Man K. Chan

Evidence for disease and antipsychotic medication effects in post-mortem brain from schizophrenia patients

Extensive research has been conducted on post-mortem brain tissue in schizophrenia (SCZ), particularly the dorsolateral prefrontal cortex (DLPFC). However, to what extent the reported changes are due to the disorder itself, and which are the cumulative effects of lifetime medication remains to be determined. In this study, we employed label-free liquid chromatography–mass spectrometry-based proteomic and proton nuclear magnetic resonance-based metabonomic profiling approaches to investigate DLPFC tissue from two cohorts of SCZ patients grouped according to their lifetime antipsychotic dose, together with tissue from bipolar disorder (BPD) subjects, and normal controls (n=10 per group). Both techniques showed profound changes in tissue from low-cumulative-medication SCZ subjects, but few changes in tissue from medium-cumulative-medication subjects. Protein expression changes were validated by Western blot and investigated further in a third group of subjects who were subjected to high-cumulative-medication over the course of their lifetime. Furthermore, key protein expression and metabolite level changes correlated significantly with lifetime antipsychotic dose. This suggests that the detected changes are present before antipsychotic therapy and, moreover, may be normalized with treatment. Overall, our analyses revealed novel protein and metabolite changes in low-cumulative-medication subjects associated with synaptogenesis, neuritic dynamics, presynaptic vesicle cycling, amino acid and glutamine metabolism, and energy buffering systems. Most of these markers were altered specifically in SCZ as determined by analysis of the same brain region from BPD patients.

Antipsychotic Treatment Alters Protein Expression Associated with Presynaptic Function and Nervous System Development in Rat Frontal Cortex

Haloperidol and olanzapine are widely used antipsychotic drugs in the treatment of schizophrenia and other psychotic disorders. Despite extensive research efforts within the biopharmaceutical industry and academia, the exact molecular mechanisms of their action remain largely unknown. Since the response of patients to existing medications can be variable and often includes severe side effects, it is critical to increase our knowledge on their mechanism of action to guide clinical usage and new drug development. In this study, we have employed the label-free liquid chromatography tandem mass spectrometry (LC-MSE) to identify differentially expressed proteins in rat frontal cortex following subchronic treatment with haloperidol or olanzapine. Subcellular fractionation was performed to increased proteomic coverage and provided insight into the subcellular location involved in the mechanism of drug action. LC-MSE profiling identified 531 and 741 annotated proteins in fractions I (cytoplasmic-) and II (membrane enriched-) in two drug treatments. Fifty-nine of these proteins were altered significantly by haloperidol treatment, 74 by olanzapine and 21 were common to both treatments. Pathway analysis revealed that both drugs altered similar classes of proteins associated with cellular assembly/organization, nervous system development/function (particularly presynaptic function) and neurological disorders, which indicate a common mechanism of action. The top affected canonical signaling pathways differed between the two treatments. The haloperidol data set showed a stronger association with Huntingtons disease signaling, while olanzapine treatment showed stronger effects on glycolysis/gluconeogenesis. This could either relate to a difference in clinical efficacy or side effect profile of the two compounds. The results were consistent with the findings reported previously by targeted studies, demonstrating the validity of this approach. However, we have also identified many novel proteins which have not been found previously to be associated with these drugs. Further study of these proteins could provide new insights into the etiology of the disease or the mechanism of antipsychotic medications.

Development of a blood-based molecular biomarker test for identification of schizophrenia before disease onset.

Recent research efforts have progressively shifted towards preventative psychiatry and prognostic identification of individuals before disease onset. We describe the development of a serum biomarker test for the identification of individuals at risk of developing schizophrenia based on multiplex immunoassay profiling analysis of 957 serum samples. First, we conducted a meta-analysis of five independent cohorts of 127 first-onset drug-naive schizophrenia patients and 204 controls. Using least absolute shrinkage and selection operator regression, we identified an optimal panel of 26 biomarkers that best discriminated patients and controls. Next, we successfully validated this biomarker panel using two independent validation cohorts of 93 patients and 88 controls, which yielded an area under the curve (AUC) of 0.97 (0.95–1.00) for schizophrenia detection. Finally, we tested its predictive performance for identifying patients before onset of psychosis using two cohorts of 445 pre-onset or at-risk individuals. The predictive performance achieved by the panel was excellent for identifying USA military personnel (AUC: 0.90 (0.86–0.95)) and help-seeking prodromal individuals (AUC: 0.82 (0.71–0.93)) who developed schizophrenia up to 2 years after baseline sampling. The performance increased further using the latter cohort following the incorporation of CAARMS (Comprehensive Assessment of At-Risk Mental State) positive subscale symptom scores into the model (AUC: 0.90 (0.82–0.98)). The current findings may represent the first successful step towards a test that could address the clinical need for early intervention in psychiatry. Further developments of a combined molecular/symptom-based test will aid clinicians in the identification of vulnerable patients early in the disease process, allowing more effective therapeutic intervention before overt disease onset.

