Transcriptome sequencing and genome-wide association analyses reveal lysosomal function and actin cytoskeleton remodeling in schizophrenia and bipolar disorder

Altered Sphingolipid Hydrolase Activities and Alpha-Synuclein Level in Late-Onset Schizophrenia

Recent data described that patients with lysosomal storage disorders (LSDs) may have clinical schizophrenia (SCZ) features. Disruption of lipid metabolism in SCZ pathogenesis was found. Clinical features of schizophrenia (SCZ) have been demonstrated in patients with several lysosomal storage disorders (LSDs). Taking into account the critical role of lysosomal function for neuronal cells' lysosomal dysfunction could be proposed in SCZ pathogenesis. The current study analyzed lysosomal enzyme activities and the alpha-synuclein level in the blood of patients with late-onset SCZ. In total, 52 SCZ patients with late-onset SCZ, 180 sporadic Parkinson's disease (sPD) patients, and 176 controls were recruited. The enzymatic activity of enzymes associated with mucopolysaccharidosis (alpha-L-Iduronidase (IDUA)), glycogenosis (acid alpha-glucosidase (GAA)) and sphingolipidosis (galactosylceramidase (GALC), glucocerebrosidase (GCase), alpha-galactosidase (GLA), acid sphingomyelinase (ASMase)) and concentration of lysosphingolipids (hexosylsphingosine (HexSph), globotriaosylsphingosine (LysoGb3), and lysosphingomyelin (LysoSM)) were measured using LC-MS/MS. The alpha-synuclein level was estimated in magnetically separated CD45+ blood cells using the enzyme-linked immunosorbent assay (ELISA). Additionally, NGS analysis of 11 LSDs genes was conducted in 21 early-onset SCZ patients and 23 controls using the gene panel PGRNseq-NDD. Decreased ASMase, increased GLA activities, and increased HexSpn, LysoGb3, and LysoSM concentrations along with an accumulation of the alpha-synuclein level were observed in late-onset SCZ patients in comparison to the controls (p < 0.05). Four rare deleterious variants among LSDs genes causing mucopolysaccharidosis type I (IDUA (rs532731688, rs74385837) and type III (HGSNAT (rs766835582)) and sphingolipidosis (metachromatic leukodystrophy (ARSA (rs201251634)) were identified in five patients from the group of early-onset SCZ patients but not in the controls. Our findings supported the role of sphingolipid metabolism in SCZ pathogenesis. Aberrant enzyme activities and compounds of sphingolipids associated with ceramide metabolism may lead to accumulation of alpha-synuclein and may be critical in SCZ pathogenesis.

BORG family proteins in physiology and human disease

The binder of rho GTPases (BORG)/Cdc42 effector proteins (Cdc42EP) family is composed of five Rho GTPase binding proteins whose functions and mechanism of actions are of emerging interest. Here, we review recent findings pertaining to the family as a whole and consider how these change our understanding of cellular organization. Recent studies have implicated BORGs in both fundamental physiology and in human diseases, mainly cancers. An emerging pattern suggests that BORG family members cancer-promoting properties are related to their ability to regulate the cytoskeleton, with many impacting the organization of acto-myosin stress fibers. This is consistent with the broader literature indicating that BORG family members are regulators of both the septin and actin cytoskeleton networks. The exact mechanism through which BORGs modify the cytoskeleton is not clear, but we consider here a few data-supported and speculative possibilities. Finally, we delve into how the Rho GTPase Cdc42 modifies BORG function in cells. This remains open-ended as Cdc42's effects on BORGs appear cell type- and cell state-dependent. Collectively, these data point to the importance of the BORG family and suggest broader themes in their function and regulation.

Serum Metabolic Profile in Schizophrenia Patients With Antipsychotic-Induced Constipation and Its relationship With Gut Microbiome

BACKGROUND AND HYPOTHESIS

Antipsychotics (APs), the cornerstone of schizophrenia treatment, confer a relatively high risk of constipation. However, the mechanisms underpinning AP-induced constipation are poorly understood. Thus, we hypothesized that (1) schizophrenia patients with AP-induced constipation have distinct metabolic patterns; (2) there is more than one mechanism at play in producing this adverse drug effect; and (3) AP-associated changes in the gut microbiome are related to the altered metabolic profiles.

STUDY DESIGN

Eighty-eight schizophrenia patients, including 44 with constipation (C) and 44 matched patients without constipation (NC), were enrolled in this study. Constipation was diagnosed by Rome IV criteria for constipation and colonic transit time using radiopaque markers (ROMs) while severity was evaluated with the Bristol Stool Form Scale (BSS) and Constipation Assessment Scale (CAS). Fasting blood samples were drawn from all participants and were subjected to non-targeted liquid chromatography-mass spectrometry (LC-MS) metabolomic analysis.

STUDY RESULTS

Eleven metabolites were significantly altered in AP-induced constipation which primarily disturbed sphingolipid metabolism, choline metabolism, and sphingolipid signaling pathway (P value < .05, FDR < 0.05). In the C group, changes in the gut bacteria showed a certain degree of correlation with 2 of the significantly altered serum metabolites and were associated with alterations in choline metabolism.

CONCLUSIONS

Our findings indicated that there were disturbances in distinct metabolic pathways that were associated with AP-induced constipation. In addition, this study presents evidence of a link between alterations in the gut microbiome and host metabolism which provides additional mechanistic insights on AP-induced constipation.

Mass Spectrometry based identification of site-specific proteomic alterations and potential pathways underlying the pathophysiology of schizophrenia

BACKGROUND

Schizophrenia (SZ) is a complex multifactorial disorder that affects 1% of the population worldwide with no available effective treatment. Although proteomic alterations are reported in SZ however proteomic expression aberrations among different brain regions are not fully determined. Therefore, the present study aimed spatial differential protein expression profiling of three distinct regions of SZ brain and identification of associated affected biological pathways in SZ progression.

METHODS AND RESULTS

Comparative protein expression profiling of three distinct autopsied human brain regions (i.e., substantia nigra, hippocampus and prefrontal cortex) of SZ was performed with respective healthy controls. Using two-dimensional electrophoresis (2DE)-based nano liquid chromatography tandem mass spectrometry (Nano-LC MS /MS) analysis, 1443 proteins were identified out of which 58 connote to be significantly dysregulated, representing 26 of substantia nigra,14 of hippocampus and 18 of prefrontal cortex. The 58 differentially expressed proteins were further analyzed using Ingenuity pathway analysis (IPA). The IPA analysis provided protein-protein interaction networks of several proteins including nuclear factor kappa-light-chain-enhancer of activated B cells (NF-kb), extracellular signal regulated kinases 1/2 (ERK1/2), alpha serine / Threonine-protein kinase (AKT1), cellular tumor antigen p53 (TP53) and amyloid precursor protein (APP), holding prime positions in networks and interacts with most of the identified proteins and their closely interacting partners.

CONCLUSION

These findings provide conceptual insights of novel SZ related pathways and the cross talk of co and contra regulated proteins. This spatial proteomic analysis will further broaden the conceptual framework for schizophrenia research in future.

LIM Kinases, LIMK1 and LIMK2, Are Crucial Node Actors of the Cell Fate: Molecular to Pathological Features

LIM kinase 1 (LIMK1) and LIM kinase 2 (LIMK2) are serine/threonine and tyrosine kinases and the only two members of the LIM kinase family. They play a crucial role in the regulation of cytoskeleton dynamics by controlling actin filaments and microtubule turnover, especially through the phosphorylation of cofilin, an actin depolymerising factor. Thus, they are involved in many biological processes, such as cell cycle, cell migration, and neuronal differentiation. Consequently, they are also part of numerous pathological mechanisms, especially in cancer, where their involvement has been reported for a few years and has led to the development of a wide range of inhibitors. LIMK1 and LIMK2 are known to be part of the Rho family GTPase signal transduction pathways, but many more partners have been discovered over the decades, and both LIMKs are suspected to be part of an extended and various range of regulation pathways. In this review, we propose to consider the different molecular mechanisms involving LIM kinases and their associated signalling pathways, and to offer a better understanding of their variety of actions within the physiology and physiopathology of the cell.

The molecular basis of p21-activated kinase-associated neurodevelopmental disorders: From genotype to phenotype

Although the identification of numerous genes involved in neurodevelopmental disorders (NDDs) has reshaped our understanding of their etiology, there are still major obstacles in the way of developing therapeutic solutions for intellectual disability (ID) and other NDDs. These include extensive clinical and genetic heterogeneity, rarity of recurrent pathogenic variants, and comorbidity with other psychiatric traits. Moreover, a large intragenic mutational landscape is at play in some NDDs, leading to a broad range of clinical symptoms. Such diversity of symptoms is due to the different effects DNA variations have on protein functions and their impacts on downstream biological processes. The type of functional alterations, such as loss or gain of function, and interference with signaling pathways, has yet to be correlated with clinical symptoms for most genes. This review aims at discussing our current understanding of how the molecular changes of group I p21-activated kinases (PAK1, 2 and 3), which are essential actors of brain development and function; contribute to a broad clinical spectrum of NDDs. Identifying differences in PAK structure, regulation and spatio-temporal expression may help understanding the specific functions of each group I PAK. Deciphering how each variation type affects these parameters will help uncover the mechanisms underlying mutation pathogenicity. This is a prerequisite for the development of personalized therapeutic approaches.

