OPEN
Citation: Transl Psychiatry (2015) 5, e678; doi:10.1038/tp.2015.159
www.nature.com/tp
ORIGINAL ARTICLE
Genome-wide analysis implicates microRNAs and their target
genes in the development of bipolar disorder
AJ Forstner1,2,50, A Hofmann1,2,50, A Maaser1,2, S Sumer3, S Khudayberdiev3, TW Mühleisen1,2,4, M Leber5, TG Schulze6, J Strohmaier7,
F Degenhardt1,2, J Treutlein7, M Mattheisen8,9, J Schumacher1,2, R Breuer7, S Meier7,10, S Herms1,2,11, P Hoffmann1,2,4,11, A Lacour12,
SH Witt7, A Reif13, B Müller-Myhsok14,15,16, S Lucae14, W Maier17, M Schwarz18, H Vedder18, J Kammerer-Ciernioch19, A Pfennig20,
M Bauer20, M Hautzinger21, S Moebus22, L Priebe1,2, S Sivalingam1,2, A Verhaert1,2, H Schulz23, PM Czerski24, J Hauser24, J Lissowska25,
N Szeszenia-Dabrowska26, P Brennan27, JD McKay28, A Wright29,30, PB Mitchell29,30, JM Fullerton31,32, PR Schofield31,32,
GW Montgomery33, SE Medland33, SD Gordon33, NG Martin33, V Krasnov34, A Chuchalin35, G Babadjanova35, G Pantelejeva36,
LI Abramova36, AS Tiganov36, A Polonikov37, E Khusnutdinova38,39, M Alda40,41, C Cruceanu42,43,44, GA Rouleau42, G Turecki43,44,45,
C Laprise46, F Rivas47, F Mayoral47, M Kogevinas48, M Grigoroiu-Serbanescu49, P Propping1, T Becker5,12, M Rietschel7, S Cichon1,2,4,11,
G Schratt3 and MM Nöthen1,2
Bipolar disorder (BD) is a severe and highly heritable neuropsychiatric disorder with a lifetime prevalence of 1%. Molecular genetic
studies have identified the first BD susceptibility genes. However, the disease pathways remain largely unknown. Accumulating
evidence suggests that microRNAs, a class of small noncoding RNAs, contribute to basic mechanisms underlying brain
development and plasticity, suggesting their possible involvement in the pathogenesis of several psychiatric disorders, including
BD. In the present study, gene-based analyses were performed for all known autosomal microRNAs using the largest genome-wide
association data set of BD to date (9747 patients and 14 278 controls). Associated and brain-expressed microRNAs were then
investigated in target gene and pathway analyses. Functional analyses of miR-499 and miR-708 were performed in rat hippocampal
neurons. Ninety-eight of the six hundred nine investigated microRNAs showed nominally significant P-values, suggesting that BDassociated microRNAs might be enriched within known microRNA loci. After correction for multiple testing, nine microRNAs
showed a significant association with BD. The most promising were miR-499, miR-708 and miR-1908. Target gene and pathway
analyses revealed 18 significant canonical pathways, including brain development and neuron projection. For miR-499, four
Bonferroni-corrected significant target genes were identified, including the genome-wide risk gene for psychiatric disorder CACNB2.
First results of functional analyses in rat hippocampal neurons neither revealed nor excluded a major contribution of miR-499 or
miR-708 to dendritic spine morphogenesis. The present results suggest that research is warranted to elucidate the precise
involvement of microRNAs and their downstream pathways in BD.
