中文摘要
目的
神經發育假說認為精神分裂症的發生是源自於異常的腦部發育。而細微體質特徵 (Minor physical anomalies, MPAs) 與神經軟性功能 (Neurological soft signs, NSSs) 被認為是胚胎發育異常的生物標記。先前研究已經報導精神分裂症患者相較於健康對照組有較高的神經發展損傷。青少年危險行為是指對青少年的整體發展和適應狀態具有負面影響的行為，然而較少研究探討細微體質特徵與青少年危險行為之間的關聯。本研究的目的首先是找出細微體質特徵或神經軟性功能的項目中與精神分裂症以及青少年危險行為較為相關的項目，以及細微體質特徵與神經軟性功能在精神分裂症及青少年危險行為的預測效度。
方法
我們結合質性與量性項目改編細微體質特徵量表，測量個案的各部位特徵，及使用神經功能評估量表 (Neurological Evaluation Scale, NES) 作為神經軟性功能的測量工具。並且發展了一份自填式危險行為問卷，作為分類危險行為的標準，包含暴力、物質濫用、性行為、情緒問題。使用混合模型 (Mixed-effect model) 比較精神分裂症患者、其家屬及健康對照組之間的差異。利用羅吉斯迴歸分析 (Logistic regression model) 比較青少年危險行為組與其對照組的差異。並且使用Receiver operating characteristic (ROC) 曲線分析估計神經發展指標的預測效度。
結果
本研究共已收案210位精神分裂症病人，109位家屬，151位健康對照組，在個別使用細微體質特徵與神經軟性功能區分精神分裂症患者與健康對照組時，準確度分別為75.8%和80.6%，而在結合兩項神經發展標記時，準確度達83.8%。另外，青少年危險行為研究中已收案118位11-19歲青少年，ROC曲線分析的結果顯示，區分危險行為各組與其對照組的準確度，暴力行為為64.4%；物質濫用為65.3%；危險性行為為78.8%；情緒問題為68.6%。
結論
本篇研究顯示當同時使用細微體質特徵與神經軟性功能作為混合型的内表型可以更精準區分精神分裂症病人、其家屬及健康對照組。並且細微體質特徵與神經軟性功能在病人及其家屬都高於健康對照組，而危險行為青少年也有些微異常的細微體質特徵，可能符合精神分裂症及危險行為皆與神經發育異常有關的假說。

關鍵字: 精神分裂症、内表型、細微體質特徵差異、神經軟性功能、神經發展標記、青少年、危險行為

Background
The neurodevelopmental hypothesis proposes that schizophrenia is originated from aberrant brain development. Minor physical anomalies (MPA) and neurological soft signs (NSS) are suggested as a biomarker associated with disruptions of fetal development. Numerous studies report an increased frequency of neurodevelopmental impairments in schizophrenic individuals compared with controls. Risk behaviors are those that can have negative effects on the overall development and well-being of youth. There were limited researches on the relationship between MPA and risk behaviors which may be derived from abnormal neurodevelopment. The aim of this study was to identify which specific MPA and NSS are more associated with schizophrenia and risk behaviors, and to determine the optimal predictive value of MPA and NSS scores in schizophrenia and adolescents with risk behaviors.
Methods
We developed a modified physical measurement scale composited of both qualitative and quantitative items and used Neurological Evaluation Scale (NES) to assess the NSS. A self-administered questionnaire for the assessment of risk behaviors was also developed. Group comparisons were conducted by using mixed-effect model among schizophrenia, their first-degree relatives, and stepwise logistic regression analysis between case and control of risk behavior. The ROC curve was conducted to evaluate predictive accuracy, sensitivity, and specificity of these neurodevelopmental markers.
Results
There were 210 patients with schizophrenia, 109 nonpsychotic first-degree relatives, 151 normal controls, and a total of 118 adolescents aged 11-19 were recruited in this study. The results of ROC curve analysis for schizophrenia were as follows: The analysis of MPA and NSS alone provided an accuracy of 75.8% and 80.6%, respectively, for schizophrenia vs. controls. The composite MPA and NSS provide a greater predictive validity in the model of patients with schizophrenia vs. controls provided an accuracy of 83.8%. The results of ROC curve analysis for risk behaviors were as follows: The model of violence vs. controls provided an accuracy of 64.4 %; the model substance abuse vs. controls provided an accuracy of 65.3%; the model of sex behavior vs. controls provided an accuracy of 78.8%; the model of emotion vs. controls provided an accuracy of 68.6%.
Conclusion
We found that subjects were most accurately classified when MPA & NSS were considered as a composite neurodevelopmental marker rather than independently. The MPA and NSS are more frequent in patients with schizophrenia, their relatives and MPA were slightly different in adolescents with risk behaviors compared to controls, which are consistent with the hypothesis of abnormal neurodevelopment in schizophrenia and adolescents with risk behaviors.

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