Title: The Endogenous and Reactive Depression Subtypes Revisited: Integrative animal
and human mRNA studies point at different molecular mechanism involved in the
pathogenesis of Major Depressive Disorder.
1
Karim Malki1, Maria Grazia Tosto1,2, Robert Keers , Anbarasu Lourdusamy3, Lucia Carboni4,
Enrico Domenici5,6, Ian Craig1, Rudolf Uher1,7, Peter McGuffin1, Leonard C. Schalkwyk1
1
King’s College London, MRC Social, Genetic and Developmental Psychiatry Centre, at
Institute of Psychiatry, UK
2
University of York, Department of Psychology
3
Queen's Medical Centre, University of Nottingham
4
Department of Biology, Psychiatry CEDD, GlaxoSmithKline, Verona, Italy
5
Center of Excellence for Drug Discovery in Psychiatry, GlaxoSmithKline Medicines
Research Centre, Verona, Italy,
6
Pharma Research and Early Development, F. Hoffmann–La Roche, Basel, Switzerland
7
Department of Psychiatry, Dalhousie University, Halifax NS, Canada
*Corresponding Author
Institute of Psychiatry
SGDP Research Centre (PO80)
De Crespigny Park
Denmark Hill
London SE5 8AF
United Kingdom
Tel: +44(0)207 848 0918
Fax: +44(0)207 848 0866
email: karim.malki@iop.kcl.ac.uk
ABSTRACT
Background:
Clinicians have long hypothesised that the way into depression (MDD) can point at the way
out, yet current diagnostic algorithms are centred on counting symptoms and are independent
of any etiological considerations. We investigated the molecular mechanisms underpinning
different types of stress that are conducive to depression-like behaviour in 3 rodent models of
depression and translate findings in a matching human post-mortem mRNA study.
Methods: Affymetrix mouse whole-genome oligonucleotide arrays were used to measure
gene expression from hippocampal tissues of 144 mice from the GENDEP project. The study
used four inbred mouse strains and two depressogenic ‘stress’ protocols (maternal separation
and Unpredictable Chronic Mild Stress) to model “reactive” depression. Stress-related
mRNA differences in mouse were compared with a parallel mRNA study using Flinders
Sensitive and Resistant rat lines as a model of “endogenous” depression. Convergent genes
differentially expressed across the animal studies were used to inform candidate gene
selection in a human mRNA post-mortem case control study from the Stanley Brain
Consortium.
Results: In the mouse ‘reactive’ model, the expression of 350 genes changed in response to
early stresses and 370 in response to late stresses. A minimal genetic overlap (less than 8.8%)
was detected in response to both stress protocols, but 30% of these genes (21) were also
differentially regulated in the ‘endogenous’ rat study. This overlap is significantly greater
than expected by chance. The VAMP-2 gene, differentially expressed across the rodent
studies, was also significantly altered in the human study after correcting for multiple testing.
Conclusions: The results suggest that different molecular mechanisms underpin
phenotypically similar effects of early and late stressors. The expression of the VAMP-2 gene
was altered across all animal studies and in the human study. The gene has previously been
associated with Axis-I disorders including MDD, bipolar Depression, Schizophrenia and with
antidepressant treatment response. The implication for disease classification, clinical
diagnosis, individualized prescription of antidepressants and future human pharmacogenetic
and pharmacogenomic studies are discussed.
Background
Pharmacotherapy with antidepressants remains the most popular treatment strategy
for major depressive disorder (MDD). Nevertheless, response is heterogeneous with fewer
than half of all patients achieving remission following the first course of treatment (1, 2).
With no robust predictors of treatment response, prescription of medication currently follows
a trial and error protocol, which is both long and costly, and may have a negative effect on
long-term outcome (3). It has been hypothesised that heterogeneity in treatment response may
be partially driven by aetiological heterogeneity in MDD. This suggests that identifying the
causes of MDD and their biological substrate may be key to understanding and predicting
response to treatment (4).
It has long been suggested that the presence or absence of stress prior to the onset of
MDD results in two aetiologically distinct subgroups of the disorder. Early studies in which
these subtypes were categorised as ‘reactive’ (occurring as the result of a stressor) or
‘endogenous’ (occurring in the absence of stress), suggested that those with ‘endogenous’
depression responded more favourably to tricyclic antidepressants (TCAs) than serotonin
reuptake inhibitors (SSRIs) (5). While the validity of these subtypes remains unclear, some
studies continue to suggest that both distal stress (occurring early in life (6)) and proximal
stress (occurring near the onset of a depressive episode (7) (8)) are predictive of treatment
response.
The mechanism by which distal or proximal stressors may lead to depressive
symptoms is not fully understood. However, several animal studies suggest that exposure to
stress may have long lasting effects on gene expression in the hippocampus (9-12). These
studies also highlight the importance of the timing of adversity and suggest that early and late
stressors may have differential tissue-specific effects on gene-expression. Taken in unison,
existing literature indicates that the pathophysiological processes underlying MDD (and
therefore response to treatment) may differ according not only to the presence or absence of a
stressor, but also by the timing of adversity (early vs. late stress).
We investigated this hypothesis by exploring hippocampal gene-expression (mRNA)
differences in three animal models of depression chosen to represent ‘reactive’ and
‘endogenous’ depression. In the ‘reactive’ depression model, mice were exposed to either
early stress (maternal separation) or later stressors (unpredictable chronic mild stress).
Flinders sensitive rats, which show congenital depression-like behaviour, were used to model
‘endogenous’ depression.
Whole genome transcription profile from disease relevant brain tissues in animals
may provide valuable support and important information on the molecular mechanisms that
may be relevant in humans. However the specific features of psychiatric illnesses means that
molecular mechanism uncovered in animal models are only suggestive and still need to be
validated in human studies(13, 14). We therefore used findings from the animal models to
inform probe set prioritisation in a comparable human post-mortem case-control study on
depression from the Stanley Brain Consortium. Specifically, we hypothesise that a set of
genes that show concordant expression differences in response to reactive and endogenous
depression models in the rodent studies may also be differentially regulated in human.
