The CHRM3 gene is implicated in abnormal thalamo-orbital frontal cortex functional connectivity in first-episode treatment-naive patients with schizophrenia

Comprehensive analysis of circRNA expression profile and circRNA-miRNA-mRNA network susceptibility to very early-onset schizophrenia

To explore the potential role of circular RNAs (circRNAs) in children developing very early-onset schizophrenia (VEOS). Total RNA was extracted from the plasma samples of 10 VEOS patients and eight healthy controls. Expression profiles of circRNAs, micro RNAs (miRNAs), and messenger RNAs (mRNAs) were analyzed using RNA-seq. The interaction networks between miRNAs and targets were predicted using the miRanda tool. A differentially expressed circRNA-miRNA-mRNA (ceRNA) network was further constructed. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of the target mRNAs in the ceRNA network were performed to predict the potential functions of their host genes. The patient group and the control group were also compared on the regulatory patterns of circRNAs on mRNAs. 1934 circRNAs were identified from the samples and reported for the first time in schizophrenia. The circRNA expression levels were lower in the VEOS group than in the healthy control group, and 1889 circRNAs were expressed only in the control group. Differential expression analysis (i.e., log2fold change > 1.5, p 0.05) identified 235 circRNAs (1 up-regulated, 234 down-regulated), 11 miRNAs (7 up-regulated, 4 down-regulated), and 2,308 mRNAs (1906 up-regulated, 402 down-regulated) respectively. In VEOS, a ceRNA network with 10 down-regulated circRNA targets, 6 up-regulated miRNAs, and 47 down-regulated mRNAs was constructed. The target genes were involved in the membrane, the signal transduction, and the cytoskeleton and transport pathways. Finally, different expression correlation patterns of circRNA and mRNA in the network were observed between the patient group and the control group. The current research is the first to reveal the differentially expressed circRNAs in the plasma of VEOS patients. A circRNA-miRNA-mRNA network was also conducted in this study. It may be implied that the circRNAs in this network are potential diagnostic biomarkers for VEOS and they play an important role in the onset and development of VEOS symptoms.

G protein-coupled receptors in neurodegenerative diseases and psychiatric disorders

Neuropsychiatric disorders are multifactorial disorders with diverse aetiological factors. Identifying treatment targets is challenging because the diseases are resulting from heterogeneous biological, genetic, and environmental factors. Nevertheless, the increasing understanding of G protein-coupled receptor (GPCR) opens a new possibility in drug discovery. Harnessing our knowledge of molecular mechanisms and structural information of GPCRs will be advantageous for developing effective drugs. This review provides an overview of the role of GPCRs in various neurodegenerative and psychiatric diseases. Besides, we highlight the emerging opportunities of novel GPCR targets and address recent progress in GPCR drug development.

Dynamic network impairments underlie cognitive fluctuations in Lewy body dementia

Cognitive fluctuations are a characteristic and distressing disturbance of attention and consciousness seen in patients with Dementia with Lewy bodies and Parkinson's disease dementia. It has been proposed that fluctuations result from disruption of key neuromodulatory systems supporting states of attention and wakefulness which are normally characterised by temporally variable and highly integrated functional network architectures. In this study, patients with DLB (n = 25) and age-matched controls (n = 49) were assessed using dynamic resting state fMRI. A dynamic network signature of reduced temporal variability and integration was identified in DLB patients compared to controls. Reduced temporal variability correlated significantly with fluctuation-related measures using a sustained attention task. A less integrated (more segregated) functional network architecture was seen in DLB patients compared to the control group, with regions of reduced integration observed across dorsal and ventral attention, sensorimotor, visual, cingulo-opercular and cingulo-parietal networks. Reduced network integration correlated positively with subjective and objective measures of fluctuations. Regions of reduced integration and unstable regional assignments significantly matched areas of expression of specific classes of noradrenergic and cholinergic receptors across the cerebral cortex. Correlating topological measures with maps of neurotransmitter/neuromodulator receptor gene expression, we found that regions of reduced integration and unstable modular assignments correlated significantly with the pattern of expression of subclasses of noradrenergic and cholinergic receptors across the cerebral cortex. Altogether, these findings demonstrate that cognitive fluctuations are associated with an imaging signature of dynamic network impairment linked to specific neurotransmitters/neuromodulators within the ascending arousal system, highlighting novel potential diagnostic and therapeutic approaches for this troubling symptom.

