An integrative functional genomics approach for discovering biomarkers in schizophrenia

Mapping miRNA Research in Schizophrenia: A Scientometric Review

Micro RNA (miRNA) research has great implications in uncovering the aetiology of neuropsychiatric conditions due to the role of miRNA in brain development and function. Schizophrenia, a complex yet devastating neuropsychiatric disorder, is one such condition that had been extensively studied in the realm of miRNA. Although a relatively new field of research, this area of study has progressed sufficiently to warrant dozens of reviews summarising findings from past to present. However, as a majority of reviews cannot encapsulate the full body of research, there is still a need to synthesise the diversity of publications made in this area in a systematic but easy-to-understand manner. Therefore, this study adopted bibliometrics and scientometrics, specifically document co-citation analysis (DCA), to review the literature on miRNAs in the context of schizophrenia over the course of history. From a literature search on Scopus, 992 papers were found and analysed with CiteSpace. DCA analysis generated a network of 13 major clusters with different thematic focuses within the subject area. Finally, these clusters are qualitatively discussed. miRNA research has branched into schizophrenia, among other medical and psychiatric conditions, due to previous findings in other forms of non-coding RNA. With the rise of big data, bioinformatics analyses are increasingly common in this field of research. The future of research is projected to rely more heavily on interdisciplinary collaboration. Additionally, it can be expected that there will be more translational studies focusing on the application of these findings to the development of effective treatments.

Hepatitis C-associated late-onset schizophrenia: a nationwide, population-based cohort study

BACKGROUND

Whether infection with the hepatitis C virus (HCV) causes schizophrenia - and whether the associated risk reverses after anti-HCV therapy - is unknown; we aimed to investigate these topics.

METHODS

We conducted a nationwide, population-based cohort study using the Taiwan National Health Insurance Research Database (TNHIRD). A diagnosis of schizophrenia was based on criteria from the International Classification of Diseases, 9th revision (295.xx).

RESULTS

From 2003 to 2012, from a total population of 19 298 735, we enrolled 3 propensity-score-matched cohorts (1:2:2): HCV-treated (8931 HCV-infected patients who had received interferon-based therapy for ≥ 6 months); HCV-untreated (17 862); and HCV-uninfected (17 862) from the TNHIRD. Of the total sample (44 655), 82.81% (36 980) were 40 years of age or older. Of the 3 cohorts, the HCV-untreated group had the highest 9-year cumulative incidence of schizophrenia (0.870%, 95% confidence interval [CI] 0.556%-1.311%; p < 0.001); the HCV-treated (0.251%, 95% CI 0.091%-0.599%) and HCV-uninfected (0.118%, 95% CI 0.062%-0.213%) cohorts showed similar cumulative incidence of schizophrenia (p = 0.33). Multivariate Cox analyses showed that HCV positivity (hazard ratio [HR] 3.469, 95% CI 2.168-5.551) was independently associated with the development of schizophrenia. The HCV-untreated cohort also had the highest cumulative incidence of overall mortality (20.799%, 95% CI 18.739%-22.936%; p < 0.001); the HCV-treated (12.518%, 95% CI 8.707%-17.052%) and HCV uninfected (6.707%, 95% CI 5.533%-8.026%) cohorts showed similar cumulative incidence of mortality (p = 0.12).

LIMITATIONS

We were unable to determine the precise mechanism of the increased risk of schizophrenia in patients with HCV infection.

CONCLUSION

In a population-based cohort (most aged ≥ 40 years), HCV positivity was a potential risk factor for the development of schizophrenia; the HCV-associated risk of schizophrenia might be reversed by interferon-based antiviral therapy.

