Similarities and differences in peripheral blood gene-expression signatures of individuals with schizophrenia and their first-degree biological relatives

A novel blood-based epigenetic biosignature in first-episode schizophrenia patients through automated machine learning

Schizophrenia (SCZ) is a chronic, severe, and complex psychiatric disorder that affects all aspects of personal functioning. While SCZ has a very strong biological component, there are still no objective diagnostic tests. Lately, special attention has been given to epigenetic biomarkers in SCZ. In this study, we introduce a three-step, automated machine learning (AutoML)-based, data-driven, biomarker discovery pipeline approach, using genome-wide DNA methylation datasets and laboratory validation, to deliver a highly performing, blood-based epigenetic biosignature of diagnostic clinical value in SCZ. Publicly available blood methylomes from SCZ patients and healthy individuals were analyzed via AutoML, to identify SCZ-specific biomarkers. The methylation of the identified genes was then analyzed by targeted qMSP assays in blood gDNA of 30 first-episode drug-naïve SCZ patients and 30 healthy controls (CTRL). Finally, AutoML was used to produce an optimized disease-specific biosignature based on patient methylation data combined with demographics. AutoML identified a SCZ-specific set of novel gene methylation biomarkers including IGF2BP1, CENPI, and PSME4. Functional analysis investigated correlations with SCZ pathology. Methylation levels of IGF2BP1 and PSME4, but not CENPI were found to differ, IGF2BP1 being higher and PSME4 lower in the SCZ group as compared to the CTRL group. Additional AutoML classification analysis of our experimental patient data led to a five-feature biosignature including all three genes, as well as age and sex, that discriminated SCZ patients from healthy individuals [AUC 0.755 (0.636, 0.862) and average precision 0.758 (0.690, 0.825)]. In conclusion, this three-step pipeline enabled the discovery of three novel genes and an epigenetic biosignature bearing potential value as promising SCZ blood-based diagnostics.

Detecting differential transcript usage in complex diseases with SPIT

Differential transcript usage (DTU) plays a crucial role in determining how gene expression differs among cells, tissues, and developmental stages, contributing to the complexity and diversity of biological systems. In abnormal cells, it can also lead to deficiencies in protein function and underpin disease pathogenesis. Analyzing DTU via RNA sequencing (RNA-seq) data is vital, but the genetic heterogeneity in populations with complex diseases presents an intricate challenge due to diverse causal events and undetermined subtypes. Although the majority of common diseases in humans are categorized as complex, state-of-the-art DTU analysis methods often overlook this heterogeneity in their models. We therefore developed SPIT, a statistical tool that identifies predominant subgroups in transcript usage within a population along with their distinctive sets of DTU events. This study provides comprehensive assessments of SPIT's methodology and applies it to analyze brain samples from individuals with schizophrenia, revealing previously unreported DTU events in six candidate genes.

Genome-wide association analyses using machine learning-based phenotyping reveal genetic architecture of occupational creativity and overlap with psychiatric disorders

Creativity is known to be heritable and exhibits familial aggregation with psychiatric disorders; however, the complex nature of their relationship has not been well-established. In the present study, we demonstrate that using an expanded and validated machine learning (ML)-based phenotyping of occupational creativity (OC) can allow us to further understand the trait of creativity, which was previously difficult to define and study. We conducted the largest genome-wide association study (GWAS) on OC with 241,736 participants from the UK Biobank and identified 25 lead variants that have not yet been reported and three candidate causal genes that were previously associated with educational attainment and psychiatric disorders. We found extensive genetic overlap between OC and psychiatric disorders with mixed effect direction through various post-GWAS analyses, including the bivariate causal mixture model. In addition, we discovered a strongly genetic correlation between our original GWAS and the GWAS adjusted for education years (rg = 0.95). Our GWAS analysis via ML-based phenotyping contributes to the understanding of the genetic architecture of creativity, which may inform genetic discovery and genetic prediction in human cognition and psychiatric disorders.

Significance of an altered lncRNA landscape in schizophrenia and cognition: clues from a case-control association study

Genetic etiology of schizophrenia is poorly understood despite large genome-wide association data. Long non-coding RNAs (lncRNAs) with a probable regulatory role are emerging as important players in neuro-psychiatric disorders including schizophrenia. Prioritising important lncRNAs and analyses of their holistic interaction with their target genes may provide insights into disease biology/etiology. Of the 3843 lncRNA SNPs reported in schizophrenia GWASs extracted using lincSNP 2.0, we prioritised n = 247 based on association strength, minor allele frequency and regulatory potential and mapped them to lncRNAs. lncRNAs were then prioritised based on their expression in brain using lncRBase, epigenetic role using 3D SNP and functional relevance to schizophrenia etiology. 18 SNPs were finally tested for association with schizophrenia (n = 930) and its endophenotypes-tardive dyskinesia (n = 176) and cognition (n = 565) using a case-control approach. Associated SNPs were characterised by ChIP seq, eQTL, and transcription factor binding site (TFBS) data using FeatSNP. Of the eight SNPs significantly associated, rs2072806 in lncRNA hsaLB_IO39983 with regulatory effect on BTN3A2 was associated with schizophrenia (p = 0.006); rs2710323 in hsaLB_IO_2331 with role in dysregulation of ITIH1 with tardive dyskinesia (p < 0.05); and four SNPs with significant cognition score reduction (p < 0.05) in cases. Two of these with two additional variants in eQTL were observed among controls (p < 0.05), acting likely as enhancer SNPs and/or altering TFBS of eQTL mapped downstream genes. This study highlights important lncRNAs in schizophrenia and provides a proof of concept of novel interactions of lncRNAs with protein-coding genes to elicit alterations in immune/inflammatory pathways of schizophrenia.

Polygenic overlap with body-mass index improves prediction of treatment-resistant schizophrenia

Treatment resistant schizophrenia (TRS) is characterized by repeated treatment failure with antipsychotics. A recent genome-wide association study (GWAS) of TRS showed a polygenic architecture, but no significant loci were identified. Clozapine is shown to be the superior drug in terms of clinical effect in TRS; at the same time it has a serious side effect profile, including weight gain. Here, we sought to increase power for genetic discovery and improve polygenic prediction of TRS, by leveraging genetic overlap with Body Mass Index (BMI). We analysed GWAS summary statistics for TRS and BMI applying the conditional false discovery rate (cFDR) framework. We observed cross-trait polygenic enrichment for TRS conditioned on associations with BMI. Leveraging this cross-trait enrichment, we identified 2 novel loci for TRS at cFDR <0.01, suggesting a role of MAP2K1 and ZDBF2. Further, polygenic prediction based on the cFDR analysis explained more variance in TRS when compared to the standard TRS GWAS. These findings highlight putative molecular pathways which may distinguish TRS patients from treatment responsive patients. Moreover, these findings confirm that shared genetic mechanisms influence both TRS and BMI and provide new insights into the biological underpinnings of metabolic dysfunction and antipsychotic treatment.