METHODS
DESIGN
Genome-wide expression profiling of the hippocampus (HIP) from two studies from the
rodent arm of the GENDEP study (http://genedep.iop.kcl.ac.uk) was used to inform candidate
gene selection in a comparable human post-mortem, case-control study on MDD from the
Stanley Brain Consortium. The mouse study used 144 animals from four strains of wellcharacterised inbred mice to model individual variation in humans. The mice were subjected
to one of two stress protocols and a control condition (maternal separation (MD) – ‘early
stress’, chronic mild stress (CMS) – ‘late stress’ - or control condition (ENV)) to model
“reactive” depression. Findings from the mouse study were cross validated in a parallel rat
study that compared hippocampal (HIP) mRNA differences between Flinders Sensitive and
Flinders Resistant rat lines as model of “endogenous” depression. Lastly, genes differentially
expressed in response to both stress protocols in the mouse study and in the rat study were
used to inform probe set selection in comparable mRNA expression study in human.
Animals
144 Male and female mice from four different strains ((129S1/SvImJ, C57LB/6J, DBA/2J
and FVB/NJ) were bred in the barrier unit at the Institute of Psychiatry, London UK. Weaning
took place when the animals were 21 to 28 days old. Animals were group-housed under
standard condition with 12/12 hr. light/dark cycle, 22 ± 11°C, food and water ad libitum. A
total of 144 animals were sacrificed by cervical dislocation. Hippocampus, liver and spleen
were dissected following previously published protocols. All housing and experimental
procedures were carried out in accordance with the UK Home Office Animals (Scientific
Procedures) Act 1986.
A total of 39 animals from two cohorts of Flinders Sensitive Lines and Flinders Resistant
Lines (22 FRL and 17 FSL) were bred and maintained at Karolinska Institutet (Stockholm)
and housed under standard room temperature (22 ± 1 °C), relative humidity (45–55%), and a
12 hr. light/dark schedule (light on at 07.00 a.m.). Food and water were available ad libitum.
The study was conducted as part of a parallel GENDEP investigation. The Stockholm's
Ethical Committee for Protection of Animals approved the study and all procedures were
conducted in conformity with the Karolinska Institutet's guidelines for the care and use
laboratory animals, which follows the European Communities Council Directive of 24
November 1986. Additional information on the rat study is available elsewhere(15).
UCMS (Unpredictable Chronic Mild Stress)
In mouse, late stress was modeled using an Unpredictable Chronic Mild Stress (UCMS)
paradigm. A third of the 144 mice (48 male and female mice) were exposed to varying
stressors on a daily basis for a period of 2 weeks. Exposure to UCMS commenced when the
animals were 10 weeks of age. The UCSM protocols include exposure to different stressors
each day in a pseudorandom order. The stressors in the UCMS regime were based on
previously published protocols including 2 hours of home cage tilting at 45 degrees, damp
bedding for 4 hours, cage switching for 2 hours, flooded cage for 10 minutes, altered length
and time of light–dark cycle and air-puff(16). Animals were exposed to either one or two
stressor each day for varying length of time (Figure 1). All UCMS-exposed mice were tested
and maintained under standard laboratory condition but were single housed. The mice body
weight, boli, coat state were monitored at regular intervals. Following UCMS regimen, a set
of animals was tested with a battery of behavioural test including Porsolt as an index of
UCMS-evoked depressive-behaviour(17). However all animals for used for this mRNA
characterisation were not behaviourally tested to control for the potential stressor effects of
the tests.
MS (Maternal Separation)
A maternal separation protocol has been applied to a subset (48) of mice as a model of early
stress in humans. A single 24-hour separation of the pup from the dam at PND 9 protocol
was chosen to elicit a sufficiently strong biological response. Day of birth was defined as
PND 0 for that particular litter. Litters of each strain were randomly allocated to the MS,
UCMS or control group. On postnatal day 9 the dam was removed from the litter for 24
hours. The litter was kept on a heating pad in their home cage at 33°C ± 2°C in a different
room than the dam in order to avoid contact through vocalization. Separated pups did not
have access to food or water during their separation period. Litters were always separated and
reunited with the mother during the first half of the light phase. The first hour after reuniting
the litter with the mother was videotaped. Litters were of different sizes and when possible
each litter came from a different breeding pair. A more detailed description of the litters is
published elsewhere(18).
Genetic model of Depression
Flinders Sensitive Lines (FSL) and Flinders Resistant Lines (FRL) rats represent a promising
genetic animal model of depression(19-22). Flinders Lines are strains originally obtained by
selective breeding of out-bred Sprague-Dawley rats (SD), according to their resistance or
sensitivity to anticholinesterase diisopropyl fluorophosphates treatment(23). FSL are
congenitally more sensitive to DFP and cholinergic agonists than FRL, which is a
neurobiological feature shared with depressed cases in humans(24). They also show many
behavioural similarities to human depressed patients including decreased psychomotor
activity and appetite, cholinergic hypersensitivity, immune and sleep abnormalities including
delay in REM sleep but preserved cognitive function and hedonic response(13).
