Evidence-based recommendations for gene-specific ACMG/AMP variant classification from the ClinGen ENIGMA BRCA1 and BRCA2 Variant Curation Expert Panel.

The ENIGMA research consortium develops and applies methods to determine clinical significance of variants in hereditary breast and ovarian cancer genes. An ENIGMA BRCA1/2 classification sub-group, formed in 2015 as a ClinGen external expert panel, evolved into a ClinGen internal Variant Curation Expert Panel (VCEP) to align with Food and Drug Administration recognized processes for ClinVar contributions. The VCEP reviewed American College of Medical Genetics and Genomics/Association of Molecular Pathology (ACMG/AMP) classification criteria for relevance to interpreting BRCA1 and BRCA2 variants. Statistical methods were used to calibrate evidence strength for different data types. Pilot specifications were tested on 40 variants and documentation revised for clarity and ease of use. The original criterion descriptions for 13 evidence codes were considered non-applicable or overlapping with other criteria. Scenario of use was extended or re-purposed for eight codes. Extensive analysis and/or data review informed specification descriptions and weights for all codes. Specifications were applied to pilot variants with pre-existing ClinVar classification as follows: 13 uncertain significance or conflicting, 14 pathogenic and/or likely pathogenic, and 13 benign and/or likely benign. Review resolved classification for 11/13 uncertain significance or conflicting variants and retained or improved confidence in classification for the remaining variants. Alignment of pre-existing ENIGMA research classification processes with ACMG/AMP classification guidelines highlighted several gaps in the research processes and the baseline ACMG/AMP criteria. Calibration of evidence strength was key to justify utility and strength of different data types for gene-specific application. The gene-specific criteria demonstrated value for improving ACMG/AMP-aligned classification of BRCA1 and BRCA2 variants.

Predicting the impact of rare variants on RNA splicing in CAGI6.

Variants which disrupt splicing are a frequent cause of rare disease that have been under-ascertained clinically. Accurate and efficient methods to predict a variant's impact on splicing are needed to interpret the growing number of variants of unknown significance (VUS) identified by exome and genome sequencing. Here, we present the results of the CAGI6 Splicing VUS challenge, which invited predictions of the splicing impact of 56 variants ascertained clinically and functionally validated to determine splicing impact. The performance of 12 prediction methods, along with SpliceAI and CADD, was compared on the 56 functionally validated variants. The maximum accuracy achieved was 82% from two different approaches, one weighting SpliceAI scores by minor allele frequency, and one applying the recently published Splicing Prediction Pipeline (SPiP). SPiP performed optimally in terms of sensitivity, while an ensemble method combining multiple prediction tools and information from databases exceeded all others for specificity. Several challenge methods equalled or exceeded the performance of SpliceAI, with ultimate choice of prediction method likely to depend on experimental or clinical aims. One quarter of the variants were incorrectly predicted by at least 50% of the methods, highlighting the need for further improvements to splicing prediction methods for successful clinical application.

SMAD4 mosaicism in juvenile polyposis: Essential contribution of somatic analysis in diagnosis.

Juvenile polyposis syndrome (JPS) is a rare disease characterized by multiple hamartomatous polyps in the gastrointestinal tract, associated with pathogenic variants of BMPR1A and SMAD4. We present the description of SMAD4 mosaicism in a 30-year-old man who had caecum adenocarcinoma, 11 juvenile colon polyps and epistaxis since childhood. We conducted NGS polyposis and CRC panel analysis on DNA extracted from two polyps, revealing a likely pathogenic SMAD4 variant: NM_005359.5:c. 1600C>T, p.(Gln534*). This variant was then identified at a very low frequency on blood and normal colonic tissue, by targeted visualization of previously obtained NGS data. These findings support the presence of a likely pathogenic mosaic SMAD4 variant that aligns with the patient's phenotype. Given the relatively frequent occurrence of de novo SMAD4 mutations, somatic mosaicism could account for a significant proportion of sporadic JPS patients with unidentified pathogenic variants. This case underscores the diagnosis challenge of detecting mosaicism and emphasizes the importance of somatic analyses.

Germline HPF1 retrogene insertion in RB1 gene involved in cancer predisposition.

