Cross-Tissue Exploration of Genetic and Epigenetic Effects on Brain Gray Matter in Schizophrenia

Association between the oral microbiome and brain resting state connectivity in schizophrenia

Recent microbiome-brain axis findings have shown evidence of the modulation of microbiome community as an environmental mediator in brain function and psychiatric illness. This work is focused on the role of the microbiome in understanding a rarely investigated environmental involvement in schizophrenia (SZ), especially in relation to brain circuit dysfunction. We leveraged high throughput microbial 16s rRNA sequencing and functional neuroimaging techniques to enable the delineation of microbiome-brain network links in SZ. N = 213 SZ and healthy control subjects were assessed for the oral microbiome. Among them, 139 subjects were scanned by resting-state functional magnetic resonance imaging (rsfMRI) to derive brain functional connectivity. We found a significant microbiome compositional shift in SZ beta diversity (weighted UniFrac distance, p = 6 × 10-3; Bray-Curtis distance p = 0.021). Fourteen microbial species involving pro-inflammatory and neurotransmitter signaling and H2S production, showed significant abundance alterations in SZ. Multivariate analysis revealed one pair of microbial and functional connectivity components showing a significant correlation of 0.46. Thirty five percent of microbial species and 87.8 % of brain functional network connectivity from each component also showed significant differences between SZ and healthy controls with strong performance in classifying SZ from healthy controls, with an area under curve (AUC) = 0.84 and 0.87, respectively. The results suggest a potential link between oral microbiome dysbiosis and brain functional connectivity alteration in relation to SZ, possibly through immunological and neurotransmitter signaling pathways and the hypothalamic-pituitary-adrenal axis, supporting for future work in characterizing the role of oral microbiome in mediating effects on SZ brain functional activity.

Molecular Regulation of Fetal Brain Development in Inbred and Congenic Mouse Strains Differing in Longevity

The objective of this study was to investigate gene regulation of the developing fetal brain from congenic or inbred mice strains that differed in longevity. Gene expression and alternative splice variants were analyzed in a genome-wide manner in the fetal brain of C57BL/6J mice (long-lived) in comparison to B6.Cg-Cav1tm1Mls/J (congenic, short-lived) and AKR/J (inbred, short-lived) mice on day(d) 12, 15, and 17 of gestation. The analysis showed a contrasting gene expression pattern during fetal brain development in these mice. Genes related to brain development, aging, and the regulation of alternative splicing were significantly differentially regulated in the fetal brain of the short-lived compared to long-lived mice during development from d15 and d17. A significantly reduced number of splice variants was observed on d15 compared to d12 or d17 in a strain-dependent manner. An epigenetic clock analysis of d15 fetal brain identified DNA methylations that were significantly associated with single-nucleotide polymorphic sites between AKR/J and C57BL/6J strains. These methylations were associated with genes that show epigenetic changes in an age-correlated manner in mice. Together, the finding of this study suggest that fetal brain development and longevity are epigenetically linked, supporting the emerging concept of the early-life origin of longevity.

Links among genetic variants and hierarchical brain structural and functional networks for antidepressant treatment: A multivariate study

BACKGROUND

Antidepressant treatment effects are strongly heritable and have substantial effects on brain function and structure, but the underlying mechanisms are still poorly understood. In this research, we aimed to evaluate the factors of single nucleotide polymorphisms (SNPs) and hierarchical brain structural and functional networks that were associated with antidepressant treatment. Moreover, we further explored the correlations and mediation pattern among "brain structure-brain function-gene" in major depressive disorder (MDD).

METHODS

We analysed 405 SNPs and rich club/feeder/local connections of hierarchical structural and functional networks with three-way parallel independent component analysis in 179 MDD patients. The group-discriminative independent components of the three modalities between responders and non-responders of antidepressant treatment were identified. Pearson correlations and mediation analysis were further utilized to investigate the associations among SNPs and connections of the structural and functional networks.

