A Novel Methodology to Recalibrate Pathogenic Range of SCA36 Repeat Expansions for PGT-M
Abstract
BackgroundSpinocerebellar ataxia-36 (SCA36) is an inherited neurodegenerative disorder caused by the heterozygous expansion of an intronic GGCCTG hexanucleotide repeat in the NOP56 gene on chromosome 20p13. Unaffected individuals typically carry 3 to 14 repeats, whereas affected individuals carry 650 to 2,500. However, based on a single study, this pathogenic range was conservatively established, limiting its extended clinical applicability such as preimplantation genetic testing (PGT). In this study, we propose a novel methodology to recalibrate the pathogenic range of SCA36 repeat expansion. MethodsWe conducted a comprehensive literature review and collected examination data from 2012 onward. We used the gamma distribution to describe the data distribution and applied Bayesian methods to update the prior distribution with data from recent publications. Based on the recalibrated distribution, the 95% confidence interval (CI) was used to determine the new lower boundary of the pathogenic range. A pedigree was collected to validate the proposal with long-read sequencing (LRS) applied to detect the high GC content and long length of repeat expansions. ResultsOur results, based on 2 studies, indicate that the data distribution is well-described by gamma distribution. The prior, likelihood and posterior distributions within the 95% CI for the integrated research of SCA36 pathogenic repeat expansions were [446, +{infty}), [124, +{infty}), and [484, +{infty}), respectively. These recalibrated pathogenic ranges were validated by an authentic case: a proband diagnosed with SCA36 carrying 418 repeats and her daughter with 499 repeats, under the detection of LRS. ConclusionsTherefore, we proposed a novel methodology that integrates updated data, 95% CI using Bayesian methods and LRS for accurate detection of repeat expansions of dynamic mutations to present an up-to-date pathogenic range of SCA36, as well as other similar diseases.
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