The impact of genome-wide supported schizophrenia risk variants in the neurogranin gene on brain structure and function

The gut microbiome is associated with brain structure and function in schizophrenia

The effect of the gut microbiome on the central nervous system and its possible role in mental disorders have received increasing attention. However, knowledge about the relationship between the gut microbiome and brain structure and function is still very limited. Here, we used 16S rRNA sequencing with structural magnetic resonance imaging (sMRI) and resting-state functional (rs-fMRI) to investigate differences in fecal microbiota between 38 patients with schizophrenia (SZ) and 38 demographically matched normal controls (NCs) and explored whether such differences were associated with brain structure and function. At the genus level, we found that the relative abundance of Ruminococcus and Roseburia was significantly lower, whereas the abundance of Veillonella was significantly higher in SZ patients than in NCs. Additionally, the analysis of MRI data revealed that several brain regions showed significantly lower gray matter volume (GMV) and regional homogeneity (ReHo) but significantly higher amplitude of low-frequency fluctuation in SZ patients than in NCs. Moreover, the alpha diversity of the gut microbiota showed a strong linear relationship with the values of both GMV and ReHo. In SZ patients, the ReHo indexes in the right STC (r = − 0.35, p = 0.031, FDR corrected p = 0.039), the left cuneus (r = − 0.33, p = 0.044, FDR corrected p = 0.053) and the right MTC (r = − 0.34, p = 0.03, FDR corrected p = 0.052) were negatively correlated with the abundance of the genus Roseburia. Our results suggest that the potential role of the gut microbiome in SZ is related to alterations in brain structure and function. This study provides insights into the underlying neuropathology of SZ.

Genes associated with gray matter volume alterations in schizophrenia

Although both schizophrenia and gray matter volume (GMV) show high heritability, however, genes accounting for GMV alterations in schizophrenia remain largely unknown. Based on risk genes identified in schizophrenia by the genome-wide association study of the Schizophrenia Working Group of the Psychiatric Genomics Consortium, we used transcription-neuroimaging association analysis to test that which of these genes are associated with GMV changes in schizophrenia. For each brain tissue sample, the expression profiles of 196 schizophrenia risk genes were extracted from six donated normal brains of the Allen Human Brain Atlas, and GMV differences between patients with schizophrenia and healthy controls were calculated based on five independent case-control structural MRI datasets (276 patients and 284 controls). Genes associated with GMV changes in schizophrenia were identified by performing cross-sample spatial correlations between expression levels of each gene and case-control GMV difference derived from the five MRI datasets integrated by harmonization and meta-analysis. We found that expression levels of 98 genes consistently showed significant cross-sample spatial correlations with GMV changes in schizophrenia. These genes were functionally enriched for chemical synaptic transmission, central nervous system development, and cell projection. Overall, this study provides a set of genes possibly associated with GMV changes in schizophrenia, which could be used as candidate genes to explore biological mechanisms underlying the structural impairments in schizophrenia.

Psychotic symptoms are associated with lower cortical folding in youth at risk for mental illness

BACKGROUND

Cortical folding is essential for healthy brain development. Previous studies have found regional reductions in cortical folding in adult patients with psychotic illness. It is unknown whether these neuroanatomical markers are present in youth with subclinical psychotic symptoms.

METHODS

We collected MRIs and examined the local gyrification index in a sample of 110 youth (mean age ± standard deviation 14.0 ± 3.7 yr; range 9–25 yr) with a family history of severe mental illness: 48 with psychotic symptoms and 62 without. Images were processed using the Human Connectome Pipeline and FreeSurfer. We tested for group differences in local gyrification index using mixed-effects generalized linear models controlling for age, sex and familial clustering. Sensitivity analysis further controlled for intracranial volume, IQ, and stimulant and cannabis use.

RESULTS

Youth with psychotic symptoms displayed an overall trend toward lower cortical folding across all brain regions. After adjusting for multiple comparisons and confounders, regional reductions were localized to the frontal and occipital lobes. Specifically, the medial (B = –0.42, pFDR = 0.04) and lateral (B = –0.39, pFDR = 0.04) orbitofrontal cortices as well as the cuneus (B = –0.47, pFDR = 0.03) and the pericalcarine (B = –0.45, pFDR = 0.03) and lingual (B = –0.38, pFDR = 0.04) gyri.