Effect of stressful life events on subclinical psychotic symptoms in first-degree relatives and healthy controls

Exposure to Stressful Life Events (SLEs) has been linked to psychosis. However, the combined effect of SLEs and familial risk on subclinical psychotic symptoms over time remains unknown. The objective of the present study was to investigate the effect of SLEs on the level of subclinical psychotic symptoms in individuals with and without familial vulnerability for psychosis. Data were collected from siblings of individuals diagnosed with psychotic disorder and healthy controls at baseline (N = 293) and three years later at follow-up (N = 928). We assessed self-reported and observer-rated subclinical positive, negative, and depressive psychotic symptoms. Participants reported the number of SLEs in the preceding 6 months. A multilevel multivariate regression analysis revealed a positive association between the retrospectively assessed number of SLEs and symptom levels, regardless of vulnerability status (p < .001 for all outcomes). The prospective analysis demonstrated that exposure to SLEs at baseline predicted higher levels of subclinical psychotic symptoms at follow-up. However, after controlling for the level of symptoms at baseline, these associations were no longer significant. Again, the vulnerability status did not modify these results. Nevertheless, siblings in our sample were approximating the end of the critical period for the development of psychotic disorder (mean age at baseline M = 29 and follow-up M = 34). The findings partly support the vulnerability-stress model of psychosis, yet do not confirm the role of familial risk in this association. SLEs may represent a risk factor for psychosis at a population level, thus supporting the continuity of the psychosis spectrum in terms of associated risk factors.

Peripheral Blood-Based Gene Expression Studies in Schizophrenia: A Systematic Review

Schizophrenia is a disorder that is characterized by delusions, hallucinations, disorganized speech or behavior, and socio-occupational impairment. The duration of observation and variability in symptoms can make the accurate diagnosis difficult. Identification of biomarkers for schizophrenia (SCZ) can help in early diagnosis, ascertaining the diagnosis, and development of effective treatment strategies. Here we review peripheral blood-based gene expression studies for identification of gene expression biomarkers for SCZ. A literature search was carried out in PubMed and Web of Science databases for blood-based gene expression studies in SCZ. A list of differentially expressed genes (DEGs) was compiled and analyzed for overlap with genetic markers, differences based on drug status of the participants, functional enrichment, and for effect of antipsychotics. This literature survey identified 61 gene expression studies. Seventeen out of these studies were based on expression microarrays. A comparative analysis of the DEGs (n = 227) from microarray studies revealed differences between drug-naive and drug-treated SCZ participants. We found that of the 227 DEGs, 11 genes (ACOT7, AGO2, DISC1, LDB1, RUNX3, SIGIRR, SLC18A1, NRG1, CHRNB2, PRKAB2, and ZNF74) also showed genetic and epigenetic changes associated with SCZ. Functional enrichment analysis of the DEGs revealed dysregulation of proline and 4-hydroxyproline metabolism. Also, arginine and proline metabolism was the most functionally enriched pathway for SCZ in our analysis. Follow-up studies identified effect of antipsychotic treatment on peripheral blood gene expression. Of the 27 genes compiled from the follow-up studies AKT1, DISC1, HP, and EIF2D had no effect on their expression status as a result of antipsychotic treatment. Despite the differences in the nature of the study, ethnicity of the population, and the gene expression analysis method used, we identified several coherent observations. An overlap, though limited, of genetic, epigenetic and gene expression changes supports interplay of genetic and environmental factors in SCZ. The studies validate the use of blood as a surrogate tissue for biomarker analysis. We conclude that well-designed cohort studies across diverse populations, use of high-throughput sequencing technology, and use of artificial intelligence (AI) based computational analysis will significantly improve our understanding and diagnostic capabilities for this complex disorder.

Differential methylation of imprinting genes and MHC locus in 22q11.2 deletion syndrome-related schizophrenia spectrum disorders

OBJECTIVES

22q11.2 deletion syndrome (DS) is the strongest known genetic risk for schizophrenia. Methylome screening was conducted to elucidate possible involvement of epigenetic alterations in the emergence of schizophrenia spectrum disorders (SZ-SD) in 22q11.2DS.

METHODS

Sixteen adult men with/without SZ-SD were recruited from a 22q11.2DS cohort and underwent genome-wide DNA methylation profile analysis. Differentially methylated probes (DMPs) and regions (DMRs) were analysed using the ChAMP software.

RESULTS

The DMPs (p-value <10^-6) and DMRs (p-valueArea <0.01) were enriched in two gene sets, 'imprinting genes' and 'chr6p21', a region overlapping the MHC locus. Most of the identified imprinting genes are involved in neurodevelopment and located in clusters under imprinting control region (ICR) regulation, including PEG10, SGCE (7q21.3), GNAS, GNAS-AS1 (20q13.32) and SNHG14, SNURF-SNRPN, SNORD115 (15q11.2). The differentially methylated genes from the MHC locus included immune HLA-genes and non-immune genes, RNF39, PPP1R18 and NOTCH4, implicated in neurodevelopment and synaptic plasticity. The most significant DMR is located in MHC locus and covered the transcription regulator ZFP57 that is required for control and maintenance of gene imprinting at multiple ICRs.

CONCLUSIONS

The differential methylation in imprinting genes and in chr6p21-22 indicate the neurodevelopmental nature of 22q11.2DS-related SZ and the major role of MHC locus in the risk to develop SZ.

Seeking for potential pathogenic genes of major depressive disorder in the Gene Expression Omnibus database

INTRODUCTION

Major depressive disorder (MDD) is one of the most common mental disorders worldwide. The aim of this study was to identify potential pathological genes in MDD.

METHODS

We searched and downloaded gene expression data from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) in MDD. Then, Kyoto Encyclopedia of Genes and Genomes pathway, Gene Ontology analysis, and protein-protein interaction (PPI) network were applied to investigate the biological function of identified DEGs. The quantitative real-time polymerase chain reaction and a published dataset were used to validate the result of bioinformatics analysis.

RESULTS

A total of 514 DEGs were identified in MDD. In the PPI network, some hub genes with high degrees were identified, such as EEF2, RPL26L1, RPLP0, PRPF8, LSM3, DHX9, RSRC1, and AP2B1. The result of in vitro validation of RPL26L1, RSRC1, TOMM20L, RPLPO, PRPF8, AP2B1, STIP1, and C5orf45 was consistent with the bioinformatics analysis. Electronic validation of C5orf45, STIP1, PRPF8, AP2B1, and SLC35E1 was consistent with the bioinformatics analysis.

