Search

SDHApathogenic germline variants (PGVs) are identified in up to 10% of patients with paraganglioma and phaeochromocytoma and up to 30% with wild-type gastrointestinal stromal tumours. MostSDHAPGV carriers present with an apparently sporadic tumour, but often the pathogenic variant has been inherited from parent who has the variant, but has not developed any clinical features. Studies ofSDHAPGV carriers suggest that lifetime penetrance for SDHA-associated tumours is low, particularly when identified outside the context of a family history. Current recommended surveillance forSDHAPGV carriers follows an intensive protocol. With increasing implementation of tumour and germline large panel and whole-genome sequencing, it is likely moreSDHAPGV carriers will be identified in patients with tumours not strongly associated withSDHA,or outside the context of a strong family history. This creates a complex situation about what to recommend in clinical practice considering low penetrance for tumour development, surveillance burden and patient anxiety. An expertSDHAworking group was formed to discuss and consider this situation. This paper outlines the recommendations from this working group for testing and management ofSDHAPGV carriers in clinical practice.

PURPOSE: Variant classifications may change over time, driven by emergence of fresh or contradictory evidence or evolution in weighing or combination of evidence items. For variant classifications above the actionability threshold, which is classification of likely pathogenic or pathogenic, clinical actions may be irreversible, such as risk-reducing surgery or prenatal interventions. Variant reclassification up or down across the actionability threshold can therefore have significant clinical consequences. Laboratory approaches to variant reinterpretation and reclassification vary widely.METHODS: Cancer Variant Interpretation Group UK is a multidisciplinary network of clinical scientists and genetic clinicians from across the 24 Molecular Diagnostic Laboratories and Clinical Genetics Services of the United Kingdom (NHS) and Republic of Ireland. We undertook surveys, polls, and national meetings of Cancer Variant Interpretation Group UK to evaluate opinions about clinical and laboratory management regarding variant reclassification.RESULTS: We generated a consensus framework on variant reclassification applicable to cancer susceptibility genes and other clinical areas, which provides explicit recommendations for clinical and laboratory management of variant reclassification scenarios on the basis of the nature of the new evidence, the magnitude of evidence shift, and the final classification score.CONCLUSION: In this framework, clinical and laboratory resources are targeted for maximal clinical effect and minimal patient harm, as appropriate to all resource-constrained health care settings.

Peer reviewed: True, OBJECTIVE: To describe national patterns of National Health Service (NHS) analysis of mismatch repair (MMR) genes in England using individual-level data submitted to the National Disease Registration Service (NDRS) by the NHS regional molecular genetics laboratories. DESIGN: Laboratories submitted individual-level patient data to NDRS against a prescribed data model, including (1) patient identifiers, (2) test episode data, (3) per-gene results and (4) detected sequence variants. Individualised per-laboratory algorithms were designed and applied in NDRS to extract and map the data to the common data model. Laboratory-level MMR activity audit data from the Clinical Molecular Genetics Society/Association of Clinical Genomic Science were used to assess early years' missing data. RESULTS: Individual-level data from patients undergoing NHS MMR germline genetic testing were submitted from all 13 English laboratories performing MMR analyses, comprising in total 16 722 patients (9649 full-gene, 7073 targeted), with the earliest submission from 2000. The NDRS dataset is estimated to comprise >60% of NHS MMR analyses performed since inception of NHS MMR analysis, with complete national data for full-gene analyses for 2016 onwards. Out of 9649 full-gene tests, 2724 had an abnormal result, approximately 70% of which were (likely) pathogenic. Data linkage to the National Cancer Registry demonstrated colorectal cancer was the most frequent cancer type in which full-gene analysis was performed. CONCLUSION: The NDRS MMR dataset is a unique national pan-laboratory amalgamation of individual-level clinical and genomic patient data with pseudonymised identifiers enabling linkage to other national datasets. This growing resource will enable longitudinal research and can form the basis of a live national genomic disease registry.

Advances in technology have led to a massive expansion in the capacity for genomic analysis, with a commensurate fall in costs. The clinical indications for genomic testing have evolved markedly; the volume of clinical sequencing has increased dramatically; and the range of clinical professionals involved in the process has broadened. There is general acceptance that our early dichotomous paradigms of variants being pathogenic–high risk and benign–no risk are overly simplistic. There is increasing recognition that the clinical interpretation of genomic data requires significant expertise in disease–gene-variant associations specific to each disease area. Inaccurate interpretation can lead to clinical mismanagement, inconsistent information within families and misdirection of resources. It is for this reason that ‘national subspecialist multidisciplinary meetings’ (MDMs) for genomic interpretation have been articulated as key for the new NHS Genomic Medicine Service, of which Cancer Variant Interpretation Group UK (CanVIG-UK) is an early exemplar. CanVIG-UK was established in 2017 and now has >100 UK members, including at least one clinical diagnostic scientist and one clinical cancer geneticist from each of the 25 regional molecular genetics laboratories of the UK and Ireland. Through CanVIG-UK, we have established national consensus around variant interpretation for cancer susceptibility genes via monthly national teleconferenced MDMs and collaborative data sharing using a secure online portal. We describe here the activities of CanVIG-UK, including exemplar outputs and feedback from the membership.