RESULTS

Notably, correlations with antidepressant treatment outcomes were found in structural, functional and SNP modalities simultaneously. The features of group-discriminative independent components included the shared feeder connections of hub regions with the inferior frontal orbital gyrus and amygdala in structural and functional modalities and genes enriched in circadian rhythmic processes and dopaminergic synapse pathways. The structural feeder network displayed close correlations with SNPs and the functional feeder network. Furthermore, the structural feeder network could mediate the association between SNPs and the functional feeder network, implying that genetic variants might influence brain function by affecting brain structure in MDD.

CONCLUSIONS

These findings provide potential biomarkers for antidepressant therapy and provide a better grasp of the associations among SNPs and hierarchical structural and functional networks in MDD.

Epigenetic regulation of fetal brain development in pig

How fetal brain development is regulated at the molecular level is not well understood. Due to ethical challenges associated with research on the human fetus, large animals particularly pigs are increasingly used to study development and disorders of fetal brain. The pig fetal brain grows rapidly during the last ∼ 50 days before birth which is around day 60 (d60) of pig gestation. But what regulates the onset of accelerated growth of the brain is unknown. The current study tests the hypothesis that epigenetic alteration around d60 is involved in the onset of rapid growth of fetal brain of pig. To test this hypothesis, DNA methylation changes of fetal brain was assessed in a genome-wide manner by Enzymatic Methyl-seq (EM-seq) during two gestational periods (GP): d45 vs. d60 (GP1) and d60 vs. d90 (GP2). The cytosine-guanine (CpG) methylation data was analyzed in an integrative manner with the RNA-seq data generated from the same brain samples from our earlier study. A neural network based modeling approach was implemented to learn changes in methylation patterns of the differentially expressed genes, and then predict methylations of the brain in a genome-wide manner during rapid growth. This approach identified specific methylations that changed in a mutually informative manner during rapid growth of the fetal brain. These methylations were significantly overrepresented in specific genic as well as intergenic features including CpG islands, introns, and untranslated regions. In addition, sex-bias methylations of known single nucleotide polymorphic sites were also identified in the fetal brain ide during rapid growth.

DNA methylation under the major depression pathway predicts pediatric quality of life four-month post-pediatric mild traumatic brain injury

BACKGROUND

Major depression has been recognized as the most commonly diagnosed psychiatric complication of mild traumatic brain injury (mTBI). Moreover, major depression is associated with poor outcomes following mTBI; however, the underlying biological mechanisms of this are largely unknown. Recently, genomic and epigenetic factors have been increasingly implicated in the recovery following TBI.

RESULTS

This study leveraged DNA methylation within the major depression pathway, along with demographic and behavior measures (features used in the clinical model) to predict post-concussive symptom burden and quality of life four-month post-injury in a cohort of 110 pediatric mTBI patients and 87 age-matched healthy controls. The results demonstrated that including DNA methylation markers in the major depression pathway improved the prediction accuracy for quality of life but not persistent post-concussive symptom burden. Specifically, the prediction accuracy (i.e., the correlation between the predicted value and observed value) of quality of life was improved from 0.59 (p = 1.20 × 10^-3) (clinical model) to 0.71 (p = 3.89 × 10^-5); the identified cytosine-phosphate-guanine sites were mainly in the open sea regions and the mapped genes were related to TBI in several molecular studies. Moreover, depression symptoms were a strong predictor (with large weights) for both post-concussive symptom burden and pediatric quality of life.

CONCLUSION

This study emphasized that both molecular and behavioral manifestations of depression symptoms played a prominent role in predicting the recovery process following pediatric mTBI, suggesting the urgent need to further study TBI-caused depression symptoms for better recovery outcome.

Differential DNA Methylation Is Associated With Hippocampal Abnormalities in Pediatric Posttraumatic Stress Disorder

BACKGROUND

Recent findings in neuroimaging and epigenetics offer important insights into brain structures and biological pathways of altered gene expression associated with posttraumatic stress disorder (PTSD). However, it is unknown to what extent epigenetic mechanisms are associated with PTSD and its neurobiology in youth.

METHODS

In this study, we combined a methylome-wide association study and structural neuroimaging measures in a Dutch cohort of youths with PTSD (8-18 years of age). We aimed to replicate findings in a similar independent U.S. cohort.

