Gene expression studies in Depression development and treatment: an overview of the underlying molecular mechanisms and biological processes to identify biomarkers

Decoding the transcriptomic signatures of psychological trauma in human cortex and amygdala

Psychological trauma has profound effects on brain function and precipitates psychiatric disorders in vulnerable individuals, however, the molecular mechanisms linking trauma with psychiatric risk remain incompletely understood. Using RNA-seq data postmortem brain tissue of a cohort of 304 donors (N=136 with trauma exposure), we investigated transcriptional signatures of trauma exposures in two cortical regions (dorsolateral prefrontal cortex, and dorsal anterior cingulate cortex) and two amygdala regions (medial amygdala and basolateral amygdala) associated with stress processing and regulation. We focused on dissecting heterogeneity of traumatic experiences in these transcriptional signatures by investigating exposure to several trauma types (childhood, adulthood, complex, single acute, combat, and interpersonal traumas) and interactions with sex. Overall, amygdala regions were more vulnerable to childhood traumas, whereas cortical regions were more vulnerable to adulthood trauma (regardless of childhood experience). Using cell-type-specific expression imputation, we identified a strong transcriptional response of medial amygdala excitatory neurons to childhood trauma, which coincided with dysregulation observed in a human induced pluripotent stem cell (hiPSC)-derived glutamatergic neurons exposed to hydrocortisone. We resolved multiscale coexpression networks for each brain region and identified modules enriched in trauma signatures and whose connectivity was altered with trauma. Trauma-associated coexpression modules provide insight into coordinated functional dysregulation with different traumas and point to potential gene targets for further dissection. Together, these data provide a characterization of the long-lasting human encoding of traumatic experiences in corticolimbic regions of human brain.

Transcriptomic profiles in major depressive disorder: the role of immunometabolic and cell-cycle-related pathways in depression with different levels of inflammation

Transcriptomic profiles are important indicators for molecular mechanisms and pathways involved in major depressive disorder (MDD) and its different phenotypes, such as immunometabolic depression. We performed whole-transcriptome and pathway analyses on 139 individuals from the observational, case-control, BIOmarkers in DEPression (BIODEP) study, 105 with MDD and 34 controls. We divided MDD participants based on levels of inflammation, as measured by serum high-sensitivity C-reactive protein (CRP), in n = 39 'not inflamed' (CRP < 1 mg/L), n = 31 with 'elevated CRP' (1-3 mg/L), and n = 35 with 'low-grade inflammation' (>3 mg/L). We performed whole-blood RNA sequencing using Illumina NextSeq 550 and statistical analyses with the Deseq2 package for R statistics (RUV-corrected) and subsequent pathway analyses with Ingenuity Pathway Analysis. Immunometabolic pathways were activated in individuals with CRP > 1 mg/L, although surprisingly the CRP 1-3 group showed stronger immune activation than the CRP > 3 group. The main pathways identified in the comparison between CRP < 1 group and controls were cell-cycle-related, which may be protective against immunometabolic abnormalities in this 'non-inflamed' depressed group. We further divided MDD participants based on exposure and response to antidepressants (n = 47 non-responders, n = 37 responders, and n = 22 unmedicated), and identified specific immunomodulatory and neuroprotective pathways in responders (especially vs. non-responders), which could be relevant to treatment response. In further subgroup analyses, we found that the specific transcriptional profile of responders is independent of CRP levels, and that the inhibition of cell-cycle-related pathways in MDD with CRP < 1 mg/L is present only in those who are currently depressed, and not in the responders. The present study demonstrates immunometabolic and cell-cycle-related transcriptomic pathways associated with MDD and different (CRP-based and treatment-based) MDD phenotypes, while shedding light on potential molecular mechanisms that could prevent or facilitate an individual's trajectory toward immunometabolic depression and/or treatment-non-responsive depression. The recognition and integration of these mechanisms will facilitate a precision-medicine approach in MDD.

