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Neuroimmune biomarkers in schizophrenia
Schizophrenia Research, In Press, Corrected Proof
Schizophrenia is a heterogeneous psychiatric disorder with a broad spectrum of clinical and biological manifestations. Due to the lack of objective tests, the accurate diagnosis and selection of effective treatments for schizophrenia remains challenging. Numerous technologies have been employed in search of schizophrenia biomarkers. These studies have suggested that neuroinflammatory processes may play a role in schizophrenia pathogenesis, at least in a subgroup of patients. The evidence indicates alterations in both pro- and anti-inflammatory molecules in the central nervous system, which have also been found in peripheral tissues and may correlate with schizophrenia symptoms. In line with these findings, certain immunomodulatory interventions have shown beneficial effects on psychotic symptoms in schizophrenia patients, in particular those with distinct immune signatures. In this review, we evaluate these findings and their potential for more targeted drug interventions and the development of companion diagnostics. Although currently no validated markers exist for schizophrenia patient stratification or the prediction of treatment efficacy, we propose that utilisation of inflammatory markers for diagnostic and theranostic purposes may lead to novel therapeutic approaches and deliver more effective care for schizophrenia patients.
Abbreviations: AP - antipsychotic, CD - cluster of differentiation, CNS - central nervous system, COMT - catechol-O-methyltransferase, COX - cyclooxygenase, CSF - cerebrospinal fluid, CSF2RA - colony stimulator factor receptor 2 alpha, DISC - disrupted in schizophrenia, GWAS - genome-wide association study, HER2 - human epidermal growth factor receptor 2, HLA - human leukocyte antigen, HSV - herpes simplex virus, IFITM - interferon-induced transmembrane protein, IFN - interferon, IL - interleukin, KYNA - kynurenic acid, MHC - major histocompatibility complex, NAC - N-acetylcysteine, NK - natural killer, NMDA - N-methyl d-aspartate, NRG - neuregulin, PANSS - Positive and Negative Syndrome Scale, PET - positron emission tomography, RA - rheumatoid arthritis, SERPINA3 - alpha-1-antichymotrypsin, SLE - systemic lupus erythematosus, SNP - single nucleotide polymorphism, TGF - transforming growth factor, Th - T helper, TNF - tumour necrosis factor, TSPO - translocator protein.
Keywords: Schizophrenia, Immune system, Biomarker, Add-on treatment, Personalised medicine.
Schizophrenia affects about 1% of the population but the understanding of its aetiology remains incomplete. At present, schizophrenia is not considered a single disorder but a group of conditions with manifestations common to other psychiatric and non-psychiatric disorders. Those manifestations include clinical symptoms, such as hallucinations, delusions, disturbed emotions and social withdrawal, and involve biological mechanisms, in particular perturbations of the immune, metabolic and endocrine systems. In the absence of a biological marker, the current diagnosis of schizophrenia and its treatment are mainly based on clinical questionnaires and it is not surprising that the response rate is unsatisfactory, in particular after multiple treatment attempts, and relapse is common for those patients who discontinue medication ( Emsley et al., 2013 ). For decades, pathophysiological studies relating to schizophrenia were focused on disturbances of dopaminergic and glutamatergic neurotransmission with limited clinical breakthroughs. Current antipsychotic drugs primarily alleviate the neurotransmitter imbalances, but most patients continue to experience residual symptoms on current treatment regimens (Chakos et al, 2001, Leucht et al, 2009, and Leucht et al, 2013). Furthermore, the rate of novel compounds coming to the market is far from satisfactory. However, recently there has been a greater focus on the identification of molecular changes in central and peripheral tissues obtained from schizophrenia patients to unravel the molecular signatures underpinning schizophrenia pathophysiology as a means of improving and accelerating this process ( Guest et al., 2013 ).
A link between inflammatory diseases and schizophrenia has been proposed over decades. The evidence suggests that some clinical, epidemiological and genetic features may be shared between schizophrenia and certain autoimmune diseases (Wright et al, 1996, Brey et al, 2002, and Benros et al, 2011). The co-prevalence between various autoimmune disorders and some cases of schizophrenia may contribute to the disease development ( Eaton et al., 2006 ). For example, Graves' disease (thyrotoxicosis) has been shown to share similar aetiological features with schizophrenia (Bianco and Lerro, 1972 and Ogah et al, 2009). In addition, a relationship between perinatal and adulthood infections and schizophrenia is supported by various lines of evidence (Maurizi, 1984, Buka et al, 2001a, Leweke et al, 2004, Brown et al, 2005, Brown, 2006, and Khandaker et al, 2012). More recently, genome-wide association studies (GWAS) have substantiated these findings by indicating a strong relationship between genes regulating immune response and schizophrenia ( Corvin and Morris, 2013 ).
