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ORIGINAL ARTICLE
Patterns of gene expression in the limbic system
of suicides with and without major depression
A Sequeira
1,3
, T Klempan
1
, L Canetti
1
, J ffrench-Mullen
2
, C Benkelfat
1
, GA Rouleau
1
and G Turecki
1
1
McGill Group for Suicide Studies, Douglas Hospital, McGill University, Montreal, QC, Canada and
2
Gene Logic Inc.,
Gaithersburg, MD, USA
The limbic system has consistently been associated with the control of emotions and with
mood disorders. The goal of this study was to identify new molecular targets associated with
suicide and with major depression using oligonucleotide microarrays in the limbic system
(amygdala, hippocampus, anterior cingulate gryus (BA24) and posterior cingulate gyrus
(BA29)). A total of 39 subjects were included in this study. They were all male subjects and
comprised 26 suicides (depressed suicides = 18, non depressed suicides = 8) and 13 matched
controls. Brain gene expression analysis was carried out on human brain samples using the
Affymetrix HG U133 chip set. Differential expression in each of the limbic regions showed
group-specific patterns of expression, supporting particular neurobiological mechanisms
implicated in suicide and depression. Confirmation of genes selected based on their
significance and the interest of their function with reverse transcriptase-polymerase chain
reaction showed consistently correlated signals with the results obtained in the microarray
analysis. Gene ontology analysis with differentially expressed genes revealed an over-
representation of transcription and metabolism-related genes in the hippocampus and
amygdala, whereas differentially expressed genes in BA24 and BA29 were more generally
related to RNA-binding, regulation of enzymatic activity and protein metabolism. Limbic
expression patterns were most extensively altered in the hippocampus, where processes
related to major depression were associated with altered expression of factors involved with
transcription and cellular metabolism. Additionally, our results confirm previous evidence
pointing to global alteration of gabaergic neurotransmission in suicide and major depression,
offering new avenues in the study and possibly treatment of such complex disorders. Overall,
these data suggest that specific patterns of expression in the limbic system contribute to the
etiology of depression and suicidal behaviors and highlight the role of the hippocampus in
major depression.
Molecular Psychiatry advance online publication, 13 March 2007; doi:10.1038/sj.mp.4001969
Keywords: microarray; gene expression; depression; suicide; limbic system; RT-PCR
Introduction
Suicide is an important public health problem that
has a strong association with psychopathology
and particularly with mood disorders.
1,2
There is a
large body of evidence suggesting that neurobiological
factors play a role increasing predisposition to
suicide.
3,4
In spite of some overlap, this neurobiolo-
gical predisposition seems to be, to a considerable
extent, different from that mediating risk to major
depression or other psychopathological processes
commonly present in suicide completers.
5
Neuroimaging studies have produced a substantial
body of knowledge about alterations of the limbic
system in mood disorders. In the amygdala, altera-
tions in cerebral blood flow and metabolism,
6
asym-
metry of amygdalar volumes,
7
as well as smaller
8–10
and larger volumes
11–14
have been observed in depres-
sed subjects when compared with normal controls.
In the hippocampus, volumetric analysis studies
have also revealed reduced volumes in subjects
suffering from major depression in some,
7,11,14–20
but
not all studies
10,21–23
comparing depressed patients
versus controls. Alterations in the cingulate cortex
have also been observed by many authors. Among
these, a smaller anterior cingulate (or Brodmann Area
24: BA24) was observed in depressed patients when
compared to controls
9,24,25
and altered activity has
also been reported.
26–28
Brodmann area 29 (BA29) or
posterior cingulate, has been associated mainly to
response to antidepressant treatment with changes
in metabolic response associated with the different
treatments.
28–31
The observed changes in these limbic
Received 12 December 2005; revised 11 November 2006; accepted
13 November 2006
Correspondence: Dr G Turecki, McGill Group for Suicide Studies,
Douglas Hospital, McGill University, 6875 LaSalle Blvd, Verdun,
QC, Canada H4H 1R3.
E-mail: gustavo.turecki@mcgill.ca
3
Current address: Department of Psychiatry and Human Behavior,
College of Medicine, University of California, Irvine, CA, USA
Molecular Psychiatry (2007),1–16
&
2007 Nature Publishing Group All rights reserved 1359-4184/07
$
30.00
www.nature.com/mp
regions may modulate the risk of suicidal behavior
through their influence on depression or stress
response. In particular, the involvement of the
hippocampus in depression and suicidal behavior
has been inferred from studies revealing morpho-
logical changes of this structure in response to stress
hormones, although these changes may often be
reversible markers of an ongoing stress or depres-
sion-related process.
32
Also, postmortem examinations have produced
a large body of evidence supporting the implication
of limbic areas in suicide. Molecular studies in
postmortem hippocampi of suicides have pointed
to altered levels of 5-HT2A receptor,
33
cyclic AMP
(cAMP) response element-binding,
34
extracellular
signal-regulated kinase1/2 mitogen-activated protein
(MAP) kinases,
35,36
protein kinase C isozymes.
36
Additionally, in a recent study, Rosel et al.
37
observed
altered levels of 5-HT2A and 5-HT4 receptors and
their respective intracellular signaling systems IP
3
and cAMP in hippocampi of suicides when compared
to controls. A number of recent investigations have
highlighted the potential for identification of genetic
predisposing factors for depression
38
and suicidal
behavior,
39
including WFS1
40–42
and p75NTR,
43
among others. However, these studies have focused
on expression levels of one or several genes at a time
and compared suicides with or without psycho-
pathology to controls, not providing an idea of the
overall changes taking place in relation to suicide
versus the ones related to major depression. Although
many of these findings may be biologically relevant,
they are difficult to confirm in the absence of larger
studies seeking to replicate these findings in similar
clinical samples with comprehensive coverage of the
variants at a particular candidate locus. It is therefore
important that genome-wide analyses of gene expres-
sion accompany these focused efforts to better under-
stand the relative significance of previously reported
findings and direct attention toward particular
biochemical pathways and processes.
A growing number of microarray-based investiga-
tions have been conducted in recent years; however,
relatively few have examined complex behavioral
phenotypes, especially in humans. There is good
evidence for differential gene expression underlying
complex phenotypes, as in the case of avoidance
learning in rodents.
44
In this study, using oligonucleo-
tide microarrays for high-throughput analysis of
mRNA levels in the limbic system (hippocampus,
amygdala, BA24 and BA29), we compared the expres-
sion patterns of male subjects suicides with and
without major depression and psychiatrically normal
controls.
Materials and methods
Subjects
Subjects were all males of French-Canadian origin, a
homogeneous population with a well-known founder
effect.
45
Both cases and controls were age and post-
mortem interval (PMI) matched. All subjects died
suddenly without a prolonged agonal state or protrac-
ted medical illness. Brain samples were obtained
from the Quebec Suicide Brain Bank and were collec-
ted with PMI of less than 36 h at autopsy. Amygdala,
hippocampus, anterior cingulate gyrus (BA24) and
posterior cingulate gyrus (BA29) were sampled at 41C
and snap-frozen in liquid nitrogen before storage at
801C. This study was approved by our local IRB and
informed consent was obtained from next of kin.