Functional characterization of two variants in the 3'-untranslated region (UTR) of transcription factor 4 gene and their association with schizophrenia in sib-pairs from multiplex families

Transcription factor 4 (TCF4) gene plays an important role in nervous system development and it always associated with the risk of schizophrenia. Since miRNAs regulate targetgenes by binding to 3'UTRs of target mRNAs, the functional variants located in 3'UTR of TCF4 are highly suggested to affect the gene expressions in schizophrenia. To test the hypothesis regarding the effects of the variants located in 3'UTR of TCF4, we conducted an in silico analysis to identify the functional variants and their predicted functions. In this study, we sequenced the 3'UTR of TCF4 in 13 multiplex schizophrenia families and 14 control families. We found two functional variants carried by three unrelated patients. We determined that the C allele of rs1272363 and the TC insert of rs373174214 might suppress post- transcriptional expression. Secondly, we cloned the region that flanked these two variants into a dual luciferase reporter system and compared the luciferase activities between the pmirGLO-TCF4 (control), pmirGLO-TCF4-rs373174214 and pmirGLO-TCF4-rs1273263. Both pmirGLO-TCF4-rs373174214 and pmirGLO-TCF4-rs1273263 caused lower reporter gene activities, as compared to the control. However, only the C allele of rs1272363 reduced the luciferase activity significantly (p = 0.0231). Our results suggested that rs1273263 is a potential regulator of TCF4 expression, and might be associated with schizophrenia.

Sex differences in DEK expression in the anterior cingulate cortex and its association with dementia severity in schizophrenia

DEK is a chromatin-remodeling phosphoprotein found in most human tissues, but its expression and function in the human brain is largely unknown. DEK depletion in vitro induces cellular and molecular anomalies associated with cognitive impairment, including down-regulation of the canonical Wnt/β-catenin signaling pathway. ToppGene analyses link DEK loss to genes associated with various dementias and age-related cognitive decline. To examine the role of DEK in cognitive impairment in severe mental illness, DEK protein expression was assayed by immunoblot in the anterior cingulate cortex (ACC) of subjects with schizophrenia. Cognitive impairment is a core feature of schizophrenia and cognitive function in subjects was assessed antemortem using the clinical dementia rating (CDR) scale. DEK protein expression was not significantly altered in schizophrenia (n = 20) compared to control subjects (n = 20). Further analysis revealed significant reduction in DEK protein expression in women with schizophrenia, and a significant increase in expression in men with schizophrenia, relative to their same-sex controls. DEK protein expression levels were inversely correlated with dementia severity in women. Conversely, in men, DEK protein expression and dementia severity were positively correlated. Notably, there was no sex difference in DEK protein expression in the control group, suggesting that this sex difference is specific to schizophrenia and not due to inherent differences in DEK expression between males and females. These results suggest a novel, sex-specific role for DEK in cognitive performance and highlight a putative sex-specific link between central nervous system DEK protein expression and a neuropsychiatric disease that is commonly associated with cognitive impairment.

Exon Array Biomarkers for the Differential Diagnosis of Schizophrenia and Bipolar Disorder

This study developed potential blood-based biomarker tests for diagnosing and differentiating schizophrenia (SZ), bipolar disorder type I (BD), and normal control (NC) subjects using mRNA gene expression signatures. A total of 90 subjects (n = 30 each for the three groups of subjects) provided blood samples at two visits. The Affymetrix exon microarray was used to profile the expression of over 1.4 million probesets. We selected potential biomarker panels using the temporal stability of the probesets and also back-tested them at two different visits for each subject. The 18-gene biomarker panels, using logistic regression modeling, correctly differentiated the three groups of subjects with high accuracy across the two different clinical visits (83-88% accuracy). The results are also consistent with the actual data and the "leave-one-out" analyses, indicating that the models should be predictive when applied to independent data cohorts. Many of the SZ and BD subjects were taking antipsychotic and mood stabilizer medications at the time of blood draw, raising the possibility that these drugs could have affected some of the differential transcription signatures. Using an independent Illumina data set of gene expression data from antipsychotic medication-free SZ subjects, the 18-gene biomarker panels produced a receiver operating characteristic curve accuracy greater than 0.866 in patients that were less than 30 years of age and medication free. We confirmed select transcripts by quantitative PCR and the nCounter® System. The episodic nature of psychiatric disorders might lead to highly variable results depending on when blood is collected in relation to the severity of the disease/symptoms. We have found stable trait gene panel markers for lifelong psychiatric disorders that may have diagnostic utility in younger undiagnosed subjects where there is a critical unmet need. The study requires replication in subjects for ultimate proof of the utility of the differential diagnosis.

