Peripheral biomarkers of major depression and antidepressant treatment response: Current knowledge and future outlooks

tiRNA-Gly-GCC-001 in major depressive disorder: Promising diagnostic and therapeutic biomarker

BACKGROUND AND PURPOSE

In major depressive disorder (MDD), exploration of biomarkers will be helpful in diagnosing the disorder as well as in choosing a treatment and predicting the treatment response. Currently, tRNA-derived small ribonucleic acids (tsRNAs) have been established as promising non-invasive biomarker candidates that may enable a more reliable diagnosis or monitoring of various diseases. Herein, we aimed to explore tsRNA expression together with functional activities in MDD development.

EXPERIMENTAL APPROACH

Serum samples were obtained from patients with MDD and healthy controls, and small RNA sequencing (RNA-Seq) was used to profile tsRNA expression. Dysregulated tsRNAs in MDD were validated by quantitative real-time polymerase chain reaction (qRT-PCR). The diagnostic utility of specific tsRNAs and the expression of these tsRNAs after antidepressant treatment were analysed.

KEY RESULTS

In total, 38 tsRNAs were significantly differentially expressed in MDD samples relative to healthy individuals (34 up-regulated and 4 down-regulated). qRT-PCR was used to validate the expression of six tsRNAs that were up-regulated in MDD (tiRNA-1:20-chrM.Ser-GCT, tiRNA-1:33-Gly-GCC-1, tRF-1:22-chrM.Ser-GCT, tRF-1:31-Ala-AGC-4-M6, tRF-1:31-Pro-TGG-2 and tRF-1:32-chrM.Gln-TTG). Interestingly, serum tiRNA-Gly-GCC-001 levels exhibited an area under the ROC curve of 0.844. Moreover, tiRNA-Gly-GCC-001 is predicted to suppress brain-derived neurotrophic factor (BDNF) expression. Furthermore, significant tiRNA-Gly-GCC-001 down-regulation was evident following an 8-week treatment course and served as a promising baseline predictor of patient response to antidepressant therapy.

CONCLUSION AND IMPLICATIONS

Our current work reports for the first time that tiRNA-Gly-GCC-001 is a promising MDD biomarker candidate that can predict patient responses to antidepressant therapy.

Homotherapy-for-heteropathy of Bupleurum Chinense DC.-Scutellaria baicalensis Georgi in treating depression and colorectal cancer: A network pharmacology and animal model approach

ETHNOPHARMACOLOGICAL RELEVANCE

Bupleurum chinense DC.-Scutellaria baicalensis Georgi (BS) is a classic drug pair that has good clinical effects on depression and many tumors. However, the concurrent targeting mechanism of how the aforementioned drug pair is valid in the two distinct diseases, has not been clarified yet.

AIM OF THE STUDY

The components of BS were detected by LC-MS, combined with network pharmacology to explore the active ingredients and common targeting mechanism of its multi-pathway regulation of BS in treating depression and CRC, and to validate the dual effects of BS using the CUMS mice model and orthotopic transplantation tumor mice model of CRC.

RESULTS

Twenty-nine components were screened, 84 common gene targets were obteined, and the top 5 key targets including STAT3, PIK3R1, PIK3CA, AKT1, IL-6 were identified by PPI network. GO and KEGG analyses revealed that PI3K/AKT and JAK/STAT signaling pathways might play a crucial role of BS in regulating depression and CRC. BS significantly modulated CUMS-induced depressive-like behavior, attenuated neuronal damage, and reduced serum EPI and NE levels in CUMS model mice. BS improved the pathological histological changes of solid tumors and liver tissues and inhibited solid tumors and liver metastases in tumor-bearing mice. BS significantly decreased the proteins' expression of IL-6, p-JAK2, p-STAT3, p-PI3K, p-AKT1 in hippocampal tissues and solid tumors, and regulated the levels of IL-2, IL-6 and IL-10 in serum of two models of mice.

CONCLUSION

BS can exert dual antidepressant and anti-CRC effects by inhibiting the expression of IL-6/JAK2/STAT3 and PI3K/AKT pathway proteins and regulating the release of inflammatory cytokines.

Metabolomics in Depression: What We Learn from Preclinical and Clinical Evidences

Depression is one of the predominant common mental illnesses that affects millions of people of all ages worldwide. Random mood changes, loss of interest in routine activities, and prevalent unpleasant senses often characterize this common depreciated mental illness. Subjects with depressive disorders have a likelihood of developing cardiovascular complications, diabesity, and stroke. The exact genesis and pathogenesis of this disease are still questionable. A significant proportion of subjects with clinical depression display inadequate response to antidepressant therapies. Hence, clinicians often face challenges in predicting the treatment response. Emerging reports have indicated the association of depression with metabolic alterations. Metabolomics is one of the promising approaches that can offer fresh perspectives into the diagnosis, treatment, and prognosis of depression at the metabolic level. Despite numerous studies exploring metabolite profiles post-pharmacological interventions, a quantitative understanding of consistently altered metabolites is not yet established. The article gives a brief discussion on different biomarkers in depression and the degree to which biomarkers can improve treatment outcomes. In this review article, we have systemically reviewed the role of metabolomics in depression along with current challenges and future perspectives.

ProMENDA: an updated resource for proteomic and metabolomic characterization in depression

Depression is a prevalent mental disorder with a complex biological mechanism. Following the rapid development of systems biology technology, a growing number of studies have applied proteomics and metabolomics to explore the molecular profiles of depression. However, a standardized resource facilitating the identification and annotation of the available knowledge from these scattered studies associated with depression is currently lacking. This study presents ProMENDA, an upgraded resource that provides a platform for manual annotation of candidate proteins and metabolites linked to depression. Following the establishment of the protein dataset and the update of the metabolite dataset, the ProMENDA database was developed as a major extension of its initial release. A multi-faceted annotation scheme was employed to provide comprehensive knowledge of the molecules and studies. A new web interface was also developed to improve the user experience. The ProMENDA database now contains 43,366 molecular entries, comprising 20,847 protein entries and 22,519 metabolite entries, which were manually curated from 1370 human, rat, mouse, and non-human primate studies. This represents a significant increase (more than 7-fold) in molecular entries compared to the initial release. To demonstrate the usage of ProMENDA, a case study identifying consistently reported proteins and metabolites in the brains of animal models of depression was presented. Overall, ProMENDA is a comprehensive resource that offers a panoramic view of proteomic and metabolomic knowledge in depression. ProMENDA is freely available at https://menda.cqmu.edu.cn .

A comprehensive Mendelian randomization study highlights the relationship between psychiatric disorders and non-tumor gastrointestinal diseases

Objective

Previous observational studies revealed the potential correlation between psychiatric disorders (PDs) and non-tumor gastrointestinal diseases (NTGDs). However, their causation remains unclear.

Methods

We explored the causal relationship between PDs and NTGDs through bidirectional two-sample Mendelian randomization (MR) study. Large-scale genome-wide association study (GWAS) summary statistics and bidirectional two-sample MR study were used to assess the causality between PDs and NTGDs. Multiple sensitivity analyses were used to identify the robustness of our results.

Results

We found that major depression was causally associated with increased risk of gastric ulcer (OR: 1.812, 95% CI: 1.320-2.487, p < 0.001) and irritable bowel syndrome (OR: 1.645, 95% CI: 1.291-2.097, p < 0.001). Meanwhile, genetically predicted gastroesophageal reflux disease contributed to the increased risk of anxiety disorders (OR: 1.425, 95% CI: 1.295-1.568, p < 0.001), and ulcerative colitis was related to increased risk of attention deficit/hyperactivity disorder (OR: 1.042, 95% CI: 1.008-1.078, p = 0.0157).

Conclusion

Our study provided MR evidence to support the close causality and identify the specific direction between eight PDs and eight common NTGDs. Experimental studies to further examine the causality, underlying mechanism, and therapeutic potential of PDs and NTGDs are required.

