Blood transcriptional response to treatment-resistant depression during electroconvulsive therapy

An integrated machine learning framework for developing and validating a diagnostic model of major depressive disorder based on interstitial cystitis-related genes

BACKGROUND

Major depressive disorder (MDD) and interstitial cystitis (IC) are two highly debilitating conditions that often coexist with reciprocal effect, significantly exacerbating patients' suffering. However, the molecular underpinnings linking these disorders remain poorly understood.

METHODS

Transcriptomic data from GEO datasets including those of MDD and IC patients was systematically analyzed to develop and validate our model. Following removal of batch effect, differentially expressed genes (DEGs) between respective disease and control groups were identified. Shared DEGs of the conditions then underwent functional enrichment analyses. Additionally, immune infiltration analysis was quantified through ssGSEA. A diagnostic model for MDD was constructed by exploring 113 combinations of 12 machine learning algorithms with 10-fold cross-validation on the training sets following by external validation on test sets. Finally, the "Enrichr" platform was utilized to identify potential drugs for MDD.

RESULTS

Totally, 21 key genes closely associated with both MDD and IC were identified, predominantly involved in immune processes based on enrichment analyses. Immune infiltration analysis revealed distinct profiles of immune cell infiltration in MDD and IC compared to healthy controls. From these genes, a robust 11-gene (ABCD2, ATP8B4, TNNT1, AKR1C3, SLC26A8, S100A12, PTX3, FAM3B, ITGA2B, OLFM4, BCL7A) diagnostic signature was constructed, which exhibited superior performance over existing MDD diagnostic models both in training and testing cohorts. Additionally, epigallocatechin gallate and 10 other drugs emerged as potential targets for MDD.

CONCLUSION

Our work developed a diagnostic model for MDD employing a combination of bioinformatic techniques and machine learning methods, focusing on shared genes between MDD and IC.

Comparison of microRNA expression levels in patients with schizophrenia before and after electroconvulsive therapy

OBJECTIVE

Exploring the role of microRNAs in the antipsychotic efficacy of electroconvulsive therapy (ECT) will contribute to understanding the underlying mechanism through which ECT exerts its therapeutic effects. The primary objective of this study was to identify microRNA alterations before and after ECT in patients with schizophrenia.

METHODS

We compared microarray-based microRNA profiles in peripheral blood from eight patients with schizophrenia before and after ECT and eight healthy controls. Then, we aimed to validate selected differentially expressed microRNAs in 30 patients with schizophrenia following a course of ECT, alongside 30 healthy controls by using quantitative reverse-transcription PCR.

RESULTS

Microarray-based expression profiling revealed alterations in 681 microRNAs when comparing pre- and post-ECT samples. Subsequent quantitative reverse-transcription PCR analysis of the selected microRNAs (miR-20a-5p and miR-598) did not reveal any statistical differences between pre- and post-ECT samples nor between pre-ECT samples and those of healthy controls.

CONCLUSION

As neuroepigenetic studies on ECT are still in their infancy, the results reported in this study are best interpreted as exploratory outcomes. Additional studies are required to explore the potential epigenetic mechanisms underlying the therapeutic efficacy of ECT.

miRNAs in treatment-resistant depression: a systematic review

BACKGROUND

Treatment-resistant depression (TRD) is a condition in a subset of depressed patients characterized by resistance to antidepressant medications. The global prevalence of TRD has been steadily increasing, yet significant advancements in its diagnosis and treatment remain elusive despite extensive research efforts. The precise underlying pathogenic mechanisms are still not fully understood. Epigenetic mechanisms play a vital role in a wide range of diseases. In recent years, investigators have increasingly focused on the regulatory roles of miRNAs in the onset and progression of TRD. miRNAs are a class of noncoding RNA molecules that regulate the translation and degradation of their target mRNAs via interaction, making the exploration of their functions in TRD essential for elucidating their pathogenic mechanisms.

METHODS AND RESULTS

A systematic search was conducted in four databases, namely PubMed, Web of Science, Cochrane Library, and Embase, focusing on studies related to treatment-resistant depression and miRNAs. The search was performed using terms individually or in combination, such as "treatment-resistant depression," "medication-resistant depression," and "miRNAs." The selected articles were reviewed and collated, covering the time period from the inception of each database to the end of February 2024. We found that miRNAs play a crucial role in the pathophysiology of TRD through three main aspects: 1) involvement in miRNA-mediated inflammatory responses (including miR-155, miR-345-5p, miR-146a, and miR-146a-5p); 2) influence on 5-HT transport processes (including miR-674,miR-708, and miR-133a); and 3) regulation of synaptic plasticity (including has-miR-335-5p,has-miR- 1292-3p, let-7b, and let-7c). Investigating the differential expression and interactions of these miRNAs could contribute to a deeper understanding of the molecular mechanisms underlying TRD.

CONCLUSIONS

miRNAs might play a pivotal role in the pathogenesis of TRD. Gaining a deeper understanding of the roles and interrelations of miRNAs in TRD will contribute to elucidating disease pathogenesis and potentially provide avenues for the development of novel diagnostic and therapeutic strategies.

