Translational neuroscience of schizophrenia: seeking a meeting of minds between mouse and man.
ABSTRACT Understanding the etiology of developmental brain disorders such as schizophrenia is critical for achieving advances in treatment and requires new research strategies that control for individual variation in genetic background, environmental challenges, and expression of phenotype. SYSGENET, a European systems genetics network for the study of complex genetic human diseases with mouse genetic reference populations, brought together in Helsinki a cross-disciplinary group of clinical and basic scientists and mouse geneticists to debate, formulate, and prioritize a strategy for future research based on mouse models. The main conclusions of this meeting are summarized here.
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ABSTRACT: We have applied the Neuro Behavior Ontology (NBO), an ontology for the annotation of behavioral gene functions and behavioral phenotypes, to the annotation of more than 1,000 genes in the mouse that are known to play a role in behavior. These annotations can be explored by researchers interested in genes involved in particular behaviors and used computationally to provide insights into the behavioral phenotypes resulting from differences in gene expression. We developed the OntoFUNC tool and have applied it to enrichment analyses over the NBO to provide high-level behavioral interpretations of gene expression datasets. The resulting increase in the number of gene annotations facilitates the identification of behavioral or neurologic processes by assisting the formulation of hypotheses about the relationships between gene, processes, and phenotypic manifestations resulting from behavioral observations.Mammalian Genome 11/2013; · 2.42 Impact Factor
- Molecular Psychiatry 02/2014; 19(2):144. · 15.15 Impact Factor
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ABSTRACT: Animal studies play a central role in the identification and testing of novel drugs for CNS disorders. In his longstanding career, Berend Olivier has significantly contributed to CNS drug discovery by applying and supporting novel views and methodologies in the fields of behavioural neuroscience, pharmacology, and (epi-) genetics. Here we review and put forward some of these integrated approaches that have led to a productive collaboration and new insights into the genetic and epigenetic regulation of neurobehavioural traits related to psychiatric disorders.European journal of pharmacology. 08/2014;
, 102mr3 (2011);
3 Sci Transl Med
, et al. Martien J. Kas
Between Mouse and Man
Translational Neuroscience of Schizophrenia: Seeking a Meeting of Minds
for schizophrenia; a summary and the conclusions are presented.
A meeting held 9 June 2011 in Helsinki, Finland, discussed the requirements for creating useful mouse models
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Translational Neuroscience of Schizophrenia:
Seeking a Meeting of Minds Between Mouse and Man
Martien J. Kas,1* René S. Kahn,2David A. Collier,3John L. Waddington,4Jesper Ekelund,5
David J. Porteous,6Klaus Schughart,7Iiris Hovatta8,9
Understanding the etiology of developmental brain disorders such as schizophrenia is critical for achieving
advances in treatment and requires new research strategies that control for individual variation in genetic
background, environmental challenges, and expression of phenotype. SYSGENET, a European systems genetics
network for the study of complex genetic human diseases with mouse genetic reference populations, brought
together in Helsinki a cross-disciplinary group of clinical and basic scientists and mouse geneticists to debate,
formulate, and prioritize a strategy for future research based on mouse models. The main conclusions of this
meeting are summarized here.
Schizophrenia is a psychotic disorder characterized by positive and neg-
ative symptoms, including reality distortion (delusions and halluci-
nations), psychomotor poverty (poverty of speech, social withdrawal,
and blunting of affect), and disorganization (inappropriate affect and
thought disorder), together with cognitive deficits; negative symptoms
and cognitive deficits are the primary determinants of poor functional
outcome. Lifetime risk for schizophrenia is about 1%, and because of
its onset in early adulthood and severity, it causes considerable disabil-
ity to patients and high socioeconomic costs to society. Schizophrenia
is a complex disease influenced by both genetic and environmental fac-
tors, with heritability estimated at about 80%. In recent years, several
susceptibility genes have been identified in human cohorts, leading to
new insights into pathogenetic mechanisms of this neurodevelopmen-
tal disorder (1–3). However, current medications for schizophrenia are
only partially effective; for example, although they reduce psychotic
symptoms, current drugs are minimally effective in improving cogni-
tion (4) and induce a range of potentially life-threatening long-term
side effects. Therefore, there is a need for better treatment practices
for schizophrenia that target positive and negative symptoms and im-
prove cognitive deficits. Increased understanding of the neurobiological
mechanisms underlying schizophrenia should facilitate this task.
