Quantitative Trait Locus and Brain Expression of HLA-DPA1 Offers Evidence of Shared Immune Alterations in Psychiatric Disorders

Relationship between inflammation/immunity and epilepsy: A multi-omics mendelian randomization study integrating GWAS, eQTL, and mQTL data

OBJECTIVES

Increasing evidence suggests that activated innate/adaptive immunity induces an inflammatory response, thereby participating in epileptogenesis. However, the biological explanation of inflammation/immunity as a potential cause for epilepsy remains largely unknown. This research aimed to determine the causal effects of inflammation/immune-related genes in epilepsy based on multi-omics mendelian randomization (MR).

METHODS

We employed summary-data-based MR (SMR) approach to combine GWAS for epilepsy (12,891 cases and 312,803 control) with gene expression quantitative trait loci (cis-eQTL, 31,684 participants) and DNA methylation QTL (cis-mQTL, 1,980 participants) data. Five additional MR methods were then used for sensitivity analyses to confirm the reliability of causal associations. In addition, enrichment analysis of key genes was conducted to provide insight into the biological functions of epilepsy risk variants.

RESULTS

A total of 386 inflammation/immune-related genes were selected for further analyses. Primary SMR analysis indicated that 37 DNA methylation sites and six genes regulated by them had potential causal relationship with epilepsy. MR analysis further refined the results, identifying three genes that had a causal effect on epilepsy. Notably, VEGFA (OR: 0.925; 95 % CI: 0.862-0.994) expression was negatively correlated with epilepsy risk, whereas IL16 (OR: 1.076; 95 % CI: 1.028-1.126) and HLA-DPA1 (OR: 1.041; 95 % CI: 1.009-1.074) expressions were positively associated with epilepsy risk. Functional enrichment analysis revealed that the identified genes were involved in GO-BP terms related to VEGF activation signaling and chemotaxis regulation.

CONCLUSION

This analysis confirms the causal role of inflammation/immunity in epilepsy, and the identified candidate genes provide clues for drug development in clinical practice.

Variation within the non-coding genome influences genetic and epigenetic regulation of the human leukocyte antigen genes

Variation within the non-coding genome may influence the regulation and expression of important genes involved in immune control such as the human leukocyte antigen (HLA) system. Class I and Class II HLA molecules are essential for peptide presentation which is required for T lymphocyte activation. Single nucleotide polymorphisms within non-coding regions of HLA Class I and Class II genes may influence the expression of these genes by affecting the binding of transcription factors and chromatin modeling molecules. Furthermore, an interplay between genetic and epigenetic factors may also influence HLA expression. Epigenetic factors such as DNA methylation and non-coding RNA, regulate gene expression without changing the DNA sequence. However, genetic variation may promote or allow genes to escape regulation by epigenetic factors, resulting in altered expression. The HLA system is central to most diseases, therefore, understanding the role of genetics and epigenetics on HLA regulation will tremendously impact healthcare. The knowledge gained from these studies may lead to novel and cost-effective diagnostic approaches and therapeutic interventions. This review discusses the role of non-coding variants on HLA regulation. Furthermore, we discuss the interplay between genetic and epigenetic factors on the regulation of HLA by evaluating literature based on polymorphisms within DNA methylation and miRNA regulatory sites within class I and Class II HLA genes. We also provide insight into the importance of the HLA non-coding genome on disease, discuss ethnic-specific differences across the HLA region and provide guidelines for future HLA studies.

Causal role of immune cells in bipolar disorder: a Mendelian randomization study

Background

The understanding of the immunological mechanisms underlying bipolar disorder (BD) has enhanced in recent years due to the extensive use of high-density genetic markers for genotyping and advancements in genome-wide association studies (GWAS). However, studies on the relationship between immune cells and the risk of BD remain limited, necessitating further investigation.

Methods

Bidirectional two-sample Mendelian Randomization (MR) analysis was employed to investigate the causal association between immune cell morphologies and bipolar disorder. Immune cell traits were collected from a research cohort in Sardinia, whereas the GWAS summary statistics for BD were obtained from the Psychiatric Genomics Consortium. Sensitivity analyses were conducted, and the combination of MR-Egger and MR-Presso was used to assess horizontal pleiotropy. Cochran's Q test was employed to evaluate heterogeneity, and the results were adjusted for false discovery rate (FDR).

