Elsevier

Journal of Psychiatric Research

Volume 82, November 2016, Pages 58-67
Journal of Psychiatric Research

The microRNA network is altered in anterior cingulate cortex of patients with unipolar and bipolar depression

https://doi.org/10.1016/j.jpsychires.2016.07.012Get rights and content

Abstract

MicroRNAs (miRNAs) are small, non-coding RNAs acting as post-transcriptional regulators of gene expression. Though implicated in multiple CNS disorders, miRNAs have not been examined in any psychiatric disease state in anterior cingulate cortex (AnCg), a brain region centrally involved in regulating mood. We performed qPCR analyses of 29 miRNAs previously implicated in psychiatric illness (major depressive disorder (MDD), bipolar disorder (BP) and/or schizophrenia (SZ)) in AnCg of patients with MDD and BP versus controls. miR-132, miR-133a and miR-212 were initially identified as differentially expressed in BP, miR-184 in MDD and miR-34a in both MDD and BP (although none survived multiple correction testing and must be considered preliminary). In silico target prediction algorithms identified putative targets of differentially expressed miRNAs. Nuclear Co-Activator 1 (NCOA1), Nuclear Co-Repressor 2 (NCOR2) and Phosphodiesterase 4B (PDE4B) were selected based upon predicted targeting by miR-34a (with NCOR2 and PDE4B both targeted by miR-184) and published relevance to psychiatric illness. Luciferase assays identified PDE4B as a target of miR-34a and miR-184, while NCOA1 and NCOR2 were targeted by miR-34a and 184, respectively. qPCR analyses were performed to determine whether changes in miRNA levels correlated with mRNA levels of validated targets. NCOA1 showed an inverse correlation with miR-34a in BP, while NCOR2 demonstrated a positive correlation. In sum, this is the first study to demonstrate miRNA changes in AnCg in psychiatric illness and validate miR-34a as differentially expressed in CNS in MDD. These findings support a mechanistic role for miRNAs in the regulation of stress-responsive genes disrupted in psychiatric illness.

Introduction

Known as melancholia at the time of Hippocrates, ‘depression’ is a general term that encompasses a large number of mood disorders. Two of these particularly debilitating disorders—major depressive disorder (MDD, or unipolar depression) and bipolar disorder (BP; bipolar depression)—are also extremely common, with a lifetime prevalence of 16.6% and 3.9%, respectively (Kessler et al., 2005). Though a genetic component has been established (due in part to a high degree of heritability (Bierut et al., 1999, Burton et al., 2007, Lohoff, 2010, McGuffin et al., 2003, Sklar et al., 2011, Smoller and Finn, 2003)), the genomic architecture of these disorders remains poorly understood.

In recent years, however, microRNAs (miRNAs)—small, 21–23 nt RNAs that canonically act as post-transcriptional regulators of gene expression—have become an increasing focus for understanding CNS processes. Greater than 40% of all protein-coding transcripts are predicted to be regulated by miRNAs (Tan et al., 2009, Xie et al., 2005). MiRNAs are also highly enriched within the CNS, with greater than two-thirds of identified miRNAs expressed in brain (Bak et al., 2008, Cao et al., 2006, Sempere et al., 2004). MiRNAs are also key governors of CNS processes at both the cellular level (e.g. synaptic plasticity, neuronal differentiation and neuronal migration (Cui et al., 2012, Makeyev et al., 2007, Morgado et al., 2014, Schratt et al., 2006)) and the systems level, with miRNAs linked to the regulation of HPA axis glucocorticoid negative feedback and complex behaviors such as responses to both acute and chronic stress as well as mood and anxiety (Bahi et al., 2014, Haramati et al., 2011, Honda et al., 2013, Katsuura et al., 2012, Muinos-Gimeno et al., 2011, Vreugdenhil et al., 2009).

The role of miRNAs in the regulation of stress responses is of particular interest given that chronic stress is not only a precipitant of mood and affective disorders (Breslau and Davis, 1986, Ilgen and Hutchison, 2005) but HPA axis disruption is one of the most commonly observed pathophysiologies in MDD patients, with symptomatic severity correlating with extent of hypercortisolemia (Gibbons and Mc, 1962, Vythilingam et al., 2004). Intriguingly, a number of studies have directly demonstrated dysregulation of the miRNA regulatory network in patients with a variety of mood and affective disorders, with the vast majority focusing on schizophrenia (SZ) (Beveridge et al., 2010, Beveridge et al., 2008, Kim et al., 2010, Miller et al., 2012, Moreau et al., 2011, Perkins et al., 2007, Santarelli et al., 2011, Shi et al., 2012, Smalheiser et al., 2014, Wan et al., 2015). Absent from these studies, however, has been analysis of the anterior cingulate cortex (AnCg), a brain region centrally involved in the regulation of mood, affect and cognition (Drevets et al., 2008, Ebert and Ebmeier, 1996, Mayberg et al., 1999, Posner and DiGirolamo, 1998). Alterations in AnCg function have been increasingly linked to mood disorders with AnCg activity previously demonstrated to differentiate patients with unipolar versus bipolar depression (Diler et al., 2014) and also to predict successful pharmaceutical and cognitive treatment response (Fujino et al., 2015, Mulert et al., 2007, Pizzagalli et al., 2001, Salvadore et al., 2009). Further work has also established alterations in various systems within AnCg in MDD and BP disorders, including dysregulation in the fibroblast growth factor (FGF) system and clock genes (Bunney et al., 2015, Cheng et al., 2007, Evans et al., 2004).

