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The current diagnosis of schizophrenia involves examination and monitoring by psychiatrists,
a process which can take between 2 and 5 years. Currently, schizophrenia is diagnosed on
the basis of patient reports and several clinical observations. By any reckoning this is a
rather subjective and sometimes long-lasting uncertain process. Although schizophrenia is a
severe mental disease affecting primarily the brain, it is becoming more apparent that the
whole body is involved. Studies over the last two decades have shown that many patients
with schizophrenia or other psychiatric disorders have abnormalities in insulin signalling,
similar to those seen in type II diabetes mellitus. There are also reports that schizophrenia is
associated with a mild pro-inflammatory state resulting in increased permeability of the brainblood barrier. Therefore, brain “signature” changes in biomolecules should be reflected by
changes in the cerebrospinal fluid (CSF) and blood (serum/ plasma) levels of the same or
related molecules. It is through this process that peripheral biomarkers for brain disorders
can be identified. In order to increase the efficiency of the diagnostic process and to guide
treatment approaches, the identification of molecular biomarkers appears to be essential.
Most biomarker approaches for schizophrenia and most other medical conditions have thus
far focussed on overall changes in protein levels.
The aim of the EU project «Developing minimally invasive, high throughput, low-cost
molecular assays for the early diagnosis of schizophrenia and other psychiatric disorders»
(acronym “SchizDX”) was to identify novel biomarkers in order to support, differentiate, and
validate the diagnosis of schizophrenia as well as the diagnosis of other severe psychiatric
disorders. In each case, the study of patients was always conducted in comparison to
carefully matched controls. The definite advantage of this project was that some human CSF
samples already existed which could be used to compare the types and levels of containing
biomolecules with those of (freshly) collected blood (serum/plasma) samples. The study
focussed more on the blood samples as these are far more accessible in the clinical
environment.
From the beginning it was clear that not only the clinical part of the project had to be
accompanied and observed by the corresponding ethical committees but an independent
ethical advisor should have an eye on the entire project as well. With respect to the clinical
part, the risk for the patients and healthy comparison subjects recruited was relatively small
because “only” blood samples (total amount <100 mL per patient) were drawn in a hospital
environment. In accordance with national and EU legal requirements and data protection,
written informed consent of each included individual and complete anonymization of the
samples were prerequisites for this procedure. This project was reviewed regularly by
representatives from the project - Professor Matthias Rothermundt, Dr Markus Leweke and
Dr Sabine Bahn - and independently approved by the accompanying competent local ethics
committees at the three participating clinics in Cologne, Muenster and Mannheim, Germany.
The Central Institute of Mental Health (CIMH; Mannheim) and Muenster Institutional Review
Boards (IRBs) have continually monitored the study and request updated reports on the
research protocols and related materials (e.g. informed consent documents, information
sheets) to ensure the protection of rights and welfare of participating human subjects on a
regular basis.
A critical phase of the project was the collection of high quality clinical samples to support
the biomarker development efforts. Recruitment took place at the University of Muenster, the
University of Cologne and the CIMH at Mannheim in Germany. Blood samples of all patients
were collected and stored by trained study nurses and all procedures were coordinated
across the sites to minimise technical variation. Clinical data collection comprised an
attentive screening of medical records and information given by the treating physician. All
clinical raters were selected and trained using strict criteria by experienced clinicians.
Extensive training was conducted regularly at the University of Muenster to establish
satisfactory inter-rater reliability. The deliverable was met with the collection of 748 samples
for the main validation study. In addition, the deliverable was exceeded with the provision of
806 additional samples for a further validation study and 77 prospective samples from
schizophrenia patients before and after 6 weeks treatment with antipsychotics as in kind
contributions. This also enabled all assay development and biomarker screening
deliverables to be met.