LIMITATIONS

Inference about developmental trajectories was limited by the cross-sectional data.

CONCLUSION

Psychotic symptoms in youth are associated with cortical folding deficits, even in the absence of psychotic illness. The current study helps clarify the neurodevelopmental basis of psychosis at an early stage, before medication, drug use and other confounds have had a persistent effect on the brain.

Non-Coding RNAs in Psychiatric Disorders and Suicidal Behavior

It is well known that only a small proportion of the human genome code for proteins; the rest belong to the family of RNAs that do not code for protein and are known as non-coding RNAs (ncRNAs). ncRNAs are further divided into two subclasses based on size: 1) long non-coding RNAs (lncRNAs; >200 nucleotides) and 2) small RNAs (<200 nucleotides). Small RNAs contain various family members that include microRNAs (miRNAs), small interfering RNAs (siRNAs), piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), and small nuclear RNAs (snRNAs). The roles of ncRNAs, especially lncRNAs and miRNAs, are well documented in brain development, homeostasis, stress responses, and neural plasticity. It has also been reported that ncRNAs can influence the development of psychiatric disorders including schizophrenia, major depressive disorder, and bipolar disorder. More recently, their roles are being investigated in suicidal behavior. In this article, we have comprehensively reviewed the findings of lncRNA and miRNA expression changes and their functions in various psychiatric disorders including suicidal behavior. We primarily focused on studies that have been done in postmortem human brain. In addition, we have briefly reviewed the role of other small RNAs (e.g. piwiRNA, siRNA, snRNA, and snoRNAs) and their expression changes in psychiatric illnesses.

The association between rs12807809 polymorphism in neurogranin gene and risk of schizophrenia: A meta-analysis

BACKGROUND

The correlation between single nucleotide polymorphism (SNP) rs12807809 in Neurogranin (NRGN) gene and Schizophrenia (SCZ) was investigated by several studies, whereas the results were conflicting. Thus, we performed the present meta-analysis to combine and analyze the available studies in order to provide a more accurate result on the association of rs12807809 polymorphism in NRGN gene and SCZ vulnerability.

METHODS

A comprehensive retrieval in PubMed, EMBASE, Web of Science, Cochrane Library and Wanfang was performed for relevant studies on the relationship of rs12807809 polymorphism and SCZ. Summary odds ratios (OR) with 95% confidence interval (95% CI) were calculated in allelic, homozygous, heterozygous, dominant and recessive model to appraise the association.

RESULTS

The meta-analysis included 8 studies containing 12552 SCZ cases and 34783 controls. The results showed a statistically significant correlation between SCZ and rs12807809 polymorphism in overall population in allelic model (OR = 1.10, 95%CI 1.04-1.17). However, subgroup analysis indicated the association only existed in Caucasians but not Asian.

CONCLUSION

The results of present meta-analysis suggested significant association between SNP rs12807809 in NRGN gene and SCZ susceptibility in Caucasians but not Asians.

Unravelling the genetic basis of schizophrenia and bipolar disorder with GWAS: A systematic review

OBJECTIVES

To systematically review findings of GWAS in schizophrenia (SZ) and in bipolar disorder (BD); and to interpret findings, with a focus on identifying independent replications.

METHOD

PubMed search, selection and review of all independent GWAS in SZ or BD, published since March 2011, i.e. studies using non-overlapping samples within each article, between articles, and with those of the previous review (Li et al., 2012).

RESULTS

From the 22 GWAS included in this review, the genetic associations surviving standard GWAS-significance were for genetic markers in the regions of ACSL3/KCNE4, ADCY2, AMBRA1, ANK3, BRP44, DTL, FBLN1, HHAT, INTS7, LOC392301, LOC645434/NMBR, LOC729457, LRRFIP1, LSM1, MDM1, MHC, MIR2113/POU3F2, NDST3, NKAPL, ODZ4, PGBD1, RENBP, TRANK1, TSPAN18, TWIST2, UGT1A1/HJURP, WHSC1L1/FGFR1 and ZKSCAN4. All genes implicated across both reviews are discussed in terms of their function and implication in neuropsychiatry.

