Reliable prediction of high-risk infants of autism with cortical microstructural biomarker

利用皮质微结构生物标志物可靠预测自闭症高危婴儿

基本信息

  • 批准号:
    10378703
  • 负责人:
  • 金额:
    $ 19.61万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-04-01 至 2025-03-31
  • 项目状态:
    未结题

项目摘要

Abstract The diagnosis of neuropsychiatric disorders such as autism spectrum disorder (ASD) is based on behavioral assessments that cannot be confirmed until 2-3 years of age. ASD affects 1 in 59 children in the U.S., and infants from high-risk families have 20 times of risk to develop ASD compared to the general population. Current paradigm misses the precious time window for potential early intervention from birth to 2-3 years of age. Therefore, the focus in ASD research is shifting toward developing early biomarkers which can predict the risk of an infant developing future behavioral abnormalities, while the infant is still in pre- symptomatic stage. Imaging markers play major roles in understanding of both ASD and typical developing (TD) brains. Neural MRI at early infancy may improve the current paradigm for diagnosis for ASD in high-risk infants. Macrostructural measurements such as cortical thickness and surface area from conventional T1 weighted MRI (T1w) have been the primary measurements for characterizing the maturation of infant cortex. However, T1w MRI cannot reveal information about the complex microstructural changes inside the cortical mantle. Cortical microstructure, associated with the underlying cellular and molecular processes, plays a vital role in neuronal circuit formation and emergence of brain functions. We have recently developed a novel protocol to quantify the cortical microstructure using advanced diffusion MRI (dMRI), including diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI). These advanced dMRI-based cortical microstructural measurements are sensitive imaging markers for the microstructural differentiation that characterizes the infant cortex maturation. We hypothesize that dMRI-based cortical microstructure measurements in early infancy could be potential biomarkers for early detection of ASD in high-risk infants. The goal of this study is to develop and test a novel protocol, using dMRI-based cortical microstructure feature, to reliably predict clinical score of infants at high risk for ASD and other brain disorders in general. We aim: 1) to develop a technique that incorporates dMRI-based cortical microstructural measures at early infancy with cutting-edge multi-kernel machine learning algorithms to reliably predict infants’ future neurodevelopmental outcomes at 2 years of age; 2) to demonstrate the initial clinical utility of the technique in infants at high-risk for ASD. To accomplish these goals, we leverage a large cohort of infant study that consists 100 TD infants who longitudinally undergo multi- modal MRI scans at early infancy and neuropsychological testing at 2 years for developing the prediction techniques, and a high-risk ASD study that allows us to longitudinally image the infants during infancy for testing our developed techniques. Finally, it should be emphasized that, although the present project focuses on its clinical applications in infants at high risk for ASD, the method developed also has important utility in detecting behavioral abnormalities in high risk subjects for other brain disorders (e.g. schizophrenia, ADHD), at a time prior to the age of diagnosis. Thus, this technique is expected to have a broad clinical impact.
摘要 自闭症谱系障碍(Asd)等神经精神障碍的诊断是基于 直到2-3岁才能确认的行为评估。在美国,每59名儿童中就有一名患有ASD 美国,来自高危家庭的婴儿患自闭症的风险是普通家庭的20倍 人口。当前范式错过了从出生到2-3岁潜在早期干预的宝贵时间窗口 几年前。因此,ASD研究的重点正在转向开发早期生物标志物,这些生物标志物可以 预测婴儿将来出现行为异常的风险,而婴儿仍处于 有症状的阶段。影像标记物在了解ASD和典型发展过程中发挥着重要作用 (TD)大脑。婴儿期早期的神经MRI可能会改进目前诊断高危ASD的范例 婴儿。常规T1的皮质厚度和表面积等宏观结构测量 磁共振加权成像(T1w)已成为表征婴儿大脑皮质成熟程度的主要指标。 然而,T1wMRI不能揭示皮质内部复杂的微结构变化的信息 披风。皮质微结构,与潜在的细胞和分子过程相关,发挥着至关重要的作用 在神经回路的形成和脑功能的出现中的作用。我们最近写了一本小说 使用包括扩散张量的高级弥散磁共振成像(DMRI)定量皮质微结构的方案 成像(DTI)和弥散峰度成像(DKI)。这些先进的基于dMRI的皮质微结构 测量是表征婴儿微结构分化的敏感的成像标志 皮质成熟。我们假设,在婴儿早期,基于dMRI的皮质微结构测量 可能成为早期发现高危婴儿ASD的潜在生物标志物。这项研究的目标是开发 并测试了一种新的方案,使用基于dMRI的皮质微结构特征来可靠地预测 一般来说,婴儿患自闭症和其他大脑疾病的风险很高。我们的目标是:1)开发一种技术 将基于dMRI的早期皮质微结构测量与尖端多核技术相结合 机器学习算法可以可靠地预测婴儿2岁时未来的神经发育结果; 2)论证该技术在ASD高危婴儿中的初步临床应用。要实现这些目标 目标,我们利用一项由100名TD婴儿组成的大型婴儿队列研究,这些婴儿纵向接受多项- 在婴儿早期进行模式核磁共振扫描,并在2岁时进行神经心理测试以发展预测 技术,以及一项高危ASD研究,使我们能够纵向成像婴儿在婴儿期 测试我们开发的技术。最后,应当强调的是,尽管本项目侧重于 在ASD高危婴儿的临床应用中,所开发的方法在 检测其他脑部疾病(如精神分裂症、多动症)高危受试者的行为异常,请访问 早于确诊年龄的时间。因此,这项技术有望产生广泛的临床影响。

项目成果

期刊论文数量(4)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Flattened Structural Network Changes and Association of Hyperconnectivity With Symptom Severity in 2-7-Year-Old Children With Autism.
  • DOI:
    10.3389/fnins.2021.757838
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    4.3
  • 作者:
    Ouyang M;Peng Y;Sotardi S;Hu D;Zhu T;Cheng H;Huang H
  • 通讯作者:
    Huang H
Infant brain regional cerebral blood flow increases supporting emergence of the default-mode network.
  • DOI:
    10.7554/elife.78397
  • 发表时间:
    2023-01-24
  • 期刊:
  • 影响因子:
    7.7
  • 作者:
    Yu Q;Ouyang M;Detre J;Kang H;Hu D;Hong B;Fang F;Peng Y;Huang H
  • 通讯作者:
    Huang H
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Minhui Ouyang其他文献

Minhui Ouyang的其他文献

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{{ truncateString('Minhui Ouyang', 18)}}的其他基金

Reliable prediction of high-risk infants of autism with cortical microstructural biomarker
利用皮质微结构生物标志物可靠预测自闭症高危婴儿
  • 批准号:
    10218522
  • 财政年份:
    2021
  • 资助金额:
    $ 19.61万
  • 项目类别:

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