Repeat expansions cause over 30, predominantly neurogenetic, inherited disorders. These can present with overlapping clinical phenotypes, making molecular diagnosis challenging. Single gene or small panel PCR-based methods are employed to identify the precise genetic cause, but can be slow and costly, and often yield no result. Genomic analysis via whole exome and whole genome sequencing (WES and WGS) is being increasingly performed to diagnose genetic disorders. However, until recently analysis protocols could not identify repeat expansions in these datasets.A new method, called exSTRa (expandedShortTandemRepeatalgorithm) for the identification of repeat expansions using either WES or WGS was developed and performance of exSTRa was assessed in a simulation study. In addition, four retrospective cohorts of individuals with eleven different known repeat expansion disorders were analysed with the new method. Results were assessed by comparing to known disease status. Performance was also compared to three other analysis methods (ExpansionHunter, STRetch and TREDPARSE), which were developed specifically for WGS data. Expansions in the STR loci assessed were successfully identified in WES and WGS datasets by all four methods, with high specificity and sensitivity, excepting the FRAXA STR where expansions were unlikely to be detected. Overall exSTRa demonstrated more robust/superior performance for WES data in comparison to the other three methods. exSTRa can be applied to existing WES or WGS data to identify likely repeat expansions and can be used to investigate any STR of interest, by specifying location and repeat motif. We demonstrate that methods such as exSTRa can be effectively utilized as a screening tool to interrogate WES data generated with PCR-based library preparations and WGS data generated using either PCR-based or PCR-free library protocols, for repeat expansions which can then be followed up with specific diagnostic tests. exSTRa is available via GitHub (https://github.com/bahlolab/exSTRa).
ObjectiveTo compare the frequency and impact on channel function of KCNH2 variants in SUDEP patients with epilepsy controls comprising patients older than 50 years, a group with low SUDEP risk, and establish loss-of-function KCNH2 variants as predictive biomarkers of SUDEP risk.MethodsWe searched for KCNH2 variants with a minor allele frequency of < 5%. Functional analysis in Xenopus laevis oocytes was performed for all KCNH2 variants identified.ResultsKCNH2 variants were found in 11.1% (10/90) of SUDEP individuals compared to 6.0% (20/332) of epilepsy controls (p = 0.11). Loss-of-function KCNH2 variants, defined as causing > 20% reduction in maximal amplitude, were observed in 8.9% (8/90) SUDEP patients compared to 3.3% (11/332) epilepsy controls suggesting about three-fold enrichment (nominal p = 0.04). KCNH2 variants that did not change channel function occurred at a similar frequency in SUDEP (2.2%; 2/90) and epilepsy control (2.7%; 9/332) cohorts (p > 0.99). Rare KCNH2 variants (< 1% allele frequency) associated with greater loss of function and an ∼11-fold enrichment in the SUDEP cohort (nominal p = 0.03). In silico tools were unable to predict the impact of a variant on function highlighting the need for electrophysiological analysis.ConclusionsThese data show that loss-of-function KCNH2 variants are enriched in SUDEP patients and suggest that cardiac mechanisms contribute to SUDEP risk. We propose that genetic screening in combination with functional analysis can identify loss-of-function KCNH2 variants that could act as biomarkers of an individual’s SUDEP risk.
A patient presented with a history of recurrent pyoderma gangrenosum, arthritis and extensive acne, prompting a genetic workup for PAPA syndrome. An MEFV mutation was identified and a change in therapeutic strategy from anakinra to colchicine was successful. Click https://www.wileyhealthlearning.com/#/online-courses/b52447c0-1d37-472d-b0c0-7817352d6f68 for the corresponding questions to this CME article.
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