Human Sample:
The human samples used in this study were donated to the Stanley Foundation Brain
Collection at the Department of Psychiatry, University of the Health Sciences, Betheda, MD,
USA and have been made available to researchers world-wide. The primary transcriptionwide analysis was performed and described by Iwamato and colleagues(25). For consistency
and quality assurance, the same subset has been used without additions or subtractions of
cases. All data has been processed from raw files. The samples used consist of post-mortem
prefrontal cortex from the Stanley Foundation Neuropathology Consortium from deceased
patients affected with major depression disorder and carefully matched controls. Exclusion
criteria include poor mRNA quality, age (>65). A total of 26 samples, 11 cases and 15
controls were used congruent with the primary data analysis (Table 1). Clinical diagnosis of
MDD was made following DSM-IV diagnostic guideless and reviewed independently by a
pathologist and psychiatrist. Additional information on the human sample can be found in the
Iwamato and colleague paper(25).
mRNA extraction
Mouse brain, liver and spleen were dissected from each animal and frozen on dry ice. Total
RNA was extracted from frozen hippocampal tissue and 3-ug RNA was processed using the
One Cycle Target Labelling kit (Affymetrix, Santa Clara, California) and hybridized to the
mouse MOE430v2 Gene Expression Array (Affymetrix) following standard Affymetrix
protocols. Hippocampal mRNA extraction from Flinders rats was performed by another
participating group from the GENDEP project(26). Briefly cRNA probes were obtained and
hybridised to Affymetrix Rat Genome 230 2.0 using Affymetrix’s One-Cycle Eukaryotic
Target Labelling Assay protocol. Protocols used for the human post-mortem mRNA
extraction are describe in detail in the paper by Iwamato and colleagues(27). Briefly, total
RNA was extracted from 0.1g of frozen prefrontal cortex tissues using Trizol (Invitrogen,
Groningen, The Netherlands). A total of 8-10mg of mRNA was reverse transcribed and
synthesised into cDNA, hybridized onto Affymetrix HU95A oligonucleotide arrays and
scanned using an HP GeneArray scanner (Hewlett-Packard, Palo Alto, CA, USA).
Statistical Analysis of Microarray Data
Probe intensity data from 144 Affymetrix mouse whole-genome oligonucleotide arrays
(MOE 430 v2) was normalized and summarized using Robust Multichip Average (RMA
method)(28). Probe sets that were systematically absent (based on the MAS 5.0 detection
present/absent call) across all the arrays were removed leaving 37,231 out of the original
45,101 probe sets(29). A battery of quality control metrics and exploratory analysis on the
144 arrays identified ten arrays that differed significantly in quality. These arrays were
removed for the purpose of the subsequent analysis. Normalized expression values were
adjusted for sex, dose, and drug and the residuals were carried forward for analysis
implementing
the
following
regression
equation
in
R
(http://cran.r-project.org/),
Rijkl=Drugi+Dosej+Sexk+el.
In order to identify genes differentially expressed in response to early and late stress
protocols we performed two sets of analyses. First we compared normalized gene expression
measurements between maternally separated animal (MS) and control (CON). Second we
compared normalized gene expression measurements between Unpredictable Chronic Mild
Stress (UCMS) and control (CON). Differences were statistically evaluated using the nonparametric algorithms implemented in RankProd package in R environment (http://www.rproject.org/)(30). RankProd enabled us to combine datasets from four different strains using a
meta-analysis approach with the RPadvance function. This allowed us to circumvent issues
arising from the predominant strain effects by evaluating differences within each strain first.
Genes differentially expressed in a single strain were analyzed using rank product (RP)
function from the same package, using the ‘data from single origin’ option. The p-values
were calculated with 1,000,000 permutations, and multiple testing was taken into account by
using the percentage of false prediction at the very conservative threshold of pfp < 0.001. A
common method to control for the number of rejected hypothesis in ‘omics’ study is to
compute and report the false discovery rate (FDR) as proposed by Benjamini and Hochberg.
The RankProd package returns proportion of false positive (PDP) which is a method
proposed by Fernando and colleagues. Contrary to FDR, PDP does not rely on the correlation
between tests and the number of tests performed(31). Although PFP and FDR are often
equated, the two methods differ in that PFP controls the proportion of accumulated false
positives while FDR controls the expected proportion of false positive. FDR is not the best
method to use in cases where there is a relationship between variables, which in mRNA
studies is generally driven by genetic regulatory pathways and cross hybridization. We
therefore corrected using the PFP method across all studies where we use the RankProd
algorithim. The genes significantly altered were identified by PANTHER classification
system (http://www.pantherdb.org). Genes with pfp < 0.001 were subsequently uploaded to
the ingenuity database for pathway analysis with the Ingenuty Pathway Analysis (IPA)
software (http://www.ingenuity.com/).
Expression data from FSL and FRL animals have been made available on the Gene
Expression Omnibus (GEO; accession number GS2088, http://www.ncbi.nlm.nih.gov/geo).
Data has been processed from raw .CEL files to ensure consistency of data analysis across all
animal studies. To control for potential batch effects we combined the rat datasets from two
cohorts using the ComBat function built into the inSilicoMerging package for the R
environment(32).
Probe sets were normalized and summarized using Robust Multichip
Average (RMA method). Probe sets that were systematically absent (based on the MAS 5.0
absent/present detection call) were removed. Probe-set summaries from FSL and FRL were
then compared using the RankProd non-parametric algorithm implemented in R using the
PRadvance function and single origin option. P-values were evaluated using 1,000,000
permutations. A conservative false discovery rate (pfp) threshold of p<0.001 and a change
fold >1.5 was used. Probe sets that met the statistical thresholds were subsequently annotated
using PANTHER (http://www.pantherdb.org) to obtain a list of gene symbols. We then
matched all genes differentially expressed across all rodent studies using scripts written in
Python (http://www.python.org/). Convergent genes differentially expressed across all rodent
studies were subsequently analyzed using the Ingenuity Pathway Analysis (IPA) software.
Lastly, all genes differentially expressed in response to both “reactive” and “endogenous”
models of depression were used to inform probe set selection in the human study.