Results

The study identified six immune cell phenotypes significantly associated with BD incidence (P< 0.01). These phenotypes include IgD- CD27- %lymphocyte, CD33br HLA DR+ CD14- AC, CD8 on CD28+ CD45RA+ CD8br, CD33br HLA DR+ AC, CD14 on CD14+ CD16+ monocyte, and HVEM on CD45RA- CD4+. After adjusting the FDR to 0.2, two immune cell phenotypes remained statistically significant: IgD-CD27-% lymphocyte (OR=1.099, 95% CI: 1.051-1.149, P = 3.51E-05, FDR=0.026) and CD33br HLA DR+ CD14-AC (OR=0.981, 95% CI: 0.971-0.991, P = 2.17E-04, FDR=0.079). In the reverse MR analysis, BD significantly impacted the phenotypes of four monocytes (P< 0.01), including CD64 on CD14+ CD16+ monocyte, CD64 on monocyte, CX3CR1 on CD14- CD16-, CD64 on CD14+ CD16- monocyte. However, after applying the FDR correction (FDR < 0.2), no statistically significant results were observed.

Conclusions

This MR investigation reveals associations between immune cell phenotypes, bipolar disorder, and genetics, providing novel perspectives on prospective therapeutic targets for bipolar disorder.

Immune, RNA, and Neurocognitive Genetic Networks in Bipolar Disorder Subtypes: A Transcriptomic Meta-Analysis

Background

Little is known about the pathogenesis of Bipolar Disorder, and even less is known about the genetic differences between its subtypes. Bipolar Disorder is classified into different subtypes, which present different symptoms and lifetime courses. While genetic studies have been conducted in Bipolar Disorder, most examined the gene expression of only Bipolar Disorder Type 1. Studies that include Bipolar Disorder Type 1 and Bipolar Disorder Type 2 often fail to differentiate them into separate conditions. Few large transcriptomic meta-analyses in Bipolar Disorder have been conducted to identify genetic pathways. Thus, using publicly available data sets we aim here to uncover significant differential gene expression that allows distinguishing Type 1 and Type 2 Bipolar Disorders, as well as find patterns in Bipolar Disorder as a whole.

Methods

We analyze 17 different gene expression data sets from different tissue in Bipolar Disorder using GEO2R and manual analysis, of which 15 contained significant differential gene expression results. We use STRING and Cytoscape to examine Gene Ontology to find significantly affected genetic pathways. We identify hub genes using cytoHubba, a plugin in Cytoscape. We find genes common to data sets of the same material or subtype.

Results

12 out of 15 data sets are enriched for immune system and RNA related pathways. 9 out of 15 data sets are enriched for neurocognitive and metal ion related GO terms. Analysis of Bipolar Disorder Type 1 vs Bipolar Disorder Type 2 revealed most differentially expressed genes were related to immune function, especially cytokines. Terms related to synaptic signaling and neurotransmitter secretion were found in down-regulated GO terms while terms related to neuron apoptosis and death were up-regulated. We identify the gene SNCA as a potential biomarker for overall Bipolar Disorder diagnosis due to its prevalence in our data sets.

Conclusions

The immune system and RNA related pathways are significantly enriched across the Bipolar Disorder data sets. The role of these pathways is likely more critically important to the function of Bipolar Disorder than currently understood. Further studies should clearly label the subtype of Bipolar Disorder used in their research and more effort needs to be undertaken to collect samples from Cyclothymic Disorder and Bipolar Disorder Type 2.

Pilot study of genome-wide DNA methylation and gene expression for treatment response to escitalopram in panic disorder

BACKGROUND

Antidepressants, particularly selective serotonin reuptake inhibitors, are currently considered the first-line treatment for panic disorder (PD). However, little is known about the relationship between the biomarkers that may predict better treatment.

AIM

To compare genome-wide methylation and gene expression patterns between responsive and non-responsive patients with PD after 4 wk of escitalopram treatment.

