1Department of Psychosomatic Medicine, People’s Hospital of Deyang City, Deyang, Sichuan, China
2Department of Neurology, Jiading Branch of Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
3Department of Neurosurgery, the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
4Department of Family and Community Health, School of Nursing, Health Sciences Center, West Virginia University, Morgantown, WV, USA
5Tianjin Mental Health Center, Tianjin, China
6Shengli Clinical Medical College of Fujian Medical University, Fujian Medical University
7Beijing Huilongguan Hospital, Peking University Huilongguan Clinical School of Medicine, Beijing, China
8Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
The aim of this study is to provide a comprehensive overview of spatial multiomics analysis, including its definition, processes, applications, significance and relevant research in psychiatric disorders. To achieve this, a literature search was conducted, focusing on three major spatial omics techniques and their application to three common psychiatric disorders: Alzheimer’s disease (AD), schizophrenia, and autism spectrum disorders. Spatial genomics analysis has revealed specific genes associated with neuropsychiatric disorders in certain brain regions. Spatial transcriptomics analysis has identified genes related to AD in areas such as the hippocampus, olfactory bulb, and middle temporal gyrus. It has also provided insight into the response to AD in mouse models. Spatial proteogenomics has identified autism spectrum disorder (ASD)-risk genes in specific cell types, while schizophrenia risk loci have been linked to transcriptional signatures in the human hippocampus. In summary, spatial multiomics analysis offers a powerful approach to understand AD pathology and other psychiatric diseases, integrating multiple data modalities to identify risk genes for these disorders. It is valuable for studying psychiatric disorders with high or low cellular heterogeneity and provides new insights into the brain nucleome to predict disease progression and aid diagnosis and treatment.
Keywords: Spatial Genomics; Spatial Transcriptomics; Spatial Proteogenomics; Alzheimer’s Disease; Schizophrenia; Autism Spectrum Disorder
Xingguang Luo, Bin Chen., et al. Spatial Multiomics Analysis in Psychiatric Disorders. EC Psychology and Psychiatry 12.6 (2023): 01-05.
© 2023 Xingguang Luo, Bin Chen., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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