Raw scores from 26 Affymetrix human oligonucleotide arrays (HU95A) were normalized and
summarized into probe sets using the Robust Multichip Average (RMA) method, which
returned log2 transformed intensities (28). Intensity distributions, profile correlations and
quality control metrics were applied. MAS 5.0 expression values were calculated based on
scaling to a target intensity of 100, then transformed by Log2 and calls were computed using
the MAS5.0 present/absent algorithm. Affymetrix HU95A incorporates over 12000 probe
sets, tagging the expression of over 5000 well-characterized genes. Human genes, ortholog to
genes differentially expressed across all three rodent studies, were obtained using the Mouse
Genome Informatics orthology query (http:// www.informatics.jax.org/). Affymetrix Netaffx
tool (www.affymetrix.com/analysis/index.affx) was used to identify probe sets on the HU95A
chip (Affymetrix) tagging the expression of the human genes. Expression differences
between human depressed cases and controls were evaluated using the RankProd nonparametric algorithm implemented in R using the single origin function. Genes were
considered differentially expressed at a stringent corrected significance threshold pfp < 0.05
using permutation testing with 1,000,000 permutations.
RESULTS
mRNA changes in response to early and late stresses
The Rankprod method was used to identify the most robustly differentially expressed genes
between ‘late’ (UCMS) stressed animals and control and between ‘early’ (MD) stressed
animals and control. Variance explained by the factors Sex, Dose and Drug was removed
prior to the analysis as described previously. We considered only those genes that show
consistency in the direction of change across all four strains. Inconsistency in the direction of
change indicates Stress x Strain interaction effects, which are not specific to our research
question. The results of this analysis uncovered 406 probe sets altered in response to UCMS
across all four strains. These probe tag the expression of 370 known genes in mouse. A
summary of genes uncovered from this analysis with a previously association with stress
response or MDD is presented in table 1. The results reveal a number of genes previously
associated with UCMS protocols and believed to play a role in the pathogenesis on MDD.
The same analysis was repeated to compare maternally separated animal (MD) and control.
The results from this analysis revealed 396 probe sets differentially regulated in response to
the maternal separation protocol. These probe sets could be mapped to 350 known genes in
mouse. A summary of the top genes differentially expressed in response to maternal
separation protocols is presented in table 2. We then explored the number of altered genes in
response to either ‘early’ or ‘late’ stressors as well as the genetic overlap between the two
conditions (figure 2). These were remarkably few. Only 67 genes, less than 8.8% of
significantly altered genes were in common between mice exposed to early and late stress
paradigms. The minimal genomic overlap suggests that the biological substrate underpinning
response to early and late stressors differs although it leads to phenotypically similar
depression-like behaviors.
In order to gain further understanding into differences between the molecular substrate
underpinning response to early and late stresses, genes differentially expressed for each of the
two
conditions
were
analyzed
using
Ingenuity
Pathway
Analysis
(IPA)
(http://www.ingenuity.com). IPA has been chosen for its ability to uncover gene networks
showing the molecular relationship between the genes presented. Each network revealed by
IPA is scored according to the fit of significant genes in each dataset(33). First, we explored
gene networks associated with ‘late’ UCMS protocols. A total of 350 genes from our
reference list were found on the IPA database. The top two functional networks identified by
IPA have a scores > 42 with 29 reference molecules included in the first network and 23 in
the second. Both networks uncovered are significantly associated with stress signaling
response. The most significant transcription regulators in the network include ELK1/2/4
TFIIA, SMARCB, CREB1 and THRB (see supplementary figure 1 and 2). We repeated the
pathway analysis with genes differentially expressed in response to ‘early’ (MD) stressors. A
total of 347 genes from our reference list were found on the IPA knowledge database. IPA
returned 3 networks with a score > 40. The associated functions of the top networks include
mRNA post-transcriptional modification, protein synthesis and cellular development. The
networks are associated with developmental and neurological disorders, which is a good
match to the “early” stress protocol used. The top-ranking network (see supplementary figure
3) includes 29 focus molecules from our reference gene set. The most prominent interacting
genes within this network are with the Yhwaz and Yhwag. These genes are of particular
interest as they have been systematically uncovered across several proteomic and
transcriptomic studies from the GENDEP project in both mouse and in rat(13, 26, 33, 34).
These genes show a direct interaction with the STK25 kinase, which plays a role in stress
response. The second network (supplementary figure 4) is composed of 27 molecules from
our reference data set. This network is centered on the NF-KB complex. The Nuclear factor-
kB (NF-kB) is a ubiquitous transcription factor involved in the regulation of gene expression
and cell stress response and cell proliferation. Interestingly NF-kB can be activated by
different stimuli, including cytokines (such as TNF-a and IL-1): this finding is congruent with
the inflammation hypothesis for MDD(35-39).
Stress-syndrome validation in Flinders rat lines
To gain an understanding of the similarities between stress-induced ‘reactive’ transcription
changes and a congenital ‘endogenous’ model of depression, we compared genes
differentially regulated in response to early (MD) and late stress (UCMS) with mRNA
differences between Flinders sensitive and resistant lines. Flinders lines are a genetic animal
model of depression that allow us to cross-validate stress-altered genes with in a parallel,
independent mRNA study where depressive-behaviors occur in the absence of environmental
stressors. The RankProd algorithm and conservative cut-offs described previously was used
to evaluated mRNA differences between Flinders Sensitive and Flinders Resistant lines. The
results revealed 715 down-regulated and 1145 up-regulated probe sets. To obtain a list of
gene names, probe sets obtained were subsequently annotated using PANTHER
(http://www.pantherdb.org). The probe sets tagged the expression of 501 down-regulated and
727 up-regulated genes. A total of 1228 genes were used for cross validation with the mouse
study. Firstly, we explored the genomic overlap between maternally deprived animals and
Flinders line rats. From a total of 350 genes differentially regulated in maternally deprived
mouse, a total of 65 genes (19%) were also differentially regulated in rat. The same
comparison was performed with genes differentially expressed in mice exposed to UCMS. A
total of 52 genes (11%) were differentially expressed between ‘late’ stress animal and
flinders. A compelling finding is that 21 genes are differentially expressed in rat and in both
early and late stressed mouse (figure 3). This is an important genetic overlap given that only
67 genes were commonly expressed between early and late stressed animals in the first place.
