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自闭症中改变的皮质复杂性的分子结构

Molecular architecture of the altered cortical complexity in autism.

作者信息

Mamat Makliya, Chen Yiyong, Shen Wenwen, Li Lin

机构信息

School of Basic Medical Sciences, Health Science Center, Ningbo University, No. 818 Fenghua Road, Jiangbei District, Ningbo, 315211, Zhejiang, People's Republic of China.

Affiliated Kangning Hospital of Ningbo University, Ningbo, 315201, Zhejiang, People's Republic of China.

出版信息

Mol Autism. 2025 Jan 6;16(1):1. doi: 10.1186/s13229-024-00632-2.

DOI:10.1186/s13229-024-00632-2
PMID:39763008
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11705879/
Abstract

Autism spectrum disorder (ASD) is characterized by difficulties in social interaction, communication challenges, and repetitive behaviors. Despite extensive research, the molecular mechanisms underlying these neurodevelopmental abnormalities remain elusive. We integrated microscale brain gene expression data with macroscale MRI data from 1829 participants, including individuals with ASD and typically developing controls, from the autism brain imaging data exchange I and II. Using fractal dimension as an index for quantifying cortical complexity, we identified significant regional alterations in ASD, within the left temporoparietal, left peripheral visual, right central visual, left somatomotor (including the insula), and left ventral attention networks. Partial least squares regression analysis revealed gene sets associated with these cortical complexity changes, enriched for biological functions related to synaptic transmission, synaptic plasticity, mitochondrial dysfunction, and chromatin organization. Cell-specific analyses, protein-protein interaction network analysis and gene temporal expression profiling further elucidated the dynamic molecular landscape associated with these alterations. These findings indicate that ASD-related alterations in cortical complexity are closely linked to specific genetic pathways. The combined analysis of neuroimaging and transcriptomic data enhances our understanding of how genetic factors contribute to brain structural changes in ASD.

摘要

自闭症谱系障碍(ASD)的特征在于社交互动困难、沟通障碍和重复行为。尽管进行了广泛研究,但这些神经发育异常背后的分子机制仍然难以捉摸。我们将来自1829名参与者(包括来自自闭症大脑成像数据交换I和II的自闭症患者和正常发育对照)的微观大脑基因表达数据与宏观MRI数据进行了整合。使用分形维数作为量化皮质复杂性的指标,我们在左颞顶叶、左周边视觉、右中央视觉、左躯体运动(包括脑岛)和左腹侧注意网络中发现了ASD患者显著的区域改变。偏最小二乘回归分析揭示了与这些皮质复杂性变化相关的基因集,这些基因集在与突触传递、突触可塑性、线粒体功能障碍和染色质组织相关的生物学功能方面得到了富集。细胞特异性分析、蛋白质-蛋白质相互作用网络分析和基因时间表达谱进一步阐明了与这些改变相关的动态分子格局。这些发现表明,ASD相关的皮质复杂性改变与特定的遗传途径密切相关。神经影像学和转录组数据的联合分析增强了我们对遗传因素如何导致ASD患者大脑结构变化的理解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d20/11705879/4dff1bd6e335/13229_2024_632_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d20/11705879/97b62f8926b4/13229_2024_632_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d20/11705879/adfac1dbf6eb/13229_2024_632_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d20/11705879/a9a261476ddb/13229_2024_632_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d20/11705879/4dff1bd6e335/13229_2024_632_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d20/11705879/97b62f8926b4/13229_2024_632_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d20/11705879/adfac1dbf6eb/13229_2024_632_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d20/11705879/a9a261476ddb/13229_2024_632_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d20/11705879/4dff1bd6e335/13229_2024_632_Fig4_HTML.jpg

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本文引用的文献

1
CAT: a computational anatomy toolbox for the analysis of structural MRI data.CAT:用于分析结构磁共振成像数据的计算解剖工具箱。
Gigascience. 2024 Jan 2;13. doi: 10.1093/gigascience/giae049.
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Cortical gene expression architecture links healthy neurodevelopment to the imaging, transcriptomics and genetics of autism and schizophrenia.皮质基因表达结构将健康的神经发育与自闭症和精神分裂症的影像学、转录组学和遗传学联系起来。
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Fractal-Based Analysis of Histological Features of Brain Tumors.
基于分形的脑肿瘤组织学特征分析。
Adv Neurobiol. 2024;36:501-524. doi: 10.1007/978-3-031-47606-8_26.
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Fractal dimension of the cortical gray matter outweighs other brain MRI features as a predictor of transition to dementia in patients with mild cognitive impairment and leukoaraiosis.在轻度认知障碍和脑白质疏松症患者中,皮质灰质的分形维数作为向痴呆症转变的预测指标,比其他脑MRI特征更为重要。
Front Hum Neurosci. 2023 Sep 26;17:1231513. doi: 10.3389/fnhum.2023.1231513. eCollection 2023.
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Altered markers of mitochondrial function in adults with autism spectrum disorder.自闭症谱系障碍成人中线粒体功能改变的标志物。
Autism Res. 2023 Nov;16(11):2125-2138. doi: 10.1002/aur.3029. Epub 2023 Sep 16.
6
Fractal dimension: analyzing its potential as a neuroimaging biomarker for brain tumor diagnosis using machine learning.分形维数:利用机器学习分析其作为脑肿瘤诊断神经影像生物标志物的潜力。
Front Physiol. 2023 Jul 17;14:1201617. doi: 10.3389/fphys.2023.1201617. eCollection 2023.
7
Impairment in reading negative social cues extends beyond the face in autism.自闭症患者对负面社会线索的识别障碍不仅局限于面部。
J Psychiatr Res. 2023 Aug;164:350-356. doi: 10.1016/j.jpsychires.2023.06.032. Epub 2023 Jun 26.
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Altered cortical gyrification, sulcal depth, and fractal dimension in the autism spectrum disorder comorbid attention-deficit/hyperactivity disorder than the autism spectrum disorder.与自闭症谱系障碍相比,自闭症谱系障碍合并注意缺陷多动障碍患者的皮质脑回形成、脑沟深度和分形维数存在改变。
Neuroreport. 2023 Feb 1;34(2):93-101. doi: 10.1097/WNR.0000000000001864. Epub 2022 Dec 17.
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Using fractal dimension analysis to assess the effects of normal aging and sex on subregional cortex alterations across the lifespan from a Chinese dataset.利用分形维数分析,从一个中国数据集评估正常衰老和性别对整个生命周期内亚区域皮质变化的影响。
Cereb Cortex. 2023 Apr 25;33(9):5289-5296. doi: 10.1093/cercor/bhac417.
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Sensory Perception in Autism: What Can We Learn?自闭症的感觉知觉:我们能从中学习到什么?
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