METHODS

Thirty patients with PD were enrolled in this study (responders = 13; non-responders = 17). All patients were assessed using the PD Severity Scale-Chinese version before and after treatment. The Illumina Infinium MethylationEPIC (850k) BeadChip for genome-wide methylation screening and mRNA sequencing was used in all patients with PD.

RESULTS

A total of 701 differentially methylated positions (DMPs) were found between responders and non-responders (|Δβ| ≥ 0.06, q < 0.05), and the hyper- and hypomethylated CpG sites were 511 (72.9%) and 190 (27.1%), respectively. Relative to non-responders, there were 59 differential transcripts, of which 20 were downregulated and 39 were upregulated (q < 0.05). However, no differentially expressed genes were identified by mRNA sequencing after correcting for multiple testing (|log2(FC)| > 1, q > 0.05).

CONCLUSION

This preliminary study showed that DMPs might be associated with the treatment response to escitalopram in PD; however, these DMPs need to be verified in large samples.

Patients with schizophrenia and bipolar disorder display a similar global gene expression signature in whole blood that reflects elevated proportion of immature neutrophil cells with association to lipid changes

Schizophrenia (SCZ) and bipolar disorder (BD) share clinical characteristics, genetic susceptibility, and immune alterations. We aimed to identify differential transcriptional patterns in peripheral blood cells of patients with SCZ or BD versus healthy controls (HC). We analyzed microarray-based global gene expression data in whole blood from a cohort of SCZ (N = 329), BD (N = 203) and HC (N = 189). In total, 65 genes were significantly differentially expressed in SCZ and 125 in BD, as compared to HC, with similar ratio of up- and downregulated genes in both disorders. Among the top differentially expressed genes, we found an innate immunity signature that was shared between SCZ and BD, consisting of a cluster of upregulated genes (e.g., OLFM4, ELANE, BPI and MPO) that indicate an increased fraction of immature neutrophils. Several of these genes displayed sex differences in the expression pattern, and post-hoc analysis demonstrated a positive correlation with triglyceride and a negative correlation with HDL cholesterol. We found that many of the downregulated genes in SCZ and BD were associated with smoking. These findings of neutrophil granulocyte-associated transcriptome signatures in both SCZ and BD point at altered innate immunity pathways with association to lipid changes and potential for clinical translation.

Consolidation of metabolomic, proteomic, and GWAS data in connective model of schizophrenia

Despite of multiple systematic studies of schizophrenia based on proteomics, metabolomics, and genome-wide significant loci, reconstruction of underlying mechanism is still a challenging task. Combination of the advanced data for quantitative proteomics, metabolomics, and genome-wide association study (GWAS) can enhance the current fundamental knowledge about molecular pathogenesis of schizophrenia. In this study, we utilized quantitative proteomic and metabolomic assay, and high throughput genotyping for the GWAS study. We identified 20 differently expressed proteins that were validated on an independent cohort of patients with schizophrenia, including ALS, A1AG1, PEDF, VTDB, CERU, APOB, APOH, FASN, GPX3, etc. and almost half of them are new for schizophrenia. The metabolomic survey revealed 18 group-specific compounds, most of which were the part of transformation of tyrosine and steroids with the prevalence to androgens (androsterone sulfate, thyroliberin, thyroxine, dihydrotestosterone, androstenedione, cholesterol sulfate, metanephrine, dopaquinone, etc.). The GWAS assay mostly failed to reveal significantly associated loci therefore 52 loci with the smoothened p < 10^-5 were fractionally integrated into proteome-metabolome data. We integrated three omics layers and powered them by the quantitative analysis to propose a map of molecular events associated with schizophrenia psychopathology. The resulting interplay between different molecular layers emphasizes a strict implication of lipids transport, oxidative stress, imbalance in steroidogenesis and associated impartments of thyroid hormones as key interconnected nodes essential for understanding of how the regulation of distinct metabolic axis is achieved and what happens in the conditioned proteome and metabolome to produce a schizophrenia-specific pattern.