Neurobiology and medico-legal aspects of suicides among older adults: a narrative review

The task of preventing suicide in older adults is an important social burden as older adults aged above 65 are exposed to singular psychological aspects that increase suicide risks. Moreover, when an older adult corpse is found, the medico-legal inspection represents a fundamental tool to identify the exact cause of death, classifying or excluding it as suicide. In this scenario, this review aims to explore the neurobiological factors that could be related to suicidal behavior in older adults. A further goal of this review is the exploration of the medico-legal aspects surrounding older adult suicides, clarifying the importance of forensic investigation. Particularly, this review examines issues such as neurotransmitter imbalances, cognitive impairment, neuroinflammation, psychosocial factors related to geriatric suicide, and neurodegenerative diseases. Additionally, medico-legal aspects such as policy considerations, legal frameworks, mental health assessments, ethical implications and forensic investigation were explored. Considering the importance of this phenomenon, especially in western countries, a need has emerged for focused screening tools on suicidal behavior among older adults, in order to contain it. Therefore, this review makes an exhaustive appraisal of the literature giving insights into the delicate interplay between neurobiology as well as mental health in relation to older adult suicide within a medico-legal context. The comprehension of different aspects about this complex phenomenon is fundamental to propose new and more effective interventions, supporting tailored initiatives such as family support and improving healthcare, specifically towards vulnerable ageing societies to reduce older adult suicide risks.

Graph convolutional network with attention mechanism improve major depressive depression diagnosis based on plasma biomarkers and neuroimaging data

BACKGROUND

The absence of clinically-validated biomarkers or objective protocols hinders effective major depressive disorder (MDD) diagnosis. Compared to healthy control (HC), MDD exhibits anomalies in plasma protein levels and neuroimaging presentations. Despite extensive machine learning studies in psychiatric diagnosis, a reliable tool integrating multi-modality data is still lacking.

METHODS

In this study, blood samples from 100 MDD and 100 HC were analyzed, along with MRI images from 46 MDD and 49 HC. Here, we devised a novel algorithm, integrating graph neural networks and attention modules, for MDD diagnosis based on inflammatory cytokines, neurotrophic factors, and Orexin A levels in the blood samples. Model performance was assessed via accuracy and F1 value in 3-fold cross-validation, comparing with 9 traditional algorithms. We then applied our algorithm to a dataset containing both the aforementioned protein quantifications and neuroimages, evaluating if integrating neuroimages into the model improves performance.

RESULTS

Compared to HC, MDD showed significant alterations in plasma protein levels and gray matter volume revealed by MRI. Our new algorithm exhibited superior performance, achieving an F1 value and accuracy of 0.9436 and 94.08 %, respectively. Integration of neuroimaging data enhanced our novel algorithm's performance, resulting in an improved F1 value and accuracy, reaching 0.9543 and 95.06 %.

LIMITATIONS

This single-center study with a small sample size requires future evaluations on a larger test set for improved reliability.

CONCLUSIONS

In comparison to traditional machine learning models, our newly developed MDD diagnostic model exhibited superior performance and showed promising potential for inclusion in routine clinical diagnosis for MDD.

Decoding depression: a comprehensive multi-cohort exploration of blood DNA methylation using machine learning and deep learning approaches