In the present study we assessed miRNA expression in the AnCg of both MDD and BP patients compared to controls. As miRNAs exert their regulatory effects by targeting mRNA transcripts, we employed bioinformatics approaches to identify mRNA targets of miRNAs whose expression varied due to disease and validated several mRNAs as direct targets. Finally, we examined the steady-state levels of a subset of validated mRNA targets and identified two that vary as a function of affective disease.

Section snippets

Postmortem brain tissue and RNA extraction

RNA samples derived from human post-mortem AnCg tissue were provided by the Pritzker Neuropsychiatric Research Consortium. The initial acquisition of tissue, microdissection of AnCg and subsequent RNA extraction that generated these samples is described in detail in (Evans et al., 2003). Briefly, brains were extracted during autopsy and sliced into coronal slabs approximately 0.75 cm thick. Slabs were then snap-frozen and stored at −80° C until subsequent dissections. Anterior cingulate cortex

Differential expression of a subset of miRNAs in AnCg of patients with MDD or BP disorder

Following qPCR detection 3 miRNAs—miR-33a, miR-144 and miR-431*—were excluded from analysis due to high variability among technical replicates and cycle threshold values > 30. After exclusion, 26 miRNAs were examined for differential expression in BP and MDD cohorts versus controls. Of these, 5 miRNAs—miR-132, miR-133a and miR-212 in the BP cohort; miR-184 in the MDD cohort, and miR-34a shared between cohorts—exhibited raw p-values < 0.05 (Fig. 1) (although none passed multiple correction

Discussion

Given their enrichment in the brain, their regulation of key CNS processes, their widespread regulation of protein-coding transcripts and their dysregulation in a number of illnesses, miRNAs are uniquely positioned to play a key role in the pathology of psychiatric illness. In this study we examined the expression of 26 miRNAs in the AnCg of MDD and BP patients versus controls. From this, we identified 5 miRNAs—3 in BP, 1 in MDD and 1 shared across both cohorts—that were differentially

Role of contributors

Joshua A Azevedo: study design, data analysis, manuscript drafting and final revision of manuscript.

Bradley S Carter: early-stage technical feasibility, final revision of manuscript.

Fan Meng: bioinformatics analysis, final revision of manuscript.

David L Turner: bioinformatics analysis, final revision of manuscript.

Manhong Dai: bioinformatics analysis, final revision of manuscript.

Alan F Schatzberg: overall study design and post-mortem sample procurement, final revision of manuscript.

Jack D

Role of the funding sources

This work was supported by NIH Grant R21 MH083175 (RCT). J. Azevedo was supported by NIH T-32-NS076401. This work was also funded by the Pritzker Neuropsychiatric Disorders Research Consortium, which is supported by the Pritzker Neuropsychiatric Disorders Research Fund L.L.C. A shared intellectual property agreement exists between this philanthropic fund and the University of Michigan, Stanford University, the Weill Medical College of Cornell University, the University of California at Irvine,

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgement

This work was supported by NIH Grant R21 MH083175 (RCT). J. Azevedo was supported by NIH T-32-NS076401. This work was also funded by the Pritzker Neuropsychiatric Disorders Research Consortium, which is supported by the Pritzker Neuropsychiatric Disorders Research Fund L.L.C. A shared intellectual property agreement exists between this philanthropic fund and the University of Michigan, Stanford University, the Weill Medical College of Cornell University, the University of California at Irvine,

References (95)

  • J. Fujino et al.

    Anterior cingulate volume predicts response to cognitive behavioral therapy in major depressive disorder

    J. Affect Disord.

    (2015)
  • J.L. Gibbons et al.

    Plasma cortisol in depressive illness

    J. Psychiatr. Res.

    (1962)
  • M.A. Ilgen et al.

    A history of major depressive disorder and the response to stress

    J. Affect Disord.

    (2005)
  • S. Katsuura et al.

    MicroRNAs miR-144/144* and miR-16 in peripheral blood are potential biomarkers for naturalistic stress in healthy Japanese medical students

    Neurosci. Lett.

    (2012)
  • A.H. Kim et al.

    MicroRNA expression profiling in the prefrontal cortex of individuals affected with schizophrenia and bipolar disorders

    Schizophr. Res.

    (2010)
  • B.P. Lewis et al.

    Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets

    Cell

    (2005)
  • K.J. Livak et al.

    Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method

    Methods

    (2001)
  • E.V. Makeyev et al.

    The MicroRNA miR-124 promotes neuronal differentiation by triggering brain-specific alternative pre-mRNA splicing

    Mol. Cell.