A large-scale polygenic risk score analysis identified candidate proteins associated with anxiety, depression and neuroticism

Psychiatric disorders and neuroticism are closely associated with central nervous system, whose proper functioning depends on efficient protein renewal. This study aims to systematically analyze the association between anxiety / depression / neuroticism and each of the 439 proteins. 47,536 pQTLs of 439 proteins in brain, plasma and cerebrospinal fluid (CSF) were collected from recent genome-wide association study. Polygenic risk scores (PRS) of the 439 proteins were then calculated using the UK Biobank cohort, including 120,729 subjects of neuroticism, 255,354 subjects of anxiety and 316,513 subjects of depression. Pearson correlation analyses were performed to evaluate the correlation between each protein and each of the mental traits by using calculated PRSs as the instrumental variables of protein. In general population, six correlations were identified in plasma and CSF such as plasma protease C1 inhibitor (C1-INH) with neuroticism score (r = - 0.011, P = 2.56 × 10^- 9) in plasma, C1-INH with neuroticism score (r = -0.010, P = 3.09 × 10^- 8) in CSF, and ERBB1 with self-reported depression (r = - 0.012, P = 4.65 × 10^- 5) in CSF. C1-INH and ERBB1 may induce neuroticism and depression by affecting brain function and synaptic development. Gender subgroup analyses found that BST1 was correlated with neuroticism score in male CSF (r = - 0.011, P = 1.80 × 10^- 5), while CNTN2 was correlated with depression score in female brain (r = - 0.013, P = 6.43 × 10^- 4). BST1 and CNTN2 may be involved in nervous system metabolism and brain health. Six common candidate proteins were associated with all three traits (P < 0.05) and were confirmed in relevant proteomic studies, such as C1-INH in plasma, CNTN2 and MSP in the brain. Our results provide novel clues for revealing the roles of proteins in the development of anxiety, depression and neuroticism.

Critical review of the evidence base regarding theories conceptualising the aetiology of psychosis

A critical review of literature related to the aetiology of psychosis was conducted with specific emphasis on genetics. It was found that, although many published articles were retrieved via database searches, the format of the information was disparate in presentation leading to unnecessary inconsistences. This suggests the need for insightful collaboration by authors and standardisation of published articles to prevent academic and specialism barriers remaining as a discouragement to non-specialists wishing to access this information.

Profiling of the Peripheral Blood Mononuclear Cell Proteome in Schizophrenia and Mood Disorders for the Discovery of Discriminatory Biomarkers: A Proof-of-Concept Study

INTRODUCTION

Current diagnoses in psychiatry are solely based on the evaluation of clinical presentation by the treating psychiatrist. This results in a high percentage of misdiagnosis and consequential inefficient treatment; especially regarding major depressive disorder (MDD), depression in the context of bipolar disorder (BD-D), bipolar disorder with manic symptoms (BD-M), and psychosis in the context of schizophrenia (SZ). Objective biomarkers allowing for accurate discriminatory diagnostics are therefore urgently needed.

METHODS

Peripheral blood mononuclear cell (PBMC) proteomes of patients with MDD (n = 5) , BD-D (n = 3), BD-M (n = 4), and SZ (n = 4), and also of healthy controls (HC; n = 6) were analyzed by state-of-the-art mass spectrometry. Proteins with a differential expression of a >2 standard deviation (SD) expression fold change from that of the HC and between either MDD versus BD-D or BD-M versus SZ were subsequently identified as potential discriminatory biomarkers.

RESULTS

In total, 4,271 individual proteins were retrieved from the HC. Of these, about 2,800 were detected in all patient and HC samples. For objective discrimination between MDD and BD-D, 66 candidate biomarkers were found. In parallel, 72 proteins might harbor a biomarker capacity for differential diagnostics of BD-M and SZ. A single biomarker was contraregulated versus HC in each pair of comparisons.

DISCUSSION

With this work, we provide a register of candidate biomarkers with the potential to objectively discriminate MDD from BD-D, and BD-M from SZ. Although concerning a proof-of-concept study with limited sample size, these data provide a stepping-stone for follow-up research on the validation of the true discriminatory potential and feasibility of clinical implementation of the discovered biomarker candidates.