Validations in an independent, methodologically different study using a genetic model of
depression points at an important genetic overlap between stress-related and syndromerelated mechanisms. In order to gain further biological insight, genes significantly altered in
response to both stresses in mice and between Flinders Sensitive and Resistant lines were
carried forward for analysis using Ingenuity’s IPA system. All 21 genes were found in the
Ingenuity reference database. A significant network with a score > 40 consisting of over 55%
of the reference molecules (12/21) was revealed (figure 4). Among the genes in the pathway
4 genes (Ywhaz, Ppm1a, Nkfb and Mapk1) are of particular interest as they have been
previously reported across different “omics” GENDEP investigations(34, 40-43).
mRNA differences in human
From a total of 21 genes differentially expressed across all 3 rodent studies, 15 human
orthologs were found. The expression of these 15 genes is tagged by 21 probe sets on the
Affymetrix HU95A oligonucleotide array. The RankProd algorithm was used to evaluate
expression between post-mortem cases and controls. Out of a total of 15 genes, the VAMP-2
is significantly down regulated (supplementary figure 5) after correcting for the number of
multiple non-independent tests using a prediction of false discovery rate of pfp <0.05 (Table
3). In our study, the Vesicle-Associated Membrane Protein 2 (VAMP-2: Synaptobrevin2)
gene is significantly altered across all rodent studies and in the human study.
Discussion
The main objective of this study was to compare the genomic footprints of ‘early’ and ‘late’
stresses with a genetic model of depression and translate findings to a human study. We
modelled ‘endogenous’ and ‘reactive’ subtypes of depression in 3 rodent studies and used
convergent evidence from the animal models to inform candidate gene selection in a
comparable human study. First, the minimal genetic overlap uncovered between the two
different stress-paradigms in mouse points to different molecular aetiologies that may be used
to parse major depressive disorder into subtypes. The results show that the two distinct stress
mechanisms are conducive to a convergent set of depression-like symptoms but are
characterised by a different set of genes, gene networks and functional pathways. Early
exposure to stress modulates the expression of genes belonging to pathways associated with
neurodevelopmental mechanisms. These changes may condition an individual exposure to
later stresses and response to pharmacological and behavioural interventions later in life in
yet unclear ways. Conversely, late onset stresses are thought to act primarily on brain
neurochemistry with neurostructural changes occurring via cascading effects of
neurochemically-related mechanisms including neurogenesis and apostosis(44). One of the
more compelling finding from our study is the minimal genetic overlap between early and
late stresses (~8.8%). Differences in genomic signatures between the two experimental
groups point at different molecular aetiologies MDD. Interestingly, gene pathway analysis
returned plausible functional networks, with the more significant network for ‘early’ stressed
animals associated with neurodevelopmental disorders and those of ‘late’ stressed animals
associated with cell stress response and cell-signalling. The difference in molecular substrate
may offer an explanatory framework as to why some antidepressant work for some patients
and not others and why prescription of therapeutic drugs still follows a trial and error
protocol. The results from the animal studies suggest that phenotypic heterogeneity in
antidepressant treatment response could be driven by aetiological heterogeneity within the
disorder. Simply, the way into the disorder may alter the expression of different genes and
molecular targets that may or may not be a good match to the mechanism of action of the first
prescribe antidepressant drug.
Stress related mRNA changes associated with Depression
To date our understanding of the molecular aetiology of MDD has largely been informed by
the mechanism of action of antidepressant medications; in this sense cure is used to inform
cause. However this may not be the ideal approach to uncover the molecular substrates
underpinning the disorder. In this study we validated transcriptional changes in response to
stressful life event (as a model of ‘reactive’ type depression) with a genetic model of
depression based on a well-established paradigm that compares Flinders Sensitive and
Flinders Resistant lines. The results show that approximately 30% of the genes differentially
expressed between animals exposed to both ‘early’ and ‘late’ SLE are also differentially
expressed in Flinders rats. A large proportion of genes altered by stress are the same as those
altered in animals that show congenital, depression-like behaviours. This convergent set of
genes has been used to uncover pathways that may be associated with depressive symptoms
irrespectively of cause and could inform molecular targets for new drug discovery efforts; in
this sense cause could be used to inform cure.
We conducted pathway analysis on the set of genes differentially regulated across all three
rodent studies to extract further biological insight. The genes revealed a gene network that
shows a plausible functional relationship across the reference molecules uploaded to the IPA
software. Among the genes present in this network we find four genes of particular interest,
Ppm1a, Ywhaz, Nkfb and Mapk. The first gene, Ppm1a is of particular interest as we
previously reported that several single-nucleotide polymorphisms within this gene were
significantly associated with nortriptyline response in both a mouse study and in a parallel
human pharmacogenetic study(45). In humans, PPM1A down regulates TGF-beta signalling
and inhibits the stress-responsive JNK and p38 MAPK pathways that regulate cellular stress
response in eukaryotes. The tyrosine 3-monooxygenase/tryptophan 5-monooxygenase
activation protein (Ywhaz) has systematically been uncovered across several GENDEP
studies and appears to play a role both in the syndrome and in mediating response to
medication. Studies have shown that Ywhaz plays a role in cell proliferation and
neurogenesis, which is a current explanatory model of MDD(46-49). Moreover it interacts
with IRS1 protein and MAPK pathway by modulating the activation of JNK1 and p38 MAPK
both of which have been systematically associated with depressive mechanisms (49-55).
Lastly the Nfkb gene has extensively been associated with peripheral inflammation and is
consistent with the inflammation hypothesis for MDD(56).
