Epigenetic profiles associated with major depression in the human brain

A CLRN3-Based CD8+ T-Related Gene Signature Predicts Prognosis and Immunotherapy Response in Colorectal Cancer

BACKGROUND

Colorectal cancer (CRC) ranks among the most prevalent malignancies affecting the gastrointestinal tract. The infiltration of CD8+ T cells significantly influences the prognosis and progression of tumor patients.

METHODS

This study establishes a CRC immune risk model based on CD8+ T cell-related genes. CD8+ T cell-related genes were identified through Weighted Gene Co-expression Network Analysis (WGCNA), and the enriched gene sets were annotated via Gene Ontology (GO) and Reactome pathway analysis. Employing machine learning methods, including the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm and Random Forest (RF), we identified nine genes associated with CD8+ T-cell infiltration. The infiltration levels of immune cells in CRC tissues were assessed using the ssGSEA algorithm.

RESULTS

These genes provide a foundation for constructing a prognostic model. The TCGA-CRC sample model's prediction scores were categorized, and the prediction models were validated through Cox regression analysis and Kaplan-Meier curve analysis. Notably, although CRC tissues with higher risk scores exhibited elevated levels of CD8+ T-cell infiltration, they also demonstrated heightened expression of immune checkpoint genes. Furthermore, comparison of microsatellite instability (MSI) and gene mutations across the immune subgroups revealed notable gene variations, particularly with APC, TP53, and TNNT1 showing higher mutation frequencies. Finally, the predictive model's efficacy was corroborated through the use of Tumor Immune Dysfunction and Exclusion (TIDE), Immune Profiling Score (IPS), and immune escape-related molecular markers. The predictive model was validated through an external cohort of CRC and the Bladder Cancer Immunotherapy Cohort. CLRN3 expression levels in tumor and adjacent normal tissues were assessed using quantitative real-time polymerase chain reaction (qRT-PCR) and western blot. Subsequent in vitro and in vivo experiments demonstrated that CLRN3 knockdown significantly attenuated the malignant biological behavior of CRC cells, while overexpression had the opposite effect.

CONCLUSIONS

This study presents a novel prognostic model for CRC, providing a framework for enhancing the survival rates of CRC patients by targeting CD8+ T-cell infiltration.

Association of whole-person eigen-polygenic risk scores with Alzheimer's disease

Late-Onset Alzheimer's Disease (LOAD) is a heterogeneous neurodegenerative disorder with complex etiology and high heritability. Its multifactorial risk profile and large portions of unexplained heritability suggest the involvement of yet unidentified genetic risk factors. Here we describe the "whole person" genetic risk landscape of polygenic risk scores for 2218 traits in 2044 elderly individuals and test if novel eigen-PRSs derived from clustered subnetworks of single-trait PRSs can improve the prediction of LOAD diagnosis, rates of cognitive decline, and canonical LOAD neuropathology. Network analyses revealed distinct clusters of PRSs with clinical and biological interpretability. Novel eigen-PRSs (ePRS) from these clusters significantly improved LOAD-related phenotypes prediction over current state-of-the-art LOAD PRS models. Notably, an ePRS representing clusters of traits related to cholesterol levels was able to improve variance explained in a model of the brain-wide beta-amyloid burden by 1.7% (likelihood ratio test P = 9.02 × 10-7). All associations of ePRS with LOAD phenotypes were eliminated by the removal of APOE-proximal loci. However, our association analysis identified modules characterized by PRSs of high cholesterol and LOAD. We believe this is due to the influence of the APOE region from both PRSs. We found significantly higher mean SNP effects for LOAD in the intersecting APOE region SNPs. Combining genetic risk factors for vascular traits and dementia could improve current single-trait PRS models of LOAD, enhancing the use of PRS in risk stratification. Our results are catalogued for the scientific community, to aid in generating new hypotheses based on our maps of clustered PRSs and associations with LOAD-related phenotypes.