Translational Psychiatry (2015) 5, e678; doi:10.1038/tp.2015.159; published online 10 November 2015
1
Institute of Human Genetics, University of Bonn, Bonn, Germany; 2Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany; 3Institute of Physiological
Chemistry, Philipps-University Marburg, Marburg, Germany; 4Institute of Neuroscience and Medicine, Research Center Juelich, Juelich, Germany; 5Institute for Medical Biometry,
Informatics and Epidemiology, University of Bonn, Bonn, Germany; 6Institute of Psychiatric Phenomics and Genomics, Ludwig-Maximilians-University Munich, Munich, Germany;
7
Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim/University of Heidelberg, Heidelberg, Germany; 8Department
of Biomedicine, Aarhus University, Aarhus, Denmark; 9Institute for Genomics Mathematics, University of Bonn, Bonn, Germany; 10National Center Register-Based Research, Aarhus
University, Aarhus, Denmark; 11Division of Medical Genetics, Department of Biomedicine, University of Basel, Basel, Switzerland; 12German Center for Neurodegenerative
Diseases, Bonn, Germany; 13Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt am Main, Frankfurt, Germany; 14Max Planck
Institute of Psychiatry, Munich, Germany; 15Munich Cluster for Systems Neurology (SyNergy), Munich, Germany; 16University of Liverpool, Institute of Translational Medicine,
Liverpool, UK; 17Department of Psychiatry, University of Bonn, Bonn, Germany; 18Psychiatric Center Nordbaden, Wiesloch, Germany; 19Center of Psychiatry Weinsberg, Weinsberg,
Germany; 20Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, TU Dresden, Dresden, Germany; 21Department of Psychology, Clinical Psychology
and Psychotherapy, Eberhard Karls University Tübingen, Tübingen, Germany; 22Institute of Medical Informatics, Biometry and Epidemiology, University Duisburg-Essen, Essen,
Germany; 23Cologne Center for Genomics, University of Cologne, Cologne, Germany; 24Department of Psychiatry, Laboratory of Psychiatric Genetics, Poznan University of Medical
Sciences, Poznan, Poland; 25Department of Cancer Epidemiology and Prevention, Maria Sklodowska-Curie Memorial Cancer Centre and Institute of Oncology Warsaw, Warsaw,
Poland; 26Department of Epidemiology, Nofer Institute of Occupational Medicine, Lodz, Poland; 27Genetic Epidemiology Group, International Agency for Research on Cancer,
Lyon, France; 28Genetic Cancer Susceptibility Group, International Agency for Research on Cancer, Lyon, France; 29School of Psychiatry, University of New South Wales, Randwick,
NSW, Australia; 30Black Dog Institute, Prince of Wales Hospital, Randwick, NSW, Australia; 31Neuroscience Research Australia, Sydney, NSW, Australia; 32School of Medical Sciences,
Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia; 33Queensland Institute of Medical Research, Brisbane, QLD, Australia; 34Moscow Research Institute of
Psychiatry, Moscow, Russian Federation; 35Institute of Pulmonology, Russian State Medical University, Moscow, Russian Federation; 36Russian Academy of Medical Sciences,
Mental Health Research Center, Moscow, Russian Federation; 37Department of Biology, Medical Genetics and Ecology, Kursk State Medical University, Kursk, Russian Federation;
38
Institute of Biochemistry and Genetics, Ufa Scientific Center of Russian Academy of Sciences, Ufa, Russian Federation; 39Department of Genetics and Fundamental Medicine,
Bashkir State University, Ufa, Russian Federation; 40Department of Psychiatry, Dalhousie University, Halifax, NS, Canada; 41National Institute of Mental Health, Klecany, Czech
Republic; 42Montreal Neurological Institute, McGill University, Montreal, QC, Canada; 43Department of Human Genetics, McGill University, Montreal, QC, Canada; 44McGill Group
for Suicide Studies and Douglas Research Institute, Montreal, QC, Canada; 45Department of Psychiatry, McGill University, Montreal, QC, Canada; 46Département des sciences
fondamentales, Université du Québec à Chicoutimi (UQAC), Chicoutimi, QC, Canada; 47Department of Psychiatry, Hospital Regional Universitario, Biomedical Institute of Malaga,
Malaga, Spain; 48Center for Research in Environmental Epidemiology, Barcelona, Spain and 49Biometric Psychiatric Genetics Research Unit, Alexandru Obregia Clinical Psychiatric
Hospital, Bucharest, Romania. Correspondence: Professor MM Nöthen, Institute of Human Genetics, University of Bonn, Sigmund-Freud-Strasse 25, Bonn 53127, Germany.
E-mail: markus.noethen@uni-bonn.de
50
These authors contributed equally to this work.
