2013-08-012024-05-14https://scholars.lib.ntu.edu.tw/handle/123456789/657747摘要：背景：自閉症類群是常見之神經發展疾患，臨床上呈現社會功能缺損、語言發展遲緩、與情緒調節障礙，此障礙通常會持續終生，目前仍缺乏有效治療模式。其病因可能與遺傳和環境等多種因素有關，唯仍知之甚少。過去對於環境因素的研究顯示，某些懷孕或生產過程的併發症、雙親年紀、環境毒素等可能會增加罹患自閉症的風險，但尚無亞洲資料。環境因素之重要性在於，可針對高風險個案即早診斷與療育，並深化對病因的了解，以對此症提出嶄新治療思維與預防之道。本團隊過去已在本土樣本中發現若干影響腦部發育之基因(CNS patterning genes)與自閉症類群的有無有統計顯著相關，顯示影響腦部發育基因在本土自閉症類群可能扮演重要角色。期望在這個計畫中，對環境因素諸如懷孕史、生產史、成長史等做詳細評估，並針對上述影響腦部發育之基因，進一步驗證其與環境因素是否有交互作用，以及此交互作用是否影響自閉症類群之臨床表現。本研究所得結果，可對此症之病因研究建立足夠之實證基礎，以開啟未來相關之上位遺傳研究(epigenetic study)。 目的：為了解台灣本土自閉症類群之非基因危險因子(亦即廣義之環境因素)，本研究旨在探討在台灣自閉症類群之非基因之危險因子，研究這些因素對於自閉症臨床表現與神經認知功能的影響，並以影響腦發育之基因為標的，探討基因與環境之交互作用是否影響自閉症臨床表現與患者之神經認知功能。 方法：本研究擬自既有之自閉症類群世代中挑選 400 位診斷為自閉症或亞斯伯格症之患者，並邀請其未罹病手足加入，以及招募 400 位年齡與性別配對、正常發展之健康對照組，比較三組之懷孕或生產過程的併發症、雙親年紀、環境毒素等因素之盛行率。此外，並針對自閉症類群患者，進行詳細臨床評估、自閉症相關量表、神經認知功能測驗、以及基因檢測(候選基因為影響腦發育之基因：EN2、WNT2、與 DISC1)，以進一步探討前述之環境/非基因因素，對於患者臨床上自閉症症狀嚴重度、以及神經認知功能的影響。另外，並分析環境/非基因因素與基因之交互作用，對於自閉症症狀、以及神經認知功能的影響。有鑑於多重因素之複雜關係，在統計分析方面，除採用傳統之迴歸分析方法之外，並另採用兩種新無母數分析方法：多因子面向歸納法(extended multifactor dimension reduction method)與類神經網路(artificial neural network)之分析方法來互相驗證所得結果。<br> Abstract: Background: Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders with life-long deficits without effective treatment. The development of ASD has been associated with a complex collection of variables, both genetic and environmental. Nongenetic factors such as advanced parental age, prenatal/perinatal infection, or environmental toxins have been proposed to increase the risk of autism. Yet, we know little about the contribution of environmental factors in Taiwan’s ASD population. Our previous study has shown that the CNS patterning genes were significantly associated with ASD in Taiwan’s ASD population. To further investigate the role of these genes and their gene-environmental interaction on the psychopathology of ASD, this study applies a gene-environment interaction approach to elucidate the contribution of nongenetic factors and its relationship with genetic factors. Nongenetic factors imply a new way for intervention and prevention for ASD, and may serve as a new solution to find the genetic etiology of autism. Objectives: This project aims to survey the frequency of environmental risk factors among individuals with ASD and their non-affected siblings, to test for each environmental effect on phenotypes of ASD among ASD participants, to test for genetic effects of CNS patterning genes on phenotypes of ASD, and to test whether if gene-environment interaction on the phenotypes of ASD. Methods: This study will recruit 400 individuals with ASD from an autism cohort, their nonaffected siblings and 400 age-, sex-matched neurotypical children/adults. Each participant will receive clinical assessment and environmental data collection, including prenatal/perinatal conditions, medical history, other environmental history, etc. Measures of questionnaires regarding the severity of autistic core symptoms and neurocognitive testing for sustained attention, set-shifting and executive function will be used to assess all probands with ASD, as well as genotyping of tagging SNPs of three CNS patterning genes (EN2, WNT2, and DISC1). As to data analysis, the frequency of each environmental factor, both prenatal and perinatal factors, will be compared between probands with ASD, their siblings, and neurotypical controls. Taking the autistic core symptoms and the neurocognitive function as dependent variables, the environmental factors, the genetic factors, and the GE interaction will be tested for their main effects, after adjustment of sex and age. Specifically, each environmental and genetic variable is tested for its association with the dependent variable, to find the variable which can modify autistic symptoms and/or neurocognitive function. Subsequently, the significant variables are then put together for multivariate analysis. To assess the interaction between genetic factors and environmental factors, an interaction term (genetic factor * environmental factor) will be examined in the regression model to test its influence on the severity of autistic symptoms and neurocognitive deficits. Besides, we will also apply two new non- or semi-parametric methods: extended multifactor dimension reduction method and artificial neural network to validate the results.自閉症自閉症類群基因-環境交互作用生產前周產期環境因子autismautism spectrum disordersgene-environment interactionprenatalperinatalenvironmental