Major depressive disorder: hypothesis, mechanism, prevention and treatment

Worldwide, the incidence of major depressive disorder (MDD) is increasing annually, resulting in greater economic and social burdens. Moreover, the pathological mechanisms of MDD and the mechanisms underlying the effects of pharmacological treatments for MDD are complex and unclear, and additional diagnostic and therapeutic strategies for MDD still are needed. The currently widely accepted theories of MDD pathogenesis include the neurotransmitter and receptor hypothesis, hypothalamic-pituitary-adrenal (HPA) axis hypothesis, cytokine hypothesis, neuroplasticity hypothesis and systemic influence hypothesis, but these hypothesis cannot completely explain the pathological mechanism of MDD. Even it is still hard to adopt only one hypothesis to completely reveal the pathogenesis of MDD, thus in recent years, great progress has been made in elucidating the roles of multiple organ interactions in the pathogenesis MDD and identifying novel therapeutic approaches and multitarget modulatory strategies, further revealing the disease features of MDD. Furthermore, some newly discovered potential pharmacological targets and newly studied antidepressants have attracted widespread attention, some reagents have even been approved for clinical treatment and some novel therapeutic methods such as phototherapy and acupuncture have been discovered to have effective improvement for the depressive symptoms. In this work, we comprehensively summarize the latest research on the pathogenesis and diagnosis of MDD, preventive approaches and therapeutic medicines, as well as the related clinical trials.

Erythrocyte Membrane Fatty Acid Composition as a Potential Biomarker for Depression

BACKGROUND

Major depressive disorders is a chronic and severe psychiatric disorder with poor prognosis and quality of life. Abnormal erythrocyte fatty acid (FA) composition in depressed patients were found in our previous study, but the relationship between erythrocyte membrane FA levels and different severity of depressive and anxiety symptoms remains to be explored.

METHODS

This cross-sectional study included 139 patients with first-diagnosed, drug-naïve depression and 55 healthy controls whose erythrocyte FA composition was analyzed. Patients with depression were divided into severe depression and mild to moderate depression or depression with severe anxiety and mild to moderate anxiety. Then the differences of FA levels among different groups were analyzed. Finally, the receiver operating characteristic curve analysis was applied to identify potential biomarkers in distinguishing the severity of depressive symptoms.

RESULTS

Levels of erythrocyte membrane FAs were elevated among patients with severe depression compared with healthy controls or patients with mild to moderate depression of almost all kinds. While C18:1n9t (elaidic acid), C20:3n6 (eicosatrienoic acid), C20:4n6 (arachidonic acid), C22:5n3 (docosapentaenoic acid), total fatty acids (FAs), and total monounsaturated FAs were elevated in patients with severe anxiety compared with patients with mild to moderate anxiety. Furthermore, the level of arachidonic acid, C22:4n6 (docosatetraenoic acid), elaidic acid, and the combination of all 3 were associated with the severity of depressive symptoms.

CONCLUSIONS

The results suggested that erythrocyte membrane FA levels have the potential to be the biological indicator of clinical characteristics for depression, such as depressive symptoms and anxiety. In the future, more research is needed to explore the causal association between FA metabolism and depression.

BDNF gene hydroxymethylation in hippocampus related to neuroinflammation-induced depression-like behaviors in mice

BACKGROUND

Neuroinflammation is a multifactorial condition related to glial cells and neurons activation, and it is implicated in CNS disorders including depression. BDNF is a crucial molecule that related to the pathology of depression, and it is the target of DNA methylation. DNA hydroxymethylation, an active demethylation process can convert 5-mC to 5-hmC by Tets catalyzation to regulate gene transcription. The regulatory function for BDNF gene in response to neuroinflammation remains poorly understood.

METHODS

Neuroinflammation and depressive-like behaviors were induced by lipopolysaccharide (LPS) administration in mice. The microglial activation and cellular 5-hmC localization in the hippocampus were confirmed by immunostaining. The transcripts of Tets and BDNF were examined by qPCR method. The global 5-hmC levels and enrichment of 5-hmC in BDNF gene in the hippocampus were analyzed using dot bolt and hMeDIP-sequencing analysis.