All subjects were psychiatrically characterized
by psychological autopsies, which are validated
methods to reconstruct psychiatric history by means
of extensive proxy-based interviews, as outlined
elsewhere.
46
The sample consisted of subjects who
committed suicide during an episode of major
depression (SMD; n= 18); suicide victims (S; n=8)
with no lifetime history of major depression; and
matched controls (C; n= 13) with no history of
suicidal behavior or a major psychiatric diagnosis.
Microarray analysis
Sample processing, RNA extraction, RNA quality
control and gene expression by microarray were
performed at Gene Logic Inc. (Gaithersburg, MD,
USA, www.genelogic.com). All microarray data and
clinical information were embedded into Gene Logic’s
Genesis 2.0 software as a component of its Bioexpress
system. RNA samples used in the current study had a
minimum A260/A280 ratio of 1.9. The samples were
further checked for evidence of degradation and
integrity. Samples had a minimum 28S/18S ratio of
> 1.6 (2100-Bioanalyzer, Agilent Technologies, Palo
Alto, CA, USA). We used the Human Genome U133
Set, which consists of two GeneChip arrays with
B45 000 probe sets representing > 39 000 transcripts
derived from B33 000 well-substantiated human
genes (available at http://www.affymetrix.com).
GeneChip analysis was performed in Genesis 2.0
(Gene Logic Inc.) and with Microarray Analysis Suite
(MAS) 5.0, Data Mining Tool 2.0, and Micro-
array Database software (available at http://www.
affymetrix.com). All of the genes represented on the
GeneChip were globally normalized and scaled to
a signal intensity of 100.
Several microarray RNA integrity indicators were
used in this study to filter samples for quality for final
analysis. Principal Component Analysis (PCA) was
used to quickly identify outlier arrays. Microarray
quality control parameters included the following:
noise (RawQ), consistent number of genes detected as
present across arrays, consistent scale factors, and
consistent b-actin and glyceraldehyde-3-phosphate
dehydrogenase (GAPDH) 50/30signal ratios. Outlier
arrays subjects were excluded on a region basis
without any subject being excluded from all the
regions. Similar number of subjects were included in
the final analysis across the three regions (amygdala:
C = 8, S = 6 SMD = 14; hippocampus: C = 6, S = 6,
SMD = 10; BA24: C = 7, S = 5, SMD = 9; BA29: C = 8,
S = 7, SMD = 10).
Patterns of gene expression in the limbic system of suicides
A Sequeira et al
2
Molecular Psychiatry
Data analysis
For a gene to be included in the final analysis, it had
to be ‘present’ (according to MAS 5.0) in at least 75%
of the subjects in at least one of the three groups to
reduce the chances of false-positive results and to
exclude bad probe sets. Expression data was analyzed
using Genesis 2.0 (GeneLogic Inc., Gaithersburg, MD,
USA) and AVADIS software (Strand Genomics, Red-
wood City, CA, USA). Gene expression values were
floored to 1 and then log
2
transformed.
Analysis of variance (ANOVA)s were performed for
each gene to identify statistically significant gene
expression changes. To identify differences between
the SMD, suicides (S), and controls (C), statistically
significant genes were subjected to a post hoc t-test
for the contrasts SMD versus C, S versus C, and SMD
versus S. Two criteria were used in all to determine
whether a gene was differentially expressed. First, a
gene had to have an ANOVA P-value of less than or
equal to 0.01. Second, for a given contrast a gene had
to have a fold change/P-value combination of at least
1.3-fold change in both direction and Pp0.01.
Cluster analysis was performed using average-
linkage hierarchical cluster analysis with a correla-
tion metric. Both expression patterns in individuals
and genes were clustered. PCA was performed based
on the initial gene sets and on the selected genes
(according to our significance criteria). PCA based on
the initial gene set did not discriminate the groups.
PCA based on the selected genes showed discrimina-
tion of the three groups.
Gene ontology analysis was conducted for differ-
entially expressed genes using the enrichment algo-
rithm integrated in the Database for Annotation,
Visualization and Integrated Discovery (DAVID 2.0).
DAVID is a web-based application that allows users
to access relational databases for functional annota-
tions.
47
Real-time PCR
Total RNA was re-extracted from 10–20 mg of frozen
tissue in the four areas examined using Trizol
(Invitrogen Corp, Carlsbad, CA, USA). These samples
were independent from those used in the microarray
assays, and were obtained from adjacent tissue
dissections. Quality of the RNA was established using
OD measurements and evaluation on an Agilent 2100
Bioanalyzer (Agilent Technologies, Palo Alto, CA,
USA), with samples below an RNA integrity number
of 5 excluded from further analysis. Synthesis of
complementary DNA (cDNA) from 1 mg of total RNA
was carried out by oligo(dT)-priming using Super-
Script II reverse transcriptase (Invitrogen Corp). Real-
time analysis of expression results for genes of
interest (spermidine/spermine N-1-acetyltransferase
gene (SSAT)1, SSAT2, OATL1, SYT4, ADCY8, APLP2
and BACE1) was carried out using TaqMan gene
expression assays (Applied Biosystems, Foster City,
CA, USA) with 5 ng of cDNA template in a 15 ml reac-
tion volume. The polymerase chain reaction (PCR)
reactions were run on an ABI 7900HT Real-Time PCR
system (Applied Biosystems) according to the manu-
facturer specified conditions (ABI TaqMan gene
expression assays protocol, Rev E). Fold changes
between groups were evaluated using relative quanti-
tation (delta C
t
method) with b-actin and GAPDH
endogenous controls (demonstrating low variation
from microarray analysis), and all real-time reactions
carried out in triplicate. Real-time results were
analyzed using the SDS software (Applied Biosys-
tems, v.2.2.1), with automatic computation of baseline
and threshold fluorescence levels. Gene expression C
t
values below that of endogenous controls were discar-
ded from analyses and outlier removal was performed
in cases where the standard deviation of C
t
values
exceeded 0.3 cycles. Student’s t-tests and Pearson’s
correlations (between microarray and real-time com-
parative fold changes) were employed in statistical
analysis (SPSS, v.12.0, Chicago, IL, USA). The genes
chosen for validation were selected based on their
involvement in stress response, signal transduction
and neurotransmission, and on the strength of
findings from microarray analysis.
Results
No significant differences were observed in terms of
age (C = 35.3711.5; S = 35.179.0; SMD = 36.5712.3),
pH (C = 6.570.3; S = 6.370.3; SMD = 6.570.4) and
PMI (C = 23.775.8; S = 24.374.5; SMD = 24.176.5)
between the groups (Table 1). The effect of age and
PMI on quality control parameters like b-actin and
GAPDH 50/30ratios and the number of present cells
was evaluated. No significant correlation was ob-
served between PMI and any of the quality control
variables in our sample in all the regions studied.
Figure 1 shows the correlations between pH and PMI
with 50/30ratios for b-actin and GAPDH in hippo-
campus. Similar relationships were also observed in
the other limbic areas.