DISCUSSION

The deregulated genes could be used as potential pathological factors of MDD. In addition, EEF2, RPL26L1, RPLP0, PRPF8, LSM3, DHX9, RSRC1, and AP2B1 might be therapeutic targets for MDD.

Genetic Intersections of Language and Neuropsychiatric Conditions

PURPOSE OF REVIEW

To better understand the shared basis of language and mental health, this review examines the behavioral and neurobiological features of aberrant language in five major neuropsychiatric conditions. Special attention is paid to genes implicated in both language and neuropsychiatric disorders, as they reveal biological domains likely to underpin the processes controlling both.

RECENT FINDINGS

Abnormal language and communication are common manifestations of neuropsychiatric conditions, and children with impaired language are more likely to develop psychiatric disorders than their peers. Major themes in the genetics of both language and psychiatry include master transcriptional regulators, like FOXP2; key developmental regulators, like AUTS2; and mediators of neurotransmission, like GRIN2A and CACNA1C.

Neurobiological effects of aerobic exercise, with a focus on patients with schizophrenia

Schizophrenia is a severe neuropsychiatric disease that is associated with neurobiological alterations in multiple brain regions and peripheral organs. Negative symptoms and cognitive deficits are present in about half of patients and are difficult to treat, leading to an unfavorable functional outcome. To investigate the impact of aerobic exercise on various neurobiological parameters, we conducted a narrative review. Add-on aerobic exercise was shown to be effective in improving negative and general symptoms, cognition, global functioning, and quality of life in schizophrenia patients. Based on findings in healthy individuals and animal models, this qualitative review gives an overview of different lines of evidence on how aerobic exercise impacts brain structure and function and molecular mechanisms in patients with schizophrenia and how its effects could be related to clinical and functional outcomes. Structural magnetic resonance imaging studies showed a volume increase in the hippocampus and cortical regions in schizophrenia patients and healthy controls after endurance training. However, results are inconsistent and individual risk factors may influence neuroplastic processes. Animal studies indicate that alterations in epigenetic mechanisms and synaptic plasticity are possible underlying mechanisms, but that differentiation of glial cells, angiogenesis, and possibly neurogenesis may also be involved. Clinical and animal studies also revealed effects of aerobic exercise on the hypothalamus-pituitary-adrenal axis, growth factors, and immune-related mechanisms. Some findings indicate effects on neurotransmitters and the endocannabinoid system. Further research is required to clarify how individual risk factors in schizophrenia patients mediate or moderate the neurobiological effects of exercise on brain and cognition. Altogether, aerobic exercise is a promising candidate in the search for pathophysiology-based add-on interventions in schizophrenia.

Endophenotypes in Schizophrenia: Digging Deeper to Identify Genetic Mechanisms

Schizophrenia (SZ) is a severe psychotic disorder that is highly heritable and common in the general population. The genetic heterogeneity of SZ is substantial, with contributions from common, rare, and de novo variants, in addition to environmental factors. Large genome-wide association studies have detected many variants that are associated with SZ, yet the pathways by which these variants influence risk remain largely unknown. SZ is also clinically heterogeneous, with patients exhibiting a broad range of deficits and symptom severity that vary over the course of illness and treatment, which has complicated efforts to identify risk variants. However, the underlying brain dysfunction forms a more stable trait marker that quantitative neurocognitive and neurophysiological endophenotypes may be able to objectively measure. These endophenotypes are less likely to be heterogeneous than the disorder and provide a neurobiological context to detect risk variants and underlying pathways among genes associated with SZ diagnosis. Furthermore, many endophenotypes are translational into animal model systems, allowing for direct evaluation of the neural circuit dysfunctions and neurobiological substrates. We review a selection of the most promising SZ endophenotypes, including prepulse inhibition, mismatch negativity, oculomotor antisaccade, letter-number sequencing, and continuous performance tests. We also highlight recent findings from large consortia that suggest the potential role of genes, particularly in the neuregulin and glutamate pathways, in several of these endophenotypes. Although endophenotypes require additional time and effort to assess, the insight into the underlying neurobiology that they provide may ultimately reveal the underlying genetic architecture for SZ and suggest novel treatment targets.

A genome-wide association study of shared risk across psychiatric disorders implicates gene regulation during fetal neurodevelopment

There is mounting evidence that seemingly diverse psychiatric disorders share genetic etiology, but the biological substrates mediating this overlap are not well characterized. Here we leverage the unique Integrative Psychiatric Research Consortium (iPSYCH) study, a nationally representative cohort ascertained through clinical psychiatric diagnoses indicated in Danish national health registers. We confirm previous reports of individual and cross-disorder single-nucleotide polymorphism heritability for major psychiatric disorders and perform a cross-disorder genome-wide association study. We identify four novel genome-wide significant loci encompassing variants predicted to regulate genes expressed in radial glia and interneurons in the developing neocortex during mid-gestation. This epoch is supported by partitioning cross-disorder single-nucleotide polymorphism heritability, which is enriched at regulatory chromatin active during fetal neurodevelopment. These findings suggest that dysregulation of genes that direct neurodevelopment by common genetic variants may result in general liability for many later psychiatric outcomes.

Gene expression signature for detection of gastric cancer in peripheral blood

Gastric cancer (stomach cancer) is the fifth most common malignancy and the third leading cause of cancer-associated mortality worldwide. Identifying gastric cancer patients at an early and curable stage of the disease is essential if mortality rates for this disease are to decrease. A non-invasive blood-based test that is an indicator of gastric cancer risk would likely be of benefit in identifying gastric cancer patients at an early stage, and such a test may enhance clinical decision making. This study identified a four-gene expression signature in peripheral blood samples associated with gastric cancer. A total of 216 blood samples were collected, including those from 36 gastric cancer patients, 55 healthy controls and 125 patients with other carcinomas, and gene expression profiles were examined using an Affymetrix Gene Profiling microarray. Blood gene expression profiles were compared between patients with stomach cancer, healthy controls and patients affected with other malignancies. A four-gene panel was identified comprising purine-rich element binding protein B, structural maintenance of chromosomes 1A, DENN/MADD domain containing 1B and programmed cell death 4. The four-gene panel discriminated gastric cancer with an area under the receiver-operating-characteristic curve of 0.99, an accuracy of 95%, sensitivity of 92% and specificity of 96%. The non-invasive nature of the blood test, together with the relatively high accuracy of the four-gene panel may assist physicians in gastric cancer screening decision making.

