Scientific Issues Relevant to Improving the Diagnosis, Risk Assessment, and Treatment of Major Depression

Serum KNG and FVIII may serve as potential biomarkers for depression

BACKGROUND

The global burden of major depressive disorder (MDD) is rising, with current diagnostic methods hindered by significant subjectivity and low inter-rater reliability. Several studies have implied underlying link between coagulation-related proteins, such as kininogen (KNG) and coagulation factor VIII (FVIII), and depressive symptoms, offering new insights into the exploration of depression biomarkers. This study aims to elucidate the roles of KNG and FVIII in depression, potentially providing a foundational basis for biomarker research in this field.

METHODS

A three-part experiment was conducted: (1) we measured serum levels of KNG and FVIII in the chronic unpredictable mild stress (CUMS) model; (2) KNG adeno-associated-virus overexpression (KNG-AAV-OE) model was constructed to further investigate the roles of KNG and FVIII. Meanwhile, quantity PCR, western blotting and immunofluorescence staining detected the KNG-FVIII pathway. (3) Peripheral blood samples were gathered from healthy control (HC, N = 21), as well as first-episode drug-naive patients with MDD (FEDN-MDD, N = 21), to further confirm the association between KNG, FVIII and depression.

RESULTS

Firstly, serum KNG and FVIII levels were significantly elevated in the CUMS model. Then, the rats exhibited pronounced depressive-like behaviors in the KNG-AAV-OE model, with corresponding increases in serum KNG and FVIII. Lastly, clinical data showed increased KNG and FVIII levels in FEDN-MDD compared to HC. Furthermore, KNG and FVIII levels exhibited a strong positive correlation with the scores of the 24-item Hamilton Depression Scale and the 14-item Hamilton Anxiety Scale.

CONCLUSION

To sum up, this study highlights critical roles of serum KNG and FVIII in depression and the KNG-AAV-OE may lead the augment of FVIII in serum. Consequently, our research may offer new evidence and foundation for depression biomarkers research in the future.

Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorder

Biobanks often contain several phenotypes relevant to diseases such as major depressive disorder (MDD), with partly distinct genetic architectures. Researchers face complex tradeoffs between shallow (large sample size, low specificity/sensitivity) and deep (small sample size, high specificity/sensitivity) phenotypes, and the optimal choices are often unclear. Here we propose to integrate these phenotypes to combine the benefits of each. We use phenotype imputation to integrate information across hundreds of MDD-relevant phenotypes, which significantly increases genome-wide association study (GWAS) power and polygenic risk score (PRS) prediction accuracy of the deepest available MDD phenotype in UK Biobank, LifetimeMDD. We demonstrate that imputation preserves specificity in its genetic architecture using a novel PRS-based pleiotropy metric. We further find that integration via summary statistics also enhances GWAS power and PRS predictions, but can introduce nonspecific genetic effects depending on input. Our work provides a simple and scalable approach to improve genetic studies in large biobanks by integrating shallow and deep phenotypes.

Acute but not long-lasting antidepressant-like effect of psilocybin in differential reinforcement of low-rate 72 schedule in rats

BACKGROUND

In clinical studies, psychedelics including psilocybin and D-lysergic acid diethylamide (LSD) demonstrate rapid and persistent antidepressant effects. Since the effective treatment with psychedelics is usually provided with psychotherapy, it is debatable whether their prolonged efficacy can be observed in infrahuman species. Preclinical reports on psychedelics' effects most often address their acute actions, and different tests and models provide inconsistent results. The goal of this study was to examine whether the treatment with psilocybin and/or LSD would demonstrate immediate and/or sustained antidepressant-like effects in the differential reinforcement of low-rate responding (DRL) schedule in rats. In contrast to the antidepressant screening tools, the DRL 72s test is known to detect antidepressants with high predictive validity as it differentiates clinically effective antidepressants from other psychoactive drugs in non-stressed animals.

METHODS

Adult male Sprague Dawley rats were injected over three consecutive days with psilocybin (1 mg/kg), LSD (0.08 mg/kg), or saline and then tested in DRL 72s for the following 4 weeks.

