Genetic similarities and differences among distinct definitions of depression

Epigenetic Aging in Major Depressive Disorder: Clocks, Mechanisms and Therapeutic Perspectives

Depression, a chronic mental disorder characterized by persistent sadness, loss of interest, and difficulty in daily tasks, impacts millions globally with varying treatment options. Antidepressants, despite their long half-life and minimal effectiveness, leave half of patients undertreated, highlighting the need for new therapies to enhance well-being. Epigenetics, which studies genetic changes in gene expression or cellular phenotype without altering the underlying Deoxyribonucleic Acid (DNA) sequence, is explored in this article. This article delves into the intricate relationship between epigenetic mechanisms and depression, shedding light on how environmental stressors, early-life adversity, and genetic predispositions shape gene expression patterns associated with depression. We have also discussed Histone Deacetylase (HDAC) inhibitors, which enhance cognitive function and mood regulation in depression. Non-coding RNAs, (ncRNAs) such as Long Non-Coding RNAs (lncRNAs) and micro RNA (miRNAs), are highlighted as potential biomarkers for detecting and monitoring major depressive disorder (MDD). This article also emphasizes the reversible nature of epigenetic modifications and their influence on neuronal growth processes, underscoring the dynamic interplay between genetics, environment, and epigenetics in depression development. It explores the therapeutic potential of targeting epigenetic pathways in treating clinical depression. Additionally, it examines clinical findings related to epigenetic clocks and their role in studying depression and biological aging.

Clinical data mining: challenges, opportunities, and recommendations for translational applications

Clinical data mining of predictive models offers significant advantages for re-evaluating and leveraging large amounts of complex clinical real-world data and experimental comparison data for tasks such as risk stratification, diagnosis, classification, and survival prediction. However, its translational application is still limited. One challenge is that the proposed clinical requirements and data mining are not synchronized. Additionally, the exotic predictions of data mining are difficult to apply directly in local medical institutions. Hence, it is necessary to incisively review the translational application of clinical data mining, providing an analytical workflow for developing and validating prediction models to ensure the scientific validity of analytic workflows in response to clinical questions. This review systematically revisits the purpose, process, and principles of clinical data mining and discusses the key causes contributing to the detachment from practice and the misuse of model verification in developing predictive models for research. Based on this, we propose a niche-targeting framework of four principles: Clinical Contextual, Subgroup-Oriented, Confounder- and False Positive-Controlled (CSCF), to provide guidance for clinical data mining prior to the model's development in clinical settings. Eventually, it is hoped that this review can help guide future research and develop personalized predictive models to achieve the goal of discovering subgroups with varied remedial benefits or risks and ensuring that precision medicine can deliver its full potential.

Research trend of epigenetics and depression: adolescents' research needs to strengthen

Objective

With its high prevalence, depression's pathogenesis remains unclear. Recent attention has turned to the interplay between depression and epigenetic modifications. However, quantitative bibliometric analyses are lacking. This study aims to visually analyze depression epigenetics trends, utilizing bibliometric tools, while comprehensively reviewing its epigenetic mechanisms.

Methods

Utilizing the Web of Science core dataset, we collected depression and epigenetics-related studies. Employing VOSViewer software, we visualized data on authors, countries, journals, and keywords. A ranking table highlighted field leaders.

Results

Analysis encompassed 3,469 depression epigenetics studies published from January 2002 to June 2023. Key findings include: (1) Gradual publication growth, peaking in 2021; (2) The United States and its research institutions leading contributions; (3) Need for enhanced collaborations, spanning international and interdisciplinary efforts; (4) Keyword clustering revealed five main themes-early-life stress, microRNA, genetics, DNA methylation, and histone acetylation-highlighting research hotspots; (5) Limited focus on adolescent depression epigenetics, warranting increased attention.

Conclusion

Taken together, this study revealed trends and hotspots in depression epigenetics research, underscoring global collaboration, interdisciplinary fusion, and multi-omics data's importance. It discussed in detail the potential of epigenetic mechanisms in depression diagnosis and treatment, advocating increased focus on adolescent research in this field. Insights aid researchers in shaping their investigative paths toward understanding depression's epigenetic mechanisms and antidepressant interventions.

Reviewing the role of gut microbiota in the pathogenesis of depression and exploring new therapeutic options

The relationship between gut microbiota (GM) and mental health is one of the focuses of psychobiology research. In recent years, the microbial-gut-brain axis (MGBA) concept has gradually formed about this bidirectional communication between gut and brain. But how the GM is involved in regulating brain function and how they affect emotional disorders these mechanisms are tenuous and limited to animal research, and often controversial. Therefore, in this review, we attempt to summarize and categorize the latest advances in current research on the mechanisms of GM and depression to provide valid information for future diagnoses and therapy of mental disorders. Finally, we introduced some antidepressant regimens that can help restore gut dysbiosis, including classic antidepressants, Chinese materia medica (CMM), diet, and exogenous strains. These studies provide further insight into GM's role and potential pathways in emotion-related diseases, which holds essential possible clinical outcomes for people with depression or related psychiatric disorders. Future research should focus on clarifying the causal role of GM in disease and developing microbial targets, applying these findings to the prevention and treatment of depression.