The American College of Medical Genetics and American College of Pathologists (ACMG/AMP) variant classification guidelines for clinical reporting are widely used in diagnostic laboratories for ...variant interpretation. The ACMG/AMP guidelines recommend complete concordance of predictions among all in silico algorithms used without specifying the number or types of algorithms. The subjective nature of this recommendation contributes to discordance of variant classification among clinical laboratories and prevents definitive classification of variants.
Using 14,819 benign or pathogenic missense variants from the ClinVar database, we compared performance of 25 algorithms across datasets differing in distinct biological and technical variables. There was wide variability in concordance among different combinations of algorithms with particularly low concordance for benign variants. We also identify a previously unreported source of error in variant interpretation (false concordance) where concordant in silico predictions are opposite to the evidence provided by other sources. We identified recently developed algorithms with high predictive power and robust to variables such as disease mechanism, gene constraint, and mode of inheritance, although poorer performing algorithms are more frequently used based on review of the clinical genetics literature (2011-2017).
Our analyses identify algorithms with high performance characteristics independent of underlying disease mechanisms. We describe combinations of algorithms with increased concordance that should improve in silico algorithm usage during assessment of clinically relevant variants using the ACMG/AMP guidelines.
Whole-exome sequencing can provide insight into the relationship between observed clinical phenotypes and underlying genotypes.
We conducted a retrospective analysis of data from a series of 7374 ...consecutive unrelated patients who had been referred to a clinical diagnostic laboratory for whole-exome sequencing; our goal was to determine the frequency and clinical characteristics of patients for whom more than one molecular diagnosis was reported. The phenotypic similarity between molecularly diagnosed pairs of diseases was calculated with the use of terms from the Human Phenotype Ontology.
A molecular diagnosis was rendered for 2076 of 7374 patients (28.2%); among these patients, 101 (4.9%) had diagnoses that involved two or more disease loci. We also analyzed parental samples, when available, and found that de novo variants accounted for 67.8% (61 of 90) of pathogenic variants in autosomal dominant disease genes and 51.7% (15 of 29) of pathogenic variants in X-linked disease genes; both variants were de novo in 44.7% (17 of 38) of patients with two monoallelic variants. Causal copy-number variants were found in 12 patients (11.9%) with multiple diagnoses. Phenotypic similarity scores were significantly lower among patients in whom the phenotype resulted from two distinct mendelian disorders that affected different organ systems (50 patients) than among patients with disorders that had overlapping phenotypic features (30 patients) (median score, 0.21 vs. 0.36; P=1.77×10
).
In our study, we found multiple molecular diagnoses in 4.9% of cases in which whole-exome sequencing was informative. Our results show that structured clinical ontologies can be used to determine the degree of overlap between two mendelian diseases in the same patient; the diseases can be distinct or overlapping. Distinct disease phenotypes affect different organ systems, whereas overlapping disease phenotypes are more likely to be caused by two genes encoding proteins that interact within the same pathway. (Funded by the National Institutes of Health and the Ting Tsung and Wei Fong Chao Foundation.).
The prevalence of childhood cancer attributable to genetic predisposition was generally considered very low. However, recent reports suggest that at least 10% of pediatric cancer patients harbor a ...germline mutation in a cancer predisposition gene. Although some of these children will have a family history suggestive of a cancer predisposition syndrome, many others will not. Evidence from recent pediatric studies suggests that surveillance and early detection of cancer in individuals carrying a germline cancer predisposing mutation may result in improved outcomes. However, there is a lack of consistency in the design of cancer surveillance regimens across centers both nationally and internationally. To standardize approaches, the Pediatric Cancer Working Group of the American Association for Cancer Research (AACR) convened a workshop, during which consensus screening recommendations for children with the most common cancer predisposition syndromes were developed. In general, we considered a 5% or greater chance of developing a childhood cancer to be a reasonable threshold to recommend screening. Conditions for which the cancer risk was between 1% to 5% were addressed individually. In a series of manuscripts accompanying this article, we provide recommendations for surveillance, focusing on when to initiate and/or discontinue specific screening measures, which modalities to use, and the frequency of screening. Points of controversy are also reviewed. We present the outcome of our deliberations on consensus screening recommendations for specific disorders in 18 position articles as Open Access publications, which are freely available on an AACR-managed website.