Schizophrenia: A review of potential biomarkers

OBJECTIVES

Understanding the biological process and progression of schizophrenia is the first step to developing novel approaches and new interventions. Research on new biomarkers is extremely important when the goal is an early diagnosis (prediction) and precise theranostics. The objective of this review is to understand the research on biomarkers and their effects in schizophrenia to synthesize the role of these new advances.

METHODS

In this review, we search and review publications in databases in accordance with established limits and specific objectives. We look at particular endpoints such as the category of biomarkers, laboratory techniques and the results/conclusions of the selected publications.

RESULTS

The investigation of biomarkers and their potential as a predictor, diagnosis instrument and therapeutic orientation, requires an appropriate methodological strategy. In this review, we found different laboratory techniques to identify biomarkers and their function in schizophrenia.

CONCLUSION

The consolidation of this information will provide a large-scale application network of schizophrenia biomarkers.

Neurodevelopmental MACPFs: The vertebrate astrotactins and BRINPs

Astrotactins (ASTNs) and Bone morphogenetic protein/retinoic acid inducible neural-specific proteins (BRINPs) are two groups of Membrane Attack Complex/Perforin (MACPF) superfamily proteins that show overlapping expression in the developing and mature vertebrate nervous system. ASTN(1-2) and BRINP(1-3) genes are found at conserved loci in humans that have been implicated in neurodevelopmental disorders (NDDs). Here we review the tissue distribution and cellular localization of these proteins, and discuss recent studies that provide insight into their structure and interactions. We highlight the genetic relationships and co-expression of Brinps and Astns; and review recent knock-out mouse phenotypes that indicate a possible overlap in protein function between ASTNs and BRINPs.

PoCos: Population Covering Locus Sets for Risk Assessment in Complex Diseases

Susceptibility loci identified by GWAS generally account for a limited fraction of heritability. Predictive models based on identified loci also have modest success in risk assessment and therefore are of limited practical use. Many methods have been developed to overcome these limitations by incorporating prior biological knowledge. However, most of the information utilized by these methods is at the level of genes, limiting analyses to variants that are in or proximate to coding regions. We propose a new method that integrates protein protein interaction (PPI) as well as expression quantitative trait loci (eQTL) data to identify sets of functionally related loci that are collectively associated with a trait of interest. We call such sets of loci “population covering locus sets” (PoCos). The contributions of the proposed approach are three-fold: 1) We consider all possible genotype models for each locus, thereby enabling identification of combinatorial relationships between multiple loci. 2) We develop a framework for the integration of PPI and eQTL into a heterogenous network model, enabling efficient identification of functionally related variants that are associated with the disease. 3) We develop a novel method to integrate the genotypes of multiple loci in a PoCo into a representative genotype to be used in risk assessment. We test the proposed framework in the context of risk assessment for seven complex diseases, type 1 diabetes (T1D), type 2 diabetes (T2D), psoriasis (PS), bipolar disorder (BD), coronary artery disease (CAD), hypertension (HT), and multiple sclerosis (MS). Our results show that the proposed method significantly outperforms individual variant based risk assessment models as well as the state-of-the-art polygenic score. We also show that incorporation of eQTL data improves the performance of identified POCOs in risk assessment. We also assess the biological relevance of PoCos for three diseases that have similar biological mechanisms and identify novel candidate genes. The resulting software is publicly available at http://compbio.case.edu/pocos/.