A Novel 16-Genes Signature Scoring System as Prognostic Model to Evaluate Survival Risk in Patients with Glioblastoma

Previous studies have found that gene expression levels are associated with prognosis and some genes can be used to predict the survival risk of glioblastoma (GBM) patients. However, most of them just built the survival-related gene signature, and personal survival risk can be evaluated only in group. This study aimed to find the prognostic survival related genes of GBM, and construct survival risk prediction model, which can be used to evaluate survival risk by individual. We collected gene expression data and clinical information from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Cox regression analysis and LASSO-cox regression analysis were performed to get survival-related genes and establish the overall survival prediction model. The ROC curve and Kaplan Meier analysis were used to evaluate the prediction ability of the model in training set and two independent cohorts. We also analyzed the biological functions of survival-related genes by GO and KEGG enrichment analysis. We identified 99 genes associated with overall survival and selected 16 genes (IGFBP2, GPRASP1, C1R, CHRM3, CLSTN2, NELL1, SEZ6L2, NMB, ICAM5, HPCAL4, SNAP91, PCSK1N, PGBD5, INA, UCHL1 and LHX6) to establish the survival risk prediction model. Multivariate Cox regression analysis indicted that the risk score could predict overall survival independent of age and gender. ROC analyses showed that our model was more robust than four existing signatures. The sixteen genes can also be potential transcriptional biomarkers and the model can assist doctors on clinical decision-making and personalized treatment of GBM patients.

Integrative omics of schizophrenia: from genetic determinants to clinical classification and risk prediction

Schizophrenia (SCZ) is a debilitating neuropsychiatric disorder with high heritability and complex inheritance. In the past decade, successful identification of numerous susceptibility loci has provided useful insights into the molecular etiology of SCZ. However, applications of these findings to clinical classification and diagnosis, risk prediction, or intervention for SCZ have been limited, and elucidating the underlying genomic and molecular mechanisms of SCZ is still challenging. More recently, multiple Omics technologies - genomics, transcriptomics, epigenomics, proteomics, metabolomics, connectomics, and gut microbiomics - have all been applied to examine different aspects of SCZ pathogenesis. Integration of multi-Omics data has thus emerged as an approach to provide a more comprehensive view of biological complexity, which is vital to enable translation into assessments and interventions of clinical benefit to individuals with SCZ. In this review, we provide a broad survey of the single-omics studies of SCZ, summarize the advantages and challenges of different Omics technologies, and then focus on studies in which multiple omics data are integrated to unravel the complex pathophysiology of SCZ. We believe that integration of multi-Omics technologies would provide a roadmap to create a more comprehensive picture of interactions involved in the complex pathogenesis of SCZ, constitute a rich resource for elucidating the potential molecular mechanisms of the illness, and eventually improve clinical assessments and interventions of SCZ to address clinical translational questions from bench to bedside.

Shaping the Trans-Scale Properties of Schizophrenia via Cerebral Alterations on Magnetic Resonance Imaging and Single-Nucleotide Polymorphisms of Coding and Non-Coding Regions

Schizophrenia is a complex mental illness with genetic heterogeneity, which is often accompanied by alterations in brain structure and function. The neurobiological mechanism of schizophrenia associated with heredity remains unknown. Recently, the development of trans-scale and multi-omics methods that integrate gene and imaging information sheds new light on the nature of schizophrenia. In this article, we summarized the results of brain structural and functional changes related to the specific single-nucleotide polymorphisms (SNPs) in the past decade, and the SNPs were divided into non-coding regions and coding regions, respectively. It is hoped that the relationship between SNPs and cerebral alterations can be displayed more clearly and intuitively, so as to provide fresh approaches for the discovery of potential biomarkers and the development of clinical accurate individualized treatment decision-making.