Initial filtering in the amygdala, which consisted of
selecting genes called ‘present’ (according to MAS
5.0) in at least 75% of the subjects in at least one
group, resulted in 15 007 genes that were included
in the analysis. The ANOVA and post hoc analysis
resulted in 182 differentially expressed genes. Among
these, 127 genes were significant for the SMD-C
comparison, 51 for the S-C comparison and 33 for
the SMD-S comparison (Figure 2). The intersections
show the number of significant genes common for two
comparisons. The PCA plot and the clustered image
map show the degree of discrimination between the
groups using the differentially expressed genes
(Figure 3a and b). Gene ontology analysis based on
the differentially expressed genes revealed an over-
representation of genes implicated in the regulation
of transcription and in nucleic acid metabolism in
the amygdala (Table 2). For instance, X-box binding
protein 1, a transcription factor gene whose expres-
sion was shown previously to be implicated in
bipolar disorder,
48
was upregulated in the two suicide
groups and even more among the suicides without
Patterns of gene expression in the limbic system of suicides
A Sequeira et al
3
Molecular Psychiatry
major depression (Table 3). Also, several genes
playing a role in the regulation of second messenger
systems were differentially expressed in the amygda-
la, among these, there were several protein kinase and
protein phosphatases genes, as well as cAMP-depen-
dent kinases (Table 3).
In the hippocampus, 14 537 genes passed the initial
filtering and were included in the analysis. A total of
429 genes were differentially expressed between the
three groups, 35 for the SMD-C comparison, 120 for
the S-C comparison and 359 for the SMD-S compar-
ison (Figure 2). It is noteworthy that in contrast to
the other regions, in the hippocampus the vast
majority of genes were significantly different between
the two groups of suicides, with and without major
depression. Accordingly, the hierarchical clustering
analysis showed the biggest separation between the
two groups of suicides and the clustered image
map clearly shows two groups of genes differentially
expressed between the two suicide groups (Figure 4a).
Also, in the PCA, the 20 genes contributing most
to the first component of the PCA are differentially
expressed between these two groups, as reflected by
their separation in the two-dimensional space (Figure
4b). Gene ontology analysis revealed an overrepre-
sentation of genes implicated mainly in the regulation
of transcription and in nucleic acid-binding and
metabolism (Table 2). Overrepresented ontology cate-
gories corresponded to several kinases, phosphatases,
one phosphodiesterase and one adenylate cyclase
(ADCY8), all implicated in intracellular signaling
cascades and second messenger systems (Table 2).
Several genes implicated in neurotransmission were
also altered in the hippocampus such as the genes
coding for the multiple coiled-coil GABABR1-binding
protein the inositol 1,4,5-triphosphate receptor type 1
the cannabinoid receptor 2 (CNR2) and the leptin
receptor. Finally, three genes coding for proteins
involved in the biosynthesis and catabolism of
polyamines were also differentially expressed in the
hippocampus: SSAT2, spermine synthase, and or-
nithine aminotransferase-like 1 (OATL1).
Analysis in BA24 was conducted on 14 556 genes
after the initial filtering and revealed 84 genes as
differentially expressed between the three groups.
Post hoc analysis identified 52 genes as differentially
expressed for the SMD-C comparison, 20 genes for the
S-C comparison and 27 genes for the SMD-S compar-
ison (Figure 2). A good separation and clustering of
the groups was observed with the PCA and the
hierarchical clustering analysis using the differen-
tially expressed genes (Figure 5a and b). Gene
ontology analysis of the differentially expressed genes
revealed an overrepresentation of binding and bind-
ing-related functions such as RNA and nucleic acid
binding, as well as enzymatic regulation (Table 2).
Interestingly, the b-site amyloid precursor protein
(APP)-cleaving enzyme 1 (BACE1) known to play an
important role in neurodegeneration and in Alzhei-
mer disease
49
was downregulated in the depressed
suicide group when compared with controls, suggest-
ing a possible role for this enzyme in the neurobiology
of depression. Two gabaergic receptors were also
differentially expressed in opposite ways in BA24.
Although the g-aminobutyric acid (GABA) A receptor,
a-1 (GABRA1) was highly downregulated among
the depressed suicides versus the controls, the GABA
A receptor, b-1 (GABRB1) showed an important
upregulation for that same comparison. Suicides
without major depression showed intermediate
levels, suggesting possible quantitative effects on the
phenotype.
After filtering, 15 032 genes were included in the
analysis for BA29, 83 of which were differentially
expressed according to the defined criteria. More
specifically, 19 genes were significant for the SMD-C
comparison, 40 for the S-C comparison and 40 for
the SMD-S comparison (Figure 2). Differentially
expressed genes used for the PCA and the hierarchical
clustering were able to discriminate the groups,
which showed a good separation and an accurate
clustering (Figure 6a and b). Gene ontology analysis
was performed with the differentially expressed
genes, but only 69 genes were fully annotated and
Figure 1 Graphical representation of the correlation
between pH and PMI with50/30ratios for b-actin and GAPDH
in hippocampus. Similar relationships are observed in the
other limbic areas.
Patterns of gene expression in the limbic system of suicides
A Sequeira et al
4
Molecular Psychiatry
were included in the enrichment analysis. Probably,
owing to the small number of genes, only two
ontology terms were significant in BA29 correspond-
ing to organismal movement and protein metabo-
lism. One of these metabolic genes, the SSAT1, was
differentially expressed between the two suicide
groups.
Because some of the subjects in the three groups
had a history of substance dependence or abuse,
possibly implicating more chronic substance-related
gene expression changes, whereas other subjects
had negative history of substance-related disorders,
but had a positive toxicological result for alcohol or
cocaine (Table 1), which may be associated to more
acute substance-related gene expression alterations,
we performed an ANOVA to control for these
two different effects on our gene-expression findings.
The majority of genes differentially expressed
remained significant following this analysis, suggest-
ing that the most of our findings are more
directly related to depression and suicide. Table 3
shows the corrected P-values (*P) for genes of
interest. Some genes (Table 4) were significantly
affected (Pp0.01) by the history of dependence/
abuse of substance (amygdala = 2; hippocampus = 8;
BA24 = 0; BA29= 2) and presence according to the
toxicology screening (amygdala = 4; hippocampus = 4;
BA24 = 1; BA29 = 1). However, owing to the limited
number of subjects per category, further analysis
will need to be done in a larger sample to investigate
the role played by those genes in substance abuse
and intoxication.
