Brain functional connectivity correlates of autism diagnosis and familial liability in 24-month-olds.

IF 4.1 2区 医学 Q1 CLINICAL NEUROLOGY
John R Pruett, Alexandre A Todorov, Zoë W Hawks, Muhamed Talovic, Tomoyuki Nishino, Steven E Petersen, Savannah Davis, Lyn Stahl, Kelly N Botteron, John N Constantino, Stephen R Dager, Jed T Elison, Annette M Estes, Alan C Evans, Guido Gerig, Jessica B Girault, Heather Hazlett, Leigh MacIntyre, Natasha Marrus, Robert C McKinstry, Juhi Pandey, Robert T Schultz, William D Shannon, Mark D Shen, Abraham Z Snyder, Martin Styner, Jason J Wolff, Lonnie Zwaigenbaum, Joseph Piven
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引用次数: 0

Abstract

Background: fcMRI correlates of autism spectrum disorder (ASD) diagnosis and familial liability were studied in 24-month-olds at high (older affected sibling) and low familial likelihood for ASD.

Methods: fcMRI comparisons of high-familial-likelihood (HL) ASD-positive (HLP, N = 23) and ASD-negative (HLN, N = 91), and low-likelihood ASD-negative (LLN, N = 27) 24-month-olds from the Infant Brain Imaging Study (IBIS) Network were conducted, employing object oriented data analysis (OODA), support vector machine (SVM) classification, and network-level fcMRI enrichment analyses.

Results: OODA (alpha = 0.0167, 3 comparisons) revealed differences in HLP and LLN fcMRI matrices (p = 0.012), but none for HLP versus HLN (p = 0.047) nor HLN versus LLN (p = 0.225). SVM distinguished HLP from HLN (accuracy = 99%, PPV = 96%, NPV = 100%), based on connectivity involving many networks. SVM accurately classified (non-training) LLN subjects with 100% accuracy. Enrichment analyses identified a cross-group fcMRI difference in the posterior cingulate default mode network 1 (pcDMN1)- temporal default mode network (tDMN) pair (p = 0.0070). Functional connectivity for implicated connections in these networks was consistently lower in HLP and HLN than in LLN (p = 0.0461 and 0.0004). HLP did not differ from HLN (p = 0.2254). Secondary testing showed HL children with low ASD behaviors still differed from LLN (p = 0.0036).

Conclusions: 24-month-old high-familial-likelihood infants show reduced intra-DMN connectivity, a potential neural finding related to familial liability, while widely distributed functional connections correlate with ASD diagnosis.

24个月大婴儿自闭症诊断与家族责任的脑功能连接关系。
背景:研究了24个月大的自闭症谱系障碍(ASD)高(年龄较大的兄弟姐妹)和低家族可能性的自闭症谱系障碍(ASD)诊断和家族责任的fcMRI相关性。方法:采用面向对象数据分析(OODA)、支持向量机(SVM)分类和网络级fcMRI富集分析,对婴儿脑成像研究(IBIS)网络中24月龄的高家族似然(HL) asd阳性(HLP, N = 23)、asd阴性(HLN, N = 91)和低家族似然asd阴性(LLN, N = 27)进行fcMRI比较。结果:OODA (alpha = 0.0167, 3个比较)显示HLP和LLN的fcMRI矩阵差异(p = 0.012),但HLP与HLN之间无差异(p = 0.047), HLN与LLN之间无差异(p = 0.225)。SVM基于多个网络的连通性来区分HLP和HLN(准确率为99%,PPV = 96%, NPV = 100%)。SVM准确分类(非训练)LLN主题,准确率为100%。富集分析发现,后扣带默认模式网络1 (pcDMN1)-颞叶默认模式网络(tDMN)对在fcMRI上存在跨组差异(p = 0.0070)。这些网络中涉及连接的功能连通性在HLP和HLN中始终低于LLN (p = 0.0461和0.0004)。HLP与HLN差异无统计学意义(p = 0.2254)。二次检测显示HL患儿低ASD行为仍与LLN患儿有差异(p = 0.0036)。结论:24个月大的高家族可能性婴儿显示dmn内连接减少,这是一种潜在的与家族倾向相关的神经发现,而广泛分布的功能连接与ASD诊断相关。
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来源期刊
CiteScore
7.60
自引率
4.10%
发文量
58
审稿时长
>12 weeks
期刊介绍: Journal of Neurodevelopmental Disorders is an open access journal that integrates current, cutting-edge research across a number of disciplines, including neurobiology, genetics, cognitive neuroscience, psychiatry and psychology. The journal’s primary focus is on the pathogenesis of neurodevelopmental disorders including autism, fragile X syndrome, tuberous sclerosis, Turner Syndrome, 22q Deletion Syndrome, Prader-Willi and Angelman Syndrome, Williams syndrome, lysosomal storage diseases, dyslexia, specific language impairment and fetal alcohol syndrome. With the discovery of specific genes underlying neurodevelopmental syndromes, the emergence of powerful tools for studying neural circuitry, and the development of new approaches for exploring molecular mechanisms, interdisciplinary research on the pathogenesis of neurodevelopmental disorders is now increasingly common. Journal of Neurodevelopmental Disorders provides a unique venue for researchers interested in comparing and contrasting mechanisms and characteristics related to the pathogenesis of the full range of neurodevelopmental disorders, sharpening our understanding of the etiology and relevant phenotypes of each condition.
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