Epigenetic clock analysis in methamphetamine dependence

Epigenome-wide association study on methamphetamine dependence

Repeated abuse of methamphetamine (METH) can cause dependence, repeated relapse of psychotic symptoms, compulsive drug-seeking behaviour, and various neurological symptoms. These long-term biological changes may be associated with epigenetic mechanisms; however, the association between METH use and epigenetic mechanisms has been poorly investigated. Thus, we performed an epigenome-wide association study of METH dependence using genomic DNA extracted from the blood samples of 24 patients with METH dependence and 24 normal controls. All participants were of Japanese descent. We tested the association between METH dependence and DNA methylation using linear regression analysis. We found epigenome-wide significant associations at four CpG sites, one of which occurred in the CNOT1 gene and another in the PUM1 gene. We especially noted the CNOT1 and PUM1 genes as well as several other genes that indicated some degree of association with METH dependence. Among the relatively enriched Gene Ontology terms, we were interested in terms of mRNA metabolism, respirasome, and excitatory extracellular ligand-gated ion channel activity. Among the relatively enriched Kyoto Encyclopedia of Genes and Genome pathways, we noted pathways of several neurological diseases. Our results indicate that genetic changes akin to those in other psychiatric or neurodegenerative disorders may also occur via epigenetic mechanisms in patients with METH dependence.

The role of NF-κB signaling pathway in reactive astrocytes among neurodegeneration after methamphetamine exposure by integrated bioinformatics

BACKGROUND

Methamphetamine (METH) is a highly addictive stimulant that has become one of the top five risk substances cause deaths from substance abuse. METH exposure increases the risk of neurodegenerative disease (ND), such as Parkinson's disease (PD), leading to disability and death. Activation of reactive astrocytes is an essential factor in neurodegeneration, and their complex role in METH exposure remains unclear. This study explored the role of reactive astrocyte overactivation in neurodegeneration after METH exposure.

METHODS

METH bulk RNA sequencing data (GSE107015 and GSE98793) and single-cell RNA sequencing data (GSE119861) were obtained from the GEO database. We performed immune infiltration analysis on the bulk RNA data. After cell clustering using the single-cell RNA data, astrocytes were extracted for downstream analysis. Differentially expressed genes (DEGs) were identified from the bulk and single-cell RNA sequencing datasets, and GO, KEGG, and GSEA pathway analyses were performed. The PPI network and random forest methods were performed on the overlapping genes of the DEGs to screen hub genes. To explore the common ground between METH exposure and neurodegenerative diseases, we applied a random forest algorithm to PD chip data (GSE99039 and GSE72267) to establish a diagnostic model using the hub genes in METH. New object recognition and the Morris water maze were used to examine cognitive function in mice exposed to METH for 14 days in vivo. Astrocytes were cocultured with neurons for the detection of intercellular crosstalk.

RESULTS

DEGs in the METH group significantly enriched pathways related to NDs, inflammation, and the NF-κB signaling pathway. Immune infiltration analysis revealed significantly increased infiltration of monocytes, T cells, and NK cells and decreased infiltration of neutrophils in the METH group. An intersection of 44 hub genes was screened based on the PPI network and random forest algorithm. These genes suggest that there might be similar pathogenesis between METH exposure and PD. METH exposure resulted in learning memory impairment, hippocampal astrocyte activation, and upregulation of NF-κB expression in mice. Activation of reactive astrocytes cocultured with neurons causes neural damage.

CONCLUSIONS

This study explored the crosstalk between astrocytes and neurons in METH exposure, providing a potential pathogenesis to explore the altered immune microenvironment involving reactive astrocytes after METH exposure.

Epigenetic clock analysis reveals increased plasma cystatin C levels based on DNA methylation in major depressive disorder

Major depressive disorder (MDD) is a common mental illness and a major public health concern worldwide. Depression is associated with epigenetic changes that regulate gene expression, and analyzing these changes may help elucidate the pathophysiology of MDD. Genome-wide DNA methylation (DNAm) profiles can function as 'epigenetic clocks' that can help estimate biological aging. Here, we assessed biological aging in patients with MDD using various DNAm-based indicators of epigenetic aging. We used a publicly available dataset containing data obtained from the whole blood samples of MDD patients (n = 489) and controls (n = 210). We analyzed five epigenetic clocks (HorvathAge, HannumAge, SkinBloodAge, PhenoAge, and GrimAge) and DNAm-based telomere length (DNAmTL). We also investigated seven DNAm-based age-predictive plasma proteins (including cystatin C) and smoking status, which are components of GrimAge. Following adjustment for confounding factors such as age and sex, patients with MDD showed no significant difference in epigenetic clocks and DNAmTL. However, DNAm-based plasma cystatin C levels were significantly higher in patients with MDD than controls. Our findings revealed specific DNAm changes predicting plasma cystatin C levels in MDD. These findings may help elucidate the pathophysiology of MDD, leading to the development of new biomarkers and medications.