The causes of depression are complex, and the current diagnosis methods rely solely on psychiatric evaluations with no incorporation of laboratory biomarkers in clinical practices. We investigated the stability of blood DNA methylation depression signatures in six different populations using six public and two domestic cohorts (n = 1942) conducting mega-analysis and meta-analysis of the individual studies. We evaluated 12 machine learning and deep learning strategies for depression classification both in cross-validation (CV) and in hold-out tests using merged data from 8 separate batches, constructing models with both biased and unbiased feature selection. We found 1987 CpG sites related to depression in both mega- and meta-analysis at the nominal level, and the associated genes were nominally related to axon guidance and immune pathways based on enrichment analysis and eQTM data. Random forest classifiers achieved the highest performance (AUC 0.73 and 0.76) in CV and hold-out tests respectively on the batch-level processed data. In contrast, the methylation showed low predictive power (all AUCs < 0.57) for all classifiers in CV and no predictive power in hold-out tests when used with harmonized data. All models achieved significantly better performance (>14% gain in AUCs) with pre-selected features (selection bias), with some of the models (joint autoencoder-classifier) reaching AUCs of up to 0.91 in the final testing regardless of data preparation. Different algorithmic feature selection approaches may outperform limma, however, random forest models perform well regardless of the strategy. The results provide an overview over potential future biomarkers for depression and highlight many important methodological aspects for DNA methylation-based depression profiling including the use of machine learning strategies.

Inflammation and immune system pathways as biological signatures of adolescent depression-the IDEA-RiSCo study

The biological mechanisms underlying the onset of major depressive disorder (MDD) have predominantly been studied in adult populations from high-income countries, despite the onset of depression typically occurring in adolescence and the majority of the world's adolescents living in low- and middle-income countries (LMIC). Taking advantage of a unique adolescent sample in an LMIC (Brazil), this study aimed to identify biological pathways characterizing the presence and increased risk of depression in adolescence, and sex-specific differences in such biological signatures. We collected blood samples from a risk-stratified cohort of 150 Brazilian adolescents (aged 14-16 years old) comprising 50 adolescents with MDD, 50 adolescents at high risk of developing MDD but without current MDD, and 50 adolescents at low risk of developing MDD and without MDD (25 females and 25 males in each group). We conducted RNA-Seq and pathway analysis on whole blood. Inflammatory-related biological pathways, such as role of hypercytokinemia/hyperchemokinemia in the pathogenesis of influenza (z-score = 3.464, p < 0.001), interferon signaling (z-score = 2.464, p < 0.001), interferon alpha/beta signaling (z-score = 3.873, p < 0.001), and complement signaling (z-score = 2, p = 0.002) were upregulated in adolescents with MDD compared with adolescents without MDD independently from their level of risk. The up-regulation of such inflammation-related pathways was observed in females but not in males. Inflammatory-related pathways involved in the production of cytokines and in interferon and complement signaling were identified as key indicators of adolescent depression, and this effect was present only in females.

Genetic factors associated with suicidal behaviors and alcohol use disorders in an American Indian population

American Indians (AI) demonstrate the highest rates of both suicidal behaviors (SB) and alcohol use disorders (AUD) among all ethnic groups in the US. Rates of suicide and AUD vary substantially between tribal groups and across different geographical regions, underscoring a need to delineate more specific risk and resilience factors. Using data from over 740 AI living within eight contiguous reservations, we assessed genetic risk factors for SB by investigating: (1) possible genetic overlap with AUD, and (2) impacts of rare and low-frequency genomic variants. Suicidal behaviors included lifetime history of suicidal thoughts and acts, including verified suicide deaths, scored using a ranking variable for the SB phenotype (range 0-4). We identified five loci significantly associated with SB and AUD, two of which are intergenic and three intronic on genes AACSP1, ANK1, and FBXO11. Nonsynonymous rare and low-frequency mutations in four genes including SERPINF1 (PEDF), ZNF30, CD34, and SLC5A9, and non-intronic rare and low-frequency mutations in genes OPRD1, HSD17B3 and one lincRNA were significantly associated with SB. One identified pathway related to hypoxia-inducible factor (HIF) regulation, whose 83 nonsynonymous rare and low-frequency variants on 10 genes were significantly linked to SB as well. Four additional genes, and two pathways related to vasopressin-regulated water metabolism and cellular hexose transport, also were strongly associated with SB. This study represents the first investigation of genetic factors for SB in an American Indian population that has high risk for suicide. Our study suggests that bivariate association analysis between comorbid disorders can increase statistical power; and rare and low-frequency variant analysis in a high-risk population enabled by whole-genome sequencing has the potential to identify novel genetic factors. Although such findings may be population specific, rare functional mutations relating to PEDF and HIF regulation align with past reports and suggest a biological mechanism for suicide risk and a potential therapeutic target for intervention.