Psycho-neuro-endocrino-immunologic issues in multiple sclerosis: a critical review of clinical and therapeutic implications

Multiple sclerosis (MS) is a multifactorial, chronic, immune-mediated, and neurodegenerative disease, having a well-known hypothalamic-pituitary-adrenal (HPA) axis dysfunction. Several hormones have a great impact in the immune dysregulation, psychology, and cognitive status of patients with MS, as also in the fertility and response to treatment. In this comprehensive review, as an introduction, we mention basic data concerning MS: epidemiology, genetics, immunogenetics, epigenetics, pathophysiology, and neuroimmunology. Hormonal components of the disease cascade, mainly glucocorticoids (stress-related hormone), estrogens, prolactin and dehydroepiandrosterone (sex-related hormones), melatonin, and vitamin D, are discussed, aiming at focusing on core data regarding the impact of these hormones in MS pathophysiology, severity of the disease, correlation with comorbid mental disorders, and fertility. A great focus is given in the pre- and post-pregnancy period of MS patients, in the context of the disease-modifying treatments (DMTs) and HPA status, having in mind that there are only very limited knowledge and few papers on this specific life period of these women, having MS. All this data are presented in the main text and also in the workable tables, for the first time, suggesting targeted topics that need to be addressed in the near future.

Molecular alterations in the medial temporal lobe in schizophrenia

The medial temporal lobe (MTL) and its individual structures have been extensively implicated in schizophrenia pathophysiology, with considerable efforts aimed at identifying structural and functional differences in this brain region. The major structures of the MTL for which prominent differences have been revealed include the hippocampus, the amygdala and the superior temporal gyrus (STG). The different functions of each of these regions have been comprehensively characterized, and likely contribute differently to schizophrenia. While neuroimaging studies provide an essential framework for understanding the role of these MTL structures in various aspects of the disease, ongoing efforts have sought to employ molecular measurements in order to elucidate the biology underlying these macroscopic differences. This review provides a summary of the molecular findings in three major MTL structures, and discusses convergent findings in cellular architecture and inter-and intra-cellular networks. The findings of this effort have uncovered cell-type, network and gene-level specificity largely unique to each brain region, indicating distinct molecular origins of disease etiology. Future studies should test the functional implications of these molecular changes at the circuit level, and leverage new advances in sequencing technology to further refine our understanding of the differential contribution of MTL structures to schizophrenia.

Comparative characterization of human induced pluripotent stem cells (hiPSC) derived from patients with schizophrenia and autism

Human induced pluripotent stem cells (hiPSC) provide an attractive tool to study disease mechanisms of neurodevelopmental disorders such as schizophrenia. A pertinent problem is the development of hiPSC-based assays to discriminate schizophrenia (SZ) from autism spectrum disorder (ASD) models. Healthy control individuals as well as patients with SZ and ASD were examined by a panel of diagnostic tests. Subsequently, skin biopsies were taken for the generation, differentiation, and testing of hiPSC-derived neurons from all individuals. SZ and ASD neurons share a reduced capacity for cortical differentiation as shown by quantitative analysis of the synaptic marker PSD95 and neurite outgrowth. By contrast, pattern analysis of calcium signals turned out to discriminate among healthy control, schizophrenia, and autism samples. Schizophrenia neurons displayed decreased peak frequency accompanied by increased peak areas, while autism neurons showed a slight decrease in peak amplitudes. For further analysis of the schizophrenia phenotype, transcriptome analyses revealed a clear discrimination among schizophrenia, autism, and healthy controls based on differentially expressed genes. However, considerable differences were still evident among schizophrenia patients under inspection. For one individual with schizophrenia, expression analysis revealed deregulation of genes associated with the major histocompatibility complex class II (MHC class II) presentation pathway. Interestingly, antipsychotic treatment of healthy control neurons also increased MHC class II expression. In conclusion, transcriptome analysis combined with pattern analysis of calcium signals appeared as a tool to discriminate between SZ and ASD phenotypes in vitro.