In the past years, a significant proportion of clinical and molecular studies have attempted to unravel the role of immune dysregulation in schizophrenia and explore the possibility of targeting these pathways especially as add-on intervention to existing therapies (Muller and Schwarz, 2010, Meyer et al, 2011, Keller et al, 2013, Kirkpatrick and Miller, 2013, Najjar et al, 2013, Smyth and Lawrie, 2013, Feigenson et al, 2014, Girgis et al, 2014, and Kroken et al, 2014). As the immune system is dynamic and sensitive to changes, the research into the relationship between schizophrenia and immune system abnormalities has yielded contradictory results. This is most likely due to a complex interplay between genetic predisposition, environmental risk factors, disease stage and side effects of antipsychotic medication. Recent findings from our group indicate that molecular changes in schizophrenia patients show an overlap with certain inflammatory as well as metabolic disorders ( Chan et al., 2011 ). The utility of the immunological markers for diagnosis and prognosis of schizophrenia is yet to be established.
In this review we will evaluate findings of neuroimmune changes in schizophrenia. We will discuss the evidence of central and peripheral immune findings in schizophrenia, their potential causes, and effects of immunomodulatory therapies on symptoms and outline potential applications of these markers in managing the disease.
2. Neuroimmune alterations and schizophrenia features
2.1. Central nervous system markers
Imaging studies have shown that the brains of schizophrenia patients display characteristic structural changes at the onset of the disease, which cannot be attributed to drug effects or other confounding factors. Most often, decreased hippocampal and cortical volumes, accompanied by enlarged ventricular spaces, have been identified ( Harrison, 1999 ). Contrary to the findings in Alzheimer's disease, the changes in schizophrenia do not result from an ongoing neurodegenerative processes or neuronal death, but are related to changes in the organisation and size of neurons and other brain cells ( Harrison, 1999 ). Although central nervous system (CNS) changes show only low sensitivity and specificity for identification of patients compared to controls, they have improved our understanding of the mechanisms underlying schizophrenia symptoms ( Allen et al., 2009 ). It has been postulated that psychotic symptoms, at least in part, are due to impaired dopaminergic and glutamatergic neurotransmission in the extended limbic system (hippocampus, dorsolateral prefrontal cortex and cingulate gyrus). However, the exact underpinning processes remain largely unknown.
Molecular profiling studies have suggested that molecules related to oxidative stress and immune regulation are implicated in the pathophysiology of certain brain regions in schizophrenia. However, their relation to the structural changes is not clear. These studies have repeatedly shown altered expression of immune-related markers in prefrontal (Arion et al, 2007, Saetre et al, 2007, Martins-de-Souza et al, 2009, and Fillman et al, 2013) and temporal ( Wu et al., 2012 ) cortices as well as in the hippocampus ( Hwang et al., 2013 ) of schizophrenia patients. Since brain profiling studies can be performed only in post-mortem brain tissue, and as most patients have been treated long-term before death, these results suggest that current treatment approaches are not effective in alleviating the immune manifestations of the disease. Some studies have found that only about 40% of schizophrenia patients display signs of immune activation, e.g. changes in IL1B, IL6, IL8 and alpha-1-antichymotrypsin (SERPINA3) transcript levels (Fillman et al, 2013 and Fillman et al, 2014). These findings are consistent with the proportion of schizophrenia patients displaying structural abnormalities ( Allen et al., 2009 ), but further studies are required to assess precisely the association between immune activation and brain volume. Also, changes in other cytokines related mostly to the innate immune system have been observed in brains of schizophrenia patients, including tumour necrosis factor alpha (TNF-α) ( Rao et al., 2013 ), and interferon-induced transmembrane proteins 1 and 2 (IFITM2/IFITM3) ( Saetre et al., 2007 ); as well as the microglia marker CD11b ( Rao et al., 2013 ) ( Table 1 ). In line with these findings, immunohistochemical studies have shown that the density of microglial cells and their marker, HLA-DR, are higher in post-mortem schizophrenia brains, in particular in those patients who committed suicide (Bayer et al, 1999, Radewicz et al, 2000, Steiner et al, 2006b, and Fillman et al, 2013). Microglia are the equivalent of macrophages in the brain and one of their main roles is immune defence of the CNS. Therefore, activation of these cells indicates ongoing immunological processes in the CNS.