Apple polyphenol extract ameliorates sugary-diet-induced depression-like behaviors in male C57BL/6 mice by inhibiting the inflammation of the gut-brain axis

To explore whether apple polyphenol extract (APE) ameliorates sugary-diet-induced depression-like behaviors, thirty male C57BL/6 mice (3-4 weeks old) were assigned to three groups randomly to receive different treatments for 8 consecutive weeks: (1) control group (CON), (2) S-HSD group (60% high sucrose diet feeding with 0.1 mg mL-1 sucralose solution as drinking water), and (3) S-APE group (S-HSD feeding with 500 mg per (kg bw day) APE solution gavage). The S-HSD group showed significant depression-like behaviors compared with the CON group, which was manifested by an increased number of buried marbles in the marble burying test, prolonged immobility time in both the tail suspension test and forced swimming test, and cognitive impairment based on the Morris water maze test. However, APE intervention significantly improved the depression-like behaviors by reducing serum levels of corticosterone and adrenocorticotropic hormone, and increasing the serum level of IL-10. Moreover, APE intervention inhibited the activation of the NF-κB inflammatory pathway, elevated colonic MUC-2 protein expression, and elevated the colonic and hippocampal tight junction proteins of occludin and ZO-1. Furthermore, APE intervention increased the richness and diversity of gut microbiota by regulating the composition of microbiota, with increased relative abundance of Firmicutes and Bacteroidota, decreased relative abundance of Verrucomicrobiota at the phylum level, significantly lowered relative abundance of Akkermansia at the genus level, and rebalanced abnormal relative abundance of Muribaculaceae_unclassified, Coriobacteriaceae_UCG-002, and Lachnoclostridium induced by S-HSD feeding. Thus, our study supports the potential application of APE as a dietary intervention for ameliorating depression-like behavioral disorders.

Exploring Predictors of Ketamine Response in Adolescent Treatment-Resistant Depression

Objective: Ketamine has proved effective as a rapid-acting antidepressant agent, but treatment is not effective for everyone (approximately a quarter to a half of patients). Some adult studies have begun to investigate predictors of ketamine's antidepressant response, but no studies have examined this in adolescents with depression. Methods: We conducted a secondary data analysis of adolescents who participated in a randomized, single-dose, midazolam-controlled crossover trial of ketamine for adolescents with treatment-resistant depression. We examined the relationship between 19 exploratory demographic and clinical variables and depression symptom improvement (using the Montgomery-Åsberg Depression Rating Scale [MADRS]) at 1 and 7 days postinfusion. Results: Subjects who had fewer medication trials of both antidepressant medications and augmentation treatments were more likely to experience depression symptom improvement with ketamine. Subjects with shorter duration of their current depressive episode were more likely to experience depression symptom improvement with ketamine. Subjects currently being treated with selective serotonin reuptake inhibitor medications, and not being treated with serotonin-norepinephrine reuptake inhibitor medications, also experienced greater symptom improvement with ketamine. When receiving the midazolam control, less severe depressive symptoms, as measured by the Children's Depression Rating Scale (CDRS) (but not MADRS), and a comorbid attention-deficit/hyperactivity disorder diagnosis were associated with increased response. Conclusions: Findings should be viewed as preliminary and exploratory given the small sample size and multiple secondary analyses. Identifying meaningful predictors of ketamine response is important to inform future therapeutic use of this compound, however, considerably more research is warranted before such clinical guidance is established. The trial was registered in clinicaltrials.gov with the identifier NCT02579928.

Alcohol use associated alterations in the circulating metabolite profile in the general population and in individuals with major depressive disorder

Our aim was to evaluate whether alcohol use is associated with changes in the circulating metabolite profile similar to those present in persons with depression. If so, these findings could partially explain the link between alcohol use and depression. We applied a targeted liquid chromatography mass spectrometry method to evaluate correlates between concentrations of 86 circulating metabolites and self-reported alcohol use in a cohort of the non-depressed general population (GP) (n = 247) and a cohort of individuals with major depressive disorder (MDD) (n = 99). Alcohol use was associated with alterations in circulating concentrations of metabolites in both cohorts. Our main finding was that self-reported alcohol use was negatively correlated with serum concentrations of hippuric acid in the GP cohort. In the GP cohort, consumption of six or more doses per week was associated with low hippuric acid concentrations, similar to those observed in the MDD cohort, but in these individuals it was regardless of their level of alcohol use. Reduced serum concentrations of hippuric acid suggest that already moderate alcohol use is associated with depression-like changes in the serum levels of metabolites associated with gut microbiota and liver function; this may be one possible molecular level link between alcohol use and depression.

TCF4 and RBFOX1 as peripheral biomarkers for the differential diagnosis and treatment of major depressive disorder

BACKGROUND

Recent genome-wide association studies on major depressive disorder (MDD) have indicated the involvement of LRFN5 and OLFM4; however, the expression levels and roles of these molecules in MDD remain unclear. The present study aimed to determine the serum levels of TCF4 and RBFOX1 in patients with MDD and to investigate whether these molecules could be used as biomarkers for MDD diagnosis.

METHODS

The study included 99 drug-naïve MDD patients, 90 drug-treated MDD patients, and 81 healthy controls (HCs). Serum TCF4 and RBFOX1 levels were measured by ELISA. Pearson's correlation analysis was conducted to determine the association between TCF4/RBFOX1 and clinical variables. Linear support vector machine classifier was used to evaluate the diagnostic capabilities of TCF4 and RBFOX1.

RESULTS

Serum TCF4 and RBFOX1 levels were substantially higher in MDD patients than in HCs and significantly lower in drug-treated MDD patients than in drug-naïve MDD patients. Moreover, serum TCF4 and RBFOX1 levels were associated with the Hamilton Depression Scale score, duration of illness, serum lipids levels, and hepatic function. Thus, both these molecules showed potential as biomarkers for MDD. TCF4 and RBFOX1 combination exhibited a higher diagnostic performance, with the mean area under the curve values of 0.9861 and 0.9936 in the training and testing sets, respectively.

LIMITATIONS

Small sample size and investigation of only the peripheral nervous system.

CONCLUSIONS

TCF4 and RBFOX1 may be involved in the pathogenesis of MDD, and their combination may serve as a diagnostic biomarker panel for MDD.

Assessing the risk of prenatal depressive symptoms in Chinese women: an integrated evaluation of serum metabolome, multivitamin supplement intake, and clinical blood indicators

Background

Prenatal depressive symptoms (PDS) is a serious public health problem. This study aimed to develop an integrated panel and nomogram to assess at-risk populations by examining the association of PDS with the serum metabolome, multivitamin supplement intake, and clinical blood indicators.

Methods

This study comprised 221 pregnant women, categorized into PDS and non-PDS groups based on the Edinburgh postnatal depression scale. The participants were divided into training and test sets according to their enrollment time. We conducted logistic regression analysis to identify risk factors, and employed liquid chromatography/high resolution mass spectrometry-based serum metabolome analysis to identify metabolic biomarkers. Multiple factor analysis was used to combine risk factors, clinical blood indicators and key metabolites, and then a nomogram was developed to estimate the probability of PDS.

Results

We identified 36 important differential serum metabolites as PDS biomarkers, mainly involved in amino acid metabolism and lipid metabolism. Multivitamin intake works as a protective factor for PDS. The nomogram model, including multivitamin intake, HDL-C and three key metabolites (histidine, estrone and valylasparagine), exhibited an AUC of 0.855 in the training set and 0.774 in the test set, and the calibration curves showed good agreement, indicating that the model had good stability.

Conclusion

Our approach integrates multiple models to identify metabolic biomarkers for PDS, ensuring their robustness. Furthermore, the inclusion of dietary factors and clinical blood indicators allows for a comprehensive characterization of each participant. The analysis culminated in an intuitive nomogram based on multimodal data, displaying potential performance in initial PDS risk assessment.

Circadian light therapy and light dose for depressed young people: a systematic review and meta-analysis

Background

Empirical evidence has shown that light therapy (LT) can reduce depression symptoms by stimulating circadian rhythms. However, there is skepticism and inconclusive results, along with confusion regarding dosing. The purpose of this study is to quantify light as a stimulus for the circadian system and create a dose-response relationship that can help reduce maladies among adolescents and young adults (AYAs). This will provide a reference for light exposure and neural response, which are crucial in the neuropsychological mechanism of light intervention. The study also aims to provide guidance for clinical application.

Methods

The latest quantitative model of CLA (circadian light) and CSt,f (circadian stimulus) was adopted to quantify light dose for circadian phototransduction in youth depression-related light therapy. Articles published up to 2023 through Web of Science, Cochrane Library, Medline (OVID), CINAHL, APA PsycINFO, Embase, and Scholars were retrieved. A meta-analysis of 31 articles (1,031 subjects) was performed using Stata17.0, CMA3.0 (comprehensive meta-analysis version 3.0) software, and Python 3.9 platform for light therapy efficacy comparison and dose-response quantification.