Schizophrenia patients and their healthy siblings share decreased prefronto-thalamic connectivity but not increased sensorimotor-thalamic connectivity

The pattern of decreased prefronto-thalamic connectivity and increased sensorimotor-thalamic connectivity has been consistently documented in schizophrenia. However, whether this thalamo-cortical abnormality pattern is of genetic predisposition remains unknown. The present study for the first time aimed to investigate the common and distinct characteristics of this circuit in schizophrenia patients and their unaffected siblings who share half of the patient's genotype. Totally 293 participants were recruited into this study including 94 patients with schizophrenia, 96 their healthy siblings, and 103 healthy controls scanned using gradient-echo echo-planar imaging at rest. By using a fine-grained atlas of thalamus with 16 sub-regions, we mapped the thalamocortical network in three groups. Decreased thalamo-prefronto-cerebellar connectivity was shared between schizophrenia and their healthy siblings, but increased sensorimotor-thalamic connectivity was only found in schizophrenia. The shared thalamo-prefronto-cerebellar dysconnectivity showed an impressively gradient reduction pattern in patients and siblings comparing to controls: higher in the controls, lower in the patients and intermediate in the siblings. Anatomically, the decreased thalamic connectivity mostly centered on the pre-frontal thalamic subregions locating at the mediodorsal nucleus, while the increased functional connectivity with sensorimotor cortices was only observed in the caudal temporal thalamic subregion anchoring at the dorsal and ventral lateral nuclei. Moreover, both decreased thalamo-prefronto-cerebellar connectivity and increased sensorimotor-thalamic connectivity were related to clinical symptoms in patients. Our findings extend the evidence that the decreased thalamo-prefronto-cerebellar connectivity may be related to the high genetic risk in schizophrenia, while increased sensorimotor-thalamic connectivity potentially represents a neural biomarker for this severe mental disorder.

Integration of methylation QTL and enhancer-target gene maps with schizophrenia GWAS summary results identifies novel genes

MOTIVATION

Most trait-associated genetic variants identified in genome-wide association studies (GWASs) are located in non-coding regions of the genome and thought to act through their regulatory roles.

RESULTS

To account for enriched association signals in DNA regulatory elements, we propose a novel and general gene-based association testing strategy that integrates enhancer-target gene pairs and methylation quantitative trait locus data with GWAS summary results; it aims to both boost statistical power for new discoveries and enhance mechanistic interpretability of any new discovery. By reanalyzing two large-scale schizophrenia GWAS summary datasets, we demonstrate that the proposed method could identify some significant and novel genes (containing no genome-wide significant SNPs nearby) that would have been missed by other competing approaches, including the standard and some integrative gene-based association methods, such as one incorporating enhancer-target gene pairs and one integrating expression quantitative trait loci.

AVAILABILITY AND IMPLEMENTATION

Software: wuchong.org/egmethyl.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A regulatory variant of CHRM3 is associated with cannabis-induced hallucinations in European Americans

Cannabis, the most widely used illicit drug, can induce hallucinations. Our understanding of the biology of cannabis-induced hallucinations (Ca-HL) is limited. We used the Semi-Structured Assessment for Drug Dependence and Alcoholism (SSADDA) to identify cannabis-induced hallucinations (Ca-HL) among long-term cannabis users (used cannabis ≥1 year and ≥100 times). A genome-wide association study (GWAS) was conducted by analyzing European Americans (EAs) and African Americans (AAs) in Yale-Penn 1 and 2 cohorts individually, then meta-analyzing the two cohorts within population. In the meta-analysis of Yale-Penn EAs (n = 1917), one genome-wide significant (GWS) signal emerged at the CHRM3 locus, represented by rs115455482 (P = 1.66 × 10^-10), rs74722579 (P = 2.81 × 10^-9), and rs1938228 (P = 1.57 × 10^-8); signals were GWS in Yale-Penn 1 EAs (n = 1092) and nominally significant in Yale-Penn 2 EAs (n = 825). Two SNPs, rs115455482 and rs74722579, were available from the Collaborative Study on the Genetics of Alcoholism data (COGA; 3630 long-term cannabis users). The signals did not replicate, but when meta-analyzing Yale-Penn and COGA EAs, the two SNPs' association signals were increased (meta-P-values 1.32 × 10^-10 and 2.60 × 10^-9, respectively; n = 4291). There were no significant findings in AAs, but in the AA meta-analysis (n = 3624), nominal significance was seen for rs74722579. The rs115455482*T risk allele was associated with lower CHRM3 expression in the thalamus. CHRM3 was co-expressed with three psychosis risk genes (GABAG2, CHRNA4, and HRH3) in the thalamus and other human brain tissues and mouse GABAergic neurons. This work provides strong evidence for the association of CHRM3 with Ca-HL and provides insight into the potential involvement of thalamus for this trait.