About half of the human genome is composed of repeated sequences derived from mobile elements, mainly retrotransposons, generally without pathogenic effect. Familial forms of retinoblastoma are caused by germline pathogenic variants in RB1 gene. Here, we describe a family with retinoblastoma affecting a father and his son. No pathogenic variant was identified after DNA analysis of RB1 gene coding sequence and exon-intron junctions. However, RB1 mRNA analysis showed a chimeric transcript with insertion of 114 nucleotides from HPF1 gene inside RB1 gene. This chimeric transcript led to an insertion of 38 amino acids in functional domain of retinoblastoma protein. Subsequent DNA analysis in RB1 intron 17 revealed the presence of a full-length HPF1 retrogene insertion in opposite orientation. Functional assay shows that this insertion has a deleterious impact on retinoblastoma protein function. This is the first report of a full-length retrogene insertion involved in human Mendelian disease leading to a chimeric transcript and a non-functional chimeric protein. Some retrogene insertions may be missed by standard diagnostic genetic testing, so contribution of retrogene insertions to human disease may be underestimated. The increasing use of whole genome sequencing in diagnostic settings will help to get a more comprehensive view of retrogenes.

SPiP: Splicing Prediction Pipeline, a machine learning tool for massive detection of exonic and intronic variant effects on mRNA splicing.

Modeling splicing is essential for tackling the challenge of variant interpretation as each nucleotide variation can be pathogenic by affecting pre-mRNA splicing via disruption/creation of splicing motifs such as 5'/3' splice sites, branch sites, or splicing regulatory elements. Unfortunately, most in silico tools focus on a specific type of splicing motif, which is why we developed the Splicing Prediction Pipeline (SPiP) to perform, in one single bioinformatic analysis based on a machine learning approach, a comprehensive assessment of the variant effect on different splicing motifs. We gathered a curated set of 4616 variants scattered all along the sequence of 227 genes, with their corresponding splicing studies. The Bayesian analysis provided us with the number of control variants, that is, variants without impact on splicing, to mimic the deluge of variants from high-throughput sequencing data. Results show that SPiP can deal with the diversity of splicing alterations, with 83.13% sensitivity and 99% specificity to detect spliceogenic variants. Overall performance as measured by area under the receiving operator curve was 0.986, better than SpliceAI and SQUIRLS (0.965 and 0.766) for the same data set. SPiP lends itself to a unique suite for comprehensive prediction of spliceogenicity in the genomic medicine era. SPiP is available at: https://sourceforge.net/projects/splicing-prediction-pipeline/.

Assessment of Multiplex Digital Droplet RT-PCR as a Diagnostic Tool for SARS-CoV-2 Detection in Nasopharyngeal Swabs and Saliva Samples.

BACKGROUND: Reverse transcription-quantitative PCR on nasopharyngeal swabs is currently the reference COVID-19 diagnosis method but exhibits imperfect sensitivity. METHODS: We developed a multiplex reverse transcription-digital droplet PCR (RT-ddPCR) assay, targeting 6 SARS-CoV-2 genomic regions, and evaluated it on nasopharyngeal swabs and saliva samples collected from 130 COVID-19 positive or negative ambulatory individuals, who presented symptoms suggestive of mild or moderate SARS-CoV2 infection. RESULTS: For the nasopharyngeal swab samples, the results obtained using the 6-plex RT-ddPCR and RT-qPCR assays were all concordant. The 6-plex RT-ddPCR assay was more sensitive than RT-qPCR (85% versus 62%) on saliva samples from patients with positive nasopharyngeal swabs. CONCLUSION: Multiplex RT-ddPCR represents an alternative and complementary tool for the diagnosis of COVID-19, in particular to control RT-qPCR ambiguous results. It can also be applied to saliva for repetitive sampling and testing individuals for whom nasopharyngeal swabbing is not possible.

Further delineation of the NTHL1 associated syndrome: A report from the French Oncogenetic Consortium.

Biallelic pathogenic variants in the NTHL1 (Nth like DNA glycosylase 1) gene cause a recently identified autosomal recessive hereditary cancer syndrome predisposing to adenomatous polyposis and colorectal cancer. Half of biallelic carriers also display multiple colonic or extra-colonic primary tumors, mainly breast, endometrium, urothelium, and brain tumors. Published data designate NTHL1 as an important contributor to hereditary cancers but also underline the scarcity of available informations. Thanks to the French oncogenetic consortium (Groupe Génétique et Cancer), we collected NTHL1 variants from 7765 patients attending for hereditary colorectal cancer or polyposis (n = 3936) or other hereditary cancers (n = 3829). Here, we describe 10 patients with pathogenic biallelic NTHL1 germline variants, that is, the second largest NTHL1 series. All carriers were from the "colorectal cancer or polyposis" series. All nine biallelic carriers who underwent colonoscopy presented adenomatous polyps. For digestive cancers, average age at diagnosis was 56.2 and we reported colorectal, duodenal, caecal, and pancreatic cancers. Extra-digestive malignancies included sarcoma, basal cell carcinoma, breast cancer, urothelial carcinoma, and melanoma. Although tumor risks remain to be precisely defined, these novel data support NTHL1 inclusion in diagnostic panel testing. Colonic surveillance should be conducted based on MUTYH recommendations while extra-colonic surveillance has to be defined.