RESULTS

We found significant methylome-wide associations for pediatric PTSD (false discovery rate p < .05) compared with non-PTSD control groups (traumatized and nontraumatized youths). Methylation differences on nine genes were replicated, including genes related to glucocorticoid functioning. In both cohorts, methylation on OLFM3 gene was further associated with anterior hippocampal volume.

CONCLUSIONS

These findings point to molecular pathways involved in inflammation, stress response, and neuroplasticity as potential contributors to neural abnormalities and provide potentially unique biomarkers and treatment targets for pediatric PTSD.

Sparse deep neural networks on imaging genetics for schizophrenia case-control classification

Deep learning methods hold strong promise for identifying biomarkers for clinical application. However, current approaches for psychiatric classification or prediction do not allow direct interpretation of original features. In the present study, we introduce a sparse deep neural network (DNN) approach to identify sparse and interpretable features for schizophrenia (SZ) case–control classification. An L₀‐norm regularization is implemented on the input layer of the network for sparse feature selection, which can later be interpreted based on importance weights. We applied the proposed approach on a large multi‐study cohort with gray matter volume (GMV) and single nucleotide polymorphism (SNP) data for SZ classification. A total of 634 individuals served as training samples, and the classification model was evaluated for generalizability on three independent datasets of different scanning protocols (N = 394, 255, and 160, respectively). We examined the classification power of pure GMV features, as well as combined GMV and SNP features. Empirical experiments demonstrated that sparse DNN slightly outperformed independent component analysis + support vector machine (ICA + SVM) framework, and more effectively fused GMV and SNP features for SZ discrimination, with an average error rate of 28.98% on external data. The importance weights suggested that the DNN model prioritized to select frontal and superior temporal gyrus for SZ classification with high sparsity, with parietal regions further included with lower sparsity, echoing previous literature. The results validate the application of the proposed approach to SZ classification, and promise extended utility on other data modalities and traits which ultimately may result in clinically useful tools.

Epigenome-wide meta-analysis of blood DNA methylation and its association with subcortical volumes: findings from the ENIGMA Epigenetics Working Group

DNA methylation, which is modulated by both genetic factors and environmental exposures, may offer a unique opportunity to discover novel biomarkers of disease-related brain phenotypes, even when measured in other tissues than brain, such as blood. A few studies of small sample sizes have revealed associations between blood DNA methylation and neuropsychopathology, however, large-scale epigenome-wide association studies (EWAS) are needed to investigate the utility of DNA methylation profiling as a peripheral marker for the brain. Here, in an analysis of eleven international cohorts, totalling 3337 individuals, we report epigenome-wide meta-analyses of blood DNA methylation with volumes of the hippocampus, thalamus and nucleus accumbens (NAcc)-three subcortical regions selected for their associations with disease and heritability and volumetric variability. Analyses of individual CpGs revealed genome-wide significant associations with hippocampal volume at two loci. No significant associations were found for analyses of thalamus and nucleus accumbens volumes. Cluster-based analyses revealed additional differentially methylated regions (DMRs) associated with hippocampal volume. DNA methylation at these loci affected expression of proximal genes involved in learning and memory, stem cell maintenance and differentiation, fatty acid metabolism and type-2 diabetes. These DNA methylation marks, their interaction with genetic variants and their impact on gene expression offer new insights into the relationship between epigenetic variation and brain structure and may provide the basis for biomarker discovery in neurodegeneration and neuropsychiatric conditions.

Clinical Correlates of the NR3C1 Gene Methylation at Various Stages of Psychosis

BACKGROUND

Dysregulation of epigenetic processes might account for alterations of the hypothalamic-pituitary-adrenal axis observed in patients with schizophrenia. Therefore, in this study, we aimed to investigate methylation of the glucocorticoid receptor (NR3C1) gene in patients with schizophrenia-spectrum disorders, individuals at familial high risk of schizophrenia (FHR-P), and healthy controls with respect to clinical manifestation and a history of psychosocial stressors.

METHODS

We recruited 40 first-episode psychosis patients, 45 acutely relapsed schizophrenia (SCZ-AR) patients, 39 FHR-P individuals, and 56 healthy controls. The level of methylation at 9 CpG sites of the NR3C1 gene was determined using pyrosequencing.