CONCLUSION

Taking all GWAS to date into account, AMBRA1, ANK3, ARNTL, CDH13, EFHD1 (albeit with different alleles), MHC, PLXNA2 and UGT1A1 have been implicated in either disorder in at least two reportedly non-overlapping samples. Additionally, evidence for a SZ/BD common genetic basis is most strongly supported by the implication of ANK3, NDST3, and PLXNA2.

Association between NRGN gene polymorphism and resting-state hippocampal functional connectivity in schizophrenia

BACKGROUND

Based on genome-wide association studies, a single-nucleotide polymorphism in the NRGN gene (rs12807809) is considered associated with schizophrenia (SZ). Moreover, hippocampal dysfunction is associated with rs12807809. In addition, converging evidence suggests that hippocampal dysfunction is involved in SZ pathophysiology. However, the association among rs12807809, hippocampal dysfunction and SZ pathophysiology is unknown. Therefore, this study investigated the association between rs12807809 and hippocampal functional connectivity at rest in SZ.

METHODS

In total, 158 participants were studied, including a C-carrier group carrying the non-risk C allele (29 SZ patients and 46 healthy controls) and a TT homozygous group carrying the risk T allele (30 SZ patients and 53 healthy controls). All participants were scanned using resting-state functional magnetic resonance imaging. Hippocampal functional connectivity was computed and compared among the 4 groups.

RESULTS

Significant main effects of diagnosis were observed in the functional connectivity between the hippocampus and bilateral fusiform gyrus, bilateral lingual gyrus, left inferior temporal gyrus, left caudate nucleus, bilateral thalamus and bilateral anterior cingulate gyri. In contrast, no significant main effect of genotype was found. In addition, a significant genotype by diagnosis interaction in the functional connectivity between the hippocampus and left anterior cingulate gyrus, as well as bilateral middle cingulate gyri, was observed, with TT homozygotes with SZ showing less functional connectivity than C-carriers with SZ and healthy control TT homozygotes.

CONCLUSIONS

These findings are the first to suggest an association between rs12807809 and abnormal Papez circuit function in patients with SZ. This study also implicates NRGN variation and abnormal Papez circuit function in SZ pathophysiology.

Neurogranin regulates sensorimotor gating through cortico-striatal circuitry

Glutamate dysregulation is known to contribute to many psychiatric disorders including schizophrenia. Aberrant cortico-striatal activity and therefore glutamate levels might be relevant to this disease characterized by reduced prepulse inhibition (PPI), however, the molecular and behavioral mechanism of the pathophysiology of schizophrenia remains unclear. The focus of this study was to contribute to the current understanding of the glutamate and neurogranin (Ng) pathway, in relation to the cortico-striatal pathology of schizophrenia using a mouse model. A variant of the Ng gene has been detected in people with schizophrenia, implicating maladaptation of cortical glutamate signaling and sensorimotor gating. To test Ng-mediated PPI regulation in the mouse model, we utilized Ng null mice, viral-mediated Ng expression, and genetics approaches. Our results demonstrate that lack of Ng in mice decreases PPI. Ng over-expression in the prefrontal cortex (PFC) increases PPI, while Ng expression in either the nucleus accumbens (NAc) or hippocampus induces no change in PPI. Using optogenetics and chemogenetics, we identified that cortico-striatal activation is involved in PPI regulation. Finally, pharmacological regulation of Ng using glutamate receptor inhibitors demonstrated altered PPI between genotypes. In this study, we have investigated the impact of Ng expression on sensorimotor gating. This study contributes to a better understanding of the glutamatergic theory of schizophrenia, opening novel therapeutic avenues that may lead to glutamatergic treatments to ameliorate the symptoms of schizophrenia.