|Marker||Description||Genetic association||CNS/CSF expression||Peripheral expression||References|
|IL-1β||Macrophage origin; pro-inflammatory; induces COX2 in CNS||rs16944
|↑/↔||↑state||Toyooka et al. (2003) ; Soderlund et al. (2009) ; Xu and He (2010) ; Miller et al. (2011) ; Fillman et al. (2013) ; Rao et al. (2013)|
|IL-1RA||Macrophage origin; anti-inflammatory||(86 bp)n repeats||↓||↑state||Toyooka et al. (2003) ; Zanardini et al. (2003) ; de Witte et al. (2014)|
|IL-6||Th2/macrophage origin; pro- and anti-inflammatory; role in autoimmune processes||rs1800795||↑/↔||↑state||Soderlund et al. (2009) ; Paul-Samojedny et al. (2010) ; Miller et al. (2011) ; Fillman et al. (2013)|
|IL-10||Th2/macrophage origin; anti-inflammatory||rs1800896
|–||↑state||Bocchio Chiavetto et al. (2002) ; Yu et al. (2004) ; He et al. (2006) ; Ozbey et al. (2009) ; Paul-Samojedny et al. (2010) ; de Witte et al. (2014)|
|IL-12B||Macrophage origin; Th1 polarisation; linked to autoimmune diseases||rs2853694||–||↑trait/state||Shirts et al. (2008) ; Miller et al. (2011) ; Tourjman et al. (2013)|
|MHC||Expressed by antigen presenting cells and other cells; antigen recognition||rs6904071
|↑HLA-DR||–||Bayer et al. (1999) ; Radewicz et al. (2000) ; Steiner et al. (2006b) ; Stefansson et al. (2009) ; Corvin and Morris (2013) ; Fillman et al. (2013) ; Ripke et al. (2013) ; Walters et al., 2013|
|S100B||Glial origin; neurotrophic factor||rs9722
|↑||↑state||Rothermundt et al. (2001) ; Rothermundt et al. (2004) ; Steiner et al. (2006a) ; Zhai et al. (2011) ; Zhai et al. (2012)|
|TNF-α||Th1/NK/macrophage origin; pro-inflammatory; viral inhibitor||rs1800629||↑||↑trait||Boin et al. (2001) ; Hanninen et al. (2005) ; Miller et al. (2011) ; Rao et al. (2013)|
Signs of immune dysregulation in schizophrenia have also been observed using in vivo brain imaging. Activated microglia express the 18 kDa translocator protein (TSPO) on the mitochondrial membrane. This protein has been targeted in positron emission tomography (PET) studies by measuring binding of the radiolabeled ligand, PK11195. Studies have shown increased binding of PK11195 in total grey matter of recent onset patients with schizophrenia ( van Berckel et al., 2008 ) and in hippocampus of recovering patients ( Doorduin et al., 2009 ), suggesting activation of microglial cells in these regions at different stages of the disease. Also, astrocytes have been reported to show signs of activation in schizophrenia, as indicated by an increased release of S100B protein into the cerebrospinal fluid (CSF). S100B is a marker of nervous system damage and increased levels have been observed in the CSF of schizophrenia patients at disease onset and in drug-naïve patients (Rothermundt et al, 2004 and Steiner et al, 2006a). This protein induces the production of several other immune markers by microglia cells, including cyclooxygenase-2 (COX-2) and prostaglandin E2 (PGE2) ( Najjar et al., 2013 ), which are considered to be potential novel drug targets for the treatment of schizophrenia (Laan et al, 2010 and Weiser et al, 2012).
Interestingly, many other cytokines showing changes in schizophrenia brains and CSF can be linked to microglia activation (IL-1β, IL-12, TNF-α) or are secreted by activated astrocytes [IL-6, IL-10, transforming growth factor beta (TGF-β)]. It is hypothesized that the interaction between these two glial cell types increases the production of quinolinic acid by microglia and kynurenic acid (KYNA) by astrocytes ( Kroken et al., 2014 ). These metabolites activate N-methyld-aspartate (NMDA) receptors ( Muller and Schwarz, 2006 ), which provides a direct link between immune activation and hypoglutamatergic neurotransmission in schizophrenia. KYNA has been found to be elevated in the CSF of drug-naïve first episode schizophrenia patients ( Erhardt et al., 2001 ), as well as in chronically ill patients ( Linderholm et al., 2012 ), consistent with findings from post-mortem studies ( Schwarcz et al., 2001 ). Drugs targeting the kynurenine pathway have shown positive effects on cognitive function in animal models ( Wu et al., 2014 ), but have not yet been tested in schizophrenia patients.
2.2. Peripheral markers
Several studies have suggested that immune alterations in the CNS may originate from peripheral immune activation, crossing the blood–brain barrier in a subgroup of patients (Kirch et al, 1985 and Kirch et al, 1992). Peripheral cytokines can cross the blood–brain barrier and are known to perturb brain function through the hypothalamic–pituitary–adrenal (HPA) axis, precipitating changes in mood, behaviour and cognition ( Watanabe et al., 2010 ). Although this causality is not well-established, characteristic immune imbalances are observed in the blood of schizophrenia patients ( Table 1 ). The majority of studies have focused on cytokine changes in serum of schizophrenia patients and have been extensively reviewed in several meta-analyses (Potvin et al, 2008, Miller et al, 2011, and Tourjman et al, 2013). Importantly, a review from 2008 ( Potvin et al., 2008 ) challenged the previous hypothesis of blunted Th1 and enhanced Th2 responses in schizophrenia, reporting increased IL-1RA levels in both unmedicated and treated patients, elevated IL-6 only in the untreated group and high sIL-2R solely in drug-treated patients. A subsequent review ( Miller et al., 2011 ) focused on evaluating differences between first episode and relapsed patients and found that the plasma concentrations of IL-1β, IL-6 and TGF-β were elevated in both patient groups and normalised with antipsychotic treatment. This suggested that these represent disease state markers. In contrast, the levels of IL-12, IFN-γ, TNF-α and sIL-2R were increased in patients but did not normalise with treatment, suggesting that these changes may represent trait markers. The most recent meta-analysis evaluated antipsychotic drug effects from follow-up studies ( Tourjman et al., 2013 ), suggesting that treatment with antipsychotics decreases levels of IL-1β and IFN-γ, and increases IL-12 and sIL-2R levels. It should be noted that these studies did not control for potential confounding factors such as body mass index or smoking, which can significantly affect cytokine levels ( Tappia et al., 1995 ). The most robust analysis assessing cytokine levels in first onset and drug-naïve schizophrenia patients to date has revealed a mixed pro- and anti-inflammatory profile, with limited response of cytokines to treatment, although some important cytokines were not investigated in this study ( de Witte et al., 2014 ).