RESULTS

The level of NR3C1 methylation was significantly lower in first-episode psychosis patients and significantly higher in SCZ-AR patients compared with other subgroups of participants. Individuals with FHR-P and healthy controls had similar levels of NR3C1 methylation. A history of adverse childhood experiences was associated with significantly lower NR3C1 methylation in all subgroups of participants. Higher methylation of the NR3C1 gene was related to worse performance of attention and immediate memory as well as lower level of general functioning in patients with psychosis.

CONCLUSIONS

Patients with schizophrenia-spectrum disorders show altered levels of NR3C1 methylation that are significantly lower in first-episode psychosis patients and significantly higher in SCZ-AR patients. Higher methylation of the NR3C1 gene might be related to cognitive impairment observed in this clinical population. The association between a history of adverse childhood experiences and lower NR3C1 methylation is not specific to patients with psychosis. Longitudinal studies are needed to establish causal mechanisms underlying these observations.

Network modules linking expression and methylation in prefrontal cortex of schizophrenia

Tremendous work has demonstrated the critical roles of genetics, epigenetics as well as their interplay in brain transcriptional regulations in the pathology of schizophrenia (SZ). There is great success currently in the dissection of the genetic components underlying risk-conferring transcriptomic networks. However, the study of regulating effect of epigenetics in the etiopathogenesis of SZ still faces many challenges. In this work, we investigated DNA methylation and gene expression from the dorsolateral prefrontal cortex (DLPFC) region of schizophrenia patients and healthy controls using weighted correlation network approach. We identified and replicated two expression and two methylation modules significantly associated with SZ. Among them, one pair of expression and methylation modules were significantly overlapped in the module genes which were significantly enriched in astrocyte-associated functional pathways, and specifically expressed in astrocytes. Another two linked expression-methylation module pairs were involved ageing process with module genes mostly related to oligodendrocyte development and myelination, and specifically expressed in oligodendrocytes. Further examination of underlying quantitative trait loci (QTLs) showed significant enrichment in genetic risk of most psychiatric disorders for expression QTLs but not for methylation QTLs. These results support the coherence between methylation and gene expression at the network level, and suggest a combinatorial effect of genetics and epigenetics in regulating gene expression networks specific to glia cells in relation to SZ and ageing process.

Multimodal Data Analysis of Alzheimer's Disease Based on Clustering Evolutionary Random Forest

Alzheimer's disease (AD) has become a severe medical challenge. Advances in technologies produced high-dimensional data of different modalities including functional magnetic resonance imaging (fMRI) and single nucleotide polymorphism (SNP). Understanding the complex association patterns among these heterogeneous and complementary data is of benefit to the diagnosis and prevention of AD. In this paper, we apply the appropriate correlation analysis method to detect the relationships between brain regions and genes, and propose "brain region-gene pairs" as the multimodal features of the sample. In addition, we put forward a novel data analysis method from technology aspect, cluster evolutionary random forest (CERF), which is suitable for "brain region-gene pairs". The idea of clustering evolution is introduced to improve the generalization performance of random forest which is constructed by randomly selecting samples and sample features. Through hierarchical clustering of decision trees in random forest, the decision trees with higher similarity are clustered into one class, and the decision trees with the best performance are retained to enhance the diversity between decision trees. Furthermore, based on CERF, we integrate feature construction, feature selection and sample classification to find the optimal combination of different methods, and design a comprehensive diagnostic framework for AD. The framework is validated by the samples with both fMRI and SNP data from ADNI. The results show that we can effectively identify AD patients and discover some brain regions and genes associated with AD significantly based on this framework. These findings are conducive to the clinical treatment and prevention of AD.

Association of rs1059004 polymorphism in the OLIG2 locus with whole-brain functional connectivity in first-episode schizophrenia