Existing treatments for schizophrenia are only partially effective and are often associated
with adverse side effects resulting in a high rate of non-compliance. Furthermore, traditional
pharmacotherapy for schizophrenia using “blockbuster” drugs usually leads to administration
and switching of drugs multiple times until an adequate response is achieved. Therefore, it is
not surprising that there is a low treatment response rate and relapse is common. This is
most likely a result of the insufficient understanding of the underlying pathophysiology of
schizophrenia to inform diagnosis or guide treatment selection. Therefore, identification of
new strategies for early intervention aimed at improving treatment response, reducing side
effects and thereby increasing compliance are required.
A major objective was to identify up to 50 candidate biomarkers which showed changes in
concentration in drug naive, first onset schizophrenia patient CSF and serum samples or
changing in similar patients following 4 weeks of antipsychotic drug treatment. This was
achieved using three complementary approaches:
1. Label-free nano-LC-MSE-based proteomic profiling
2. Glycoprotein profiling
3. Multianalyte profiling (multiplex immunoassays)
Glycoprotein analysis was carried out on serum and CSF samples from healthy controls and
schizophrenia patients. Statistically significant glycoprotein changes were found in serum
and CSF samples from first-onset schizophrenia patients compared to control subjects.
There was also some indication that the patterns of glycoprotein changes were different
between male and female patients. Further studies using this approach should lead to
identification of a new class of biomarkers for schizophrenia, based on glycosylation-specific
changes. The additional study of phosphorylation changes in serum proteins could lead to
new insights into disease and drug mechanism of action at the functional level. Comparative
proteomic and phosphoproteomic analyses of serum from 20 first-onset antipsychotic-naïve
schizophrenia patients and 20 control subjects was carried out. Phosphoproteins were
enriched using immobilised metal ion affinity chromatography (IMAC) and LC-MSE was used
for identification and quantitation. Analysis of the IMAC-enriched fraction resulted in
identification of 75 phosphoproteins with altered phosphorylation patterns. Of these, 65
phosphoproteins showed changes in phosphorylation, with no overall changes in the parent
protein levels. These altered phosphoproteins were involved in acute phase response,
complement and coagulation canonical signalling pathways. Further studies are warranted to
determine whether assays for these proteins should be incorporated into the multiplex
immunoassay platform.
A comprehensive molecular analysis of serum from first onset schizophrenia patients before
and after treatment with olanzapine, risperidone, quetiapine or a mixture of antipsychotics
using LC-MSE analysis was carried out. The experimental goal was the identification of drug
response protein biomarkers for schizophrenia using label-free nanoflow liquid
chromatography tandem mass spectrometry (nano-LC-MS/MS). Two sets of serum samples
from two clinical centres were prepared. The main findings were that two proteins, lumican
and apolipoprotein C2, were increased by all treatments. However further studies are
warranted to determine whether assays for these proteins should be incorporated into the
multiplex immunoassay platform.
The glycoprotein and phosphoprotein studies described above are more novel approaches
in biomarker discovery, as most other researchers have focussed on overall changes in
protein levels. However, disease or treatment-associated changes in post-translational
modifications could be even more informative, as this could lead to information on functional
changes in protein networks. Therefore, research in this project also included identification of
changes in the glycosylation pattern of glycoproteins before and after antipsychotic
treatment. Glycosylation-specific changes were found in serum from schizophrenia patients
after 4 weeks treatment with olanzapine. Two dimensional gel electrophoresis was carried
out to isolate protein candidates which were likely to be associated with the glycan changes.
MS analyses confirmed that the glycan changes were associated with the α1 acid
glycoprotein. These findings illustrate the potential importance of such studies to elucidate
whether glycosylation-specific changes can be used to predict response of schizophrenia
patients to treatment with antipsychotics.
Multiplex immunoassay profiling of drug treated schizophrenic patients before and after 4
weeks of treatment identified 7 candidate treatment response biomarkers that changed in
expression levels in two or more of the following treatment cases: olanzapine, risperidone,
quetiapine, or a combination. Prolactin levels were significantly increased in 3 of the 4
treatment groups, reflecting dopamine D2 receptor antagonist effects. The other 6 proteins
were affected in two of the treatment groups and approximately 10 molecules were changed
in only one treatment category. These data suggest that even antipsychotic compounds with
overlapping pharmacological profiles are likely to have specific treatment response
biomarker signatures.
