Highlights d A genome-wide polygenic score can quantify inherited susceptibility to obesity d Polygenic score effect on weight emerges early in life and increases into adulthood d Effect of polygenic score can be similar to a rare, monogenic obesity mutation d High polygenic score is a strong risk factor for severe obesity and associated diseases
The 2015 ACMG/AMP sequence variant interpretation guideline provided a framework for classifying variants based on several benign and pathogenic evidence criteria, including a pathogenic criterion (PVS1) for predicted loss of function variants. However, the guideline did not elaborate on specific considerations for the different types of loss of function variants, nor did it provide decision-making pathways assimilating information about variant type, its location, or any additional evidence for the likelihood of a true null effect. Furthermore, this guideline did not take into account the relative strengths for each evidence type and the final outcome of their combinations with respect to PVS1 strength. Finally, criteria specifying the genes for which PVS1 can be applied are still missing. Here, as part of the ClinGen Sequence Variant Interpretation (SVI) Workgroup's goal of refining ACMG/AMP criteria, we provide recommendations for applying the PVS1 criterion using detailed guidance addressing the above-mentioned gaps. Evaluation of the refined criterion by seven disease-specific groups using heterogeneous types of loss of function variants (n = 56) showed 89% agreement with the new recommendation, while discrepancies in six variants (11%) were appropriately due to disease-specific refinements. Our recommendations will facilitate consistent and accurate interpretation of predicted loss of function variants.
Due to the high genetic heterogeneity of hearing loss, current clinical testing includes sequencing large numbers of genes, which often yields a significant number of novel variants. Therefore, the standardization of variant interpretation is crucial to provide consistent and accurate diagnoses. The Hearing Loss Variant Curation Expert Panel was created within the Clinical Genome Resource to provide expert guidance for standardized genomic interpretation in the context of hearing loss. As one of its major tasks, our Expert Panel has adapted the ACMG/AMP guidelines for the interpretation of sequence variants in hearing loss genes. Here, we provide a comprehensive illustration of the newly specified ACMG/AMP hearing loss rules. Three rules remained unchanged, four rules were removed, and the remaining twenty-one rules were specified. These rules were further validated and refined using a pilot set of 51 variants assessed by curators and expert opinion. Of the 51 variants evaluated in the pilot, 37% (19/51) changed category based upon application of the expert panel specified rules and/or aggregation of evidence across laboratories. These hearing loss-specific ACMG/AMP rules will help standardize variant interpretation, ultimately leading to better care for individuals with hearing loss.
With advances in genomic sequencing technology, the number of reported gene-disease relationships has rapidly expanded. However, the evidence supporting these claims varies widely, confounding accurate evaluation of genomic variation in a clinical setting. Despite the critical need to differentiate clinically valid relationships from less well-substantiated relationships, standard guidelines for such evaluation do not currently exist. The NIH-funded Clinical Genome Resource (ClinGen) has developed a framework to define and evaluate the clinical validity of gene-disease pairs across a variety of Mendelian disorders. In this manuscript we describe a proposed framework to evaluate relevant genetic and experimental evidence supporting or contradicting a gene-disease relationship, and the subsequent validation of this framework using a set of representative gene-disease pairs. The framework provides a semi-quantitative measurement for the strength of evidence of a gene-disease relationship which correlates to a qualitative classification: “Definitive”, “Strong”, “Moderate”, “Limited”, “No Reported Evidence” or “Conflicting Evidence.” Within the ClinGen structure, classifications derived using this framework are reviewed and confirmed or adjusted based on clinical expertise of appropriate disease experts. Detailed guidance for utilizing this framework and access to the curation interface is available on our website. This evidence-based, systematic method to assess the strength of gene-disease relationships will facilitate more knowledgeable utilization of genomic variants in clinical and research settings.
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.
Non-alcoholic fatty liver disease is prevalent in human obesity and type 2 diabetes, and is characterized by increases in both hepatic triglyceride accumulation (denoted as steatosis) and expression of pro-inflammatory cytokines such as IL-1β. We report here that the development of hepatic steatosis requires IL-1 signaling, which upregulates Fatty acid synthase to promote hepatic lipogenesis. Using clodronate liposomes to selectively deplete liver Kupffer cells in ob/ob mice, we observed remarkable amelioration of obesity-induced hepatic steatosis and reductions in liver weight, triglyceride content and lipogenic enzyme expressions. Similar results were obtained with diet-induced obese mice, although visceral adipose tissue macrophage depletion also occurred in response to clodronate liposomes in this model. There were no differences in the food intake, whole body metabolic parameters, serum β-hydroxybutyrate levels or lipid profiles due to clodronate-treatment, but hepatic cytokine gene expressions including IL-1β were decreased. Conversely, treatment of primary mouse hepatocytes with IL-1β significantly increased triglyceride accumulation and Fatty acid synthase expression. Furthermore, the administration of IL-1 receptor antagonist to obese mice markedly reduced obesity-induced steatosis and hepatic lipogenic gene expression. Collectively, our findings suggest that IL-1β signaling upregulates hepatic lipogenesis in obesity, and is essential for the induction of pathogenic hepatic steatosis in obese mice.
ClinVar Miner is a Web-based suite that utilizes the data held in the National Center for Biotechnology Information's ClinVar archive. The goal is to render the data more accessible to processes pertaining to conflict resolution of variant interpretation as well as tracking details of data submission and data management for detailed variant curation. Here, we establish the use of these tools to address three separate use cases and to perform analyses across submissions. We demonstrate that the ClinVar Miner tools are an effective means to browse and consolidate data for variant submitters, curation groups, and general oversight. These tools are also relevant to the variant interpretation community in general.
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