It has been shown that blood-based molecular biomarker signatures can be utilised to distinguish schizophrenia patients from healthy controls and bipolar disorder patients (Domenici et al, 2010, Schwarz et al, 2010, and Schwarz et al, 2012a). Interestingly, many of the differentially regulated molecules are involved in immune system regulation. We have shown that certain immune markers (macrophage migration inhibitory factor, IL-8, IL-1RA, IL-18, and IL-16) can be utilised to identify a subgroup of schizophrenia patients with prominent immune changes, in contrast to another distinct subgroup of patients with changes in growth factor and hormonal pathways ( Schwarz et al., 2014 ). In another study, we found that certain immune markers (IL-6R, CD5L, IL-17) are specifically changed prior to the manifestation and diagnosis of schizophrenia, but not in pre-onset bipolar disorder patients ( Schwarz et al., 2012b ). In addition, the levels of TGF-α, CD5L, CD40, macrophage-derived chemokine and tumour necrosis factor receptor like 2 protein have been associated with the prediction of relapse in schizophrenia ( Schwarz et al., 2012c ). These results suggest that schizophrenia may be linked to a systemic change in inflammatory activity that also affects the brain.
Altered expression of plasma cytokines may originate from aberrant immune cell function. Profiling studies of lymphocytes from schizophrenia patients have provided evidence that immune processes are involved also at the cellular level (Xu et al, 2012 and Sainz et al, 2013). Differences in the subtypes of immune cell populations are observed in schizophrenia patients. In drug-naïve patients, increased numbers of total lymphocytes, T lymphocytes (CD3-positive), T helper cells (CD4-positive) and a higher ratio between T helper and T cytotoxic cells (CD4/CD8) have been observed, while the proportion of T lymphocytes was reduced ( Miller et al., 2013 ). In acutely relapsed patients, a higher proportion of CD4-positive and CD56-positive cells (T helper and natural killer cells, respectively) have been observed ( Miller et al., 2013 ). Following treatment, the CD4/CD8 ratio decreased and the concentration of CD56-positive cells increased ( Miller et al., 2013 ). It is important to mention that very few studies have investigated the distribution of rare but functionally important blood cell populations in schizophrenia patients ( Drexhage et al., 2011 ), therefore these results require further critical validation. Several studies have suggested a role of the mononuclear phagocyte system in the pathophysiology of psychiatric disorders (Drexhage et al, 2010 and Drexhage et al, 2011). For example, changes in inflammatory gene expression patterns were observed in monocytes of 60% of recent onset patients with schizophrenia ( Drexhage et al., 2010 ).
Blood cells from schizophrenia patients show abnormalities not only in numbers, but also in function, such as altered responses to mitogenic stimulation ( Craddock et al., 2007 ) and in association with smoking ( Herberth et al., 2010 ). Processes that underlie abnormal blood cell function in schizophrenia are similar to those in the brain and involve mostly cell cycle, intracellular signalling, oxidative stress and metabolism pathways (Vawter et al, 2004, Bowden et al, 2006, Craddock et al, 2007, and Herberth et al, 2011). This similarity is not surprising, since it is known that blood and CNS gene expression patterns are correlated ( Sullivan et al., 2006 ). We have also identified a reproducible cellular molecular signature associated with altered immune function of blood cells isolated from first onset and drug-naïve schizophrenia patients ( Herberth et al., 2014 ). Further studies on lymphocytes as a functional model of the disease may help to unravel the complex molecular mechanisms underlying schizophrenia.
Recent studies suggest that the perturbations in immune system function seen in psychiatric disorders may result from failure to mount an appropriate inflammatory response. Such an event could be related to impaired metabolism (Nilsson et al, 2006 and Craddock et al, 2007), as inflammatory responses consume large amounts of energy ( Peters, 2006 ), largely due to rapid immune cell proliferation, migration and cytokine production. However, it is still not clear why the inflammatory response appears to be altered in some schizophrenia patients. Initially, it was thought that this was secondary to frequently occurring weight gain, metabolic syndrome and type II diabetes, attributed as a side effect of antipsychotic medications such as clozapine and olanzapine ( Pramyothin and Khaodhiar, 2010 ). This comes from an observation that metabolic disorders are associated with low grade systemic inflammatory conditions. However, a few studies have suggested that drug-naïve schizophrenia patients, as well as first-degree relatives of schizophrenia patients, also have impaired insulin signalling (Ryan et al, 2003, Spelman et al, 2007, and Guest et al, 2011). In support of this, we have recently reported changes in glycolytic metabolism in stimulated peripheral blood mononuclear cells isolated from schizophrenia patients, suggesting a direct link between immune function and glucose metabolism ( Herberth et al., 2011 ). More recently, it has been reported that increased glucose transport via glucose transporter GLUT1 increases the pro-inflammatory response in macrophages ( Freemerman et al., 2014 ), which may be relevant for the microglial hypothesis of schizophrenia. This occurs as GLUT1 is the rate limiting glucose transporter on proinflammatory macrophages and other immune cells (Peters, 2006 and Freemerman et al, 2014). These results indicate an association between energy metabolism pathways and inflammatory response, two processes that are often perturbed in schizophrenia.
