The HPA Axis as Target for Depression

Depression, stress, and tryptophan metabolism through the kynurenine pathway: treatment strategies from the perspective of Chinese herbal medicine

The pathogenesis of depression is complex, involving abnormalities in tryptophan (TRP) metabolism through the kynurenine pathway (KP). Moreover, depression is closely related to the hypothalamic-pituitary-adrenal (HPA) axis, the gut-brain axis, neuroinflammation, and stress. These factors collectively influence the multidimensional pathological mechanisms of depression. TRP, a fundamental amino acid, serves as a precursor for neuroactive metabolites vital to physiological functions. Central to TRP metabolism is the KP, and the imbalance between neurotoxic and neuroprotective metabolites is closely related to the onset and progression of depression. Therefore, maintaining the balance of KP metabolites is important. In this review, we have investigated the role of the KP in depression and explored the complexity of KP dysregulation and its therapeutic importance. Here, we highlight how a deeper understanding of the KP and its regulation can pave the way for new treatment strategies. Specifically, we have summarized the latest advances in elucidating the key mechanisms of rate-limiting enzyme inhibitors, providing insights into their potential therapeutic efficacy. In addition, we have explored the emerging field of Chinese herbal medicine, discussing its potential to regulate KP metabolites and alleviate depressive symptoms, thereby expanding the treatment options for depression. Our findings emphasize the multifaceted nature of depression and the necessity of interdisciplinary research to fully utilize KP regulation and Chinese herbal medicine as strategies to advance the treatment of depression.

Is There such a Thing as Post-Viral Depression?: Implications for Precision Medicine

Viral infections are increasingly recognized as triggers for depressive disorders, particularly following the SARS-CoV-2 pandemic and the rise of long COVID. Viruses such as Herpes Simplex Virus (HSV), Epstein-Barr Virus (EBV), Cytomegalovirus (CMV), and Human Immunodeficiency Virus (HIV) are linked to depression through complex neurobiological mechanisms. These include immune system dysregulation, chronic inflammation, and neurotransmitter imbalances that affect brain function and mood regulation. Viral activation of the immune system leads to the release of pro-inflammatory cytokines, resulting in neuroinflammation and associated depressive symptoms. Furthermore, specific viruses can disrupt neurotransmitter systems, including serotonin, dopamine, and glutamate, all of which are essential for mood stabilization. The unique interactions of different viruses with these systems underscore the need for virus-specific therapeutic approaches. Current broad-spectrum treatments often overlook the precise neurobiological pathways involved in post-viral depression, reducing their efficacy. This review emphasizes the need to understand these virus-specific interactions to create tailored interventions that directly address the neurobiological effects induced by each type of virus. These interventions may include immunomodulatory treatments that target persistent inflammation, antiviral therapies to reduce the viral load, or neuroprotective strategies that restore neurotransmitter balance. Precision medicine offers promising avenues for the effective management of virus-induced depression, providing patient-specific approaches that address the specific biological mechanisms involved. By focusing on the development of these targeted treatments, this review aims to pave the way for a new era in psychiatric care that fully addresses the root causes of depression induced by viral infections.

Deep phenotyping reveals CRH and FKBP51-dependent behavioral profiles following chronic social stress exposure in male mice

The co-chaperone FKBP51, encoded by FKBP5 gene, is recognized as a psychiatric risk factor for anxiety and depressive disorders due to its crucial role in the stress response. Another key modulator in stress response regulation is the corticotropin releasing hormone (CRH), which is co-expressed with FKBP51 in many stress-relevant brain-regions and cell-types. Together, they intricately influence the balance of the hypothalamic-pituitary-adrenal (HPA) axis, one of the primary stress response systems. Previous research underscores the potential moderating effects these genes have on the regulation of the stressful life events towards the vulnerability of major depressive disorder (MDD). However, the specific function of FKBP51 in CRH-expressing neurons remains largely unexplored. Here, through deep behavioral phenotyping, we reveal heightened stress effects in mice lacking FKBP51 in CRH co-expressing neurons (CRHFKBP5-/-), particularly evident in social contexts. Our findings highlight the importance of considering cell-type specificity and context in comprehending stress responses and advocate for the utilization of machine-learning-driven phenotyping of mouse models. By elucidating these intricacies, we lay down the groundwork for personalized interventions aimed at enhancing stress resilience and individual well-being.

