Associating Multimodal Neuroimaging Abnormalities With the Transcriptome and Neurotransmitter Signatures in Schizophrenia

作者：Yuling Luo, Debo Dong, Huan Huang, Jingyu Zhou, Xiaojun Zuo, Jian Hu, Hui He, Sisi Jiang, Mingjun Duan, Dezhong Yao, Cheng Luo · 发表于：Schizophrenia Bulletin · 年份：2023 · DOI：10.1093/schbul/sbad047 · 被引用次数：27 · 研究领域：Functional Brain Connectivity Studies、Schizophrenia research and treatment、Neural dynamics and brain function

BACKGROUND AND HYPOTHESIS: Schizophrenia is a multidimensional disease. This study proposes a new research framework that combines multimodal meta-analysis and genetic/molecular architecture to solve the consistency in neuroimaging biomarkers of schizophrenia and whether these link to molecular genetics. STUDY DESIGN: We systematically searched Web of Science, PubMed, and BrainMap for the amplitude of low-frequency fluctuations (ALFF) or fractional ALFF, regional homogeneity, regional cerebral blood flow, and voxel-based morphometry analysis studies investigating schizophrenia. The pooled-modality, single-modality, and illness duration-dependent meta-analyses were performed using the activation likelihood estimation algorithm. Subsequently, Spearman correlation and partial least squares regression analyses were conducted to assess the relationship between identified reliable convergent patterns of multimodality and neurotransmitter/transcriptome, using prior molecular imaging and brain-wide gene expression. STUDY RESULTS: In total, 203 experiments comprising 10 613 patients and 10 461 healthy controls were included. Multimodal meta-analysis showed that brain regions of significant convergence in schizophrenia were mainly distributed in the frontotemporal cortex, anterior cingulate cortex, insula, thalamus, striatum, and hippocampus. Interestingly, the analyses of illness-duration subgroups identified aberrant functional and structural evolutionary patterns: Lines from the str...