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.

Consensus paper of the WFSBP Task Force on Biological Markers: Criteria for biomarkers and endophenotypes of schizophrenia, part III: Molecular mechanisms

OBJECTIVES

Despite progress in identifying molecular pathophysiological processes in schizophrenia, valid biomarkers are lacking for both the disease and treatment response.

METHODS

This comprehensive review summarises recent efforts to identify molecular mechanisms on the level of protein and gene expression and epigenetics, including DNA methylation, histone modifications and micro RNA expression. Furthermore, it summarises recent findings of alterations in lipid mediators and highlights inflammatory processes. The potential that this research will identify biomarkers of schizophrenia is discussed.

RESULTS

Recent studies have not identified clear biomarkers for schizophrenia. Although several molecular pathways have emerged as potential candidates for future research, a complete understanding of these metabolic pathways is required to reveal better treatment modalities for this disabling condition.

CONCLUSIONS

Large longitudinal cohort studies are essential that pair a thorough phenotypic and clinical evaluation for example with gene expression and proteome analysis in blood at multiple time points. This approach might identify biomarkers that allow patients to be stratified according to treatment response and ideally also allow treatment response to be predicted. Improved knowledge of molecular pathways and epigenetic mechanisms, including their potential association with environmental influences, will facilitate the discovery of biomarkers that could ultimately be effective tools in clinical practice.

The human BDNF gene: peripheral gene expression and protein levels as biomarkers for psychiatric disorders

Brain-derived neurotrophic factor (BDNF) regulates the survival and growth of neurons, and influences synaptic efficiency and plasticity. The human BDNF gene consists of 11 exons, and distinct BDNF transcripts are produced through the use of alternative promoters and splicing events. The majority of the BDNF transcripts can be detected not only in the brain but also in the blood cells, although no study has yet investigated the differential expression of BDNF transcripts at the peripheral level. This review provides a description of the human BDNF gene structure as well as a summary of clinical and preclinical evidence supporting the role of BDNF in the pathogenesis of psychiatric disorders. We will discuss several mechanisms as possibly underlying BDNF modulation, including epigenetic mechanisms. We will also discuss the potential use of peripheral BDNF as a biomarker for psychiatric disorders, focusing on the factors that can influence BDNF gene expression and protein levels. Within this context, we have also characterized, for we believe the first time, the expression of BDNF transcripts in the blood, with the aim to provide novel insights into the molecular mechanisms and signaling that may regulate peripheral BDNF gene expression levels.

Transcriptome-wide mega-analyses reveal joint dysregulation of immunologic genes and transcription regulators in brain and blood in schizophrenia

The application of microarray technology in schizophrenia research was heralded as paradigm-shifting, as it allowed for high-throughput assessment of cell and tissue function. This technology was widely adopted, initially in studies of postmortem brain tissue, and later in studies of peripheral blood. The collective body of schizophrenia microarray literature contains apparent inconsistencies between studies, with failures to replicate top hits, in part due to small sample sizes, cohort-specific effects, differences in array types, and other confounders. In an attempt to summarize existing studies of schizophrenia cases and non-related comparison subjects, we performed two mega-analyses of a combined set of microarray data from postmortem prefrontal cortices (n=315) and from ex-vivo blood tissues (n=578). We adjusted regression models per gene to remove non-significant covariates, providing best-estimates of transcripts dysregulated in schizophrenia. We also examined dysregulation of functionally related gene sets and gene co-expression modules, and assessed enrichment of cell types and genetic risk factors. The identities of the most significantly dysregulated genes were largely distinct for each tissue, but the findings indicated common emergent biological functions (e.g. immunity) and regulatory factors (e.g., predicted targets of transcription factors and miRNA species across tissues). Our network-based analyses converged upon similar patterns of heightened innate immune gene expression in both brain and blood in schizophrenia. We also constructed generalizable machine-learning classifiers using the blood-based microarray data. Our study provides an informative atlas for future pathophysiologic and biomarker studies of schizophrenia.

Reduced cardiac autonomic response to deep breathing: A heritable vulnerability trait in patients with schizophrenia and their healthy first-degree relatives

Reduced resting heart rate variability (HRV) has been observed in patients with schizophrenia and their relatives, suggesting genetic predispositions. However, findings have not been consistent. We assessed cardiac autonomic response to deep breathing in first-degree relatives of patients with schizophrenia (n=45; 26 female; aged 39.69±14.82 years). Data were compared to healthy controls (n=45; 26 female; aged 38.27±9.79 years) matched for age, gender, body mass index and physical activity as well as to unmedicated patients with acute schizophrenia (n=45; 25 female; aged 37.31±12.65 years). Electrocardiograms were recorded under supine resting and deep-breathing conditions (10-12breaths/min). We measured HRV components including variance, low-frequency (LF) power, which may reflect baroreflex function, high-frequency (HF) power, which reflects cardiac parasympathetic activity, and LF/HF ratio, which may reflect sympatho-vagal balance. Patients rather than relatives exhibited lower resting-state HRV (variance, LF, and HF) than controls. As expected, deep breathing induced an increase in variance and HF-HRV in controls. However, such a response was significantly reduced in both patients and their relatives. In conclusion, the diminished cardiac autonomic reactivity to deep breathing seen in patients and their unaffected relatives indicates that this pattern of cardiac autonomic dysregulation may be regarded as a genetic trait marker for schizophrenia.

From Linkage Studies to Epigenetics: What We Know and What We Need to Know in the Neurobiology of Schizophrenia

Schizophrenia is a complex psychiatric disorder characterized by the presence of positive, negative, and cognitive symptoms that lacks a unifying neuropathology. In the present paper, we will review the current understanding of molecular dysregulation in schizophrenia, including genetic and epigenetic studies. In relation to the latter, basic research suggests that normal cognition is regulated by epigenetic mechanisms and its dysfunction occurs upon epigenetic misregulation, providing new insights into missing heritability of complex psychiatric diseases, referring to the discrepancy between epidemiological heritability and the proportion of phenotypic variation explained by DNA sequence difference. In schizophrenia the absence of consistently replicated genetic effects together with evidence for lasting changes in gene expression after environmental exposures suggest a role of epigenetic mechanisms. In this review we will focus on epigenetic modifications as a key mechanism through which environmental factors interact with individual's genetic constitution to affect risk of psychotic conditions throughout life.