Merging knowledge from genetics, genomics, epidemiology, phys-
iology, and pharmacology, including both preclinical and clinical
studies, is needed to resolve core aspects of schizophrenia. In this
regard, studies using animal models can contribute considerably to
a better understanding of the biological processes that underlie dis-
ease risk and development. Experimental animal models will also be
required for the development of new, etiology-directed medication.
The mouse is well placed to address most of these requirements, by
virtue of its advanced genetics, understanding of developmental and
behavioral biology, short generation time, and low cost (5). In par-
ticular, the effects of targeted, experimental, and natural genetic var-
iations and their phenotypic consequences can be studied in mouse
populations or in genetically engineered lines, such as mouse gene
knockout lines (6, 7). However, to provide real insight and to be of
meaningful translational value, it is first essential to identify the core
biological phenotypes and mechanisms that underpin schizophrenia.
This challenge was the focus of the targeted workshop of SYSGENET
on cross-species studies of schizophrenia.
CORE FEATURES OF SCHIZOPHRENIA
Compromised function of the nervous system in schizophrenia is ev-
ident, on a population basis, as early as the first year of life when pa-
tients show slightly delayed developmental milestones such as walking
(8). Manifestations become more evident during early adolescence
(ages 11 to 16 years) and are characterized by cognitive decline and
social withdrawal. During late adolescence/young adulthood (16 to
25 years), the first symptoms of psychosis appear, most typically hal-
lucinations and delusions. Thus, the first material signs of the illness
are not the more obvious psychotic symptoms but, rather, the slow
but steady decline in cognitive functioning that precedes the onset of
psychosis by an average of 9 years (9, 10) and may continue to pro-
gress thereafter (11). Indeed, cognitive dysfunction constitutes not
only one of the core features of the illness (10) but also one of the
most intractable to treat (4). Although the words “dementia praecox,”
as Kraepelin named the disease he delineated in 1895, may not carry
a hopeful message, the “dementia,” that is, the cognitive decline, re-
flects a core process in the illness we currently call schizophrenia.
Not only does cognition worsen during the early course of schizo-
phrenia, there is accompanying loss of cerebral gray matter in excess
of what is seen with normal aging. Brain imaging studies in healthy
humans have revealed that the developing and aging human brain
1Department of Neuroscience and Pharmacology, University Medical Center Utrecht,
3584CG Utrecht, Netherlands.2Department of Psychiatry, Rudolf Magnus Institute of
Neuroscience, University Medical Center Utrecht, 3584CX Utrecht, Netherlands.3Social
Genetic and Developmental Psychiatry Centre, Kings College London, Institute of
Psychiatry, De Crespigny Park, Denmark Hill, London SE5 8AF, UK.4Molecular and
Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin 2, Ireland.5Depart-
ment of Psychiatry, University of Helsinki, Vaasa Hospital District and Mental Health
and Substance Abuse Services, National Institute of Health and Welfare, 00251 Helsinki,
Finland.6Medical Genetics Section, University of Edinburgh Centre for Molecular Medicine,
Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road,
Edinburgh EH4 2XU, UK.7Department of Infection Genetics, Helmholtz Centre for In-
fection Research and University of Veterinary Medicine Hannover, 38124 Braunschweig,
Germany.8Research Programs Unit, Molecular Neurology, Biomedicum-Helsinki and
Haartman Institute, Department of Medical Genetics, University of Helsinki, 00290 Helsinki,
Finland.9Mental Health and Substance Abuse Services, National Institute for Health and
Welfare, 00300 Helsinki, Finland.