Received 20 August 2015; accepted 7 September 2015
microRNAs in bipolar disorder
AJ Forstner et al
2
INTRODUCTION
Bipolar disorder (BD) is a severe neuropsychiatric disorder with an
estimated lifetime prevalence of 1%.1 BD is characterized by
recurrent episodes of mania and depression, and shows a heritability of ~ 70%.2 Molecular genetic candidate studies and—more
recently—genome-wide association studies (GWAS) have identified the first BD susceptibility genes.3–7 However, the disease
pathways and underlying regulatory networks remain largely
unknown.8
Accumulating evidence suggests that microRNAs (miRNAs) are
implicated in the biological pathways that regulate brain development and synaptic plasticity.9,10 This in turn suggests their
possible involvement in the pathogenesis of several psychiatric
disorders,11,12 including BD.13,14 Studies of the post-mortem brain
tissue of BD patients have demonstrated altered miRNA expression profiles in the prefrontal cortex.13,14
The miRNAs are a class of 21–25-nucleotide small noncoding
RNAs. In the nucleus they are transcribed by RNA polymerase II to
primary miRNA (pri-miRNA) transcripts, which are double-stranded
stem loop structures comprising 100–1000 nucleotides.15,16
Approximately 50% of all vertebrate miRNAs are processed from
the introns of protein-coding genes or from genes encoding other
noncoding RNA classes. However, miRNAs can also be encoded in
intergenic regions.17
The pri-miRNAs are then processed by the Drosha-DGCR8
complex to precursor miRNAs.18,19 These precursor miRNAs are
60–70 nucleotides in length. The precursor miRNAs are exported
to the cytoplasm, where they are cleaved into ∼ 20-base pair (bp)
mature miRNAs by the Dicer enzyme.16,20 The mature miRNAs are
incorporated into the RNA-induced silencing complex, which then
targets distinct sets of messenger RNAs (mRNAs).21
The miRNAs control the expression of their target genes by
binding to target sites within the mRNAs, typically in their 3′
untranslated regions.22,23 A region of 2–7 or 2–8 consecutive
nucleotides from the 5′ end of the mature miRNA forms the seed
region, which is crucial for the recognition of the target genes.24 In
general, each miRNA controls up to several hundred target
mRNAs, whereas one mRNA target can be subjected to synergistic
regulation by multiple miRNAs.25,26 In consequence, miRNAs
integrate different intracellular signals and regulate a number of
signaling pathways.27,28 Interestingly, the miRNA regulatory effect
itself has been shown to be a heritable trait in humans.29
The hypothesis that miRNAs are implicated in BD is also
supported by the results of the largest GWAS of BD to date.6 In
this study, a single-nucleotide polymorphism (SNP) in an
intergenic region flanking MIR2113 on chromosome 6q16.1 was
the eighth strongest finding. However, no significant enrichment
of BD-associated genes within the known or predicted targets of
MIR2113 was observed.6
Several studies have investigated the role of single miRNAs in
the development of psychiatric disorder,30–32 including BD.33
However, to our knowledge, no systematic, genome-wide analysis
of miRNA-coding genes has yet been performed. The aim of the
present study was, thus, to determine whether common variants
at any of the known miRNA loci contribute to the development of BD.
MATERIALS AND METHODS
Sample description
The gene-based tests were performed using data from our previous GWAS
of BD (9747 patients and 14 278 controls).6 This GWAS data set combined
data from Canada, Australia and four European countries (MooDS) with the
GWAS results of the multinational Psychiatric Genomics Consortium
(PGC).3 The study was approved by the respective local Ethics Committees.
Written informed consent was obtained from all participants.6
Translational Psychiatry (2015), 1 – 8
Genome-wide miRNA association analysis
For the gene-based analyses, a set-based testing approach adapted from
the versatile gene-based test for GWAS34 was used. This algorithm is
obtainable upon request. The chromosomal positions of all miRNAs
(n = 718) were obtained from miRBase release 13.0.35 This release contains
a high confidence set of miRNAs for which detailed information about
miRNA function and predicted target genes is available. Using the
summary statistics, gene-wide P-values were calculated for all 636
autosomal miRNAs and their ± 20 kilobase (kb) flanking sequences.
Twenty-seven of these miRNA loci contained no common SNP. Therefore,
gene-wide P-values were obtained for 609 miRNAs.
The applied statistical algorithm is described in more detail in the article
by Liu et al.34 Briefly, SNPs within these boundaries were grouped together,
and a set-based test statistic was calculated as the sum of the χ2 one
degree of freedom association P-values within the miRNA. The test statistic
was compared with simulated test statistics from the multivariate normal
distribution. An empirical miRNA-based P-value was calculated as the
proportion of simulated test statistics above the observed test statistic. For
the purposes of the present study, the 10% most significant SNPs for each
miRNA were summarized. The calculated gene-based P-values were
Bonferroni-corrected for multiple testing according to the number of
investigated miRNAs (n = 609).
As different reference panels were used for the imputation of the
MooDS and PGC genotype data (1000 Genomes Project, February 2012
release, and HapMap phase 2 CEU, respectively), we used simulated test
statistics on the basis of an intermarker linkage disequilibrium (LD)
structure as derived from the HapMap phase 2 population genotypes.
However, for miRNAs that showed a significant association with BD after
Bonferroni correction, we also calculated gene-based tests based on 1000
Genomes Project phase 3 population genotypes.
Inflation of the observed and expected P-values for different SNP
subcategories (SNPs in miRNA loci, SNPs in genes and intergenic SNPs) was
defined as the degree of deviation from the expected uniform distribution
in the quantile–quantile (Q–Q) plot and tested for significance using
Fisher’s exact test (one-sided) for different P-value thresholds. Only LDpruned SNPs (r2 o 0.8) were used for the enrichment analysis.
Follow-up of miRNA association results—regional association plots
A window-based approach that included common variants in miRNAs and
flanking sequences was applied. To determine whether the signal was
associated with any of the miRNAs of interest, visual inspection of the
regional association plots was performed.