Endo-Lysosomal and Autophagy Pathway and Ubiquitin-Proteasome System in Mood Disorders: A Review Article

Mood disorders are disabling conditions that cause significant functional impairment. Due to the clinical heterogeneity and complex nature of these disorders, diagnostic and treatment strategies face challenges. The etiology of mood disorders is multifactorial, involving genetic and environmental aspects that are associated with specific biological pathways including inflammation, oxidative stress, and neuroprotection. Alterations in these pathways may reduce the cell's ability to recover from stress conditions occurring during mood episodes. The endo-lysosomal and autophagy pathway (ELAP) and the ubiquitin-proteasome system (UPS) play critical roles in protein homeostasis, impacting neuroplasticity and neurodevelopment. Thus, emerging evidence has suggested a role for these pathways in mental disorders. In the case of neurodegenerative diseases (NDDs), a deeper understanding in the role of ELAP and UPS has been critical to discover new treatment targets. Since it is suggested that NDDs and mood disorders share clinical symptomatology and risk factors, it has been hypothesized that there might be common underlying molecular pathways. Here, we review the importance of the ELAP and UPS for the central nervous system and for mood disorders. Finally, we discuss potential translational strategies for the diagnosis and treatment of major depressive disorder and bipolar disorder associated with these pathways.

Schizophrenia and oxidative stress from the perspective of bibliometric analysis

BACKGROUND

A growing number of studies has implicated oxidative stress in the pathophysiology of psychiatric disorders including schizophrenia. The aim of this study was to explore the field of schizophrenia and oxidative stress-related research from a bibliometric perspective.

METHODS

All relevant publications on schizophrenia and oxidative stress were obtained from Web of Science Core Collection (WOSCC) database from its inception date to November 8, 2022. VOSviewer software was used to examine co-authorships and co-occurring keywords. R software was used to present the main characteristics of publications and cooperation frequency among countries. CiteSpace was used to investigate keywords with the strongest citation bursts.

RESULTS

A total of 3,510 publications on schizophrenia and oxidative stress were included. The United States had the largest number of publications (26.1%), and international collaborations. University of Melbourne was the most productive institution, while Schizophrenia Research was the most productive journal in this field. Apart from "schizophrenia" and "oxidative stress", the terms "prefrontal cortex", "brain" and "nitric oxide" were among the most frequently used keywords.

CONCLUSIONS

In conclusion, research on the association between oxidative stress and schizophrenia has received growing attention in the academic literature that is expected to continue its upward trajectory during the next two decades. Existing research suggests there has been a transition from research focused on pathways to animal models, and subsequently to clinical applications. Intervention studies on oxidative stress and schizophrenia are likely to be an important focus of related work in the near future.

Analysis of merged transcriptomic and genomic datasets to identify genes and pathways underlying residual feed intake in growing pigs

Improvement of feed efficiency (FE) in pigs is an important milestone in order to reduce the economic and environmental impact of pig production. The goal of finding biomarkers for FE has persisted for decades. However, due to the complexity of the FE trait, these goals have still not been met. Here, we search for quantitative trait loci (QTL), candidate genes, and biological pathways associated with FE using both genotype and RNA-seq data. We obtained genotype and colon epithelium RNA-seq data for 375 and 96 pigs, respectively. In total, a genome-wide association study (GWAS) and differential expression (DE) analysis led to detection of three QTL on SSC9 and 17 DE-genes associated with FE. Possible intersection points between genes located in QTL and DE-genes were found on levels of transcription factor-target interaction. Moreover, cis-eQTL analysis revealed associations between genotype and expression levels of three DE-genes and three genes located in the GWAS QTLs, which may establish the connection between genotype and phenotype through DE. Finally, single nucleotide polymorphism calling using RNA-seq data for genes located in GWAS QTLs revealed 53 polymorphisms of which eleven were missense variants.

Dysfunction of mitochondria and GABAergic interneurons in the anterior cingulate cortex of individuals with schizophrenia

Here we re-analyze RNA-sequencing data from the anterior cingulate cortex (ACC) of SZ patients using recent methods to improve accuracy and sensitivity of results, such as the quality surrogate variable analysis (qSVA) method and the derfinder R package. We found that genes significantly down-regulated in SZ demonstrated an enrichment for parvalbumin-positive interneurons (FDR < 0.0001). Down-regulated genes were also enriched in oxidative phosphorylation functions (FDR < 0.05). We also addressed whether lifetime exposure to antipsychotics might influence gene expression, highlighting DUSP6, LBH, and NR1D1. Our results support the role of redox imbalance/mitochondrial dysfunction and implicate interneuron subtypes in SZ pathophysiology.

The microtubule cytoskeleton: An old validated target for novel therapeutic drugs

Compounds targeting microtubules are widely used in cancer therapy with a proven efficacy. However, because they also target non-cancerous cells, their administration leads to numerous adverse effects. With the advancement of knowledge on the structure of tubulin, the regulation of microtubule dynamics and their deregulation in pathological processes, new therapeutic strategies are emerging, both for the treatment of cancer and for other diseases, such as neuronal or even heart diseases and parasite infections. In addition, a better understanding of the mechanism of action of well-known drugs such as colchicine or certain kinase inhibitors contributes to the development of these new therapeutic approaches. Nowadays, chemists and biologists are working jointly to select drugs which target the microtubule cytoskeleton and have improved properties. On the basis of a few examples this review attempts to depict the panorama of these recent advances.

Exploring Links Between Psychosis and Frontotemporal Dementia Using Multimodal Machine Learning: Dementia Praecox Revisited

Importance

The behavioral and cognitive symptoms of severe psychotic disorders overlap with those seen in dementia. However, shared brain alterations remain disputed, and their relevance for patients in at-risk disease stages has not been explored so far.

Objective

To use machine learning to compare the expression of structural magnetic resonance imaging (MRI) patterns of behavioral-variant frontotemporal dementia (bvFTD), Alzheimer disease (AD), and schizophrenia; estimate predictability in patients with bvFTD and schizophrenia based on sociodemographic, clinical, and biological data; and examine prognostic value, genetic underpinnings, and progression in patients with clinical high-risk (CHR) states for psychosis or recent-onset depression (ROD).

Design, Setting, and Participants

This study included 1870 individuals from 5 cohorts, including (1) patients with bvFTD (n = 108), established AD (n = 44), mild cognitive impairment or early-stage AD (n = 96), schizophrenia (n = 157), or major depression (n = 102) to derive and compare diagnostic patterns and (2) patients with CHR (n = 160) or ROD (n = 161) to test patterns' prognostic relevance and progression. Healthy individuals (n = 1042) were used for age-related and cohort-related data calibration. Data were collected from January 1996 to July 2019 and analyzed between April 2020 and April 2022.

Main Outcomes and Measures

Case assignments based on diagnostic patterns; sociodemographic, clinical, and biological data; 2-year functional outcomes and genetic separability of patients with CHR and ROD with high vs low pattern expression; and pattern progression from baseline to follow-up MRI scans in patients with nonrecovery vs preserved recovery.

Results

Of 1870 included patients, 902 (48.2%) were female, and the mean (SD) age was 38.0 (19.3) years. The bvFTD pattern comprising prefrontal, insular, and limbic volume reductions was more expressed in patients with schizophrenia (65 of 157 [41.2%]) and major depression (22 of 102 [21.6%]) than the temporo-limbic AD patterns (28 of 157 [17.8%] and 3 of 102 [2.9%], respectively). bvFTD expression was predicted by high body mass index, psychomotor slowing, affective disinhibition, and paranoid ideation (R2 = 0.11). The schizophrenia pattern was expressed in 92 of 108 patients (85.5%) with bvFTD and was linked to the C9orf72 variant, oligoclonal banding in the cerebrospinal fluid, cognitive impairment, and younger age (R2 = 0.29). bvFTD and schizophrenia pattern expressions forecasted 2-year psychosocial impairments in patients with CHR and were predicted by polygenic risk scores for frontotemporal dementia, AD, and schizophrenia. Findings were not associated with AD or accelerated brain aging. Finally, 1-year bvFTD/schizophrenia pattern progression distinguished patients with nonrecovery from those with preserved recovery.

Conclusions and Relevance

Neurobiological links may exist between bvFTD and psychosis focusing on prefrontal and salience system alterations. Further transdiagnostic investigations are needed to identify shared pathophysiological processes underlying the neuroanatomical interface between the 2 disease spectra.