Second generation antipsychotics (also known as atypical antipsychotics) have been used
for treatment of schizophrenia patients for approximately 20 years and appear to be effective
for treatment of the negative symptoms and cognitive deficits of schizophrenia. However, the
use of these compounds is associated with prominent metabolic side effects, including
weight gain, hyperglycaemia, prolactinaemia, insulin resistance and dyslipidaemia hence a
substantial proportion of schizophrenia patients discontinue treatment with second
generation antipsychotics due to these side effects. Clinicians are now required to monitor
patients receiving atypical antipsychotics closely for side effects which are risk factors for
development of cardiovascular disease, type II diabetes and metabolic syndrome. Therefore,
a test for the early identification of adverse metabolic effects is of great interest and could
help to minimize or prevent drug-induced complications. One of the earliest physical
indicators of metabolic side effects resulting from antipsychotic treatment is an increase in
body weight, which may undermine adherence to treatment.
Despite these concerns, there are currently no accurate methods which can be used for
predicting which patients will experience antipsychotic-associated metabolic side effects.
Multiplex immunoassay analyses of serum samples taken from patients before and after
treatment with antipsychotics were carried out in an attempt to identify molecules which can
predict or are associated with these changes. The levels of serum molecules were tested to
determine whether they can be used to predict weight gain in 77 patients before 6 weeks of
treatment with antipsychotics. This showed that the levels of 8 serum molecules at T0 were
significantly associated with ΔBMI, including interleukin-6 receptor, epidermal growth factor
and insulin-like growth factor 1. Further studies investigating these molecules in the context
of treatment side effects may lead to molecular tests that can aid in the selection of
antipsychotic treatments that offer an optimal efficacy – side effect balance.
The same approach was used to identify biomarkers which could predict relapse. Treated
schizophrenia patients were followed up over 25 months with four aims: 1) to identify
molecules associated with symptom severity in antipsychotic naive and unmedicated
patients, 2) to determine biomarker signatures that could predict response over a six-week
treatment period, 3) to identify molecular panels that could predict the time to relapse in a
cross-sectional population of patients in remission and 4) to investigate how the biological
relapse signature changed throughout the treatment course. This led to identification of
molecular signatures that could predict symptom improvement over the first 6 weeks of
treatment as well as predict time to relapse in a subset of 18 patients who experienced
recurrence of symptoms.
This is the first study to identify serum molecules which may be indicative of relapse. The
results suggested that molecular processes associated with weight gain and metabolic
changes play a central role in relapse. Specifically, a lower BMI and non-response of the
molecular signature to treatment was associated with a shorter time to relapse. The
identification of biomarkers such as proinsulin, C-peptide and insulin, along with changes in
the hormone leptin, is consistent with previous studies showing changes in these molecules
in first onset antipsychotic naive schizophrenia patients. It is not clear whether any of the
changes in biomarker profiles are involved in the mechanism of action of antipsychotics or if
they are a consequence of changes which occur in the brain. Studies, which have found that
hyper-insulinaemia can affect cognition, provide some evidence that the response of some
molecules could be mechanism-based. We also identified molecular signatures associated
with symptom severity and response although this was limited by the high proportion of
patients who showed improved PANSS in response to treatment. Further testing of these
findings in validation studies are required for the development of molecular tools which could
be useful for early monitoring of response and to ensure a better clinical outcome in
schizophrenia patients treated with antipsychotics. It may also provide an early indication for
cases in which switching of antipsychotics may be required.