Convergent Animal-Human Genes
Animal models are an attractive proposition for the study of mood disorders as they allow
access to disease relevant brain tissues and to control for environmental conditions. However,
given the nature and characteristic of psychiatric disorders, there are aspects of these illnesses
that can only be studied in humans. We therefore cross-validate the set of convergent genes
across all the rodent studies and in a matching human post-mortem mRNA studies on
depressed cases and controls. One gene, the VAMP-2 gene, remained significantly down
regulated after correcting for multiple testing in the human study. The expression of the
VAMP-2 gene has previously been found to be altered in both schizophrenia and bipolar
disorder within a combined microarray analysis of the Stanley Foundation's brain
collections(57). Moreover several other studies have implicated this gene in Axis-I
psychiatric disorders and in antidepressant treatment response(58-61). The vesicle-associated
membrane protein (VAMP-2; synaptobrevin2) plays a role in the molecular regulation of
transmitter release at the presynaptic plasma membrane. There are two isoforms of the
VAMP gene; VAMP-1 and VAMP-2. Each of the two isoforms are transcribed by two
separate genes and are expressed in the central nervous system. Previous studies have shown
that the VAMP2/synaptobrevin-2 gene is commonly increased in rat frontal cortex after
chronic antidepressant treatment and repeated ECT although the finding has not been
consistently replicated(62, 63).
Validity of current ICD10 and DSM V classification of MDD
From ICD 9, diagnosis by a binary system has been abandoned in favour of a unitary system
of diagnosis that focuses on symptom severity and persistence. The main virtue of adopting
this system is that it allows diagnosis to be made independently from any aetiological
considerations. Moreover, epidemiological studies suggest that depressive symptoms are
quantitatively distributed and a further advantage of a unitary system is that it solves the
problems of establishing categorical boundaries. Studies have also shown that diagnostic
stability over time of the diagnosis for “endogenous” and “reactive” depression is low(64).
Moreover the use of a binary classification holds no predictive validity for suicide ideation
and actualisation. While a symptom-centred diagnostic system may be preferred for clinical
applications the implication for individualized prescription of therapeutic drugs and research
purposes need to be considered. First, efforts to identify susceptibility loci for major
depression inevitably requires the recruitment of patients groups that are selected based on
current diagnostic criterions. We suggest that the consequences of adopting this diagnostic
criterion for scientific endeavours leads to a phenotype that may not be sufficiently accurate
to allow the detection of loci of small penetrance. In genome-wide association and genomewide pharmacogenetic studies any increase in power provided by a larger sample may be
partially offset by molecular heterogeneity within the sample group.
Although clinical
characteristic have been shown to be a poor predictor of responders and non-responders for
antidepressants drugs, there is current trend towards individualized prescription of
pharmacological agents in mental health. However reliable biomarkers are needed. Genome
wide pharmacogenetic association studies still represent an attractive proposition for the
development of individualized treatment strategies and to gain further understanding into the
molecular substrate underpinning antidepressant treatment response. However all the large
pharmacogenetic association studies on antidepressant response including GENDEP, MARS
and STAR*D have been unsuccessful in uncovering genome-wide significant genotypephenotype associations(65-70). One of the explanatory frameworks proposed is that even
larger sample sizes are needed to detect genetic variants of small penetrance. At the time of
writing, the primary report from the largest pharmacogenetic study of any psychotropic
medication NEWMEDS, a consortium project funded by the Innovations in Medicine
Initiative (IMI) of the European Commission as a joint enterprise with the European
Federation of Pharmaceutical Industries, was released(71). The study is the largest
pharmacogenetic study undertaken to date, and was powered to detect common genetic
variant that may predict response to commonly used classes of antidepressants in a clinically
meaningful way. The results of this study are clearly negative. Moreover a meta-analysis of
NEWMEDS and the Sequenced Treatment Alternatives to Relieve Depression (STAR*D),
which includes over 3000 individuals treated with antidepressants also yielded negative
findings. Furthermore, polygenic scoring found no convergence among multiple associations
in NEWMEDS and STAR*D. The combination of the two largest pharmacogenetic samples
makes this a definite study in the field of antidepressant pharmacogenetics. Taken in unison
the results from all current pharmacogenetic association studies demonstrate that it is
extremely unlikely that any previously reported or novel common genetic variant could be
used to inform antidepressant prescription. It is now clear that increase sample size is not
linked with increased detection rate. The results from our study suggest that any advantage in
statistical power provided by the larger sample size, may be compensated by increased noise
driven by the heterogeneity within the sample group. The inclusion of patient groups
diagnosed as moderately to severely depressed based on clinical characteristic independently
of any aetiological consideration may not be suitable for research endeavours.
Conclusion:
Using an animal model we have gained information that can potentially lead to a better
understanding on the pathophysiology of major depression. We have shown that time of onset
of stressful life events plays on different biological substrates that may account for some of
the heterogeneity in antidepressant treatment response. In animals, we have shown two
distinct paths leading to a common set of depression-like behaviors. Moreover, we have
shown that environmental stressors can also influence some of the same genes differentially
expressed in a congenital model of depression pointing to a potentially causal link between
stress and behavior. Depression remains a very complex phenotype that involves both genetic
and environmental factors. Moreover it remains a probabilistic rather than deterministic
syndrome that can occur even in the absence of stressful life events and independently of any
genetic risk liabilities. Conceptualizing the disorder for any given patient therefore remains
challenging and this has been used as justification for refusing to distinguish one depressed
patient from another. However, further understanding into the etiology and alternative
subtypes of depression could eventually be used to inform treatment choice. Moreover a
diagnostic system that is independent of etiological consideration may not be suitable to
recruit patient groups for research and drug-discovery endeavors. As of today, the failure of
genome wide pharmacogenetic and association studies in identifying biomarker’s that can
predict response to treatment in a meaningful way and uncover genotype-phenotype
associations reflect this notion.