Results

Under various circadian stimulus conditions (0.1 < CSt,f < 0.7) of light therapy (LT), malady reductions among AYAs were observed (pooled SMD = -1.59, 95%CI = -1.86 to -1.32; z = -11.654, p = 0.000; I2 = 92.8%), with temporal pattern (p = 0.044) and co-medication (p = 0.000) suggested as main heterogeneity sources. For the efficacy advantage of LT with a higher circadian stimulus that is assumed to be influenced by visualization, co-medication, disease severity, and time pattern, sets of meta-analysis among random-controlled trials (RCTs) found evidence for significant efficacy of circadian-active bright light therapy (BLT) over circadian-inactive dim red light (SMD = -0.65, 95% CI = -0.96 to -0.34; z = -4.101, p = 0.000; I2 = 84.9%) or circadian-active dimmer white light (SMD = -0.37, 95% CI = -0.68 to -0.06; z = -2.318, p = 0.02; I2 = 33.8%), whereas green-blue, circadian-active BLT showed no significant superiority over circadian-inactive red/amber light controls (SMD = -0.21, 95% CI = -0.45 to 0.04; z = -2.318, p = 0.099; I2 = 0%). Overall, circadian-active BLT showed a greater likelihood of clinical response than dim light controls, with increased superiority observed with co-medication. For pre-to-post-treatment amelioration and corresponding dose-response relationship, cumulative duration was found more influential than other categorical (co-medication, severity, study design) or continuous (CSt,f) variables. Dose-response fitting indicated that the therapeutic effect would reach saturation among co-medicated patients at 32-42 days (900-1,000 min) and 58-59 days (1,100-1,500 min) among non-medicated AYAs. When exerting high circadian stimulus of light therapy (0.6 < CSt,f < 0.7), there was a significantly greater effect size in 1,000-1,500 min of accumulative duration than <1,000 or >1,500 min of duration, indicating a threshold for practical guidance.

Limitations

The results have been based on limited samples and influenced by a small sample effect. The placebo effect could not be ignored.

Conclusions

Although the superiority of LT with higher circadian stimulus over dimmer light controls remains unproven, greater response potentials of circadian-active BLT have been noticed among AYAs, taking co-medication, disease severity, time pattern, and visual characteristics into consideration. The dose-response relationship with quantified circadian stimulus and temporal pattern had been elaborated under various conditions to support clinical depression treatment and LT device application in the post-pandemic era.

[Movement as a Neuromodulator: How Physical Activity Influences the Physiology of Adolescent Depression]

Movement as a Neuromodulator: How Physical Activity Influences the Physiology of Adolescent Depression Abstract: In the context of adolescent depression, physical activity is becoming increasingly recognized for its positive effects on neuropathology. Current scientific findings indicate that physical training affects the biological effects of depression during adolescence. Yet the pathophysiology of adolescent depression is not yet fully understood. Besides psychosocial and genetic influences, various neurobiological factors are being discussed. One explanation model describes a dysfunction of the hypothalamus-pituitary-adrenal axis (HPA axis) with a sustained elevation in cortisol concentration. Recent studies highlight neuroimmunological processes and a reduced concentration of growth factors as causative factors. These changes appear to lead to a dysregulation of the excitation and inhibition balance of the cerebral cortex as well as to cerebral morphological alterations. Regular physical training can potentially counteract the dysregulation of the HPA axis and normalize cortisol levels. The release of proinflammatory cytokines is inhibited, and the expression of growth factors involved in adult neurogenesis is stimulated. One should ensure the synergistic interaction of biological and psychosocial factors when designing the exercise schedule (endurance or strength training, group or individual sports, frequency, duration, and intensity). Addressing these open questions is essential when integrating physical activity into the guidelines for treating depressive disorders in children and adolescents.

Protein Plasma Levels of the IGF Signalling System Are Altered in Major Depressive Disorder

The Insulin-like growth factor 2 (IGF-2) has been recently proven to alleviate depressive-like behaviors in both rats and mice models. However, its potential role as a peripheral biomarker has not been evaluated in depression. To do this, we measured plasma IGF-2 and other members of the IGF family such as Binding Proteins (IGFBP-1, IGFBP-3, IGFBP-5 and IGFBP-7) in a depressed group of patients (n = 51) and in a healthy control group (n = 48). In some of these patients (n = 15), we measured these proteins after a period (19 ± 6 days) of treatment with antidepressants. The Hamilton Depressive Rating Scale (HDRS) and the Self-Assessment Anhedonia Scale (SAAS) were used to measure depression severity and anhedonia, respectively. The general cognition state was assessed by the Mini-Mental State Examination (MMSE) test and memory with the Free and Cued Selective Reminding Test (FCSRT). The levels of both IGF-2 and IGFBP-7 were found to be significantly increased in the depressed group; however, only IGF-2 remained significantly elevated after correction by age and sex. On the other hand, the levels of IGF-2, IGFBP-3 and IGFBP-5 were significantly decreased after treatment, whereas only IGFBP-7 was significantly increased. Therefore, peripheral changes in the IGF family and their response to antidepressants might represent alterations at the brain level in depression.

Biomarkers of Postpartum Depression: A Narrative Review

Postpartum depression (PPD) is a disorder that impairs the formation of the relationship between mother and child, and reduces the quality of life for affected women to a functionally significant degree. Studying markers associated with PPD can help in early detection, prevention, or monitoring treatment. The purpose of this paper is to review biomarkers linked to PPD and to present selected theories on the pathogenesis of the disease based on data from biomarker studies. The complex etiology of the disorder reduces the specificity and sensitivity of markers, but they remain a valuable source of information to help clinicians. The biggest challenge of the future will be to translate high-tech methods for detecting markers associated with postpartum depression into more readily available and less costly ones. Population-based studies are needed to test the utility of potential PPD markers.

Mental stress objective screening for workers using urinary neurotransmitters

BACKGROUND

Almost 10% of the population develop depression or anxiety disorder during their lifetime. Considering that people who are exposed to high stress are more likely to develop mental disorders, it is important to detect and remove mental stress before depression or anxiety disorder develops. We aimed to develop an objective screening test that quantifies mental stress in workers so that they can recognize and remove it before the disorder develops.

METHODS

We obtained urine specimens from 100 healthy volunteers (49 men and 51 women; age = 48.2 ± 10.8 years) after they received medical checks and answered the Brief Job Stress Questionnaire (BJSQ). Participants were divided into high- and low- stress groups according to their total BJSQ scores. We further analyzed six urinary neurotransmitters (dopamine, serotonin, 5-hydoroxyindoleacetic acid, gamma-aminobutyric acid, homovanillic acid, and vanillylmandelic acid) using liquid chromatography-mass spectrometry to compare their levels between the two groups.

RESULTS

We obtained the concentrations of the six analytes from 100 examinees and revealed that the levels of urinary dopamine (p = 0.0042) and homovanillic acid (p = 0.020) were significantly lower in the high-stress group than those in the low-stress group. No biases were observed between the two groups in 36 laboratory items. The stress index generated from the six neurotransmitter concentrations recognized high-stress group significantly. Moreover, we discovered that the level of each urinary neurotransmitter changed depending on various stress factors, such as dissatisfaction, physical fatigue, stomach and intestine problems, poor appetite, poor working environments, sleep disturbance, isolation, worry, or insecurity.

CONCLUSION

We revealed that urinary neurotransmitters could be a promising indicator to determine underlying mental stress. This study provides clues for scientists to develop a screening test not only for workers but also for patients with depression.

Meta-analysis of soluble tumour necrosis factor receptors in severe mental illnesses

Tumour necrosis factor (TNF), as an innate immune defense molecule, functions through binding to TNF receptor 1 (TNFR1) or TNF receptor 2 (TNFR2). Peripheral levels of soluble TNFR1 (sTNFR1) and soluble TNFR2 (sTNFR2) were widely measured in severe mental illnesses (SMIs) including schizophrenia (SCZ), bipolar disorder (BD) and major depressive disorder (MDD) but inconsistencies existed. Hence, the present meta-analysis was conducted to identify the overall association between plasma/serum sTNFR1 and sTNFR2 levels and SMIs. Published studies were searched using Pubmed and Scopus. Data were analysed using Comprehensive Meta-Analysis version 2. Hedges's g effect sizes and 95% confidence intervals were pooled using fixed-effect or random-effects models. Heterogeneity, publication bias and study quality were assessed. Sensitivity analysis and subgroup analysis were performed. Our findings revealed that sTNFR1 level was significantly higher in SMI, particularly in BD. The sTNFR2 level significantly elevated in SMI but with smaller effect size. These findings further support the association between altered immune system and inflammatory abnormalities in SMI, especially in patients with BD. Subgroup analysis showed that younger age of onset, longer illness duration and psychotropic medication raised both sTNFR levels, especially sTNFR1, as these factors may contribute to the activation of inflammation. Future studies were suggested to identify the causality between TNFR pathway and SCZ, BD and MDD respectively using homogenous group of each SMI, and to determine the longitudinal effect of each psychotropic medication on TNFR pathway.

