臺灣FGFR3基因相關骨骼發育不全症之分子診斷與基因型－表現型之分析

Abstract

背景 骨骼異常在新生兒中之發生率大約為1/4,000到1/5,000，常見的骨骼異常往往包含了骨骼發育、生長、骨骼平衡的整體系統異常。其中FGFR3基因相關骨骼異常疾病為最常見的骨骼發育異常，其常見種類包含以下四種：軟骨發育不全症 (Achondroplasia; ACH)、次軟骨發育不全症 (Hypochondroplasia; HCH)、和致死性畸胎侏儒症第一型及第二型 (Thanatophoric Dysplasia type I II; TD I II)。ACH的患者之智力發育正常，但普遍身形矮小、前額凸出、及鼻梁扁平，該疾病之發生率約1/15,000 到 1/40,000；HCH的患者出生時症狀並不明顯，因出生時身高體重及頭圍皆為正常，但於童年時期約2~4歲時症狀會變得顯著；而TD為新生兒期致死性的疾病，特徵是骨骼發育異常，包括四肢嚴重的變短、窄的胸部及水腦症，但軀幹長度正常，其中致死性畸胎侏儒症也可依照形態不同分成Type I 和 Type II，患者無法長大成人，疾病之發生率大約1/20,000到1/50,000。 不論在產前或者是出生後，當醫療人員觀察到腿骨短小或身材矮小的時候，往往直接懷疑為FGFR3基因相關的骨骼異常疾病，但不夠精確的診斷卻會導致FGFR3基因的檢出率低下。因此，希望可以合併症狀蒐集清單，用以建立一個更完整的篩檢流程，給予診斷一個切入的著手點。除此之外，記錄更詳盡的臨床症狀，亦可協助臨床端之醫療人員判別該症狀是否和FGFR3基因相關之骨骼異常疾病有關，藉此確立是否需要進行基因檢測，並且提高檢出效率，避免不必要的花費和檢測。 方法 蒐集2003年09月10日至2016年06月03日由臺大醫院、禾馨婦產科、和禾馨民權婦幼診所，送檢至慧智臨床基因醫學實驗室，進行FGFR3基因檢測之檢體共158份進行FGFR3 基因突變熱點之檢測，並且以FGFR3基因相關之骨骼發育異常疾病症狀蒐集清單，做回溯性臨床症狀資料搜集，藉此希望降低單靠臨床症狀診斷的偽陽性。產前個案我們蒐集「基因檢測送檢時」之臨床資料，而出生後個案則蒐集「送基因檢測前至送檢半年內」的臨床資料。其中FGFR3基因相關之骨骼發育異常疾病症狀蒐集清單，分類為產前四大項和出生後五大項，並且以各大項中之子項進行敘述統計以及多變項邏輯回歸分析。 結果 在158位蒐集個案之FGFR3基因檢出率為26% (41/158)，以基因點位歸類的疾病種類比例中軟骨發育不全症 (Achondroplasia; ACH)所佔比例為54% (22/41)、次軟骨發育不全症 (Hypochondroplasia; HCH) 佔20% (8/41)、致死性畸胎侏儒症第一型 (Thanatophoric Dysplasia type I; TD I) 佔24% (10/41)、致死性畸胎侏儒症第二型 (Thanatophoric Dysplasia type II; TD II) 佔2% (1/41)；其中產前108份檢體的FGFR3基因檢出率為22% (24/108)，而出生後的50份檢體的FGFR3基因檢出率為34% (17/50)。 若按照症狀蒐集清單記錄之項目分析，產前個案若記錄超過三項以上的子項，檢出效率可以超過50%；出生後個案若記錄超過六項以上的子項，檢出效率可以超過50%。 結論 現行臺灣骨骼異常之個案，雖然導因於FGFR3基因相關之骨骼異常疾病在臨床上相對常見，但其檢出效率卻始終低下，經由本次的資料統計和分析後發現，若在臨床上在送基因檢測前合併使用症狀蒐集清單，或許可透過勾選的項目總數（產前個案記錄超過三項以上及出生後個案記錄超過六項以上）提升送基因診斷後的檢出效率，但更重要的是可利用症狀蒐集清單蒐集更多臨床症狀，進而建議未來於基因診斷前先以症狀蒐集清單評估個案。 另外，本症狀蒐集清單對於FGFR3基因相關之骨骼異常疾病的家族基因諮詢上，可藉由此清單分析同家族之各個體是否有表現型上的差異，進而預期疾病的病情進展和可能遭遇的症狀；對於自體突變的個案來說，此清單不但可以增加臨床症狀的資料搜集，還可以藉由勾選的清單分析個案之臨床症狀是否和FGFR3基因相關骨骼異常疾病相似，亦可邁向提升檢出效率的目標。且因骨骼發育相關之致病基因種類繁多，在目標疾病檢測流程中，未於FGFR3基因熱點找到突變點位之個案，可利用NGS平台進行其他骨骼發育異常的基因檢測。