The rs1059004 in the oligodendrocyte lineage transcription factor 2 (OLIG2) gene has been reported to be a candidate single nucleotide polymorphism (SNP) for schizophrenia (SZ). A variety of functional magnetic resonance imaging (fMRI) studies have revealed disconnection in SZ. We aimed to investigate the association of rs1059004 polymorphism with whole-brain functional connectivity (FC) and to further explore the correlation between altered FC and cognitive behavioral scales. Fifty-five SZ patients and fifty-three matched healthy controls were included in this study. The general linear model was used to test the role of rs1059004 polymorphism in whole-brain FC based on resting-state fMRI. Spearman's rank correlation test was used to calculate the correlation coefficient between FC strength and behavior score. In the whole-brain FC analysis, we found that the FC pattern in SZ patients differs from healthy controls. Furthermore, compared to homozygous C carriers, risk A allele carriers have reduced FC strength in both SZ patients and healthy controls. For the correlation analysis in risk A allele carriers, we found a positive correlation between FC strength and verbal fluency score in SZ patients, while healthy controls appeared to have the opposite result. Our results revealed that participants carrying the risk A allele show FC patterns differing from those of homozygous C carriers. This result suggests that rs1059004 polymorphism and SZ have synergistic effects on brain connections. The correlation analysis result suggests that special attention should be paid to SZ patients who carry the risk A allele because the patients perform worse in verbal fluency.

A systematic review of associations between functional MRI activity and polygenic risk for schizophrenia and bipolar disorder

Genetic factors account for up to 80% of the liability for schizophrenia (SCZ) and bipolar disorder (BD). Genome-wide association studies have successfully identified several genes associated with increased risk for both disorders. This has allowed researchers to model the aggregate effect of genes associated with disease status and create a polygenic risk score (PGRS) for each individual. The interest in imaging genetics using PGRS has grown in recent years, with several studies now published. We have conducted a systematic review to examine the effects of PGRS of SCZ, BD and cross psychiatric disorders on brain function and connectivity using fMRI data. Results indicate that the effect of genetic load for SCZ and BD on brain function affects task-related recruitment, with frontal areas having a more prominent role, independent of task. Additionally, the results suggest that the polygenic architecture of psychotic disorders is not regionally confined but impacts on the task-dependent recruitment of multiple brain regions. Future imaging genetics studies with large samples, especially population studies, would be uniquely informative in mapping the spatial distribution of the genetic risk to psychiatric disorders on brain processes during various cognitive tasks and may lead to the discovery of biological pathways that could be crucial in mediating the link between genetic factors and alterations in brain networks.

Multi-omics integrative analysis identified SNP-methylation-mRNA: Interaction in peripheral blood mononuclear cells

Genetic variants have potential influence on DNA methylation and thereby regulate mRNA expression. This study aimed to comprehensively reveal the relationships among SNP, methylation and mRNA, and identify methylation-mediated regulation patterns in human peripheral blood mononuclear cells (PBMCs). Based on in-house multi-omics datasets from 43 Chinese Han female subjects, genome-wide association trios were constructed by simultaneously testing the following three association pairs: SNP-methylation, methylation-mRNA and SNP-mRNA. Causal inference test (CIT) was used to identify methylation-mediated genetic effects on mRNA. A total of 64,184 significant cis-methylation quantitative trait loci (meQTLs) were identified (FDR < 0.05). Among the 745 constructed trios, 464 trios formed SNP-methylation-mRNA regulation chains (CIT). Network analysis (Cytoscape 3.3.0) constructed multiple complex regulation networks among SNP, methylation and mRNA (eg a total of 43 SNPs simultaneously connected to cg22517527 and further to PRMT2, DIP2A and YBEY). The regulation chains were supported by the evidence from 4DGenome database, relevant to immune or inflammatory related diseases/traits, and overlapped with previous eQTLs from dbGaP and GTEx. The results provide new insights into the regulation patterns among SNP, DNA methylation and mRNA expression, especially for the methylation-mediated effects, and also increase our understanding of functional mechanisms underlying the established associations.

The Translational Potential of Neuroimaging Genomic Analyses To Diagnosis And Treatment In The Mental Disorders