Biomarkers in schizophrenia: A focus on blood based diagnostics and theranostics

Identifying biomarkers that can be used as diagnostics or predictors of treatment response (theranostics) in people with schizophrenia (Sz) will be an important step towards being able to provide personalized treatment. Findings from the studies in brain tissue have not yet been translated into biomarkers that are practical in clinical use because brain biopsies are not acceptable and neuroimaging techniques are expensive and the results are inconclusive. Thus, in recent years, there has been search for blood-based biomarkers for Sz as a valid alternative. Although there are some encouraging preliminary data to support the notion of peripheral biomarkers for Sz, it must be acknowledged that Sz is a complex and heterogeneous disorder which needs to be further dissected into subtype using biological based and clinical markers. The scope of this review is to critically examine published blood-based biomarker of Sz, focusing on possible uses for diagnosis, treatment response, or their relationship with schizophrenia-associated phenotype. We sorted the studies into six categories which include: (1) brain-derived neurotrophic factor; (2) inflammation and immune function; (3) neurochemistry; (4) oxidative stress response and metabolism; (5) epigenetics and microRNA; and (6) transcriptome and proteome studies. This review also summarized the molecules which have been conclusively reported as potential blood-based biomarkers for Sz in different blood cell types. Finally, we further discusses the pitfall of current blood-based studies and suggest that a prediction model-based, Sz specific, blood oriented study design as well as standardize blood collection conditions would be useful for Sz biomarker development.

Blood genome-wide transcriptional profiles reflect broad molecular impairments and strong blood-brain links in Alzheimer's disease

To date, little is known regarding the etiology and disease mechanisms of Alzheimer's disease (AD). There is a general urgency for novel approaches to advance AD research. In this study, we analyzed blood RNA from female patients with advanced AD and matched healthy controls using genome-wide gene expression microarrays. Our data showed significant alterations in 3,944 genes (≥2-fold, FDR ≤1%) in AD whole blood, including 2,932 genes that are involved in broad biological functions. Importantly, we observed abnormal transcripts of numerous tissue-specific genes in AD blood involving virtually all tissues, especially the brain. Of altered genes, 157 are known to be essential in neurological functions, such as neuronal plasticity, synaptic transmission and neurogenesis. More importantly, 205 dysregulated genes in AD blood have been linked to neurological disease, including AD/dementia and Parkinson's disease, and 43 are known to be the causative genes of 42 inherited mental retardation and neurodegenerative diseases. The detected transcriptional abnormalities also support robust inflammation, profound extracellular matrix impairments, broad metabolic dysfunction, aberrant oxidative stress, DNA damage, and cell death. While the mechanisms are currently unclear, this study demonstrates strong blood-brain correlations in AD. The blood transcriptional profiles reflect the complex neuropathological status in AD, including neuropathological changes and broad somatic impairments. The majority of genes altered in AD blood have not previously been linked to AD. We believe that blood genome-wide transcriptional profiling may provide a powerful and minimally invasive tool for the identification of novel targets beyond Aβ and tauopathy for AD research.

An update on the epigenetics of psychotic diseases and autism

The examination of potential roles of epigenetic alterations in the pathogenesis of psychotic diseases have become an essential alternative in recent years as genetic studies alone are yet to uncover major gene(s) for psychosis. Here, we describe the current state of knowledge from the gene-specific and genome-wide studies of postmortem brain and blood cells indicating that aberrant DNA methylation, histone modifications and dysregulation of micro-RNAs are linked to the pathogenesis of mental diseases. There is also strong evidence supporting that all classes of psychiatric drugs modulate diverse features of the epigenome. While comprehensive environmental and genetic/epigenetic studies are uncovering the origins, and the key genes/pathways affected in psychotic diseases, characterizing the epigenetic effects of psychiatric drugs may help to design novel therapies in psychiatry.

Genome-Wide Studies of Specific Language Impairment

Specific language impairment (SLI) is a multifactorial neurodevelopmental disorder which occurs unexpectedly and without an obvious cause. Over a decade of research suggests that SLI is highly heritable. Several genes and loci have already been implicated in SLI through linkage and targeted association methods. Recently, genome-wide association studies (GWAS) of SLI and language traits in the general population have been reported and, consequently, new candidate genes have been identified. This review aims to summarise the literature concerning genome-wide studies of SLI. In addition, this review highlights the methodologies that have been used to research the genetics of SLI to date, and also considers the current, and future, contributions that GWAS can offer.

Peripheral biomarkers revisited: integrative profiling of peripheral samples for psychiatric research

Peripheral samples, such as blood and skin, have been used for decades in psychiatric research as surrogates for central nervous system samples. Although the validity of the data obtained from peripheral samples has been questioned and other state-of-the-art techniques, such as human brain imaging, genomics, and induced pluripotent stem cells, seem to reduce the value of peripheral cells, accumulating evidence has suggested that revisiting peripheral samples is worthwhile. Here, we re-evaluate the utility of peripheral samples and argue that establishing an understanding of the common signaling and biological processes in the brain and peripheral samples is required for the validity of such models. First, we present an overview of the available types of peripheral cells and describe their advantages and disadvantages. We then briefly summarize the main achievements of omics studies, including epigenome, transcriptome, proteome, and metabolome analyses, as well as the main findings of functional cellular assays, the results of which imply that alterations in neurotransmission, metabolism, the cell cycle, and the immune system may be partially responsible for the pathophysiology of major psychiatric disorders such as schizophrenia. Finally, we discuss the future utility of peripheral samples for the development of biomarkers and tailor-made therapies, such as multimodal assays that are used as a battery of disease and trait pathways and that might be potent and complimentary tools for use in psychiatric research.

Genome-wide association analyses of child genotype effects and parent-of-origin effects in specific language impairment

Specific language impairment (SLI) is a neurodevelopmental disorder that affects linguistic abilities when development is otherwise normal. We report the results of a genome-wide association study of SLI which included parent-of-origin effects and child genotype effects and used 278 families of language-impaired children. The child genotype effects analysis did not identify significant associations. We found genome-wide significant paternal parent-of-origin effects on chromosome 14q12 (P = 3.74 × 10⁻⁸) and suggestive maternal parent-of-origin effects on chromosome 5p13 (P = 1.16 × 10⁻⁷). A subsequent targeted association of six single-nucleotide-polymorphisms (SNPs) on chromosome 5 in 313 language-impaired individuals and their mothers from the ALSPAC cohort replicated the maternal effects, albeit in the opposite direction (P = 0.001); as fathers’ genotypes were not available in the ALSPAC study, the replication analysis did not include paternal parent-of-origin effects. The paternally-associated SNP on chromosome 14 yields a non-synonymous coding change within the NOP9 gene. This gene encodes an RNA-binding protein that has been reported to be significantly dysregulated in individuals with schizophrenia. The region of maternal association on chromosome 5 falls between the PTGER4 and DAB2 genes, in a region previously implicated in autism and ADHD. The top SNP in this association locus is a potential expression QTL of ARHGEF19 (also called WGEF) on chromosome 1. Members of this protein family have been implicated in intellectual disability. In summary, this study implicates parent-of-origin effects in language impairment, and adds an interesting new dimension to the emerging picture of shared genetic etiology across various neurodevelopmental disorders.