Brain-Region-Specific Genes Form the Major Pathways Featuring Their Basic Functional Role: Their Implication in Animal Chronic Stress Model

The analysis of RNA-Sec data from murine bulk tissue samples taken from five brain regions associated with behavior and stress response was conducted. The focus was on the most contrasting brain region-specific genes (BRSG) sets in terms of their expression rates. These BRSGs are identified as genes with a distinct outlying (high) expression rate in a specific region compared to others used in the study. The analysis suggested that BRSG sets form non-randomly connected compact gene networks, which correspond to the major neuron-mediated functional processes or pathways in each brain region. The number of BRSGs and the connection rate were found to depend on the heterogeneity and coordinated firing rate of neuron types in each brain region. The most connected pathways, along with the highest BRSG number, were observed in the Striatum, referred to as Medium Spiny Neurons (MSNs), which make up 95% of neurons and exhibit synchronous firing upon dopamine influx. However, the Ventral Tegmental Area/Medial Raphe Nucleus (VTA/MRN) regions, although primarily composed of monoaminergic neurons, do not fire synchronously, leading to a smaller BRSG number. The Hippocampus (HPC) region, on the other hand, displays significant neuronal heterogeneity, with glutamatergic neurons being the most numerous and synchronized. Interestingly, the two monoaminergic regions involved in the study displayed a common BRSG subnetwork architecture, emphasizing their proximity in terms of axonal throughput specifics and high-energy metabolism rates. This finding suggests the concerted evolution of monoaminergic neurons, leading to unique adaptations at the genic repertoire scale. With BRSG sets, we were able to highlight the contrasting features of the three groups: control, depressive, and aggressive mice in the animal chronic stress model. Specifically, we observed a decrease in serotonergic turnover in both the depressed and aggressive groups, while dopaminergic emission was high in both groups. There was also a notable absence of dopaminoceptive receptors on the postsynaptic membranes in the striatum in the depressed group. Additionally, we confirmed that neurogenesis BRSGs are specific to HPC, with the aggressive group showing attenuated neurogenesis rates compared to the control/depressive groups. We also confirmed that immune-competent cells like microglia and astrocytes play a crucial role in depressed phenotypes, including mitophagy-related gene Prkcd. Based on this analysis, we propose the use of BRSG sets as a suitable framework for evaluating case-control group-wise assessments of specific brain region gene pathway responses.

Analysis of MicroRNA-Transcription Factors Co-Regulatory Network Linking Depression and Vitamin D Deficiency

Depression and vitamin D deficiency are often co-occurring pathologies, the common pathogenetic ground of which includes an augmented inflammatory response. However, the molecular details of this relationship remain unclear. Here, we used a bioinformatic approach to analyze GEO transcriptome datasets of major depressive disorder (MDD) and vitamin D deficiency (VDD) to identify the hub genes within the regulatory networks of commonly differentially expressed genes (DEGs). The MDD-VDD shared regulatory network contains 100 DEGs (71 upregulated and 29 downregulated), with six hub genes (PECAM1, TLR2, PTGS2, LRRK2, HCK, and IL18) all significantly upregulated, of which PTGS2 (also known as COX2) shows the highest inference score and reference count. The subsequent analysis of the miRNA-transcription factors network identified COX2, miR-146a-5p, and miR-181c-5p as key co-regulatory actors in the MDD-VDD shared molecular pathogenic mechanisms. Subsequent analysis of published MDD and VDD transcriptome data confirmed the importance of the identified hub genes, further validating our bioinformatic analytical pipeline. Our study demonstrated that PTGS2 was highly upregulated in both depressive patients and patients with low vitamin D plasma levels. Therefore, regulators targeting PTGS2, like miR-146a-5p and miR181c-5p, may have great potential in controlling both diseases simultaneously, accentuating their role in future research.