*To whom correspondence should be addressed. E-mail: email@example.com
www.ScienceTranslationalMedicine.org28 September 2011 Vol 3 Issue 102 102mr3
on September 28, 2011
undergoes dynamic changes in volume over time. Specifically, abso-
lute brain volume increases up to early puberty and, thereafter, de-
clines before the age of 20 (11). Then, there is a short episode with
slight growth followed by a decline, until a stable brain volume is
achieved around the ages of 25 to 40 years. In contrast, at illness onset,
brain volume in schizophrenic patients is already reduced relative to
matched healthy controls; subsequently, such patients exhibit an ac-
celerated decrease in brain volume, especially in frontal and temporal
cortical brain areas (11). This progressive reduction in cortical volume
in schizophrenia can occur independent of medication (12), is herita-
ble (13), and is correlated with poor prognosis and psychosis severity
(14). Cannabis use, the strongest known environmental risk factor for
schizophrenia identified thus far, worsens gray matter brain volume
loss in schizophrenia (15, 16).
A recent study aimed to reduce phenotypic heterogeneity in a large
sample of psychosis patients, their relatives, and community controls
by using latent class analysis to analyze variation in Comprehensive
Assessment of Symptoms and History (CASH) lifetime-rated symp-
toms (17). This study revealed that variation in five continuous di-
mensions (disorganization, positive, negative, mania, and depression)
was accounted for by the presence of seven homogeneous classes
(Kraepelinian schizophrenia, affective psychosis, manic depression,
deficit nonpsychosis, depression, healthy, and no symptoms). This
analysis showed that almost all (85%) of these schizophrenic patients
were assigned to the Kraepelinian schizophrenia class, whereas the
remaining patients were assigned to the affective psychosis class. Analy-
ses of symptom variation revealed that the difference between schizo-
phrenia and affective psychosis within the patient sample is based on
the distinction between low and high levels of disorganization and
negative symptoms, rather than on the level of positive, psychotic
symptoms. Levels of disorganization and negative symptoms are also
associated with diminished cognitive performance and poor outcome,
suggesting that these may be relevant dimensions to model in mice.
Together, these findings indicate that schizophrenia is a complex
neurodevelopmental disease of cognitive decline associated with pro-
gressive brain loss, negative symptoms, and the emergence of psychotic
symptoms that lead to diagnosis. The presence of measurable physio-
logical parameters should make it possible to study well-defined pheno-
types in mouse populations and mutants and to determine the genetic
basis for premature, disease-related brain loss.
HUMAN GENETIC FINDINGS
Although the heritability of schizophrenia is high, at about 80% (18), it
has been challenging to identify predisposing variants for schizo-
phrenia in humans. Early studies using linkage mapping, cytogenetic
analysis, and candidate gene studies identified several putative suscep-
tibility genes, including the dopamine receptor 2 (DRD2), neuregulin 1
(NRG1) (19), dysbindin (DTNBP1) (20), and disrupted in schizo-
phrenia 1 (DISC1) (21).The recent common variant–common disease
hypothesis has stimulated a number of genome-wide association studies
(GWAS) and resulted in the identification of variants with weaker
effects, including ZNF804A (22). Several international consortia, in-
cluding SGENE, the ISC (International Schizophrenia Consortium),
and the MGS (Molecular Genetics of Schizophrenia Collaboration),
detected their strongest association signals in the major histocom-
patibility complex (MHC) region, which seem to come from two par-
tially independent signals: one in the large histone gene cluster on
chromosome 6, near the MHC class I region, and another one near
the NOTCH4 gene, which also tags classical human leukocyte antigen
(HLA) alleles DRB1 and HLA-B (23–25). They also identified other
loci, including TCF4 and Neurogranin (23). Follow-up analyses, includ-
ing studies by the Psychiatric Genetics Consortium, and other groups
(26, 27) are gradually identifying further GWAS-significant loci.
