Identification of genetic variants influencing methylation in brain with pleiotropic effects on psychiatric disorders

Linking DNA methylation in brain regions to Alzheimer's disease risk: a Mendelian randomization study

AIM

DNA methylation in brain regions represents a potential mechanism linking genetic variation to Alzheimer's disease (ad) risk, yet most studies have focused on blood-derived methylation markers. In this study, we conducted a systematic Mendelian randomization (MR) study to evaluate associations between predicted brain region-specific DNA methylation levels and ad risk, using methylation quantitative trait loci (mQTL) as genetic instruments.

METHODS

We analyzed mQTLs from five human brain regions: cerebellum (CRBLM), frontal cortex (FCTX), causal pons (PONS), and temporal cortex (TCTX) from 600 individuals in Gibbs et al's study, as well as mQTLs from dorsolateral prefrontal cortex (DLPFC) of 543 participants in the Religious Orders Study and the Rush Memory and Aging Project (ROSMAP). In our MR analyses, we integrated these mQTLs with single nucleotide polymorphisms (SNP)-ad risk summary statistics derived from 85 934 ad-related cases and 401 577 normal controls.

RESULTS

Among 62 554 cytosine-guanine dinucleotide (CpG) sites, we identified 597 CpG sites (CpGs) significantly associated with ad risk (false discovery rate (FDR) < 0.05). Of these, 289 were confirmed through colocalization and summary-based MR (SMR) analyses, including one CpG site in CRBLM, 285 in DLPFC, one in FCTX, two in PONS, and one in TCTX. By integrating gene expression data, we identified 19 CpG sites with consistent associations across methylation levels, expression of eight target genes, and ad risk, including novel regulatory mechanisms involving RITA1's modulation of cg11558705 and PCGF3's regulation of cg10009224.

CONCLUSION

Our findings highlight brain region-specific DNA methylation as a mediator of genetic risk for ad, offering insights into ad pathogenesis and identifying potential therapeutic targets.

Multiomics Analysis of the Molecular Response to Glucocorticoids: Insights Into Shared Genetic Risk From Psychiatric to Medical Disorders

BACKGROUND

Alterations in the effects of glucocorticoids have been implicated in mediating some of the negative health effects associated with chronic stress, including increased risk for psychiatric disorders and cardiovascular and metabolic diseases. In this study, we investigated how genetic variants influence gene expression and DNA methylation in response to glucocorticoid receptor (GR) activation and their association with disease risk.

METHODS

We measured DNA methylation (n = 199) and gene expression (n = 297) in peripheral blood before and after GR activation with dexamethasone, with matched genotype data available for all samples. A comprehensive molecular quantitative trait locus (QTL) analysis was conducted, mapping GR-response methylation (me)QTLs, GR-response expression (e)QTLs, and GR-response expression quantitative trait methylation (eQTMs). A multilevel network analysis was employed to map the complex relationships between the transcriptome, epigenome, and genetic variation.

RESULTS

We identified 3772 GR-response meCpGs corresponding to 104,828 local GR-response meQTLs that did not strongly overlap with baseline meQTLs. eQTM and eQTL analyses revealed distinct genetic influences on gene expression and DNA methylation. Multilevel network analysis uncovered GR-response network trio QTLs, characterized by SNP-CpG-transcript combinations where meQTLs act as both eQTLs and eQTMs. GR-response trio variants were enriched in a genome-wide association study for psychiatric, respiratory, autoimmune, and cardiovascular diseases and conferred a higher relative heritability per SNP than GR-response meQTL and baseline QTL SNPs.

CONCLUSIONS

Genetic variants modulating the molecular effects of glucocorticoids are associated with psychiatric as well as medical diseases and not uncovered in baseline QTL analyses.

Genetic correlation, pleiotropic loci and shared risk genes between major depressive disorder and gastrointestinal tract disorders

BACKGROUND

Major depressive disorder (MDD) is associated with gastrointestinal tract (GIT) disorders, while genetic correlation, pleiotropic loci and shared risk genes remain to be explored.