RESULTS

LPS administration induced a spectrum of depression-like behaviors (including behavioral despair and anhedonia) and increased expression of Iba-1, a marker for microglia activation, in hippocampus, demonstrating that LPS treatment cloud provide stable model of neuroinflammation with depressive-like behaviors as expected. Our results showed that Tet1, Tet2 and Tet3 mRNA expressions and consequent global 5-hmC levels were significantly decreased in the hippocampus of LPS group compared to saline group. We also demonstrated that 5-hmC fluorescence in the hippocampus located in excitatory neurons identified by CaMK II immunostaining. Furthermore, we demonstrated that the enrichment of 5-hmC in BDNF gene was decreased and corresponding BDNF mRNA was down-regulated in the hippocampus in LPS group compared to saline group.

CONCLUSION

Neuroinflammation-triggered aberrant BDNF gene hydroxymethylation in the hippocampus is an important epigenetic element that relates with depression-like behaviors.

Food and nutritional insecurity is associated with depressive symptoms mediated by NR3C1 gene promoter 1F methylation

The aim of this study was to investigate socioeconomic stressors predictive of depressive symptoms and possible epigenetic changes in the glucocorticoid receptor - NR3C1-1F - an encoding gene involved in depressive symptoms. A total of 321 adult volunteers from southeastern Brazil were recruited to evaluate depressive symptoms, socio-demographic and economic factors, including food and nutritional security (FNS) or insecurity (FNiS) status, and NR3C1-1F region methylation by pyrosequencing. Depressive symptom determinants were investigated using a Poisson regression model with robust variance. Mann-Whitney tests and structural mediation equation models were used to evaluate the relationship between NR3C1 DNA methylation, FNiS, and depressive symptoms. Multivariate Poisson regression with robust variance adjusted for sex and FNiS and NR3C1-1F region methylation predicted risk factors for depressive symptoms. Mediation analysis revealed that NR3C1-1F region methylation mediated the relationship between FNiS exposure and depressive symptoms as an outcome, and depressive volunteers and FNiS individuals exhibited a significant increase in NR3C1 methylation when compared to healthy individuals and FNS volunteers, respectively. Therefore, we suggest that stress caused by FNiS may lead to depressive symptoms and that NR3C1-1F DNA methylation can act as a mediator of both FNiS and depressive symptoms.

Energy metabolism in major depressive disorder: Recent advances from omics technologies and imaging

Major depressive disorder (MDD) is a serious psychiatric disorder that associated with high rate of disability and increasing suicide rate, and the pathogenesis is still unclear. Many researches showed that the energy metabolism of patients with depression is impaired, which may be the direction of depression treatment. In this review, we focus on the "omics" technologies such as genomics, proteomics, transcriptomics and metabolomics, as well as imaging, and the progress on energy metabolism of MDD. These findings indicate that abnormal energy metabolism is one of the important mechanisms for the occurrence and development of depression. Although the research on various mechanisms of depression is still ongoing, the rapid development of new technologies and the joint use of various technologies will help to clarify the pathogenesis of depression and explore efficient diagnosis and treatment methods.

A genome-wide methylation study reveals X chromosome and childhood trauma methylation alterations associated with borderline personality disorder

Borderline personality disorder (BPD) is a severe and highly prevalent psychiatric disorder, more common in females than in males and with notable differences in presentation between genders. Recent studies have shown that epigenetic modifications such as DNA methylation may modulate gene × environment interactions and impact on neurodevelopment. We conducted an epigenome wide study (Illumina Infinium HumanMethylation450k beadchip) in a group of BPD patients with (N = 49) and without (N = 47) childhood traumas and in a control group (N = 44). Results were confirmed in a replication cohort (N = 293 BPD patients and N = 114 controls) using EpiTYPER assays. Differentially methylated CpG sites were observed in several genes and intragenic regions in the X chromosome (PQBP1, ZNF41, RPL10, cg07810091 and cg24395855) and in chromosome 6 (TAP2). BPD patients showed significantly lower methylation levels in these CpG sites than healthy controls. These differences seemed to be increased by the existence of childhood trauma. Comparisons between BPD patients with childhood trauma and patients and controls without revealed significant differences in four genes (POU5F1, GGT6, TNFRSF13C and FAM113B), none of them in the X chromosome. Gene set enrichment analyses revealed that epigenetic alterations were more frequently found in genes controlling oestrogen regulation, neurogenesis and cell differentiation. These results suggest that epigenetic alterations in the X chromosome and oestrogen-regulation genes may contribute to the development of BPD and explain the differences in presentation between genders. Furthermore, childhood trauma events may modulate the magnitude of the epigenetic alterations contributing to BPD.