Table 1 Demographic and clinical characteristics of the subjects included in the analysis
Group Age PMI pH Cause of death DSM-IV (6 months diagnosis) Toxicological findings
C 32 26.5 6.80 Cardiac arrest
C 31 24 5.95 Cardiac arrest Alcohol dependence
C 19 32 6.55 Car accident
C 47 12 6.49 Cardiac arrest Alcohol abuse
C 30 30 6.37 Cardiac arrest
C 28 27 6.32 Car accident
C 41 24 6.00 Myocardial infarction
C 31 29.5 6.67 Car accident
C 46 19.5 6.42 Myocardial infarction
C 21 24 6.42 Cardiac arrest
C 27 20.5 6.55 Cardiac arrest
C 51 15 6.83 Car accident Alcohol dependence Alcohol
C 55 24 6.75 Car accident
S 33 18 6.68 Hanging
S 38 23 6.00 Hanging Alcohol dependence,
cocaine dependence
Alcohol
S 21 21 6.59 Asphyxiation Alcohol dependence Alcohol
S 31 32.5 6.27 Hanging
S 29 26.5 6.15 Hanging
S 36 25 6.54 Hanging
S 51 21 6.12 Self inflicted gun shot Alcohol dependence
S 42 27 6.10 Carbon monoxide
SMD 22 11.5 6.35 Hanging MDD, alcohol dependence Alcohol, cocaine
SMD 19 29.5 6.17 Hanging MDD
SMD 53 29 6.30 Hanging MDD, alcohol dependence
SMD 42 21 6.40 Drowning MDD
SMD 45 20.5 6.57 Self inflicted gun shot MDD
SMD 39 25.5 6.60 Hanging MDD
SMD 49 32 6.57 Hanging MDD, alcohol abuse
SMD 26 34 6.67 Hanging MDD Cocaine
SMD 40 22 6.96 Hanging MDD
SMD 39 19 6.00 Overdose MDD
SMD 26 21.5 6.50 Carbon monoxide MDD, alcohol abuse,
cocaine dependence
Cocaine
SMD 35 31 6.81 Hanging MDD, alcohol dependence
SMD 53 14 6.45 Carbon monoxide MDD
SMD 53 33.5 6.78 Hanging MDD
SMD 18 27 7.28 Carbon monoxide MDD
SMD 22 20 6.71 Hanging MDD
SMD 40 23 6.21 Hanging MDD, alcohol dependence
SMD 28 20 6.84 Hanging MDD, alcohol dependence Alcohol
Abbreviations: SMD, suicide with major depression; MDD, major depressive disorder.
Patterns of gene expression in the limbic system of suicides
A Sequeira et al
5
Molecular Psychiatry
Similarities in terms of common differentially
expressed genes were explored between the three
regions. Few similarities in terms of differentially-
expressed genes between the regions were observed
(amygdala–hippocampus (one gene), amygdal-BA24
(zero genes), amygdala-BA29 (two genes) hippocam-
pus-BA24 (zero genes), hippocampus-BA29 (two
genes) and BA24-BA29 (two genes)). This is however
not surprising in the case of such areas, which are for
the most part functionally and neuroanatomically
distinct. More overlap was seen for instance in a
previous study by our group exploring expression in
cortical regions.
50
Some overlap was also observed between the SMD-
S and S-C comparisons, suggesting that these genes
are likely to be involved in suicide-related processes
independently of underlying depressive psycho-
pathology. In the amygdala, for instance four genes
were observed in common for those comparisons
(MAX, MYEF2, YWHAB and GRIPAP1) whereas only
one was observed in BA24 (CIRBP) and three in BA29
(RGN, TDE1 and CKLFSF1). However, in the hippo-
campus, a total of 72 genes were found in common
among which several implicated in signal transduc-
tion (ARHGEF7, MAP3K5, RAP2A, RAPH1 and
RREB1) and the CNR2.
Evaluation of the microarray fold changes was
performed in independent samples collected from
adjacent tissue from that used for the microarray
assay in a total of 11 controls, seven non-depressed
suicides and 13 depressed suicides using real-time
PCR. The genes selected for reverse-transcriptase
polymerase chain reaction (RT-PCR) validation were
chosen based on known function and the significance
of microarray findings. Real-time analyses confirmed
primary group-level changes in expression for all
seven genes selected for further study from the
initial set of significant genes: SSAT1 (BA29), SSAT2
(hippocampus), OATL1 (hippocampus), SYT4 (hippo-
campus), ADCY8 (hippocampus), APLP2 (amygdala)
and BACE1 (BA24). The precision as measured by
agreement between results of replicate real-time runs
was high (meanDC
t
SD = 0.13), with 3% of samples
showing a DC
t
SD in excess of 0.3 cycles. The fold
changes at the validation stage ranged from 1.11 to
1.62-fold, and several of these changes exceeded
those from the microarray analysis (ADCY8 and
SSAT2). For four of the seven genes, the strongest
fold change resulted from the S-SMD comparison:
OATL1 (microarray FC = 1.50, RT FC = 1.19), SSAT1
(microarray FC = 1.45, RT FC = 1.19), SSAT2 (micro-
array FC = 1.36, RT FC = 1.57), and SYT4 (micro-
array FC = 1.69, RT FC = 1.11). The BACE1 gene
showed reduced expression in the SMD group when
compared to the controls (C): BACE1 (microarray
FC = 1.32, RT FC = 1.14). Finally, two genes were
confirmed as overexpressed in the non-depressed
suicide when compared to the controls: ADCY8
(microarray FC = 1.46, RT FC = 1.62) and APLP2
(microarray FC = 1.35, RT FC = 1.33). Overall, as seen
in other studies using microarrays and brain tissue,
51
correlations between relative fold changes seen using
microarray and real-time analyses for the seven genes
were good (mean R = 0.377, s.d. = 0.179). All genes
apart from OATL1 and BACE1 demonstrated signifi-
cant approach-wise correlations in calculated fold
changes at the P< 0.05 level, across all groups. The
gene-to-gene variation in the magnitude of fold
changes and correlations is likely owing to replication
at the tissue rather than RNA level, and the use of an
overlapping, but non-identical sample set for con-
firmation.
Figure 2 Venn diagrams showing the number of genes
identified as differentially expressed and the overlap of
genes between the different comparisons in the amygdala,
hippocampus, BA24 and BA29. The intersections of the
circles indicate the number of genes in common between
contrasts.
Patterns of gene expression in the limbic system of suicides
A Sequeira et al
6
Molecular Psychiatry
Discussion
Microarray analysis was performed in four limbic
areas of suicides with and without major depression
and psychiatrically normal controls. The vast major-
ity of expression changes were observed in the
amygdala (182 probe sets), and particularly, in the
hippocampus (429 probe sets, of 761 across all four
regions). In contrast, fewer differentially expressed
genes were observed in the two cingulate cortex
regions (BA24 = 84; BA29 = 83). Selected genes for
validation with an alternative method (RT-PCR)
showed consistently correlated signals with the
results obtained in the microarray analysis, support-
ing the ability of the study design to identify
candidate molecular target that may be involved in
the neurobiology of major depression and suicide.
We used a design that allowed us to control for the
presence of suicide (suicides with major depression
versus suicides without major depression) and there-
fore, to identify processes that are more likely
to be implicated in major depression. As such, in
our design, the identification of processes exclusively
attributed to suicide is confounded by the presence of
psychopathology. Nevertheless, by having a normal
control group, we also had the ability to identify
molecular processes that may be related to suicidality
independently of major depression (S-C comparison).