Applications of blood-based protein biomarker strategies in the study of psychiatric disorders

Major psychiatric disorders such as schizophrenia, major depressive and bipolar disorders are severe, chronic and debilitating, and are associated with high disease burden and healthcare costs. Currently, diagnoses of these disorders rely on interview-based assessments of subjective self-reported symptoms. Early diagnosis is difficult, misdiagnosis is a frequent occurrence and there are no objective tests that aid in the prediction of individual responses to treatment. Consequently, validated biomarkers are urgently needed to help address these unmet clinical needs. Historically, psychiatric disorders are viewed as brain disorders and consequently only a few researchers have as yet evaluated systemic changes in psychiatric patients. However, promising research has begun to challenge this concept and there is an increasing awareness that disease-related changes can be traced in the peripheral system which may even be involved in the precipitation of disease onset and course. Converging evidence from molecular profiling analysis of blood serum/plasma have revealed robust molecular changes in psychiatric patients, suggesting that these disorders may be detectable in other systems of the body such as the circulating blood. In this review, we discuss the current clinical needs in psychiatry, highlight the importance of biomarkers in the field, and review a representative selection of biomarker studies to highlight opportunities for the implementation of personalized medicine approaches in the field of psychiatry. It is anticipated that the implementation of validated biomarker tests will not only improve the diagnosis and more effective treatment of psychiatric patients, but also improve prognosis and disease outcome.

Serum proteomic profiling of major depressive disorder

Much has still to be learned about the molecular mechanisms of depression. This study aims to gain insight into contributing mechanisms by identifying serum proteins related to major depressive disorder (MDD) in a large psychiatric cohort study. Our sample consisted of 1589 participants of the Netherlands Study of Depression and Anxiety, comprising 687 individuals with current MDD (cMDD), 482 individuals with remitted MDD (rMDD) and 420 controls. We studied the relationship between MDD status and the levels of 171 serum proteins detected on a multi-analyte profiling platform using adjusted linear regression models. Pooled analyses of two independent validation cohorts (totaling 78 MDD cases and 156 controls) was carried out to validate our top markers. Twenty-eight analytes differed significantly between cMDD cases and controls (P<0.05), whereas 10 partly overlapping markers differed significantly between rMDD cases and controls. Antidepressant medication use and comorbid anxiety status did not substantially impact on these findings. Sixteen of the cMDD-related markers had been assayed in the pooled validation cohorts, of which seven were associated with MDD. The analytes prominently associated with cMDD related to diverse cell communication and signal transduction processes (pancreatic polypeptide, macrophage migration inhibitory factor, ENRAGE, interleukin-1 receptor antagonist and tenascin-C), immune response (growth-regulated alpha protein) and protein metabolism (von Willebrand factor). Several proteins were implicated in depression. Changes were more prominent in cMDD, suggesting that molecular alterations in serum are associated with acute depression symptomatology. These findings may help to establish serum-based biomarkers of depression and could improve our understanding of its pathophysiology.

A combined metabonomic and proteomic approach identifies frontal cortex changes in a chronic phencyclidine rat model in relation to human schizophrenia brain pathology

Current schizophrenia (SCZ) treatments fail to treat the broad range of manifestations associated with this devastating disorder. Thus, new translational models that reproduce the core pathological features are urgently needed to facilitate novel drug discovery efforts. Here, we report findings from the first comprehensive label-free liquid-mass spectrometry proteomic- and proton nuclear magnetic resonance-based metabonomic profiling of the rat frontal cortex after chronic phencyclidine (PCP) intervention, which induces SCZ-like symptoms. The findings were compared with results from a proteomic profiling of post-mortem prefrontal cortex from SCZ patients and with relevant findings in the literature. Through this approach, we identified proteomic alterations in glutamate-mediated Ca2+ signaling (Ca2+/calmodulin-dependent protein kinase II, PPP3CA, and VISL1), mitochondrial function (GOT2 and PKLR), and cytoskeletal remodeling (ARP3). Metabonomic profiling revealed changes in the levels of glutamate, glutamine, glycine, pyruvate, and the Ca2+ regulator taurine. Effects on similar pathways were also identified in the prefrontal cortex tissue from human SCZ subjects. The discovery of similar but not identical proteomic and metabonomic alterations in the chronic PCP rat model and human brain indicates that this model recapitulates only some of the molecular alterations of the disease. This knowledge may be helpful in understanding mechanisms underlying psychosis, which, in turn, can facilitate improved therapy and drug discovery for SCZ and other psychiatric diseases. Most importantly, these molecular findings suggest that the combined use of multiple models may be required for more effective translation to studies of human SCZ.