Several rare, de novo copy number variants (CNVs) have also been
recently associated with schizophrenia, including deletions at 15q13.3,
1q21.1, neurexin (28), and 17p12 (29) and duplications at 16p11.2,
16p13.1 (30, 31), and VIPR2 (32–34). CNVs at some of these loci as-
sociate also with other phenotypes, including bipolar disorder, autism
spectrum disorders [for example, (29)], cardiovascular diseases such as
aortic dissection and teratology of Fallot (35), and obesity (36); these
findings have important implications with regard to potential DNA
diagnostics, understanding disease etiology across disorders, and treat-
ment development. Even though important disease pathways are be-
ginning to emerge, more than 90% of the heritability of schizophrenia
remains to be explained and larger samples and sequencing-based
approaches are expected to shed light on this issue. It is interesting
that the occurrence of de novo CNVs and recent rare point mutations
may explain why psychiatric diseases with a reduced fecundity, such
as schizophrenia and autism, remain common in the human popula-
GENETIC MOUSE MODELS
The contribution, not only of common risk variants but also of deleted
or duplicated de novo CNV regions in schizophrenia, suggests that
transgenic animals, such as knockouts or knock-ins for these specific
gene regions, may allow determination of genetic causality for schizo-
phrenia. Most mutants studied thus far do not model schizophrenia
per se; rather, they assess the functional roles of genes associated with
risk for schizophrenia (for example, DISC1, DTNBP1, and NRG1) or
putative endophenotypes (for example, Comt deletion in relation to
cognitive phenotypes). Furthermore, studying the “mental health” of
mice is challenging. There may be an unappreciated role for etholog-
ical, species-specific behaviors that become apparent in more natural-
istic settings, including components of the mouse ethogram such as
nest building. Current approaches (38, 39) have more commonly in-
volved trans-species models of positive symptoms (for example, pre-
pulse inhibition), negative symptoms (for example, social behavior),
and cognitive dysfunction (for example, working memory). In the case
of N-ethyl-N-nitrosourea–induced, amino acid substitution Disc1
mouse models, the behavioral phenotypes and pharmacological rescue
are allele-dependent (40). Certain features of schizophrenia, such as
poverty of speech, may be uniquely human. However, anhedonia,
asociality, and avolition are at least theoretically accessible in both hu-
mans and animals and can be studied in relation to genetic risk factors
for schizophrenia (41). For example, Nrg1 mutant mice have selective
disruption of the normal preference for social novelty (42). However,
the uncertainty regarding the clinical concept of schizophrenia means
that the predictive validity for such mutant phenotypes and their
pathobiology is similarly uncertain. Studies with cross-sectional mag-
netic resonance imaging have shown that, in contrast to patients with
schizophrenia, Nrg1 mutant mice have slightly smaller total ventricu-
lar volume and cerebellum when compared to wild-type controls (43).
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Gene × environment (G × E) interactions are evident in mice; for
example, interactions (i) between maternal immune activation and
Nrg1 mutation, (ii) between adolescent social defeat and Nrg1 muta-
tion, and (iii) between adolescent cannabis exposure and Comt mu-
tation regulate subsequent mouse phenotypes such as social behavior
and working memory in young adulthood (44). Such studies suggest
that, in patients, the overall psychosis phenotype may be influenced by
the interaction of risk genes with both biological and psychosocial
environmental adversities operating at critical time points during de-
velopment, but the applicability of these results from mice to patients
is still uncertain.
Genetic information has the potential to aid clinicians in risk predic-
tion and diagnostics. Both of these approaches are routinely carried
out for monogenic diseases. Certain rare genomic lesions have high
predictive value for schizophrenia, such as the t(1;11) disruption of
DISC1 (45), or the velocardiofacial syndrome (VCSF) deletion locus
on chromosome 22q11 (46). Unfortunately, GWAS of schizophrenia
published to date have generated low values for the relative risk
provided by the identified risk alleles. For example, the International
Schizophrenia Consortium (ISC) reported odds ratios of around 1.2
for their most important findings, with the risk-conferring allele being
very prevalent, around 80 to 90% in most cases (25). Translated into a
predictive test, this has very low specificity and no clinical utility. Com-
bining genetic risk factors to create a genetic risk score has been at-
tempted for other complex phenotypes, leading both to negative results
for height (47) and cardiovascular traits (48) and to statistically signif-
icant but not clinically applicable for type 2 diabetes (49) and coronary
heart disease (50). The current genetic findings do not allow clinically
relevant tests to be performed, but such tests may be possible when the
genetic landscape of schizophrenia becomes better characterized.