Protein Succinylation and Malonylation as Potential Biomarkers in Schizophrenia

Two protein post-translational modifications, lysine succinylation and malonylation, are implicated in protein regulation, glycolysis, and energy metabolism. The precursors of these modifications, succinyl-CoA and malonyl-CoA, are key players in central metabolic processes. Both modification profiles have been proven to be responsive to metabolic stimuli, such as hypoxia. As mitochondrial dysfunction and metabolic dysregulation are implicated in schizophrenia and other psychiatric illnesses, these modification profiles have the potential to reveal yet another layer of protein regulation and can furthermore represent targets for biomarkers that are indicative of disease as well as its progression and treatment. In this work, data from shotgun mass spectrometry-based quantitative proteomics were compiled and analyzed to probe the succinylome and malonylome of postmortem brain tissue from patients with schizophrenia against controls and the human oligodendrocyte precursor cell line MO3.13 with the dizocilpine chemical model for schizophrenia, three antipsychotics, and co-treatments. Several changes in the succinylome and malonylome were seen in these comparisons, revealing these modifications to be a largely under-studied yet important form of protein regulation with broad potential applications.

ARHGEF39, a Gene Implicated in Developmental Language Disorder, Activates RHOA and Is Involved in Cell De-Adhesion and Neural Progenitor Cell Proliferation

ARHGEF39 was previously implicated in developmental language disorder (DLD) via a functional polymorphism that can disrupt post-transcriptional regulation by microRNAs. ARHGEF39 is part of the family of Rho guanine nucleotide exchange factors (RhoGEFs) that activate small Rho GTPases to regulate a wide variety of cellular processes. However, little is known about the function of ARHGEF39, or how its function might contribute to neurodevelopment or related disorders. Here, we explore the molecular function of ARHGEF39 and show that it activates the Rho GTPase RHOA and that high ARHGEF39 expression in cell cultures leads to an increase of detached cells. To explore its role in neurodevelopment, we analyse published single cell RNA-sequencing data and demonstrate that ARHGEF39 is a marker gene for proliferating neural progenitor cells and that it is co-expressed with genes involved in cell division. This suggests a role for ARHGEF39 in neurogenesis in the developing brain. The co-expression of ARHGEF39 with other RHOA-regulating genes supports RHOA as substrate of ARHGEF39 in neural cells, and the involvement of RHOA in neuropsychiatric disorders highlights a potential link between ARHGEF39 and neurodevelopment and disorder. Understanding the GTPase substrate, co-expression network, and processes downstream of ARHGEF39 provide new avenues for exploring the mechanisms by which altered expression levels of ARHGEF39 may contribute to neurodevelopment and associated disorders.

Distinct proteomic profiles in prefrontal subareas of elderly major depressive disorder and bipolar disorder patients

We investigated for the first time the proteomic profiles both in the dorsolateral prefrontal cortex (DLPFC) and anterior cingulate cortex (ACC) of major depressive disorder (MDD) and bipolar disorder (BD) patients. Cryostat sections of DLPFC and ACC of MDD and BD patients with their respective well-matched controls were used for study. Proteins were quantified by tandem mass tag and high-performance liquid chromatography-mass spectrometry system. Gene Ontology terms and functional cluster alteration were analyzed through bioinformatic analysis. Over 3000 proteins were accurately quantified, with more than 100 protein expressions identified as significantly changed in these two brain areas of MDD and BD patients as compared to their respective controls. These include OGDH, SDHA and COX5B in the DLPFC in MDD patients; PFN1, HSP90AA1 and PDCD6IP in the ACC of MDD patients; DBN1, DBNL and MYH9 in the DLPFC in BD patients. Impressively, depending on brain area and distinct diseases, the most notable change we found in the DLPFC of MDD was 'suppressed energy metabolism'; in the ACC of MDD it was 'suppressed tissue remodeling and suppressed immune response'; and in the DLPFC of BD it was differentiated 'suppressed tissue remodeling and suppressed neuronal projection'. In summary, there are distinct proteomic changes in different brain areas of the same mood disorder, and in the same brain area between MDD and BD patients, which strengthens the distinct pathogeneses and thus treatment targets.

Common effects of bipolar disorder medications on expression quantitative trait loci genes

The molecular mechanism(s) underpinning the clinical efficacy of the current drugs for bipolar disorder (BD) are largely unknown. This study evaluated the transcriptional perturbations potentially playing roles in the therapeutic efficacy of four commonly prescribed psychotropic drugs used to treat BD. NT2-N cells were treated with lamotrigine, lithium, quetiapine, valproate or vehicle control for 24 h. Genome-wide mRNA expression was quantified by RNA-sequencing. Incorporating drug-induced gene expression profiles with BD-associated transcriptional changes from post-mortem brains, we identified potential therapeutic-relevant genes associated with both drug treatments and BD pathophysiology and focused on expression quantitative trait loci (eQTL) genes with genome-wide association with BD. Each eQTL gene was ranked based on its potential role in the therapeutic effect across multiple drugs. The expression of highest-ranked eQTL genes were measured by RT-qPCR to confirm their transcriptional changes observed in RNA-seq. We found 775 genes for which at least 2 drugs reversed expression levels relative to the differential expression in post-mortem brains. Pathway analysis identified enriched biological processes highlighting mitochondrial and endoplasmic reticulum function. Differential expression of SRPK2 and CHDH was confirmed by RT-qPCR following multiple-dose treatments. We pinpointed potential genes involved in the beneficial effects of drugs used for BD and their main associated biological pathways. CHDH, which encodes a mitochondrial protein, had a significant dose-responsive downregulation following treatment with increasing doses of quetiapine and lamotrigine, which in combination with the enriched mitochondrial pathways suggests potential therapeutic roles and demand more studies on mitochondrial involvement in BD to identify novel treatment targets.

Differential expression of gene co-expression networks related to the mTOR signaling pathway in bipolar disorder

Bipolar disorder (BPD) is a severe mental illness characterized by episodes of depression and mania. To investigate the molecular mechanisms underlying the pathophysiology of bipolar disorder, we performed transcriptome studies using RNA-seq data from the prefrontal cortex (PFC) of individuals with BPD and matched controls, as well as data from cell culture and animal model studies. We found 879 differentially expressed genes that were also replicated in an independent cohort of post-mortem samples. Genes involving the mechanistic target of rapamycine (mTOR) pathway were down-regulated, while genes interrelated with the mTOR pathway such as Janus kinase (JAK)-signal transducer and activator of transcription (STAT) pathway were up-regulated. Gene co-expression network analyses identified a module related to the mTOR pathway that was up-regulated in BPD and also enriched for markers of endothelial cells. We also found a down-regulated co-expression module enriched for genes involved in mTOR signalling and in mTOR related pathways and enriched with neuronal markers. The mTOR related modules were also replicated in the independent cohort of samples. To investigate whether the expression of the modules related to mTOR signalling pathway could be differentially regulated in different cell types we performed comparative network analyses in experimental models. We found both up-regulated modules in the PFC significantly overlapped with an up-regulated module in the brain endothelial cells from mice treated with lipopolysaccharides (LPS) and mTOR related pathways such as JAK-STAT, PI3K-Akt and ribosome were enriched in the common genes. In addition, the down-regulated module in the PFC significantly overlapped with a down-regulated module from neurons treated with the mTOR inhibitor, Torin1 and mTOR signalling, autophagy, and synaptic vesicle cycles were significantly enriched in the common genes. These results suggest that co-expression networks related to mTOR signalling pathways may be up- or down-regulated in different cell types in the PFC of BPD. These results provide novel insights into the molecular mechanisms underlying the pathophysiology of BPD.

Bioinformatics and Network-based Approaches for Determining Pathways, Signature Molecules, and Drug Substances connected to Genetic Basis of Schizophrenia etiology

Knowledge of heterogeneous etiology and pathophysiology of schizophrenia (SZP) is reasonably inadequate and non-deterministic due to its inherent complexity and underlying vast dynamics related to genetic mechanisms. The evolution of large-scale transcriptome-wide datasets and subsequent development of relevant, robust technologies for their analyses show promises toward elucidating the genetic basis of disease pathogenesis, its early risk prediction, and predicting drug molecule targets for therapeutic intervention. In this research, we have scrutinized the genetic basis of SZP through functional annotation and network-based system biology approaches. We have determined 96 overlapping differentially expressed genes (DEGs) from 2 microarray datasets and subsequently identified their interconnecting networks to reveal transcriptome signatures like hub proteins (FYN, RAD51, SOCS3, XIAP, AKAP13, PIK3C2A, CBX5, GATA3, EIF3K, and CDKN2B), transcription factors and miRNAs. In addition, we have employed gene set enrichment to highlight significant gene ontology (e.g., positive regulation of microglial cell activation) and relevant pathways (such as axon guidance and focal adhesion) interconnected to the genes associated with SZP. Finally, we have suggested candidate drug substances like Luteolin HL60 UP as a possible therapeutic target based on these key molecular signatures.

Transcriptomics and machine learning to advance schizophrenia genetics: A case-control study using post-mortem brain data

BACKGROUND AND OBJECTIVE

Alterations of the expression of a variety of genes have been reported in patients with schizophrenia (SCZ). Moreover, machine learning (ML) analysis of gene expression microarray data has shown promising preliminary results in the study of SCZ. Our objective was to evaluate the performance of ML in classifying SCZ cases and controls based on gene expression microarray data from the dorsolateral prefrontal cortex.

METHODS

We apply a state-of-the-art ML algorithm (XGBoost) to train and evaluate a classification model using 201 SCZ cases and 278 controls. We utilized 10-fold cross-validation for model selection, and a held-out testing set to evaluate the model. The performance metric utilizes to evaluate classification performance was the area under the receiver-operator characteristics curve (AUC).