Genomic perspectives on the circadian clock hypothesis of psychiatric disorders

Circadian rhythm disturbances are frequently described in psychiatric disorders such as major depressive disorder, bipolar disorder, and schizophrenia. Growing evidence suggests a biological connection between mental health and circadian rhythmicity, including the circadian influence on brain function and mood and the requirement for circadian entrainment by external factors, which is often impaired in mental illness. Mental (as well as physical) health is also adversely affected by circadian misalignment. The marked interindividual differences in this combined susceptibility, in addition to the phenotypic spectrum in traits related both to circadian rhythms and mental health, suggested the possibility of a shared genetic background and that circadian clock genes may also be candidate genes for psychiatric disorders. This hypothesis was further strengthened by observations in animal models where clock genes had been knocked out or mutated. The introduction of genome-wide association studies (GWAS) enabled hypothesis-free testing. GWAS analysis of chronotype confirmed the prominent role of circadian genes in these phenotypes and their extensive polygenicity. However, in GWAS on psychiatric traits, only one clock gene, ARNTL (BMAL1) was identified as one of the few loci differentiating bipolar disorder from schizophrenia, and macaque monkeys where the ARNTL gene has been knocked out display symptoms similar to schizophrenia. Another lesson from genomic analyses is that chronotype has an important genetic correlation with several psychiatric disorders and that this effect is unidirectional. We conclude that the effect of circadian disturbances on psychiatric disorders probably relates to modulation of rhythm parameters and extend beyond the core clock genes themselves.

Effects of caffeic acid on epigenetics in the brain of rats with chronic unpredictable mild stress

The present study hypothesized that caffeic acid (3,4-dihydroxycinnamic acid; CaA) may exert antidepressant-like effects in rats with chronic unpredictable mild stress via epigenetic mechanisms, such as DNA methylation and hydroxymethylation. The chronic unpredictable mild stress (CUMS) model was used to analyze the effects of CaA on behavioral phenotypes, and to evaluate the distribution of 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) in the hippocampus and prefrontal cortex using immunohistochemistry and immunofluorescence. mRNA levels of the genes encoding brain-derived neurotropic factor (BDNF) and catechol-O-methyltransferase (COMT), and key enzymes regulating DNA methylation [DNA methyltransferase (DNMT)1 and DNMT3A] and hydroxymethylation [Ten-eleven translocation (TET)1-3] were examined using quantitative (q)PCR. Furthermore, enrichment of 5mC and 5hmC at the promotor regions of the Bdnf and Comt genes was quantified using chromatin immunoprecipitation-qPCR. Behavioral data showed that CaA exerted a slight antidepressant-like effect. Bdnf and Comt genes showed differential expression patterns due to CUMS. CaA intervention induced different Dnmt1/Dnmt3a and Tet1/Tet2 mRNA levels in the hippocampus and prefrontal cortex, respectively. CaA regulated the ratio of 5mC/5hmC at the promotor region of the Bdnf and Comt genes and therefore influenced gene expression, which may be a valuable therapeutic option for major depressive disorder (MDD). In conclusion, there were epigenetic changes in the hippocampus and prefrontal cortex in CUMS rats, and CaA may function as a modulator of DNA methylation to regulate gene transcription, thus providing a mechanistic basis for the use of this phytochemical agent in the treatment of MDD.

DNA methylation of HPA-axis genes and the onset of major depressive disorder in adolescent girls: a prospective analysis