METHODS

Leveraging genome-wide association study statistics for MDD (n = 170,756), peptic ulcer disease (PUD; n = 16,666), gastroesophageal reflux disease (GORD; n = 54,854), PUD and/or GORD and/or medications (PGM; n = 90,175), irritable bowel syndrome (IBS; n = 28,518), and inflammatory bowel disease (IBD; n = 7045), we determined global and local genetic correlations, identified pleiotropic loci, performed gene-level evaluations, and inferred causal associations using bidirectional Mendelian randomization.

RESULTS

We found global correlation of MDD with PUD (rg = 0.444, P = 3.135 × 10-24), GORD (rg = 0.459, P = 2.568 × 10-65), PGM (rg = 0.498, P = 6.094 × 10-114), IBS (rg = 0.621, P = 2.483 × 10-63), and IBD (rg = 0.171, P = 1.824 × 10-5). We identified 12 locally correlated regions between MDD and GIT disorders except for IBD, and one shared region (chr11:111985737-113,103,996) for PGM, GORD, and IBS. We found one pleiotropic locus for PUD, 12 for GORD, 30 for PGM, eight for IBS, and seven for IBD, and five shared loci (rs138786869, rs2284189, rs3130063, rs35789010, rs7568369) for GORD and PGM. We respectively observed 14 and 20 overlapping genes for MDD-GORD and MDD-PGM. We showed genetic liabilities to GORD, PGM, and IBS causally increase MDD risk, while all reverse causalities are significant.

CONCLUSIONS

Our work identifies genetic architectures shared between MDD and GIT disorders, contributes genetic insights to understand depression in the context of gut-brain interactions, and provides potential targets to treat gastrointestinal symptoms in depressive patients.

Thalamocortical dysrhythmia and reward deficiency syndrome as uncertainty disorders

A common anatomical core has been described for psychiatric disorders, consisting of the dorsal anterior cingulate cortex (dACC) and anterior insula, processing uncertainty. A common neurophysiological core has been described for other brain related disorders, called thalamocortical dysrhythmia (TCD), consisting of persistent cross-frequency coupling between low and high frequencies. And a common genetic core has been described for yet another set of hypodopaminergic pathologies called reward deficiency syndromes (RDS). Considering that some RDS have the neurophysiological features of TCD, it can be hypothesized that TCD and RDS have a common anatomical core, yet a differentiating associated neurophysiological mechanism. The EEGs of 683 subjects are analysed in source space for both differences and conjunction between TCD and healthy controls, RDS and healthy controls, and between TCD and RDS. A balance between current densities of the pregenual anterior cingulate cortex (pgACC) extending into the ventromedial prefrontal cortex (vmPFC) and dACC is calculated as well. TCD and RDS share a common anatomical and neurophysiological core, consisting of beta activity in the dACC and theta activity in dACC extending into precuneus and dorsolateral prefrontal cortex. TCD and RDS differ in pgACC/vmPFC activity and demonstrate an opposite balance between pgACC/vmPFC and dACC. Based on the Bayesian brain model TCD and RDS can be defined as uncertainty disorders in which the pgACC/vmPFC and dACC have an opposite balance, possibly explained by an inverted-U curve profile of both pgACC/vmPFC and dACC.

FAM109B plays a tumorigenic role in low-grade gliomas and is associated with tumor-associated macrophages (TAMs)

BACKGROUND

Family with sequence similarity 109, member B (FAM109B) is involved in endocytic transport and affects genetic variation in brain methylation. It is one of the important genes related to immune cell-associated diseases. In the tumor immune system, methylation can regulate tumor immunity and influence the maturation and functional response of immune cells. Whether FAM109B is involved in tumor progression and its correlation with the tumor immune microenvironment has not yet been disclosed.

METHODS

A comprehensive pan-cancer analysis of FAM109B expression, prognosis, immunity, and TMB was conducted. The expression, clinical features, and prognostic value of FAM109B in low-grade gliomas (LGG) were evaluated using TCGA, CGGA, and Gravendeel databases. The expression of FAM109B was validated by qRT-PCR, immunohistochemistry (IHC), and Western blotting (WB). The relationship between FAM109B and methylation, Copy Number Variation (CNV), prognosis, immune checkpoints (ICs), and common chemotherapy drug sensitivity in LGG was explored through Cox regression, Kaplan-Meier curves, and Spearman correlation analysis. FAM109B levels and their distribution were studied using the TIMER database and single-cell analysis. The potential role of FAM109B in gliomas was further investigated through in vitro and in vivo experiments.