Acknowledgements & Conflict of Interest Statement:
The Genome-Based Therapeutic Drugs for Depression study was funded by a European
Commission Framework 6 grant, EC Contract Ref: LSHB-CT-2003–503428. The Biomedical
Research Centre for Mental Health at the Institute of Psychiatry, King’s College London and
South London, and Maudsley National Health Service Foundation Trust (funded by the
National Institute for Health Research, Department of Health, United Kingdom) and
GlaxoSmithKline contributed by funding add-on projects at the London Centre. Prof. Peter
McGuffin, Dr. Enrico Domenici, and Dr. Lucia Carboni have received consultancy fees and
honoraria for participating in expert panels from pharmaceutical companies, including Roche
and GlaxoSmithKline. All other authors report no biomedical financial interests or potential
conflicts of interest.
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Figure Legend
Figure 1: The figure shows stress administration regime for the unpredictable chronic mild
stress paradigm. The duration of the stress regime was for two consecutive weeks and the
order of the different stressors was randomised. The figure shows the stressors and
time/duration of administration for each of the two weeks.
Figure 2: Venn diagram showing the number of genes significantly altered in response to
either early or late depressogenic protocol (maternal separation in yellow and unpredictable
chronic mild stress in red). A compelling finding is the limited number of overlapping genes
(~8.8%) suggesting that etiologically different molecular mechanisms underpin a congruent
set of behaviours.
Figure 4: Venn diagram showing the number of genes overlapping between mice exposed to
UCMS or MS across the two mouse studies and with the Flinders rat study. Only 67 genes
were differentially regulated in response to both early and late stressors pointing at minimal
genetic overlap. However many of these genes ~30% were also differentially regulated in an
endogenous rat model of depression. The replication of these genes in a different organism
that shows congenital depression-like symptoms, points at molecular mechanism that may
inform potential molecular mechanisms involved in the human pathology.
Figure 5: Pathway Analysis performed on converging genes differentially regulated in
response to different stresses in mouse and between different selected Flinders lines. The
pathway comprises over half the reference molecules uploaded to the Ingenuity database
system (12 out of the 21 reference molecules). The pathway implicates a number of genes
previously associated with MDD and antidepressant treatment response including Ppm1a,
Ywhaz, NkFb and Mapk.
Supplementary Figure 1: The most significant network returned from the Ingenuity
Pathway Analysis software for genes differentially expressed in response to Unpredictable
Chronic Mild Stress. The network consists of 29 reference molecules and is significantly
association with cell stress response.
Supplementary Figure 2: A second significant pathway with a score >42 returned by the
Ingenuity Pathway Analysis software. The pathway includes 23 reference molecules and it is
also associated with cell stress response. The pathway is centered on the ELK complex hub
and is of particular interest as it shows the VAMP-2 complex and its association with the Ntype calcium channel and potassium channel.
Supplementary Figure 3: The most significant network returned from the Ingenuity
Pathway Analysis software for genes differentially expressed in response to the maternal
separation depresssogenic protocol. Of particular interest is the presence of the Yhwaz
reference molecule. The Yhwaz gene has been systematically uncovered across several animal
studies and been shown to influence neurotransmission of dopamine by regulating exocytosis
or phosphorylation of synaptic proteins. The pathway consists of 29 reference molecules and
is association with cell stress response.
Supplementary Figure 4: Second pathway returned from the Ingenuity Pathway Analysis
software for genes differentially expressed in response to the maternal separation protocol.
This pathway includes 27 reference molecules and is cantered on the NF-κB hub. The
pathway is associated with cell proliferation and the NF-κB hub has been previously found to
be associated with inflammation. Activation of the NF-κB transcription family, by nuclear
translocation of cytoplasmic complexes, plays a central role in inflammation. Human studies
have shown that major depression patients with increased early life stress exhibit enhanced
inflammatory responsiveness to psychosocial stress.
Supplementary Figure 5: Identification of up and down regulated genes in the human
analysis using the RankProd algorithm. The only gene that survives correction of multiple
testing at the threshold of probability of false prediction (pfp) <0.05 is the VAMP-2 gene. The
genes is significantly down-regulated in the human study.
Table Legend
Table 1: Summary of genes found to be differentially expressed in response to the
unpredictable chronic mild stress protocols and previously associated with stress response. A
stringent cut-off of p< 1x10-04 and consistent directionality of fold change was used to
identify differentially expressed across all four strains.
Table 2: Summary of genes found to be differentially expressed in response to the
unpredictable chronic mild stress protocol. A stringent cut-off of p< 1x10-04 and consistent
directionality of fold change was used to identify differentially expressed across all four
strains.
Table 3: 15 human genes, orthologous to those differentially expressed across the rodent
studies were present on Affymetrix HU95A oligonucleotide array. The expression profile of
these genes is tagged by 21 probe sets. Expression differences between cases and control
were evaluated using the RankProd algorithm using probability of false positive (pfp) of less
the 0.05 to control for the number of multiple testing. The table shows Probe Set ID, Gene
Symbol, RankProd value, corrected pfp value and uncorrected p-value. The only gene that
survives correction for multiple testing in the human analysis is the VAMP-2 gene.