RESULTS

We report an average AUC on 10-fold cross-validation of 0.76 and an AUC of 0.76 on testing data, not used during training. Analysis of the rolling balanced classification accuracy from high to low prediction confidence levels showed that the most certain subset of predictions ranged between 80-90%. The ML model utilized 182 gene expression probes. Further improvement to classification performance was observed when applying an automated ML strategy on the 182 features, which achieved an AUC of 0.79 on the same testing data. We found literature evidence linking all of the top ten ML ranked genes to SCZ. Furthermore, we leveraged information from the full set of microarray gene expressions available via univariate differential gene expression analysis. We then prioritized differentially expressed gene sets using the piano gene set analysis package. We augmented the ranking of the prioritized gene sets with genes from the complex multivariate ML model using hypergeometric tests to identify more robust gene sets. We identified two significant Gene Ontology molecular function gene sets: "oxidoreductase activity, acting on the CH-NH2 group of donors" and "integrin binding." Lastly, we present candidate treatments for SCZ based on findings from our study CONCLUSIONS: Overall, we observed above-chance performance from ML classification of SCZ cases and controls based on brain gene expression microarray data, and found that ML analysis of gene expressions could further our understanding of the pathophysiology of SCZ and help identify novel treatments.

Classification for psychiatric disorders including schizophrenia, bipolar disorder, and major depressive disorder using machine learning

Schizophrenia (SCZ), bipolar disorder (BP), and major depressive disorder (MDD) are the most common psychiatric disorders. Because there were lots of overlaps among these disorders from genetic epidemiology and molecular genetics, it is hard to realize the diagnoses of these psychiatric disorders. Currently, plenty of studies have been conducted for contributing to the diagnoses of these diseases. However, constructing a classification model with superior performance for differentiating SCZ, BP, and MDD samples is still a great challenge. In this study, the transcriptomic data was applied for discovering key genes and constructing a classification model. In this dataset, there were 268 samples including four groups (67 SCZ patients, 40 BP patients, 57 MDD patients, and 104 healthy controls), which were applied for constructing a classification model. First, 269 probes of differentially expressed genes (DEGs) among four sample groups were identified by the feature selection method. Second, these DEGs were validated by the literature review including disease relevance with the psychiatric disorders of these DEGs, the hub genes in the PPI (protein–protein interaction) network, and GO (gene ontology) terms and pathways. Third, a classification model was constructed using the identified DEGs by machine learning method to classify different groups. The ROC (receiver operator characteristic) curve and AUC (area under the curve) value were used to assess the classification capacity of the model. In summary, this classification model might provide clues for the diagnoses of these psychiatric disorders.

Mental depression: Relation to different disease status, newer treatments and its association with COVID-19 pandemic (Review)

The present study aimed to review major depression, including its types, epidemiology, association with different diseases status and treatments, as well as its correlation with the current COVID-19 pandemic. Mental depression is a common disorder that affects most individuals at one time or another. During depression, there are changes in mood and behavior, accompanied by feelings of defeat, hopelessness, or even suicidal thoughts. Depression has a direct or indirect relation with a number of other diseases including Alzheimer's disease, stroke, epilepsy, diabetes, cardiovascular disease and cancer. In addition, antidepressant drugs have several side effects including sedation, increased weight, indigestion, sexual dysfunction, or a decrease in blood pressure. Stopping medication may cause a relapse of the symptoms of depression and pose a risk of attempted suicide. The pandemic of COVID-19 has affected the mental health of individuals, including patients, individuals contacting patients and medical staff with a number of mental disorders that may adversely affect the immune ability of their bodies. Some of the drugs currently included in the protocols for treating COVID-19 may negatively affect the mental health of patients. Evidence accumulated over the years indicates that serotonin (5HT) deficiencies and norepinephrine (NE) in the brain can lead to mental depression. Drugs that increase levels of NE and 5HT are commonly used in the treatment of depression. The common reason for mood disorders, including mania and bipolar disease are not clearly understood. It is assumed that hyperactivity in specific parts of the brain and excessive activity of neurotransmitters may be involved. Early diagnosis and developing new treatment strategies are essential for the prevention of the severe consequences of depression. In addition, extensive research should be directed towards the investigation of the mental health disturbances occurring during and/or after COVID-19 infection. This may lead to the incorporation of a suitable antidepressant into the current treatment protocols.

Genome-wide association study revealed genetic variations of ABA sensitivity controlled by multiple stress-related genes in rice

Abscisic acid (ABA) is a critical phytohormone that regulates multiple physiological processes including plant growth and stress tolerance. The core ABA signaling pathway has been well established, but genetic variations mediating ABA responses remain largely unknown. In this study, we performed genome-wide association study (GWAS) to identify loci and genes associated with ABA sensitivity (reflected by seed germination inhibition by ABA) in a panel of 425 rice accessions. The seed germination assay revealed that Aus and indica rice had stronger ABA sensitivity than japonica rice. A total of 48 non-redundant association loci were detected in the indica subpopulation and whole population, and 386 genes in these loci were responsive to ABA or abiotic stresses. Eight association loci were overlapped with previously reported loci for yield under drought stress or for drought-indicative image traits. Haplotype analyses of important candidate genes such as OsSAPK6, a key component in the ABA signaling core, were performed to identify key SNPs/InDels that may affect gene functions through promoter activity regulation, amino acid variation, or gene splicing. These results provide insights into the genetic basis of ABA sensitivity related to stress responses.

Transcriptome Analysis of Post-Mortem Brain Tissue Reveals Up-Regulation of the Complement Cascade in a Subgroup of Schizophrenia Patients

Schizophrenia is a genetically complex neuropsychiatric disorder with largely unresolved mechanisms of pathology. Identification of genes and pathways associated with schizophrenia is important for understanding the development, progression and treatment of schizophrenia. In this study, pathways associated with schizophrenia were explored at the level of gene expression. The study included post-mortem brain tissue samples from 68 schizophrenia patients and 44 age and sex-matched control subjects. Whole transcriptome poly-A selected paired-end RNA sequencing was performed on tissue from the prefrontal cortex and orbitofrontal cortex. RNA expression differences were detected between case and control individuals, focusing both on single genes and pathways. The results were validated with RT-qPCR. Significant differential expression between patient and controls groups was found for 71 genes. Gene ontology analysis of differentially expressed genes revealed an up-regulation of multiple genes in immune response among the patients (corrected p-value = 0.004). Several genes in the category belong to the complement system, including C1R, C1S, C7, FCN3, SERPING1, C4A and CFI. The increased complement expression is primarily driven by a subgroup of patients with increased expression of immune/inflammatory response genes, pointing to important differences in disease etiology within the patient group. Weighted gene co-expression network analysis highlighted networks associated with both synaptic transmission and activation of the immune response. Our results demonstrate the importance of immune-related pathways in schizophrenia and provide evidence for elevated expression of the complement cascade as an important pathway in schizophrenia pathology.

LIM-Kinases in Synaptic Plasticity, Memory, and Brain Diseases

Learning and memory require structural and functional modifications of synaptic connections, and synaptic deficits are believed to underlie many brain disorders. The LIM-domain-containing protein kinases (LIMK1 and LIMK2) are key regulators of the actin cytoskeleton by affecting the actin-binding protein, cofilin. In addition, LIMK1 is implicated in the regulation of gene expression by interacting with the cAMP-response element-binding protein. Accumulating evidence indicates that LIMKs are critically involved in brain function and dysfunction. In this paper, we will review studies on the roles and underlying mechanisms of LIMKs in the regulation of long-term potentiation (LTP) and depression (LTD), the most extensively studied forms of long-lasting synaptic plasticity widely regarded as cellular mechanisms underlying learning and memory. We will also discuss the involvement of LIMKs in the regulation of the dendritic spine, the structural basis of synaptic plasticity, and memory formation. Finally, we will discuss recent progress on investigations of LIMKs in neurological and mental disorders, including Alzheimer’s, Parkinson’s, Williams–Beuren syndrome, schizophrenia, and autism spectrum disorders.

Beyond Neuronal Microtubule Stabilization: MAP6 and CRMPS, Two Converging Stories

The development and function of the central nervous system rely on the microtubule (MT) and actin cytoskeletons and their respective effectors. Although the structural role of the cytoskeleton has long been acknowledged in neuronal morphology and activity, it was recently recognized to play the role of a signaling platform. Following this recognition, research into Microtubule Associated Proteins (MAPs) diversified. Indeed, historically, structural MAPs—including MAP1B, MAP2, Tau, and MAP6 (also known as STOP);—were identified and described as MT-binding and -stabilizing proteins. Extensive data obtained over the last 20 years indicated that these structural MAPs could also contribute to a variety of other molecular roles. Among multi-role MAPs, MAP6 provides a striking example illustrating the diverse molecular and cellular properties of MAPs and showing how their functional versatility contributes to the central nervous system. In this review, in addition to MAP6’s effect on microtubules, we describe its impact on the actin cytoskeleton, on neuroreceptor homeostasis, and its involvement in signaling pathways governing neuron development and maturation. We also discuss its roles in synaptic plasticity, brain connectivity, and cognitive abilities, as well as the potential relationships between the integrated brain functions of MAP6 and its molecular activities. In parallel, the Collapsin Response Mediator Proteins (CRMPs) are presented as examples of how other proteins, not initially identified as MAPs, fall into the broader MAP family. These proteins bind MTs as well as exhibiting molecular and cellular properties very similar to MAP6. Finally, we briefly summarize the multiple similarities between other classical structural MAPs and MAP6 or CRMPs.In summary, this review revisits the molecular properties and the cellular and neuronal roles of the classical MAPs, broadening our definition of what constitutes a MAP.

