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Unraveling multi-scale neuroimaging biomarkers and molecular foundations for schizophrenia: A combined multivariate pattern analysis and transcriptome-neuroimaging association study

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机构: [1]School of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China [2]Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China [3]Department of Radiology, School of Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, China [4]Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China [5]Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
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关键词: gene expression multiscale analysis multivariate pattern analysis regional homogeneity schizophrenia

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AimsSchizophrenia 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.MethodsA 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.ResultsThe 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.ConclusionsThis 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. Our study highlights the potential of multi-scale ReHo analysis as a valuable neuroimaging biomarker in the diagnosis of schizophrenia. Furthermore, we observed spatial scale-dependent differences in enriched biological processes in the brain associated with schizophrenia. These related genes were mainly linked to immune responses, inflammation, synaptic signaling, ion channels, cellular development, myelination, and transporter activity.image

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出版当年[2023]版:
大类 | 1 区 医学
小类 | 2 区 神经科学 2 区 药学
最新[2023]版:
大类 | 1 区 医学
小类 | 2 区 神经科学 2 区 药学
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出版当年[2022]版:
Q1 NEUROSCIENCES Q1 PHARMACOLOGY & PHARMACY
最新[2023]版:
Q1 PHARMACOLOGY & PHARMACY Q1 NEUROSCIENCES

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第一作者机构: [1]School of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China
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