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BACKGROUND: Hypertriglyceridemia (HTG) is a complex trait defined by elevated plasma triglyceride levels. Genetic determinants of HTG have so far been examined in a piecemeal manner; understanding of its molecular basis, both monogenic and polygenic, is thus incomplete.OBJECTIVE: The objective of this study was to characterize genetic profiles of patients with severe HTG, and quantify the genetic determinants and molecular contributors.METHODS: We concurrently assessed rare and common variants in two independent cohorts of 251 and 312 Caucasian patients with severe HTG. DNA was subjected to targeted next-generation sequencing of 73 genes and 185 SNPs associated with dyslipidemia. LPL, APOC2, GPIHBP1, APOA5, and LMF1 genes were screened for rare variants, and a polygenic risk score was used to assess the accumulation of common variants.RESULTS: As there were no significant differences in the prevalence of genetic determinants between cohorts, data were combined for all 563 patients: 1.1% had biallelic (homozygous or compound heterozygous) rare variants, 14.4% had heterozygous rare variants, 32.0% had an extreme accumulation of common variants (ie, high polygenic risk), and 52.6% remained genetically undefined. Patients with HTG were 5.77 times (95% CI [4.26-7.82]; P , .0001) more likely to carry one of these types of genetic susceptibility compared with controls.CONCLUSIONS: We report the most in-depth, systematic evaluation of genetic determinants of severe HTG to date. The predominant feature was an extreme accumulation of common variants (high polygenic risk score), whereas a substantial proportion of patients also carried heterozygous rare

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.

Accurate and consistent variant classification is imperative for incorporation of rapidly developing sequencing technologies into genomic medicine for improved patient care. An essential requirement for achieving standardized and reliable variant interpretation is data sharing, facilitated by a centralized open-source database. Familial hypercholesterolemia (FH) is an exemplar of the utility of such a resource: it has a high incidence, a favorable prognosis with early intervention and treatment, and cascade screening can be offered to families if a causative variant is identified. ClinVar, an NCBI-funded resource, has become the primary repository for clinically relevant variants in Mendelian disease, including FH. Here, we present the concerted efforts made by the Clinical Genome Resource, through the FH Variant Curation Expert Panel and global FH community, to increase submission of FH-associated variants into ClinVar. Variant-level data was categorized by submitter, variant characteristics, classification method and available supporting data. To further reform interpretation of FH-associated variants, areas for improvement in variant submissions were identified and addressed; these include a need for more detailed submissions and submission of supporting variant-level data, both retrospectively and prospectively. Collaborating to provide thorough, reliable evidence-based variant interpretation will ultimately improve the care of FH patients.