Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence
1.3 PHYSICAL SCIENCES
Schizophrenia is a debilitating condition that affects 1% of the population, causes significant hardship and though there are treatments available they are characterised by several limitations. It is a complex mental disorder where some individuals show mild subclinical cognitive symptoms before psychosis onset in adolescence. The treatments available only target a portion of the symptoms and although extensive research has been conducted, a comprehensive understanding of the nature of schizophrenia remains elusive. Unlike other neurodevelopmental disorders, schizophrenia symptoms do not typically present themselves until adolescence. This study aimed to discover gene co-expression networks at multiple developmental stages to identify candidate therapeutic targets to better treat and manage schizophrenia.
Recent genome-wide association studies have identified 145 genetic loci associated with schizophrenia. Allen Brain Atlas’s BrainSpan resource provides brain development data from neurotypical brains. Using this resource it was possible to study the gene expression of 316 schizophrenia-associated genes, identified previously in a large-scale GWAS, across each of the developmental stages available in the Allen Brain Atlas. K means Clustering and a systems biology approach (WGCNA) was applied to these schizophrenia-associated genes at each developmental stage where modules within networks were created by grouping coexpressed genes. To facilitate biological interpretation of these modules co-expressed genes were visualised using Cytoscape and gene ontology pathway enrichment analysis was applied.
We identified 21 hub genes using WGCNA. Of the 316 schizophrenia-associated genes, 27 modules were identified and 3 hub genes GPR52, INA, SATB2 were common in multiple developmental stages. Our results suggest that GPR52, INA, SATB2 represent candidate genes for future evaluation of their potential as therapeutic targets of schizophrenia. Additional hub genes included TRANK1 and ALMS1, genes which were previously identified as expression quantitative trait loci. Taken together our results add further evidence that these genes could be good candidates for further research as they may regulate several schizophrenia-related genes in their respective modules. Finally, our enrichment analysis implicated a role for positive regulation of macrophage proliferation and cellular response to catecholamine stimulus, and cellular response to diacyl bacterial lipopeptide at each developmental stage. The immune system and catecholamines, including dopamine, have long been associated with schizophrenia and our results provide further support for these hypotheses.
Kelly, K. (2021). Investigating the role of Schizophrenia-associated gene expression in the developing human brain using Machine Learning. Technological University Dublin. DOI: 10.21427/R4FM-9950