Epigenomic Dysregulation in Schizophrenia: In Search of Disease Etiology and Biomarkers

Abstract

Schizophrenia is a severe psychiatric disorder with a complex array of signs and symptoms that causes very significant disability in young people. While schizophrenia has a strong genetic component, with heritability around 80%, there is also a very significant range of environmental exposures and stressors that have been implicated in disease development and neuropathology, such as maternal immune infection, obstetric complications, childhood trauma and cannabis exposure. It is postulated that epigenetic factors, as well as regulatory non-coding RNAs, mediate the effects of these environmental stressors. In this review, we explore the most well-known epigenetic marks, including DNA methylation and histone modification, along with emerging RNA mediators of epigenomic state, including miRNAs and lncRNAs, and discuss their collective potential for involvement in the pathophysiology of schizophrenia implicated through the postmortem analysis of brain tissue. Given that peripheral tissues, such as blood, saliva, and olfactory epithelium have the same genetic composition and are exposed to many of the same environmental exposures, we also examine some studies supporting the application of peripheral tissues for epigenomic biomarker discovery in schizophrenia. Finally, we provide some perspective on how these biomarkers may be utilized to capture a signature of past events that informs future treatment.

Keywords: DNA methylation; Schizophrenia; histone modification; long non-coding RNA; miRNA.

Figure 1

Transcriptional and post-transcriptional regulation of gene expression. The four panels of this schematic are representative of the major epigenomic mechanisms’ associated active and inactive states in the nucleus and cytoplasm. Active chromatin (top left) characterized by an expanded or open euchromatin domain is established by the depletion of histone H3 lysing 27 trimethylation (K27(CH3)3 red) and an increase in histone H3 and H4 acetylation (green). This gives rise to mRNA transcription and non-coding RNA, such as primary miRNA transcripts. After interaction with the microprocessor complex (Drosha/DGCR8), the processed pre-miR are exported to the cytoplasm via exportin 5. mRNA is also exported to the cytoplasm (top right panel) where it becomes associated with ribosomes and translated into protein (blue). This is facilitated by the suppression of potentially active miRNA, which are sequestered through interaction with lincRNA and circRNA. Inactive chromatin (bottom left) is associated with cytosine methylation (red), which is particularly important at CpG islands and promoters where they can bind to MeCP2 which can recruit histone de-acetylases (HDAC). These reduce histone acetylation, which leads to greater compaction of chromatin into a state known as heterochromatin. LincRNA transcripts can also form a scaffold for the assembly of a ribonucleoprotein complex, including the PRC2, that directs the activity of histone methyltransferases (HMTs) that catalyze the trimethylation of histone H3 lysine 27. This modification also further enhances the contraction of chromatin into inactive heterochromatin. Post-transcriptional regulation of gene expression (bottom right panel) can also be facilitated by the maturation of pre-miRs through the activity of dicer. The mature miRNAs guide the RNA-induced silencing complex (comprising Argonaute proteins and other co-factors) to the 3′UTR of their cognate mRNA, causing translational repression and degradation through exonuclease activity.

Figure 2

Putative target gene interaction network graph generated using Ingenuity Pathway Analysis of miR-34 and miR-181 family miRNAs nodes within a simulated cell. Target mRNA interactions are denoted by green and blue edges for the seed sequences GGCAGUG and ACAUUCA using high stringency target predictions (TargetScan) and experimental observation for miR-34 and miR-181, respectively. Protein–protein interactions between miRNA targets are illustrated in pink. Gene ontologies related to neural functions are projected from the right side (grey lines) with the highest number of interactions at the top (axonal guidance signaling) and the least at the bottom (neuregulin signaling).