Non-coding RNA dysregulation in the amygdala region of schizophrenia patients contributes to the pathogenesis of the disease

Schizophrenia (SCZ) is a neuropsychiatric disorder with a complex genetic etiology. The redundancy of the gene networks underlying SCZ indicates that many gene combinations have the potential to cause a system dysfunction that can manifest as SCZ or a related neurodevelopmental disorder. Recent studies show that small non-coding microRNA (miRNA) and long non-coding RNA (lncRNA) are important factors in shaping these networks and are dynamically regulated by neuronal activation. We investigated the genome-wide transcription profiles of 46 human amygdala samples obtained from 22 SCZ patients and 24 healthy controls. Using RNA sequencing (RNA-seq), we determined lncRNA expression levels in all samples and generated miRNA profiles for 27 individuals (13 cases and 14 controls). Previous studies have identified differentially expressed miRNAs in SCZ, including miR-132, miR-212, and miR-34a/miR-34c. Here we report differential expression of a novel miRNA, miR1307, in SCZ. Notably, miR1307 maps to a locus previously associated with SCZ through GWAS. Additionally, one lncRNA that was overexpressed in SCZ, AC005009.2, also maps to a region previously associated with SCZ based on GWAS and overlapped SCZ-related genes. The results were replicated in a large independent data set of 254 dorsolateral prefrontal cortex samples from the CommonMind consortium. Taken together, these results suggest that miRNA and lncRNAs are important contributors to the pathogenesis of SCZ.

Minor allele C of rs12807809 polymorphism in NRGN contributes to the severity of psychosis in patients with Schizophrenia in South Indian population

Schizophrenia (SCZ) as a severe and complex neuropsychiatric disorder and is characterized by positive symptoms, negative symptoms and cognitive dysfunctions. Genome-wide association studies (GWAS) have identified a strong association between the single nucleotide polymorphism (SNP) rs12807809 upstream of Neurogranin (NRGN) in a European population. This evidence prompted us to conduct an association study among 1005 schizophrenia cases and 1069 controls in a South Indian Population using TaqMan Allelic discrimination method. We observed an association of rs12807809 with SCZ in this study population. Allele frequencies and genotype frequencies of rs12807809 showed significant differences between cases and control subjects [p=0.0019; OR=0.69; 95% CI=(0.55-0.87)] and (p=0.0062). Further Genotype-Phenotype correlation revealed a moderate association of rs12807809 with flat affect (p=0.039) and Hallucinations (p=0.012). The ancestral non-risk C allele contributes to the severity of psychosis (p=0.039) in this population.

Adaptive testing for multiple traits in a proportional odds model with applications to detect SNP-brain network associations

There has been increasing interest in developing more powerful and flexible statistical tests to detect genetic associations with multiple traits, as arising from neuroimaging genetic studies. Most of existing methods treat a single trait or multiple traits as response while treating an SNP as a predictor coded under an additive inheritance mode. In this paper, we follow an earlier approach in treating an SNP as an ordinal response while treating traits as predictors in a proportional odds model (POM). In this way, it is not only easier to handle mixed types of traits, e.g., some quantitative and some binary, but it is also potentially more robust to the commonly adopted additive inheritance mode. More importantly, we develop an adaptive test in a POM so that it can maintain high power across many possible situations. Compared to the existing methods treating multiple traits as responses, e.g., in a generalized estimating equation (GEE) approach, the proposed method can be applied to a high dimensional setting where the number of phenotypes (p) can be larger than the sample size (n), in addition to a usual small P setting. The promising performance of the proposed method was demonstrated with applications to the Alzheimer's Disease Neuroimaging Initiative (ADNI) data, in which either structural MRI driven phenotypes or resting-state functional MRI (rs-fMRI) derived brain functional connectivity measures were used as phenotypes. The applications led to the identification of several top SNPs of biological interest. Furthermore, simulation studies showed competitive performance of the new method, especially for p>n.

Association of CACNA1C and SYNE1 in offspring of patients with psychiatric disorders