RESULTS

FAM109B was significantly elevated in various tumor types and was associated with poor prognosis. Its expression was related to aggressive progression and poor prognosis in low-grade glioma patients, serving as an independent prognostic marker for LGG. Glioma grade was negatively correlated with FAM109B DNA promoter methylation. Immune infiltration and single-cell analysis showed significant expression of FAM109B in tumor-associated macrophages (TAMs). The expression of FAM109B was closely related to gene mutations, immune checkpoints (ICs), and chemotherapy drugs in LGG. In vitro studies showed increased FAM109B expression in LGG, closely related to cell proliferation. In vivo studies showed that mice in the sh-FAM109B group had slower tumor growth, slower weight loss, and longer survival times.

CONCLUSIONS

FAM109B, as a novel prognostic biomarker for low-grade gliomas, exhibits specific overexpression in TAMs and may be a potential therapeutic target for LGG patients.

Genome-Wide Mendelian Randomization Study Reveals Druggable Genes for Cerebral Small Vessel Disease

BACKGROUND

Cerebral small vessel disease (CSVD) is a group of neurological disorders that affect the small blood vessels within the brain, for which no effective treatments are currently available. We conducted a Mendelian randomization (MR) study to identify candidate therapeutic genes for CSVD.

METHODS

We retrieved genome-wide association study data from 6 recently conducted, extensive investigations focusing on CSVD magnetic resonance imaging markers and performed a 2-sample MR analysis to assess the potential causal effects of gene expression and protein level within druggable genes on CSVD in blood and brain tissues. Colocalization analyses and repeat studies were undertaken to verify the relationship. Additionally, mediation analysis was conducted to explore the potential mechanisms involving druggable genes and known risk factors for CSVD. Finally, phenome-wide MR analyses were applied to evaluate the potential adverse effects related to the identified druggable genes for CSVD treatment.

RESULTS

Overall, 5 druggable genes consistently showed associations with CSVD in MR analyses across both the discovery and validation cohorts. Notably, the ALDH2 and KLHL24 genes were identified as associated with CSVD in both blood and brain tissues, whereas the genes ADRB1, BTN3A2, and EFEMP1 were exclusively detected in brain tissue. Moreover, mediation analysis elucidated the proportion of the total effects mediated by CSVD risk factors through candidate druggable genes, which ranged from 5.5% to 18.5%, and offered potential explanations for the observed results. A comprehensive phenome-wide MR analysis further emphasized both the therapeutic benefits and potential side effects of targeting these candidate druggable genes.

CONCLUSIONS

This study provides genetic evidence supporting the potential therapeutic benefits of targeting druggable genes for treating CSVD, which will be useful for prioritizing CSVD drug development.

Redefining the biological and pathophysiological role of dimethylarginine dimethylaminohydrolase 2

The enzyme dimethylarginine dimethylaminohydrolase (DDAH) 1 metabolizes asymmetric dimethylarginine (ADMA), a critical endogenous cardiovascular risk factor. In the past two decades, there has been significant controversy about whether DDAH2, the other DDAH isoform, is also able to directly metabolize ADMA. There has been evidence that DDAH2 regulates several critical processes involved in cardiovascular and immune homeostasis. However, the molecular mechanisms underpinning these effects are unclear. In this opinion, we discuss the previous and current knowledge of ADMA metabolism by DDAH in light of a recent consortium study, which convincingly demonstrated that DDAH2 is not capable of metabolizing ADMA, unlike DDAH1. Thus, further research in this field is needed to uncover the molecular mechanisms of DDAH2 and its role in various disorders.

NeuroDots: From Single-Target to Brain-Network Modulation: Why and What Is Needed?

