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The capability of genetic technologies is expanding rapidly in the field of inherited eye disease. New genetic testing approaches will deliver a step change in the ability to diagnose and extend the possibility of targeted treatments. However, evidence is lacking about the benefits of genetic testing to support service planning. Here, we report qualitative data about retinal dystrophy families' experiences of genetic testing in United Kingdom. The data were part of a wider study examining genetic eye service provision. Twenty interviewees from families in which a causative mutation had been identified by a genetic eye clinic were recruited to the study. Fourteen interviewees had chosen to have a genetic test and five had not; one was uncertain. In-depth telephone interviews were conducted allowing a thorough exploration of interviewees' views and experiences of the benefits of genetic counselling and testing. Transcripts were analysed using thematic analysis. Both affected and unaffected interviewees expressed mainly positive views about genetic testing, highlighting benefits such as diagnostic confirmation, risk information, and better preparation for the future. Negative consequences included the burden of knowledge, moral dilemmas around reproduction, and potential impact on insurance. The offer of genetic testing was often taken up, but was felt unnecessary in some cases. Interviewees in the study reported many benefits, suggesting genetic testing should be available to this patient group. The benefits and risks identified will inform future evaluation of models of service delivery. This research was part of a wider study exploring experiences of families with retinal dystrophy.

Albinism is a clinically and genetically heterogeneous group of conditions characterised by visual abnormalities and variable degrees of hypopigmentation. Multiple studies have demonstrated the clinical utility of genetic investigations in individuals with suspected albinism. Despite this, the variation in the provision of genetic testing for albinism remains significant. One key issue is the lack of a standardised approach to the analysis of genomic data from affected individuals. For example, there is variation in how different clinical genetic laboratories approach genotypes that involve incompletely penetrant alleles, including the common, ’hypomorphic’ TYR c.1205G>A (p.Arg402Gln) [rs1126809] variant. Here, we discuss the value of genetic testing as a frontline diagnostic tool in individuals with features of albinism and propose a practice pattern for the analysis of genomic data from affected families. [ABSTRACT FROM AUTHOR]

Background Genomic variant prioritisation is one of the most significant bottlenecks to mainstream genomic testing in healthcare. Tools to improve precision while ensuring high recall are critical to successful mainstream clinical genomic testing, in particular for whole genome sequencing where millions of variants must be considered for each patient. Methods We developed EyeG2P, a publicly available database and web application using the Ensembl Variant Effect Predictor. EyeG2P is tailored for efficient variant prioritisation for individuals with inherited ophthalmic conditions. We assessed the sensitivity of EyeG2P in 1234 individuals with a broad range of eye conditions who had previously received a confirmed molecular diagnosis through routine genomic diagnostic approaches. For a prospective cohort of 83 individuals, we assessed the precision of EyeG2P in comparison with routine diagnostic approaches. For 10 additional individuals, we assessed the utility of EyeG2P for whole genome analysis. Results EyeG2P had 99.5% sensitivity for genomic variants previously identified as clinically relevant through routine diagnostic analysis (n=1234 individuals). Prospectively, EyeG2P enabled a significant increase in precision (35% on average) in comparison with routine testing strategies (p<0.001). We demonstrate that incorporation of EyeG2P into whole genome sequencing analysis strategies can reduce the number of variants for analysis to six variants, on average, while maintaining high diagnostic yield. Conclusion Automated filtering of genomic variants through EyeG2P can increase the efficiency of diagnostic testing for individuals with a broad range of inherited ophthalmic disorders. [ABSTRACT FROM AUTHOR]

The genes MECP2, CDKL5, FOXG1, UBE3A, SLC9A6, and TCF4 present unique challenges for current ACMG/AMP variant interpretation guidelines. To address those challenges, the Rett and Angelman‐like Disorders Variant Curation Expert Panel (Rett/AS VCEP) drafted gene‐specific modifications. A pilot study was conducted to test the clarity and accuracy of using the customized variant interpretation criteria. Multiple curators obtained the same interpretation for 78 out of the 87 variants (~90%), indicating appropriate usage of the modified guidelines the majority of times by all the curators. The classification of 13 variants changed using these criteria specifications compared to when the variants were originally curated and as present in ClinVar. Many of these changes were due to internal data shared from laboratory members however some changes were because of changes in strength of criteria. There were no two‐step classification changes and only 1 clinically relevant change (Likely pathogenic to VUS). The Rett/AS VCEP hopes that these gene‐specific variant curation rules and the assertions provided help clinicians, clinical laboratories, and others interpret variants in these genes but also other fully penetrant, early‐onset genes associated with rare disorders. [ABSTRACT FROM AUTHOR]

Background Improving the clinical interpretation of missense variants can increase the diagnostic yield of genomic testing and lead to personalised management strategies. Currently, due to the imprecision of bioinformatic tools that aim to predict variant pathogenicity, their role in clinical guidelines remains limited. There is a clear need for more accurate prediction algorithms and this study aims to improve performance by harnessing structural biology insights. The focus of this work is missense variants in a subset of genes associated with X linked disorders. Methods We have developed a protein-specific variant interpreter (ProSper) that combines genetic and protein structural data. This algorithm predicts missense variant pathogenicity by applying machine learning approaches to the sequence and structural characteristics of variants. Results ProSper outperformed seven previously described tools, including meta-predictors, in correctly evaluating whether or not variants are pathogenic; this was the case for 11 of the 21 genes associated with X linked disorders that met the inclusion criteria for this study. We also determined gene-specific pathogenicity thresholds that improved the performance of VEST4, REVEL and ClinPred, the three best-performing tools out of the seven that were evaluated; this was the case in 11, 11 and 12 different genes, respectively. Conclusion ProSper can form the basis of a molecule-specific prediction tool that can be implemented into diagnostic strategies. It can allow the accurate prioritisation of missense variants associated with X linked disorders, aiding precise and timely diagnosis. In addition, we demonstrate that gene-specific pathogenicity thresholds for a range of missense prioritisation tools can lead to an increase in prediction accuracy. [ABSTRACT FROM AUTHOR]

The development of computational methods to assess pathogenicity of pre-messenger RNA splicing variants is critical for diagnosis of human disease. We assessed the capability of eight algorithms, and a consensus approach, to prioritize 249 variants of uncertain significance (VUSs) that underwent splicing functional analyses. The capability of algorithms to differentiate VUSs away from the immediate splice site as being 'pathogenic' or 'benign' is likely to have substantial impact on diagnostic testing. We show that SpliceAI is the best single strategy in this regard, but that combined usage of tools using a weighted approach can increase accuracy further. We incorporated prioritization strategies alongside diagnostic testing for rare disorders. We show that 15% of 2783 referred individuals carry rare variants expected to impact splicing that were not initially identified as 'pathogenic' or 'likely pathogenic'; one in five of these cases could lead to new or refined diagnoses. [ABSTRACT FROM AUTHOR]