Schizophrenia genomics and proteomics: are we any closer to biomarker discovery?

Computational analysis of spoken language in acute psychosis and mania

OBJECTIVES

This study aimed to (1) determine the feasibility of collecting behavioral data from participants hospitalized with acute psychosis and (2) begin to evaluate the clinical information that can be computationally derived from such data.

METHODS

Behavioral data was collected across 99 sessions from 38 participants recruited from an inpatient psychiatric unit. Each session started with a semi-structured interview modeled on a typical "clinical rounds" encounter and included administration of the Positive and Negative Syndrome Scale (PANSS).

ANALYSIS

We quantified aspects of participants' verbal behavior during the interview using lexical, coherence, and disfluency features. We then used two complementary approaches to explore our second objective. The first approach used predictive models to estimate participants' PANSS scores from their language features. Our second approach used inferential models to quantify the relationships between individual language features and symptom measures.

RESULTS

Our predictive models showed promise but lacked sufficient data to achieve clinically useful accuracy. Our inferential models identified statistically significant relationships between numerous language features and symptom domains.

CONCLUSION

Our interview recording procedures were well-tolerated and produced adequate data for transcription and analysis. The results of our inferential modeling suggest that automatic measurements of expressive language contain signals highly relevant to the assessment of psychosis. These findings establish the potential of measuring language during a clinical interview in a naturalistic setting and generate specific hypotheses that can be tested in future studies. This, in turn, will lead to more accurate modeling and better understanding of the relationships between expressive language and psychosis.

Investigating aberrantly expressed microRNAs in peripheral blood mononuclear cells from patients with treatment‑resistant schizophrenia using miRNA sequencing and integrated bioinformatics

Treatment-resistant schizophrenia (TRS) is a common phenotype of schizophrenia that places a considerable burden on patients as well as on society. TRS is known for its tendency to relapse and uncontrollable nature, with a poor response to antipsychotics other than clozapine. Therefore, it is urgent to identify objective biological markers, so as to guide its treatment and associated clinical work. In the present study, the peripheral blood mononuclear cells (PBMCs) of patients with TRS and a healthy control group, which were gender-, age- and ethnicity-matched, were subjected to microRNA (miRNA/miR) sequencing to screen out the top three miRNAs with the highest fold change values. These were then validated in the TRS (n=34) and healthy control (n=31) groups by reverse transcription-quantitative PCR. For two of the top three miRNAs, the PCR results were in accordance with the sequencing result (P<0.01), while the third miRNA exhibited the opposite trend (P<0.01). To elucidate the functions of these two miRNAs, Homo sapiens (hsa)-miR-218-5p and hsa-miR-1262 and their regulatory network, target gene prediction was first performed using online TargetScan and Diana-micro T software. Bioinformatics analysis was then performed using functional enrichment analysis to determine the Gene Ontology terms in the category biological process and the Kyoto Encyclopedia of Genes and Genomes pathways. It was revealed that these target genes were markedly associated with the nervous system and brain function, and it was obvious that the differentially expressed miRNAs most likely participated in the pathogenesis of TRS. A receiver operating characteristic curve was generated to confirm the distinct diagnostic value of these two miRNAs. It was concluded that aberrantly expressed miRNAs in PMBCs may be implicated in the pathogenesis of TRS and may serve as specific peripheral blood-based biomarkers for the early diagnosis of TRS.

2D-DIGE as a strategy to identify serum protein biomarkers to monitor pharmacological efficacy in dopamine-dictated states of Parkinson's disease and schizophrenia

OBJECTIVES

Parkinson's disease and schizophrenia are clinical scenarios that occur due to dopaminergic deficit and hyperactivity in the midbrain, respectively. Current pharmacological interventions for these two diseases therefore aim to restore normal dopamine levels in the midbrain. But during therapy, there is a overshooting of dopamine concentrations that result in hallucinations in Parkinson's disease patients and extra-pyramidal symptoms in schizophrenic patients. This causes a lot of inconvenience to the patents and the clinicians. There are no tests currently available to monitor drug efficacy in these two neuropsychiatric diseases.