Schizophrenia (SZ) and bipolar disorder (BD) are severe mental diseases associated with cognitive impairment, mood disturbance, and psychosis. Both disorders are highly heritable and share a common genetic background. The present study assesses, for the first time, differences in genotype frequencies of polymorphisms located in genes involved in neurodevelopment and synaptic plasticity between genetic high-risk individuals (offspring of patients with SZ or BD; N=100: 31 and 69, respectively) and control subjects (offspring of community controls; N=96). Individuals from both groups had similar ages, around 12 years. A higher percentage of men were included in the genetic high-risk group (58%) compared with the control group (40.6%). A total of 244 validated SNPs located in 35 candidate gene regions were analyzed in 196 participants. Multivariate methods based on logistic regression analysis were performed to assess differences in genotype frequencies. Bonferroni correction was applied for the multiple comparisons performed. Two polymorphisms, CACNA1C rs10848683 and SYNE1 rs214950, showed significant differences. The frequency of heterozygotes for CACNA1C rs10848683 in genetic high-risk individuals was double that in controls (OR=3.15; P=0.00016). For SYNE1 rs214950, higher frequencies of heterozygotes (OR=1.97) and homozygotes for the minor allele (OR=17.89; P=0.00020) were found in the genetic high-risk group than in the control group. In conclusion, polymorphisms in CACNA1C and SYNE1 could confer a greater risk of developing SZ and BD in individuals who are already at high risk because of their family history. This could help identify subjects with a very high genetic risk, in whom early detection and early intervention could lead to better prognosis.

Biomarkers for drug development in early psychosis: Current issues and promising directions

A major goal of current research in schizophrenia is to understand the biology underlying onset and early progression and to develop interventions that modify these processes. Biomarkers can play a critical role in identifying disease state, factors contributing to underlying progression, as well as predicting and monitoring response to treatment. Once biomarker-based therapeutics are established, biomarkers can guide treatment selection. It is increasingly clear that a wide range of potential biomarkers should be examined in schizophrenia, given the large number of genetic and environmental factors that have been identified as risk factors. New models for analysis of biomarkers are needed that represent the central nervous system as a highly complex, dynamic, and interactive system. Many tools are available with which to study relevant brain chemistry, but most are indirect measures and represent only a small fraction of the potential etiologic factors contributing to the molecular, structural and functional components of schizophrenia. This review represents the work of the International Society for CNS Clinical Trials and Methodology (ISCTM) Biomarkers Working Group. It discusses advantages and disadvantages of different categories of biomarkers and provides a summary of evidence that biomarkers representing inflammation, oxidative stress, endocannabinoids, glucocorticoid, and biogenic amines systems are dysregulated and potentially interactive in early phase schizophrenia. As has been recently demonstrated in several neurodevelopmental and neurodegenerative disorders, a multi-modal, longitudinal strategy involving a diverse array of biomarkers and new approaches to statistical modeling are needed to improve early interventions based on the fuller understanding.

Imaging genetics and psychiatric disorders

Imaging genetics is an integrated research method that uses neuroimaging and genetics to assess the impact of genetic variation on brain function and structure. Imaging genetics is both a tool for the discovery of risk genes for psychiatric disorders and a strategy for characterizing the neural systems affected by risk gene variants to elucidate quantitative and mechanistic aspects of brain function implicated in psychiatric disease. Early studies of imaging genetics included association analyses between brain morphology and single nucleotide polymorphisms whose function is well known, such as catechol-Omethyltransferase (COMT) and brain-derived neurotrophic factor (BDNF). GWAS of psychiatric disorders have identified genes with unknown functions, such as ZNF804A, and imaging genetics has been used to investigate clues of the biological function of these genes. The difficulty in replicating the findings of studies with small sample sizes has motivated the creation of largescale collaborative consortiums, such as ENIGMA, CHARGE and IMAGEN, to collect thousands of images. In a genome-wide association study, the ENIGMA consortium successfully identified common variants in the genome associated with hippocampal volume at 12q24, and the CHARGE consortium replicated this finding. The new era of imaging genetics has just begun, and the next challenge we face is the discovery of small effect size signals from large data sets obtained from genetics and neuroimaging. New methods and technologies for data reduction with appropriate statistical thresholds, such as polygenic analysis and parallel independent component analysis (ICA), are warranted. Future advances in imaging genetics will aid in the discovery of genes and provide mechanistic insight into psychiatric disorders.