Regional association results from our BD GWAS6 were plotted for all
associated miRNAs and their ± 500-kb flanking regions using LocusZoom.36
A signal was considered miRNA-associated if the top SNP of the region was
located at, or was in high or moderate LD (r240.6) with, the miRNA locus.
Follow-up of miRNA association results—miRNA brain expression
To investigate expression of the associated miRNAs in the human brain,
data from a recent study of miRNA expression patterns in the developing
human brain were re-analyzed.37 A miRNA was defined as showing brain
expression if it had a total read count of 4120 across all investigated
samples.37
In addition, miRNA expression was measured in rat cortical neurons and
forebrain. All procedures involving animals followed the guidelines of the
German Animal Protection Legislation and the experiments were approved
by the Local Committee for Animal Health (RP Gießen). Total RNA was
isolated from the postnatal day 15 rat forebrain or synaptosomes, as
described elsewhere.38 Briefly, the total RNA from the forebrain of
postnatal day-15 Sprague–Dawley rat pups was extracted using peqGOLD
TriFast reagent (Peqlab, Erlangen, Germany) in accordance with the
manufacturer’s instructions. Small RNA libraries were constructed and
sequenced at the EMBL genomic core facility (Heidelberg, Germany) using
the HiSeq platform (Illumina, San Diego, CA, USA). The web-based software
MiRanalyzer was used to determine miRNA expression levels (http://
bioinfo2.ugr.es/miRanalyzer/miRanalyzer.php.).39
miRNA target gene analysis
Targets of the associated miRNAs 499, 708 and 1908 were obtained from
TargetScan (Release 6.2).40 The Allen human brain atlas (http://www.brainmap.org/)41 was consulted to determine whether predicted target genes
are expressed in the human brain. Target genes were considered brain-
microRNAs in bipolar disorder
AJ Forstner et al
3
expressed if they had shown expression in the hippocampal formation in
at least four of the six donor brains. Gene-based P-values for all brainexpressed miRNA targets were calculated using versatile gene-based test
for GWAS,34 and our BD GWAS data set.6 To capture regulatory regions, the
default settings in versatile gene-based test for GWAS were used.
Enrichment of associated targets was calculated as follows: the number
of associated target genes for each miRNA was compared with the number
of associated genes from 100 000 random target sets of brain-expressed
genes. Each target gene set comprised the same number of genes as the
miRNA target genes itself.
Pathway analysis of target genes
The subsequent analyses were restricted to brain-expressed target genes
of miR-499, miR-708 and miR-1908, with a gene-based association P-value
of o0.05. If the chromosomal distance between two target genes was
below 100 kb or if the top SNPs of two target genes were in strong or
moderate LD (D’40.4), only the target gene with the lowest gene-based
Figure 1. Quantile–quantile (Q–Q) plot of single-nucleotide polymorphism (SNP) P-values. The − log10 of the observed genomewide association studies (GWAS) P-values for linkage disequilibrium
(LD)-pruned SNPs (on the y axis) are plotted versus the − log 10 of
the expected P-values (under null, on the x axis). The solid line
represents expected uniform distribution. Red dots represent the
data distribution of P-values of SNPs at microRNA loci; blue dots
represent SNPs in genes; black dots represent P-values of intergenic
SNPs; and green dots represent the data distribution of all SNPs.
Table 1.
P-value was retained in the pathway analysis to ensure the independency
of association signals. In total, 107 target genes were included in the
pathway analyses (Supplementary Box 1). Gene ontology (GO) and Kyoto
Encyclopaedia of Genes and Genomes pathway testing was performed
using the WebGestalt (Web-based Gene Set Analysis Toolkit) for the brainexpressed, BD-associated target genes of the three associated miRNAs.
Bonferroni correction was used to adjust for multiple testings. Significant
pathways were filtered to achieve a minimum of three genes per set.
Functional analyses of miR-499 and miR-708 in rat hippocampal
neurons
To test the possible involvement of miR-499 or miR-708 in the regulation of
synaptic function, experiments were performed to investigate the effect of
miR-499 and miR-708 overexpression on dendritic spine morphogenesis in
primary rat hippocampal neurons. We initially focused on overexpression,
as this can be easily achieved by the transfection of expression plasmids
containing pri-miRNA cassettes. miRNA overexpression constructs were
generated by inserting the respective pri-miRNA sequences into the
3’-untranslated repeat of the luciferase reporter gene within pmiRGLO
(Promega, Madison, WI, USA). Thereby, luciferase reporter assays could be
used to monitor the efficiency of pri-miRNA processing. To investigate the
potential involvement of miR-499-5p and miR-708-5p in dendritic spine
morphogenesis, hippocampal neurons of embryonic day-18 Sprague–
Dawley rats (Charles River Laboratories, Sulzfeld, Germany) were transfected with miRNA-overexpressing constructs for 6 days before fixation.
