BackgroundOver recent years genetic testing for germline mutations in BRCA1/BRCA2 has become more readily available because of technological advances and reducing costs.ObjectiveTo explore the feasibility and acceptability of offering genetic testing to all women recently diagnosed with epithelial ovarian cancer (EOC).MethodsBetween 1 July 2013 and 30 June 2015 women newly diagnosed with EOC were recruited through six sites in East Anglia, UK into the Genetic Testing in Epithelial Ovarian Cancer (GTEOC) study. Eligibility was irrespective of patient age and family history of cancer. The psychosocial arm of the study used self-report, psychometrically validated questionnaires (Depression Anxiety and Stress Scale (DASS-21); Impact of Event Scale (IES)) and cost analysis was performed.Results232 women were recruited and 18 mutations were detected (12 in BRCA1, 6 in BRCA2), giving a mutation yield of 8%, which increased to 12% in unselected women aged <70 years (17/146) but was only 1% in unselected women aged ≥70 years (1/86). IES and DASS-21 scores in response to genetic testing were significantly lower than equivalent scores in response to cancer diagnosis (p<0.001). Correlation tests indicated that although older age is a protective factor against any traumatic impacts of genetic testing, no significant correlation exists between age and distress outcomes.ConclusionsThe mutation yield in unselected women diagnosed with EOC from a heterogeneous population with no founder mutations was 8% in all ages and 12% in women under 70. Unselected genetic testing in women with EOC was acceptable to patients and is potentially less resource-intensive than current standard practice.
AIM Mutations in the SLC16A2 gene have been implicated in Allan–Herndon–Dudley syndrome (AHDS), an X-linked learning disability* syndrome associated with thyroid function test (TFT) abnormalities. Delayed myelination is a non-specific finding in individuals with learning disability whose genetic basis is often uncertain. The aim of this study was to describe neuroimaging findings and neurological features in males with SLC16A2 gene mutations. METHOD We reviewed brain magnetic resonance imaging (MRI) findings and neurological features in a cohort of five males aged between 1 year 6 months and 6 years (median 4y) from four families harbouring SLC16A2 gene mutations. RESULTS The participants presented aged between 4 and 9 months with initial hypotonia and subsequent spastic paraparesis with dystonic posturing and superimposed paroxysmal dyskinesias. Dystonic cerebral palsy was the most common initial clinical diagnosis, and AHDS was suspected only retrospectively, considering the characteristically abnormal thyroid function tests, with high serum tri-iodothyronine (T3), as the most consistent finding. Brain MRI showed absent or markedly delayed myelination in all five participants, prompting the suspicion of Pelizaeus–Merzbacher disease in one patient. INTERPRETATION Our findings indicate a consistent association between defective neuronal T3 uptake and delayed myelination. SLC16A2 involvement should be considered in males with learning disability, an associated motor or movement disorder, and evidence of delayed myelination on brain MRI. Although dysmorphic features suggestive of AHDS are not always present, T3 measurement is a reliable screening test.
Purpose Where multiple in silico tools are concordant, the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) framework affords supporting evidence toward pathogenicity or benignity, equivalent to a likelihood ratio of ~2. However, limited availability of “clinical truth sets” and prior use in tool training limits their utility for evaluation of tool performance. Methods We created a truth set of 9,436 missense variants classified as deleterious or tolerated in clinically validated high-throughput functional assays for BRCA1, BRCA2, MSH2, PTEN, and TP53 to evaluate predictive performance for 44 recommended/commonly used in silico tools. Results Over two-thirds of the tool–threshold combinations examined had specificity of <50%, thus substantially overcalling deleteriousness. REVEL scores of 0.8–1.0 had a Positive Likelihood Ratio (PLR) of 6.74 (5.24–8.82) compared to scores <0.7 and scores of 0–0.4 had a Negative Likelihood Ratio (NLR) of 34.3 (31.5–37.3) compared to scores of >0.7. For Meta-SNP, the equivalent PLR = 42.9 (14.4–406) and NLR = 19.4 (15.6–24.9). Conclusion Against these clinically validated “functional truth sets," there was wide variation in the predictive performance of commonly used in silico tools. Overall, REVEL and Meta-SNP had best balanced accuracy and might potentially be used at stronger evidence weighting than current ACMG/AMP prescription, in particular for predictions of benignity.
To determine the effects of prescribed training programs on 5 physical fitness test items, each of 50 high school boys participated for 10 wk. in one of three programs (wrestling, softball, and plyometrics; weight training; and weight training and plyometrics). (a) On the sit-ups, 40-yd. dash, vertical jump, and pull-ups, each group improved significantly from pre- to posttest. (b) On the shuttle run, none of the groups improved significantly from pre- to posttest. (c) On the vertical jump, groups had a significant effect, but the interaction was nonsignificant. No effects were significant.
Accurate classification of variants in cancer susceptibility genes (CSGs) is key for correct estimation of cancer risk and management of patients. Consistency in the weighting assigned to individual elements of evidence has been much improved by the American College of Medical Genetics (ACMG) 2015 framework for variant classification, UK Association for Clinical Genomic Science (UK-ACGS) Best Practice Guidelines and subsequent Cancer Variant Interpretation Group UK (CanVIG-UK) consensus specification for CSGs. However, considerable inconsistency persists regarding practice in the combination of evidence elements. CanVIG-UK is a national subspecialist multidisciplinary network for cancer susceptibility genomic variant interpretation, comprising clinical scientist and clinical geneticist representation from each of the 25 diagnostic laboratories/clinical genetic units across the UK and Republic of Ireland. Here, we summarise the aggregated evidence elements and combinations possible within different variant classification schemata currently employed for CSGs (ACMG, UK-ACGS, CanVIG-UK and ClinGen gene-specific guidance for PTEN, TP53 and CDH1). We present consensus recommendations from CanVIG-UK regarding (1) consistent scoring for combinations of evidence elements using a validated numerical ‘exponent score’ (2) new combinations of evidence elements constituting likely pathogenic’ and ‘pathogenic’ classification categories, (3) which evidence elements can and cannot be used in combination for specific variant types and (4) classification of variants for which there are evidence elements for both pathogenicity and benignity.
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