3. Triggers of immune activation in schizophrenia
3.1. Genetic factors
Studies in monozygotic twins have shown that the genetic contribution to schizophrenia accounts for approximately 50% ( Tsuang, 2000 ). Variants of several genes, including disrupted in schizophrenia-1 (DISC-1), neuregulin-1 (NRG-1) and catechol-O-methyltransferase (COMT), have been identified as potential risk factors for schizophrenia, but none of these showed statistical significance in subsequent genome-wide association studies. Contradictory results have been reported for the role of cytokine-encoding genes, including polymorphism of the interleukin (IL) 1 gene complex (Katila et al, 1999, Zanardini et al, 2003, Papiol et al, 2004, Saiz et al, 2006, Xu and He, 2010, and Shibuya et al, 2013),IL2( Paul-Samojedny et al., 2013 ),IL3RA( Lencz et al., 2007 ),IL6(Paul-Samojedny et al, 2010, Zakharyan et al, 2012, and Paul-Samojedny et al, 2013),IL10(Bocchio Chiavetto et al, 2002, Yu et al, 2004, He et al, 2006, Ozbey et al, 2009, and Paul-Samojedny et al, 2010),IL12B(Ozbey et al, 2008 and Shirts et al, 2008),IL18(Shirts et al, 2008 and Liu et al, 2011) and interferon (IFN) gamma ( Paul-Samojedny et al., 2011 ). Although most of these genetic findings are not significant in genome-wide comparisons, they are consistent with studies that found altered levels of these cytokines in brain and plasma of schizophrenia patients ( Table 1 ). For example, two studies have found that the high IL-10-producing haplotype is more frequent in schizophrenia patients (Bocchio Chiavetto et al, 2002 and Ozbey et al, 2009) and similar findings have been reported for theTNFAgene (Boin et al, 2001 and Hanninen et al, 2005). The above genes may also represent a link between genetic and environmental risk factors ( Fig. 1 ), such as the association reported between polymorphisms in IL-18 pathway genes and susceptibility to herpes simplex virus (HSV) 1 ( Shirts et al., 2008 ).
Recent progress in microarray and sequencing technologies has allowed the investigation of genetic associations at the genomic level. The first GWAS in schizophrenia examined about 500,000 single-nucleotide polymorphisms (SNPs) and revealed a strong effect only for the locus near the colony stimulator factor receptor 2 alpha (CSF2RA) gene ( Lencz et al., 2007 ). Subsequent sequencing revealed an association with the IL-3 receptor alpha (IL3RA) gene, which has been confirmed by other studies (Lencz et al, 2007, Sun et al, 2008, and Sun et al, 2009). The following extensive genome-wide scans excluded the single gene effects in schizophrenia and suggested multiple loci at distant genomic regions. One of the most reproducible findings involves the major histocompatibility complex (MHC) region (6p21.3–6p22.1) ((Purcell et al, 2009), (Shi et al, 2009), (Stefansson et al, 2009), and (Schizophrenia Psychiatric Genome-Wide Association Study GWAS Consortium, 2011);Bergen et al, 2012 and Ripke et al, 2013) [reviewed in ( Corvin and Morris, 2013 )]. TheMHCregion spans more than 200 genes, many of which encode key regulators of immune system function, such as the human leukocyte antigen (HLA) genes,TNFsuperfamily genes and complement cascade genes ( The MHC Sequencing Consortium, 1999 ). Two recent GWAS have examined the genetic background of five major psychiatric disorders ( Cross-Disorder Group of the Psychiatric Genomics Consortium; Genetic Risk Outcome of Psychosis (GROUP) Consortium, 2013 ; Lee et al., 2013 ). Although an overlap has been observed for the different conditions, in particular between schizophrenia and bipolar disorder ( Lee et al., 2013 ), polymorphisms within theMHCregion were specific for schizophrenia ( Cross-Disorder Group of the Psychiatric Genomics Consortium; Genetic Risk Outcome of Psychosis (GROUP) Consortium, 2013 ). MHC is a group of proteins involved in antigen recognition. Therefore, it is thought thatMHCgene polymorphisms may render individuals more susceptible to disease by altering immune system function. A few studies have specifically addressed the expression of schizophrenia susceptibility genes in post-mortem brains from schizophrenia patients and showed concordance with the genetic findings regarding theMHCregion (Kano et al, 2011 and Sinkus et al, 2013). A recent study has suggested that epigenetic regulation of immune-related genes by methylation may also play a role in schizophrenia pathogenesis ( Aberg et al., 2014 ).
3.2. Infectious agents
Genetic factors most likely contribute to schizophrenia pathogenesis only in a subgroup of patients and the immune activation in schizophrenia often cannot be attributed to genetic underpinning. This suggests a significant role of environmental factors such as infections in activating the immuno-phenotype. There is evidence that viral infections during pregnancy may increase the risk to develop schizophrenia in the offspring ( Brown, 2006 ). An association between schizophrenia and prenatal exposure to influenza has been reported for decades ( Maurizi, 1984 ) but only a study from 2004 has substantiated the direct link between maternal anti-influenza antibody levels and the risk of schizophrenia, in particular during early pregnancy ( Brown et al., 2004a ). The prevalence of schizophrenia is also higher in the offspring of mothers seropositive for HSV-2 andToxoplasma gondii(Buka et al, 2001a and Brown et al, 2005), although contradicting results have also been reported ( Khandaker et al., 2013 ). In addition, high maternal IL-8 and TNF-α levels during pregnancy have been associated with an increased risk of schizophrenia in the offspring (Buka et al, 2001b and Brown et al, 2004b).