RESULTS

Treatment with psilocybin but not LSD demonstrated an immediate antidepressant-like effect, manifested as an increased number of reinforced presses and response efficiency. By contrast, neither of the drugs showed a long-term (up to 4 weeks following administration) antidepressant-like effect.

CONCLUSIONS

Using DRL 72s schedule of reinforcement, we demonstrated the acute antidepressant-like effect of psilocybin but not of LSD, and failed to detect their persistent antidepressant-like efficacy. The present study suggests that the detection of long-lasting antidepressant-like activity in rats could be challenging and may require entirely novel behavioral methods.

Biological Diagnosis of Depression: A Biomarker Panel from Several Nonspecial Indicators Instead of the Specific Biomarker(s)

It is a consensus that the diagnosis efficiency of depression is rather low in clinic. The traditional way of diagnosing depression by symptomatology is flawed. Recent years, a growing body of evidence has underlined the importance of physiological indicators in the diagnosis of depression. However, the diagnosis of depression is difficult to be like some common clinical diseases, which have clear physiological indicators. A single physiological index provides limited information to clinicians and is of little help in the diagnosis of depression. Thus, it is more rational and practical to diagnose depression with a biomarker panel, which covers a few non-specific indicators, such as hormones, cytokines, and neurotrophins. This open review suggested that biomarker panel had a bright future in creating a new model of depression diagnosis or at least providing a reference to the existing depression criteria. The viewpoint is also the future of other psychiatric diagnosis.

MicroRNAs as Critical Biomarkers of Major Depressive Disorder: A Comprehensive Perspective

Major Depressive Disorder (MDD) represents a major global health concern, a body-mind malady of rising prevalence worldwide nowadays. The complex network of mechanisms involved in MDD pathophysiology is subjected to epigenetic changes modulated by microRNAs (miRNAs). Serum free or vesicles loaded miRNAs have starred numerous publications, denoting a key role in cell-cell communication, systematically and in brain structure and neuronal morphogenesis, activity and plasticity. Upregulated or downregulated expression of these signaling molecules may imply the impairment of genes implicated in pathways of MDD etiopathogenesis (neuroinflammation, brain-derived neurotrophic factor (BDNF), neurotransmitters, hypothalamic-pituitary-adrenal (HPA) axis, oxidative stress, circadian rhythms...). In addition, these miRNAs could serve as potential biomarkers with diagnostic, prognostic and predictive value, allowing to classify severity of the disease or to make decisions in clinical management. They have been considered as promising therapy targets as well and may interfere with available antidepressant treatments. As epigenetic malleable regulators, we also conclude emphasizing lifestyle interventions with physical activity, mindfulness and diet, opening the door to new clinical management considerations.

Multivariate Machine Learning Analyses in Identification of Major Depressive Disorder Using Resting-State Functional Connectivity: A Multicentral Study

Diagnosis of major depressive disorder (MDD) using resting-state functional connectivity (rs-FC) data faces many challenges, such as the high dimensionality, small samples, and individual difference. To assess the clinical value of rs-FC in MDD and identify the potential rs-FC machine learning (ML) model for the individualized diagnosis of MDD, based on the rs-FC data, a progressive three-step ML analysis was performed, including six different ML algorithms and two dimension reduction methods, to investigate the classification performance of ML model in a multicentral, large sample dataset [1021 MDD patients and 1100 normal controls (NCs)]. Furthermore, the linear least-squares fitted regression model was used to assess the relationships between rs-FC features and the severity of clinical symptoms in MDD patients. Among used ML methods, the rs-FC model constructed by the eXtreme Gradient Boosting (XGBoost) method showed the optimal classification performance for distinguishing MDD patients from NCs at the individual level (accuracy = 0.728, sensitivity = 0.720, specificity = 0.739, area under the curve = 0.831). Meanwhile, identified rs-FCs by the XGBoost model were primarily distributed within and between the default mode network, limbic network, and visual network. More importantly, the 17 item individual Hamilton Depression Scale scores of MDD patients can be accurately predicted using rs-FC features identified by the XGBoost model (adjusted R² = 0.180, root mean squared error = 0.946). The XGBoost model using rs-FCs showed the optimal classification performance between MDD patients and HCs, with the good generalization and neuroscientifical interpretability.