Non-pharmacological treatment-related changes of molecular biomarkers in major depressive disorder: A systematic review and meta-analysis

Background

Major depressive disorder (MDD) is a serious mood disorder and leading cause of disability. Despite treatment advances, approximately 30% of individuals with MDD do not achieve adequate clinical response. Better understanding the biological mechanism(s) underlying clinical response to specific psychopharmacological interventions may help fine tune treatments in order to further modulate their underlying mechanisms of action. However, little is known regarding the effect of non-pharmacological treatments (NPTs) on candidate molecular biomarker levels in MDD. This review aims to identify molecular biomarkers that may elucidate NPT response for MDD.

Methods

We performed a systematic review and a multilevel linear mixed-effects meta-analyses, and a meta-regression. Searches were performed in PubMed, Scopus, and PsycINFO in October 2020 and July 2021.

Results

From 1387 retrieved articles, 17 and six studies were included in the systematic review and meta-analyses, respectively. Although there was little consensus associating molecular biomarker levels with symptomology and/or treatment response, brain metabolites accessed via molecular biomarker-focused neuroimaging techniques may provide promising information on whether an individual with MDD would respond positively to NPTs. Furthermore, non-invasive brain stimulation interventions significantly increased the expression of neurotrophic factors (NTFs) compared to sham/placebo, regardless of add-on pharmacological treatment.

Conclusions

NTFs are candidate biomarkers to fine-tune NIBS for MDD treatment.

Major depressive disorder: biomarkers and biosensors

Depressive disorders belong to highly heterogeneous psychiatric diseases. Loss of in interest in previously enjoyed activities and a depressed mood are the main characteristics of major depressive disorder (MDD). Moreover, due to significant heterogeneity in clinical presentation and lack of applicable biomarkers, diagnosis and treatment remains challenging. Identification of relevant biomarkers would allow for improved disease classification and more personalized treatment strategies. Herein, we review the current state of these biomarkers and then discuss diagnostic techniques of aimed to specifically target these analytes using state of the art biosensor technology.

Immune Dysregulation in Treatment-Resistant Depression: Precision Approaches to Treatment Selection and Development of Novel Treatments

Owing to the link between immune dysfunction and treatment-resistant depression (TRD) and the overwhelming evidence that the immune dysregulation and major depressive disorder (MDD) are associated with each other, using immune profiles to identify the biological distinct subgroup may be the step forward to understanding MDD and TRD. This report aims to briefly review the role of inflammation in the pathophysiology of depression (and TRD in particular), the role of immune dysfunction to guide precision medicine, tools used to understand immune function, and novel statistical techniques.

Early antidepressant treatment response prediction in major depression using clinical and TPH2 DNA methylation features based on machine learning approaches

OBJECTIVE

To identify DNA methylation and clinical features, and to construct machine learning classifiers to assign the patients with major depressive disorder (MDD) into responders and non-responders after a 2-week treatment into responders and non-responders.

METHOD

Han Chinese patients (291 in total) with MDD comprised the study population. Datasets contained demographic information, environment stress factors, and the methylation levels of 38 methylated sites of tryptophan hydroxylase 2 (TPH2) genes in peripheral blood samples. Recursive Feature Elimination (RFE) was employed to select features. Five classification algorithms (logistic regression, classification and regression trees, support vector machine, logitboost and random forests) were used to establish the models. Performance metrics (AUC, F-Measure, G-Mean, accuracy, sensitivity, specificity, positive predictive value and negative predictive value) were computed with 5-fold-cross-validation. Variable importance was evaluated by random forest algorithm.

RESULT

RF with RFE outperformed the other models in our samples based on the demographic information and clinical features (AUC = 61.2%, 95%CI: 60.1-62.4%) / TPH2 CpGs features (AUC = 66.6%, 95%CI: 65.4-67.8%) / both clinical and TPH2 CpGs features (AUC = 72.9%, 95%CI: 71.8-74.0%).

CONCLUSION

The effects of TPH2 on the early-stage antidepressant response were explored by machine learning algorithms. On the basis of the baseline depression severity and TPH2 CpG sites, machine learning approaches can enhance our ability to predict the early-stage antidepressant response. Some potentially important predictors (e.g., TPH2-10-60 (rs2129575), TPH2-2-163 (rs11178998), age of first onset, age) in early-stage treatment response could be utilized in future fundamental research, drug development and clinical practice.

Age-specific associations between inflammatory markers and remission of depression during antidepressant use

The roles of inflammatory markers in predicting the response to antidepressants are controversial. The levels of inflammatory markers increase with age. Here, we compared the associations of inflammatory markers with remission during 12-week pharmacotherapy according to patient age. Higher high-sensitivity C-reactive protein (hsCRP) levels were associated with non-remission in younger, but not older, patients. However, higher interleukin (IL)-1β and IL-6 levels were associated with non-remission in all patients, regardless of age. Differential associations were observed between inflammatory markers and remission, according to patient age. Patient age should be considered when predicting the response to antidepressants based on serum hsCRP level.

Childhood sexual abuse related to brain activity abnormalities in right inferior temporal gyrus among major depressive disorder

Regional brain activity abnormalities have been reported in major depressive disorder (MDD) with childhood trauma (CT). However, these findings were variable and equivocal. The present study aims to explore further the correlation between CT and the amplitude of low-frequency fluctuations (ALFF) alteration in MDD. In this study, we recruited 60 healthy controls (HCs) and 66 MDD patients to complete resting-state fMRI scans. All MDD patients were evaluated clinical symptoms and childhood trauma experience using the Hamilton Depression Rating Scale-17 (HDRS-17), the Hamilton Anxiety Scale (HAMA), and the Childhood Trauma Questionnaire (CTQ). Compared to HCs, MDD patients demonstrated significantly altered ALFF in the right middle occipital gyrus (MOG), bilateral inferior temporal gyrus (ITG), bilateral cerebellum posterior lobe, bilateral anterior cingulate gyrus (ACC), and bilateral superior frontal gyrus (SFG). More importantly, we found negative correlation between childhood sexual abuse (CSA) scores and ALFF value appeared mainly in the right ITG among MDD patients. After adjusting for covariates (age, gender, mean framewise displacement (FD), HRDS-17, and HAMA scores), this correlation remained significant. Meanwhile, ALFF in the right ITG could distinguish MDD patients with or without CSA (area under the curve (AUC) = 0.713). Our findings revealed that the regional brain activity abnormalities in the right ITG might be a potential biomarker for MDD patients with CSA.

Development and validation of a machine learning-based vocal predictive model for major depressive disorder

BACKGROUND

Variations in speech intonation are known to be associated with changes in mental state over time. Behavioral vocal analysis is an algorithmic method of determining individuals' behavioral and emotional characteristics from their vocal patterns. It can provide biomarkers for use in psychiatric assessment and monitoring, especially when remote assessment is needed, such as in the COVID-19 pandemic. The objective of this study was to design and validate an effective prototype of automatic speech analysis based on algorithms for classifying the speech features related to MDD using a remote assessment system combining a mobile app for speech recording and central cloud processing for the prosodic vocal patterns.

METHODS

Machine learning compared the vocal patterns of 40 patients diagnosed with MDD to the patterns of 104 non-clinical participants. The vocal patterns of 40 patients in the acute phase were also compared to 14 of these patients in the remission phase of MDD.

RESULTS

A vocal depression predictive model was successfully generated. The vocal depression scores of MDD patients were significantly higher than the scores of the non-patient participants (p < 0.0001). The vocal depression scores of the MDD patients in the acute phase were significantly higher than in remission (p < 0.02).

LIMITATIONS

The main limitation of this study is its relatively small sample size, since machine learning validity improves with big data.

CONCLUSIONS

The computerized analysis of prosodic changes may be used to generate biomarkers for the early detection of MDD, remote monitoring, and the evaluation of responses to treatment.

The Serum Brain-Derived Neurotrophic Factor Increases in Serotonin Reuptake Inhibitor Responders Patients with First-Episode, Drug-Naïve Major Depression

Brain-derived neurotrophic factor (BDNF) is a growth factor synthesized in the cell bodies of neurons and glia, which affects neuronal maturation, the survival of nervous system, and synaptic plasticity. BDNF play an important role in the pathophysiology of major depression (MD). The serum BDNF levels changed over time, or with the improvement in depressive symptoms. However, the change of serum BDNF during pharmacotherapy remains obscure in MDD. In particular, the changes in serum BDNF associated with pharmacotherapy have not yet been fully elucidated. The present study aimed to compare the changes in serum BDNF concentrations in first-episode, drug-naive patients with MD treated with antidepressants between treatment-response and treatment-nonresponse groups. The study included 35 inpatients and outpatients composed of 15 males and 20 females aged 36.7 ± 6.8 years at the Department of Psychiatry of our University Hospital. All patients met the DSM-5 diagnostic criteria for MD. The antidepressants administered included paroxetine, duloxetine, and escitalopram. Severity of depressive state was assessed using the 17-item HAMD before and 8 weeks after drug administration. Responders were defined as those whose total HAMD scores at 8 weeks had decreased by 50% or more compared to those before drug administration, while non-responders were those whose total HAMD scores had decreased by less than 50%. Here we showed that serum BDNF levels were not significantly different at any point between the two groups. The responder group, but not the non-responder group, showed statistically significant changes in serum BDNF 0 and serum BDNF 8. The results suggest that the changes of serum BDNF might differ between the two groups. The measurement of serum BDNF has the potential to be a useful predictor of pharmacotherapy in patients with first-episode, drug-naïve MD.

