预测自闭症

第一次, autism re博彩平台ers at the University of North Carolina at Chapel Hill used MRIs of six-month olds to show how brain regions are connected and synchronized, and then predict which babies at high risk of developing autism would be diagnosed with the condition at age two. 之前由卡罗莱纳领导的一项研究发表在 自然在2月份, used MRIs to determine differences in brain anatomy that predict which babies would develop autism as toddlers.

发表在 科学转化医学, this 纸 describes a second type of brain biomarker that re博彩平台ers and potentially clinicians could use as part of a diagnostic toolkit to help identify children as early as possible, 在自闭症症状出现之前.

“ 自然 纸 focused on measuring anatomy at two time points (six and 12 months), but this new 纸 focused on how brain regions are synchronized with each other at one time point (six months) to predict at an even younger age which babies would develop autism as toddlers,资深作者约瑟夫·皮文说, 托马斯·E. Castelloe Distinguished Professor of Psychiatry at the UNC School of 医学, and director of the Carolina Institute for Developmental Disabilities. “在症状出现之前，我们对大脑了解得越多, the better prepared we will be to help children and their families.”

共同资深作者John R. Pruett小., associate professor of psychiatry at Washington University School of 医学 in St. 路易, 说, “re are no behavioral features to help us identify autism prior to the development of symptoms, 哪些是在生命的第二年出现的. 但是早期干预可以改善结果, so if in the future we could use MRI to identify children at ultra-high risk before they develop symptoms, 我们可以更早开始治疗.”

研究期间, sleeping infants were placed in an MRI machine and scanned for about 15 minutes to view neural activity across 230 different brain regions. The re博彩平台ers analyzed how various brain regions were synchronized with each other. This synchrony reflects the coordinated activity of brain regions, 哪一个对认知至关重要, 内存, 和行为, 并且可以在睡眠中观察到.

The re博彩平台ers then focused on brain region connections related to the core features of autism: language skills, 重复的行为, 以及社会行为. 例如, the re博彩平台ers determined which brain regions – synchronized at six months – were related to behaviors at age two. This helped Piven’s co-investigators create a machine learning classifier – a computer program – to sort through the differences in synchronization among those key brain regions. 一旦计算机学会了这些不同的模式, the re博彩平台ers applied the machine learning classifier to a separate set of infants.

这部分研究包括在四个地点登记的59名婴儿, including the Carolina Institute for Developmental Disabilities (CIDD) at UNC-Chapel Hill, 华盛顿大学. 路易, the Children’s Hospital of Philadelphia and the University of Washington in Seattle. 每个婴儿都有一个患有自闭症的哥哥姐姐, which means each baby had about a one-in-five chance of developing autism, 与之相对的是68分之一, 一般人群的风险大概是多少. 59名婴儿中有11名后来患上了自闭症.

The machine learning classifier was able to separate findings into two main groups: MRI data from children who developed autism and MRI data from those who did not. 仅使用此信息, the computer program correctly predicted 81 percent of babies who would later meet the criteria for autism at two years of age.

“When the classifier determined a child had autism, it was always right. 但它错过了两个孩子. They developed autism but the computer program did not predict it correctly, 根据我们六个月大时获得的数据,罗伯特·爱默生说, a former UNC-Chapel Hill postdoctoral fellow and first author of the study. “No one has done this kind of study in six-month olds before, and so it needs to be replicated. We hope to conduct a larger study soon with different study participants.”

This marks the fourth autism imaging study UNC-Chapel Hill re博彩平台ers led or co-led this year. 随着 自然 纸卡罗莱纳的研究人员和合作者 发表了一项研究 in 生物精神病学 in March linking increased cerebrospinal fluid surrounding to autism diagnoses. 二月，他们 发表论文 in 大脑皮层about the brain network functional connections involved in social behavior deficits in children with autism.

“我认为最激动人心的工作尚未到来, when instead of using one piece of information to make these predictions, 我们一起使用所有的信息,爱默生说. “I think that will be the future of using biological diagnostics for autism during infancy.”