Synthesizing the Evidence for Ketamine and Esketamine in Treatment-Resistant Depression: An International Expert Opinion on the Available Evidence and Implementation

Replicated international studies have underscored the human and societal costs associated with major depressive disorder. Despite the proven efficacy of monoamine-based antidepressants in major depression, the majority of treated individuals fail to achieve full syndromal and functional recovery with the index and subsequent pharmacological treatments. Ketamine and esketamine represent pharmacologically novel treatment avenues for adults with treatment-resistant depression. In addition to providing hope to affected persons, these agents represent the first non-monoaminergic agents with proven rapid-onset efficacy in major depressive disorder. Nevertheless, concerns remain about the safety and tolerability of ketamine and esketamine in mood disorders. Moreover, there is uncertainty about the appropriate position of these agents in treatment algorithms, their comparative effectiveness, and the appropriate setting, infrastructure, and personnel required for their competent and safe implementation. In this article, an international group of mood disorder experts provides a synthesis of the literature with respect to the efficacy, safety, and tolerability of ketamine and esketamine in adults with treatment-resistant depression. The authors also provide guidance for the implementation of these agents in clinical practice, with particular attention to practice parameters at point of care. Areas of consensus and future research vistas are discussed.

The State of Our Understanding of the Pathophysiology and Optimal Treatment of Depression: Glass Half Full or Half Empty?

Major depressive disorder is a remarkably common and often severe psychiatric disorder associated with high levels of morbidity and mortality. Patients with major depression are prone to several comorbid psychiatric conditions, including posttraumatic stress disorder, anxiety disorders, obsessive-compulsive disorder, and substance use disorders, and medical conditions, including cardiovascular disease, diabetes, stroke, cancer, which, coupled with the risk of suicide, result in a shortened life expectancy. The goal of this review is to provide an overview of our current understanding of major depression, from pathophysiology to treatment. In spite of decades of research, relatively little is known about its pathogenesis, other than that risk is largely defined by a combination of ill-defined genetic and environmental factors. Although we know that female sex, a history of childhood maltreatment, and family history as well as more recent stressors are risk factors, precisely how these environmental influences interact with genetic vulnerability remains obscure. In recent years, considerable advances have been made in beginning to understand the genetic substrates that underlie disease vulnerability, and the interaction of genes, early-life adversity, and the epigenome in influencing gene expression is now being intensively studied. The role of inflammation and other immune system dysfunction in the pathogenesis of major depression is also being intensively investigated. Brain imaging studies have provided a firmer understanding of the circuitry involved in major depression, providing potential new therapeutic targets. Despite a broad armamentarium for major depression, including antidepressants, evidence-based psychotherapies, nonpharmacological somatic treatments, and a host of augmentation strategies, a sizable percentage of patients remain nonresponsive or poorly responsive to available treatments. Investigational agents with novel mechanisms of action are under active study. Personalized medicine in psychiatry provides the hope of escape from the current standard trial-and-error approach to treatment, moving to a more refined method that augurs a new era for patients and clinicians alike.

Psilocybin for depression: Considerations for clinical trial design

Background and aims

Given the enormous global burden of depressive illness, there is an urgent need to develop novel and more effective treatments for major depressive disorder (MDD). Recent findings have suggested that psychedelic drugs may have a role in the treatment of depressive symptoms, and a number of groups are in the process of developing protocols to study this question systematically. Given the subjective quality of both the psychedelic experience and depressive symptomatology, great care must be taken when designing a protocol to study the clinical efficacy of psychedelic drugs. This study will discuss many factors to consider when designing a clinical trial of psilocybin for MDD.

Methods

We provide a thorough review of pertinent research into antidepressant clinical trial methodology and review practical considerations that are relevant to the study of psychedelic-assisted treatment for depression.

Results

We discuss participant selection (including diagnostic accuracy, exclusion criteria, characteristics of the depressive episode, and the use of concurrent medications), study interventions (including dosing regimens, placebo selection, non-pharmacological components of treatment, and the importance of blinding), trial duration, outcome measures, and safety considerations.

Conclusions

Careful and transparent study design and data analysis will maximize the likelihood of generating meaningful, reproducible results, and identifying a treatment-specific effect. Meeting the highest standards for contemporary trial design may also broaden the acceptance of psychedelic research in the scientific community at large.