Perinatal infections with other viruses such as cytomegalovirus, mumps virus, CBV-5, but not with bacteria, increase the risk of schizophrenia ( Khandaker et al., 2012 ). In addition, infections in adulthood have been linked with the onset of schizophrenia. High levels of IgG antibodies against cytomegalovirus andToxoplasma gondiiwere measured in serum and CSF of individuals with recent onset schizophrenia and normalised with antipsychotic treatment ( Leweke et al., 2004 ). Interestingly, markers related to infectious agents show correlations with functional deficits in schizophrenia. IgG antibodies againstToxoplasma gondiihave shown positive correlations with psychotic symptoms in ultra-high risk patients ( Amminger et al., 2007 ). In another study, levels of antibodies to HSV-1 have been associated with cognitive symptoms in schizophrenia ( Yolken et al., 2011 ), consistent with the known impact of this virus on brain areas involved in cognition (Schretlen et al, 2010 and Prasad et al, 2012). In addition, the effect of HSV-1 exposure on cognitive symptoms was additive to the effect of serum levels of C-reactive protein (CRP) ( Dickerson et al., 2012 ).
3.3. Autoimmune reactions
The altered function of central and peripheral immune system in schizophrenia patients and the existence of psychotic features in patients suffering from autoimmune diseases have led to studies of the link between autoimmune disorders and schizophrenia. For example, some studies have shown that schizophrenia is associated with type 1 diabetes mellitus ( Eaton et al., 2006 ), although this is thought to be rare ( Finney, 1989 ). Also, increased levels of certain auto-antibodies have been observed in schizophrenia patients. In first episode patients, the prevalence of anti-cardiolipin and NMDA receptor antibodies is increased, while in the general patient population a high prevalence of antibodies against molecules such as DNA, the dopamine receptor, lupus anticoagulant and rheumatoid factor have been reported [reviewed in ( Ezeoke et al., 2013 )]. Antibodies against the NMDA receptor have been found in approximately 5–10% of schizophrenia patients, but not in bipolar disorder patients (Zandi et al, 2011, Tsutsui et al, 2012, Ezeoke et al, 2013, and Steiner et al, 2013). These findings suggest an explicit link to impaired glutamatergic transmission in schizophrenia and related cognitive perturbations.
Psychosocial stress is known to contribute to the onset of autoimmune disease or affect disease progression ( Wright et al., 1996 ). Clinical features such as cognitive deficit and acute psychosis known to be associated with schizophrenia can also be present in patients suffering from systemic lupus erythematosus (SLE) ( Brey et al., 2002 ). At the molecular level, similar pro-inflammatory molecules have been found to be elevated in first onset schizophrenia patients and in SLE patients (Matei and Matei, 2002 and Schwarz et al, 2012a). In a comprehensive Danish study on 7704 subjects carried out between 1981 and 1998, patients with a history of autoimmune disease had a 45% increased risk of developing schizophrenia ( Eaton et al., 2006 ). Conversely, nine autoimmune conditions had higher lifetime prevalence in schizophrenia than in control groups (thyrotoxicosis, intestinal malabsorption, acquired hemolytic anaemia, chronic active hepatitis, interstitial cystitis, alopecia areata, myositis, polymyalgia rheumatic, Sjögren's syndrome) ( Eaton et al., 2006 ). In a similar study, prior autoimmune disease was associated with 29% higher risk of schizophrenia and increased synergistically with previous infections ( Benros et al., 2011 ). Interestingly, an opposite relationship has been observed for schizophrenia and rheumatoid arthritis (RA). Schizophrenia patients have a 2–3 fold decreased risk of RA in comparison to healthy subjects, and patients with RA appear to have reduced risk of schizophrenia (Eaton et al, 1992, Oken and Schulzer, 1999, and Torrey and Yolken, 2001). There is also an association of schizophrenia with atopic disorders and allergies. A nation-wide study has shown altered risk of atopic conditions such as asthma, allergic rhinitis and urticaria among schizophrenia patients ( Chen et al., 2009 ).
4. Immunomodulatory interventions in schizophrenia
Inflammatory pathways constitute a potential target for the development of future schizophrenia treatments ( Fig. 1 ). It is interesting in this regard that the most effective antipsychotic drug to date, clozapine, has been shown to mediate long-term immune suppression (Leykin et al, 1997, Maes et al, 1997, and Song et al, 2000) and attenuate microglial activation ( Hu et al., 2012 ). The anti-inflammatory properties of clozapine might also be related to its side effects — agranulocytosis and neutropenia (decreased levels of mononuclear leukocytes), hence the pre-requisite for monitoring the immune parameters during clozapine treatment ( Roge et al., 2012 ). Since other antipsychotic drugs show only limited anti-inflammatory effects on the immune system, several adjunctive treatments have been tested for alleviating psychotic symptoms. Aspirin is an inhibitor of cyclooxigenase (COX)-1 and modulator of COX-2 activity. Both of these enzymes produce prostaglandins, which mediate inflammation. In a study from 2010 ( Laan et al., 2010 ), aspirin administration was found to reduce total and positive PANSS (Positive and Negative Syndrome Scale) scores. Importantly, higher efficacy was observed with lower Th1/Th2 activity measured by evaluating the IFN-γ/IL-4 ratio. In another study, aspirin add-on therapy significantly reduced general psychopathology PANSS scores and also showed a trend for reduced total and positive PANSS scores ( Weiser et al., 2012 ).