MetaGSCA: A tool for meta-analysis of gene set differential coexpression

Analyses of gene set differential coexpression may shed light on molecular mechanisms underlying phenotypes and diseases. However, differential coexpression analyses of conceptually similar individual studies are often inconsistent and underpowered to provide definitive results. Researchers can greatly benefit from an open-source application facilitating the aggregation of evidence of differential coexpression across studies and the estimation of more robust common effects. We developed Meta Gene Set Coexpression Analysis (MetaGSCA), an analytical tool to systematically assess differential coexpression of an a priori defined gene set by aggregating evidence across studies to provide a definitive result. In the kernel, a nonparametric approach that accounts for the gene-gene correlation structure is used to test whether the gene set is differentially coexpressed between two comparative conditions, from which a permutation test p-statistic is computed for each individual study. A meta-analysis is then performed to combine individual study results with one of two options: a random-intercept logistic regression model or the inverse variance method. We demonstrated MetaGSCA in case studies investigating two human diseases and identified pathways highly relevant to each disease across studies. We further applied MetaGSCA in a pan-cancer analysis with hundreds of major cellular pathways in 11 cancer types. The results indicated that a majority of the pathways identified were dysregulated in the pan-cancer scenario, many of which have been previously reported in the cancer literature. Our analysis with randomly generated gene sets showed excellent specificity, indicating that the significant pathways/gene sets identified by MetaGSCA are unlikely false positives. MetaGSCA is a user-friendly tool implemented in both forms of a Web-based application and an R package “MetaGSCA”. It enables comprehensive meta-analyses of gene set differential coexpression data, with an optional module of post hoc pathway crosstalk network analysis to identify and visualize pathways having similar coexpression profiles.

Analyses of gene set differential coexpression often shed light on molecular mechanisms underlying phenotypes and diseases. However, results from conceptually similar individual studies are often inconsistent and underpowered to reach definitive conclusions. We provide an open-source application facilitating the aggregation of evidence of differential coexpression across studies and the estimation of more robust common effects, with an optional module of post hoc pathway crosstalk network analysis to identify and visualize pathways having similar coexpression profiles. We established the usefulness of MetaGSCA via case studies of chronic kidney disease and non-small cell lung cancer, and applied it to a pan-cancer analysis of 11 cancer types. We further demonstrated the tool with 100 randomly generated gene sets and showed excellent specificity, indicating low false positive rates.

Rewired Pathways and Disrupted Pathway Crosstalk in Schizophrenia Transcriptomes by Multiple Differential Coexpression Methods

Transcriptomic studies of mental disorders using the human brain tissues have been limited, and gene expression signatures in schizophrenia (SCZ) remain elusive. In this study, we applied three differential co-expression methods to analyze five transcriptomic datasets (three RNA-Seq and two microarray datasets) derived from SCZ and matched normal postmortem brain samples. We aimed to uncover biological pathways where internal correlation structure was rewired or inter-coordination was disrupted in SCZ. In total, we identified 60 rewired pathways, many of which were related to neurotransmitter, synapse, immune, and cell adhesion. We found the hub genes, which were on the center of rewired pathways, were highly mutually consistent among the five datasets. The combinatory list of 92 hub genes was generally multi-functional, suggesting their complex and dynamic roles in SCZ pathophysiology. In our constructed pathway crosstalk network, we found “Clostridium neurotoxicity” and “signaling events mediated by focal adhesion kinase” had the highest interactions. We further identified disconnected gene links underlying the disrupted pathway crosstalk. Among them, four gene pairs (PAK1:SYT1, PAK1:RFC5, DCTN1:STX1A, and GRIA1:MAP2K4) were normally correlated in universal contexts. In summary, we systematically identified rewired pathways, disrupted pathway crosstalk circuits, and critical genes and gene links in schizophrenia transcriptomes.

Effects of the co-administration of MK-801 and clozapine on MiRNA expression profiles in rats

MiRNAs are small, non-coding RNAs that can silence the expression of various target genes by binding their mRNAs and thus regulate a wide range of crucial bodily functions. However, the miRNA expression profile of schizophrenia after antipsychotic mediation is largely unknown. Non-competitive N-methyl-D-aspartic acid (NMDA) receptor antagonists such as MK-801 have provided useful animal models to investigate the effects of schizophrenia-like symptoms in rodent animals. Herein, the hippocampal miRNA expression profiles of Sprague-Dawley rats pretreated with MK-801 were examined after antipsychotic clozapine (CLO) treatment. Total hippocampal RNAs from three groups were subjected to next-generation sequencing (NGS), and bioinformatics analyses, including differential expression and enrichment analyses, were performed. Eight miRNAs were differentially expressed between the MK-801 and vehicle (VEH) control groups. Interestingly, 14 miRNAs were significantly differentially expressed between the CLO + MK-801 and MK-801 groups, among which rno-miR-184 was the most upregulated. Further analyses suggested that these miRNAs modulate target genes that are involved in endocytosis regulation, ubiquitin-mediated proteolysis, and actin cytoskeleton regulation and thus might play important roles in the pathogenesis of schizophrenia. Our results suggest that differentially expressed miRNAs play important roles in the complex pathophysiology of schizophrenia and subsequently impact brain functions.

Brain-immune interactions in neuropsychiatric disorders: Lessons from transcriptome studies for molecular targeting

Understanding the pathophysiological mechanisms of neuropsychiatric disorders has been a challenging quest for neurobiologists. Recent years have witnessed enormous technological advances in the field of neuroimmunology, blurring boundaries between the central nervous system and the periphery. Consequently, the discipline has expanded to cover interactions between the nervous and immune systems in health and diseases. The complex interplay between the peripheral and central immune pathways in neuropsychiatric disorders has recently been documented in various studies, but the genetic determinants remain elusive. Recent transcriptome studies have identified dysregulated genes involved in peripheral immune cell activation, blood-brain barrier integrity, glial cell activation, and synaptic plasticity in major depressive disorder, bipolar disorder, autism spectrum disorder, and schizophrenia. Herein, the key transcriptomic techniques applied in investigating differentially expressed genes and pathways responsible for altered brain-immune interactions in neuropsychiatric disorders are discussed. The application of transcriptomics that can aid in identifying molecular targets in various neuropsychiatric disorders is highlighted.

Genome-wide association study of psychiatric and substance use comorbidity in Mexican individuals

The combination of substance use and psychiatric disorders is one of the most common comorbidities. The objective of this study was to perform a genome-wide association study of this comorbidity (Com), substance use alone (Subs), and psychiatric symptomatology alone (Psych) in the Mexican population. The study included 3914 individuals of Mexican descent. Genotyping was carried out using the PsychArray microarray and genome-wide correlations were calculated. Genome-wide associations were analyzed using multiple logistic models, polygenic risk scores (PRSs) were evaluated using multinomial models, and vertical pleiotropy was evaluated by generalized summary-data-based Mendelian randomization. Brain DNA methylation quantitative loci (brain meQTL) were also evaluated in the prefrontal cortex. Genome-wide correlation and vertical pleiotropy were found between all traits. No genome-wide association signals were found, but 64 single-nucleotide polymorphism (SNPs) reached nominal associations (p < 5.00e-05). The SNPs associated with each trait were independent, and the individuals with high PRSs had a higher prevalence of tobacco and alcohol use. In the multinomial models all of the PRSs (Subs-PRS, Com-PRS, and Psych-PRS) were associated with all of the traits. Brain meQTL of the Subs-associated SNPs had an effect on the genes enriched in insulin signaling pathway, and that of the Psych-associated SNPs had an effect on the Fc gamma receptor phagocytosis pathway.