PET imaging of animal models with depressive-like phenotypes

Major depressive disorder is a growing and poorly understood pathology. Due to technical and ethical limitations, a significant proportion of the research on depressive disorders cannot be performed on patients, but needs to be investigated in animal paradigms. Over the years, animal studies have provided new insight in the mechanisms underlying depression. Several of these studies have used PET imaging for the non-invasive and longitudinal investigation of the brain physiology. This review summarises the findings of preclinical PET imaging in different experimental paradigms of depression and compares these findings with observations from human studies. Preclinical PET studies in animal models of depression can be divided into three main different approaches: (a) investigation of glucose metabolism as a biomarker for regional and network involvement, (b) evaluation of the availability of different neuroreceptor populations associated with depressive phenotypes, and (c) monitoring of the inflammatory response in phenotypes of depression. This review also assesses the relevance of the use of PET imaging techniques in animal paradigms for the understanding of specific aspects of the depressive-like phenotypes, in particular whether it might contribute to achieve a more detailed characterisation of the clinical depressive phenotypes for the development of new therapies for depression.

Investigation of the Relationship between Inflammation and Oxidative Stress Markers and Treatment Response in First-Attack Major Depression Patients: A Follow-Up Study

OBJECTIVE

There is a need to biomarkers for major depression (MD). The goals of this study are to compare serum levels of oxidative stress markers malondialdehyde (MDA) and F2-isoprostane and inflammation markers tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6) and C-reactive protein (CRP) between patients with first-episode MD and healthy controls, to investigate the change of these markers after treatment and to investigate the relationship between levels of these markers and treatment response.

METHOD

Our study was performed in 30 first-episode MD patients and 30 healthy volunteers. During the clinical evaluation Hamilton Depression Rating Scale and Clinical Global Impression Scale were applied to the participants. Serum levels of markers were measured at the baseline and after 8 weeks of treatment.

RESULTS

Compared to the control group, first-episode MD patients had significantly higher IL-6, CRP and MDA levels and lower F2- isoprostane levels. There was no difference between the groups in terms of TNF-α levels. TNF-α, IL-6, MDA and F2-isoprostane levels decreased significantly after treatment, whereas there was no significant change in CRP levels with treatment. Baseline F2-isoprostane levels were found to be significantly higher in treatment responders than nonresponders (p<0.05).

CONCLUSION

In our study, it was shown that there are irregularities related to inflammatory processes and oxidative stress in MD, even in patients who had their first-episode and did not take medication, and these irregularities can be resolved after treatment. While there was a relationship between treatment response and baseline F2-isoprostane levels, there was no relationship with other biomarkers.

Efficacy of eicosapentaenoic acid in inflammatory depression: study protocol for a match-mismatch trial

BACKGROUND

Most antidepressant treatment studies have included patients strictly based on the Diagnostic and Statistical Manual of Mental Disorders definition of Major Depressive Disorder (MDD). Given the heterogeneity of MDD, this approach may have obscured inter-patient differences and hampered the development of novel and targeted treatment strategies. An alternative strategy is ​​to use biomarkers to delineate endophenotypes of depression and test if these can be targeted via mechanism-based interventions. Several lines of evidence suggest that "inflammatory depression" is a clinically meaningful subtype of depression. Preliminary data indicate that omega-3 fatty acids, with their anti-inflammatory and neuroprotective properties, may be efficacious in this subtype of depression, and this study aims to test this hypothesis.

METHOD

We conduct a match-mismatch-trial to test if add-on omega-3 fatty acid eicosapentaenoic acid (EPA) reduces depressive symptoms in patients with MDD and systemic low-grade inflammation. MDD patients on a stable antidepressant treatment are stratified at baseline on high sensitivity-C-reactive protein (hs-CRP) levels to a high-inflammation group (hs-CRP ≥ 3 mg/L) or a low-inflammation group (hs-CRP < 3 mg/L). Both groups receive add-on EPA (2 g per day) for 8 weeks with three study visits, all including blood draws. Patients and raters are blind to inflammation status. Primary outcome measure is change in Hamilton Depression Rating Scale score between baseline and week 8. We hypothesize that the inflammation group has a superior antidepressant response to EPA compared to the non-inflammation group. Secondary outcomes include a composite score of "inflammatory depressive symptoms", quality of life, anxiety, anhedonia, sleep disturbances, fatigue, cognitive performance and change in biomarkers relating to inflammation, oxidative stress, metabolomics and cellular aging.

DISCUSSION

In this study we will, for the first time using a match-mismatch trial design, test if omega-3 is an efficacious treatment for inflammatory depression. If our study is successful, it could add to the field of precision psychiatry.

TRIAL REGISTRATION

This trial was registered May 8, 2017 on clinicaltrials.gov under the reference number NCT03143075.

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.

Clinical Utility of Fluid Biomarker in Depressive Disorder

Major depressive disorders are ranked as the single largest contributor to non-fatal health loss and biomarkers could largely improve our routine clinical activity by predicting disease course and guiding treatment. However there is still a dearth of valid biomarkers in the field of psychiatry. The initial assumption that a single biomarker can capture the myriad of complex processes proved to be naive. The purpose of this paper is to critically review the field and to illustrate the possible practical application for routine clinical care. Biomarkers derived from DNA analysis are the ones that have received the most attention. Other potential candidates include circulating transcription products, proteins, and inflammatory markers. DNA polygenic risk scores proved to be useful in other fields of medicine and preliminary results suggest that they could be useful both as risk and diagnostic biomarkers also in depression and for the choice of treatment. A number of other possible fluid biomarkers are currently under investigation for diagnosis, outcome prediction, staging, and stratification of interventions, however research is still needed before they can be used for routine clinical care. When available, clinicians may be able to receive a lab report with detailed information about disease risk, outcome prediction, and specific indications about preferred treatments.

Altered serum adiponectin and interleukin-8 levels are associated in the pathophysiology of major depressive disorder: A case-control study

BACKGROUND

Major depressive disorder (MDD) is a complex mental health condition that results in several obstacles including disabilities, loss of productivity, and economic burdens on both patients and society. Etiopathogenesis of MDD involves several factors such as sociodemographic, genetic, and biological determinants. However, any suitable biomarkers for risk assessment of depression have not been established yet. Alterations of cytokine are assumed to be involved in the pathophysiology and severity of the depressive disorder. Therefore, we aimed to evaluate serum adiponectin and interleukin-8 (IL-8) among MDD patients in Bangladesh.

METHODS

We recruited a total of 63 MDD patients and 94 age-sex matched healthy controls (HCs) in the present study. MDD patients were enrolled from a tertiary care teaching hospital, Dhaka, Bangladesh, and HCs from surrounding parts of Dhaka city. A psychiatrist assessed all the study participants following the criteria mentioned in the DSM-5. We applied the Hamilton depression (Ham-D) rating scale to assess the depression severity. Serum adiponectin and IL-8 levels were determined using ELISA kits (BosterBio, USA).

RESULTS

The mean serum concentration of adiponectin was decreased (30.67±4.43 μg/mL vs. 53.81±5.37 μg/mL), and the IL-8 level was increased (160.93±14.84 pg/mL vs. 88.68±6.33 pg/mL) in MDD patients compared to HCs. Sex-specific scatters plot graphs showed the distribution of adiponectin and IL-8 levels with Ham-D scores in MDD patients. Also, ROC curve analysis demonstrated good predictive performances of serum adiponectin and IL-8 for MDD with the area under the curve (AUC) as 0.895 and 0.806, respectively.

CONCLUSION

The present study findings suggest that alterations of serum adiponectin and IL-8 levels in MDD patients might be involved in the disease process. Therefore, we can use these changes of cytokines in serum levels as early risk assessment tools for depression. The present study findings should be considered preliminary. We propose further interventional studies to evaluate the exact role of adiponectin and IL-8 in depression.

