SEPT-GD: A decision tree to prioritise potential RNA splice variants in cardiomyopathy genes for functional splicing assays in diagnostics.

BACKGROUND: Splice prediction algorithms currently used in routine DNA diagnostics have limited sensitivity and specificity, therefore many potential splice variants are classified as variants of uncertain significance (VUSs). However, functional assessment of VUSs to test splicing is labour-intensive and time-consuming. We developed a decision tree to prioritise potential splice variants for functional studies and functionally verified the outcome of the decision tree. MATERIALS AND METHODS: We built the decision tree, SEPT-GD, by setting thresholds for the splice prediction programs implemented in Alamut. A set of 343 variants with known effects on splicing was used as control for sensitivity and specificity. We tested SEPT-GD using variants from a Dutch cardiomyopathy cohort of 2002 patients that were previously classified as VUS and predicted to have a splice effect according to diagnostic rules. We then selected 12 VUSs ranked by SEPT-GD to functionally verify the predicted effect on splicing using a minigene assay: 10 variants predicted to have a strong effect and 2 with a weak effect. RT-PCR was performed for nine variants. Variant classification was re-evaluated based on the functional test outcome. RESULTS: Compared to similar individually tested algorithms, SEPT-GD shows higher sensitivity (91 %) and comparable specificity (88 %) for both consensus (dinucleotides at the start and end of the intron, GT at the 5' end and AG at the 3' end) and non-consensus splice-site variants (excluding middle of exon variants). Using clinical diagnostic criteria, 1295 unique variants in our cardiomyopathy cohort had originally been classified as VUSs, with 57 predicted by Alamut to have an effect on splicing. Using SEPT-GD, we prioritised 31 variants in 40 patients. In the minigene assay, all 12 variants showed results concordant with SEPT-GD predictions. RT-PCR confirmed the minigene results for two variants, TMEM43 c.1000 + 5G > T and TTN c.25922-6 T > G. Based on all outcomes, the SGCD c.4-1G > A and CSRP3 c.282-5_285del variants were reclassified as likely pathogenic. CONCLUSION: SEPT-GD outperforms the tools commonly used for RNA splicing prediction and improves prioritisation of variants in cardiomyopathy genes for functional splicing analysis in a diagnostic setting.

Feasibility of Follow-Up Studies and Reclassification in Spinocerebellar Ataxia Gene Variants of Unknown Significance.

Spinocerebellar ataxia (SCA) is a heterogeneous group of neurodegenerative disorders with autosomal dominant inheritance. Genetic testing for SCA leads to diagnosis, prognosis and risk assessment for patients and their family members. While advances in sequencing and computing technologies have provided researchers with a rapid expansion in the genetic test content that can be used to unravel the genetic causes that underlie diseases, the large number of variants with unknown significance (VUSes) detected represent challenges. To minimize the proportion of VUSes, follow-up studies are needed to aid in their reclassification as either (likely) pathogenic or (likely) benign variants. In this study, we addressed the challenge of prioritizing VUSes for follow-up using (a combination of) variant segregation studies, 3D protein modeling, in vitro splicing assays and functional assays. Of the 39 VUSes prioritized for further analysis, 13 were eligible for follow up. We were able to reclassify 4 of these VUSes to LP, increasing the molecular diagnostic yield by 1.1%. Reclassification of VUSes remains difficult due to limited possibilities for performing variant segregation studies in the classification process and the limited availability of routine functional tests.

Diagnostic yield of targeted next generation sequencing in 2002 Dutch cardiomyopathy patients.

BACKGROUND: Next-generation sequencing (NGS) is increasingly used for clinical evaluation of cardiomyopathy patients as it allows for simultaneous screening of multiple cardiomyopathy-associated genes. Adding copy number variant (CNV) analysis of NGS data is not routine yet and may contribute to the diagnostic yield. OBJECTIVES: Determine the diagnostic yield of our targeted NGS gene panel in routine clinical diagnostics of Dutch cardiomyopathy patients and explore the impact of exon CNVs on diagnostic yield. METHODS: Patients (N = 2002) referred for clinical genetic analysis underwent diagnostic testing of 55-61 genes associated with cardiomyopathies. Samples were analyzed and evaluated for single nucleotide variants (SNVs), indels and CNVs. CNVs identified in the NGS data and suspected of being pathogenic based on type, size and location were confirmed by additional molecular tests. RESULTS: A (likely) pathogenic (L)P variant was detected in 22.7% of patients, including 3 with CNVs and 25 where a variant was identified in a gene currently not associated with the patient's cardiomyopathy subtype. Only 15 out of 2002 patients (0.8%) were found to carry two (L)P variants. CONCLUSION: The yield of routine clinical diagnostics of cardiomyopathies was relatively low when compared to literature. This is likely due to the fact that our study reports the outcome of patients in daily routine diagnostics, therefore also including patients not fully fulfilling (subtype specific) cardiomyopathy criteria. This may also explain why (L)P variants were identified in genes not associated with the reported subtype. The added value of CNV analysis was shown to be limited but not negligible.