Pyr1-Mediated Pharmacological Inhibition of LIM Kinase Restores Synaptic Plasticity and Normal Behavior in a Mouse Model of Schizophrenia

The search for effective treatments for neuropsychiatric disorders is ongoing, with progress being made as brain structure and neuronal function become clearer. The central roles played by microtubules (MT) and actin in synaptic transmission and plasticity suggest that the cytoskeleton and its modulators could be relevant targets for the development of new molecules to treat psychiatric diseases. In this context, LIM Kinase - which regulates both the actin and MT cytoskeleton especially in dendritic spines, the post-synaptic compartment of the synapse - might be a good target. In this study, we analyzed the consequences of blocking LIMK1 pharmacologically using Pyr1. We investigated synaptic plasticity defects and behavioral disorders in MAP6 KO mice, an animal model useful for the study of psychiatric disorders, particularly schizophrenia. Our results show that Pyr1 can modulate MT dynamics in neurons. In MAP6 KO mice, chronic LIMK inhibition by long-term treatment with Pyr1 can restore normal dendritic spine density and also improves long-term potentiation, both of which are altered in these mice. Pyr1 treatment improved synaptic plasticity, and also reduced social withdrawal and depressive/anxiety-like behavior in MAP6 KO mice. Overall, the results of this study validate the hypothesis that modulation of LIMK activity could represent a new therapeutic strategy for neuropsychiatric diseases.

nMAGMA: a network-enhanced method for inferring risk genes from GWAS summary statistics and its application to schizophrenia

MOTIVATION

Annotating genetic variants from summary statistics of genome-wide association studies (GWAS) is crucial for predicting risk genes of various disorders. The multimarker analysis of genomic annotation (MAGMA) is one of the most popular tools for this purpose, where MAGMA aggregates signals of single nucleotide polymorphisms (SNPs) to their nearby genes. In biology, SNPs may also affect genes that are far away in the genome, thus missed by MAGMA. Although different upgrades of MAGMA have been proposed to extend gene-wise variant annotations with more information (e.g. Hi-C or eQTL), the regulatory relationships among genes and the tissue specificity of signals have not been taken into account.

RESULTS

We propose a new approach, namely network-enhanced MAGMA (nMAGMA), for gene-wise annotation of variants from GWAS summary statistics. Compared with MAGMA and H-MAGMA, nMAGMA significantly extends the lists of genes that can be annotated to SNPs by integrating local signals, long-range regulation signals (i.e. interactions between distal DNA elements), and tissue-specific gene networks. When applied to schizophrenia (SCZ), nMAGMA is able to detect more risk genes (217% more than MAGMA and 57% more than H-MAGMA) that are involved in SCZ compared with MAGMA and H-MAGMA, and more of nMAGMA results can be validated with known SCZ risk genes. Some disease-related functions (e.g. the ATPase pathway in Cortex) are also uncovered in nMAGMA but not in MAGMA or H-MAGMA. Moreover, nMAGMA provides tissue-specific risk signals, which are useful for understanding disorders with multitissue origins.

Whole blood transcriptome analysis in bipolar disorder reveals strong lithium effect

BACKGROUND

Bipolar disorder (BD) is a highly heritable mood disorder with complex genetic architecture and poorly understood etiology. Previous transcriptomic BD studies have had inconsistent findings due to issues such as small sample sizes and difficulty in adequately accounting for confounders like medication use.

METHODS

We performed a differential expression analysis in a well-characterized BD case-control sample (Nsubjects = 480) by RNA sequencing of whole blood. We further performed co-expression network analysis, functional enrichment, and cell type decomposition, and integrated differentially expressed genes with genetic risk.

RESULTS

While we observed widespread differential gene expression patterns between affected and unaffected individuals, these effects were largely linked to lithium treatment at the time of blood draw (FDR < 0.05, Ngenes = 976) rather than BD diagnosis itself (FDR < 0.05, Ngenes = 6). These lithium-associated genes were enriched for cell signaling and immune response functional annotations, among others, and were associated with neutrophil cell-type proportions, which were elevated in lithium users. Neither genes with altered expression in cases nor in lithium users were enriched for BD, schizophrenia, and depression genetic risk based on information from genome-wide association studies, nor was gene expression associated with polygenic risk scores for BD.

CONCLUSIONS

These findings suggest that BD is associated with minimal changes in whole blood gene expression independent of medication use but emphasize the importance of accounting for medication use and cell type heterogeneity in psychiatric transcriptomic studies. The results of this study add to mounting evidence of lithium's cell signaling and immune-related mechanisms.

Genome-Wide Meta-Analyses of FTND and TTFC Phenotypes

INTRODUCTION

FTND (Fagerstrӧm test for nicotine dependence) and TTFC (time to smoke first cigarette in the morning) are common measures of nicotine dependence (ND). However, genome-wide meta-analysis for these phenotypes has not been reported.

METHODS

Genome-wide meta-analyses for FTND (N = 19,431) and TTFC (N = 18,567) phenotypes were conducted for adult smokers of European ancestry from 14 independent cohorts.

RESULTS

We found that SORBS2 on 4q35 (p = 4.05 × 10-8), BG182718 on 11q22 (p = 1.02 × 10-8), and AA333164 on 14q21 (p = 4.11 × 10-9) were associated with TTFC phenotype. We attempted replication of leading candidates with independent samples (FTND, N = 7010 and TTFC, N = 10 061), however, due to limited power of the replication samples, the replication of these new loci did not reach significance. In gene-based analyses, COPB2 was found associated with FTND phenotype, and TFCP2L1, RELN, and INO80C were associated with TTFC phenotype. In pathway and network analyses, we found that the interconnected interactions among the endocytosis, regulation of actin cytoskeleton, axon guidance, MAPK signaling, and chemokine signaling pathways were involved in ND.

CONCLUSIONS

Our analyses identified several promising candidates for both FTND and TTFC phenotypes, and further verification of these candidates was necessary. Candidates supported by both FTND and TTFC (CHRNA4, THSD7B, RBFOX1, and ZNF804A) were associated with addiction to alcohol, cocaine, and heroin, and were associated with autism and schizophrenia. We also identified novel pathways involved in cigarette smoking. The pathway interactions highlighted the importance of receptor recycling and internalization in ND.

IMPLICATIONS

Understanding the genetic architecture of cigarette smoking and ND is critical to develop effective prevention and treatment. Our study identified novel candidates and biological pathways involved in FTND and TTFC phenotypes, and this will facilitate further investigation of these candidates and pathways.

Expression correlation attenuates within and between key signaling pathways in chronic kidney disease

Background

Compared to the conventional differential expression approach, differential coexpression analysis represents a different yet complementary perspective into diseased transcriptomes. In particular, global loss of transcriptome correlation was previously observed in aging mice, and a most recent study found genetic and environmental perturbations on human subjects tended to cause universal attenuation of transcriptome coherence. While methodological progresses surrounding differential coexpression have helped with research on several human diseases, there has not been an investigation of coexpression disruptions in chronic kidney disease (CKD) yet.

Methods

RNA-seq was performed on total RNAs of kidney tissue samples from 140 CKD patients. A combination of differential coexpression methods were employed to analyze the transcriptome transition in CKD from the early, mild phase to the late, severe kidney damage phase.

Results

We discovered a global expression correlation attenuation in CKD progression, with pathway Regulation of nuclear SMAD2/3 signaling demonstrating the most remarkable intra-pathway correlation rewiring. Moreover, the pathway Signaling events mediated by focal adhesion kinase displayed significantly weakened crosstalk with seven pathways, including Regulation of nuclear SMAD2/3 signaling. Well-known relevant genes, such as ACTN4, were characterized with widespread correlation disassociation with partners from a wide array of signaling pathways.

Conclusions

Altogether, our analysis reported a global expression correlation attenuation within and between key signaling pathways in chronic kidney disease, and presented a list of vanishing hub genes and disrupted correlations within and between key signaling pathways, illuminating on the pathophysiological mechanisms of CKD progression.

Gene expression and response prediction to amisulpride in the OPTiMiSE first episode psychoses

A fundamental shortcoming in the current treatment of schizophrenia is the lack of valid criteria to predict who will respond to antipsychotic treatment. The identification of blood-based biological markers of the therapeutic response would enable clinicians to identify the subgroup of patients in whom conventional antipsychotic treatment is ineffective and offer alternative treatments. As part of the Optimisation of Treatment and Management of Schizophrenia in Europe (OPTiMiSE) programme, we conducted an RNA-Seq analysis on 188 subjects with first episode psychosis, all of whom were subsequently treated with amisulpride for 4 weeks. We compared gene expression on total RNA from patients' blood before and after treatment and identified 32 genes for which the expression changed after treatment in good responders only. These findings were replicated in an independent sample of 24 patients with first episode psychosis. Six genes showed a significant difference in expression level between good and poor responders before starting treatment, allowing to predict treatment outcome with a predictive value of 93.8% when combined with clinical features. Collectively, these findings identified new mechanisms to explain symptom improvement after amisulpride medication and highlight the potential of combining gene expression profiling with clinical data to predict treatment response in first episode psychoses.

Ubiquitin-proteasome system, lipid metabolism and DNA damage repair are triggered by antipsychotic medication in human oligodendrocytes: implications in schizophrenia

Schizophrenia is a chronic, severe and disabling psychiatric disorder, whose treatment is based on psychosocial interventions and the use of antipsychotic drugs. While the effects of these drugs are well elucidated in neuronal cells, they are still not so clear in oligodendrocytes, which play a vital role in schizophrenia. Thus, we aimed to characterize biochemical profiles by proteomic analyses of human oligodendrocytes (MO3.13) which were matured using a protocol we developed and treated with either haloperidol (a typical antipsychotic), clozapine (an atypical antipsychotic) or a clozapine + D-serine co-treatment, which has emerged lately as an alternative type of treatment. This was accomplished by employing shotgun proteomics, using nanoESI-LC-MS/MS label-free quantitation. Proteomic analysis revealed biochemical pathways commonly affected by all tested antipsychotics were mainly associated to ubiquitination, proteasome degradation, lipid metabolism and DNA damage repair. Clozapine and haloperidol treatments also affected proteins involved with the actin cytoskeleton and with EIF2 signaling. In turn, metabolic processes, especially the metabolism of nitrogenous compounds, were a predominant target of modulation of clozapine + D-serine treatment. In this context, we seek to contribute to the understanding of the biochemical and molecular mechanisms involved in the action of antipsychotics on oligodendrocytes, along with their possible implications in schizophrenia.

