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

Author:

Luo Yuling12,Dong Debo34ORCID,Huang Huan12,Zhou Jingyu12,Zuo Xiaojun12,Hu Jian12,He Hui15,Jiang Sisi12,Duan Mingjun15,Yao Dezhong126,Luo Cheng126ORCID

Affiliation:

1. The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China , Chengdu , China

2. High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China , Chengdu , China

3. Key Laboratory of Cognition and Personality, Ministry of Education , Chongqing , China

4. Faculty of Psychology, Southwest University , Chongqing , China

5. Mental Health Center of Chengdu, The fourth people’s Hospital of Chengdu , Chengdu , China

6. Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences , Chengdu , China

Abstract

Abstract 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 striatum to the cortical core networks to extensive cortical and subcortical regions. Subsequently, we found that these robust multimodal neuroimaging abnormalities were associated with multiple neurobiological abnormalities, such as dopaminergic, glutamatergic, serotonergic, and GABAergic systems. Conclusions This work links transcriptome/neurotransmitters with reliable structural and functional signatures of brain abnormalities underlying disease effects in schizophrenia, which provides novel insight into the understanding of schizophrenia pathophysiology and targeted treatments.

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Chengdu Science and Technology Bureau

Natural Science Foundation of Sichuan Province

Publisher

Oxford University Press (OUP)

Subject

Psychiatry and Mental health

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