Gene Regulatory Network of Dorsolateral Prefrontal Cortex: a Master Regulator Analysis of Major Psychiatric Disorders

• Published in: Molecular neurobiology 2020-03, Vol.57 (3), p.1305-1316
• Main Authors: Bristot, Giovana, De Bastiani, Marco Antônio, Pfaffenseller, Bianca, Kapczinski, Flávio, Kauer-Sant’Anna, Márcia
• Format: Article
• Language: English
• Subjects: Bioinformatics; Biomedical and Life Sciences; Biomedicine; Bipolar disorder; Bipolar Disorder - genetics; Brain - metabolism; Brain - pathology; Cell Biology; Cytoskeleton; Depressive Disorder, Major - genetics; Depressive Disorder, Major - pathology; Gene expression; Gene Regulatory Networks - genetics; Homeostasis; Humans; Immune response; Mental depression; Mental disorders; Neurobiology; Neurology; Neuronal-glial interactions; Neurosciences; Original Article; Pathophysiology; Phenotypes; Prefrontal cortex; Prefrontal Cortex - metabolism; Schizophrenia; Schizophrenia - genetics; Therapeutic applications; Transcription
• ISSN: 0893-7648; 1559-1182
• DOI: 10.1007/s12035-019-01815-2

Despite the strong genetic component of psychiatric disorders, traditional genetic studies have failed to find individual genes of large effect size. Thus, alternative methods, using bioinformatics, have been proposed to solve these biological puzzles. Of these, here we employ systems biology–based approaches to identify potential master regulators (MRs) of bipolar disorder (BD), schizophrenia (SZ), and major depressive disorder (MDD), their association with biological processes and their capacity to differentiate disorders’ phenotypes. High-throughput gene expression data was used to reconstruct standard human dorsolateral prefrontal cortex regulatory transcriptional network, which was then queried for regulatory units and MRs associated with the psychiatric disorders of interest. Furthermore, the activity status (active or repressed) of MR candidates was obtained and used in cluster analysis to characterize disease phenotypes. Finally, we explored the biological processes modulated by the MRs using functional enrichment analysis. Thirty-one, thirty-four, and fifteen MR candidates were identified in BD, SZ, and MDD, respectively. The activity state of these MRs grouped the illnesses in three clusters: MDD only, mostly BD, and a third one with BD and SZ. While BD and SZ share several biological processes related to ion transport and homeostasis, synapse, and immune function, SZ showed peculiar enrichment of processes related to cytoskeleton and neuronal structure. Meanwhile, MDD presented mostly processes related to glial development and fatty acid metabolism. Our findings suggest notable differences in functional enrichment between MDD and BD/SZ. Furthermore, similarities between BD and SZ may impose particular challenges in attempts to discriminate these pathologies based solely on their transcriptional profiles. Nevertheless, we believe that systems-oriented approaches are promising strategies to unravel the pathophysiology peculiarities underlying mental illnesses and reveal therapeutic targets.