Integrin adhesion in brain assembly: From molecular structure to neuropsychiatric disorders

Integrins are extracellular matrix receptors that mediate biochemical and mechanical bi-directional signals between the extracellular and intracellular environment of a cell thanks to allosteric conformational changes. In the brain, they are found in both neurons and glial cells, where they play essential roles in several aspects of brain development and function, such as cell migration, axon guidance, synaptogenesis, synaptic plasticity and neuro-inflammation. Although there are many successful examples of how regulating integrin adhesion and signaling can be used for therapeutic purposes, for example for halting tumor progression, this is not the case for the brain, where the growing evidence of the importance of integrins for brain pathophysiology has not translated yet into medical applications. Here, we review recent literature showing how alterations in integrin structure, expression and signaling may be involved in the etiology of autism spectrum disorder, epilepsy, schizophrenia, addiction, depression and Alzheimer's disease. We focus on common mechanisms and recurrent signaling pathways, trying to bridge studies on the genetics and molecular structure of integrins with those on synaptic physiology and brain pathology. Further, we discuss integrin-targeting strategies and their potential benefits for therapeutic purposes in neuropsychiatric disorders.

Validity and utility of Hierarchical Taxonomy of Psychopathology (HiTOP): I. Psychosis superspectrum

The Hierarchical Taxonomy of Psychopathology (HiTOP) is a scientific effort to address shortcomings of traditional mental disorder diagnoses, which suffer from arbitrary boundaries between psychopathology and normality, frequent disorder co-occurrence, heterogeneity within disorders, and diagnostic instability. This paper synthesizes evidence on the validity and utility of the thought disorder and detachment spectra of HiTOP. These spectra are composed of symptoms and maladaptive traits currently subsumed within schizophrenia, other psychotic disorders, and schizotypal, paranoid and schizoid personality disorders. Thought disorder ranges from normal reality testing, to maladaptive trait psychoticism, to hallucinations and delusions. Detachment ranges from introversion, to maladaptive detachment, to blunted affect and avolition. Extensive evidence supports the validity of thought disorder and detachment spectra, as each spectrum reflects common genetics, environmental risk factors, childhood antecedents, cognitive abnormalities, neural alterations, biomarkers, and treatment response. Some of these characteristics are specific to one spectrum and others are shared, suggesting the existence of an overarching psychosis superspectrum. Further research is needed to extend this model, such as clarifying whether mania and dissociation belong to thought disorder, and explicating processes that drive development of the spectra and their subdimensions. Compared to traditional diagnoses, the thought disorder and detachment spectra demonstrated substantially improved utility: greater reliability, larger explanatory and predictive power, and higher acceptability to clinicians. Validated measures are available to implement the system in practice. The more informative, reliable and valid characterization of psychosis-related psychopathology offered by HiTOP can make diagnosis more useful for research and clinical care.

Gene expression changes associated with trajectories of psychopathology in a longitudinal cohort of children and adolescents

We aimed to identify blood gene expression patterns associated to psychopathological trajectories retrieved from a large community, focusing on the emergence and remission of general psychiatric symptoms. Hundred and three individuals from the Brazilian High-Risk Cohort Study (BHRCS) for mental disorders were classified in four groups according to Child Behavior Checklist (CBCL) total score at the baseline (w0) and after 3 years (w1): low-high (L-H) (N = 27), high-low (H-L) (N = 12), high-high (H-H) (N = 34) and low-low (L-L) groups (N = 30). Blood gene expression profile was measured using Illumina HT-12 Beadchips, and paired analyses comparing w0 and w1 were performed for each group. Results: 98 transcripts were differentially expressed comparing w0 and w1 in the L-H, 33 in the H-L, 177 in the H-H and 273 in the L-L. Of these, 66 transcripts were differentially expressed exclusively in the L-H; and 6 only in the H-L. Cross-Lagged Panel Models analyses revealed that RPRD2 gene expression at w1 might be influenced by the CBCL score at w0. Moreover, COX5B, SEC62, and NDUFA2 were validated with another technique and were also differentially regulated in postmortem brain of subjects with mental disorders, indicating that they might be important not only to specific disorders, but also to general psychopathology and symptoms trajectories. Whereas genes related to metabolic pathways seem to be associated with the emergence of psychiatric symptoms, mitochondrial inner membrane genes might be important over the course of normal development. These results suggest that changes in gene expression can be detected in blood in different psychopathological trajectories.

C2H2-Type Zinc Finger Proteins in Brain Development, Neurodevelopmental, and Other Neuropsychiatric Disorders: Systematic Literature-Based Analysis

Neurodevelopmental disorders (NDDs) are multifaceted pathologic conditions manifested with intellectual disability, autistic features, psychiatric problems, motor dysfunction, and/or genetic/chromosomal abnormalities. They are associated with skewed neurogenesis and brain development, in part through dysfunction of the neural stem cells (NSCs) where abnormal transcriptional regulation on key genes play significant roles. Recent accumulated evidence highlights C₂H₂-type zinc finger proteins (C₂H₂-ZNFs), the largest transcription factor family in humans, as important targets for the pathologic processes associated with NDDs. In this review, we identified their significant accumulation (74 C₂H₂-ZNFs: ~10% of all human member proteins) in brain physiology and pathology. Specifically, we discuss their physiologic contribution to brain development, particularly focusing on their actions in NSCs. We then explain their pathologic implications in various forms of NDDs, such as morphological brain abnormalities, intellectual disabilities, and psychiatric disorders. We found an important tendency that poly-ZNFs and KRAB-ZNFs tend to be involved in the diseases that compromise gross brain structure and human-specific higher-order functions, respectively. This may be consistent with their characteristic appearance in the course of species evolution and corresponding contribution to these brain activities.

Whole-exome sequencing of 81 individuals from 27 multiply affected bipolar disorder families

Bipolar disorder (BD) is a highly heritable neuropsychiatric disease characterized by recurrent episodes of depression and mania. Research suggests that the cumulative impact of common alleles explains 25-38% of phenotypic variance, and that rare variants may contribute to BD susceptibility. To identify rare, high-penetrance susceptibility variants for BD, whole-exome sequencing (WES) was performed in three affected individuals from each of 27 multiply affected families from Spain and Germany. WES identified 378 rare, non-synonymous, and potentially functional variants. These spanned 368 genes, and were carried by all three affected members in at least one family. Eight of the 368 genes harbored rare variants that were implicated in at least two independent families. In an extended segregation analysis involving additional family members, five of these eight genes harbored variants showing full or nearly full cosegregation with BD. These included the brain-expressed genes RGS12 and NCKAP5, which were considered the most promising BD candidates on the basis of independent evidence. Gene enrichment analysis for all 368 genes revealed significant enrichment for four pathways, including genes reported in de novo studies of autism (p_adj < 0.006) and schizophrenia (p_adj = 0.015). These results suggest a possible genetic overlap with BD for autism and schizophrenia at the rare-sequence-variant level. The present study implicates novel candidate genes for BD development, and may contribute to an improved understanding of the biological basis of this common and often devastating disease.

Changed cortical risk gene expression in major depression and shared changes in cortical gene expression between major depression and bipolar disorders

BACKGROUND

Mood disorders likely occur in someone with a genetic predisposition who encounters a deleterious environmental factor leading to dysregulated physiological processes due to genetic mutations and epigenetic mechanisms altering gene expression. To gain data to support this hypothesis, we measured levels of gene expression in three cortical regions known to be affected by the pathophysiologies of major depression and bipolar disorders.

METHODS

Levels of RNA were measured using the Affymetrix™ Human Exon 1.0 ST Array in Brodmann's areas 9, 10 and 33 (left hemisphere) from individuals with major depression, bipolar disorder and age- and sex-matched controls with changed expression taken as a fold change in RNA ⩾1.2 at p < 0.01. Data were analysed using JMP^® genomics 6.0 and the probable biological consequences of changes in gene expression determined using Core and Pathway Designer Analyses in Ingenuity Pathway Analysis.

RESULTS

There were altered levels of RNA in Brodmann's area 9 (major depression = 424; bipolar disorder = 331), Brodmann's area 10 (major depression = 52; bipolar disorder = 24) and Brodmann's area 33 (major depression = 59 genes; bipolar disorder = 38 genes) in mood disorders. No gene was differentially expressed in all three regions in either disorder. There was a high correlation between fold changes in levels of RNA from 112 genes in Brodmann's area 9 from major depression and bipolar disorder (r² = 0.91, p < 0.001). Levels of RNA for four risk genes for major depression were lower in Brodmann's area 9 in that disorder.

CONCLUSION

Our data argue that there are complex regional-specific changes in cortical gene expression in major depression and bipolar disorder that includes the expression of some risk genes for major depression in those with that disorder. It could be hypothesised that the common changes in gene expression in major depression and bipolar disorder are involved in the genesis of symptoms common to both disorders.