Differences Between Schizophrenic and Normal Subjects Using Network Properties from fMRI

Schizophrenia has been proposed to result from impairment of functional connectivity. We aimed to use machine learning to distinguish schizophrenic subjects from normal controls using a publicly available functional MRI (fMRI) data set. Global and local parameters of functional connectivity were extracted for classification. We found decreased global and local network connectivity in subjects with schizophrenia, particularly in the anterior right cingulate cortex, the superior right temporal region, and the inferior left parietal region as compared to healthy subjects. Using support vector machine and 10-fold cross-validation, nine features reached 92.1% prediction accuracy, respectively. Our results suggest that there are significant differences between control and schizophrenic subjects based on regional brain activity detected with fMRI.

Salivary Flow Alteration in Patients Undergoing Treatment for Schizophrenia: Disease-Drug-Target Gene/Protein Association Study for Side-effects

BACKGROUND

Salivary flow alteration (SA), is a known unwarranted effect of schizophrenic medications. It manifest either as reduced (xerostomia) or increased (sialorrhea) SA, among treated schizophrenic patients. It is believed that the SA is due to action of the drugs/disease process involving the muscarinic receptor-3 to process acetyl choline, the common neurotransmitter. The genetic mediation behind the SA in such patients remains largely unexplored. We aimed to address the same by using curated literary databases to identify such relationship, if any existed.

MATERIAL AND METHODS

Curated databases of Gene-Disease Association, www.DisGeNet.org and www.networkanalyst.ca were effectively used to identify the probable genes, strength of association and the drug-genes pathway that could be possibly be involved. The genes associated with schizophrenia and SA were analyzed in detail. Protein-Protein interaction (PPI) network proven experimentally in humans were used to identify the missing or unreported links.

RESULTS

In all 28 genes associated with schizophrenia were linked to SA. The genetic network of schizophrenia and xerostomia involved FGFR2 gene prominently and network module was statistically significant (P = 9.87*10-8) was achieved that had xerostomia as a node, while schizophrenia (P = 0.025) had statistical significance. Sialorrhea had no statistical significance (P = 0.555). When schizophrenia and sialorrhea connections were analyzed for genetic interaction, only gene GCH1 emerged. On combining the three disease entities, the association of TAC1 gene with sialorrhea was also identified. Using PPI, the coordination of CHRM3, TAC1 and GPRASP1 gene were identified. This network involved several genes that has significant influence on calcium signaling pathway (P = 7.74*10-16), cholingeric synapse(P = 6 × 10-4), salivary secretion(P = 4.38*10-3), endocytosis(P = 8.23*10-4), TGFβ signaling pathway(P = 0.0031), gap junction (P = 4.08*10-3) and glutamergic synapse(P = 6.4*10-3). The involvement of G-receptor signaling protein product, GNAQ was established.

DISCUSSION AND CONCLUSION

The possible genetic pathway of SA in schizophrenic patients are discussed in light of pharmacotherapeutics. Using the knowledge effectively would help to increase the quality of life of schizophrenic besides increasing the understanding to use saliva as a biomarker of prognosis of schizophrenia and its drug effects.

Constitutional 763.3 Kb chromosome 1q43 duplication encompassing only CHRM3 gene identified by next generation sequencing (NGS) in a child with intellectual disability

Background

Deletion or duplication on the distal portion of the long arm of chromosome 1 result in complex and highly variable clinical phenotype including.

intellectual disability and autism.

Case presentation

We report on a patient with intellectual disability and a 763.3 Kb duplication on 1q43 that includes only CHRM3, which was detected by next generation sequencing (NGS). The patient presented with intellectual disability, developmental delay, autistic behavior, limited or no speech, social withdrawal, self-injurious, feeding difficulties, strabismus, short stature, hand anomalie, and no seizures, anxiety, or mood swings, and clinodactyly.

Conclusions

We propose that CHRM3 is the critical gene responsible for the common characteristics in the cases with 1q43 duplication and deletion.