Images with a resolution of 1024 × 1024 pixels were obtained using a LSM5
Zeiss Pascal confocal microscope (Jena, Germany) and in a magnification
of × 63 /1.4. A maximum projection was reconstructed with the Zeiss LSM
510 Meta software from a z-stack consisting of seven optical slices at
0.45-μm interval. The average intensity of an area of 2180 nm2 containing
250–300 spines per cell was measured using the ImageJ 1.48v software
(National Institutes of Health, Bethesda, MD, USA), as described
elsewhere.38 During imaging and analysis, the investigator was blind to
the transfection condition.
RESULTS
Overall, the nominal P-values of SNPs at miRNA loci were enriched
with lower values than would be expected with a uniform P-value
distribution (Figure 1). This deviation from the expected normal
Q–Q plot distribution indicates a general enrichment for miRNAs
among BD-associated SNPs. Category testing for different P-value
thresholds revealed a significant enrichment for BD-associated
SNPs in miRNA loci for P-values o1 × 10 − 4 (Supplementary
Table 1). This deviation was also observed among SNPs in genes
but not for intergenic SNPs.
Gene-based analysis in our BD GWAS data6 generated
nominally significant P-values for 98 of the 609 miRNAs. These
included miR-2113, which was located at the genome-wide
significant locus on chromosome 6q16.1 in the original BD GWAS
analyses.6 After correction for multiple testing, nine miRNAs
Results of the gene-based tests for the nine microRNAs that withstood Bonferroni correction
miRNA
Chr
nSNPs
Top SNP
p Top SNP
p Corr Gene
miR-499
miR-640
miR-708
miR-581
miR-644
miR-135a-1
let-7 g
miR-1908
miR-611
20
19
11
5
20
3
3
11
11
27
21
72
36
12
20
9
16
23
rs3818253
rs2965184
rs7108878
rs697112
rs7269526
rs9311474
rs6445358
rs174575
rs174535
6.58 × 10 − 7
7.23 × 10 − 7
3.45 × 10 − 7
3.61 × 10 − 6
1.22 × 10 − 5
2.16 × 10 − 5
2.23 × 10 − 5
2.85 × 10 − 5
5.03 × 10 − 5
0.0012
0.0012
0.0012
0.0073
0.0104
0.0122
0.0305
0.0353
0.0457
miRNA-assoc. signal
Expr. hum. brain
Yes
Yes
Yes
Yes
No
No
No
Yes
No
Yes
No
Yes
No
No
Yes
Yes
Yes
No
Abbreviations: Chr, chromosome; expr. hum. brain, expression in the human brain according to Ziats and Rennert;37 miRNA, microRNA; miRNA-assoc. signal,
specificity of the associated finding in the regional association plot; p Corr Gene, Bonferroni-corrected gene-based P-value; p Top SNP, P-value of the Top SNP
within gene; nSNPs, number of investigated SNPs; SNP, single-nucleotide polymorphism.
Translational Psychiatry (2015), 1 – 8
microRNAs in bipolar disorder
AJ Forstner et al
4
showed a significant association with BD (Table 1). The additional
calculation of gene-based tests for these nine miRNAs on the basis
of 1000 Genomes LD structure generated nominal P-values of
⩽ 7.20 × 10 − 5 (Supplementary Table 2).
Visual inspection of the regional association plots revealed a
miRNA-associated signal for five of the nine miRNAs (Figure 2,
Supplementary Figures 1–4).
The re-analysis of the expression data from Ziats and Rennert37
revealed that five of the nine miRNAs were expressed in the
human brain (Table 1).
Three of these (miR-499, miR-708 and miR-135a-1) were also
found to be expressed in the rat forebrain. This method could not
be used to investigate the expression of the other miRNAs, as they
are not expressed in rats.35
The regional association plots and the miRNA expression data in
human brain tissue suggest that the three brain-expressed
miRNAs, that is, miR-499, miR-708 and miR-1908, are the most
promising candidates for further analyses. The three miRNAs had
296, 181 and 67 target genes, respectively. Of these 286, 174 and
56 showed brain expression (Table 2).
The target gene enrichment analysis showed no significant
enrichment of BD-associated genes within the targets of miR-499,
miR-708 or miR-1908 (Table 2). After Bonferroni correction,
miR-1908 had one (KLC2) and miR-708 had two significant target
genes (NRAS and CREB1), whereas miR-499 had four significant
target genes (GPC6, C16orf72, WDR82 and CACNB2).
