The month of VarSeq must be October. This month we saw incredible research and clinical application being utilized with the VarSeq suite. Whole exome sequencing and variant filtering and annotation, CNV calling for oncology research, and pathogenicity classification using the ACMG guidelines. VarSeq was able to be a front-runner this month, showing the full range of capabilities.
Germline RB1 Mutation in Retinoblastoma Patients: Detection Methods and Implication in Tumor Focality
The study aimed to generate a stepwise method to reduce the workload of full-scale RB1 sequencing for germline mutation screening in retinoblastoma (RB) patients. The implication of germline mutation in tumor focality was also determined in this study. A stepwise method was created on the basis of “hotspot” exons analyzed using data on germline RB1 mutation in the RB1–Leiden Open Variation Database and then tested for mutation screening in the blood DNA of 42 patients with RB. The method was compared with the clinical next-generation sequencing (NGS) panel in terms of sequencing outcomes. The germline RB1 mutation was examined in association with multifocality in RB. Germline RB1 mutation was identified in 61% of all bilateral cases in the first step of the 3 stepwise method and in 78% and 89% for the two and three steps combined, respectively. NGS detected a mosaic variant of RB1 that was not detected by the first two steps and increased the sensitivity from 78% to 83%. Analysis of the relationship between mutation status and tumor focality indicated that multifocality in RB was dependent on germline RB1 mutation, confirming a higher tendency to have a germline RB1 mutation in patients with multifocal RB.
Rojanaporn D, Chitphuk S, Iemwimangsa N, Chareonsirisuthigul T, Saengwimol D, Aroonroch R, Anurathathapan U, Hongeng S, Kaewkhaw R. Germline RB1 Mutation in Retinoblastoma Patients: Detection Methods and Implication in Tumor Focality. Transl Vis Sci Technol. 2022 Sep 1;11(9):30. doi: 10.1167/tvst.11.9.30. PMID: 36173648; PMCID: PMC9527333.
OA30 GENETIC ANALYSIS OF WHOLE EXOME SEQUENCING IN A COHORT OF CHILDREN WITH REFRACTORY JIA REVEALS GENETIC RISK FACTORS FOR RARE JUVENILE DISEASES
Juvenile idiopathic arthritis (JIA) encompasses a group of heterogeneous rheumatic diseases of childhood onset. JIA can result in long term disability and remission is the main goal of treatment. However refractory disease can occur, which is defined as the absence of response to a standard disease therapy. A genetic basis for refractory disease has yet to explored, where deleterious rare variants complicate diagnosis or treatment outcome. This study aimed to investigate, through genetic analysis, whether children with JIA that is refractory carry rare genetic risk factors in genes linked to monogenic diseases. Whole exome sequencing of 99 children with JIA was performed with the Agilent SureSelect Human All ExonV6 kit. All quality control, variant filtering and annotation was performed in Varseq (version 2.2.1). Variants with a read depth <30 and genotype quality <80 were removed. Rarity and pathogenicity filters were then applied to remove variants with an allele frequency >1% (based on ExAC, gnomAD, gnomAD exome, NHLBI and 1KGp phase 3), classified as benign or likely benign on ClinVar, with a CADD PHRED score <15 and a REVEL score >0.7. Variants were annotated if they appeared in a gene from the primary immunodeficiency PanelApp (Martin et al., 2019), in a gene associated with an arthritis phenotype or in a gene that appeared on a paediatric monogenic gene list. The variants were then classified using ACMG guidelines (Richards et al., 2015) and benign, or likely benign, classified variants were removed. A total of 470 variants were identified and we found that 20 out of the 99 children screened were heterozygous for at least one recognised variant in a gene linked to a monogenic disease. Five of these children carried more than one recognised variant linked to monogenic genes. Here we provide a number of illustrative examples: three genes, ADAR, ATP7B and MVK, were prioritised based on prior evidence of associated disease. The variant p.Pro193Ala (gnomAD allele frequency (GAD) 2.2×10-3) of ADAR has previously been deemed pathogenic in a homozygous or compound heterozygous state for Aicardi-Goutières syndrome. Adenosine deaminases (ADARs) catalyse the hydrolytic deamination of adenosine to inosine in dsRNA and is suggested to act as a suppressor of type 1 interferon-stimulated genes. Within ATP7B, two distinct variants were detected; p.Gln1142His (GAD 1.6×10-5) and p.Ile1148Thr (GAD 4.0×10-5) have previously been reported as pathogenic, in combination with a third variant, for Wilson’s disease and were carried by one individual in this cohort. ATP7B encodes copper-transporting ATPase 2, which supplies copper to ceruloplasmin. Variant p.Val377Ile (GAD 1.6×10-3) of MVK was detected in eight individuals in this cohort, interestingly five of these individuals also carried at least one HLA-DRB1 stop-gained variant. This MVK mutation has been confirmed as pathogenic in a homozygous or compound heterozygous state for mevalonate kinase deficiency. MVK converts mevalonic acid into mevalonate-5-phosphate in the cholesterol synthesis pathway. Additionally, two stop-gained loss of function HLA-DRB1 variants, p.Tyr107Ter and p.Gln125Ter, were detected in five and 20 individuals, respectively, in this cohort. HLA-DRB1 is a recognised susceptibility locus for JIA.
Melissa Tordoff, Samantha Smith, Gillian Rice, Lucy Wedderburn, Kimme Hyrich, Andrew Morris, Tracy Briggs, Wendy Thomson, Stephen Eyre, John Bowes, OA30 Genetic analysis of whole exome sequencing in a cohort of children with refractory JIA reveals genetic risk factors for rare juvenile diseases, Rheumatology Advances in Practice, Volume 6, Issue Supplement_1, October 2022, rkac066.030, https://doi.org/10.1093/rap/rkac066.030
Estimating the likelihood of carrying pathogenic variants in the breast and ovarian cancer susceptibility genes: a validation of the BOADICEA model
The Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), now a part of CanRisk, is a comprehensive risk prediction tool for breast and/or ovarian cancer (BOC) with a high accuracy to predict the likelihood of carrying pathogenic variants (PVs) in BRCA1 and BRCA2. BOADICEA version 6 also includes PVs in PALB2, CHEK2, ATM, BARD1, RAD51C and RAD51D, but the accuracy of its predictions remains to be investigated. The study included 2,033 individuals counselled at clinical genetics departments in Denmark on suspicion of hereditary susceptibility to BOC. All counselees underwent comprehensive genetic testing by next generation sequencing of BRCA1, BRCA2, PALB2, CHEK2, ATM, BARD1, RAD51C and RAD51D. Predicted likelihoods of PVs were obtained from BOADICEA v6.1.0. The accuracy of predictions was examined by calibration using the observed-to-expected ratio (O/E) and by discrimination using the area under the receiver-operating characteristics curve (AUC). BOADICEA remained well-calibrated after addition of the additional genes. Thus, the O/E was 1.07 (95% CI 0.94-1.22) for all genes in the model combined. At sub-categories of predicted likelihood, the model performed well with only limited misestimation at the extremes of predicted likelihood. The ability to discriminate between carriers and non-carriers of PVs was acceptable with an AUC of 0.70 (95% CI 0.66-0.74), although discrimination was better for BRCA1 and BRCA2 (AUC 0.79) than for the other genes (AUC 0.59).
Nanna Bæk Møller, Desirée Sofie Boonen, Elisabeth Simone Feldner et al. Estimating the likelihood of carrying pathogenic variants in the breast and ovarian cancer susceptibility genes: a validation of the BOADICEA model, 18 October 2022, PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-2158118/v1]