Genome-wide association analysis reveals KCTD12 and miR-383-binding genes in the background of rumination

Ruminative response style is a passive and repetitive way of responding to stress, associated with several disorders. Although twin and candidate gene studies have proven the genetic underpinnings of rumination, no genome-wide association study (GWAS) has been conducted yet. We performed a GWAS on ruminative response style and its two subtypes, brooding and reflection, among 1758 European adults recruited in the general population of Budapest, Hungary, and Manchester, United Kingdom. We evaluated single-nucleotide polymorphism (SNP)-based, gene-based and gene set-based tests, together with inferences on genes regulated by our most significant SNPs. While no genome-wide significant hit emerged at the SNP level, the association of rumination survived correction for multiple testing with KCTD12 at the gene level, and with the set of genes binding miR-383 at the gene set level. SNP-level results were concordant between the Budapest and Manchester subsamples for all three rumination phenotypes. SNP-level results and their links to brain expression levels based on external databases supported the role of KCTD12, SRGAP3, and SETD5 in rumination, CDH12 in brooding, and DPYSL5, MAPRE3, KCNK3, ATXN7L3B, and TPH2 in reflection, among others. The relatively low sample size is a limitation of our study. Results of the first GWAS on rumination identified genes previously implicated in psychiatric disorders underscoring the transdiagnostic nature of rumination, and pointed to the possible role of the dorsolateral prefrontal cortex, hippocampus, and cerebellum in this cognitive process.

GWAS and systems biology analysis of depressive symptoms among smokers from the COPDGene cohort

BACKGROUND

Large sample GWAS is needed to identify genetic factors associated with depression. This study used genome-wide genotypic and phenotypic data from the COPDGene study to identify genetic risk factors for depression.

METHODS

Data were from 9716 COPDGene subjects with ≥10 pack-year history. Depression was defined as antidepressant use and/or a HADS depression subscale score ≥8. Non-Hispanic White (6576) and African-American (3140) subsets were analyzed. A GWAS pipeline identified SNPs associated with depression in each group. Network analysis software analyzed gene interactions through common biological pathways, genetic interactions, and tissue-specific gene expression.

RESULTS

The mean age was 59.4 years (SD 9.0) with 46.5% female subjects. Depression was in 24.7% of the NHW group (1622) and 12.5% of the AA group (391). No SNPs had genome-wide significance. One of the top SNPs, rs12036147 (p = 1.28 × 10^-6), is near CHRM3. Another SNP was near MDGA2 (rs17118176, p = 3.52 × 10^-6). Top genes formed networks for synaptic transmission with a statistically significant level of more co-expression in brain than other tissues, particularly in the basal ganglia (p = 1.00 × 10^-4).

LIMITATIONS

Limitations included a depression definition based on antidepressant use and a limited HADS score subgroup, which could increase false negatives in depressed patients not on antidepressants. Antidepressants used for smoking cessation in non-depressed patients could lead to false positives.

CONCLUSIONS

Systems biology analysis identified statistically significant pathways whereby multiple genes influence depression. The gene set pathway analysis and COPDGene data can help investigate depression in future studies.

The common variants implicated in microstructural abnormality of first episode and drug-naïve patients with schizophrenia

Both post-mortem and neuroimaging studies have identified abnormal white matter (WM) microstructure in patients with schizophrenia. However, its genetic underpinnings and relevant biological pathways remain unclear. In order to unravel the genes and the pathways associated with abnormal WM microstructure in schizophrenia, we recruited 100 first-episode, drug-naïve patients with schizophrenia and 140 matched healthy controls to conduct genome-wide association analysis of fractional anisotropy (FA) value measured using diffusing tensor imaging (DTI), followed by multivariate association study and pathway enrichment analysis. The results showed that one intergenic SNP (rs11901793), which is 20 kb upstream of CXCR7 gene on chromosome 2, was associated with the total mean FA values with genome-wide significance (p = 4.37 × 10⁻⁸), and multivariate association analysis identified a strong association between one region-specific SNP (rs10509852), 400 kb upstream of SORCS1 gene on chromosome 10, and the global trait of abnormal WM microstructure (p = 1.89 × 10⁻⁷). Furthermore, one pathway that is involved in cell cycle regulation, REACTOME_CHROMOSOME _MAINTENANCE, was significantly enriched by the genes that were identified in our study (p = 1.54 × 10⁻¹⁷). In summary, our study provides suggestive evidence that abnormal WM microstructure in schizophrenia is associated with genes that are likely involved in diverse biological signals and cell-cycle regulation although further replication in a larger independent sample is needed.