Cerebrospinal fluid exploratory proteomics and ketamine metabolite pharmacokinetics in human volunteers after ketamine infusion

Ketamine is a treatment for both refractory depression and chronic pain syndromes. In order to explore ketamine's potential mechanism of action and whether ketamine or its metabolites cross the blood brain barrier, we examined the pharmacokinetics of ketamine and its metabolites-norketamine (NK), dehydronorketamine (DHNK), and hydroxynorketamines (HNKs)-in cerebrospinal fluid (CSF) and plasma, as well as in an exploratory proteomic analysis in the CSF of nine healthy volunteers who received ketamine intravenously (0.5 mg/kg IV). We found that ketamine, NK, and (2R,6R;2S,6S)-HNK readily crossed the blood brain barrier. Additionally, 354 proteins were altered in the CSF in at least two consecutive timepoints (p < 0.01). Proteins in the classes of tyrosine kinases, cellular adhesion molecules, and growth factors, including insulin, were most affected, suggesting an interplay of altered neurotransmission, neuroplasticity, neurogenesis, synaptogenesis, and neural network functions following ketamine administration.

A systematic mini-review of epigenetic mechanisms associated with electroconvulsive therapy in humans

Introduction

Electroconvulsive therapy (ECT) is one of the most effective strategies for treating resistant major depression. Although the mechanism of action is not fully understood and studies are limited, epigenetics is a promising area for the development of biomarkers associated with ECT treatment response.

Aim

We reviewed studies available in the literature that explored the epigenetics of ECT in peripheral samples from patients with major depressive disorder (MDD).

Methods

A systematic review was performed following The PRISMA guidelines. The search was performed in seven electronic databases: Scopus, Web of Science, Medline, PsycINFO, Embase, Cochrane, and Cinahl.

Results

Nine studies were included. Seven assessed DNA methylation and three investigated microRNAs (miR). Overall, most studies were exploratory, with small sample sizes, and we found high heterogeneity between the study’s design, ECT protocols, molecular biology methods, and epigenetic findings. Investigated candidates with some evidence of association with ECT treatment response were BDNF, S100A10, RNF213M, TNKS, FKBP5, miR-126, miR-106a, and miR-24.

Conclusion

The present findings seem to support previous preclinical research, suggesting that epigenetic mechanisms play an important role in the molecular mechanism underlying ECT effects.

An insight into the sprawling microverse of microRNAs in depression pathophysiology and treatment response

Stress-related neuropathologies are pivotal in developing major depressive disorder (MDD) and are often governed by gene-regulatory changes. Being a stress-responsive gene-regulatory factor, microRNAs (miRNAs) have tremendous biomolecular potential to define an altered gene-regulatory landscape in the MDD brain. MiRNAs' regulatory roles in the MDD brain are closely aligned with changes in plasticity, neurogenesis, and stress-axis functions. MiRNAs act at the epigenetic interface between stress-induced environmental stimuli and cellular pathologies by triggering large-scale gene expression changes in a highly coordinated fashion. The parallel changes in peripheral circulation may provide an excellent opportunity for miRNA to devise more effective treatment strategies and help explore their potential as biomarkers in treatment response. This review discusses the role of miRNAs as epigenetic modifiers in the etiopathogenesis of MDD. Concurrently, key research is highlighted to show the progress in using miRNAs as predictive biomarkers for treatment response.

Understanding treatment-resistant depression using "omics" techniques: A systematic review

BACKGROUND

Treatment-resistant depression (TRD) results in huge healthcare costs and poor patient clinical outcomes. Most studies have adopted a "candidate mechanism" approach to investigate TRD pathogenesis, however this is made more challenging due to the complex and heterogeneous nature of this condition. High-throughput "omics" technologies can provide a more holistic view and further insight into the underlying mechanisms involved in TRD development, expanding knowledge beyond already-identified mechanisms. This systematic review assessed the information from studies that examined TRD using hypothesis-free omics techniques.

METHODS

PubMed, MEDLINE, Embase, APA PsycInfo, Scopus and Web of Science databases were searched on July 2022. 37 human studies met the eligibility criteria, totalling 17,518 TRD patients, 571,402 healthy controls and 62,279 non-TRD depressed patients (including antidepressant responders and untreated MDD patients).

RESULTS

Significant findings were reported that implicate the role in TRD of various molecules, including polymorphisms, genes, mRNAs and microRNAs. The pathways most commonly reported by the identified studies were involved in immune system and inflammation, neuroplasticity, calcium signalling and neurotransmitters.

LIMITATIONS

Small sample sizes, variability in defining TRD, and heterogeneity in study design and methodology.

CONCLUSIONS

These findings provide insight into TRD pathophysiology, proposing future research directions for novel drug targets and potential biomarkers for clinical staging and response to antidepressants (citalopram/escitalopram in particular) and electroconvulsive therapy (ECT). Further validation is warranted in large prospective studies using standardised TRD criteria. A multi-omics and systems biology strategy with a collaborative effort will likely deliver robust findings for translation into the clinic.