Predicting Depression Among Chinese Patients with Narcolepsy Type 1: A Machine-Learning Approach

Objective

Depression is a common psychiatric issue among patients with narcolepsy type 1 (NT1). Effective management requires accurate screening and prediction of depression in NT1 patients. This study aims to identify relevant factors for predicting depression in Chinese NT1 patients using machine learning (ML) approaches.

Methods

A total of 203 drug-free NT1 patients (aged 5-61), diagnosed based on the ICSD-3 criteria, were consecutively recruited from the Sleep Medicine Center at Peking University People's Hospital between September 2019 and April 2023. Depression, daytime sleepiness, and impulsivity were assessed using the Center for Epidemiologic Studies Depression Scale for Children (CES-DC) or the Self-Rating Depression Scale (SDS), the Epworth Sleepiness Scale for adult or children and adolescents (ESS or ESS-CHAD), and the Barratt Impulse Scale (BIS-11). Demographic characteristics and objective sleep parameters were also analyzed. Three ML models-Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM)-were used to predict depression. Model performance was evaluated using receiver operating curve (AUC), accuracy, precision, recall, F1 score, and decision curve analysis (DCA).

Results

The LR model identified hallucinations (OR 2.21, 95% CI 1.01-4.90, p = 0.048) and motor impulsivity (OR 1.10, 95% CI 1.02-1.18, p = 0.015) as predictors of depression. Among the ML models, SVM showed the best performance with an AUC of 0.653, accuracy of 0.659, sensitivity of 0.727, and F1 score of 0.696, reflecting its effectiveness in integrating sleep-related and psychosocial factors.

Conclusion

This study highlights the potential of ML models for predicting depression in NT1 patients. The SVM model shows promise in identifying patients at high risk of depression, offering a foundation for developing a data-driven, personalized decision-making tool. Further research should validate these findings in diverse populations and include additional psychological variables to enhance model accuracy.

Connecting the dots: sex, depression, and musculoskeletal health

Depression and multiple musculoskeletal disorders are overrepresented in women compared with men. Given that depression is a modifiable risk factor and improvement of depressive symptoms increases positive outcomes following orthopedic intervention, efforts to improve clinical recognition of depressive symptoms and increased action toward ameliorating depressive symptoms among orthopedic patients are positioned to reduce complications and positively affect patient-reported outcomes. Although psychosocial factors play a role in the manifestation and remittance of depression, it is also well appreciated that primary biochemical changes are capable of causing and perpetuating depression. Unique insight for novel treatments of depression may be facilitated by query of the bidirectional relationship between musculoskeletal health and depression. This Review aims to synthesize the diverse literature on sex, depression, and orthopedics and emphasize the potential for common underlying biological substrates. Given the overrepresentation of depression and musculoskeletal disorders among women, increased emphasis on the biological drivers of the co-occurrence of these disorders is positioned to improve women's health.

Microbiota-gut-brain axis in health and neurological disease: Interactions between gut microbiota and the nervous system

Along with mounting evidence that gut microbiota and their metabolites migrate endogenously to distal organs, the 'gut-lung axis,' 'gut-brain axis,' 'gut-liver axis' and 'gut-renal axis' have been established. Multiple animal recent studies have demonstrated gut microbiota may also be a key susceptibility factor for neurological disorders such as Alzheimer's disease, Parkinson's disease and autism. The gastrointestinal tract is innervated by the extrinsic sympathetic and vagal nerves and the intrinsic enteric nervous system, and the gut microbiota interacts with the nervous system to maintain homeostatic balance in the host gut. A total of 1507 publications on the interactions between the gut microbiota, the gut-brain axis and neurological disorders are retrieved from the Web of Science to investigate the interactions between the gut microbiota and the nervous system and the underlying mechanisms involved in normal and disease states. We provide a comprehensive overview of the effects of the gut microbiota and its metabolites on nervous system function and neurotransmitter secretion, as well as alterations in the gut microbiota in neurological disorders, to provide a basis for the possibility of targeting the gut microbiota as a therapeutic agent for neurological disorders.

