Division of Pediatric Neurology, Developmental Medicine and Social Pediatrics, Center for Neuromuscular Disorders in Childhood. Dr. von Hauner Children's Hospital, University Hospital, LMU Munich, Germany.
genetikum® Center for Human Genetics, Neu-Ulm, Germany.
J Neuromuscul Dis. 2017;4(4):315-325. doi: 10.3233/JND-170231.
BACKGROUND: Early-onset myopathies are a heterogeneous group of neuromuscular diseases with broad clinical, genetic and histopathological overlap. The diagnostic approach has considerably changed since high throughput genetic methods (next generation sequencing, NGS) became available. OBJECTIVE: We present diagnostic subgroups in a single neuromuscular referral center and describe an algorithm for the diagnostic work-up. METHODS: The diagnostic approach of 98 index patients was retrospectively analysed. In 56 cases targeted sequencing of a known gene was performed, in 44 patients NGS was performed using large muscle specific panels, and in 12 individuals whole exome sequencing (WES) was undertaken. One patient was diagnosed via array CGH. Clinical features of all patients are provided. RESULTS: The final diagnosis could be found in 63 out of 98 patients (64%) with molecular genetic analysis. In 55% targeted gene sequencing could establish the genetic diagnosis. However, this rate largely depended on the presence of distinct histological or clinical features. NGS (large myopathy-related panels and WES) revealed genetic diagnosis in 58.5% (52% and 67%, respectively). The genes detected by WES in our cohort of patients were all covered by the panels. Based on our findings we propose an algorithm for a practical diagnostic approach.Prevalences:MTM1- and LAMA2-patients are the two biggest subgroups, followed by SEPN1-, RYR1- and Collagen VI-related diseases. 31% of genetically confirmed cases represents a group with overlap between "congenital myopathies (CM)" and "congenital muscular dystrophies (CMD)". In 36% of the patients a specific genetic diagnosis could not be assigned. CONCLUSIONS: A final diagnosis can be confirmed by high throughput genetic analysis in 58.5% of the cases, which is a higher rate than reported in the literature for muscle biopsy and should in many cases be considered as a first diagnostic tool. NGS cannot replace neuromuscular expertise and a close discussion with the geneticists on NGS is mandatory. Targeted candidate gene sequencing still plays a role in selected cases with highly suspicious clinical or histological features. There is a relevant clinical and genetic overlap between the entities CM and CMD.
背景：早发性肌病是一组具有广泛临床、遗传和组织病理学重叠的神经肌肉疾病。自从高通量遗传方法（下一代测序，NGS）问世以来，诊断方法发生了很大的变化。
目的：我们在一个单一的神经肌肉转诊中心介绍了诊断亚组，并描述了诊断工作流程的算法。
方法：回顾性分析了 98 例索引患者的诊断方法。在 56 例中进行了已知基因的靶向测序，在 44 例中进行了大肌肉特异性面板的 NGS，在 12 例中进行了全外显子组测序（WES）。有 1 例患者通过 array CGH 进行诊断。提供了所有患者的临床特征。
结果：98 例患者中有 63 例（64%）通过分子遗传学分析找到了最终诊断。在 55%的情况下，靶向基因测序可以确定遗传诊断。然而，这一比率在很大程度上取决于是否存在明显的组织学或临床特征。NGS（大肌病相关面板和 WES）在 58.5%的患者中发现了遗传诊断（分别为 52%和 67%）。在我们的患者队列中，WES 检测到的基因都被面板覆盖。基于我们的发现，我们提出了一种实用的诊断方法的算法。患病率：MTM1-和 LAMA2-患者是两个最大的亚组，其次是 SEPN1-、RYR1-和 Collagen VI-相关疾病。31%的基因确诊病例代表了“先天性肌病（CM）”和“先天性肌营养不良症（CMD）”之间重叠的一组。在 36%的患者中，无法确定特定的遗传诊断。
结论：通过高通量遗传分析，58.5%的病例可以得到最终诊断，这一比率高于文献中报道的肌肉活检，在许多情况下，应将其视为一种首选的诊断工具。NGS 不能替代神经肌肉专业知识，与遗传学家就 NGS 进行密切讨论是必要的。在具有高度可疑临床或组织学特征的选定病例中，靶向候选基因测序仍具有作用。CM 和 CMD 之间存在相关的临床和遗传重叠。
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