MATERIALS AND METHODS

Parkinson's disease and schizophrenic naïve patients were recruited. Serum proteins isolated from these two clinical phenotypes were labeled with fluorescent cyanine dyes and analyzed by two-dimensional difference in gel electrophoresis proteomic experiment. Differentially expressed spots that had consistent expression pattern across five sets of biological replicate gels were trypsin digested and subjected to mass spectrometric analysis for protein identification. Validation experiments were done for the identified proteins using antibody-based assay on a patient cohort that included naïve, treated, and those who had side effects.

RESULTS

Serum α- and β-globin chains were identified as differentially expressed proteins having threefold higher expressions in Parkinson's patients as compared to schizophrenia. Interestingly, concentrations of these two proteins had an inverse correlation across clinical phenotypes in the dopaminergic spectrum. RBC contamination as a source for these proteins was ruled out.

CONCLUSION

There is a clear association of free serum globin with dopaminergic clinical states. This lays a platform for protein biomarker-based monitoring of pharmacological efficacy in Parkinson's disease and schizophrenia.

The Myth of Optimality in Clinical Neuroscience

Clear evidence supports a dimensional view of psychiatric illness. Within this framework the expression of disorder-relevant phenotypes is often interpreted as a breakdown or departure from normal brain function. Conversely, health is reified, conceptualized as possessing a single ideal state. We challenge this concept here, arguing that there is no universally optimal profile of brain functioning. The evolutionary forces that shape our species select for a staggering diversity of human behaviors. To support our position we highlight pervasive population-level variability within large-scale functional networks and discrete circuits. We propose that, instead of examining behaviors in isolation, psychiatric illnesses can be best understood through the study of domains of functioning and associated multivariate patterns of variation across distributed brain systems.

A preliminary analysis of microRNA-21 expression alteration after antipsychotic treatment in patients with schizophrenia

Schizophrenia is a severe and debilitating psychiatric disorder of unknown etiology, and its diagnosis is essentially based on clinical symptoms. Despite growing evidence on the relation of altered expression of miRNAs and schizophrenia, most patients with schizophrenia usually had an extensive antipsychotic treatment history before miRNA expression profile analysis, and the pharmacological effects on miRNA expression are largely unknown. To overcome these impediments, miRNA microarray analysis was performed in peripheral blood mononuclear cells (PBMCs) obtained from patients with schizophrenia who were not on antipsychotic medication and healthy controls. Then, using quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR), we verified the top 10 miRNAs with the highest fold-change values from microarray analysis in 82 patients with schizophrenia and 43 healthy controls, and nine miRNAs demonstrated significant differences in expression levels. Finally, we compared these nine miRNA profiles before and after antipsychotic treatment. Our results revealed that serum miR-21 expression decreased strikingly in patients after antipsychotic treatment. The change of miR-21 expression was negatively correlated with improvement of positive, general psychopathology, and aggressiveness symptoms. This study preliminarily analyzed the possible changes in circulating miRNAs expression in response to antipsychotic medication for schizophrenia, and the molecular mechanisms of this needs to be further explored.

Aberrant Expression of Long Non-Coding RNAs in Schizophrenia Patients

Background

Dysfunction of long non-coding RNAs (lncRNAs) has been demonstrated to be involved in psychiatric diseases. However, the expression patterns and functions of the regulatory lncRNAs in schizophrenia (SZ) patients have rarely been systematically reported.

Material/Methods

The lncRNAs in peripheral blood mononuclear cells (PBMCs) were screened and compared between the SZ patients and demographically-matched healthy controls using microarray analysis, and then were validated by quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) method. Three verified significantly dysregulated lncRNAs of PBMCs were selected and then measured in SZ patients before and after the antipsychotic treatment. SZ symptomatology improvement was measured by Positive And Negative Syndrome Scale (PANSS) scores.