Converging evidence of blood-based biomarkers for schizophrenia: an update.

This chapter has carried out a review of the literature and combined this with the results of in-house studies to identify candidate blood-based biomarkers for schizophrenia and antipsychotic drug response. Literature searches retrieved 185 publications describing a total of 273 schizophrenia biomarkers identified in serum and/or plasma. Examination of seven in-house multicenter studies resulted in the identification of 137 serum/plasma biomarkers. Taken together, the findings suggested an ongoing immunological and inflammatory process in schizophrenia. This was accompanied by altered cortisol levels which suggested activated stress response and altered hypothalamic-pituitary-adrenal axis function in these patients. The authors conclude that such biomarkers may prove useful as additional parameters for characterizing specific immune and/or metabolic or hormonal subsystems in schizophrenia and might, therefore, facilitate the development of future patient stratification and personalized medicine strategies.

The use of proteomic biomarkers for improved diagnosis and stratification of schizophrenia patients

Schizophrenia is characterized by a wide spectrum of clinical manifestations, including strong effects on mood and behavior. Patients can also suffer from serious comorbidities including immune system or metabolic abnormalities. Recent advances using proteomic profiling approaches have increased our understanding of these molecular effects and have laid the groundwork for unraveling the heterogeneity of this broadly defined disease. These findings could lead to improved diagnosis and stratification of patients through identification of biochemically different disease subtypes and personalized medicine approaches. The inclusion of molecular signatures in psychiatry will be an important leap forward in providing more effective treatment of patients suffering from this debilitating disorder.

Distinct proteomic profiles in post-mortem pituitary glands from bipolar disorder and major depressive disorder patients

Disturbances of the hypothalamic-pituitary-adrenal axis have been implicated in the pathophysiology of bipolar disorder (BD) and major depressive disorder (MDD). To examine this further, we carried out proteomic profiling of post-mortem pituitaries from 13 BD and 14 MDD patients, in comparison to 15 controls. Liquid chromatography-mass spectrometry (LC-MS(E)) analysis showed that BD patients had significantly increased levels of the major pituitary hormones pro-opiomelanocortin (POMC) and galanin. BD patients also showed changes in proteins associated with gene transcription, stress response, lipid metabolism and growth signalling. In contrast, LC-MS(E) profiling revealed that MDD patients had significantly decreased levels of the prohormone-converting enzyme carboxypeptidease E and follow-up enzymatic analysis showed decreased activity of prolyl-oligopeptidase convertase. This suggested that altered prohormone processing may occur in pituitaries of MDD patients. In addition, MDD patients had significant changes in proteins involved in intracellular transport and cytoskeletal signalling. Finally, we carried out selective reaction monitoring (SRM) mass spectrometry profiling for validation of protein changes in key biological pathways. This confirmed increased POMC levels in BD patients with no change in the levels of this prohormone in MDD. This study demonstrates that proteomic profiling analysis of the pituitary can lead to new insights into the pathophysiology of BD and MDD. Also, given that the pituitary directly releases a variety of bioactive molecules into the bloodstream, many of the proteins identified here could serve as focal points in the search for peripheral biomarkers in clinical or drug treatment studies of BD and MDD patients.

Serum proteomic profiles of depressive subtypes

Depression is a highly heterogeneous disorder. Accumulating evidence suggests biological and genetic differences between subtypes of depression that are homogeneous in symptom presentation. We aimed to evaluate differences in serum protein profiles between persons with atypical and melancholic depressive subtypes, and compare these profiles with serum protein levels of healthy controls. We used the baseline data from the Netherlands Study of Depression and Anxiety on 414 controls, 231 persons with a melancholic depressive subtype and 128 persons with an atypical depressive subtype for whom the proteomic data were available. Depressive subtypes were previously established using a data-driven analysis, and 171 serum proteins were measured on a multi-analyte profiling platform. Linear regression models were adjusted for several covariates and corrected for multiple testing using false discovery rate q-values. We observed differences in analytes between the atypical and melancholic subtypes (9 analytes, q<0.05) and between atypical depression and controls (23 analytes, q<0.05). Eight of the nine markers differing between the atypical and melancholic subtype overlapped with markers from the comparison between atypical subtype and controls (mesothelin, leptin, IGFBP1, IGFBP2, FABPa, insulin, C3 and B2M), and were mainly involved in cellular communication and signal transduction, and immune response. No markers differed significantly between the melancholic subtype and controls. To conclude, although some uncertainties exist in our results as a result of missing data imputation and lack of proteomic replication samples, many of the identified analytes are inflammatory or metabolic markers, which supports the notion of atypical depression as a syndrome characterized by metabolic disturbances and inflammation, and underline the importance and relevance of subtypes of depression in biological and genetic research, and potentially in the treatment of depression.