Plitt Mark, Barnes Kelly Anne, Wallace Gregory L, Kenworthy Lauren, Martin Alex
Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892;
Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892; Department of Speech and Hearing Sciences, George Washington University, Washington, DC 20052;
Proc Natl Acad Sci U S A. 2015 Dec 1;112(48):E6699-706. doi: 10.1073/pnas.1510098112. Epub 2015 Nov 16.
Although typically identified in early childhood, the social communication symptoms and adaptive behavior deficits that are characteristic of autism spectrum disorder (ASD) persist throughout the lifespan. Despite this persistence, even individuals without cooccurring intellectual disability show substantial heterogeneity in outcomes. Previous studies have found various behavioral assessments [such as intelligence quotient (IQ), early language ability, and baseline autistic traits and adaptive behavior scores] to be predictive of outcome, but most of the variance in functioning remains unexplained by such factors. In this study, we investigated to what extent functional brain connectivity measures obtained from resting-state functional connectivity MRI (rs-fcMRI) could predict the variance left unexplained by age and behavior (follow-up latency and baseline autistic traits and adaptive behavior scores) in two measures of outcome--adaptive behaviors and autistic traits at least 1 y postscan (mean follow-up latency = 2 y, 10 mo). We found that connectivity involving the so-called salience network (SN), default-mode network (DMN), and frontoparietal task control network (FPTCN) was highly predictive of future autistic traits and the change in autistic traits and adaptive behavior over the same time period. Furthermore, functional connectivity involving the SN, which is predominantly composed of the anterior insula and the dorsal anterior cingulate, predicted reliable improvement in adaptive behaviors with 100% sensitivity and 70.59% precision. From rs-fcMRI data, our study successfully predicted heterogeneity in outcomes for individuals with ASD that was unaccounted for by simple behavioral metrics and provides unique evidence for networks underlying long-term symptom abatement.
尽管自闭症谱系障碍（ASD）的社交沟通症状和适应性行为缺陷通常在儿童早期就已被识别，但这些特征会贯穿人的一生。尽管这种情况持续存在，但即使是没有并发智力残疾的个体，其结果也存在很大的异质性。先前的研究发现，各种行为评估（如智商、早期语言能力以及基线自闭症特征和适应性行为得分）可预测结果，但功能方面的大部分差异仍无法用这些因素来解释。在本研究中，我们调查了从静息态功能连接磁共振成像（rs-fcMRI）获得的功能性脑连接测量在多大程度上能够预测在两种结果测量指标（扫描后至少1年的适应性行为和自闭症特征，平均随访延迟 = 2年10个月）中未被年龄和行为（随访延迟以及基线自闭症特征和适应性行为得分）解释的差异。我们发现，涉及所谓突显网络（SN）、默认模式网络（DMN）和额顶叶任务控制网络（FPTCN）的连接对未来自闭症特征以及同一时期自闭症特征和适应性行为的变化具有高度预测性。此外，主要由前脑岛和背侧前扣带回组成的涉及SN的功能连接预测了适应性行为的可靠改善，敏感性为100%，精确性为70.59%。从rs-fcMRI数据来看，我们的研究成功预测了ASD个体中未被简单行为指标解释的结果异质性，并为长期症状减轻背后的神经网络提供了独特的证据。