Pathway testing revealed 18 significant canonical pathways that
are driven by brain-expressed target genes of the three miRNAs
(Table 2). For each miRNA, the results of the GO analysis are
presented as directed acyclic graphs (Supplementary Figure 5).
The target genes that drive a particular pathway are listed in
Supplementary Table 3.
Luciferase assays revealed efficient processing of pri-miR-499,
but not pri-miR-708, upon transfection of the respective constructs
in neurons (Supplementary Figure 6). Overexpression of miR-499
led to a small and statistically nonsignificant increase in spine
volume (Figure 3), but no effect on spine density was observed. As
expected, transfection of the non-effective miR-708 expression
construct had no significant effect on spine morphological
parameters. Taken together, these results suggest that increasing
levels of the BD-associated miR-499 have no—or only minimal—
modulatory function during dendritic spine morphogenesis.
DISCUSSION
The present genetic association results for miRNA-coding genes
suggest that miRNAs and their target genes may be implicated in
the development of BD. The nominal P-values of SNPs at miRNA
loci showed early deviation from the expected null line in the Q–Q
plot, and this leftward shift reflects an enrichment of BDassociated SNPs at miRNA loci.
For the nine miRNAs that withstood Bonferroni correction, we
additionally calculated the gene-based tests on the basis of the
1000 Genomes LD structure. This analysis revealed nominally
gene-based P-values ⩽ 7.20 × 10 − 5 for all nine miRNAs, indicating
that the results of gene-based tests on the basis of either HapMap
phase 2 or 1000 Genomes Project data are highly comparable
using our BD GWAS data.
Eight of the nine associated miRNAs were located in a host
gene, including the three brain-expressed miRNAs miR-499,
miR-708 and miR-1908. Recent studies have reported a high
correlation between the expression of a host gene and the
resident miRNA.15,42 Previous authors have hypothesized that this
finding may be because of the fact that miRNAs residing in introns
are likely to share their regulatory elements and primary transcript
with their host gene.24 Some authors point out that host genes
and their resident miRNAs may even have synergistic effects,
which would have important implications for the fine-tuning of
Translational Psychiatry (2015), 1 – 8
gene expression patterns in the genome.43,44 On the basis of the
present genetic association results, it is impossible to determine
whether the association was attributable to the host gene, the
miRNA or both. Further analyses are therefore warranted to clarify
this, which was beyond the scope of the present analysis.
However, the general enrichment of BD-associated SNPs at miRNA
loci (Figure 1) and the results of our target gene analyses support
the hypothesis that the majority of the associated miRNAs are
implicated in BD etiology.
Regional association plots and expression data suggest that the
miRNAs miR-499, miR-708 and miR-1908 are the most promising
candidates in terms of the development of BD.
The miRNA miR-499 is located in a region on chromosome
20q11 that showed genome-wide significant association in a
previous GWAS of BD.45 As miR-499 is located in a region of high
LD, which includes the genes GSS, MYH7B and TRPC4AP (Figure 2),
further analyses of this chromosomal region are required to refine
the association signal.45 However, miR-499 represents a very
promising candidate in this region.
MiR-499 regulates apoptotic pathways involving the calciumdependent protein phosphatase calcineurin.46 A recent study
demonstrated an upregulation of miR-499 in the prefrontal cortex
of patients with depression.47 In a study of exosomal miRNA
expression, miR-499 showed differential expression in the postmortem brains of BD patients compared with controls.48 When
considering a possible pathomechanism, it is important to note
that a common SNP (rs3746444) is located in the seed region of
the mature miR-499-3p.49 This seed region is crucial for both the
recognition of the target sites and the binding of the target genes.
The SNP rs3746444 was not among the 2 267 487 SNPs analyzed
in our large BD meta-analysis.6 However, rs3746444 achieved a
nominally significant P-value of 0.0023 (risk allele: rs3746444-G) in
a combined analysis of the seven MooDS samples (2266 patients
and 5028 controls),6 which excluded the PGC data set.3
Furthermore, the allele rs3746444-G has been associated with
hallucinations and lack of motivation in schizophrenia patients.50
This suggests that this SNP may confer susceptibility to BD by
influencing depressive and psychotic endophenotypes. However,
it may only partly explain the association signal at this locus.
Our target gene analysis revealed that miR-499 had four
significant target genes, including the previously reported
genome-wide significant risk gene for psychiatric disorders
CACNB2.51
Brain-expressed target genes of miR-499-5p exhibited an
enrichment in biological processes related to cerebral development, which might however, at least partly, reflect the fact that
our pathway analysis was restricted to brain-expressed genes. In
addition, our pathway analysis indicates a potential role of
miR-499 in the regulation of the actin cytoskeleton. Interestingly,
this pathway has been identified in a previous investigation of
differentially and concordantly expressed genes enriched in
association signals for schizophrenia and BD.52 Substantial
research evidence suggests that the rearrangement of the
cytoskeleton is crucial for neuronal cell migration and maturation,
neurite outgrowth and maintenance of synaptic density and
plasticity.53–56 These combined data suggest that miR-499 is an
interesting candidate for BD pathogenesis.
