Genetic Evaluation of 114 Chinese Short Stature Children in the Next Generation Era: a Single Center Study

Author:

Huang Zhuo,Sun Yu,Fan Yanjie,Wang Lili,Liu Huili,Gong Zhuwen,Wang Jianguo,Yan Hui,Wang Yu,Hu Guorui,Wang Ruifang,Ye Jun,Han Lianshu,Qiu Wenjuan,Zhang Huiwen,Liang Lili,Yang Yu,Dauber Andrew,Yu Yongguo,Gu Xue-Fan

Abstract

Background/Aims: The genetics of human height is a frequently studied and complex issue. However, there is limited genetic research of short stature. To uncover the subgroup of patients to have higher yield and to propose a simplified diagnostic algorithm in the next generation era. Methods: This study included 114 Chinese children with height SDS ≤ -2.5 and unknown etiology from 2014 to 2015. Target/whole exome sequencing (referred as NGS) and chromosomal microarray analysis (CMA) were performed on the enrolled patients sequentially to identify potential genetic etiologies. The samples solved by NGS and CMA were retrospectively studied to evaluate the clinical pathway of the patients following a standard diagnostic algorithm. Results: In total, a potential genetic etiology was identified in 41 (36%) patients: 38 by NGS (33.3%), two by CMA (1.8%), and an additional one by both (0.9%). There were 46 different variants in 29 genes and 2 pathogenic CNVs identified. The diagnostic yield was significantly higher in patients with facial dysmorphism or skeletal abnormalities than those without the corresponding phenotype (P=0.006 and P=0.009, respectively, Pearson’s χ2 test). Retrospectively study the cohort indicate 83.3% patients eventually would be evaluated by NGS/CMA. Conclusion: This study confirms the utility of high-throughput molecular detection techniques for the etiological diagnosis of undiagnosed short stature and suggests that NGS could be used as a primary diagnostic strategy. Patients with facial dysmorphism and/or skeletal abnormalities are more likely to have a known genetic etiology. Moving NGS forward would simplified the diagnostic algorithm.

Publisher

S. Karger AG

Subject

Physiology

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