Epigenetics of schizophrenia: an open and shut case

During the last decade and a half, there has been an explosion of data regarding epigenetic changes in schizophrenia. Most initial studies have suggested that schizophrenia is characterized by an overly restrictive chromatin state based on increases in transcription silencing histone modifications and DNA methylation at schizophrenia candidate gene promoters and increases in the expression of enzymes that catalyze their formation. However, recent studies indicate that the pathology is more complex. This complexity may greatly impact pharmacological approaches directed at targeting epigenetic abnormalities in schizophrenia. The current review explores epigenetic studies of schizophrenia and what this can tell us about the underlying pathophysiology. We hypothesize based on recent studies that it is also plausible that drugs that further restrict chromatin may be efficacious.

Effect of illness expression and liability on familial associations of clinical and subclinical psychosis phenotypes

OBJECTIVE

Given the familial influences on schizophrenia, it may be hypothesized that specific symptom domains also cluster within families, and that this applies to both clinical and subclinical levels of expression. This hypothesis was put to the test in a group of patients with a DSM-IV diagnosis of psychotic disorder together with their unaffected siblings, and a group of healthy sib-pairs.

METHOD

Subclinical positive, negative and depressive symptoms in relatives and healthy controls were assessed with the Community Assessment of Psychic Experiences (CAPE). Positive and negative schizotypy in relatives and controls was measured with the Structured Interview for Schizotypy-Revised. Multilevel linear regression analyses were conducted to investigate clustering of symptom dimensions within patient-relative sib-pairs (N = 811 pairs), healthy sib-pairs of affected families (N = 136 pairs) and healthy control sib-pairs (N = 58 pairs).

RESULTS

Familial clustering of symptoms was found in all three groups. Effect sizes were largest in healthy control sib-pairs, smallest in patient-relative sib-pairs and intermediate in healthy sib-pairs of affected families.

CONCLUSION

Studies of sibling associations in genetic studies of psychometric expression of psychosis liability need to take into account the fact that the higher levels of background genetic risk and presence of diagnosed illness are inversely associated with sibling associations.

Horizons of psychiatric genetics and epigenetics: where are we and where are we heading?

Today multinational studies using genome-wide association scan (GWAS) for >1000,000 polymorphisms on >100,000 cases with major psychiatric diseases versus controls, combined with next-generation sequencing have found ~100 genetic polymorphisms associated with schizophrenia (SCZ), bipolar disorder (BD), autism, attention deficit and hyperactivity disorder (ADHD), etc. However, the effect size of each genetic mutation has been generally low (<1%), and altogether could portray a tiny fraction of these mental diseases. Furthermore, none of these polymorphisms was specific to disease phenotypes indicating that they are simply genetic risk factors rather than causal mutations. The lack of identification of the major gene(s) in huge genetic studies increased the tendency for reexamining the roles of environmental factors in psychiatric and other complex diseases. However, this time at cellular/molecular levels mediated by epigenetic mechanisms that are heritable, but reversible while interacting with the environment. Now, gene-specific or whole-genome epigenetic analyses have introduced hundreds of aberrant epigenetic marks in the blood or brain of individuals with psychiatric diseases that include aberrations in DNA methylation, histone modifications and microRNA expression. Interestingly, most of the current psychiatric drugs such as valproate, lithium, antidepressants, antipsychotics and even electroconvulsive therapy (ECT) modulate epigenetic codes. The existing data indicate that, the impacts of environment/nurture, including the uterine milieu and early-life events might be more significant than genetic/nature in most psychiatric diseases. The lack of significant results in large-scale genetic studies led to revise the bolded roles of genetics and now we are at the turning point of genomics for reconsidering environmental factors that through epigenetic mechanisms may impact the brain development/functions causing disease phenotypes.

Taiwan Schizophrenia Linkage Study: lessons learned from endophenotype-based genome-wide linkage scans and perspective

Taiwan Schizophrenia Linkage Study (TSLS) was initiated with a linkage strategy for locating multiple genes, each of small to moderate effect, and aimed to recruit a large enough sample of pairs of affected siblings and their families ascertained from a multisite study. With a sample of 607 families successfully recruited, a total of 2,242 individuals (1,207 affected and 1,035 unaffected) from 557 families were genotyped using 386 microsatellite markers spaced at an average of 9-cM intervals. Here the author reviews the establishment of TSLS and initial signal derived from linkage scan using the diagnosis of schizophrenia. Based on the limited success of the initial linkage analysis, a sufficient-component causal model is proposed to incorporate endophenotypes and genes for schizophrenia. Four types of candidate endophenotype measured in TSLS, including schizotypal personality, Continuous Performance Test, Wisconsin Card Sorting Test, and niacin skin flush test, are briefly described. The author discusses different strategies of linkage analysis incorporating these endophenotypes, including quantitative trait loci (QTL) linkage analysis, clustering-derived subgroups, ordered subset analysis (OSA), and latent classes for linkage scan. Then the author summarizes the linkage signals generated from seven studies of endophenotype-based linkage analysis using TSLS, including QTL scan of neurocognitive performance, QTL scan of niacin skin flush, the family cluster of attention deficit and execution deficit, OSA by schizophrenia-schizotypy factors, nested OSA by age at onset and neurocognitive performance, and the latent class of deficit schizophrenia for linkage analysis. The perspective of combining next-generation sequencing with linkage analysis of families is also discussed.

Research ethics in the post-genomic era

New high-throughput 'omics techniques are providing exciting opportunities in clinical medicine and toxicology, especially in the development of biomarkers. In health science research there are traditional ethical considerations that are reasonably obvious, like balancing health benefits and health risks, autonomy mainly pursued by informed consent, and protecting privacy. Epidemiological studies applying new large-scale approaches (e.g., high-throughput or high-content methods and global studies that utilize biobanking of samples and produce large-scale datasets) present new challenges that call for re-evaluation of standard ethical considerations. In this context, assessment of the ethics underlying study designs, bioinformatics, and statistics applied in the generation and clinical translation of research results should also be considered. Indeed, there are ethical considerations in the research process itself, in research objectives and how research is pursued (e.g., which methodologies are selected and how they are carried out). Maintaining research integrity is critical, as demonstrated by the relatively frequent retraction of scientific papers following violations of good scientific practice. Abiding by the laws is necessary but not sufficient for good research ethics, which is and remains in the hands of the scientific community at the level of both individual scientists and organizations. Senior scientists are responsible for the transfer of research tradition to the next generation of scientists through education, mentorship, and setting an example by their own behavior, as well as by creating systems in institutions that support good research ethics.