Over the course of this project, several potential molecular biomarkers were identified by
Psynova Neurotech Ltd, using and array of targeted and multiplex profiling platforms such as
fluorescent-based immunoadsorbent assays and liquid chromatography mass spectrometry
profiling. Other candidate biomarkers were selected based on findings in the literature. The
main aim was to produce new immunoassays for incorporation into new multiplex tests for
schizophrenia. The initial aim was to purchase commercially available antibodies and other
reagents as available and test these for incorporation into the multiplexes. In the majority of
cases, suitable antibodies were not available and therefore it was necessary to raise
polyclonal antiserum for building new assays. New polyclonal antibodies were produced and
other reagents acquired for development of 25 new two-site immunoassays. Thirteen of
these assays have already been incorporated into the Myriad-RBM DiscoveryMAP
immunoassay platform which has been used for profiling in the large scale validation study.
In addition, 9 further assays have been developed as extra contributions for incorporation
into future multiplex immunoassays for the study of psychiatric disorders and their treatment.
The key objectives of developing novel assays for validation screening of approximately 800
subjects has been achieved twice. Firstly, novel assays were incorporated into the
DiscoveryMAP multiplex immunoassay platform and testing with this panel showed high
performance for distinguishing schizophrenia patients from control subjects (748 individuals
in total). Secondly, a novel 51-plex assay system was produced and used to screen samples
from 806 subjects, and again this resulted in high performance. In addition to this major
achievement, the project also developed additional two-site bead based assays for
incorporation into multiplexes which are relevant to schizophrenia and/or antipsychotic
treatment.
For more than 100 years, discussions have been on-going that the immune system plays an
important role in the aetiology of schizophrenia. Most immune cells and antibodies are
prevented from entering the brain by the blood-brain barrier under normal conditions and this
has been demonstrated for only some mononuclear cells, activated T cells and
macrophages. However, the analysis of CSF samples has shown that the proportion of
mononuclear macrophages is significantly higher in schizophrenia patients compared to
controls patients. Also, the macrophage–T-cell theory of bipolar disorder and schizophrenia
suggests that inflammatory compounds produced by chronically-activated macrophages,
microglia, and T cells can destabilize brain function, which eventually leads to psychiatric
symptoms. Based on these observations, the SchizDX consortium decided to integrate
whole blood stimulation assays into the biomarker screening process.
The major advantage of whole-blood culture assays is that all components of the blood,
including cellular and extracellular components, are present and can therefore reflect the
function of the whole immune repertoire compared to purified peripheral blood cell
preparations. Furthermore, cells in whole blood cultures have not been deprived of their
normal environmental constituents, no xenogenic constituents such as serum supplements
have been added and they have not been subjected to the usual stress of preparation by
several stages of centrifugation. Finally, leukocytes in these whole-blood cultures do not
become plastic-adherent, therefore eliminating this artificial type of background activation.
A novel ex vivo blood culture system (TruCulture) combined with the use of a 33-plex
cytokine/chemokine immunoassay panel was implemented to identify further schizophrenia
biomarkers and to provide a clinically-relevant system for identification of drug-predictive or
response biomarkers and for novel drug discovery.
The TruCulture procedure was incorporated as an extra non-funded activity to follow up
future phases of this project which will target more the drug discovery aspects of
schizophrenia. Furthermore, this can be combined with use of the 33-plex
cytokine/chemokine panel as a readout for the effect of various psychiatric medications in
clinical studies. By application of this model it is hoped to provide this as a novel preclinical
screening tool for the characterization of existing psychiatric medications and the
identification of potential novel treatment strategies.
The task to carry out validation of 800 samples using the novel schizophrenia biomarker
panels proved to be a ground-breaking development of a serum-based test to help confirm
the diagnosis of schizophrenia. A multiplex panel of 51 immunoassays was developed that
allowed reproducible identification of schizophrenia patients compared to controls with high
sensitivity and specificity. Validation of this test consisted of developing a linear support
vector machine (SVM) decision rule and testing its performance using cross-validation. The
resulting decision rule delivered a sensitive and specific prediction for presence of
schizophrenia in subjects compared to matched controls (806 subjects), with a receiver
operating characteristic-area under the curve of 0.88.