Dietary Polyphenols as Prospective Natural-Compound Depression Treatment from the Perspective of Intestinal Microbiota Regulation

The broad beneficial effects of dietary polyphenols on human health have been confirmed. Current studies have shown that dietary polyphenols are important for maintaining the homeostasis of the intestinal microenvironment. Moreover, the corresponding metabolites of dietary polyphenols can effectively regulate intestinal micro-ecology and promote human health. Although the pathogenesis of depression has not been fully studied, it has been demonstrated that dysfunction of the microbiota-gut-brain axis may be its main pathological basis. This review discusses the interaction between dietary polyphenols and intestinal microbiota to allow us to better assess the potential preventive effects of dietary polyphenols on depression by modulating the host gut microbiota.

The missing mechanistic link: Improving behavioral treatment efficacy for pediatric chronic pain

Pediatric chronic pain is a significant global issue, with biopsychosocial factors contributing to the complexity of the condition. Studies have explored behavioral treatments for pediatric chronic pain, but these treatments have mixed efficacy for improving functional and psychological outcomes. Furthermore, the literature lacks an understanding of the biobehavioral mechanisms contributing to pediatric chronic pain treatment response. In this mini review, we focus on how neuroimaging has been used to identify biobehavioral mechanisms of different conditions and how this modality can be used in mechanistic clinical trials to identify markers of treatment response for pediatric chronic pain. We propose that mechanistic clinical trials, utilizing neuroimaging, are warranted to investigate how to optimize the efficacy of behavioral treatments for pediatric chronic pain patients across pain types and ages.

Identification and Characterization of Elevated Expression of Transferrin and Its Receptor TfR1 in Mouse Models of Depression

Depression has become one of the severe mental disorders threatening global human health. In this study, we first used the proteomics approach to obtain the differentially expressed proteins in the liver between naive control and chronic social defeat stress (CSDS) induced depressed mice. We have identified the upregulation of iron binding protein transferrin (TF) in the liver, the peripheral blood, and the brain in CSDS-exposed mice. Furthermore, bioinformatics analysis of the Gene Expression Omnibus (GEO) database from various mouse models of depression revealed the significantly upregulated transcripts of TF and its receptor TfR1 in multiple brain regions in depressed mice. We also used the recombinant TF administration via the tail vein to detect its permeability through the blood-brain barrier (BBB). We demonstrated the permeability of peripheral TF into the brain through the BBB. Together, these results identified the elevated expression of TF and its receptor TfR1 in both peripheral liver and the central brain in CSDS-induced depressed mice, and peripheral administration of TF can be transported into the brain through the BBB. Therefore, our data provide a compelling information for understanding the potential role and mechanisms of the cross-talk between the liver and the brain in stress-induced depression.

C-reactive protein could predict the efficacy of SSRIs in clinical practice: A cohort study of large samples in the real world

BACKGROUND

C-reactive protein (CRP) has been shown to predict antidepressant treatment outcomes in several trials, but they were limited to small-sample and strictly-restricted conditions. This study plans to verify if CRP can predict antidepressant efficacy in large samples in the real world.

METHODS

918 depressed patients who had tested CRP were included, then were followed up through their outpatient visits or by telephone to obtain information about their medication therapy (SSRIs, SNRIs, MT, NaSSA) and assess efficacy using the Clinical Global Impressions-Improvement scale (CGII). Efficacy was classified as effective and ineffective and CRP was separated into the low CRP group (CRP <1 mg/L, n = 709) and the high CRP group (CRP ≥1 mg/L, n = 209).The efficacy was compared in different groups.

RESULTS

Using Kaplan-Meier survival analysis and Cox proportional regression model to analyze, it was discovered that SNRIs were more effective than SSRIs in treating patients with high CRP(HR = 1.652, p = 0.037,95 % CI:1.031-2.654), and SSRIs were more effective in treating patients with low CRP than those with high CRP (HR = 1.257, p = 0.047,95 % CI:1.003-1.574), while no difference in efficacy between the two groups was found in patients using SNRIs, MT, NaSSA.

LIMITATIONS

Small amounts of MT and NaSSA were included, and some factors that may affect CRP value have not been controlled.

CONCLUSION

CRP could predict the efficacy of SSRIs in the real world, depressed patients with high CRP may be more likely to respond poorly to SSRIs.

The antidepressant effects and serum metabonomics of bifid triple viable capsule in a rat model of chronic unpredictable mild stress

Background

Probiotics have shown potential antidepressant effects. This study evaluated the effect and probable mechanisms of bifid triple viable capsules (BTVCs) on a rat model of chronic unpredictable mild stress (CUMS).

Materials and methods

Rats were randomly divided into Normal, CUMS model, fluoxetine hydrochloride (FLX), BTVCs, and FLX+BTVCs groups. Depressive-like behaviours, pathological changes in the hippocampus, changes in serum metabolites and potential biomarkers, and metabolic pathways were detected via behavioural tests, haematoxylin-eosin staining, nissl staining, non-targetted metabolomics, and ingenuity pathway analysis (IPA).

Results

The rats displayed depressive-like behaviours after CUMS exposure, but BTVCs ameliorated the depressive-like behaviours. In addition, the pathological results showed that the hippocampal tissue was damaged in rats after CUMS exposure and that the damage was effectively alleviated by treatment with BTVCs. A total of 20 potential biomarkers were identified. Treatment with BTVCs regulated D-phenylalanine, methoxyeugenol, (±)-myristoylcarnitine, 18:3 (6Z, 9Z, 12Z) /P-18:1 (11Z), propionyl-L-carnitine, and arachidonic acid (AA) concentrations, all compounds that are involved with biosynthesis of unsaturated fatty acids, glycerophospholipid metabolism, linoleic acid metabolism and AA metabolism. The IPA demonstrated that endothelin-1 signalling and cyclic adenosine monophosphate response element binding protein (CREB) signalling in neurons may be involved in the development of depression.

Conclusion

Our findings suggest that BTVCs can alleviate depressive-like behaviours, restore damage to the hippocampus in CUMS rats and regulate serum metabolism, which may be related to endothelin-1 signalling or CREB signalling in neurons.

The emergence of psychoanalytical electrochemistry: the translation of MDD biomarker discovery to diagnosis with electrochemical sensing

The disease burden and healthcare costs of psychiatric diseases along with the pursuit to understand their underlying biochemical mechanisms have led to psychiatric biomarker investigations. Current advances in evaluating candidate biomarkers for psychiatric diseases, such as major depressive disorder (MDD), focus on determining a specific biomarker signature or profile. The origins of candidate biomarkers are heterogenous, ranging from genomics, proteomics, and metabolomics, while incorporating associations with clinical characterization. Prior to clinical use, candidate biomarkers must be validated by large multi-site clinical studies, which can be used to determine the ideal MDD biomarker signature. Therefore, identifying valid biomarkers has been challenging, suggesting the need for alternative approaches. Following validation studies, new technology must be employed to transition from biomarker discovery to diagnostic biomolecular profiling. Current technologies used in discovery and validation, such as mass spectroscopy, are currently limited to clinical research due to the cost or complexity of equipment, sample preparation, or measurement analysis. Thus, other technologies such as electrochemical detection must be considered for point-of-care (POC) testing with the needed characteristics for physicians' offices. This review evaluates the advantages of using electrochemical sensing as a primary diagnostic platform due to its rapidity, accuracy, low cost, biomolecular detection diversity, multiplexed capacity, and instrument flexibility. We evaluate the capabilities of electrochemical methods in evaluating current candidate MDD biomarkers, individually and through multiplexed sensing, for promising applications in detecting MDD biosignatures in the POC setting.

The role and mechanism of tryptophan - kynurenine metabolic pathway in depression

Major depressive disorder (MDD) is a common mental illness characterized by persistent low mood and anhedonia, normally accompanied with cognitive impairment. Due to its rising incidence and high rate of recurrence and disability, MDD poses a substantial threat to patients' physical and mental health, as well as a significant economic cost to society. However, the etiology and pathogenesis of MDD are still unclear. Chronic inflammation may cause indoleamine-2,3-dioxygenase (IDO) to become overactive throughout the body and brain, resulting in excess quinolinic acid (QUIN) and less kynuric acid (KYNA) in the brain. QUIN's neurotoxicity damages glial cells and neurons, accelerates neuronal apoptosis, hinders neuroplasticity, and causes depression due to inflammation. Therefore, abnormal TRP-KYN metabolic pathway and its metabolites have been closely related to MDD, suggesting changes in the TRP-KYN metabolic pathway might contribute to MDD. In addition, targeting TRP-KYN with traditional Chinese medicine showed promising treatment effects for MDD. This review summarizes the recent studies on the TRP-KYN metabolic pathway and its metabolites in depression, which would provide a theoretical basis for exploring the etiology and pathogenesis of depression.