Several studies try to predict the individual disease risk using genetic data obtained from genome wide association studies (GWAS). Earlier studies only focus on individual genetic variants. However, studies on disease mechanisms suggest the aggregation of genomic variants may contribute to diseases. For this reason, researchers commonly use prior biological knowledge to identify genetic variants that are functionally related. However, these approaches are often limited to variants that are in the coding regions of genes. However, several risk variants are in the regulatory region. Here, we incorporate known regulatory and functional interactions to find sets of genetic variants which are informative features for risk assessment. Our result on seven complex diseases show that our method outperforms individual variant based risk assessment models, as well as other methods that integrate multiple genetic variants.

Consensus paper of the WFSBP Task Force on Biological Markers: Criteria for biomarkers and endophenotypes of schizophrenia part II: Cognition, neuroimaging and genetics

OBJECTIVES

Schizophrenia is a group of severe psychiatric disorders with high heritability but only low odds ratios of risk genes. Despite progress in the identification of pathophysiological processes, valid biomarkers of the disease are still lacking.

METHODS

This comprehensive review summarises recent efforts to identify genetic underpinnings, clinical and cognitive endophenotypes and symptom dimensions of schizophrenia and presents findings from neuroimaging studies with structural, functional and spectroscopy magnetic resonance imaging and positron emission tomography. The potential of findings to be biomarkers of schizophrenia is discussed.

RESULTS

Recent findings have not resulted in clear biomarkers for schizophrenia. However, we identified several biomarkers that are potential candidates for future research. Among them, copy number variations and links between genetic polymorphisms derived from genome-wide analysis studies, clinical or cognitive phenotypes, multimodal neuroimaging findings including positron emission tomography and magnetic resonance imaging, and the application of multivariate pattern analyses are promising.

CONCLUSIONS

Future studies should address the effects of treatment and stage of the disease more precisely and apply combinations of biomarker candidates. Although biomarkers for schizophrenia await validation, knowledge on candidate genomic and neuroimaging biomarkers is growing rapidly and research on this topic has the potential to identify psychiatric endophenotypes and in the future increase insight on individual treatment response in schizophrenia.

Brinp1(-/-) mice exhibit autism-like behaviour, altered memory, hyperactivity and increased parvalbumin-positive cortical interneuron density

BACKGROUND

BMP/RA-inducible neural-specific protein 1 (Brinp1) is highly conserved in vertebrates, and continuously expressed in the neocortex, hippocampus, olfactory bulb and cerebellum from mid-embryonic development through to adulthood.

METHODS

Brinp1 knock-out (Brinp1(-/-)) mice were generated by Cre-recombinase-mediated removal of the third exon of Brinp1. Knock-out mice were characterised by behavioural phenotyping, immunohistochemistry and expression analysis of the developing and adult brain.

RESULTS

Absence of Brinp1 during development results in a behavioural phenotype resembling autism spectrum disorder (ASD), in which knock-out mice show reduced sociability and changes in vocalisation capacity. In addition, Brinp1(-/-) mice exhibit hyper-locomotor activity, have impaired short-term memory, and exhibit poor reproductive success. Brinp1(-/-) mice show increased density of parvalbumin-expressing interneurons in the adult mouse brain. Brinp1(-/-) mice do not show signs of altered neural precursor proliferation or increased apoptosis during late embryonic brain development. The expression of the related neuronal migration genes Astn1 and Astn2 is increased in the brains of Brinp1(-/-) mice, suggesting that they may ameliorate the effects of Brinp1 loss.

CONCLUSIONS

Brinp1 plays an important role in normal brain development and function by influencing neuronal distribution within the cortex. The increased cortical PV-positive interneuron density and altered behaviour of Brinp1(-/-) mice resemble features of a subset of human neurological disorders; namely autism spectrum disorder (ASD) and the hyperactivity aspect of attention deficit hyperactivity disorder (ADHD).