Substantial DNA methylation differences between two major neuronal subtypes in human brain

The brain is built from a large number of cell types which have been historically classified using location, morphology and molecular markers. Recent research suggests an important role of epigenetics in shaping and maintaining cell identity in the brain. To elucidate the role of DNA methylation in neuronal differentiation, we developed a new protocol for separation of nuclei from the two major populations of human prefrontal cortex neurons—GABAergic interneurons and glutamatergic (GLU) projection neurons. Major differences between the neuronal subtypes were revealed in CpG, non-CpG and hydroxymethylation (hCpG). A dramatically greater number of undermethylated CpG sites in GLU versus GABA neurons were identified. These differences did not directly translate into differences in gene expression and did not stem from the differences in hCpG methylation, as more hCpG methylation was detected in GLU versus GABA neurons. Notably, a comparable number of undermethylated non-CpG sites were identified in GLU and GABA neurons, and non-CpG methylation was a better predictor of subtype-specific gene expression compared to CpG methylation. Regions that are differentially methylated in GABA and GLU neurons were significantly enriched for schizophrenia risk loci. Collectively, our findings suggest that functional differences between neuronal subtypes are linked to their epigenetic specification.

Brain structure and function correlates of cognitive subtypes in schizophrenia

Stable neuropsychological deficits may provide a reliable basis for identifying etiological subtypes of schizophrenia. The aim of this study was to identify clusters of individuals with schizophrenia based on dimensions of neuropsychological performance, and to characterize their neural correlates. We acquired neuropsychological data as well as structural and functional magnetic resonance imaging from 129 patients with schizophrenia and 165 healthy controls. We derived eight cognitive dimensions and subsequently applied a cluster analysis to identify possible schizophrenia subtypes. Analyses suggested the following four cognitive clusters of schizophrenia: (1) Diminished Verbal Fluency, (2) Diminished Verbal Memory and Poor Motor Control, (3) Diminished Face Memory and Slowed Processing, and (4) Diminished Intellectual Function. The clusters were characterized by a specific pattern of structural brain changes in areas such as Wernicke's area, lingual gyrus and occipital face area, and hippocampus as well as differences in working memory-elicited neural activity in several fronto-parietal brain regions. Separable measures of cognitive function appear to provide a method for deriving cognitive subtypes meaningfully related to brain structure and function. Because the present study identified brain-based neural correlates of the cognitive clusters, the proposed groups of individuals with schizophrenia have some external validity.

Patterns of cortical thinning in different subgroups of schizophrenia

BACKGROUND

Alterations of cortical thickness have been shown in imaging studies of schizophrenia but it is unclear to what extent they are related to disease phenotype (including symptom profile) or other aspects such as genetic liability, disease onset and disease progression.

AIMS

To test the hypothesis that cortical thinning would vary across different subgroups of patients with chronic schizophrenia, delineated according to their symptom profiles.

METHOD

We compared high-resolution magnetic resonance imaging data of 87 patients with DSM-IV schizophrenia with 108 controls to detect changes in cortical thickness across the entire brain (P<0.05, false discovery rate-adjusted). The patient group was divided into three subgroups, consisting of patients with predominantly negative, disorganised or paranoid symptoms.

RESULTS

The negative symptoms subgroup showed the most extensive cortical thinning, whereas thinning in the other subgroups was focused in prefrontal and temporal cortical subregions.

CONCLUSIONS

Our findings support growing evidence of potential subtypes of schizophrenia that have different brain structural deficit profiles.

Neurogranin binds α-synuclein in the human superior temporal cortex and interaction is decreased in Parkinson's disease

Neurogranin is a calmodulin binding protein that has been implicated in learning and memory, long-term potentiation and synaptic plasticity. Neurons expressing neurogranin in the cortex degenerate in late stages of Parkinson's disease with widespread α-synuclein pathology. While analyzing neurogranin gene expression levels through rtPCR in brains of mouse models overexpressing human α-synuclein, we found levels were elevated 2.5 times when compared to nontransgenic animals. Immunohistochemistry in the cortex revealed colocalization between α-synuclein and neurogranin in mouse transgenics when compared to control mice. Coimmunoprecipitation studies in the superior temporal cortex in humans confirmed interaction between α-synuclein and neurogranin, and decreased interaction between α-synuclein and neurogranin was noticed in patients diagnosed with Parkinson's disease when compared to normal control brains. Additionally, phosphorylated neurogranin levels were also decreased in the human superior temporal cortex in patients diagnosed with Parkinson's disease and patients diagnosed with dementia with Lewy bodies. Here, we show for the first time that neurogranin binds to α-synuclein in the human cortex, and this interaction decreases in Parkinson's disease along with the phosphorylation of neurogranin, a molecular process thought to be involved in learning and memory.