that some patients with colons that are colonized with C. diff. do not develop any infection while others develop severe or recurrent infections. To identify common genetic variants associated with CDI, we performed a genome-wide association analysis in 19,861 participants (1349 cases; 18,512 controls) from the Electronic Medical Records and Genomics (eMERGE) Network. Using logistic regression, we found strong evidence for genetic variation in the DRB locus of the MHC (HLA) II region that predisposes individuals to CDI (P > 1.0 × 10-14; OR 1.56). Altered transcriptional regulation in the HLA region may play a role in conferring susceptibility to this opportunistic enteric pathogen.
Subject(s)
Clostridium Infections , Genome-Wide Association Study , Humans , Clostridium Infections/genetics , Diarrhea , Histocompatibility Antigens , HLA Antigens/genetics , Histocompatibility Antigens Class II , Genetic VariationABSTRACT
Objective: Data from DNA genotyping via a 96-SNP panel in a study of 25,015 clinical samples were utilized for quality control and tracking of sample identity in a clinical sequencing network. The study aimed to demonstrate the value of both the precise SNP tracking and the utility of the panel for predicting the sex-by-genotype of the participants, to identify possible sample mix-ups. Results: Precise SNP tracking showed no sample swap errors within the clinical testing laboratories. In contrast, when comparing predicted sex-by-genotype to the provided sex on the test requisition, we identified 110 inconsistencies from 25,015 clinical samples (0.44%), that had occurred during sample collection or accessioning. The genetic sex predictions were confirmed using additional SNP sites in the sequencing data or high-density genotyping arrays. It was determined that discrepancies resulted from clerical errors, samples from transgender participants and stem cell or bone marrow transplant patients along with undetermined sample mix-ups.
ABSTRACT
OBJECTIVE: The Genomic Medicine Working Group of the National Advisory Council for Human Genome Research virtually hosted its 13th genomic medicine meeting titled "Developing a Clinical Genomic Informatics Research Agenda". The meeting's goal was to articulate a research strategy to develop Genomics-based Clinical Informatics Tools and Resources (GCIT) to improve the detection, treatment, and reporting of genetic disorders in clinical settings. MATERIALS AND METHODS: Experts from government agencies, the private sector, and academia in genomic medicine and clinical informatics were invited to address the meeting's goals. Invitees were also asked to complete a survey to assess important considerations needed to develop a genomic-based clinical informatics research strategy. RESULTS: Outcomes from the meeting included identifying short-term research needs, such as designing and implementing standards-based interfaces between laboratory information systems and electronic health records, as well as long-term projects, such as identifying and addressing barriers related to the establishment and implementation of genomic data exchange systems that, in turn, the research community could help address. DISCUSSION: Discussions centered on identifying gaps and barriers that impede the use of GCIT in genomic medicine. Emergent themes from the meeting included developing an implementation science framework, defining a value proposition for all stakeholders, fostering engagement with patients and partners to develop applications under patient control, promoting the use of relevant clinical workflows in research, and lowering related barriers to regulatory processes. Another key theme was recognizing pervasive biases in data and information systems, algorithms, access, value, and knowledge repositories and identifying ways to resolve them.
Subject(s)
Medical Informatics , Electronic Health Records , Genome, Human , Genomics , Humans , Research DesignABSTRACT
Importance: Multiple polygenic risk scores (PRSs) for breast cancer have been developed from large research consortia; however, their generalizability to diverse clinical settings is unknown. Objective: To examine the performance of previously developed breast cancer PRSs in a clinical setting for women of European, African, and Latinx ancestry. Design, Setting, and Participants: This cohort study using the Electronic Medical Records and Genomics (eMERGE) network data set included 39â¯591 women from 9 contributing medical centers in the US that had electronic medical records (EMR) linked to genotype data. Breast cancer cases and controls were identified through a validated EMR phenotyping algorithm. Main Outcomes and Measures: Multivariable logistic regression was used to assess the association between breast cancer risk and 7 previously developed PRSs, adjusting for age, study site, breast cancer family history, and first 3 ancestry informative principal components. Results: This study included 39â¯591 women: 33â¯594 with European, 3801 with African, and 2196 with Latinx ancestry. The mean (SD) age at breast cancer diagnosis was 60.7 (13.0), 58.8 (12.5), and 60.1 (13.0) years for women with European, African, and Latinx ancestry, respectively. PRSs derived from women with European ancestry were associated with breast cancer risk in women with European ancestry (highest odds ratio [OR] per 1-SD increase, 1.46; 95% CI, 1.41-1.51), women with Latinx ancestry (highest OR, 1.31; 95% CI, 1.09-1.58), and women with African ancestry (OR, 1.19; 95% CI, 1.05-1.35). For women with European ancestry, this association with breast cancer risk was largest in the extremes of the PRS distribution, with ORs ranging from 2.19 (95% CI, 1.84-2.53) to 2.48 (95% CI, 1.89-3.25) for the 3 different PRSs examined for those in the highest 1% of the PRS compared with those in the middle quantile. Among women with Latinx and African ancestries at the extremes of the PRS distribution, there were no statistically significant associations. Conclusions and Relevance: This cohort study found that PRS models derived from women with European ancestry for breast cancer risk generalized well for women with European, Latinx, and African ancestries across different clinical settings, although the effect sizes for women with African ancestry were smaller, likely because of differences in risk allele frequencies and linkage disequilibrium patterns. These results highlight the need to improve representation of diverse population groups, particularly women with African ancestry, in genomic research cohorts.
Subject(s)
Black People/genetics , Breast Neoplasms/ethnology , Genetic Predisposition to Disease/ethnology , Hispanic or Latino/genetics , White People/genetics , Algorithms , Breast Neoplasms/genetics , Electronic Health Records , Female , Gene Frequency , Genomics , Humans , Information Storage and Retrieval , Linkage Disequilibrium , Logistic Models , Middle Aged , Odds Ratio , Phenotype , Risk FactorsABSTRACT
A femoral vein thrombosis, originally diagnosed with conventional ultrasound, was fully elucidated and monitored utilizing serial high-resolution magnetic resonance venography in a 19-year-old female with a family history of venous thromboembolism. Genetic testing revealed she was heterozygous for a F5 gene mutation, an abnormality that predisposes carriers to factor V Leiden thrombophilia. An additional risk factor included use of oral contraceptive pills. Subsequent testing of her family uncovered other carriers of the mutation, allowing for the implementation of preventive measures for the entire family. Although magnetic resonance venography has not yet proven to be a cost-effective method for monitoring clot resolution, the case presented here encourages further research on the clinical utility and cost-benefit of utilizing this technology for monitoring venous thrombosis and for clinical management purposes.