次世代基因定序於致病性身材矮小病患之應用

Abstract

背景 身材矮小是小兒內分泌門診中最常見的就診原因，但造成身材矮小的因素，包括父母身高與進入青春期的年紀、環境因素、營養、賀爾蒙失調、系統性疾病及遺傳等因素。根據全基因組關聯分析(genome-wide association study, GWAS)，目前已知有大於600個以上的基因與身材矮小有關。部份基因變異造成的臨床表現十分相似，各自影響身高的強度亦不同，因此需要藉由高通量的次世代基因定序技術(Next Generation Sequencing , NGS)，才能在短時間內大量定序DNA，來瞭解身材矮小的患者的基因變異與臨床症狀的影響。 方法 自2018年2月至2019年12月間，我們納入台灣地區70位身材矮小並排除體質性生長遲滯及明顯家族性身材矮小的受試者。利用NGS身材矮小相關基因套組檢測來分析可能影響身高的變異。此套組包含194個基因，以及13個用來計算身材矮小風險分數的與人類身高相關的核苷酸多形性(SNP)變異。同時，我們也蒐集受試者的臨床表徵來協助分子診斷的確立。 結果 在這70位患者，共有25名受試者(35.7%)找到身材矮小的致病基因。這些基因包括ACAN, COL10A1, COL11A2, COL2A1, COL9A1, COL9A2, FGFR3, GDF5, NPR2, NF1, PTPN11, LHX4, OBSL1等13個基因。在身材矮小風險分數分析中，無法有效辨別風險分數與是否帶有致病性變異之相關性。 結論 我們的資料顯示身材矮小套組基因檢驗的確可以找到與單基因的身材矮小相關致病性變異，而利用多基因模型的身材矮小風險分析則不適用本研究的族群，較適用於家族性身材矮小(familial short stature , FSS)之族群。

Background Short stature is the most common encountered complaint in pediatric endocrine clinic with heterogeneous etiology. While evaluating a patient with short stature, many factors including parental heights and their age entering puberty, environmental factors, nutrition, hormonal disorders and systemic disease should be considered. Genome-wide association studies have identified more than 600 genes associated with adult height with genetic heterogeneity and various impacts. Under this situation, next generation sequencing (NGS) is a high-throughput sequencing technique that allows large-scaled DNA sequencing. We used NGS analysis to understand the correlation between short stature associate variants and clinical phenotypes. Methods During the period from Feb 2018 to Dec 2019, we included 70 patients with short stature and without constitutional delay of growth and adolescence and familial short stature. NGS-based targeted gene panel were used to search for causative variants. This panel included 194 short stature associate genes and 13 human height related SNPs for calculating short stature risk score. Clinical presentations of these patients were collected as well to help establish molecular diagnosis. Results A total of 70 patients were analyzed and 13 disease-causing genes were identified in 25 patients (35.7%), including ACAN, COL10A1, COL11A2, COL2A1, COL9A1, COL9A2, FGFR3, GDF5, NPR2, NF1, PTPN11 and OBSL1 genes. In short stature risk score analysis, there was no significant correlation between risk score and the pathogenicity of disease-causing variants. Conclusion Our data demonstrates that the short stature panel could help identify monogenic causes of short stature. However, risk score analysis with polygenic model is more likely to be suitable for patients with familial short stature which were not included in our study.