The CRF/Urocortin systems as therapeutic targets for alcohol use disorders

Development and maintenance of alcohol use disorders have been proposed to recruit critical mechanisms involving Corticotropin Releasing Factor and Urocortins (CRF/Ucns). The CRF/Ucns system is comprised of a family of peptides (CRF, Ucn 1, Ucn 2, Ucn 3) which act upon two receptor subtypes, CRFR1 and CRFR2, each with different affinity profiles to the endogenous peptides and differential brain distribution. Activity of CRF/Ucn system is further modulated by CRF binding protein (CRF-BP), which regulates availability of CRF and Ucns to exert their actions. Extensive evidence in preclinical models support the involvement of CRF/Ucn targets in escalated alcohol drinking, as well as point to changes in CRF/Ucn brain function as a result of chronic alcohol exposure and/or withdrawal. It highlights the role of CRF and CRFR1-mediated signaling in conditions of excessive alcohol taking and seeking, including during various stages of withdrawal and relapse to alcohol. Besides its role in the hypothalamic-pituitary-adrenal (HPA) axis, the importance of extra-hypothalamic CRF pathways, especially in the extended amygdala, in the neurobiology of alcohol abuse and dependence is emphasized. Emerging roles for other targets of the CRF/Ucn system, such as CRF2 receptors, CRF-BP and Ucns in escalated alcohol drinking is also discussed. Finally, the limited translational value of CRF/Ucn interventions in stress-related and alcohol use disorders is discussed. So far, CRFR1 antagonists have shown little or no efficacy in human clinical trials, although a range of unexplored conditions and possibilities remain to be explored.

Advances in biosensors for major depressive disorder diagnostic biomarkers

Depression is one of the most common mental disorders and is mainly characterized by low mood or lack of interest and pleasure. It can be accompanied by varying degrees of cognitive and behavioral changes and may lead to suicide risk in severe cases. Due to the subjectivity of diagnostic methods and the complexity of patients' conditions, the diagnosis of major depressive disorder (MDD) has always been a difficult problem in psychiatry. With the discovery of more diagnostic biomarkers associated with MDD in recent years, especially emerging non-coding RNAs (ncRNAs), it is possible to quantify the condition of patients with mental illness based on biomarker levels. Point-of-care biosensors have emerged due to their advantages of convenient sampling, rapid detection, miniaturization, and portability. After summarizing the pathogenesis of MDD, representative biomarkers, including proteins, hormones, and RNAs, are discussed. Furthermore, we analyzed recent advances in biosensors for detecting various types of biomarkers of MDD, highlighting representative electrochemical sensors. Future trends in terms of new biomarkers, new sample processing methods, and new detection modalities are expected to provide a complete reference for psychiatrists and biomedical engineers.

Association of hair cortisol concentration with brain-derived neurotrophic factor gene methylation: The role of sex as a moderator