Imaging genomics focuses on characterizing genomic influence on the variation of neurobiological traits, holding promise for illuminating the pathogenesis, reforming the diagnostic system, and precision medicine of mental disorders. This paper aims to provide an overall picture of the current status of neuroimaging-genomic analyses in mental disorders, and how we can increase their translational potential into clinical practice. The review is organized around three perspectives. (a) Towards reliability, generalizability and interpretability, where we summarize the multivariate models and discuss the considerations and trade-offs of using these methods and how reliable findings may be reached, to serve as ground for further delineation. (b) Towards improved diagnosis, where we outline the advantages and challenges of constructing a dimensional transdiagnostic model and how imaging genomic analyses map into this framework to aid in deconstructing heterogeneity and achieving an optimal stratification of patients that better inform treatment planning. (c) Towards improved treatment. Here we highlight recent efforts and progress in elucidating the functional annotations that bridge between genomic risk and neurobiological abnormalities, in detecting genomic predisposition and prodromal neurodevelopmental changes, as well as in identifying imaging genomic biomarkers for predicting treatment response. Providing an overview of the challenges and promises, this review hopefully motivates imaging genomic studies with multivariate, dimensional and transdiagnostic designs for generalizable and interpretable findings that facilitate development of personalized treatment.

Dynamic changes of functional segregation and integration in vulnerability and resilience to schizophrenia

Schizophrenia (SZ) is a highly heritable disease with neurodevelopmental origins and significant functional brain network dysfunction. Functional network is heavily influenced by neurodevelopment processes and can be characterized by the degree of segregation and integration. This study examines functional segregation and integration in SZ and their first-degree relatives (high risk [HR]) to better understand the dynamic changes in vulnerability and resiliency, and disease markers. Resting-state functional magnetic resonance imaging data acquired from 137 SZ, 89 HR, and 210 healthy controls (HCs). Small-worldness σ was computed at voxel level to quantify balance between segregation and integration. Interregional functional associations were examined based on Euclidean distance between regions and reflect degree of segregation and integration. Distance strength maps were used to localize regions of altered distance-based functional connectivity. σ was significantly decreased in SZ compared to HC, with no differences in high risk (HR). In three-group comparison, significant differences were noted in short-range connectivity (primarily in the primary sensory, motor and their association cortices, and the thalamus) and medium/long-range connectivity (in the prefrontal cortices [PFCs]). Decreased short- and increased medium/long-range connectivity was found in SZ. Decreased short-range connectivity was seen in SZ and HR, while HR had decreased medium/long-range connectivity. We observed disrupted balance between segregation and integration in SZ, whereas relatively preserved in HR. Similarities and differences between SZ and HR, specific changes of SZ were found. These might reflect dynamic changes of segregation in primary cortices and integration in PFCs in vulnerability and resilience, and disease markers in SZ.

Shared Genetic Risk of Schizophrenia and Gray Matter Reduction in 6p22.1

Genetic factors are known to influence both risk for schizophrenia (SZ) and variation in brain structure. A pressing question is whether the genetic underpinnings of brain phenotype and the disorder overlap. Using multivariate analytic methods and focusing on 1,402 common single-nucleotide polymorphisms (SNPs) mapped from the Psychiatric Genomics Consortium (PGC) 108 regions, in 777 discovery samples, we identified 39 SNPs to be significantly associated with SZ-discriminating gray matter volume (GMV) reduction in inferior parietal and superior temporal regions. The findings were replicated in 609 independent samples. These 39 SNPs in chr6:28308034-28684183 (6p22.1), the most significant SZ-risk region reported by PGC, showed regulatory effects on both DNA methylation and gene expression of postmortem brain tissue and saliva. Furthermore, the regulated methylation site and gene showed significantly different levels of methylation and expression in the prefrontal cortex between cases and controls. In addition, for one regulated methylation site we observed a significant in vivo methylation-GMV association in saliva, suggesting a potential SNP-methylation-GMV pathway. Notably, the risk alleles inferred for GMV reduction from in vivo imaging are all consistent with the risk alleles for SZ inferred from postmortem data. Collectively, we provide evidence for shared genetic risk of SZ and regional GMV reduction in 6p22.1 and demonstrate potential molecular mechanisms that may drive the observed in vivo associations. This study motivates dissecting SZ-risk variants to better understand their associations with focal brain phenotypes and the complex pathophysiology of the illness.

A Schizophrenia-Related Genetic-Brain-Cognition Pathway Revealed in a Large Chinese Population

BACKGROUND

In the past decades, substantial effort has been made to explore the genetic influence on brain structural/functional abnormalities in schizophrenia, as well as cognitive impairments. In this work, we aimed to extend previous studies to explore the internal mediation pathway among genetic factor, brain features and cognitive scores in a large Chinese dataset.