Assessment of branch point prediction tools to predict physiological branch points and their alteration by variants.

BACKGROUND: Branch points (BPs) map within short motifs upstream of acceptor splice sites (3'ss) and are essential for splicing of pre-mature mRNA. Several BP-dedicated bioinformatics tools, including HSF, SVM-BPfinder, BPP, Branchpointer, LaBranchoR and RNABPS were developed during the last decade. Here, we evaluated their capability to detect the position of BPs, and also to predict the impact on splicing of variants occurring upstream of 3'ss. RESULTS: We used a large set of constitutive and alternative human 3'ss collected from Ensembl (n = 264,787 3'ss) and from in-house RNAseq experiments (n = 51,986 3'ss). We also gathered an unprecedented collection of functional splicing data for 120 variants (62 unpublished) occurring in BP areas of disease-causing genes. Branchpointer showed the best performance to detect the relevant BPs upstream of constitutive and alternative 3'ss (99.48 and 65.84% accuracies, respectively). For variants occurring in a BP area, BPP emerged as having the best performance to predict effects on mRNA splicing, with an accuracy of 89.17%. CONCLUSIONS: Our investigations revealed that Branchpointer was optimal to detect BPs upstream of 3'ss, and that BPP was most relevant to predict splicing alteration due to variants in the BP area.

Novel diagnostic tool for prediction of variant spliceogenicity derived from a set of 395 combined in silico/in vitro studies: an international collaborative effort.

Variant interpretation is the key issue in molecular diagnosis. Spliceogenic variants exemplify this issue as each nucleotide variant can be deleterious via disruption or creation of splice site consensus sequences. Consequently, reliable in silico prediction of variant spliceogenicity would be a major improvement. Thanks to an international effort, a set of 395 variants studied at the mRNA level and occurring in 5' and 3' consensus regions (defined as the 11 and 14 bases surrounding the exon/intron junction, respectively) was collected for 11 different genes, including BRCA1, BRCA2, CFTR and RHD, and used to train and validate a new prediction protocol named Splicing Prediction in Consensus Elements (SPiCE). SPiCE combines in silico predictions from SpliceSiteFinder-like and MaxEntScan and uses logistic regression to define optimal decision thresholds. It revealed an unprecedented sensitivity and specificity of 99.5 and 95.2%, respectively, and the impact on splicing was correctly predicted for 98.8% of variants. We therefore propose SPiCE as the new tool for predicting variant spliceogenicity. It could be easily implemented in any diagnostic laboratory as a routine decision making tool to help geneticists to face the deluge of variants in the next-generation sequencing era. SPiCE is accessible at (https://sourceforge.net/projects/spicev2-1/).

First estimate of the scale of canonical 5' splice site GT>GC variants capable of generating wild-type transcripts.

It has long been known that canonical 5' splice site (5'SS) GT>GC variants may be compatible with normal splicing. However, to date, the actual scale of canonical 5'SSs capable of generating wild-type transcripts in the case of GT>GC substitutions remains unknown. Herein, combining data derived from a meta-analysis of 45 human disease-causing 5'SS GT>GC variants and a cell culture-based full-length gene splicing assay of 103 5'SS GT>GC substitutions, we estimate that ~15-18% of canonical GT 5'SSs retain their capacity to generate between 1% and 84% normal transcripts when GT is substituted by GC. We further demonstrate that the canonical 5'SSs in which substitution of GT by GC-generated normal transcripts exhibit stronger complementarity to the 5' end of U1 snRNA than those sites whose substitutions of GT by GC did not lead to the generation of normal transcripts. We also observed a correlation between the generation of wild-type transcripts and a milder than expected clinical phenotype but found that none of the available splicing prediction tools were capable of reliably distinguishing 5'SS GT>GC variants that generated wild-type transcripts from those that did not. Our findings imply that 5'SS GT>GC variants in human disease genes may not invariably be pathogenic.