Over the past decade, genome-wide association studies have identified genetic variation associated with a wide range of human diseases and traits. These findings are now commonly aggregated into polygenic risk scores, which can bridge the gap between the initial discovery efforts and clinical applications for disease risk estimation. However, there is remarkable heterogeneity in the reporting of these risk scores due to a lack of accepted standards for the development, reporting, and application of PRS. This lack of rigorous standards hinders the translation of PRS into clinical care. The ClinGen Complex Disease Working Group, in a collaboration with the Polygenic Score (PGS) Catalog, have developed a novel PRS Reporting Statement (PRS-RS), updating previous standards to the current state of the field. Drawing upon experts in epidemiology, statistics, disease-specific applications, implementation, and policy, this 33-item reporting framework defines the minimal information needed to interpret and evaluate a PRS, especially with respect to any downstream clinical applications. Items span detailed descriptions of the study population (recruitment method, key demographics, inclusion/exclusion criteria, and phenotype definition), statistical methods for both PRS development and validation, and considerations for potential limitations of the published risk score and downstream clinical utility. Additionally, emphasis has been placed on data availability and transparency to facilitate reproducibility and benchmarking against other PRS, such as deposition in the publicly available PGS Catalog. By providing these criteria in a structured format that borrows from existing standards and ontologies, the use of this framework in publishing PRS will facilitate PRS translation into clinical care and progress towards defining best practices.

Background Polygenic scores—which quantify inherited risk by integrating information from many common sites of DNA variation—may enable a tailored approach to clinical medicine. However, alongside considerable enthusiasm, we and others have highlighted a lack of standardized approaches for score disclosure. Here, we review the landscape of polygenic score reporting and describe a generalizable approach for development of a polygenic score disclosure tool for coronary artery disease. Methods We assembled a working group of clinicians, geneticists, data visualization specialists, and software developers. The group reviewed existing polygenic score reports and then designed a two-page mock report for coronary artery disease. We then conducted a qualitative user-experience study with this report using an interview guide focused on comprehension, experience, and attitudes. Interviews were transcribed and analyzed for themes identification to inform report revision. Results Review of nine existing polygenic score reports from commercial and academic groups demonstrated significant heterogeneity, reinforcing the need for additional efforts to study and standardize score disclosure. Using a newly developed mock score report, we conducted interviews with ten adult individuals (50% females, 70% without prior genetic testing experience, age range 20–70 years) recruited via an online platform. We identified three themes from interviews: (1) visual elements, such as color and simple graphics, enable participants to interpret, relate to, and contextualize their polygenic score, (2) word-based descriptions of risk and polygenic scores presented as percentiles were the best recognized and understood, (3) participants had varying levels of interest in understanding complex genomic information and therefore would benefit from additional resources that can adapt to their individual needs in real time. In response to user feedback, colors used for communicating risk were modified to minimize unintended color associations and odds ratios were removed. All 10 participants expressed interest in receiving a polygenic score report based on their personal genomic information. Conclusions Our findings describe a generalizable approach to develop a polygenic score report understandable by potential patients. Although additional studies are needed across a wider spectrum of patient populations, these results are likely to inform ongoing efforts related to polygenic score disclosure within clinical practice.

Purpose of reviewThe relationship between elevated triglyceride levels (i.e. hypertriglyceridemia) and risk of atherosclerotic cardiovascular disease (ASCVD) has been investigated for decades. Recent genetic studies have sought to resolve the decades-old question of a causal relationship. Recent findingsGenetic studies seem to demonstrate associations between elevated triglyceride levels and ASCVD risk. Mendelian randomization studies suggest this association may be causal. However, simultaneous pleiotropic effects of metabolically linked lipid variables -such as non-HDL cholesterol, apolipoprotein B and HDL cholesterol -often go unaccounted for in these studies. Complex underlying pleiotropic interactions of triglycerides with these lipid fractions together with unmeasured intercalated nonlipid-related mechanisms, such as inflammation and coagulation, impair the ability of genetic studies to implicate a direct role for triglycerides on ASCVD risk. One potential mechanism seems largely driven by the cholesterol carried within triglyceride-rich lipoproteins and their remnants, rather than their triglyceride content.

IMPORTANCE Pathogenic variants associated with inherited cardiomyopathy are recognized as important and clinically actionable when identified, leading some clinicians to recommend population-wide genomic screening.OBJECTIVE To determine the prevalence and clinical importance of pathogenic variants associated with inherited cardiomyopathy within the context of contemporary clinical care. DESIGN, SETTING, AND PARTICIPANTS This was a genetic association study of participants in Atherosclerosis in Risk Communities (ARIC), recruited from 1987 to 1989, with median follow-up of 27 years, and the UK Biobank, recruited from 2006 to 2010, with median follow-up of 10 years. ARIC participants were recruited from 4 sites across the US. UK Biobank participants were recruited from 22 sites across the UK. Participants in the US were of African and European ancestry; those in the UK were of African, East Asian, South Asian, and European ancestry. Statistical analyses were performed between August 1, 2021, and February 9, 2022. EXPOSURES Rare genetic variants predisposing to inherited cardiomyopathy. MAIN OUTCOMES AND MEASURES Pathogenicity of observed DNA sequence variants in sequenced exomes of 13 genes (ACTC1,