Gene expression profiling in treatment-naive schizophrenia patients identifies abnormalities in biological pathways involving AKT1 that are corrected by antipsychotic medication

Distinct gene expression profiles can be detected in peripheral blood mononuclear cells (PBMCs) in patients with schizophrenia; however, little is known about the effects of antipsychotic medication. This study compared gene expression profiles in PMBCs from treatment-naive patients with schizophrenia before and after antipsychotic drug treatment. PBMCs were obtained from 10 treatment-naive schizophrenia patients before and 6 wk after initiating antipsychotic drug treatment and compared to PMBCs collected from 11 healthy community volunteers. Genome-wide expression profiling was conducted using Illumina HumanHT-12 expression bead arrays and analysed using significance analysis of microarrays. This analysis identified 624 genes with altered expression (208 up-regulated, 416 down-regulated) prior to antipsychotic treatment (p < 0.05) including schizophrenia-associated genes AKT1, DISC1 and DGCR6. After 6-8 wk treatment of patients with risperidone or risperidone in combination with haloperidol, only 106 genes were altered, suggesting that the treatment corrected the expression of a large proportion of genes back to control levels. However, 67 genes continued to show the same directional change in expression after treatment. Ingenuity® pathway analysis and gene set enrichment analysis implicated dysregulation of biological functions and pathways related to inflammation and immunity in patients with schizophrenia. A number of the top canonical pathways dysregulated in treatment-naive patients signal through AKT1 that was up-regulated. After treatment, AKT1 returned to control levels and less dysregulation of these canonical pathways was observed. This study supports immune dysfunction and pathways involving AKT1 in the aetiopathophysiology of schizophrenia and their response to antipsychotic medication.

Blood RNA biomarker panel detects both left- and right-sided colorectal neoplasms: a case-control study

Background

Colonoscopy is widely regarded to be the gold standard for colorectal cancer (CRC) detection. Recent studies, however, suggest that the effectiveness of colonoscopy is mostly confined to tumors on the left side of the colon (descending, sigmoid, rectum), and that the technology has poor tumor detection for right-sided (cecum, ascending, transverse) lesions. A minimally invasive test that can detect both left-sided and right-sided lesions could increase the effectiveness of screening colonoscopy by revealing the potential presence of neoplasms in the right-sided “blind spot”.

Methods

We previously reported on a seven-gene, blood-based biomarker panel that effectively stratifies a patient’s risk of having CRC. For the current study, we assessed the effectiveness of the seven-gene panel for the detection of left- and right-sided CRC lesions. Results were evaluated for 314 patients with CRC (left-sided: TNM I, 65; TNM II, 57; TNM III, 60; TNM IV, 17; unknown, 9. right-sided: TNM I, 28; TNM II, 29; TNM III, 38; TNM IV, 12; unknown, 1 and including two samples with both left and right lesions) and 328 control samples. Blood samples were obtained prior to clinical staging and therapy. Most CRC subjects had localized disease (stages I and II, 58%); regional (stage III) and systemic (stage IV) disease represented 32% and 9%, respectively, of the study population.

Results

The panel detected left-sided (74%, 154/208) and right-sided (85%, 92/108) lesions with an overall sensitivity of 78% (215/316) at a specificity of 66% (215/328). Treatable cancer (stages I to III) was detected with left-sided lesion sensitivity of 76% (138/182) and right-sided sensitivity of 84% (80/95).

Conclusion

This seven-gene biomarker panel detected right-sided CRC lesions across all cancer stages with a sensitivity that is at least equal to that for left-sided lesions. This study supports the use of this panel as the basis for a patient-friendly, blood-based test that can be easily incorporated into a routine physical examination in advance of colonoscopy to provide a convenient companion diagnostic and a pre-screening alert, ultimately leading to enhanced CRC screening effectiveness.

Biomarker investigations related to pathophysiological pathways in schizophrenia and psychosis

Post-mortem brain investigations of schizophrenia have generated swathes of data in the last few decades implicating candidate genes and protein. However, the relation of these findings to peripheral biomarker indicators and symptomatology remain to be elucidated. While biomarkers for disease do not have to be involved with underlying pathophysiology and may be largely indicative of diagnosis or prognosis, the ideal may be a biomarker that is involved in underlying disease processes and which is therefore more likely to change with progression of the illness as well as potentially being more responsive to treatment. One of the main difficulties in conducting biomarker investigations for major psychiatric disorders is the relative inconsistency in clinical diagnoses between disorders such as bipolar and schizophrenia. This has led some researchers to investigate biomarkers associated with core symptoms of these disorders, such as psychosis. The aim of this review is to evaluate the contribution of post-mortem brain investigations to elucidating the pathophysiology pathways involved in schizophrenia and psychosis, with an emphasis on major neurotransmitter systems that have been implicated. This data will then be compared to functional neuroimaging findings as well as findings from blood based gene expression investigations in schizophrenia in order to highlight the relative overlap in pathological processes between these different modalities used to elucidate pathogenesis of schizophrenia. In addition we will cover some recent and exciting findings demonstrating microRNA (miRNA) dysregulation in both the blood and the brain in patients with schizophrenia. These changes are pertinent to the topic due to their known role in post-transcriptional modification of gene expression with the potential to contribute or underlie gene expression changes observed in schizophrenia. Finally, we will discuss how post-mortem studies may aid future biomarker investigations.

Blood-based gene-expression predictors of PTSD risk and resilience among deployed marines: a pilot study

Susceptibility to PTSD is determined by both genes and environment. Similarly, gene-expression levels in peripheral blood are influenced by both genes and environment, and expression levels of many genes show good correspondence between peripheral blood and brain. Therefore, our objectives were to test the following hypotheses: (1) pre-trauma expression levels of a gene subset (particularly immune-system genes) in peripheral blood would differ between trauma-exposed Marines who later developed PTSD and those who did not; (2) a predictive biomarker panel of the eventual emergence of PTSD among high-risk individuals could be developed based on gene expression in readily assessable peripheral blood cells; and (3) a predictive panel based on expression of individual exons would surpass the accuracy of a model based on expression of full-length gene transcripts. Gene-expression levels were assayed in peripheral blood samples from 50 U.S. Marines (25 eventual PTSD cases and 25 non-PTSD comparison subjects) prior to their deployment overseas to war-zones in Iraq or Afghanistan. The panel of biomarkers dysregulated in peripheral blood cells of eventual PTSD cases prior to deployment was significantly enriched for immune genes, achieved 70% prediction accuracy in an independent sample based on the expression of 23 full-length transcripts, and attained 80% accuracy in an independent sample based on the expression of one exon from each of five genes. If the observed profiles of pre-deployment mRNA-expression in eventual PTSD cases can be further refined and replicated, they could suggest avenues for early intervention and prevention among individuals at high risk for trauma exposure.