Integrating genome-wide association study with regulatory SNP annotation information identified candidate genes and pathways for schizophrenia

BACKGROUND

Schizophrenia is a complex mental disorder. The genetic mechanism of schizophrenia remains elusive now.

METHODS

We conducted a large-scale integrative analysis of two genome-wide association studies of schizophrenia with functional annotation datasets of regulatory single-nucleotide polymorphism (rSNP). The significant SNPs identified by the two genome-wide association studies were first annotated to obtain schizophrenia associated rSNPs and their target genes and proteins, respectively. We then compared the integrative analysis results to identify the common rSNPs and their target regulatory genes and proteins, shared by the two genome-wide association studies of schizophrenia. Finally, DAVID tool was used to conduct gene ontology and pathway enrichment analysis of the identified targets genes and proteins.

RESULTS

We detected 53 schizophrenia-associated target genes for rSNP, such as FOS (P value = 2.18×10^-20), ATXN1 (P value = 5.22×10^-21) and HLA-DQA1 (P value = 1.98×10^-10). Pathway enrichment analysis identified 24 pathways for transcription factors binding regions, chromatin interacting regions, long non-coding RNAs, topologically associated domains, circular RNAs and post-translational modifications, such as hsa05034:Alcoholism (P value = 2.57×10^-7) and hsa04612:Antigen processing and presentation (P value = 6.82×10^-8).

CONCLUSION

We detected multiple candidate genes, gene ontology terms and pathways for schizophrenia, supporting the functional importance of rSNPs, and providing novel clues for understanding the genetic architecture of schizophrenia.

Activity-dependent modulation of hippocampal synaptic plasticity via PirB and endocannabinoids

The threshold for Hebbian synaptic plasticity in the CNS is modulated by prior synaptic activity. At adult CA3-CA1 synapses, endocannabinoids play a role in this process, but how activity engages and maintains this retrograde signaling system is not well understood. Here we show that conditional deletion of Paired Immunoglobulin-like receptor B (PirB) from pyramidal neurons in adult mouse hippocampus results in deficient LTD at CA3-CA1 synapses over a range of stimulation frequencies, accompanied by an increase in LTP. This finding can be fully explained by the disengagement of retrograde endocannabinoid signaling selectively at excitatory synapses. In the absence of PirB, the NMDAR-dependent regulation of endocannabinoid signaling is lost, while CB1R-dependent and group I mGluR-dependent regulation are intact. Moreover, mEPSC frequency in mutant CA1 pyramidal cells is elevated, consistent with a higher density of excitatory synapses and altered synapse pruning. Mice lacking PirB also perform better than WT in learning and memory tasks. These observations suggest that PirB is an integral part of an NMDA receptor-mediated synaptic mechanism that maintains bidirectional Hebbian plasticity and learning via activity-dependent endocannabinoid signaling.

Analysis of shared homozygosity regions in Saudi siblings with attention deficit hyperactivity disorder

AIM

Genetic and clinical complexities are common features of most psychiatric illnesses that pose a major obstacle in risk-gene identification. Attention deficit hyperactivity disorder (ADHD) is the most prevalent child-onset psychiatric illness, with high heritability. Over the past decade, numerous genetic studies utilizing various approaches, such as genome-wide association, candidate-gene association, and linkage analysis, have identified a multitude of candidate loci/genes. However, such studies have yielded diverse findings that are rarely reproduced, indicating that other genetic determinants have not been discovered yet. In this study, we carried out sib-pair analysis on seven multiplex families with ADHD from Saudi Arabia. We aimed to identify the candidate chromosomal regions and genes linked to the disease.

PATIENTS AND METHODS

A total of 41 individuals from multiplex families were analyzed for shared regions of homozygosity. Genes within these regions were prioritized according to their potential relevance to ADHD.

RESULTS

We identified multiple genomic regions spanning different chromosomes to be shared among affected members of each family; these included chromosomes 3, 5, 6, 7, 8, 9, 10, 13, 17, and 18. We also found specific regions on chromosomes 8 and 17 to be shared between affected individuals from more than one family. Among the genes present in the regions reported here were involved in neurotransmission (GRM3, SIGMAR1, CHAT, and SLC18A3) and members of the HLA gene family (HLA-A, HLA-DPA1, and MICC).