Having a comparison group with multiplex develop-
mental disorder (MDD) that did not die by suicide
would have allowed us to fully separate effects
attributed to suicide. However, for such a group to
be comparable, it would have been necessary to
include subjects who were affected with MDD before
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Control
Suicide
SMD
20 30
a
b
C
C
C
C
C
C
C
C
S
S
S
S
S
S
SMD
SMD
SMD
SMD
SMD
SMD
SMD
SMD
SMD
SMD
SMD
SMD
SMD
SMD
Figure 3 Amygdala gene expression patterns. (a) Clustered image map (CIM) of the differentially expressed genes in the
amygdala. Both expression patterns in individuals and genes were clustered. The color and intensity indicate direction and
level of change: blue spectrum colors indicate downregulated expression, whereas red spectrum colors indicate upregulated
expression. (b) PCA based on the differentially expressed genes. The color and intensity indicate direction and level of
change: blue spectrum colors indicate downregulated expression, whereas red spectrum colors indicate upregulated
expression (online version only).
Patterns of gene expression in the limbic system of suicides
A Sequeira et al
7
Molecular Psychiatry
death, or at least in the last 6 month. Collecting a
group that would be demographically comparable
with the suicide group and that died while affected
with MDD is operationally challenging.
The large number of differentially expressed genes
in the hippocampus was mainly owing to differences
between the two groups of suicides. As processes
related to the neurobiology of suicide are controlled
for when comparing both suicide groups, the obser-
ved expression differences in this region are probably
more specifically associated to biological mechanisms
related to major depression. This supports recent
findings indicating an important role of the hippo-
campus in depression and in the antidepressant
response to pharmacotherapy.
52,53
Also, altered size
and impaired function of the hippocampus have been
found in a number of recent clinical imaging studies
of major depression (for a meta-analysis see Camp-
bell
54
). Furthermore, expression changes in genes
implicated in the second messenger systems, such
as kinases, phosphatases and the adenylate cyclase 8
gene (ADCY8) were observed in the hippocampus,
supporting previous evidence of synaptic plasticity
alterations in mood disorders
55,56
and in antidepres-
sant response beyond the neurotransmitter and
receptor level.
57
Recent molecular studies in post-
mortem brains have also revealed alterations in
second messenger systems in hippocampi of suicides
and depressed suicides.
36,37,58,59
Few studies have explored global expression
changes between groups of suicides and psychiatri-
cally normal controls, some have however focused on
a particular psychiatric diagnosis, such as bipolar
disorder or schizophrenia, and included within
these groups subjects that died by suicide.
60–67
Sibille
et al.
51
recently compared expression patterns in BA9
and BA47 of depressed suicides versus psychiatri-
cally normal controls matched on the basis of sex, age,
Table 2 Enriched gene ontology terms calculated using the differentially expressed genes per region
Category Term Genes Total DAVID genes % P-value
Amygdala
Biological process Intracellular signaling cascade 11 135 8.1 0.028
Biological process Cell proliferation 11 135 8.1 0.049
Biological process Transcription 17 135 12.6 0.038
Biological process Regulation of biological process 22 135 16.3 0.035
Biological process Nucleotide and nucleic acid metabolism 23 135 17 0.038
Biological process Cellular process 43 135 31.9 0.043
Biological process Metabolism 46 135 34.1 0.046
Molecular function Adenyl nucleotide binding 12 135 8.9 0.045
Molecular function Protein binding 23 135 17 0.000
Hippocampus
Biological process Regulation of transcription, DNA-dependent 35 348 10.1 0.034
Biological process Regulation of transcription 35 348 10.1 0.048
Biological process Regulation of metabolism 38 348 10.9 0.035
Biological process Regulation of biological process 53 348 15.2 0.009
Biological process Nucleotide and nucleic acid metabolism 58 348 16.7 0.003
Molecular function Zinc ion binding 29 348 8.3 0.011
Molecular function Transition metal ion binding 33 348 9.5 0.005
Molecular function DNA binding 40 348 11.5 0.012
Molecular function Ion binding 43 348 12.4 0.020
Molecular function Metal ion binding 43 348 12.4 0.020
Molecular function Protein binding 44 348 12.6 0.001
Molecular function Nucleic acid binding 63 348 18.1 0.001
Molecular function Catalytic activity 95 348 27.3 0.002
BA24
Molecular function Enzyme regulator activity 7 70 10 0.003
Molecular function RNA binding 8 70 11.4 0.000
Molecular function Protein binding 11 70 15.7 0.030
Molecular function Nucleic acid binding 15 70 21.4 0.036
Molecular function Binding 34 70 48.6 0.008
BA29
Biological process Organismal movement 5 66 7.6 0.032
Biological process Protein metabolism 14 66 21.2 0.036
DAVID genes correspond to the total number of unique DAVID annotated genes. The percentage represents the number of
differentially expressed genes belonging to a given category over the total number of DAVID annotated genes.
Patterns of gene expression in the limbic system of suicides
A Sequeira et al
8
Molecular Psychiatry
Table 3 Selected differentially expressed genes in amygdala, hippocampus, BA24 and BA29
Probe set Gene title Symbol Cytoband C S SMD *PSMD-C S-C S-SMD
PFC PFC PFC
Amygdala
208704_x_at Amyloid beta (A4) precursor-like protein 2 APLP2 11q23-q25 1058 1415 1225 0.013 0.06 1.16 0.00 1.35 0.06 1.16
203006_at Inositol polyphosphate-5-phosphatase, 40 kDa INPP5A 10q26.3 204 288 265 0.008 0.01 1.29 0.00 1.41 0.33 1.10
225278_at Protein kinase, AMP-activated, b-2 non-catalytic subunit PRKAB2 1q21.1 219 275 305 0.001 0.00 1.40 0.01 1.27 0.21 1.10
225011_at Protein kinase, cAMP-dependent, regulatory, type II, alpha PRKAR2A 3p21.3-p21.2 368 419 486 0.001 0.00 1.32 0.06 1.14 0.02 1.16
206687_s_at Protein tyrosine phosphatase, non-receptor type 6 PTPN6 12p13 51 31 36 0.012 0.01 1.43 0.01 1.61 0.34 1.12