Nevertheless, clinical studies in schizophrenia can inform selection
of the most relevant phenotypes for studies in mice. When construct-
ing a mouse to model aspects of schizophrenia, it is important to dis-
tinguish whether one seeks to model a rare, severe trait, potentially
with quantitative endophenotypes, or a trait that is present quantita-
tively in the human population. Traditionally, a stress-diathesis model
has prevailed. This model views disease state as dichotomous but the
underlying risk phenotypes as quantitative. There is also evidence to
suggest that the actual phenotype of psychosis is common and quan-
titatively distributed in the population, with no point of rarity. First,
more than 3% of individuals have a diagnosed psychotic disorder (51).
Moreover, brief auditory illusions when falling asleep/waking up are
common and normal; many widowed persons have sensory impres-
sions of their loved ones; experimental sleep deprivation and sensory
deprivation can cause hallucinations in experimental settings. When
susceptibility to psychosis in the population is assessed by a question-
naire (the Perceptual Aberration Scale), less than half of individuals
report no psychotic-like experiences and the number of psychotic-like
experiences in the population follows a Poisson distribution, with no
point of rarity (52). These findings do not support a dichotomous view
of psychosis in itself. The research community seems divided on this
dichotomous/continuous debate, and whichever eventually turns out
to be true, it is something to keep in mind when constructing mouse
models for this disorder.
Another important issue to consider is which human phenotypes
can be modeled in the mouse and which are human-specific (53). Re-
cent cognitive neuropsychiatric models of psychosis emphasize the
role of attention disturbances and inappropriate incentive learning
in the development of disturbances of thought, such as delusions. It
is clear that more proximal phenotypes, such as sensory gating ab-
normalities, would be a better choice for modeling in mouse than
human-specific, distal phenotypes like delusions of reference. The
most critical question is where on this proximal-distal scale to put
traits such as disruption to social behavior and brain imaging abnor-
malities. These considerations suggest that the phenotypes to be
modeled in the mouse should be a reliably detectable, physiological
measure of proximal processes in the etiological chain of events in
MODELING CLINICAL RELEVANT PHENOTYPES IN MICE
This overview of our current knowledge of the neurobiology of schizo-
phrenia signals an urgent need for animal models that also take into
account the genetic complexity of the small effect size genetic variants
that contribute to the development of core features of the disease. One
main conclusion from this workshop was that schizophrenia is a com-
plex neurodevelopmental disease associated with early, progressive
cognitive decline in association with accelerated reduction in brain
volume of cortical areas and, possibly, the cerebellum. Manifestation
of the diagnostic symptoms of psychosis during late adolescence may
result from the effects of moderate- to high-risk mutations such as
CNVs in some individuals and interaction of a large number of low-
risk polymorphisms with several environmental adversities at critical
time points during development. Future studies should aim at devel-
oping specific, standardized phenotypes to be measured longitudinally,
including cortical thickness and other structural phenotypes, cognitive
phenotypes, prepulse inhibition, sociability/social novelty prefer-
ence, and habituation of exploratory behavior in a novel environment.
These phenotypes will need to be assessed in standardized contexts of
G × G and G × E interaction and measured longitudinally to address
both multifactorial and progressive aspects such as reduction in brain
volume and cognitive decline. Here, mouse model systems will be of
MOUSE MODELS CAN INFORM STUDY OF THE ETIOLOGY
Targeted therapies for schizophrenia are desperately needed, but their
development and effective use require understanding the molecular
mechanisms involved in the etiology of schizophrenia. Genetics offer
an ideal route to the molecular basis of schizophrenia, as any identified
genes can potentially be linked to their functions from the cellular to
the behavioral level. Mouse models can be very informative both in
the identification of susceptibility genes and in understanding their
biological function (5, 38). In addition to revealing the function of
the gene in a defined genetic background (39), single gene knockout
mouse models of candidate genes for schizophrenia allow studies of
G × E interactions (44). Furthermore, the same mice can be used in
detailed analysis of gene expression, proteomic, and neuronal phe-
notypes both in the intact brain and in cellular models to provide
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on September 28, 2011
additional tools for drug development and testing (for example, with
approaches such as connectivity mapping) (54). Some of these models,
such as those that exhibit positive symptoms, can be validated with
existing drugs for schizophrenia to provide some predictive validity
(40). However, others, such as those with negative symptoms and cog-
nitive dysfunction, which respond poorly even to clozapine, cannot be
validated in this way (53).