BACKGROUND Skeletal dysplasia (SD), characterized by developmental delay of long bone, is not a common skeletal disorder. It has been estimated that the incidence of SD in newborns is about 1 in 4,000 ~ 5,000. In terms of etiology, most of SD are FGFR3 gene related. Clinically, there are four different types for FGFR3 gene related SD, i.e. achondroplasia (ACH), hypochondroplasia (HCH), thanatophoric dysplasia types-I (TD I) -II (TD II). Patients with ACH are often short in stature, bossing of frontal lobe and low in nasal bridge. The intelligence development for ACH patient is usually normal. The incidence of ACH is estimated to be 1 in 15,000 and 40,000. The clinical severity of HCH patients is much less than that of ACH ones. The body height, head size and body weight at birth of the HCH patient are normal; but the growth rate becomes slow since their 2 ~4 years old. Patients with TD are usually lethal. Patients with TD I and TD II present extreme short extremities, hypoplastic thorax and hydrocephalus. The incidence for TD is 1 in 20,000 and 50,000, which is much lower than that of ACH. FGFR3 gene related SD is the most common type among the patients with SD. Screening for a mutation of FGFR3 gene is frequently requested in clinical practice. However, the low detection rate might be a hurdle for diagnosis. In this study, I traced the medical recordings and evaluated the frequencies of individual symptoms and signs in both prenatal and postnatal referred patients. Frequencies of presentations were also measured in patients with a positive mutation in FGFR3 gene hotspot. The goal is to improve the detection rate of FGFR3 mutation based on the clinical screening checklist. METHOD One hundred and fifty-eight patients were recruited from National Taiwan University Hospital and Diathus MFM clinic between September 10th, 2013 and June 3rd, 2016. After the DNA is extracted, it has been subjected to screen for a mutation in FGFR3 gene. The exons with a mutation hotspot and their flanking regions were amplified by polymerase chain reaction. The amplicons were sequenced by an DNA automatic sequencer to identify a variant. In addition to determine the detection rate, the medical records of the patients were traced to obtain the clinical features. Based on the features, a clinical screening checklist has been designed. The list was categorized into prenatal and postnatal parts, which had four and five items, respectively, which we analysis with descriptive statistics and multiple logistic regression analysis. RESULTS The detection rate for FGFR3 mutations in patients with SD is 26% (41/158), which is 22% (24/108) for prenatal cases and 34% (17/50) for postnatal ones. Among the forty-one SD patients, twenty-two had a clinical diagnosis of ACH, eight with HCH, ten with TD I and only one with TD II. The detection rate could attain 50% or even higher, if the SD patients had the clinical features fulfilling 3 items in prenatal- and 6 items in postnatal- checklist. Moreover, we expect to use the clinical screening checklist to obtain more clinical symptoms of FGFR3 gene related SD patients, and by doing so, we recommend to use the clinical screening checklist before having a FGFR3 gene hotspot test. CONCLUSION Up to date, the detection rate for a FGFR3 mutation in SD patients is not high, although it is the most common cause. According to our study, the situation could be improved as long as careful scoring the clinical features based on the symptom screening checklist. For those patients with a positive family history, the list can help us to uncover the variable manifestations among the family members with the same mutation. In those patients with a de novo mutation, any newly identified clinical features can also expand the database to be more comprehensive. These findings can help a genetic counselor to estimate the detection rate of a FGFR3 mutation; then, to give a suggestion to the couple who have a positive family history of SD. Moreover, for those patients who didn't harbor a mutation in FGFR3 gene could check for skeletal Dysplasia related NGS panel for further evaluation.