Table 1
Genes Dysregulated by UCMS
Transcript
Gene Name
1418687_at
1452453_a_at
1427663_a_at
1436983_at
1433733_a_at
1443805_at
1438892_at
1419580_at
1453994_at
1430436_at
1418240_at
1417949_at
1415899_at
1457899_at
1438403_s_at
1419568_at
1420931_at
1425459_at
1425014_at
1416505_at
1458176_at
1416211_a_at
1440001_at
1439940_at
1444489_at
1421924_at
1421225_a_at
1455876_at
1457357_at
Arc
Camk2a
Clk4
Crebbp
Cry1
Dact3
Dep1
Dlg4
Eml6
Fam115a
Gbp2
Ilf2
Junb
Kalrn
Malat1
Mapk1
Mapk8
Mtmr2
Nr2c2
Nr4a1
Per3
Ptn
Rian
Slc1a2
Slc25a12
Slc2a3
Slc4a4
Slc4a7
Tlk2
Pr. Rsum
2841.834
2834.213
4161.448
1498.852
5285.620
4920.751
3046.244
3239.403
5673.323
4086.744
3167.576
4243.511
3330.616
4503.738
1725.168
923.836
2498.977
4168.453
3897.542
4665.395
4870.404
4211.224
4837.821
2581.498
4744.455
3356.425
3960.423
4614.381
3989.909
c57
-0.242
0.247
-0.420
0.600
0.438
-0.339
0.157
-0.224
0.164
0.425
-0.183
-0.431
-0.246
0.238
-0.183
-0.704
-0.336
-0.344
0.420
-0.234
0.269
-0.439
0.284
0.547
0.293
-0.435
0.408
0.313
0.288
Log 2 Fold Change
DBA
FVB
-0.279
0.276
-0.025
0.156
0.113
-0.097
0.142
-0.115
0.194
0.025
-0.368
-0.112
-0.300
0.169
-0.464
-0.328
-0.180
-0.198
0.016
-0.148
0.168
-0.151
0.070
0.079
0.077
-0.125
0.160
0.158
0.100
-0.221
0.003
-0.196
0.176
0.070
-0.084
0.164
-0.177
0.104
0.069
-0.335
-0.115
-0.349
0.088
-0.248
-0.203
-0.268
-0.206
0.169
-0.225
0.106
-0.176
0.192
0.059
0.117
-0.202
0.073
0.209
0.059
129
Pfp -Value
-0.127
0.235
-0.289
0.566
0.238
-0.292
0.571
-0.299
0.189
0.434
-0.169
-0.279
-0.232
0.408
-0.139
-0.486
-0.193
-0.236
0.421
-0.161
0.222
-0.225
0.279
0.441
0.197
0.000
0.278
0.235
0.395
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
Table 2
Genes Dysregulated by MS
Transcript
Gene Name
1454655_at
1450392_at
1416250_at
1416332_at
1427663_a_at
1458518_at
1451977_at
1421142_s_at
1439717_at
1422223_at
1438441_at
1420931_at
1425459_at
1437660_at
1443970_at
1437213_at
1453750_x_at
1418015_at
1428462_at
1428905_at
1421346_a_at
1420867_at
1435770_at
1459737_s_at
1420833_at
1450308_a_at
1420816_at
1448219_a_at
Dgkd
Abca1
Btg2
Cirbp
Clk4
Cpeb2
Dyrk1a
Foxp1
Gabrg3
Grin2b
Id4
Mapk8
Mtmr2
Nktr
Ntrk3
Nudt21
Pitpnc1
Pum2
Ppp2r5e
Rraga
Slc6a6
Tmed2
Tmx4
Ttr
Vamp2
Xrn1
Ywhag
Ywhaz
Pr. Rsum
3024.390
3716.966
2390.318
3963.875
3977.651
2642.230
4954.256
3977.517
5191.066
4777.728
3829.228
2623.666
4660.997
5633.677
3929.819
4091.995
5481.080
3066.939
5555.808
2709.505
2560.666
2172.246
4098.309
1229.204
3820.922
2743.074
1838.774
3773.496
c57
DBA
0.276
0.014
-0.346
-0.301
-0.349
-0.336
-0.133
-0.369
-0.174
-0.220
0.313
-0.158
-0.283
-0.089
0.261
0.234
-0.305
-0.032
-0.212
-0.266
-0.421
-0.329
-0.197
0.678
-0.133
-0.175
-0.265
-0.314
Log 2 Fold Change
FVB
0.399
0.208
-0.301
-0.086
-0.215
-0.401
-0.206
-0.264
-0.254
-0.129
0.324
-0.373
-0.212
-0.008
0.388
0.294
-0.146
-0.362
-0.192
-0.447
-0.418
-0.291
-0.078
0.186
-0.172
-0.373
-0.294
-0.283
129
0.147
0.150
-0.161
-0.237
-0.271
-0.247
-0.235
-0.153
-0.169
-0.225
0.290
-0.164
-0.165
-0.178
0.117
0.040
-0.065
-0.146
-0.085
-0.169
-0.238
-0.457
-0.313
0.074
-0.256
-0.340
-0.419
-0.323
Pfp -Value
0.273
0.319
-0.500
-0.335
-0.127
-0.177
-0.168
-0.143
-0.021
-0.223
0.046
-0.333
-0.169
-0.226
0.254
0.018
-0.179
-0.438
-0.273
-0.322
-0.333
-0.250
-0.140
0.376
-0.244
-0.306
-0.362
-0.252
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
<1.00E-04
Table 3
Probe Set ID
1034_at
1035_g_at
1235_at
2018_at
296_at
297_g_at
32254_at
32531_at
32572_at
32761_at
34387_at
34642_at
36307_at
36760_at
38211_at
38710_at
39331_at
39725_at
40096_at
40125_at
968_i_at
Gene Symbol
TIMP3
TIMP3
YWHAZ
GJA1
TUBB2A
TUBB2A
VAMP2**
GJA1
USP9X
SRRM2
LPGAT1
YWHAZ
ARC
YWHAZ
ZBTB20
OTUB1
TUBB2A
RBM39
ATP5A1
CANX
USP9X
RP/Rsum
10.3564
10.788
8.1361
10.6102
8.1718
10.38
9.7002
5.6354
9.6037
11.6727
10.5963
6.7492
8.5526
9.8422
8.6008
9.566
8.2579
10.946
8.5727
8.2587
11.0827
pfp
1.0512
0.9069
1.8677
0.9224
1.4332
0.9872
0.0024
0.4128
1.0556
0.9074
0.9769
0.8804
1.0273
0.9712
0.8204
1.145
1.2097
0.888
0.9088
1.0086
0.8662
p.value
0.6398
0.7097
0.2436
0.6818
0.2493
0.6438
0.5228
0.018
0.5049
0.8285
0.6796
0.0766
0.3127
0.5489
0.321
0.4978
0.263
0.7336
0.3161
0.2631
0.7532
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