    (2007)
  • M.P. Moreau et al.

    Altered microRNA expression profiles in postmortem brain samples from individuals with schizophrenia and bipolar disorder

    Biol. Psychiatry

    (2011)
  • M. Muinos-Gimeno et al.

    Human microRNAs miR-22, miR-138-2, miR-148a, and miR-488 are associated with panic disorder and regulate several anxiety candidate genes and related pathways

    Biol. Psychiatry

    (2011)
  • X.R. Qi et al.

    Aberrant stress hormone receptor balance in the human prefrontal cortex and hypothalamic paraventricular nucleus of depressed patients

    Psychoneuroendocrinology

    (2013)
  • C.S. Ruan et al.

    Mice deficient for wild-type p53-induced phosphatase 1 display elevated anxiety- and depression-like behaviors

    Neuroscience

    (2015)
  • G. Salvadore et al.

    Increased anterior cingulate cortical activity in response to fearful faces: a neurophysiological biomarker that predicts rapid antidepressant response to ketamine

    Biol. Psychiatry

    (2009)
  • D.M. Santarelli et al.

    Upregulation of dicer and microRNA expression in the dorsolateral prefrontal cortex Brodmann area 46 in schizophrenia

    Biol. Psychiatry

    (2011)
  • W. Shi et al.

    Aberrant expression of serum miRNAs in schizophrenia

    J. Psychiatr. Res.

    (2012)
  • S.J. Tsai et al.

    Haplotype analysis of single nucleotide polymorphisms in the vascular endothelial growth factor (VEGFA) gene and antidepressant treatment response in major depressive disorder

    Psychiatry Res.

    (2009)
  • M. Vythilingam et al.

    Hippocampal volume, memory, and cortisol status in major depressive disorder: effects of treatment

    Biol. Psychiatry

    (2004)
  • R.M. Walker et al.

    Preliminary investigation of miRNA expression in individuals at high familial risk of bipolar disorder

    J. Psychiatr. Res.

    (2015)
  • J.Y. Yu et al.

    MicroRNA miR-124 regulates neurite outgrowth during neuronal differentiation

    Exp. Cell Res.

    (2008)
  • P. Yuan et al.

    Phosphodiesterase 4 inhibitors enhance sexual pleasure-seeking activity in rodents

    Pharmacol. Biochem. Behav.

    (2011)
  • M. Bak et al.

    MicroRNA expression in the adult mouse central nervous system

    RNA

    (2008)
  • S. Bavamian et al.

    Dysregulation of miR-34a links neuronal development to genetic risk factors for bipolar disorder

    Mol. Psychiatry

    (2015)
  • H. Benjamini et al.

    Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

    J Royal Stat. Soc. Series B

    (1995)
  • D. Berent et al.

    Vascular endothelial growth factor A gene expression level is higher in patients with major depressive disorder and not affected by cigarette smoking, hyperlipidemia or treatment with statins

    Acta Neurobiol. Exp. (Wars)

    (2014)
  • W. Berrettini

    Evidence for shared susceptibility in bipolar disorder and schizophrenia

    Am. J. Med. Genet. C Semin. Med. Genet.

    (2003)
  • D. Betel et al.

    Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites

    Genome Biol.

    (2010)
  • N.J. Beveridge et al.

    Schizophrenia is associated with an increase in cortical microRNA biogenesis

    Mol. Psychiatry

    (2010)
  • N.J. Beveridge et al.

    Dysregulation of miRNA 181b in the temporal cortex in schizophrenia

    Hum. Mol. Genet.

    (2008)
  • L.J. Bierut et al.

    Major depressive disorder in a community-based twin sample: are there different genetic and environmental contributions for men and women?

    Arch. Gen. Psychiatry

    (1999)
  • N. Breslau et al.

    Chronic stress and major depression

    Arch. Gen. Psychiatry

    (1986)
  • J.A. Broderick et al.

    Argonaute protein identity and pairing geometry determine cooperativity in mammalian RNA silencing

    RNA

    (2011)
  • B.G. Bunney et al.

    Circadian dysregulation of clock genes: clues to rapid treatments in major depressive disorder

    Mol. Psychiatry

    (2015)
  • P.R. Burton et al.

    Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls

    Nature

    (2007)
  • X. Cao et al.

    Noncoding RNAs in the mammalian central nervous system

    Annu. Rev. Neurosci.

    (2006)
  • Y. Cui et al.

    MiR-125b orchestrates cell proliferation, differentiation and migration in neural stem/progenitor cells by targeting nestin

    BMC Neurosci.

    (2012)
  • R.S. Diler et al.

    Differential anterior cingulate activity during response inhibition in depressed adolescents with bipolar and unipolar major depressive disorder

    J. Can. Acad. Child. Adolesc. Psychiatry

    (2014)
  • W.C. Drevets et al.

    The subgenual anterior cingulate cortex in mood disorders

    CNS Spectr.

    (2008)
  • Cited by (61)

    View all citing articles on Scopus
    View full text