The miRNA miR-708 is located in the first intron of ODZ4 (odd
Oz/ten-m homolog 4, TENM4), which has been reported as a
genome-wide significant susceptibility gene for BD.3
A recent study of postpartum psychosis—a disorder that often
heralds the incipient onset of BD57—suggested differential
expression of miR-708 in the monocytes of affected patients
compared with controls.58 In another study, Xu et al.59 demonstrated an altered expression profile for miR-708 in mouse
hippocampal neurons and showed that this was mediated by
oxidative stress. Another recent study found that miR-708
regulated the expression of neuronatin, which is a membrane
microRNAs in bipolar disorder
AJ Forstner et al
5
Figure 2. Regional association plots of miR-499, miR-708 and miR-1908. Regional association results for the three most promising associated
microRNAs miR-499 (a), miR-708 (b) and miR-1908 (c), and their ± 500-kb flanking regions were plotted using LocusZoom (Pruim et al.36). The
plot of miR-1908 (c) includes miR-611, which is also localized at the depicted chromosomal locus.
Translational Psychiatry (2015), 1 – 8
microRNAs in bipolar disorder
AJ Forstner et al
6
Table 2.
Target gene and pathway analysis for miR-499, miR-708 and miR-1908
MicroRNA
miR-499-5p
miR-708-5p
miR-1908-5p
No. of brain-expressed target
genes
No. of brain-expressed target
genes, Po0.05
P enrichment
No. of significant targets
(corr)
No. of significant
pathways
286
174
56
59
37
17
0.7172
0.9265
0.1422
4
2
1
12
1
5
Abbreviations: No. of significant pathways, number of significant pathways at P ≤ 0.05; No. of significant targets (corr), number of significant target genes after
Bonferroni correction for multiple testing; P enrichment, P-value of the enrichment analysis (Χ2-test). Results of the target gene analysis for the three brainexpressed microRNAs miR-499, miR-708 and miR-1908 that were associated with bipolar disorder after correction for multiple testing.
Figure 3. Effect of the overexpression of miR-499 and miR-708 on dendritic spine size and density in primary rat hippocampal neurons. DIV14
primary hippocampal neurons were transfected with: (i) empty pmirGLO (250 ng) or (ii) pmirGLO (250 ng) containing pri-miR-499 or pri-miR-708
in the 3’-untranslated repeat of the Firefly luciferase gene and green fluorescent protein (GFP). The transfected neurons were then cultured
until DIV19 and fixed for fluorescence microscopy. (a) Representative images for cells transfected with the indicated pmirGLO constructs or
GFP only. A three-dimensional reconstruction was made from seven 45-μm stacks; scale bars, 5 μm. (b) Spine volume quantification of
hippocampal neurons transfected with the indicated pmirGLO constructs. Values are represented as means ± s.d. (n = 3; 24 neurons per
condition with a 200–250 spine count per cell). (c) Spine density of hippocampal neurons transfected with the indicated pmirGLO constructs.
Values are represented as means ± s.d. per 10 μm dendritic length (n = 3; 24 neurons per condition). Data are presented as the mean of three
independent transfections normalized to the empty pmirGLO condition ± s.d.
protein in the endoplasmic reticulum. Interestingly, the
neuronatin-mediated regulation of intracellular Ca2+ levels has
been implicated in cell migration and neural induction within
embryonic stem cells.60
Our target gene analysis revealed that miR-708 had two
significant target genes. These include CREB1 that has previously
been identified as a susceptibility gene for major depressive
disorder.61–63 In addition, CREB1 was found to be associated with
BD in a recent study of large-scale BD samples64 that included
8403 patients and 11 588 controls of our BD GWAS.6 However, the
present pathway analysis provided no strong evidence for an
enrichment of biological processes of relevance to psychiatric
disorder.
MiR-1908 is located in the first intron of the fatty acid desaturase
1 (FADS1) gene on chromosome 11. To date, few published studies
have investigated the function of miR-1908. One recent study
implicated miR-1908 as a cancer biomarker.65 A further study
found that miR-1908 belonged to a miRNA cluster that downregulates the MARK1 signaling pathway, thus altering cell
proliferation and differentiation.66
Pathway analysis results for miR-1908 indicate a potential role of
the miRNA-regulated target gene network in key neuronal
processes (GO subcategories: neuron projection and nervous
system development). As these pathways showed the strongest
Translational Psychiatry (2015), 1 – 8
enrichment, further research into miR-1908 and its regulated
network appears to be warranted.