Results

One hundred and twenty-five lncRNAs were significantly differentially expressed in SZ patients compared with healthy controls, of which 62 were up-regulated and 63 were down-regulated. Concurrent with the significant decrease of the PANSS scores of patients after the treatment, the PBMC levels of lncRNA NONHSAT089447 and NONHSAT041499 were strikingly decreased (P<0.05). Down-regulation of PBMC expression of NONHSAT041499 was significantly correlated to the improvement of positive and activity symptoms of patients (r=−0.444 and −0.423, respectively, P<0.05, accounting for 16.9% and 15.1%, respectively), and was also significantly associated with better outcomes (odds ratio 2.325 for positive symptom and 12.340 for activity symptom).

Conclusions

LncRNA NONHSAT089447 and NONHSAT041499 might be involved in the pathogenesis and development of SZ, and the PBMC level of NONHSAT041499 is significantly associated with the treatment outcomes of SZ.

A Review of Biomarkers in Mood and Psychotic Disorders: A Dissection of Clinical vs. Preclinical Correlates

Despite significant research efforts aimed at understanding the neurobiological underpinnings of mood (depression, bipolar disorder) and psychotic disorders, the diagnosis and evaluation of treatment of these disorders are still based solely on relatively subjective assessment of symptoms as well as psychometric evaluations. Therefore, biological markers aimed at improving the current classification of psychotic and mood-related disorders, and that will enable patients to be stratified on a biological basis into more homogeneous clinically distinct subgroups, are urgently needed. The attainment of this goal can be facilitated by identifying biomarkers that accurately reflect pathophysiologic processes in these disorders. This review postulates that the field of psychotic and mood disorder research has advanced sufficiently to develop biochemical hypotheses of the etiopathology of the particular illness and to target the same for more effective disease modifying therapy. This implies that a "one-size fits all" paradigm in the treatment of psychotic and mood disorders is not a viable approach, but that a customized regime based on individual biological abnormalities would pave the way forward to more effective treatment. In reviewing the clinical and preclinical literature, this paper discusses the most highly regarded pathophysiologic processes in mood and psychotic disorders, thereby providing a scaffold for the selection of suitable biomarkers for future studies in this field, to develope biomarker panels, as well as to improve diagnosis and to customize treatment regimens for better therapeutic outcomes.

Aberrant microRNA expression in peripheral plasma and mononuclear cells as specific blood-based biomarkers in schizophrenia patients

Findings from multiple studies on microRNA (miRNA) expression profiling in schizophrenia patients have produced conflicting results. In order to investigate miRNA as specific biomarkers in the peripheral plasma and peripheral blood mononuclear cells (PBMC) of schizophrenia patients, expression levels of the nine most frequently reported schizophrenia-associated miRNA (miR-30e, miR-34a, miR-181b, miR-195, miR-346, miR-432, miR-7, miR-132 and miR-212) were examined in the peripheral plasma and PBMC in 25 schizophrenia patients and 13 healthy controls using quantitative real-time reverse transcription polymerase chain reaction. We observed significantly increased expressions of miR-132, miR-195, miR-30e and miR-7 in plasma samples (p<0.05 to p<0.001), and miR-212, miR-34a and miR-30e in PBMC samples (p<0.05 to p<0.01). Receiver operating characteristic curve analysis revealed that the area under the curve (AUC) of miR-30e in plasma was 0.767 (95% confidence interval [CI] 0.608-0.926) with sensitivity and specificity of 90.90% and 60.00% respectively, and the AUC of miR-30e in PBMC was 0.756 (95% CI 0.584-0.929) with sensitivity and specificity of 81.80% and 68.00%, respectively. Logistic regression analysis demonstrated that miR-30e in plasma was more sensitive to differentiate schizophrenia patients from normal controls than miR-30e in PBMC. Our findings indicate that miRNA expression is more significant in plasma than in PBMC, and suggest that miR-30e in plasma may be a more sensitive biomarker for schizophrenia diagnosis, although its aberrant expression can be detected in both plasma and PBMC.