The stress response system is disrupted in individuals with major depressive disorder (MDD) as well as in those at elevated risk for developing MDD. We examined whether DNA methylation (DNAm) levels of CpG sites within HPA-axis genes predict the onset of MDD. Seventy-seven girls, approximately half (n = 37) of whom were at familial risk for MDD, were followed longitudinally. Saliva samples were taken in adolescence (M age = 13.06 years [SD = 1.52]) when participants had no current or past MDD diagnosis. Diagnostic interviews were administered approximately every 18 months until the first onset of MDD or early adulthood (M age of last follow-up = 19.23 years [SD = 2.69]). We quantified DNAm in saliva samples using the Illumina EPIC chip and examined CpG sites within six key HPA-axis genes (NR3C1, NR3C2, CRH, CRHR1, CRHR2, FKBP5) alongside 59 genotypes for tagging SNPs capturing cis genetic variability. DNAm levels within CpG sites in NR3C1, CRH, CRHR1, and CRHR2 were associated with risk for MDD across adolescence and young adulthood. To rule out the possibility that findings were merely due to the contribution of genetic variability, we re-analyzed the data controlling for cis genetic variation within these candidate genes. Importantly, methylation levels in these CpG sites continued to significantly predict the onset of MDD, suggesting that variation in the epigenome, independent of proximal genetic variants, prospectively predicts the onset of MDD. These findings suggest that variation in the HPA axis at the level of the methylome may predict the development of MDD.

Association between epigenetic age acceleration and depressive symptoms in a prospective cohort study of urban-dwelling adults

OBJECTIVE

This study tests associations of DNA methylation-based (DNAm) measures of epigenetic age acceleration (EAA) with cross-sectional and longitudinal depressive symptoms in an urban sample of middle-aged adults.

METHODS

White and African-American adult participants in the Healthy Aging in Neighborhoods of Diversity across the Life Span study for whom DNA samples were analyzed (baseline age: 30-65 years) we included. We estimated three DNAm based EAA measures: (1) universal epigenetic age acceleration (AgeAccel); (2) intrinsic epigenetic age acceleration (IEAA); and (3) extrinsic epigenetic age acceleration (EEAA). Depressive symptoms were assessed using the 20-item Center for Epidemiological Studies-Depression scale total and sub-domain scores at baseline (2004-2009) and follow-up visits (2009-2013). Linear mixed-effects regression models were conducted, adjusting potentially confounding covariates, selection bias and multiple testing (N = 329 participants, ∼52% men, k = 1.9 observations/participant, mean follow-up time∼4.7 years).

RESULTS

None of the epigenetic age acceleration measures were associated with total depressive symptom scores at baseline or over time. IEAA - a measure of cellular epigenetic age acceleration irrespective of white blood cell composition - was cross-sectionally associated with decrement in "positive affect" in the total population (γ011± SE = -0.090 ± 0.030, P = 0.003, Cohen's D: -0.16) and among Whites (γ011 ± SE = -0.135 ± 0.048, P = 0.005, Cohen's D: -0.23), after correction for multiple testing. Baseline "positive affect" was similarly associated with AgeAccel.

LIMITATIONS

Limitations included small sample size, weak-moderate effects and measurement error.

CONCLUSIONS

IEAA and AgeAccel, two measures of EAA using Horvath algorithm, were linked to a reduced "positive affect", overall and among Whites. Future studies are needed to replicate our findings and test bi-directional relationships.

Co-expression network modeling identifies key long non-coding RNA and mRNA modules in altering molecular phenotype to develop stress-induced depression in rats

Long non-coding RNAs (lncRNAs) have recently emerged as one of the critical epigenetic controllers, which participate in several biological functions by regulating gene transcription, mRNA splicing, protein interaction, etc. In a previous study, we reported that lncRNAs may play a role in developing depression pathophysiology. In the present study, we have examined how lncRNAs are co-expressed with gene transcripts and whether specific lncRNA/mRNA modules are associated with stress vulnerability or resiliency to develop depression. Differential regulation of lncRNAs and coding RNAs were determined in hippocampi of three group of rats comprising learned helplessness (LH, depression vulnerable), non-learned helplessness (NLH, depression resilient), and tested controls (TC) using a single-microarray-based platform. Weighted gene co-expression network analysis (WGCNA) was conducted to correlate the expression status of protein-coding transcripts with lncRNAs. The associated co-expression modules, hub genes, and biological functions were analyzed. We found signature co-expression networks as well as modules that underlie normal as well as aberrant response to stress. We also identified specific hub and driver genes associated with vulnerability and resilience to develop depression. Altogether, our study provides evidence that lncRNA associated complex trait-specific networks may play a crucial role in developing depression.