A Multisite Neurobehavioral Assessment of Fetal Alcohol Spectrum Disorders

项目摘要 这一资金更新请求是对NIH/NIAAA资助机会的回应， “胎儿酒精谱系障碍合作倡议（CIFASD）”（RFA-AA-17-007）。总体 当前提案的目的是开发、验证和实施临床新颖和创新的测量 工具，以准确识别受产前酒精暴露影响的儿童。拟定研究 与CIFASD资助机会的总体目标相关，以加速特定领域的研究 与FASD临床病例识别的新功能或改进功能的翻译相关。”这是一个关键的需要。 虽然有一个协调一致的研究努力，因为最初的临床描绘胎儿酒精综合征 (FAS)，了解产前酒精暴露的全方位影响仍然不完整，阻碍了 有效干预。尽管产前酒精暴露的个体可能会经历显著的 这些人的身份识别不足。漏诊率高 误诊导致干预机会的丧失和对观察到的病因的误解 困难开发准确和具体的识别工具将提高诊断能力， 关于治疗的临床决策为此，在以往的供资期间， 提高了对产前酒精暴露影响的特异性的理解， 受酒精影响的年轻人我们的分层CIFASD决策树，开发和验证了超过800 受试者，表明管理只有4个措施可以区分受酒精影响的青年， 有和没有行为问题或条件的非暴露对照，准确率> 80%。而 一个重要的进步，决策树是在一个高风险的研究样本中开发和验证的 酒精的影响。目前提案的一个目的是开发和测试《决定》的电子版 树（eTree）在低风险，国际，基于人群和基于诊所的样本。的另一个目的 根据RFA的具体目标，建议使用创新技术筛查畸形和/或 神经行为缺陷，以帮助识别酒精暴露的个人，是发展和 FASD在线神经行为筛查（FONS）的实施，基于网络的神经行为筛查 评估工具，用于通过门户网站招募的受试者（参见Foroud U01）。FONS将测量 已知FASD受影响的领域，包括神经行为诊断标准中所代表的领域 产前酒精暴露相关疾病（ND-PAE）eTree和FONS将通过以下方式进行验证： 基于实验室的产前酒精史儿童的神经心理学评估 暴露和非暴露对照，有和没有行为问题或条件。的结果 拟议的研究将实现我们的研究目标，提高招聘，最重要的是准确地识别 这将有助于改善受产前酒精暴露影响的个人的临床诊断和干预。

Project Summary This request for a renewal of funding is in response to the NIH/NIAAA funding opportunity entitled, “Collaborative Initiative on Fetal Alcohol Spectrum Disorders (CIFASD)” (RFA-AA-17-007). The overarching aim of the current proposal is to develop, validate, and implement clinically novel and innovative measurement tools to accurately identify children who are affected by prenatal alcohol exposure. The proposed study is relevant to the overall objective of the CIFASD funding opportunity “to accelerate specific areas of research related to the translation of new or improved capabilities in FASD clinical case recognition.” This is critical need. While there has been a concerted research effort since the initial clinical delineation of fetal alcohol syndrome (FAS), understanding the full spectrum of effects of prenatal alcohol exposure remains incomplete, hindering effective intervention. Although individuals with prenatal alcohol exposure may experience significantly impairing functional difficulties, identification of these individuals is inadequate. High rates of missed diagnoses and misdiagnosis result in lost opportunities for intervention and misunderstanding of the etiology of observed difficulties. Development of accurate and specific identification tools will improve diagnostic capability and clinical decision-making regarding treatment. To this end, during previous funding periods we substantially enhanced the understanding of the specificity of effects of prenatal alcohol exposure to increase identification of alcohol-affected youth. Our hierarchical CIFASD Decision Tree, developed and validated on over 800 subjects, indicates that administration of just 4 measures can distinguish alcohol-affected youth from nonexposed controls with and without behavioral concerns or conditions with accuracy rates of >80%. While a significant step forward, the Decision Tree was developed and validated in a research sample with a high risk of alcohol effects. One aim of the current proposal is to develop and test an electronic version of the Decision Tree (the eTree) in lower risk, international, population-based, and clinic-based samples. Another aim of the proposal, in line with the specific RFA goal to use innovative technologies to screen for dysmorphology and/or neurobehavioral deficits to aid in the identification of alcohol-exposed individuals, is the development and implementation of the FASD Online Neurobehavioral Screen (FONS), a web-based neurobehavioral assessment tool for use with subjects recruited via a web portal (cf. Foroud U01). The FONS will measure domains known to be affected in FASD, including those represented in diagnostic criteria for neurobehavioral disorder associated with prenatal alcohol exposure (ND-PAE). The eTree and the FONS will be validated using laboratory-based in-person neuropsychological assessment of children with histories of prenatal alcohol exposure and non-exposed controls with and without behavioral concerns or conditions. The results of the proposed research will fulfill our research goals, improve recruitment, and most importantly accurately identify individuals affected by prenatal alcohol exposure, leading to improved clinical diagnosis and intervention.