New measures of mental state and behavior based on data collected from sensors, smartphones, and the Internet

With the rapid and ubiquitous acceptance of new technologies, algorithms will be used to estimate new measures of mental state and behavior based on digital data. The algorithms will analyze data collected from sensors in smartphones and wearable technology, and data collected from Internet and smartphone usage and activities. In the future, new medical measures that assist with the screening, diagnosis, and monitoring of psychiatric disorders will be available despite unresolved reliability, usability, and privacy issues. At the same time, similar non-medical commercial measures of mental state are being developed primarily for targeted advertising. There are societal and ethical implications related to the use of these measures of mental state and behavior for both medical and non-medical purposes.

Imprinted DLK1-DIO3 region of 14q32 defines a schizophrenia-associated miRNA signature in peripheral blood mononuclear cells

MicroRNAs (miRNAs) regulate gene expression at the post-transcriptional level and are important for coordinating nervous system development and neuronal function in the mature brain. We have recently identified schizophrenia-associated alteration of cortical miRNA biogenesis and expression in post-mortem brain tissue with implications for the dysregulation of schizophrenia candidate genes. Although these changes were observed in the central nervous system, it is plausible that schizophrenia-associated miRNA expression signatures may also be detected in non-neural tissue. To explore this possibility, we investigated the miRNA expression profile of peripheral blood mononuclear cells (PBMCs) from 112 patients with schizophrenia and 76 non-psychiatric controls. miRNA expression analysis of total RNA conducted using commercial miRNA arrays revealed that 33 miRNAs were significantly downregulated after correction for multiple testing with a false discovery rate (FDR) of 0%, which increased to 83 when we considered miRNA with an FDR<5%. Seven miRNAs altered in microarray analysis of schizophrenia were also confirmed to be downregulated by quantitative real-time reverse transcription-polymerase chain reaction. A large subgroup consisting of 17 downregulated miRNAs is transcribed from a single imprinted locus at the maternally expressed DLK1-DIO3 region on chromosome 14q32. This pattern of differentially expressed miRNA in PBMCs may be indicative of significant underlying genetic or epigenetic alteration associated with schizophrenia.

Do we have any solid evidence of clinical utility about the pathophysiology of schizophrenia?

A diagnosis of schizophrenia, as in most of psychiatric practice, is made largely by eliciting symptoms with reference to subjective, albeit operationalized, criteria. This diagnosis then provides some rationale for management. Objective diagnostic and therapeutic tests are much more desirable, provided they are reliably measured and interpreted. Definite advances have been made in our understanding of schizophrenia in recent decades, but there has been little consideration of how this information could be used in clinical practice. We review here the potential utility of the strongest and best replicated risk factors for and manifestations of schizophrenia within clinical, epidemiological, cognitive, blood biomarker and neuroimaging domains. We place particular emphasis on the sensitivity, specificity and predictive power of pathophysiological indices for making a diagnosis, establishing an early diagnosis or predicting treatment response in schizophrenia. We conclude that a number of measures currently available have the potential to increase the rigour of clinical assessments in schizophrenia. We propose that the time has come to more fully evaluate these and other well replicated abnormalities as objective potential diagnostic and prognostic guides, and to steer future clinical, therapeutic and nosological research in this direction.

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.

Biomarkers in psychiatry: drawbacks and potential for misuse

For more than 20 years, researchers have attempted to identify diagnostic and prognostic biomarkers for psychiatric disorders including schizophrenia, major (unipolar) depression, and bipolar disorder. Advocates of this research contend that identifying such biomarkers will aid in the diagnosis of these disorders, as well as the possible development of effective psychiatric medications to treat them. Currently, there are no diagnostic tests available. This is largely due to the multi-factorial nature of psychiatric disorders. Biomarker testing of individuals is also prohibitively expensive because significant expertise is required to conduct tests and follow-up counseling for the patient is often necessary. It is cautioned that widespread biomarker testing could lead to negative consequences such as discrimination in health insurance and employment, as well as selective abortion.