OBJECTIVES

Current techniques in brain stimulation are still largely based on a phrenologic approach that a single brain target can treat a brain disorder. Nevertheless, meta-analyses of brain implants indicate an overall success rate of 50% improvement in 50% of patients, irrespective of the brain-related disorder. Thus, there is still a large margin for improvement. The goal of this manuscript is to 1) develop a general theoretical framework of brain functioning that is amenable to surgical neuromodulation, and 2) describe the engineering requirements of the next generation of implantable brain stimulators that follow from this theoretic model.

MATERIALS AND METHODS

A neuroscience and engineering literature review was performed to develop a universal theoretical model of brain functioning and dysfunctioning amenable to surgical neuromodulation.

RESULTS

Even though a single target can modulate an entire network, research in network science reveals that many brain disorders are the consequence of maladaptive interactions among multiple networks rather than a single network. Consequently, targeting the main connector hubs of those multiple interacting networks involved in a brain disorder is theoretically more beneficial. We, thus, envision next-generation network implants that will rely on distributed, multisite neuromodulation targeting correlated and anticorrelated interacting brain networks, juxtaposing alternative implant configurations, and finally providing solid recommendations for the realization of such implants. In doing so, this study pinpoints the potential shortcomings of other similar efforts in the field, which somehow fall short of the requirements.

CONCLUSION

The concept of network stimulation holds great promise as a universal approach for treating neurologic and psychiatric disorders.

General and specific patterns of cortical gene expression as spatial correlates of complex cognitive functioning

Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given gene's expression fluctuates across the brain may be governed by general rules. Quantifying patterns of spatial covariation across genes would offer insights into the molecular characteristics of brain areas supporting, for example, complex cognitive functions. Here, we use principal component analysis to separate general and unique gene regulatory associations with cortical substrates of cognition. We find that the region-to-region variation in cortical expression profiles of 8235 genes covaries across two major principal components : gene ontology analysis suggests these dimensions are characterised by downregulation and upregulation of cell-signalling/modification and transcription factors. We validate these patterns out-of-sample and across different data processing choices. Brain regions more strongly implicated in general cognitive functioning (g; 3 cohorts, total meta-analytic N = 39,519) tend to be more balanced between downregulation and upregulation of both major components (indicated by regional component scores). We then identify a further 41 genes as candidate cortical spatial correlates of g, beyond the patterning of the two major components (|β| range = 0.15 to 0.53). Many of these genes have been previously associated with clinical neurodegenerative and psychiatric disorders, or with other health-related phenotypes. The results provide insights into the cortical organisation of gene expression and its association with individual differences in cognitive functioning.

A Comprehensive Landscape of Imaging Feature-Associated RNA Expression Profiles in Human Breast Tissue

The expression abundance of transcripts in nondiseased breast tissue varies among individuals. The association study of genotypes and imaging phenotypes may help us to understand this individual variation. Since existing reports mainly focus on tumors or lesion areas, the heterogeneity of pathological image features and their correlations with RNA expression profiles for nondiseased tissue are not clear. The aim of this study is to discover the association between the nucleus features and the transcriptome-wide RNAs. We analyzed both microscopic histology images and RNA-sequencing data of 456 breast tissues from the Genotype-Tissue Expression (GTEx) project and constructed an automatic computational framework. We classified all samples into four clusters based on their nucleus morphological features and discovered feature-specific gene sets. The biological pathway analysis was performed on each gene set. The proposed framework evaluates the morphological characteristics of the cell nucleus quantitatively and identifies the associated genes. We found image features that capture population variation in breast tissue associated with RNA expressions, suggesting that the variation in expression pattern affects population variation in the morphological traits of breast tissue. This study provides a comprehensive transcriptome-wide view of imaging-feature-specific RNA expression for healthy breast tissue. Such a framework could also be used for understanding the connection between RNA expression and morphology in other tissues and organs. Pathway analysis indicated that the gene sets we identified were involved in specific biological processes, such as immune processes.