Hair cortisol concentration (HCC) reflects the long-term activity of the hypothalamus-pituitary-adrenal (HPA) axis in response to stress. Brain-derived neurotrophic factor DNA methylation (BDNF DNAM) may affect HCC, and sex and Val66Met may contribute to this association. Thus, the aim of this study was to investigate the associations between HCC and Brain-derived neurotrophic factor (BDNF) DNAM, and the moderating effects of Val66Met and sex. We recruited 191 healthy young participants (96 women, mean age 23.0 ± 2.6 years) and collected body samples to evaluate HCC, and to determine BDNF DNAM and Val66Met genotypes. We analyzed the effects of BDNF DNAM, sex, and Val66Met on HCC. We also evaluated the associations between BDNF DNAM and HCC in groups separated by sex and genotypes. We found a marked association of BDNF DNAM with HCC across men and women. After dividing the data by sex, a positive correlation of HCC with BDNF DNAM was found only in women. There was no substantial moderation effect of Val66Met genotypes on the association between BDNF DNAM and HCC. Therefore, BDNF DNAM was found to have positive association with HCC only in healthy young women, indicating that sex moderates the association of BDNF DNAM with long-term HPA axis activity.

Potential antidepressant effects of Traditional Chinese botanical drug formula Chaihu-Shugan-San and its active ingredients

Background: Depression is a severe mental disorder that poses a significant threat to both the physical and mental wellbeing of individuals. Currently, there are various methods for treating depression, including traditional Chinese herbal formulations like Chaihu-Shugan-San (CSS), which have shown effective antidepressant effects in both clinical and animal research. Objective: This review aims to provide a comprehensive synthesis of evidence related to CSS, considering both preclinical and clinical studies, to uncover its potential multi-level, multi-pathway, and multi-target mechanisms for treating depression and identify its active ingredients. Methods: A thorough search was conducted in electronic databases, including PubMed, MEDLINE, Web of Science, Google Scholar, CNKI, and Wanfang, using keywords such as "Chaihu Shugan" and "depression" to retrieve relevant literature on CSS and its active ingredients. The review process adhered to the PRISMA guidelines. Results: This review consolidates the mechanisms underlying antidepressant effects of CSS and its active ingredients. It emphasizes its involvement in the regulation of monoaminergic neurotransmitter systems, synaptic plasticity, and the hypothalamic-pituitary-adrenal axis, among other aspects. Conclusion: CSS exerts a pivotal role in treating depression through various pathways, including the monoaminergic neurotransmitter system, the hypothalamic-pituitary-adrenal axis, synaptic plasticity, inflammation, brain-derived neurotrophic factor levels, and the brain-gut axis. This review facilitates a comprehensive understanding of the current state of CSS research, fostering an in-depth exploration of the etiological mechanisms of depression and the potential discovery of novel antidepressant drugs.

The protective role of ginsenoside Rg3 in heart diseases and mental disorders

Ginsenoside Rg3, a compound derived from Panax ginseng C. A. Mey., is increasingly recognized for its wide range of pharmacological effects. Under the worldwide healthcare challenges posed by heart diseases, Rg3 stands out as a key subject in modern research on Chinese herbal medicine, offering a novel approach to therapy. Mental illnesses are significant contributors to global disease mortality, and there is a well-established correlation between cardiac and psychiatric conditions. This connection is primarily due to dysfunctions in the sympathetic-adrenomedullary system (SAM), the hypothalamic-pituitary-adrenal axis, inflammation, oxidative stress, and brain-derived neurotrophic factor impairment. This review provides an in-depth analysis of Rg3's therapeutic benefits and its pharmacological actions in treating cardiac and mental health disorders respectively. Highlighting its potential for the management of these conditions, Rg3 emerges as a promising, multifunctional therapeutic agent.

Biomarker-Guided Tailored Therapy in Major Depression

This chapter provides a comprehensive examination of a broad range of biomarkers used for the diagnosis and prediction of treatment outcomes in major depressive disorder (MDD). Genetic, epigenetic, serum, cerebrospinal fluid (CSF), and neuroimaging biomarkers are analyzed in depth, as well as the integration of new technologies such as digital phenotyping and machine learning. The intricate interplay between biological and psychological elements is emphasized as essential for tailoring MDD management strategies. In addition, the evolving link between psychotherapy and biomarkers is explored to uncover potential associations that shed light on treatment response. This analysis underscores the importance of individualized approaches in the treatment of MDD that integrate advanced biological insights into clinical practice to improve patient outcomes.