Current understanding of bipolar disorder: Toward integration of biological basis and treatment strategies

Biological studies of bipolar disorder initially focused on the mechanism of action for antidepressants and antipsychotic drugs, and the roles of monoamines (e.g., serotonin, dopamine) have been extensively studied. Thereafter, based on the mechanism of action of lithium, intracellular signal transduction systems, including inositol metabolism and intracellular calcium signaling, have drawn attention. Involvement of intracellular calcium signaling has been supported by genetics and cellular studies. Elucidation of the neural circuits affected by calcium signaling abnormalities is critical, and our previous study suggested a role of the paraventricular thalamic nucleus. The genetic vulnerability of mitochondria causes calcium dysregulation and results in the hyperexcitability of serotonergic neurons, which are suggested to be susceptible to oxidative stress. Efficacy of anticonvulsants, animal studies of candidate genes, and studies using induced pluripotent stem cell-derived neurons have suggested a relation between bipolar disorder and the hyperexcitability of neurons. Recent genetic findings suggest the roles of polyunsaturated acids. At the systems level, social rhythm therapy targets circadian rhythm abnormalities, and cognitive behavioral therapy may target emotion/cognition (E/C) imbalance. In the future, pharmacological and psychosocial treatments may be combined and optimized based on the biological basis of each patient, which will realize individualized treatment.

Microglia along sex lines: From brain colonization, maturation and function, to implication in neurodevelopmental disorders

In addition to their traditional role as immune sentinels, recent discoveries over the last decade have shown that microglial functions now include regulation of neuronal/glial cell migration, differentiation and maturation, as well as neuronal network formation. It was thus proposed that disruption of these microglial roles, during critical periods of brain development, could lead to the pathological onset of several neurodevelopmental disorders, including autism spectrum disorder, attention deficit hyperactivity disorder, epilepsy, schizophrenia, and major depressive disorder. The prevalence of these disorders exhibits a clear distinction along sex lines with very little known about the mechanisms underlying this difference. One of the fundamental discoveries that arose from recent research into the physiological roles of microglia in neurodevelopment is their sexual dimorphism, raising the intriguing possibility that sex differences in microglial colonization, maturation and/or function in the developing brain could underlie the emergence of various neurodevelopmental disorders. This review discusses the physiological roles of microglia across neurodevelopment, these roles in the two sexes, and the recent evidence that microglial sexually dimorphic nature may contribute, at least partially, to neurodevelopmental disorders.

Regional Heterogeneity in Gene Expression, Regulation, and Coherence in the Frontal Cortex and Hippocampus across Development and Schizophrenia

The hippocampus formation, although prominently implicated in schizophrenia pathogenesis, has been overlooked in large-scale genomics efforts in the schizophrenic brain. We performed RNA-seq in hippocampi and dorsolateral prefrontal cortices (DLPFCs) from 551 individuals (286 with schizophrenia). We identified substantial regional differences in gene expression and found widespread developmental differences that were independent of cellular composition. We identified 48 and 245 differentially expressed genes (DEGs) associated with schizophrenia within the hippocampus and DLPFC, with little overlap between the brain regions. 124 of 163 (76.6%) of schizophrenia GWAS risk loci contained eQTLs in any region. Transcriptome-wide association studies in each region identified many novel schizophrenia risk features that were brain region-specific. Last, we identified potential molecular correlates of in vivo evidence of altered prefrontal-hippocampal functional coherence in schizophrenia. These results underscore the complexity and regional heterogeneity of the transcriptional correlates of schizophrenia and offer new insights into potentially causative biology.

Commonality in dysregulated expression of gene sets in cortical brains of individuals with autism, schizophrenia, and bipolar disorder

Individuals affected with different neuropsychiatric disorders such as autism (AUT), schizophrenia (SCZ) and bipolar disorder (BPD), may share similar clinical manifestations, suggesting shared genetic influences and common biological mechanisms underlying these disorders. Using brain transcriptome data gathered from postmortem donors affected with AUT, SCZ and BPD, it is now possible to identify shared dysregulated gene sets, i.e., those abnormally expressed in brains of neuropsychiatric patients, compared to non-psychiatric controls. Here, we apply a novel aberrant gene expression analysis method, coupled with consensus co-expression network analysis, to identify gene sets with shared dysregulated expression in cortical brains of individuals affected with AUT, SCZ and BPD. We identify eight gene sets with dysregulated expression shared by AUT, SCZ and BPD, 23 by AUT and SCZ, four by AUT and BPD, and two by SCZ and BPD. The identified genes are enriched with functions relevant to amino acid transport, synapse, neurotransmitter release, oxidative stress, nitric oxide synthase biosynthesis, immune response, protein folding, lysophosphatidic acid-mediated signaling and glycolysis. Our method has been proven to be effective in discovering and revealing multigene sets with dysregulated expression shared by different neuropsychiatric disorders. Our findings provide new insights into the common molecular mechanisms underlying the pathogenesis and progression of AUT, SCZ and BPD, contributing to the study of etiological overlap between these neuropsychiatric disorders.

Translational bioinformatics in mental health: open access data sources and computational biomarker discovery

Mental illness is increasingly recognized as both a significant cost to society and a significant area of opportunity for biological breakthrough. As -omics and imaging technologies enable researchers to probe molecular and physiological underpinnings of multiple diseases, opportunities arise to explore the biological basis for behavioral health and disease. From individual investigators to large international consortia, researchers have generated rich data sets in the area of mental health, including genomic, transcriptomic, metabolomic, proteomic, clinical and imaging resources. General data repositories such as the Gene Expression Omnibus (GEO) and Database of Genotypes and Phenotypes (dbGaP) and mental health (MH)-specific initiatives, such as the Psychiatric Genomics Consortium, MH Research Network and PsychENCODE represent a wealth of information yet to be gleaned. At the same time, novel approaches to integrate and analyze data sets are enabling important discoveries in the area of mental and behavioral health. This review will discuss and catalog into an organizing framework the increasingly diverse set of MH data resources available, using schizophrenia as a focus area, and will describe novel and integrative approaches to molecular biomarker discovery that make use of mental health data.

Fine-mapping scan of bipolar disorder susceptibility loci in Latino pedigrees

We previously identified bipolar disorder (BD) susceptibility loci on 8q24, 14q32, and 2q12-14 in a genome-wide nonparametric linkage screen in a Latino cohort. We now perform a fine mapping analysis using a dense map of additional SNPs to identify BD susceptibility genes within these regions. One thousand nine hundred and thirty-eight individuals with Latino ancestry (880 individuals with BD Type I or Schizoaffective, Bipolar Type) from 416 Latino pedigrees from the United States, Mexico, Costa Rica, and Guatemala were genotyped with 3,074 SNPs to provide dense coverage of the 8q24 (11.5 cM), 14q32 (7.5 cM), and 2q12-14 (6.5 cM) chromosomal loci. Single-marker association tests in the presence of linkage were performed using the LAMP software. The top linkage peak (rs7834818; LOD = 5.08, p = 3.30E - 5) and associated single marker (rs2280915, p = 2.70E - 12) were located within FBXO32 on 8q24. On chromosome 2, the top linkage peak (rs6750326; LOD = 5.06, p = 3.50E - 5) and associated single marker (rs11887088, p = 2.90E - 6) were located in intragenic regions near ACTR3 and DPP10. None of the additional markers in the region around chromosome 14q32 met significance levels for linkage or association. We identified six SNPs on 2q12-q14 and one SNP in FBXO32 on 8q24 that were significantly associated with BD in this Latino cohort.

Mega-analysis of Odds Ratio: A Convergent Method for a Deep Understanding of the Genetic Evidence in Schizophrenia

Numerous high-throughput omics studies have been conducted in schizophrenia, providing an accumulated catalog of susceptible variants and genes. The results from these studies, however, are highly heterogeneous. The variants and genes nominated by different omics studies often have limited overlap with each other. There is thus a pressing need for integrative analysis to unify the different types of data and provide a convergent view of schizophrenia candidate genes (SZgenes). In this study, we collected a comprehensive, multidimensional dataset, including 7819 brain-expressed genes. The data hosted genome-wide association evidence in genetics (eg, genotyping data, copy number variations, de novo mutations), epigenetics, transcriptomics, and literature mining. We developed a method named mega-analysis of odds ratio (MegaOR) to prioritize SZgenes. Application of MegaOR in the multidimensional data resulted in consensus sets of SZgenes (up to 530), each enriched with dense, multidimensional evidence. We proved that these SZgenes had highly tissue-specific expression in brain and nerve and had intensive interactions that were significantly stronger than chance expectation. Furthermore, we found these SZgenes were involved in human brain development by showing strong spatiotemporal expression patterns; these characteristics were replicated in independent brain expression datasets. Finally, we found the SZgenes were enriched in critical functional gene sets involved in neuronal activities, ligand gated ion signaling, and fragile X mental retardation protein targets. In summary, MegaOR analysis reported consensus sets of SZgenes with enriched association evidence to schizophrenia, providing insights into the pathophysiology underlying schizophrenia.