Resequencing and association analysis of PTPRA, a possible susceptibility gene for schizophrenia and autism spectrum disorders

Background

The PTPRA gene, which encodes the protein RPTP-α, is critical to neurodevelopment. Previous linkage studies, genome-wide association studies, controlled expression analyses and animal models support an association with both schizophrenia and autism spectrum disorders, both of which share a substantial portion of genetic risks.

Methods

We sequenced the protein-encoding areas of the PTPRA gene for single nucleotide polymorphisms or small insertions/deletions (InDel) in 382 schizophrenia patients. To validate their association with the disorders, rare (minor allele frequency <1%), missense mutations as well as one InDel in the 3′UTR region were then genotyped in another independent sample set comprising 944 schizophrenia patients, 336 autism spectrum disorders patients, and 912 healthy controls.

Results

Eight rare mutations, including 3 novel variants, were identified during the mutation-screening phase. In the following association analysis, L59P, one of the two missense mutations, was only observed among patients of schizophrenia. Additionally, a novel duplication in the 3′UTR region, 174620_174623dupTGAT, was predicted to be located within a Musashi Binding Element.

Major Conclusions

No evidence was seen for the association of rare, missense mutations in the PTPRA gene with schizophrenia or autism spectrum disorders; however, we did find some rare variants with possibly damaging effects that may increase the susceptibility of carriers to the disorders.

Allosteric modulators for the treatment of schizophrenia: targeting glutamatergic networks

Schizophrenia is a highly debilitating mental disorder which afflicts approximately 1% of the global population. Cognitive and negative deficits account for the lifelong disability associated with schizophrenia, whose symptoms are not effectively addressed by current treatments. New medicines are needed to treat these aspects of the disease. Neurodevelopmental, neuropathological, genetic, and behavioral pharmacological data indicate that schizophrenia stems from a dysfunction of glutamate synaptic transmission, particularly in frontal cortical networks. A number of novel pre- and postsynaptic mechanisms affecting glutamatergic synaptic transmission have emerged as viable targets for schizophrenia. While developing orthosteric glutamatergic agents for these targets has proven extremely difficult, targeting allosteric sites of these targets has emerged as a promising alternative. From a medicinal chemistry perspective, allosteric sites provide an opportunity of finding agents with better drug-like properties and greater target specificity. Furthermore, allosteric modulators are better suited to maintaining the highly precise temporal and spatial aspects of glutamatergic synaptic transmission. Herein, we review neuropathological and genomic/genetic evidence underscoring the importance of glutamate synaptic dysfunction in the etiology of schizophrenia and make a case for allosteric targets for therapeutic intervention. We review progress in identifying allosteric modulators of AMPA receptors, NMDA receptors, and metabotropic glutamate receptors, all with the aim of restoring physiological glutamatergic synaptic transmission. Challenges remain given the complexity of schizophrenia and the difficulty in studying cognition in animals and humans. Nonetheless, important compounds have emerged from these efforts and promising preclinical and variable clinical validation has been achieved.

Coding and noncoding gene expression biomarkers in mood disorders and schizophrenia

Mood disorders and schizophrenia are common and complex disorders with consistent evidence of genetic and environmental influences on predisposition. It is generally believed that the consequences of disease, gene expression, and allelic heterogeneity may be partly the explanation for the variability observed in treatment response. Correspondingly, while effective treatments are available for some patients, approximately half of the patients fail to respond to current neuropsychiatric treatments. A number of peripheral gene expression studies have been conducted to understand these brain-based disorders and mechanisms of treatment response with the aim of identifying suitable biomarkers and perhaps subgroups of patients based upon molecular fingerprint. In this review, we summarize the results from blood-derived gene expression studies implemented with the aim of discovering biomarkers for treatment response and classification of disorders. We include data from a biomarker study conducted in first-episode subjects with schizophrenia, where the results provide insight into possible individual biological differences that predict antipsychotic response. It is concluded that, while peripheral studies of expression are generating valuable results in pathways involving immune regulation and response, larger studies are required which hopefully will lead to robust biomarkers for treatment response and perhaps underlying variations relevant to these complex disorders.