Genotype-phenotype correlation analysis in Japanese patients with Noonan syndrome
Genotype-phenotype correlation analysis in Japanese patients with Noonan syndrome
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DOI：
10.1507/endocrj.ej18-0564
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发表时间：
2019-01-01
影响因子：
2
通讯作者：
Kawai, Masanobu
中科院分区：
文献类型：
--
作者：
Shoji, Yasuko;Ida, Shinobu;Kawai, Masanobu
努南综合征（NS）是一种具有多种先天性畸形的异质性疾病。分子和遗传方法的最新进展已经确定了许多与NS有关的基因，其中大多数是RAS/MAPK信号通路的组成部分，基因型-表型相关分析已经广泛进行；然而，对日本NS患者的分析是有限的。在这里，我们评估了遗传诊断的NS患者的临床特征及其与基因型的关系。共纳入48例临床诊断为NS的患者，在39例（81.3%）患者中鉴定出相关突变，其中PTPN11突变最为普遍，其次是SOS1突变。包括肺狭窄和肥厚性心肌病在内的心脏异常最为普遍（87.2%），且未PTPN11突变的患者的肥厚性心肌病患病率高于PTPN11突变的患者。矮小是第二常见的特征（69.2%），目前的身高SD评分与1岁时的身高SD评分显著相关。SOS1突变的患者在婴儿期有更高的身高SD评分和更好的生长。这些发现表明日本NS患者存在基因型-表型相关性，这使我们能够使用遗传信息来预测临床病程，并可能允许基于基因型的医学干预。
Noonan syndrome (NS) is a heterogeneous disorder with multiple congenital malfonnations. Recent advances in molecular and genetic approaches have identified a number of responsible genes for NS, most of which are components of the RAS/MAPK signaling pathway, and genotype-phenotype correlation analyses have been extensively performed; however, analysis of Japanese NS patients is limited. Here, we evaluated clinical characteristics in genetically diagnosed NS patients and their relationships to genotypes. A total of 48 clinically diagnosed NS were included, and responsible mutations were identified in 39 patients (81.3%) with PTPN11 mutations being the most prevalent followed by SOS1 mutations. Cardiac anomalies including pulmonary stenosis and hypertrophic cardiomyopathy were most prevalent (87.2%), and the prevalence of hypertrophic cardiomyopathy was greater in patients without PTPN11 mutations than in those with PTPN11 mutations. Short stature was the second-most prevalent (69.2%) characteristic, and present height SD score was significantly associated with height SD score at 1 year old. Patients with SOS1 mutations had greater present height SD score and better growth during infancy. These findings suggest the presence of a genotype-phenotype correlation in Japanese patients with NS, which enables us to use genetic information to predict the clinical course and may allow for genotype-based medical interventions.