Peregrine: A rapid and unbiased method to produce strand-specific RNA-Seq libraries from small quantities of starting material

Use of second generation sequencing (SGS) technologies for transcriptional profiling (RNA-Seq) has revolutionized transcriptomics, enabling measurement of RNA abundances with unprecedented specificity and sensitivity and the discovery of novel RNA species. Preparation of RNA-Seq libraries requires conversion of the RNA starting material into cDNA flanked by platform-specific adaptor sequences. Each of the published methods and commercial kits currently available for RNA-Seq library preparation suffers from at least one major drawback, including long processing times, large starting material requirements, uneven coverage, loss of strand information and high cost. We report the development of a new RNA-Seq library preparation technique that produces representative, strand-specific RNA-Seq libraries from small amounts of starting material in a fast, simple and cost-effective manner. Additionally, we have developed a new quantitative PCR-based assay for precisely determining the number of PCR cycles to perform for optimal enrichment of the final library, a key step in all SGS library preparation workflows.

Whole blood transcriptome correlates with treatment response in nasopharyngeal carcinoma

Background

Treatment protocols for nasopharyngeal carcinoma (NPC) developed in the past decade have significantly improved patient survival. In most NPC patients, however, the disease is diagnosed at late stages, and for some patients treatment response is less than optimal. This investigation has two aims: to identify a blood-based gene-expression signature that differentiates NPC from other medical conditions and from controls and to identify a biomarker signature that correlates with NPC treatment response.

Methods

RNA was isolated from peripheral whole blood samples (2 x 10 ml) collected from NPC patients/controls (EDTA vacutainer). Gene expression patterns from 99 samples (66 NPC; 33 controls) were assessed using the Affymetrix array. We also collected expression data from 447 patients with other cancers (201 patients) and non-cancer conditions (246 patients). Multivariate logistic regression analysis was used to obtain biomarker signatures differentiating NPC samples from controls and other diseases. Differences were also analysed within a subset (n = 28) of a pre-intervention case cohort of patients whom we followed post-treatment.

Results

A blood-based gene expression signature composed of three genes — LDLRAP1, PHF20, and LUC7L3 — is able to differentiate NPC from various other diseases and from unaffected controls with significant accuracy (area under the receiver operating characteristic curve of over 0·90). By subdividing our NPC cohort according to the degree of patient response to treatment we have been able to identify a blood gene signature that may be able to guide the selection of treatment.

Conclusion

We have identified a blood-based gene signature that accurately distinguished NPC patients from controls and from patients with other diseases. The genes in the signature, LDLRAP1, PHF20, and LUC7L3, are known to be involved in carcinoma of the head and neck, tumour-associated antigens, and/or cellular signalling. We have also identified blood-based biomarkers that are (potentially) able to predict those patients who are more likely to respond to treatment for NPC. These findings have significant clinical implications for optimizing NPC therapy.

Convergent functional genomics of schizophrenia: from comprehensive understanding to genetic risk prediction

We have used a translational convergent functional genomics (CFG) approach to identify and prioritize genes involved in schizophrenia, by gene-level integration of genome-wide association study data with other genetic and gene expression studies in humans and animal models. Using this polyevidence scoring and pathway analyses, we identify top genes (DISC1, TCF4, MBP, MOBP, NCAM1, NRCAM, NDUFV2, RAB18, as well as ADCYAP1, BDNF, CNR1, COMT, DRD2, DTNBP1, GAD1, GRIA1, GRIN2B, HTR2A, NRG1, RELN, SNAP-25, TNIK), brain development, myelination, cell adhesion, glutamate receptor signaling, G-protein-coupled receptor signaling and cAMP-mediated signaling as key to pathophysiology and as targets for therapeutic intervention. Overall, the data are consistent with a model of disrupted connectivity in schizophrenia, resulting from the effects of neurodevelopmental environmental stress on a background of genetic vulnerability. In addition, we show how the top candidate genes identified by CFG can be used to generate a genetic risk prediction score (GRPS) to aid schizophrenia diagnostics, with predictive ability in independent cohorts. The GRPS also differentiates classic age of onset schizophrenia from early onset and late-onset disease. We also show, in three independent cohorts, two European American and one African American, increasing overlap, reproducibility and consistency of findings from single-nucleotide polymorphisms to genes, then genes prioritized by CFG, and ultimately at the level of biological pathways and mechanisms. Finally, we compared our top candidate genes for schizophrenia from this analysis with top candidate genes for bipolar disorder and anxiety disorders from previous CFG analyses conducted by us, as well as findings from the fields of autism and Alzheimer. Overall, our work maps the genomic and biological landscape for schizophrenia, providing leads towards a better understanding of illness, diagnostics and therapeutics. It also reveals the significant genetic overlap with other major psychiatric disorder domains, suggesting the need for improved nosology.

Comparison of brain and blood gene expression in an animal model of negative symptoms in schizophrenia

OBJECTIVES

To investigate the potential of white blood cells as probes for central processes we have measured gene expression in both the anterior cingulate cortex and white blood cells using a putative animal model of negative symptoms in schizophrenia.

METHODS

The model is based on the capability of ketamine to induce psychotic symptoms in healthy volunteers and to worsen such symptoms in schizophrenic patients. Classical fear conditioning is used to assess emotional processing and cognitive function in animals exposed to sub-chronic ketamine vs. controls. Gene expression was measured using a commercially sourced whole genome rat gene array. Data analyses were performed using ANOVA (Systat 11).

RESULTS

In both anterior cingulate cortex and white blood cells a significant interaction between ketamine and fear conditioning could be observed. The outcome is largely supported by our subsequent metagene analysis. Moreover, the correlation between gene expression in brain and blood is about constant when no ketamine is present (r~0.4). With ketamine, however, the correlation becomes very low (r~0.2) when there is no fear, but it increases to ~0.6 when fear and ketamine are both present. Our results show that under normal conditions ketamine lowers gene expression in the brain, but this effect is completely reversed in combination with fear conditioning, indicating a stimulatory action.

CONCLUSION

This paradoxical outcome indicates that extreme care must be taken when using gene expression data from white blood cells as marker for psychiatric disorders, especially when pharmacological and environmental interactions are at play.