Replication proofreading is crucial to avoid mutation accumulation in dividing cells. In humans, proofreading and replication repair is maintained by the exonuclease domains of DNA polymerases and ...the mismatch repair system. Individuals harboring germline mutations in genes involved in this process are at increased risk of early cancers from multiple organs. Biallelic mutations in any of the four mismatch repair genes
, and
result in one of the most aggressive childhood cancer predisposition syndromes, termed constitutional mismatch repair deficiency or constitutional mismatch repair deficiency syndrome (CMMRD). Data gathered in the last decade allow us to better define the clinical manifestations, tumor spectrum, and diagnostic algorithms for CMMRD. In this article, we summarize this information and present a comprehensive consensus surveillance protocol for these individuals. Ongoing research will allow for further definition of replication repair-deficient cancer syndromes, assessing the cost-effectiveness of such surveillance protocols and potential therapeutic interventions for these children and families.
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 semiquantitative measurement for the strength of evidence of a gene-disease relationship that correlates to a qualitative classification: “Definitive,” “Strong,” “Moderate,” “Limited,” “No Reported Evidence,” or “Conflicting Evidence.” Within the ClinGen structure, classifications derived with 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.
Meningiomas account for one-third of all primary brain tumors. Although typically benign, about 20% of meningiomas are aggressive, and despite the rigor of the current histopathological ...classification system there remains considerable uncertainty in predicting tumor behavior. Here, we analyzed 160 tumors from all 3 World Health Organization (WHO) grades (I through III) using clinical, gene expression, and sequencing data. Unsupervised clustering analysis identified 3 molecular types (A, B, and C) that reliably predicted recurrence. These groups did not directly correlate with the WHO grading system, which classifies more than half of the tumors in the most aggressive molecular type as benign. Transcriptional and biochemical analyses revealed that aggressive meningiomas involve loss of the repressor function of the DREAM complex, which results in cell-cycle activation; only tumors in this category tend to recur after full resection. These findings should improve our ability to predict recurrence and develop targeted treatments for these clinically challenging tumors.
The Clinical Genome Resource (ClinGen) Sequence Variant Interpretation Working Group set out to refine the American College of Medical Genetics and Genomics and the Association of Molecular ...Pathologists (ACMG/AMP) variant pathogenicity recommendations for stand‐alone rule BA1 (a variant with minor allele frequency MAF > 0.05 is benign), by clarifying how it should be used and specifying a set of variants that should be exempted from this rule. We cross‐referenced ClinVar and Exome Aggregation Consortium data to identify variants for which there was a plausible argument for pathogenicity and the variant exists in one or more population data sets at MAF > 0.05. We identified nine such variants that were present in these data sets that may not be benign. The ACMG/AMP criteria were applied to these variants that resulted in four pathogenic and five variants of uncertain significance. We have refined benign rule BA1 by clarifying terms used to describe its use, which databases we recommend using, and assumptions made about this rule. We also recognized an initial list of nine variants for which there was some evidence of pathogenicity even though the MAF was high for these variants. We specify processes whereby individuals can petition ClinGen for amendments to our variant‐specific assertions and the criteria experts should use when setting a numerically lower threshold for BA1 for specific genes.
The ACMG/AMP variant pathogenicity recommendations include a stand‐alone rule BA1 (variant with MAF >0.05 is benign). We cross‐referenced ClinVar and ExAC for variants with MAF >0.05 and reasonable evidence for pathogenicity, identifying nine (four pathogenic and five VOUS) variants as a part of an initial exclusion list. We specify how individuals can amend this list. Additionally, we clarified terms, criteria and assumptions about rule BA1 and specify the criteria that experts should use when setting lower gene‐specific BA1 thresholds.
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