CONCLUSION

The candidate regions identified in this study highlight the genetic diversity of ADHD. Upon further investigation, these loci may reveal candidate genes that enclose variants associated with ADHD. Although most ADHD studies were conducted in other populations, our study provides insight from an understudied, ethnically interesting population.

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.

Microvascular anomaly conditions in psychiatric disease. Schizophrenia - angiogenesis connection

Schizophrenia (SZ) is a severe mental disorder with unknown etiology and elusive neuropathological and neurobiological features have been a focus of many theoretical hypotheses and empirical studies. Current genetic and neurobiology information relevant to SZ implicates neuronal developmental and synaptic plasticity abnormalities, and neurotransmitter, microglial and oligodendrocytes dysfunction. Several recent theories have highlighted the neurovascular unit as a potential contributor to the pathophysiology of SZ. We explored the biological plausibility of a link between SZ and the neurovascular system by examining insights gained from genetic, neuroimaging and postmortem studies, which include gene expression and neuropathology analyses. We also reviewed information from animal models of cerebral angiogenesis in order to understand better the complex interplay between angiogenic and neurotrophic factors in development, vascular endothelium/blood brain barrier remodeling and maintenance, all of which contribute to sustaining adequate regional blood flow and safeguarding normal brain function. Microvascular and hemodynamic alterations in SZ highlight the importance of further research and reveal the neurovascular unit as a potential therapeutic target in SZ.

Microvascular anomaly conditions in psychiatric disease. Schizophrenia - angiogenesis connection

Schizophrenia (SZ) is a severe mental disorder with unknown etiology and elusive neuropathological and neurobiological features have been a focus of many theoretical hypotheses and empirical studies. Current genetic and neurobiology information relevant to SZ implicates neuronal developmental and synaptic plasticity abnormalities, and neurotransmitter, microglial and oligodendrocytes dysfunction. Several recent theories have highlighted the neurovascular unit as a potential contributor to the pathophysiology of SZ. We explored the biological plausibility of a link between SZ and the neurovascular system by examining insights gained from genetic, neuroimaging and postmortem studies, which include gene expression and neuropathology analyses. We also reviewed information from animal models of cerebral angiogenesis in order to understand better the complex interplay between angiogenic and neurotrophic factors in development, vascular endothelium/blood brain barrier remodeling and maintenance, all of which contribute to sustaining adequate regional blood flow and safeguarding normal brain function. Microvascular and hemodynamic alterations in SZ highlight the importance of further research and reveal the neurovascular unit as a potential therapeutic target in SZ.

Correlated expression analysis of genes implicated in schizophrenia: identification of putative disease-related pathways

Schizophrenia (SCZ) is a severe psychiatric disorder affecting 0.7% of the population.[1] When inadequately treated, subjects with SCZ experience symptoms that render them dysfunctional and unable to discern aspects of reality. Despite the fact that the majority of subjects with SCZ are sporadic cases and do not have a known family history of SCZ, a family history is one of the largest risk factors for developing SCZ.[2-4] A large genome-wide association study (GWAS) recently pinpointed 108 significant loci within the human genome that contribute to SCZ pathogenesis.[5] While some loci include genes that have been previously implicated in SCZ, the majority, due to the unbiased nature of the genetic investigation, include genes with unknown relevance to SCZ. This investigation is based on the premise that: 1) at least one of the genes at the 108 loci contribute to SCZ etiology; 2) some of the genes contributing to SCZ etiology are in a common pathway; and 3) some genes in a common pathway will have correlated gene expression. Gene expression data available in the gene expression omnibus (GEO) was used to identify correlated expression among the 369 genes (853 isoforms) found at the 108 loci associated with SCZ. Expression data came from bone marrow CD34+ selected cells isolated from 66 individuals (GSE4619). First, correlation among genes related to the DRD2 pathway was analyzed to test the hypothesis that some SCZ genes are in a common pathway and have correlated expression. Then, two pathways were generated based on correlated expression of genes at the 108 loci. One pathway consisted of the largest number of genes with correlated expression (56) and included four genes from the DRD2 pathway and seven of the 33 genes that were previously implicated in SCZ. The second pathway, a novel pathway of 12 genes, was constructed by excluding both the 33 genes that were previously implicated in SCZ and other genes that exhibited significantly correlated expression with these 33 genes. Correlated expression analysis among SCZ-associated genes at the 108 loci provides evidence implicating those genes with correlated expression in SCZ pathogenesis. In addition, these analyses will facilitate pathway identification creating starting points for targeted experiments to verify or refute the hypothetical pathways generated here. Ultimately identifying the genes and pathways at the 108 loci involved in SCZ genesis will inform novel pharmaceutical development for treatment and prevention of SCZ.