Although initial efforts have been made to elucidate the
regulation of miRNA expression,67 the manner in which miRNA
expression and processing are regulated remains largely
unknown. Given that pri-miRNAs have a length of 100–1000 bp,16 the present study investigated common variants at the
miRNA loci and ± 20 kb flanking sequences in order to capture
possible regulatory regions. However, further analyses of the
regulation of miRNA expression by common variants are required
to determine whether, and how, the presently described
association signals influence the expression levels and function
of the implicated miRNAs. The present approach did not allow
investigation of SNPs with trans-expression quantitative trait loci
(eQTL) effects on miRNAs. As recent studies suggest that ~ 50% of
the identified miRNA eQTLs are trans-eQTLs,68 investigations into
the association between miRNA trans-eQTLs and BD are indicated.
The results of the functional analyses of miR-499 and miR-708 in
rat hippocampal neurons revealed no major contribution of these
miRNAs to the morphogenesis of dendritic spines, which
represent the major sites of synaptic contact. However, only the
results for miR-499 can be considered robust, as the miR-708
expression construct did not increase miR-708 in primary neurons
effectively. Alternative strategies for miR-708 expression, together
microRNAs in bipolar disorder
AJ Forstner et al
7
with miR-499/708 loss-of-function approaches, must be tested
before definite conclusions regarding the role of these miRNAs in
dendritic spine morphogenesis can be drawn. Moreover, to obtain
more comprehensive insights into the potential effects of these
miRNAs on synaptic function, future experiments should be
complemented by immunocytochemistry analyses of synaptic
marker proteins and electrophysiological recordings. Beyond a
potential involvement in dendritic spine morphogenesis, these
miRNAs could also regulate other aspects of neuronal morphology, such as dendrite arborization or axon growth, which could be
tested in future studies.
CONCLUSION
The results of the present miRNA and target gene analyses
suggest that the brain-expressed miRNAs miR-499, miR-708 and
miR-1908 may contribute to the development of BD. Further
research is warranted to elucidate the involvement of these
miRNAs and their downstream pathways in BD.
CONFLICT OF INTEREST
The authors declare no conflict of interest.
ACKNOWLEDGMENTS
We are grateful to all of the patients and control subjects who contributed to this
study. The study was supported by the German Federal Ministry of Education and
Research (BMBF) through the Integrated Network IntegraMent (Integrated Understanding of Causes and Mechanisms in Mental Disorders), under the auspices of the
e:Med Programme (grant 01ZX1314A to MMN and SC, grant 01ZX1314G to MR, grant
01ZX1314J to BMM), and through e:AtheroSysMed (Systems medicine of myocardial
infarction and stroke, grant 01ZX1313B to BMM). MMN is a member of the DFGfunded Excellence-Cluster ImmunoSensation. MMN also received support from the
Alfried Krupp von Bohlen und Halbach-Stiftung. The study was supported by the
German Research Foundation (DFG; grant FOR2107; RI908/11-1 to MR; SCHR1136/3-1
to GS; NO246/10-1 to MMN). MG-S received the grant no. 89/2012 from UEFISCDI,
Romania. Canadian patients were genotyped within the ConLiGen project (www.
ConLiGen.org), with the support of a grant from the Deutsche Forschungsgemeinschaft to MR, MB and TGS (RI 908/7-1). Controls for Germany II were drawn from
the Heinz Nixdorf Recall Study (HNR) cohort, which was established with the support
of the Heinz Nixdorf Foundation. Recruitment of the Australian sample was
supported by an Australian NHMRC program grant (number 1037196). The
recruitment of the Canadian patients was supported by a grant from the Canadian
Institutes of Health Research #64410 to MA. The study also used data generated by
the GABRIEL consortium (controls for the sample Russia). Funding for the generation
of these data was provided by the European Commission as part of GABRIEL contract
number 018996 under the Integrated Program LSH-2004-1.2.5-1. Post-genomic
approaches to understand the molecular basis of asthma aiming at a preventive or
therapeutic control and the Wellcome Trust under award 084703. Canadian controls
were drawn from the French Canadian study (SLSJ), which was supported in part by
the Canada Research Chair Environment and genetics of respiratory diseases and
allergy, the Canadian Institutes of Health Research (Operating grant No. MOP-13506)
and the Quebec Respiratory Network of the Fonds de recherche en Santé du Québec
(FRQS). Polish controls were recruited by the International Agency for Research on
Cancer (IARC)/Centre National de Genotypage (CNG) GWAS Initiative. We thank the
Bipolar Disorder Working Group of the PGC (PGC-BD) for providing access to the
relevant data.
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Translational Psychiatry (2015), 1 – 8