Spatial Multiomics Analysis in Psychiatric Disorders.

Abstract

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.