In this multicentre study, a biomarker panel for schizophrenia based on biological and
technical reproducibility of the molecular signature was discovered and validated. All stages
of the process, including conduction of the assays, assay selection, assay panel refinement,
development and recalibration of the decision rule, were carried out in a CLIA-certified
laboratory at Myriad-RBM. Assay selection was based on a large number of samples
collected from antipsychotic naïve, acutely psychotic patients to facilitate relatively uniform
conditions. Subjects were recruited from four independent clinical centres and samples
collected according to strict standard operating procedures to maximize reliability and
accuracy of the results. As the assay progresses from beta site testing into exposure to
different subpopulations, the performance against present clinical classification and
observed prevalence and incidence were monitored and differences examined.
The implementation of the 51-plex molecular assay decision rule was based on a cohort
comprised of both untreated and treated schizophrenia patients who were either
experiencing a first episode of illness or who were chronically ill (54% of patients were on
current antipsychotic treatment). This collection is likely to represent the patient population
encountered in clinical practice. High classification performance demonstrated that the
decision rule could identify schizophrenia patients with high accuracy irrespective of the
disease duration or treatment state. Interestingly, the biomarker signal was still apparent in
subjects even after 4-6 weeks of successful treatment with antipsychotic medication.
Further work based on earlier findings of the funding period in the identification of biomarker
signatures for schizophrenia and the incorporation of novel assays for achieving this into the
multiplex immunoassay profiling MAP panels at Myriad-RBM resulted in the identification of
a biomarker panel that was capable of distinguishing schizophrenia from healthy controls
with a sensitivity of 0.86, a specificity of 0.81, and a receiver operating characteristic-area
under the curve (ROC-AUC) of 0.83. This panel contained the 13 novel assays for molecules
such as proinsulin and chromogranin A which were developed during the early phase of the
project and were suggestive of the underlying effects on hormonal and metabolic balance.
However, this signature showed lower performance for separating schizophrenia from the
affective disorders of major depressive disorder and bipolar disorder with a sensitivity of
0.37, a specificity of 0.87, and a ROC-AUC of 0.67. This suggested the panel was
successful for distinguishing schizophrenia from control subjects. In addition, further work on
this panel should help to increase its differential diagnostic capability of schizophrenia
compared with the affective disorders. One means could be to reverse the strategy by
identifying biomarkers in these disorders and then applying these to the study of
schizophrenia.
For dissemination purposes a dedicated website http://schizdx.pera.com was set up and
maintained and a project leaflet was designed and produced, this was made available to all
partners.
The project has resulted in a number of novel discoveries which has resulted in the
application for 9 patents to establish a priority date.
In addition, the project has so far resulted in 21 publications in peer reviewed journals and at
least 4 others which have been submitted.
Perhaps of most importance, the SchizDX project has resulted in the launch of the first
molecular assay for the diagnosis of schizophrenia (VeriPsych®) by Psynova and MyriadRBM in the USA. The test is being marketed to assist with the diagnosis of first onset
schizophrenia and may result in a quicker and more cost effective diagnosis for some
patients. It is well known that early intervention can result in a much better outcome for
schizophrenia patients. Therefore, the outputs from the SchizDX project may be of
significant benefit to patients and their families.
The suite of biomarkers identified by the project is also being evaluated for diagnosis of
other mental disorders including bipolar disorder, various forms of depression and autism
etc. It is often challenging for clinicians to distinguish between these disorders due to
overlapping symptoms so a molecular test capable of differentiating between disorders
would be of major benefit to patients.
The societal benefit of improved diagnosis of mental disorders will be manifested through
more effective treatment of patients leading to a reduced financial burden on healthcare
systems and better integration of patients into the community.
The SchizDX project is contributing to a better understanding of mental disorders such as
schizophrenia and, in time, this improved understanding may help to combat the widespread
negative attitudes towards the mentally ill.