Similarly, treatment with a selective COX-2 inhibitor celecoxib decreased symptoms in recent onset and chronic schizophrenia patients (Muller et al, 2004, Muller et al, 2010, and Akhondzadeh et al, 2007), in particular those with lower soluble TNF-α receptor-1 concentrations ( Muller et al., 2004 ). However, an extensive meta-analysis revealed that the overall effect of celecoxib supplementation in schizophrenia was not significant ( Sommer et al., 2014 ). Also adjunctive minocycline, an antibiotic with anti-inflammatory and neuroprotective properties targeting microglia, yielded inconclusive results ( Sommer et al., 2014 ). Only one study has been carried out utilising N-acetylcysteine (NAC) supplementation in schizophrenia ( Berk et al., 2008 ) and this resulted in reduced total, negative and general psychopathology PANSS scores. NAC is a glutathione precursor with anti-inflammatory and anti-oxidant properties, and it also has modulatory glutamatergic and neurotropic effects that may benefit schizophrenia patients (Lavoie et al, 2008, Bulut et al, 2009, and Dean et al, 2011). Further studies are required to assess the utility of immunomodulatory therapies at different stages of the disease and their relationship to inflammatory markers.
5. Future directions
5.1. Clinical need
To enable personalised medicine strategies, there is an urgency to further investigate the biological abnormalities associated with severe mental illnesses such as schizophrenia ( Maccarrone et al., 2013 ). Thus, early and accurate empirical biomarkers are needed to aid the current interview-based clinical diagnosis ( Fig. 2 ). Moreover, establishing the molecular signatures underpinning the prodromal stages, early onset of the disease and managing the chronicity of the disease, will not only aid in increasing our understanding of the pathophysiology of schizophrenia, but will also improve the disease diagnosis or guide clinicians towards a better pharmacotherapeutic selection. Furthermore, current antipsychotic treatments targeting patients suffering from schizophrenia are not effective for all patients and many suffer from side effects. This can lead to problems with compliance and switching of drugs by clinicians multiple times in order to achieve efficacious responses ( Valenstein et al., 2004 ).
As immune dysregulation is an intrinsic part of schizophrenia at the early onset as well as the late stages of the disease, using molecular biomarkers to identify subgroups of patients with prominent immune changes could help to inhibit disease progression and improve outcomes ( Schwarz et al., 2014 ). Molecular profiles aiding patient stratification may also be used for identifying those patients who are most likely to respond to a particular drug intervention ( Madaan et al., 2010 ). A biomarker-guided treatment in schizophrenia would lead to improvements in clinical practice, as it would enable development of new and personalized treatment strategies and decision rules for continuation or termination of a selected treatment. This would reduce unnecessary drug exposure and side effects for the non-responders. The healthcare system would benefit by cutting costs associated with the large number of non-responders.
5.2. Limitations and implications
In regard to the adjuvant therapies for schizophrenia, it has been observed that anti-inflammatory intervention is more effective at the early stages of the disease, when the pathological changes associated with chronic inflammatory processes are not severe ( Muller et al., 2010 ). This assumes that alterations at the later stages of the disease might be irreversible or require prolonged anti-inflammatory treatment. Despite evidence that there are subgroups of patients with distinct molecular profiles in serum or plasma related to response to treatment (Muller et al, 2004, Laan et al, 2010, and Schwarz et al, 2013), no clinical trials to date have applied patient enrichment strategies in their design. We suggest that stratifying patients according to their inflammatory profile would improve outcomes of the clinical trials and help to minimise adverse effects ( Table 2 ). This stratification approach could be based on genetic, imaging and molecular biomarker data regarding immune dysfunction in schizophrenia, as described in this review. This would help to facilitate a personalized medicine approach in schizophrenia, which could ultimately lead to improved treatment outcomes for patients. In addition, it has been suggested that indiscriminate suppression of the immune system may not be the most optimal way to treat immune imbalances in schizophrenia ( Kroken et al., 2014 ). Instead, more targeted approaches should be tested, such as specific suppression of excessive cytokine secretion via treatment with humanised monoclonal antibody approaches. Also, the relationship between particular immune markers and symptom severity should be further evaluated for identification of additional relevant drug targets.