200670_at X-box binding protein 1 XBP1 22q12.1 74 99 92 0.022 0.01 1.23 0.01 1.33 0.42 1.08
Hippocampus
206811_at Adenylate cyclase 8 (brain) ADCY8 8q24 52 76 64 0.013 0.10 1.20 0.00 1.46 0.06 1.22
226463_at ATPase, H þtransporting, lysosomal 42kDa, V1 subunit C, isoform 1 ATP6V1C1 8q22.3 580 425 609 0.002 0.66 1.05 0.01 1.36 0.00 1.43
204311_at ATPase, Na þ/K þtransporting, b-2 polypeptide ATP1B2 17p13.1 294 486 339 0.009 0.37 1.14 0.00 1.66 0.02 1.46
206586_at Cannabinoid receptor 2 (macrophage) CNR2 1p36.11 99 143 99 0.006 0.90 1.01 0.00 1.44 0.01 1.46
213275_x_at Cathepsin B CTSB 8p22 296 236 364 0.002 0.07 1.26 0.22 1.24 0.00 1.56
227961_at Cathepsin B CTSB 8p22 564 358 650 0.006 0.26 1.25 0.16 1.49 0.00 1.86
203710_at Inositol 1,4,5-triphosphate receptor, type 1 ITPR1 3p26-p25 229 201 347 0.004 0.01 1.56 0.55 1.11 0.00 1.73
211323_s_at Inositol 1,4,5-triphosphate receptor, type 1 ITPR1 3p26-p25 110 101 155 0.014 0.02 1.42 0.64 1.08 0.01 1.54
227095_at Leptin receptor LEPR 1p31 94 91 67 0.015 0.01 1.44 0.67 1.04 0.02 1.38
238600_at Multiple coiled-coil GABABR1-binding protein MARLIN1 4p16.1 420 303 476 0.000 0.08 1.14 0.04 1.43 0.00 1.63
205669_at Neural cell adhesion molecule 2 NCAM2 21q21.1 54 65 45 0.013 0.09 1.23 0.14 1.19 0.01 1.46
229463_at Neurotrophic tyrosine kinase, receptor, type 2 NTRK2 9q22.1 368 277 487 0.002 0.07 1.29 0.10 1.42 0.00 1.83
236095_at Neurotrophic tyrosine kinase, receptor, type 2 NTRK2 9q22.1 209 188 264 0.002 0.01 1.27 0.33 1.11 0.00 1.41
227820_at Ornithine aminotransferase-like 1 OATL1 Xp11.3-
p11.23
150 196 135 0.020 0.41 1.13 0.02 1.33 0.01 1.50
236300_at Phosphodiesterase 3A, cGMP-inhibited PDE3A 12p12 104 131 91 0.011 0.26 1.15 0.04 1.27 0.00 1.46
203680_at Protein kinase, cAMP-dependent, regulatory, type II, beta PRKAR2B 7q22 207 240 318 0.001 0.00 1.53 0.15 1.17 0.02 1.30
227728_at Protein phosphatase 1A PPM1A 14q23.1 519 379 579 0.001 0.13 1.11 0.02 1.42 0.00 1.57
235061_at Protein phosphatase 1 K (PP2C domain containing) PPM1K 4q22.1 215 194 319 0.016 0.03 1.58 0.90 1.03 0.00 1.62
208617_s_at Protein tyrosine phosphatase type IVA, member 2 PTP4A2 1p35 476 672 527 0.016 0.33 1.12 0.01 1.44 0.01 1.29
225272_at Spermidine/spermine N1-acetyltransferase 2 SSAT2 17p13.1 636 509 694 0.005 0.35 1.08 0.03 1.26 0.00 1.36
202043_s_at Spermine synthase SMS Xp22.1 109 136 154 0.011 0.00 1.40 0.05 1.24 0.23 1.13
205551_at Synaptic vesicle glycoprotein 2B SV2B 15q26.1 936 775 1055 0.008 0.12 1.13 0.13 1.22 0.00 1.39
225721_at Synaptopodin 2 SYNPO2 4q26 179 258 175 0.012 0.90 1.02 0.02 1.47 0.00 1.50
223529_at Synaptotagmin IV SYT4 18q12.3 1579 1353 2359 0.001 0.03 1.45 0.24 1.16 0.00 1.69
225204_at T-cell activation protein phosphatase 2C TA-PP2C 12q24.11 333 231 331 0.006 0.88 1.02 0.01 1.46 0.01 1.43
225213_at T-cell activation protein phosphatase 2C TA-PP2C 12q24.11 377 228 347 0.002 0.36 1.09 0.01 1.71 0.00 1.57
BA24
24335_s_at b-site APP-cleaving enzyme 1 BACE1 11q23.2-q23.3 339 303 253 0.015 0.00 1.32 0.37 1.10 0.02 1.20
206678_at g-aminobutyric acid (GABA) A receptor, alpha 1 GABRA1 5q34-q35 301 244 175 0.020 0.00 1.72 0.29 1.21 0.06 1.42
207010_at g-aminobutyric acid (GABA) A receptor, beta 1 GABRB1 4p12 510 478 714 0.007 0.00 1.42 0.72 1.05 0.00 1.49
229773_at Synaptosomal-associated protein, 23 kDa SNAP23 15q15.1 83 63 78 0.013 0.40 1.07 0.00 1.33 0.03 1.25
BA29
221482_s_at Cyclic AMP phosphoprotein, 19 kDa ARPP-19 15q21.2 1000 1197 873 0.014 0.13 1.22 0.04 1.21 0.01 1.48
242482_at Protein kinase, cAMP-dependent, regulatory, type I, aPRKAR1A 17q23-q24 107 80 86 0.014 0.02 1.24 0.01 1.33 0.38 1.07
203455_s_at Spermidine/spermine N1-acetyltransferase SSAT Xp22.1 230 279 199 0.008 0.16 1.18 0.08 1.23 0.00 1.45
For a gene to be considered as differentially expresses it had to have an ANOVA Pp0.01 and for a given contrast a fold change/P-value combination of at least 1.3-fold
change in both direction and Pp0.01. Corrected P-values (*P) are shown after controlling for the possible confounder effect of substance dependence/abuse. Significant
comparisons (FC > |1.3| and Pp0.01) are in bold.
Patterns of gene expression in the limbic system of suicides
A Sequeira et al
9
Molecular Psychiatry
PMI, and race. Despite the number of transcripts
investigated they observed no significant evidence of
differences in gene expression that correlated with
major depression and suicide. In limbic regions,
structural abnormalities have been observed consis-
tently in the past decades in psychiatric disorders
68–70
and recent expression studies in suicides have
confirmed altered expression of genes implicated in
neurotransmission and intracellular signalling in
some limbic areas
33,35–37,58,71–73
in agreement with the
observed results in the present paper.
One potential limitation of human brain microarray
studies is the possible confounding effect on gene
expression by psychoactive drugs. In spite of the
presence of psychopathology in suicides, most of
the cases used in this study were not actively treated
before death. Accordingly, only two cases had a
history of antidepressant treatment. This is consistent
with data from the literature that indicates that most
suicide completers were not properly treated before
death.
74,75
In our sample, as expected for suicides,
several subjects had a history of substance depen-
dence/abuse, primarily involving alcohol. This was
the case in the two suicide groups, and to a lesser
degree, also in the control group. However, after
controlling for the history of alcohol and/or cocaine
dependence/abuse or the presence of substance
intoxication as per toxicological results, the group
effect on the expression differences observed for most
genes remained significant, suggesting that the gene
expression patterns observed are not owing to the
effect of alcohol or cocaine. Nevertheless, for certain
genes, a specific effect of acute or chronic substance
exposure was observed. The effect alcohol and
cocaine on the expression of those genes in the
context of suicide and depression should be further
explored.
One of the challenges with microarray studies is to
process the large amounts of information generated.