On the other hand, clinically relevant mouse models of schizo-
phrenia will complement human genetic efforts to identify small effect
susceptibility variants, because human GWAS fail to capture more
than a modest fraction of the measured heritability (55). Quantitative
trait locus (QTL) mapping with mice has been used to identify sus-
ceptibility genes for endophenotypes of schizophrenia, including ven-
tricular size (56) and prepulse inhibition (57–60) in F2animals and
chromosome substitution strains. However, the relatively small num-
ber of highly polymorphic alleles in these strains might not be optimal
in identifying genes for complex diseases such as schizophrenia.
At the core of the SYSGENET network (http://www.helmholtz-hzi.
de/sysgenet/) is the use of mouse genetic reference populations (GRPs).
An important new GRP that will soon become available is the Collab-
orative Cross (CC), comprising a large panel of recombinant inbred
(RI) strains derived from a genetically diverse set of eight founder
strains and designed specifically for complex trait analysis (61, 62).
The CC population also includes wild derived mouse strains and thus
represents a greater degree of genetic variation than do currently avail-
able GRPs. This resource should offer larger phenotypic and behavioral
variations that are relevant to schizophrenia and other neurodevelop-
mental and behavioral disorders. GRPs also have the intrinsic advan-
tages of access to brain tissue at any chosen developmental time point,
before or after behavioral testing and/or environmental or pharmaco-
logical intervention. Polymorphisms within susceptibility genes may
lead to differences in gene function or expression; these differences
can be studied with gene expression, proteomic, and metabolomic
analyses, allowing identification of gene regulatory networks perturbed
in schizophrenia. Therefore, the set of clinically relevant phenotypes
discussed above should be measured in the CC population. Longitu-
dinal quantitative measurements of brain morphology (for example,
cortical thickness), sensory processing, and behavioral phenotypes
(for example, social behavior) in GRPs will allow the systematic
modeling of clinically relevant phenotypes of schizophrenia at differ-
ent developmental stages and under controlled genetic and environ-
mental conditions (Table 1).
All participants of the meeting concluded that there is a real oppor-
tunity and need for knowledge exchange between preclinical and clin-
ical researchers to better understand the etiology of schizophrenia and
related developmental brain disorders. The laboratory mouse can play
a vital role in constructing and testing hypotheses of direct transla-
tional relevance. The CC will provide an important complement to
the established armamentariumofmouse genetic techniquesand tools.
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Table 1. Core features of schizophrenia for mouse modeling.
Critical developmental stages Age-matched developmental stages
Disease progression Longitudinal phenotypic assessment
Environmental factorsMaternal infection/stressful
Candidate genesTargeted and “humanized” genetic models
Genetic background/epistasisCollaborative cross/crossing mutant lines
Sensory processing (for example,
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63. Acknowledgments: The meeting was supported by the SYSGENET network (http://www.
helmholtz-hzi.de/sysgenet/). SYSGENET represents a network of scientists in Europe who
use the mouse as an experimental model system to identify genetic factors that influence
complex phenotypic traits relevant for human diseases. Funding: SYSGENET is funded
through COST, an intergovernmental framework for European Cooperation in Science
and Technology (http://www.cost.eu/about_cost).
Submitted 14 July 2011
Accepted 6 September 2011
Published 28 September 2011
Citation: M. J. Kas, R. S. Kahn, D. A. Collier, J. L. Waddington, J. Ekelund, D. J. Porteous,
K. Schughart, I. Hovatta, Translational neuroscience of schizophrenia: Seeking a meeting of
minds between mouse and man. Sci. Transl. Med. 3, 102mr3 (2011).
www.ScienceTranslationalMedicine.org 28 September 2011Vol 3 Issue 102 102mr3
on September 28, 2011