ClinGen expert clinical validity curation of 164 hearing loss gene–disease pairs

DiStefano, Marina T.; Hemphill, Sarah E.; Oza, Andrea M.; Siegert, Rebecca K.; Grant, Andrew R.; Hughes, Madeline Y.; Cushman, Brandon J.; Azaiez, Héla; Booth, Kevin T.; Chapin, Alex; Duzkale, Hatice; Matsunaga, Tatsuo; Shen, Jun; Zhang, Wenying; Kenna, Margaret A.; Schimmenti, Lisa A.; Tekin, Mustafa; Rehm, Heidi L.; Tayoun, Ahmad N. Abou; Amr, Sami S.

doi:10.1038/s41436-019-0487-0

Cited by 79 publications

(66 citation statements)

References 29 publications

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“…The number of detected, probably pathogenic variants increases with the use of advanced sequencing techniques, which may lead to overinterpretation of genotyping results. Particular caution and use of specific guidelines is required by data analysis and selection of causative variants in order to provide accurate diagnosis and counseling for the patients and reliable data for the medical genetic community [5, 14].…”

Section: Resultsmentioning

confidence: 99%

Overinterpretation of high throughput sequencing data in medical genetics: first evidence against TMPRSS3/GJB2 digenic inheritance of hearing loss

et al. 2019

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Background Hearing loss (HL) is the most common disability of human senses characterized by a great allelic heterogeneity. GJB2 and TMPRSS3 are two well-known HL genes typically underlying its monogenic form. Recently, TMPRSS3/GJB2 digenic inheritance has been proposed. As results of genetic testing can be easily overinterpreted, we aimed to verify the hypothesis. Methods From genetic database of HL patients with at least one TMPRSS3 pathogenic variants we have selected individuals with additional GJB2 pathogenic variants. All of the available family members were recruited for the study. Segregation analysis of the respective TMPRSS3 and GJB2 pathogenic variants was performed within the families. Results The strategy has allowed to identify four individuals who were double heterozygous for known pathogenic TMPRSS3 and GJB2 variants. Two individuals from different families had GJB2 c.35delG and TMPRSS3 c.208delC and in two other individuals from one family GJB2 c.35delG together with TMPRSS3 c.1343T>C variants were found. None of these subjects has ever reported hearing problems and their hearing status was normal. Conclusions Our data provide evidence against TMPRSS3 / GJB2 digenic inheritance of HL. As high throughput sequencing is increasingly used for genetic testing, particular caution should be taken to provide the patients with accurate genetic counseling.

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Section: Resultsmentioning

confidence: 99%

Overinterpretation of high throughput sequencing data in medical genetics: first evidence against TMPRSS3/GJB2 digenic inheritance of hearing loss

et al. 2019

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“…This is mainly because mutations in the same gene cause a broad range of diseases and the gene‐disease associations are heterogeneous, which finally determines whether preliminary PVS1 strength levels should be altered, if at all (Abou Tayoun et al, 2018). For example, the GJB3 gene (MIM: 603324) has a “Strong” association with erythrokeratodermia variabilis, whereas it has a “Disputed” association with nonsyndromic genetic deafness (DiStefano et al, 2019). Therefore, no PVS1 rating should be assigned when interpreting a null variant in GJB3 gene identified from a hearing loss patient because the GJB3 gene is less likely to cause the phenotype (hearing loss).…”

Section: Discussionmentioning

confidence: 99%

AutoPVS1: An automatic classification tool for PVS1 interpretation of null variants

et al. 2020

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Null variants are prevalent within the human genome, and their accurate interpretation is critical for clinical management. In 2018, the ClinGen Sequence Variant Interpretation (SVI) Working Group refined the only criterion with a very strong pathogenicity rating (PVS1). To streamline PVS1 interpretation, we have developed an automatic classification tool with a graphical user interface called AutoPVS1. The performance of AutoPVS1 was assessed using 56 variants manually curated by the ClinGen's SVI Working Group; it achieved an interpretation concordance of 93% (52/56). A further analysis of 28,586 putative loss‐of‐function variants by AutoPVS1 demonstrated that at least 27.7% of them do not reach a very strong strength level, 17.5% because of variant‐specific issues and 10.2% due to disease mechanism considerations. Notably, 41.0% (1,936/4,717) of splicing variants were assigned a decreased preliminary PVS1 strength level, a significantly greater fraction than in frameshift variants (13.2%) and nonsense variants (10.8%). Our results reinforce the necessity of considering variant‐specific issues and disease mechanisms in variant interpretation and demonstrate that AutoPVS1 meets an urgent need by enabling biocurators to easily assign accurate, reliable and reproducible PVS1 strength levels in the process of variant interpretation. AutoPVS1 is publicly available at http://autopvs1.genetics.bgi.com/.

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“…12 For example, GJB3 gene (MIM: 603324) had a “Strong” association with erythrokeratodermia variabilis, whereas it has a “Disputed” association with nonsyndromic genetic deafness. 36 Therefore, PVS1 should not be applied at any strength level when interpreting a null variant in GJB3 gene with hearing loss, but it is applicable for erythrokeratodermia variabilis.…”

Section: Discussionmentioning

confidence: 99%

AutoPVS1: An automatic classification tool for PVS1 interpretation of null variants

Xiang

Peng

2019

Preprint

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Null variants are prevalent within human genome, and their accurate interpretation is critical for clinical management. In 2018, the ClinGen Sequence Variant Interpretation (SVI) Working Group refined the only criterion (PVS1) for pathogenicity in the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) guidelines. The refinement may improve interpretation consistency, but it also brings hurdles to biocurators because of the complicated workflows and multiple bioinformatics sources required. To address these issues, we developed an automatic classification tool called AutoPVS1 to streamline PVS1 interpretation. We assessed the performance of AutoPVS1 using 56 variants manually curated by ClinGen's SVI Working Group and achieved an interpretation concordance of 95% (53/56). A further analysis of 28,586 putative loss-of-function variants by AutoPVS1 demonstrated that at least 27.6% of them do not reach a very strong strength level, with 17.4% based on variant-specific issues and 10.2% on disease mechanism considerations. Moreover, 40.7% (1,918/4,717) of splicing variants were assigned a decreased PVS1 strength level, significantly higher than frameshift and nonsense variants. Our results reinforce the necessity of considering variant-specific issues and disease mechanisms in variant interpretation, and demonstrate that AutoPVS1 is an accurate, reproducible, and reliable tool which facilitates PVS1 interpretation and will thus be of great importance to curators.

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ClinGen expert clinical validity curation of 164 hearing loss gene–disease pairs

Cited by 79 publications

References 29 publications

Overinterpretation of high throughput sequencing data in medical genetics: first evidence against TMPRSS3/GJB2 digenic inheritance of hearing loss

Overinterpretation of high throughput sequencing data in medical genetics: first evidence against TMPRSS3/GJB2 digenic inheritance of hearing loss

AutoPVS1: An automatic classification tool for PVS1 interpretation of null variants

AutoPVS1: An automatic classification tool for PVS1 interpretation of null variants

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