Blood-based biomarkers of antidepressant response to ketamine and esketamine: A systematic review and meta-analysis

(R,S)-ketamine (ketamine) and its enantiomer (S)-ketamine (esketamine) can produce rapid and substantial antidepressant effects. However, individual response to ketamine/esketamine is variable, and there are no well-accepted methods to differentiate persons who are more likely to benefit. Numerous potential peripheral biomarkers have been reported, but their current utility is unclear. We conducted a systematic review/meta-analysis examining the association between baseline levels and longitudinal changes in blood-based biomarkers, and response to ketamine/esketamine. Of the 5611 citations identified, 56 manuscripts were included (N = 2801 participants), and 26 were compatible with meta-analytical calculations. Random-effect models were used, and effect sizes were reported as standardized mean differences (SMD). Our assessments revealed that more than 460 individual biomarkers were examined. Frequently studied groups included neurotrophic factors (n = 15), levels of ketamine and ketamine metabolites (n = 13), and inflammatory markers (n = 12). There were no consistent associations between baseline levels of blood-based biomarkers, and response to ketamine. However, in a longitudinal analysis, ketamine responders had statistically significant increases in brain-derived neurotrophic factor (BDNF) when compared to pre-treatment levels (SMD [95% CI] = 0.26 [0.03, 0.48], p = 0.02), whereas non-responders showed no significant changes in BDNF levels (SMD [95% CI] = 0.05 [-0.19, 0.28], p = 0.70). There was no consistent evidence to support any additional longitudinal biomarkers. Findings were inconclusive for esketamine due to the small number of studies (n = 2). Despite a diverse and substantial literature, there is limited evidence that blood-based biomarkers are associated with response to ketamine, and no current evidence of clinical utility.

Combinatorial panel with endophenotypes from multilevel information of diffusion tensor imaging and lipid profile as predictors for depression

OBJECTIVE

Clinical heterogeneity in major depressive disorder likely reflects the range of etiology and contributing factors in the disorder, such as genetic risk. Identification of more refined subgroups based on biomarkers such as white matter integrity and lipid-related metabolites could facilitate precision medicine in major depressive disorder.

METHODS

A total of 148 participants (15 genetic high-risk participants, 57 patients with first-episode major depressive disorder and 76 healthy controls) underwent diffusion tensor imaging and plasma lipid profiling. Alterations in white matter integrity and lipid metabolites were identified in genetic high-risk participants and patients with first-episode major depressive disorder. Then, shared alterations between genetic high-risk and first-episode major depressive disorder were used to develop an imaging x metabolite diagnostic panel for genetically based major depressive disorder via factor analysis and logistic regression. A fivefold cross-validation test was performed to evaluate the diagnostic panel.

RESULTS

Alterations of white matter integrity in corona radiata, superior longitudinal fasciculus and the body of corpus callosum and dysregulated unsaturated fatty acid metabolism were identified in both genetic high-risk participants and patients with first-episode major depressive disorder. An imaging x metabolite diagnostic panel, consisting of measures for white matter integrity and unsaturated fatty acid metabolism, was identified that achieved an area under the receiver operating characteristic curve of 0.86 and had a significantly higher diagnostic performance than that using either measure alone. And cross-validation confirmed the adequate reliability and accuracy of the diagnostic panel.

CONCLUSION

Combining white matter integrity in corpus callosum, superior longitudinal fasciculus and corona radiata, and unsaturated fatty acid profile may improve the identification of genetically based endophenotypes in major depressive disorder to advance precision medicine strategies.

Pharmacogenomic biomarkers as source of evidence of the effectiveness and safety of antidepressant therapy

OBJECTIVE

The main goal of this work was to identify, describe, characterize, and classify the scientific evidence regarding the use of pharmacogenomic biomarkers in antidepressant treatment.

METHODS

The work was developed in two phases: i) a search for pharmacogenomic biomarkers in summaries of antidepressant drugs with marketing authorization in Portugal; and ii) a systematic literature review based on the data obtained in the first phase, with the main objective of finding international literature that could describe and characterize previously reported biomarkers and identify other relevant biomarkers. Finally, the levels of evidence and recommendation grades were classified.

RESULTS

Among the 26 drugs with marketing authorization in Portugal, only 16 had pharmacogenomic information. The most widely studied pharmacogenomic biomarker was CYP2D6. These results were mostly supported by the systematic literature review, which yielded 103 papers, 63 of which were ultimately included in the review. The systematic literature review also revealed the existence of other relevant biomarkers. Most of the included studies show a good level of evidence, which guarantees reliability and good recommendation grades. For the database (built during phase i), the results were informative but resulted in no specific recommendations.

CONCLUSIONS

Most pharmacogenomic variants are not studied or acknowledged by genetic tests, and more scientific research is needed to confirm their usefulness. Therefore, only a small number of variants are considered when prescribing antidepressant drugs. In addition, genotyping of patients is not common in clinical practice.

Salivary Biomarkers Associated with Psychological Alterations in Patients with Diabetes: A Systematic Review

The care of individuals with diabetes needs a holistic perspective, taking into account both the physical disease and the mental health problems that may be associated. Different studies show a higher prevalence of depression or anxiety issues in diabetes patients than in the general population, which is why diabetes can be considered one of the chronic diseases in which psychological care is crucial to maintain quality of life. The objective of this review is to examine the published articles that relate the bidirectional associations between objective and subjective measures of anxiety, depressive symptomatology, stress, sleep quality, and salivary biomarkers in patients with diabetes. For this, a search was carried out in the electronic databases PubMed, Cochrane, and SCOPUS using the keywords "diabetes", "saliva", "sleep", "anxiety", "depression", and "stress" for works published up until May 2022 and limited to the English and Spanish languages. The sample comprised 14 articles, 5 of which analysed the associations between depressive symptomatology and salivary biomarkers in people with diabetes. Among the salivary biomarkers most frequently used to evaluate psychological alterations in persons with diabetes are cortisol and melatonin. Thus, significant changes in the levels of these biomarkers were observed in most studies. Four out of five studies reported a statistically significant relationship between increased salivary cortisol in the evening/midnight or the cortisol awakening response and depressive symptoms. In contrast, lower cortisol levels upon waking in the morning were observed when there was no depression or anxiety. Regarding the association between salivary cortisol values and sleep quality in patients with diabetes, lower morning cortisol values related to prolonged nighttime sleep were common in the analysed studies. Low melatonin concentrations showed a negative correlation with sleep quality. As it is an easy-to-apply and non-invasive method, the measurement of salivary biomarkers can be very useful for predicting psychological alterations in patients with diabetes. Further scientific studies are required to determine the sensitivity of these biological substances acting as biomarkers for detecting sleep disorders and psychological alterations.

Prospective associations of multimodal serum biomarkers with 12-week and 12-month remission in patients with depressive disorders receiving stepwise psychopharmacotherapy

Prognostic biomarkers for depression treatment outcomes have yet to be elucidated. This study sought to evaluate whether a multi-modal serum biomarker panel was prospectively associated with 12-week and 12-month remission in outpatients with depressive disorders receiving stepwise psychopharmacotherapy. At baseline, 14 serum biomarkers and socio-demographic/clinical characteristics were evaluated in 1094 patients. They received initial antidepressant monotherapy followed, as required by a protocol of successive alternative pharmacological strategies administered in 3-week steps during the acute (3-12 week) phase (N = 1086), and in 3-month steps during the continuation (6-12 month) phase (N = 884). Remission was defined as a Hamilton Depression Rating Scale score of ≤ 7. Remission was achieved in 490 (45.1%) over the 12-week, and in 625 (70.7%) over the 12-month, treatment periods. Combination scores of four serum biomarkers (high-sensitivity C-reactive protein, interleukin-1 beta, interleukin-6, and leptin) were prospectively associated with 12-week remission; and four (high-sensitivity C-reactive protein, tumor necrosis factor-alpha, interleukin-1 beta, and brain-derived neurotrophic factor) were prospectively associated with 12-month remission in a clear gradient manner (P-values < 0.001) and after adjustment for relevant covariates. These associations were evident after the Step 1 treatment monotherapy but weakened with increasing treatment steps, falling below statistical significance after 4 + treatment steps. Application of combined multiple serum biomarkers, particularly on inflammatory markers, could improve predictability of remission at acute and continuation treatment phases for depressive disorders. Patients with unfavourable biomarkers might require alternative treatment regimes for better outcomes.