Purpose: Conditions and thresholds applied for evidence weighting of within-codon concordance (PM5) for pathogenicity vary widely between laboratories and expert groups. Because of the sparseness of available clinical classifications, there is little evidence for variation in practice. Methods: We used as a truthset 7541 dichotomous functional classifications of BRCA1 and MSH2, spanning 311 codons of BRCA1 and 918 codons of MSH2, generated from large-scale functional assays that have been shown to correlate excellently with clinical classifications. We assessed PM5 at 5 stringencies with incorporation of 8 in silico tools. For each analysis, we quantified a positive likelihood ratio (pLR, true positive rate/false positive rate), the predictive value of PM5-lookup in ClinVar compared with the functional truthset. Results: pLR was 16.3 (10.6-24.9) for variants for which there was exactly 1 additional colocated deleterious variant on ClinVar, and the variant under examination was equally or more damaging when analyzed using BLOSUM62. pLR was 71.5 (37.8-135.3) for variants for which there were 2 or more colocated deleterious ClinVar variants, and the variant under examination was equally or more damaging than at least 1 colocated variant when analyzed using BLOSUM62. Conclusion: These analyses support the graded use of PM5, with potential to use it at higher evidence weighting where more stringent criteria are met.

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 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.

Purpose To investigate the prevalence of biallelic PKD1 and PKD2 variants underlying very early onset (VEO) polycystic kidney disease (PKD) in a large international pediatric cohort referred for clinical indications over a 10-year period (2010–2020). Methods All samples were tested by Sanger sequencing and multiplex ligation-dependent probe amplification (MLPA) of PKD1 and PKD2 genes and/or a next-generation sequencing panel of 15 additional cystic genes including PKHD1 and HNF1B. Two patients underwent exome or genome sequencing. Results Likely causative PKD1 or PKD2 variants were detected in 30 infants with PKD-VEO, 16 of whom presented in utero. Twenty-one of 30 (70%) had two variants with biallelic in trans inheritance confirmed in 16/21, 1 infant had biallelic PKD2 variants, and 2 infants had digenic PKD1/PKD2 variants. There was no known family history of ADPKD in 13 families (43%) and a de novo pathogenic variant was confirmed in 6 families (23%). Conclusion We report a high prevalence of hypomorphic PKD1 variants and likely biallelic disease in infants presenting with PKD-VEO with major implications for reproductive counseling. The diagnostic interpretation and reporting of these variants however remains challenging using current American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) and Association of Clinical Genetic Science (ACGS) variant classification guidelines in PKD-VEO and other diseases affected by similar variants with incomplete penetrance.

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.

Non-allelic homologous recombination between chromosome-specific LCRs is the most common mechanism leading to recurrent microdeletions and duplications. To look for locus-specific differences, we have used microsatellites to determine the parental and chromosomal origins of a large series of patients with de novo deletions of chromosome 7q11.23 (Williams syndrome), 15q11-q13 (Angelman syndrome, Prader-Willi syndrome) and 22q11 (Di George syndrome) and duplications of 15q11-q13. Overall the majority of rearrangements were interchromosomal, so arising from unequal meiotic exchange, and there were approximately equal numbers of maternal and paternal deletions. Duplications and deletions of 15q11-q13 appear to be reciprocal products that arise by the same mechanisms. The proportion arising from interchromosomal exchanges varied among deletions with 22q11 the highest and 15q11-q13 the lowest. However, parental and chromosomal origins were not always independent. For 15q11-q13, maternal deletions tended to be interchromosomal while paternal deletions tended to be intrachromosomal; for 22q11 there was a possible excess of maternal cases among intrachromosomal deletions. Several factors are likely to be involved in the formation of recurrent rearrangements and the relative importance of these appear to be locus-specific.

Human trisomy is attributable to many different mechanisms and the relative importance of each mechanism is highly chromosome specific. The association between altered recombination and maternal non-disjunction is well documented: reductions in recombination have been reported for maternal meiosis I (MI) errors involving chromosomes 15, 16, 18 and 21 and increased recombination has been reported for meiosis II (MII) errors involving chromosome 21. We therefore investigated maternal X chromosome non-disjunction, to determine whether the effects of recombination are unique to the X chromosome or similar to any of the autosomes thus far studied. We genotyped 45 47,XXX females and 95 47,XXY males of maternal origin. Our results demonstrate that 49% arose during MI, 29% during MII and 16% were postzygotic events; a further 7% were meiotic but could not be assigned as either MI or MII because of recombination at the centromere. Among the MI cases, a majority (56%) had no detectable transitions and so absent recombination is an important factor for X chromosome non-disjunction. However, similar to trisomy 15 and unlike trisomy 21, we observed a significant increase in the mean maternal age of transitional MI errors compared with nullitransitional cases. In our studies of MII errors, recombination appeared normal and there was no obvious effect of maternal age, distinguishing our results from MII non-disjunction of chromosomes 18 or 21. Thus, surprisingly, the risk factors associated with both MI and MII non-disjunction appear to be different for virtually every chromosome that has been adequately studied.

We report the parental origin, and where possible the chromosomal origin of 115 de novo unbalanced structural chromosome abnormalities detectable by light microscopy. These consisted of 39 terminal deletions, 35 interstitial deletions, 8 rings, 12 duplications and 21 unbalanced translocations. In all categories the majority of abnormalities were of paternal origin, although the proportions varied from a high of 84% in the interstitial deletions and rings to a low of 58% in the duplications. Among the interstitial deletions and duplications, there were approximately equal numbers of intra- and interchromosomal abnormalities, while the majority of unbalanced translocations were isodisomic for the duplicated chromosome. The examination of the parental ages in the four main classes of abnormality showed terminal deletions of maternal origin to be associated with a significantly reduced maternal age. Thus, there is a clear propensity for structural chromosome abnormalities to occur in male germ cells, although the chromosomal origin seems similar irrespective of the parental origin.