METHODS

Gray matter (GM) volume, fractional amplitude of low-frequency fluctuations (fALFF), and 4522 schizophrenia-susceptible single nucleotide polymorphisms (SNP) from 905 Chinese subjects were jointly analyzed, to investigate the multimodal association. Based on the identified imaging-genetic pattern, correlations with cognition and mediation analysis were then conducted to reveal the potential mediation pathways.

FINDINGS

One linked imaging-genetic pattern was identified to be group discriminative, which was also associated with working memory performance. Particularly, GM reduction in thalamus, putamen and bilateral temporal gyrus in schizophrenia was associated with fALFF decrease in medial prefrontal cortex, both were also associated with genetic factors enriched in neuron development, synapse organization and axon pathways, highlighting genes including CSMD1, CNTNAP2, DCC, GABBR2 etc. This linked pattern was also replicated in an independent cohort (166 subjects), which although showed certain age and clinical differences with the discovery cohort. A further mediation analysis suggested that GM alterations significantly mediated the association from SNP to fALFF, while fALFF mediated the association from SNP and GM to working memory performance.

INTERPRETATION

This study has not only verified the impaired imaging-genetic association in schizophrenia, but also initially revealed a potential genetic-brain-cognition mediation pathway, indicating that polygenic risk factors could exert impact on phenotypic measures from brain structure to function, thus could further affect cognition in schizophrenia.

A Perspective of the Cross-Tissue Interplay of Genetics, Epigenetics, and Transcriptomics, and Their Relation to Brain Based Phenotypes in Schizophrenia

Genetic association studies of psychiatric disorders have provided unprecedented insight into disease risk profiles with high confidence. Yet, the next research challenge is how to translate this rich information into mechanisms of disease, and further help interventions and treatments. Given other comprehensive reviews elsewhere, here we want to discuss the research approaches that integrate information across various tissue types. Taking schizophrenia as an example, the tissues, cells, or organisms being investigated include postmortem brain tissues or neurons, peripheral blood and saliva, in vivo brain imaging, and in vitro cell lines, particularly human induced pluripotent stem cells (iPSC) and iPSC derived neurons. There is a wealth of information on the molecular signatures including genetics, epigenetics, and transcriptomics of various tissues, along with neuronal phenotypic measurements including neuronal morphometry and function, together with brain imaging and other techniques that provide data from various spatial temporal points of disease development. Through consistent or complementary processes across tissues, such as cross-tissue methylation quantitative trait loci (QTL) and expression QTL effects, systemic integration of such information holds the promise to put the pieces of puzzle together for a more complete view of schizophrenia disease pathogenesis.

Nosip functions during vertebrate eye and cranial cartilage development

BACKGROUND

The nitric oxide synthase interacting protein (Nosip) has been associated with diverse human diseases including psychological disorders. In line, early neurogenesis of mouse and Xenopus is impaired upon Nosip deficiency. Nosip knockout mice show craniofacial defects and the down-regulation of Nosip in the mouse and Xenopus leads to microcephaly. Until now, the exact underlying molecular mechanisms of these malformations were still unknown.

RESULTS

Here, we show that nosip is expressed in the developing ocular system as well as the anterior neural crest cells of Xenopus laevis. Furthermore, Nosip inhibition causes severe defects in eye formation in the mouse and Xenopus. Retinal lamination as well as dorso-ventral patterning of the retina were affected in Nosip-depleted Xenopus embryos. Marker gene analysis using rax, pax6 and otx2 reveals an interference with the eye field induction and differentiation. A closer look on Nosip-deficient Xenopus embryos furthermore reveals disrupted cranial cartilage structures and an inhibition of anterior neural crest cell induction and migration shown by twist, snai2, and egr2. Moreover, foxc1 as downstream factor of retinoic acid signalling is affected upon Nosip deficiency.

CONCLUSIONS

Nosip is a crucial factor for the development of anterior neural tissue such the eyes and neural crest cells. Developmental Dynamics 247:1070-1082, 2018. © 2018 Wiley Periodicals, Inc.