|Patient heterogeneity||➢ Stringent inclusion/exclusion criteria
➢ Patient stratification by immune status
➢ Systems biology approaches
➢ Clinical and molecular target identification
➢ Diagnostic and prognostic biomarkers
➢ Gender associations
|Heterogeneity of disease stages||➢ Evaluation of the immune biomarkers in prodromal, recent onset and chronic patients
➢ Longitudinal studies
➢ Impact of antipsychotic treatment
➢ Prevention/early intervention trials
|Low response to add-on treatment||➢ Patient enrichment strategies in clinical trial design
➢ Application of prognostic biomarkers
➢ Prior power calculations to enhance effect sizes
➢ Biomarker-targeted treatments
➢ Use of drugs crossing blood–brain barrier
➢ Replication studies
|Side effects||➢ Prognostic and monitoring biomarkers
➢ Adjunctive pharmacological intervention (e.g. anti-diabetic)
|Specificity||➢ Differential expression of neuroimmune biomarkers between schizophrenia, bipolar disorder and other neuropsychiatric diseases
➢ Molecular similarities between schizophrenia and immune conditions for improved therapeutic strategies
It should be noted that a significant proportion of the reports related to neuroimmune schizophrenia biomarkers are underpowered or have ill-defined or non-stringent inclusion and exclusion criteria ( Table 2 ). The outcome of such studies is generally only suggestive and the authors recommend follow up investigations on a larger scale, ideally in independent cohorts. Moreover, few longitudinal follow up studies have been performed to validate potential candidate biomarkers, which might only represent a snapshot of the disease progression and differ between prodromal, recent onset and chronic stages of the disease, or be related to gender ( Ramsey et al., 2013 ). Surrogate markers should be used in conjunction with clinical endpoints, with careful assessments of reproducibility and validity. A combination of clinical, genetic, imaging, “omics” and multivariate analysis methods (systems biology) would help to achieve a comprehensive correlative assessment throughout disease progression. Finally, the issue of specificity of the neuroinflammatory biomarkers between schizophrenia and other neuropsychiatric disorders should be evaluated in more detail, in particular in relation to bipolar disorder and other relevant differential diagnostic disease groups.
6. Conclusions and implications
Central nervous system disorders, especially those of psychiatric nature, may present unique challenges to the acceptance of peripheral markers ( Katz, 2004 ). Although there are currently no established validated biomarkers for treatment efficacy or patient stratification in schizophrenia, it is has been shown that central and peripheral inflammatory status is a significant component of the early and late stages of the disease. As ongoing studies aim to investigate the relationship between the cause and effect of the inflammatory component of schizophrenia, advances in molecular profiling platforms, imaging and genetic studies have opened the possibility to understand the disease at a more fundamental level. This should pave the way for designing biomarker-based tests for stratification of patients based on molecular profiles at different stages of the disease.
Stratification of schizophrenia patients based on inflammation profiles to assign the right treatments to the right patients is consistent with the personalised medicine approach that is emerging in other areas of medicine such as oncology. In breast cancer, for example, over-expression of the human epidermal growth factor receptor 2 (HER2) has been used to identify those female patients who are most likely to benefit from treatment with the monoclonal antibody-based treatment, Trastuzumab ( Demonty et al., 2007 ). A related approach in schizophrenia research could lead to novel therapeutic targets and to the personalization of treatment approaches, increasing the chances of a positive therapeutic outcome for each patient. Testing of blood samples could be used for stratification of patients based on whether they show distinct changes in key biological pathways such as the effects on immune dysfunction described here. In addition, new adjunctive drug treatment strategies could be developed which target the inflammatory pathway for combined treatments with either existing or newly developed antipsychotics. Targeting the inflammatory component of multi-factorial diseases such as schizophrenia requires well-designed clinical studies to correlate molecular data with clinical ratings. This comprehensive strategy should enable not only the use of anti-inflammatory agents at late stages to manage disease symptoms, but also at the prodromal and in the early phases of psychosis or schizophrenia. Moreover, the use of such approaches at different stages of the disease might lead to alleviation of some symptoms, preventing disease onset or slowing its progression.
Role of funding source
This study was supported by the Virgo consortium, funded by the Dutch government project number FES0908; by the Netherlands Genomics Initiative (NGI) project number 050-060-452; by the Dutch Fund for Economic Structure Reinforcement, the NeuroBasic PharmaPhenomics project (no. 0908); by the EU FP7 funding scheme: Marie Curie Actions Industry Academia Partnerships and Pathways (nr. 286334, PSYCH-AID project) and by the Stanley Medical Research Institute (SMRI).
JT and HR managed the literature searches and prepared the first draft of the manuscript. All authors contributed to and have approved the final manuscript.
Conflict of interest
JT is a consultant for Psynova Neurotech Ltd. and HR, PCG and SB are consultants for Myriad-RBM, although this does not interfere with policies of the journal regarding sharing of data or materials.
This study was supported by the Virgo consortium, funded by the Dutch government project number FES0908; by the Netherlands Genomics Initiative (NGI) project number 050-060-452; by the Dutch Fund for Economic Structure Reinforcement, the NeuroBasic PharmaPhenomics project (no. 0908); by the EU FP7 funding scheme: Marie Curie Actions Industry Academia Partnerships and Pathways (nr. 286334, PSYCH-AID project) and by the Stanley Medical Research Institute (SMRI).
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a Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK
b Department of Neuroscience, Erasmus Medical Centre, Rotterdam, The Netherlands
1 Authors contributed equally.
© 2014 Published by Elsevier B.V.