Association of NKAPL rs1635 With Cognitive Function in Early-Onset Schizophrenia

BACKGROUND: Schizophrenia is a severe mental disorder with high heritability, and cognitive dysfunction is one of the core features. Growing evidence suggests the genetic risk of schizophrenia may contribute to cognitive impairments. The variant rs1635 (nucleotide sequence: c.455C>A; amino acid sequence: T152N) located on the (NFKB activating protein like) NKAPL gene confers risk for schizophrenia and might play a role in the neurodevelopmental process, which is particularly relevant to cognitive function. However, the relationship between rs1635 and cognitive function remains unclear. METHODS: A total of 130 patients with early-onset schizophrenia (EOS) and 300 patients with adult-onset schizophrenia (AOS) of Han Chinese were recruited and underwent neurocognitive tests by using the MATRICS Consensus Cognitive Battery (MCCB). The NKAPL rs1635 was genotyped by using DNA sequencing. The peripheral blood NKAPL mRNA expression level was examined in 152T or 152N carriers (n = 20) in EOS patients, by using the qRT-PCR. The phosphorylation level of NAKPL T152N polymorphism was detected by cell experiments. In utero electroporation of mouse embryos was examined to explore the effect of Nkapl on neuronal migration. RESULTS: Compared with rs1635 AA and AC carriers, CC (the CC genotype encodes the protein NKAPL-152T) carriers of EOS patients performed better in cognitive domain of speed of processing (t = 2.644, p = 0.009), trail making test (t = 2.221, p = 0.028) and category fluency (t = 2.578, p = 0.011). However, patients with AOS exhibited no significant differences in seven domains among the three genotype groups. There were no significant differences in cognitive performance between EOS and AOS. In EOS patients, NKAPL mRNA level in NKAPL-152N carriers is significantly lower than that of NKAPL-152T carriers. The phosphorylation level of NKAPL-152N is significantly decreased compared to NKAPL-152T. In utero electroporation showed that Nkapl deletion impairs the embryonic radial migration process. CONCLUSION: The present study found that NKAPL rs1635 was associated with cognitive impairments and peripheral blood mRNA expression level in EOS patients. The NKAPL full-length protein is required for embryonic cortical neuronal migration. The phosphorylation level of NKAPL-152N is significantly decreased. The NKAPL T152N may affect the NAKPL mRNA expression level and embryonic cortical neuronal migration by regulating the NAKPL protein phosphorylation. These data suggest that NKAPL rs1635 affects cognitive function by regulating early brain development in early-onset schizophrenia.

m6A Regulator-Mediated RNA Methylation Modification Patterns are Involved in the Pathogenesis and Immune Microenvironment of Depression

Depression is a genetical disease characterized by neuroinflammatory symptoms and is difficult to diagnose and treat effectively. Recently, modification of N6-methyladenosine (m6A) at the gene level was shown to be closely related to immune regulation. This study was conducted to explore the effect of m6A modifications on the occurrence of depression and composition of the immune microenvironment. We downloaded gene expression profile data of healthy and depressed rats from the Gene Expression Omnibus. We described the overall expression of m6A regulators in animal models of depression and constructed risk and clinical prediction models using training and validation sets. Bioinformatics analysis was performed using gene ontology functions, gene set enrichment analysis, gene set variation analysis, weighted gene co-expression network analysis, and protein-protein interaction networks. We used CIBERSORT to identify immune-infiltrating cells in depression and perform correlation analysis. We then constructed two molecular subtypes of depression and assessed the correlation between the key genes and molecular subtypes. Through differential gene analysis of m6A regulators in depressed rats, we identified seven m6A regulators that were significantly upregulated in depressed rats and successfully constructed a clinical prediction model. Gene Ontology functional annotation showed that the m6A regulators enriched differentially expressed genes in biological processes, such as the regulation of mRNA metabolic processes. Further, 12 hub genes were selected from the protein-protein interaction network. Immune cell infiltration analysis showed that levels of inflammatory cells, such as CD4 T cells, were significantly increased in depressed rats and were significantly correlated with the depression hub genes. Depression was divided into two subtypes, and the correlation between hub genes and these two subtypes was clarified. We described the effect of m6A modification on the pathogenesis of depression, focusing on the role of inflammatory infiltration.