Characterization of cross-tissue genetic-epigenetic effects and their patterns in schizophrenia

Background

One of the major challenges in current psychiatric epigenetic studies is the tissue specificity of epigenetic changes since access to brain samples is limited. Peripheral tissues have been studied as surrogates but the knowledge of cross-tissue genetic-epigenetic characteristics remains largely unknown. In this work, we conducted a comprehensive investigation of genetic influence on DNA methylation across brain and peripheral tissues with the aim to characterize cross-tissue genetic-epigenetic effects and their roles in the pathophysiology of psychiatric disorders.

Methods

Genome-wide methylation quantitative trait loci (meQTLs) from brain prefrontal cortex, whole blood, and saliva were identified separately and compared. Focusing on cis-acting effects, we tested the enrichment of cross-tissue meQTLs among cross-tissue expression QTLs and genetic risk loci of various diseases, including major psychiatric disorders. CpGs targeted by cross-tissue meQTLs were also tested for genomic distribution and functional enrichment as well as their contribution to methylation correlation across tissues. Finally, a consensus co-methylation network analysis on the cross-tissue meQTL targeted CpGs was performed on data of the three tissues collected from schizophrenia patients and controls.

Results

We found a significant overlap of cis meQTLs (45–73 %) and targeted CpG sites (31–68 %) among tissues. The majority of cross-tissue meQTLs showed consistent signs of cis-acting effects across tissues. They were significantly enriched in genetic risk loci of various diseases, especially schizophrenia, and also enriched in cross-tissue expression QTLs. Compared to CpG sites not targeted by any meQTLs, cross-tissue targeted CpGs were more distributed in CpG island shores and enhancer regions, and more likely had strong correlation with methylation levels across tissues. The targeted CpGs were also annotated to genes enriched in multiple psychiatric disorders and neurodevelopment-related pathways. Finally, we identified one co-methylation network shared between brain and blood showing significant schizophrenia association (p = 5.5 × 10⁻⁶).

Conclusions

Our results demonstrate prevalent cross-tissue meQTL effects and their contribution to the correlation of CpG methylation across tissues, while at the same time a large portion of meQTLs show tissue-specific characteristics, especially in brain. Significant enrichment of cross-tissue meQTLs in expression QTLs and genetic risk loci of schizophrenia suggests the potential of these cross-tissue meQTLs for studying the genetic effect on schizophrenia. The study provides compelling motivation for a well-designed experiment to further validate the use of surrogate tissues in the study of psychiatric disorders.

Electronic supplementary material

The online version of this article (10.1186/s13073-018-0519-4) contains supplementary material, which is available to authorized users.

Opposite Epigenetic Associations With Alcohol Use and Exercise Intervention

Alcohol use disorder (AUD) is a devastating public health problem in which both genetic and environmental factors play a role. Growing evidence supports that epigenetic regulation is one major mechanism in neuroadaptation that contributes to development of AUD. Meanwhile, epigenetic patterns can be modified by various stimuli including exercise. Thus, it is an intriguing question whether exercise can lead to methylation changes that are opposite to those related to drinking. We herein conducted a comparative study to explore this issue. Three cohorts were profiled for DNA methylation (DNAm), including a longitudinal exercise intervention cohort (53 healthy participants profiled at baseline and after a 12-months exercise intervention), a cross-sectional case-control cohort (81 hazardous drinkers and 81 healthy controls matched in age and sex), and a cross-sectional binge drinking cohort (281 drinkers). We identified 906 methylation sites showing significant DNAm differences between drinkers and controls in the case-control cohort, as well as, associations with drinking behavior in the drinking cohort. In parallel, 341 sites were identified for significant DNAm alterations between baseline and follow-up in the exercise cohort. Thirty-two sites overlapped between these two set of findings, of which 15 sites showed opposite directions of DNAm associations between exercise and drinking. Annotated genes of these 15 sites were enriched in signaling pathways related to synaptic plasticity. In addition, the identified methylation sites significantly associated with impaired control over drinking, suggesting relevance to neural function. Collectively, the current findings provide preliminary evidence that exercise has the potential to partially reverse DNAm differences associated with drinking at some CpG sites, motivating rigorously designed longitudinal studies to better characterize epigenetic effects with respect to prevention and intervention of AUD.