Differentially expressed genes were fully annotated
using electronic databases (NetAffix) and further
explored using gene ontology and enrichment algo-
rithms (DAVID), which constitutes an interesting way
to summarize and functionally explore microarray
data despite some problems concerning vague higher
functional classifications. In our study, we imple-
mented stringent significance criteria in the identifi-
cation of differentially expressed genes (minimum
Color bar
–
20 2
10
0
E1:8,81%
E0:48,67%
–10
–20
–100 –50 0 50
Control
Suicide
SMD
a
b
C
C
C
C
C
C
S
S
S
S
S
S
SMD
SMD
SMD
SMD
SMD
SMD
SMD
SMD
SMD
SMD
Figure 4 Hippocampus gene expression patterns. (a) CIM of the differentially expressed genes in the hippocampus. Both
expression patterns in individuals and genes were clustered. The color and intensity indicate direction and level of change:
blue spectrum colors indicate downregulated expression, whereas red spectrum colors indicate upregulated expression.
(b) PCA based on the differentially expressed genes. The color and intensity indicate direction and level of change: blue
spectrum colors indicate downregulated expression, whereas red spectrum colors indicate upregulated expression (online
version only).
Patterns of gene expression in the limbic system of suicides
A Sequeira et al
10
Molecular Psychiatry
1.3-fold change, ANOVA and t-test P-values < 0.01) to
reduce the complexity of the data and enrich for
genes, which are biologically relevant to suicide and
depression. The combination of the ANOVA and
subsequent t-tests is commonly referred to as Fisher
protected least significant difference (LSD) test. In the
case of gene expression studies of complex traits such
as psychiatric disorders, it has been suggested to use
less stringent criteria in the initial analysis stages,
76
and the use of only t-tests or Fisher protected LSD test
has been commonly accepted in psychiatric brain
expression studies
50,64,65
as well as in other research
areas.
77
Multiplicity is always a concern when performing
microarray analysis and many correction procedures
have been developed to address it such as the
Bonferroni-method or false discovery rate-based
methods.
78
However, these methods as commonly
used, assume independence of the hypotheses being
tested.
79
This is far from reality in the context of gene
expression in brain tissue, where there is extensive
multicollinearity between probe-sets as a result of
genes in pathways, or those implicated in a particular
molecular function, which can be regulated in a
coordinated manner. For instance, many researchers
have found not genes but families of genes or
pathways as being implicated in psychiatric disorders
in the past.
62,64,65,76,80–85
One additional consideration
for this research was the distinction between de-
pressed and non-depressed suicides, permitting the
evaluation of depression-specific effects on gene
expression separately from suicide-specific effects.
The observation of a disproportionate number of
genes identified as differentially expressed between
Color bar
–20 2
6
4
2
0
–2
–4
–6
E1:17,52%
E0:35,22%
–10 –50 510
Control
Suicid
e
SMD
a
b
C
C
C
C
C
C
C
S
S
S
S
S
SMD
SMD
SMD
SMD
SMD
SMD
SMD
SMD
SMD
Figure 5 BA24 gene expression patterns. (a) Clustered
image map (CIM) of the differentially expressed genes in
BA24. Both expression patterns in individuals and genes
were clustered. The color and intensity indicate direction
and level of change: blue spectrum colors indicate down-
regulated expression, whereas red spectrum colors indicate
upregulated expression. (b) PCA based on the differentially
expressed genes. The color and intensity indicate direction
and level of change: blue spectrum colors indicate down-
regulated expression, whereas red spectrum colors indicate
upregulated expression (online version only).
Color bar
–202
4
2
0
–2
–4
E1:17,31%
E0:29,43%
–8–6–4–202468
Control
Suicide
SMD
a
b
C
C
C
C
C
C
C
C
S
S
S
S
S
S
S
SMD
SMD
SMD
SMD
SMD
SMD
SMD
SMD
SMD
SMD
Figure 6 BA29 gene-expression patterns. (a) CIM of the
differentially expressed genes in BA29. Both expression
patterns in individuals and genes were clustered. The color
and intensity indicate direction and level of change: blue
spectrum colors indicate downregulated expression,
whereas red spectrum colors indicate upregulated expres-
sion. (b) PCA based on the differentially expressed genes.
The color and intensity indicate direction and level of
change: blue spectrum colors indicate downregulated
expression, whereas red spectrum colors indicate upregu-
lated expression (online version only).
Patterns of gene expression in the limbic system of suicides
A Sequeira et al
11
Molecular Psychiatry
Table 4 Genes significantly affected by the history of substance dependence or abuse (chronic substance effects) and positive substance intoxication as per toxicological
result for alcohol or cocaine (acute substance effects) in the amygdala, hippocampus, BA24 and BA29
Probeset Gene title Symbol Chromosome Substance effects
Groups Chronic Acute
df F P*dfF Pdf F P
Amygdala
219855_at Nudix (nucleoside diphosphate linked
moiety X)-type motif 11
NUDT11 Xp11.22 2 11.525 0.000 1 8.874 0.007 1 6.104 0.021
223497_at KIAA1411 KIAA1411 6q12-q13 2 10.511 0.001 1 2.388 0.136 1 12.133 0.002
225919_s_at Chromosome 9 open reading frame 72 C9orf72 9p21.2 2 3.574 0.044 1 9.640 0.005 1 0.771 0.389
226406_at Chromosome 18 open reading frame 25 C18orf25 18q21.1 2 9.360 0.001 1 0.103 0.752 1 16.885 0.000
239425_at Full length insert cDNA clone ZC34E11 1 2 11.306 0.000 1 1.846 0.187 1 10.178 0.004
239437_at Transcribed locus 6 2 7.152 0.004 1 5.937 0.023 1 14.912 0.001
Hippo
202780_at 3-oxoacid CoA transferase 1 OXCT1 5p13.1 2 14.357 0.000 1 5.016 0.039 1 10.543 0.005
204258_at Chromodomain helicase DNA
binding-protein 1
CHD1 5q15-q21 2 11.834 0.001 1 7.676 0.013 1 10.944 0.004
210176_at Toll-like receptor 1 TLR1 4p14 2 12.077 0.001 1 1.749 0.204 1 9.115 0.008
212262_at Quaking homolog, KH domain RNA
binding (mouse)
QKI 6q26-27 2 20.340 0.000 1 10.686 0.005 1 6.355 0.022
219269_at Hypothetical protein FLJ21616 FLJ21616 8p21.1 2 10.775 0.001 1 12.002 0.003 1 1.707 0.209
223880_x_at Chromosome 20 open reading frame 24 C20orf24 20q11.23 2 12.852 0.000 1 9.985 0.006 1 8.341 0.010
227450_at Hypothetical protein FLJ32115 FLJ32115 12p12.3 2 17.002 0.000 1 10.596 0.005 1 10.475 0.005
228549_at KIAA0792 gene product KIAA0792 2 9.882 0.001 1 9.793 0.006 1 0.415 0.528
229966_at Ewing sarcoma breakpoint region 1 EWSR1 22q12.2 2 11.193 0.001 1 10.866 0.004 1 3.943 0.063
235366_at Zinc-finger protein 10 ZNF10 12q24.33 2 11.702 0.001 1 13.546 0.002 1 3.837 0.067
91816_f_at Ring-finger and KH domain-containing 1 RKHD1 19p13.3 2 11.926 0.001 1 8.789 0.009 1 1.095 0.310
BA24
52837_at KIAA1644 protein KIAA1644 2 8.426 0.003 1 0.309 0.586 1 9.014 0.008
BA29
204544_at Hermansky–Pudlak syndrome 5 HPS5 11p14 2 13.681 0.000 1 14.823 0.001 1 9.748 0.005
241876_at Mdm4, transformed 3T3 cell double
minute 4, p53-binding protein (mouse)
MDM4 1q32 2 12.587 0.000 1 11.142 0.003 1 1.647 0.214
Corrected P-values (*P), after controlling for the possible confounder effect of substance dependence/abuse and P-values associated with the history of substance
dependence or abuse (Chronic) and positive toxicological result (Acute) for alcohol or cocaine are shown.