Prognostic Significance of Blood-Based Baseline Biomarkers in Treatment-Resistant Depression: A Literature Review of Available Studies on Treatment Response

Major depressive disorder is a leading cause of disability worldwide and a major contributor to the overall global burden of disease. While there are several options for antidepressant treatment, only about 40–60% of patients respond to initial monotherapy, while 30–40% of patients may even show resistance to treatment. This article offers a narrative review of those studies evaluating the predictive properties of various blood-based baseline biomarkers regarding treatment responses to the pharmacological, stimulation, or behavioral treatment of patients with treatment-resistant depression (TRD). Our results show that overall, there is only a very limited number of studies assessing baseline peripheral biomarkers regarding treatment response in TRD. Although there is some evidence for the predictive significance of particular biomarkers (e.g., IL-6, CRP, BDNF), the majority of the results are either single-study reports or studies with conflicting results. This may contribute to the wide variety of treatment protocols and different TRD definition criteria, the small number of patients included, and the existence of different biological phenotypes of the disorder used within the various studies. Taken together, there does not yet appear to be any specific baseline peripheral biomarker with sufficient discriminative predictive validity that can be used in the routine clinical practice of TRD. The discovery of new biomarkers and the better clinical characterization of known biomarkers could support the better classification and staging of TRD, the development of personalized treatment algorithms with higher rates of remission and fewer side effects, and the development of new precision drugs for specific subgroups of patients.

Digital tools for the assessment of pharmacological treatment for depressive disorder: State of the art

Depression is an invalidating disorder, marked by phenotypic heterogeneity. Clinical assessments for treatment adjustments and data-collection for pharmacological research often rely on subjective representations of functioning. Better phenotyping through digital applications may add unseen information and facilitate disentangling the clinical characteristics and impact of depression and its pharmacological treatment in everyday life. Researchers, physicians, and patients benefit from well-understood digital phenotyping approaches to assess the treatment efficacy and side-effects. This review discusses the current possibilities and pitfalls of wearables and technology for the assessment of the pharmacological treatment of depression. Their applications in the whole spectrum of treatment for depression, including diagnosis, treatment of an episode, and monitoring of relapse risk and prevention are discussed. Multiple aspects are to be considered, including concerns that come with collecting sensitive data and health recordings. Also, privacy and trust are addressed. Available applications range from questionnaire-like apps to objective assessment of behavioural patterns and promises in handling suicidality. Nonetheless, interpretation and integration of this high-resolution information with other phenotyping levels, remains challenging. This review provides a state-of-the-art description of wearables and technology in digital phenotyping for monitoring pharmacological treatment in depression, focusing on the challenges and opportunities of its application in clinical trials and research.

The clinical and mechanistic roles of bile acids in depression, Alzheimer's disease, and stroke

The burden of neurological and neuropsychiatric disorders continues to grow with significant impacts on human health and social economy worldwide. Increasing clinical and preclinical evidences have implicated that bile acids (BAs) are involved in the onset and progression of neurological and neuropsychiatric diseases. Here, we summarized recent studies of BAs in three types of highly prevalent brain disorders, depression, Alzheimer's disease, and stroke. The shared and specific BA profiles were explored and potential markers associated with disease development and progression were summarized. The mechanistic roles of BAs were reviewed with focuses on inflammation, gut-brain-microbiota axis, cellular apoptosis. We also discussed future perspectives for the prevention and treatment of neurological and neuropsychiatric disorders by targeting BAs and related molecules and gut microbiota. Our understanding of BAs and their roles in brain disorders is still evolving. A large number of questions still need to be addressed on the emerging crosstalk among central, peripheral, intestine and their contribution to brain and mental health. This article is protected by copyright. All rights reserved.

Brain differential gene expression and blood cross-validation of a molecular signature of patients with major depressive disorder

INTRODUCTION

The agreement between clinicians diagnosing major depressive disorder (MDD) is poor. The objective of this study was to identify a reproducible and robust gene expression marker capable of differentiating MDD from healthy control (HC) subjects.

MATERIALS AND METHODS

Brain and blood gene expression datasets were searched, which included subjects with MDD and HC. The largest database including different areas of brain samples (GSE80655) was used to identify an initial gene expression marker. Tests of robustness and reproducibility were then implemented in 13 brain and 7 blood independent datasets. Correlations between expression in brain and blood samples were also examined. Finally, an enrichment analysis to explore the marker biological meaning was completed.

RESULTS

Twenty-eight genes were differentially expressed in GSE80655, of which 23 were critical to differentiate MDD from HC. The accuracy obtained using the 23 genes was 0.77 and 0.8, before and after the forward selection model, respectively. The gene marker's robustness and reproducibility were between the range of 0.46 and 0.63 in the other brain datasets and between 0.45 and 0.78 for the blood datasets. Brain and blood expression tended to correlate in some samples. Thirteen of the 23 genes were related to stress and immune response.

CONCLUSION

A 23 gene expression marker was able to distinguish subjects with MDD from HC, with adequate reproducibility and low robustness in the independent databases investigated. This gene set was similarly expressed in the brain and blood and involved genes related to stress and immune response.

Static and treatment-responsive brain biomarkers of depression relapse vulnerability following prophylactic psychotherapy: Evidence from a randomized control trial

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A prospective study of neural biomarkers of relapse in remitted depressed patients.

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Assessed neural response to dysphoric mood-induction before and after psychotherapy.

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Relapse over a 2-year follow-up linked to dysphoria-evoked sensory inhibition.

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Relapse risk was lower when dorsolateral prefrontal reactivity decreased over time.

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Depression prophylaxis may involve reducing dysphoria-evoked sensory inhibition.

Background

Neural reactivity to dysphoric mood induction indexes the tendency for distress to promote cognitive reactivity and sensory avoidance. Linking these responses to illness prognosis following recovery from Major Depressive Disorder informs our understanding of depression vulnerability and provides engagement targets for prophylactic interventions.

Methods

A prospective fMRI neuroimaging design investigated the relationship between dysphoric reactivity and relapse following prophylactic intervention. Remitted depressed outpatients (N = 85) were randomized to 8 weeks of Cognitive Therapy with a Well-Being focus or Mindfulness Based Cognitive Therapy. Participants were assessed before and after therapy and followed for 2 years to assess relapse status. Neural reactivity common to both assessment points identified static biomarkers of relapse, whereas reactivity change identified dynamic biomarkers.

Results

Dysphoric mood induction evoked prefrontal activation and sensory deactivation. Controlling for past episodes, concurrent symptoms and medication status, somatosensory deactivation was associated with depression recurrence in a static pattern that was unaffected by prophylactic treatment, HR 0.04, 95% CI [0.01, 0.14], p < .001. Treatment-related prophylaxis was linked to reduced activation of the left lateral prefrontal cortex (LPFC), HR 3.73, 95% CI [1.33, 10.46], p = .013. Contralaterally, the right LPFC showed dysphoria-evoked inhibitory connectivity with the right somatosensory biomarker

Conclusions

These findings support a two-factor model of depression relapse vulnerability, in which: enduring patterns of dysphoria-evoked sensory deactivation contribute to episode return, but vulnerability may be mitigated by targeting prefrontal regions responsive to clinical intervention. Emotion regulation during illness remission may be enhanced by reducing prefrontal cognitive processes in favor of sensory representation and integration.

The intestinal microbiota as a predictor for antidepressant treatment outcome in geriatric depression: a prospective pilot study

OBJECTIVES

(1) To investigate if gut microbiota can be a predictor of remission in geriatric depression and to identify features of the gut microbiota that is associated with remission. (2) To determine if changes in gut microbiota occur with remission in geriatric depression.

DESIGN

Secondary analysis of a parent randomized placebo-controlled trial (NCT02466958).

SETTING

Los Angeles, CA, USA (2016-2018).

PARTICIPANTS

Seventeen subjects with major depressive disorder, over 60 years of age, 41.2% female.

INTERVENTION

Levomilacipran (LVM) or placebo.

MEASUREMENTS

Remission was defined by Hamilton Depression Rating Scale score of 6 or less at 12 weeks. 16S-ribosomal RNA sequencing based fecal microbiota composition and diversity were measured at baseline and 12 weeks. Differences in fecal microbiota were evaluated between remitters and non-remitters as well as between baseline and post-treatment samples. LVM and placebo groups were combined in all the analyses.

RESULTS

Baseline microbiota showed no community level α-diversity or β-diversity differences between remitters and non-remitters. At the individual taxa level, a random forest classifier created with nine genera from the baseline microbiota was highly accurate in predicting remission (AUC = .857). Of these, baseline enrichment of Faecalibacterium, Agathobacter and Roseburia relative to a reference frame was associated with treatment outcome of remission. Differential abundance analysis revealed significant genus level changes from baseline to post-treatment in remitters, but not in non-remitters.

CONCLUSIONS

This is the first study demonstrating fecal microbiota as a potential predictor of treatment response in geriatric depression. Our findings need to be confirmed in larger prospective studies.

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.