School of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China.
Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China.
CNS Neurosci Ther. 2024 Aug;30(8):e14906. doi: 10.1111/cns.14906.
Schizophrenia is characterized by alterations in resting-state spontaneous brain activity; however, it remains uncertain whether variations at diverse spatial scales are capable of effectively distinguishing patients from healthy controls. Additionally, the genetic underpinnings of these alterations remain poorly elucidated. We aimed to address these questions in this study to gain better understanding of brain alterations and their underlying genetic factors in schizophrenia.
A cohort of 103 individuals with diagnosed schizophrenia and 110 healthy controls underwent resting-state functional MRI scans. Spontaneous brain activity was assessed using the regional homogeneity (ReHo) metric at four spatial scales: voxel-level (Scale 1) and regional-level (Scales 2-4: 272, 53, 17 regions, respectively). For each spatial scale, multivariate pattern analysis was performed to classify schizophrenia patients from healthy controls, and a transcriptome-neuroimaging association analysis was performed to establish connections between gene expression data and ReHo alterations in schizophrenia.
The ReHo metrics at all spatial scales effectively discriminated schizophrenia from healthy controls. Scale 2 showed the highest classification accuracy at 84.6%, followed by Scale 1 (83.1%) and Scale 3 (78.5%), while Scale 4 exhibited the lowest accuracy (74.2%). Furthermore, the transcriptome-neuroimaging association analysis showed that there were not only shared but also unique enriched biological processes across the four spatial scales. These related biological processes were mainly linked to immune responses, inflammation, synaptic signaling, ion channels, cellular development, myelination, and transporter activity.
This study highlights the potential of multi-scale ReHo as a valuable neuroimaging biomarker in the diagnosis of schizophrenia. By elucidating the complex molecular basis underlying the ReHo alterations of this disorder, this study not only enhances our understanding of its pathophysiology, but also pave the way for future advancements in genetic diagnosis and treatment of schizophrenia.
精神分裂症的特征是静息状态下大脑自发性活动的改变；然而，目前尚不清楚不同空间尺度的变化是否能够有效地将患者与健康对照区分开来。此外，这些改变的遗传基础仍不清楚。我们旨在通过这项研究来解决这些问题，以更好地理解精神分裂症中大脑的改变及其潜在的遗传因素。
一项由 103 名确诊精神分裂症患者和 110 名健康对照者组成的队列接受了静息态功能磁共振成像扫描。使用局部一致性（ReHo）指标在四个空间尺度上评估自发性脑活动：体素水平（尺度 1）和区域水平（尺度 2-4：分别为 272、53、17 个区域）。对于每个空间尺度，我们进行了多变量模式分析，以将精神分裂症患者与健康对照组进行分类，并进行了转录组-神经影像学关联分析，以建立精神分裂症中基因表达数据与 ReHo 改变之间的联系。
所有空间尺度的 ReHo 指标都能有效地将精神分裂症与健康对照组区分开来。尺度 2 的分类准确率最高，为 84.6%，其次是尺度 1（83.1%）和尺度 3（78.5%），而尺度 4 的准确率最低（74.2%）。此外，转录组-神经影像学关联分析表明，四个空间尺度之间不仅存在共享的富集生物学过程，而且存在独特的富集生物学过程。这些相关的生物学过程主要与免疫反应、炎症、突触信号、离子通道、细胞发育、髓鞘形成和转运体活性有关。
这项研究强调了多尺度 ReHo 作为精神分裂症诊断有价值的神经影像学生物标志物的潜力。通过阐明该疾病 ReHo 改变的复杂分子基础，本研究不仅增强了我们对其病理生理学的理解，也为未来精神分裂症的遗传诊断和治疗提供了新的思路。
Zotero 插件