Patterns of gene expression in the limbic system of suicides
A Sequeira et al
12
Molecular Psychiatry
the suicide groups in the hippocampus is clearly
reflected in the PCA, with the top 10 eigen values for
the first component arising from genes differentially
expressed between the depressed and non-depressed
suicide groups. This contrast between suicide groups
is consistent with the prominent role of the highly
plastic hippocampus in depression and stress re-
sponse,
20,54
discriminating between depressive and
non-depressive states for a subset of differentially
expressed genes. A gene ontology analysis of probes
that were significantly differentially expressed bet-
ween the two suicide groups in the hippocampus
reveals a strong overrepresentation of factors involved
in transcriptional regulation and metabolism, similar
to the result including all comparisons in the
hippocampus, but with a much higher degree of
significance. The enrichment of factors involved in
metabolic processes may outline a differential stress
response between the suicide groups, whereas the
preponderance of transcriptional regulators may act
on diverse networks of additional genes, enhancing
the apparent difference between these two groups in
the hippocampus. In addition, the gene expression
pattern in the hippocampus may be broadly related to
long-term changes caused by a recurrent depressive
state, this being contrary to changes brought about
by a more transient and excitable state for the non-
depressed suicides. A more focused and critical
investigation of the hippocampus in further suicide
victims will help to discriminate between these
possibilities.
Amongst the genes validated in the four limbic
regions, several play fundamental roles in generalized
neurotransmission, as in the case of APP-like protein
2 (APLP2), the absence of which in knockout mice is
associated with a reduction in both density and
number of docked vesicles at the active zone.
86
Both
APLP2 and APP are processed by the product of the
also identified BACE1 gene,
87
exposing a pathway
considered of primary importance in the pathogenesis
of Alzheimer’s disease. The apparent upregulation of
synaptotagmin 4 (SYT4, a presynaptic calcium-sensor
and regulator of synaptic release) gene expression in
the hippocampus of depressed suicide victims paral-
lels findings in the SYT4 knockout mouse, which
displays reduced levels of anxiety and depression-
like behavior, as well as altered short-term plasticity
(CA1) and hippocampal-dependent memory,
88,89
and
the upregulated hippocampal expression of ADCY8
in non-depressed suicides compared with controls
integrates with a convincing body of research
demonstrating perturbed cAMP signaling in bipolar
disorder,
90
depression
91
and suicide.
92–94
These genes
constitute interesting avenues for further investi-
gation.
Several gabaergic system genes were identified as
differentially expressed in this investigation, in both
BA24 and hippocampus, drawing attention to a
possible gabaergic dysfunction in the limbic system
of suicidal and depressive individuals. Two genes are
of particular interest, GABA A receptor, a-1 (GABRA1)
and GABA A receptor, b-1 (GABRB1) (Table 3), as
GABA receptors mRNA levels have been associated
previously with depression and suicidality.
95
Inhibi-
tory neurotransmission in the mammalian brain is
mainly accomplished by gabaergic neurons, respon-
sible for the release of GABA.
96
GABA neurotrans-
mission modulates the activity of noradrenergic,
dopaminergic and serotonergic systems.
96
Clinical
data have pointed to an alteration in gabaergic
neurotransmission in mood disorders and more
specifically in major depression.
97
Thus, cerebrosp-
inal fluid and plasma studies have observed altered
levels of GABA in depressed patients. Also, SSRIs are
known to increase GABA levels in the brain of
depressed patients.
98
Finally, our results also confirm
the recent findings of another group concerning gene
expression abnormalities in GABA signal transmis-
sion in the cerebral cortex of subjects, who had
suffered from depression and more specifically
GABA(A) and GABA(B) alterations in individuals
who died by suicide suggesting their potential role
in suicidality.
62
Our findings together with previous
studies clearly point to an alteration of gabaergic
neurotransmission in suicide and major depression in
the context of suicide and offers new potential
pharmacological targets for the treatment of such
complex disorders.
Real-time PCR has been widely used in the confir-
mation of findings from microarray studies owing to
its high sensitivity and precision. However, although
these advantages may be significant, a number of
technique and analysis-specific parameters capable of
greatly influencing the final result have recently been
discussed,
99
including factors such as quality of the
template, the reverse-transcription step, selection of
endogenous controls, and the data analysis approach
employed. Current research has emphasized the need
for multiple control genes for relative quantifica-
tion
100
owing to the inconsistence in expression of
what were considered previously as ‘housekeeping’
genes. Rigorous sample quality control and two
reference genes were used in this study, with the
real-time fold changes and correlations between
microarray and real-time data supporting the valida-
tion of the most significant results from the micro-
array component. The correlation between microarray
and real-time data could at first sight seem modest,
but one has to take into account the fact that this RT-
PCR assays were not carried out in the same RNA
sample, but rather on RNA extracted from additional
samples from the same subjects obtained from adja-
cent tissue to that used for in the original microarray
experiments. This is different from what is usually
performed in most microarray studies, which use the
same RNA sample. By doing our procedure, we are
not only validating the microarray result, but also
the intra subject reproducibility. Finally, because the
purpose of the RT-PCR was solely a technical
replication of the results obtained in the microarray,
the biological replication was obtained by using
multiple samples from different subjects, a slightly
Patterns of gene expression in the limbic system of suicides
A Sequeira et al
13
Molecular Psychiatry
less conservative criteria for RNA quality was used for
the RT-PCR than for the microarray. As our RT-PCR
results correlate positively with the microarray data,
even when using adjacent samples from the same
subjects for both experiments, we can consider with
an acceptable degree of confidence that issues related
to RNA integrity were unlikely to be responsible for
our results.
Microarray experiments should be regarded as
screening assays capable of shedding light onto
biological processes involved in complex conditions
such as those investigated in this study. As such, the
sets of differentially expressed genes obtained in each
region constitute interesting targets for future studies
focused on suicide and major depression. To our
knowledge this investigation represents the first gene
expression study on suicides and depressed suicides
examining genome-wide alterations in limbic brain
regions. The expression profile in the hippocampus
underlies the importance of this structure in major
depression in the context of suicide, and implicates a
fundamental role for alterations of the second mes-
senger systems. Additionally, our results confirm
previous evidence pointing to alterations of gabaergic
neurotransmission in suicide and major depression,
offering new avenues in the study, and possibly
treatment, of such complex conditions. Further
studies are warranted to confirm these results not
only at the mRNA level, but also at the protein and
functional level, as well as the link between mole-
cular alterations with symptoms and risk factors
associated with suicide and with major depression.
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