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认知发育迟缓高危新生儿的脑连接组拓扑结构改变:一项跨病因学研究。

Altered Connectome Topology in Newborns at Risk for Cognitive Developmental Delay: A Cross-Etiologic Study.

作者信息

Speckert Anna, Payette Kelly, Knirsch Walter, von Rhein Michael, Grehten Patrice, Kottke Raimund, Hagmann Cornelia, Natalucci Giancarlo, Moehrlen Ueli, Mazzone Luca, Ochsenbein-Kölble Nicole, Padden Beth, Latal Beatrice, Jakab Andras

机构信息

Center for MR Research, University Children's Hospital Zurich, Zurich, Switzerland.

Neuroscience Center Zurich, University of Zurich, Zurich, Switzerland.

出版信息

Hum Brain Mapp. 2025 Jan;46(1):e70084. doi: 10.1002/hbm.70084.

Abstract

The human brain connectome is characterized by the duality of highly modular structure and efficient integration, supporting information processing. Newborns with congenital heart disease (CHD), prematurity, or spina bifida aperta (SBA) constitute a population at risk for altered brain development and developmental delay (DD). We hypothesize that, independent of etiology, alterations of connectomic organization reflect neural circuitry impairments in cognitive DD. Our study aim is to address this knowledge gap by using a multi-etiologic neonatal dataset to reveal potential commonalities and distinctions in the structural brain connectome and their associations with DD. We used diffusion tensor imaging of 187 newborns (42 controls, 51 with CHD, 51 with prematurity, and 43 with SBA). Structural weighted connectomes were constructed using constrained spherical deconvolution-based probabilistic tractography and the Edinburgh Neonatal Atlas. Assessment of brain network topology encompassed the analysis of global graph features, network-based statistics, and low-dimensional representation of global and local graph features. The Cognitive Composite Score of the Bayley scales of Infant and Toddler Development 3rd edition was used as outcome measure at corrected 2 years for the preterm born individuals and SBA patients, and at 1 year for the healthy controls and CHD. We detected differences in the connectomic structure of newborns across the four groups after visualizing the connectomes in a two-dimensional space defined by network integration and segregation. Further, analysis of covariance analyses revealed differences in global efficiency (p < 0.0001), modularity (p < 0.0001), mean rich club coefficient (p = 0.017), and small-worldness (p = 0.016) between groups after adjustment for postmenstrual age at scan and gestational age at birth. Moreover, small-worldness was significantly associated with poorer cognitive outcome, specifically in the CHD cohort (r = -0.41, p = 0.005). Our cross-etiologic study identified divergent structural brain connectome profiles linked to deviations from optimal network integration and segregation in newborns at risk for DD. Small-worldness emerges as a key feature, associating with early cognitive outcomes, especially within the CHD cohort, emphasizing small-worldness' crucial role in shaping neurodevelopmental trajectories. Neonatal connectomic alterations associated with DD may serve as a marker identifying newborns at-risk for DD and provide early therapeutic interventions. Trial Registration: ClinicalTrials.gov identifier: NCT00313946.

摘要

人类大脑连接组具有高度模块化结构和高效整合的双重特性,支持信息处理。患有先天性心脏病(CHD)、早产或开放性脊柱裂(SBA)的新生儿构成了大脑发育改变和发育迟缓(DD)风险人群。我们假设,无论病因如何,连接组组织的改变反映了认知性DD中的神经回路损伤。我们的研究目的是通过使用多病因新生儿数据集来填补这一知识空白,以揭示大脑结构连接组中的潜在共性和差异及其与DD的关联。我们对187名新生儿(42名对照、51名患有CHD、51名早产、43名患有SBA)进行了扩散张量成像。使用基于约束球面反卷积的概率纤维束成像和爱丁堡新生儿图谱构建结构加权连接组。对脑网络拓扑结构的评估包括全局图特征分析、基于网络的统计以及全局和局部图特征的低维表示。对于早产个体和SBA患者,采用贝利婴幼儿发展量表第三版的认知综合评分作为矫正2岁时的结果指标,对于健康对照和CHD患者则为1岁时的指标。在由网络整合和分离定义的二维空间中可视化连接组后,我们检测到四组新生儿连接组结构的差异。此外,协方差分析显示,在对扫描时的月经后年龄和出生时的胎龄进行调整后,各组之间在全局效率(p < 0.0001)、模块化(p < 0.0001)、平均富俱乐部系数(p = 0.017)和小世界特性(p = 0.016)方面存在差异。此外,小世界特性与较差的认知结果显著相关,特别是在CHD队列中(r = -0.41,p = 0.005)。我们的跨病因研究确定了与DD风险新生儿中偏离最佳网络整合和分离相关的不同大脑结构连接组特征。小世界特性成为一个关键特征,与早期认知结果相关,尤其是在CHD队列中,强调了小世界特性在塑造神经发育轨迹中的关键作用。与DD相关的新生儿连接组改变可能作为识别DD风险新生儿的标志物,并提供早期治疗干预。试验注册:ClinicalTrials.gov标识符:NCT00313946。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97c0/11718324/0ef75295d528/HBM-46-e70084-g003.jpg

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