Meta-analysis of transcriptional regulatory networks for lipid metabolism in neural cells from schizophrenia patients based on an open-source intelligence approach

There have been a number of reports about the transcriptional regulatory networks in schizophrenia. However, most of these studies were based on a specific transcription factor or a single dataset, an approach that is inadequate to understand the diverse etiology and underlying common characteristics of schizophrenia. Here we reconstructed and compared the transcriptional regulatory network for lipid metabolism enzymes using 15 public transcriptome datasets of neural cells from schizophrenia patients. Since many of the well-known schizophrenia-related SNPs are in enhancers, we reconstructed a network including enhancer-dependent regulation and found that 53.3 % of the total number of edges (7,577 pairs) involved regulation via enhancers. By examining multiple datasets, we found common and unique transcriptional modes of regulation. Furthermore, enrichment analysis of SNPs that were connected with genes in the transcriptional regulatory networks by eQTL suggested an association with hematological cell counts and some other traits/diseases, whose relationship to schizophrenia was either not or insufficiently reported in previous studies. Based on these results, we suggest that in future studies on schizophrenia, information on genotype, comorbidities and hematological cell counts should be included, along with the transcriptome, for a more detailed genetic stratification and mechanistic exploration of schizophrenia.

Automated summary

By reconstructing and comparing the transcriptional regulatory network for lipid metabolism enzymes using transcriptome datasets from schizophrenia patients, this study identifies common and unique transcriptional modes of regulation and reveals associations between SNPs and hematological cell counts as well as other traits/diseases that were not adequately reported in previous studies.