Consistently altered expression of gene sets in postmortem brains of individuals with major psychiatric disorders

The measurement of gene expression in postmortem brain is an important tool for understanding the pathogenesis of serious psychiatric disorders. We hypothesized that major molecular deficits associated with psychiatric disease would affect the entire brain, and such deficits may be shared across disorders. We performed RNA sequencing and quantified gene expression in the hippocampus of 100 brains in the Stanley Array Collection followed by replication in the orbitofrontal cortex of 57 brains in the Stanley Neuropathology Consortium. We then identified genes and canonical pathway gene sets with significantly altered expression in schizophrenia and bipolar disorder in the hippocampus and in schizophrenia, bipolar disorder and major depression in the orbitofrontal cortex. Although expression of individual genes varied, gene sets were significantly enriched in both of the brain regions, and many of these were consistent across diagnostic groups. Further examination of core gene sets with consistently increased or decreased expression in both of the brain regions and across target disorders revealed that ribosomal genes are overexpressed while genes involved in neuronal processes, GABAergic signaling, endocytosis and antigen processing have predominantly decreased expression in affected individuals compared to controls without a psychiatric disorder. Our results highlight pathways of central importance to psychiatric health and emphasize messenger RNA processing and protein synthesis as potential therapeutic targets for all three of the disorders.

CD74-Downregulation of Placental Macrophage-Trophoblastic Interactions in Preeclampsia

RATIONALE

We hypothesized that cluster of differentiation 74 (CD74) downregulation on placental macrophages, leading to altered macrophage-trophoblast interaction, is involved in preeclampsia.

OBJECTIVE

Preeclamptic pregnancies feature hypertension, proteinuria, and placental anomalies. Feto-placental macrophages regulate villous trophoblast differentiation during placental development. Disturbance of this well-balanced regulation can lead to pathological pregnancies.

METHODS AND RESULTS

We performed whole-genome expression analysis of placental tissue. CD74 was one of the most downregulated genes in placentas from preeclamptic women. By reverse transcriptase-polymerase chain reaction, we confirmed this finding in early-onset (<34 gestational week, n=26) and late-onset (≥34 gestational week, n=24) samples from preeclamptic women, compared with healthy pregnant controls (n=28). CD74 protein levels were analyzed by Western blot and flow cytometry. We identified placental macrophages to express CD74 by immunofluorescence, flow cytometry, and RT-PCR. CD74-positive macrophages were significantly reduced in preeclamptic placentas compared with controls. CD74-silenced macrophages showed that the adhesion molecules ALCAM, ICAM4, and Syndecan-2, as well as macrophage adhesion to trophoblasts were diminished. Naive and activated macrophages lacking CD74 showed a shift toward a proinflammatory signature with an increased secretion of tumor necrosis factor-α, chemokine (C-C motif) ligand 5, and monocyte chemotactic protein-1, when cocultured with trophoblasts compared with control macrophages. Trophoblasts stimulated by these factors express more CYP2J2, sFlt1, TNFα, and IL-8. CD74-knockout mice showed disturbed placental morphology, reduced junctional zone, smaller placentas, and impaired spiral artery remodeling with fetal growth restriction.

CONCLUSIONS

CD74 downregulation in placental macrophages is present in preeclampsia. CD74 downregulation leads to altered macrophage activation toward a proinflammatory signature and a disturbed crosstalk with trophoblasts.