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.

Immune gene co-expression signatures implicated in occurence and persistence of cognitive dysfunction in depression

Cognitive dysfunction contributes significantly to the burden caused by Major Depressive Disorder (MDD). Yet, while compelling evidence suggests that different biological processes play a part in both MDD aetiology and the development of cognitive decline more generally, we only begin to understand the molecular underpinnings of depression-related cognitive impairment. Developments in psychometric assessments, molecular high-throughput methods and systems biology derived analysis strategies advance this endeavour. Here, we aim to identify gene expression signatures associated with cognitive dysfunction and cognitive improvement following therapy using RNA sequencing to analyze the whole blood-derived transcriptome of altogether 101 MDD patients who enrolled in the CERT-D study. The mRNA(Nova)Seq based transcriptome was analyzed from whole blood taken at baseline assessment, and patients' cognitive performance was measured twice at baseline and following eight weeks of therapy by means of the THINC integrated tool. Thirty-six patients showed comparatively low cognitive performance at baseline assessment, and 32 patients showed comparatively strong cognitive improvement following therapy. Differential gene expression analysis was performed using limma to a significance threshold of 0.05 and a logFC cutoff of |1.2|. Although we observed some indications for expression differences related to low cognitive performance and cognitive therapy response, signals did not withstand adjustment for multiple testing. Applying WGCNA, we retrieved altogether 25 modules of co-expressed genes and we used a combination of correlational and linear analyses to identify modules related to baseline cognitive performance and cognitive improvement following therapy. Three immune modules reflected distinct but interrelated immune processes (the yellow module: neutrophil-mediated immunity, the darkorange module: interferon signaling, the tan module: platelet activation), and higher expression of the yellow (r = -0.21, p < .05), the dark orange (r = 0.2, p < .05), and the tan (r = -0.23, p < .05) module correlated significantly negatively with patients' cognitive baseline performance. Patients' cognitive baseline performance was a significant predictor of the darkorange module (b = -0.039, p < .05) and the tan module's expression (b = 0.02, p < .05) and was close to becoming a significant predictor of the yellow module's expression (b = -0.02, p = .05). Furthermore, patients characterized by comparatively low cognitive performance at baseline showed significantly higher expression of the tan module when compared to all other patients F(1,97) = 4.32, p < .05, η= 0.04. Following eight weeks of treatment, we observed altogether significant improvement in patients' cognitive performance (b = 0.30, p < .001), and patients with comparatively high cognitive gain showed noticeably lower, but not significantly lower F(1,98) = 3.76, p = .058, expression of a dark turquoise module, which reflects complement and B-cell-associated immune processes. Noteworthy, the relation between cognitive performance and module expression remained observable after controlling for symptom severity and BMI, which partly accounted for variance in module expression. As such, our findings provide further evidence for the involvement of immune processes in MDD related cognitive dysfunction and they suggest that different immune processes contribute to the development and long-term persistence of cognitive dysfunction in the context of depression.

Microglia Transcriptional Profiling in Major Depressive Disorder Shows Inhibition of Cortical Gray Matter Microglia

BACKGROUND

Microglia have been implicated in the pathophysiology of major depressive disorder (MDD), but information on biological mechanisms is limited. Therefore, we investigated the gene expression profile of microglial cells in relation to neuronal regulators of microglia activity in well-characterized MDD and control autopsy brains.

METHODS

Pure, intact microglia were isolated at brain autopsy from occipital cortex gray matter (GM) and corpus callosum white matter of 13 donors with MDD and 10 age-matched control donors for RNA sequencing. Top differentially expressed genes were validated using immunohistochemistry staining. Because gene expression changes were only detected in GM microglia, neuronal regulators of microglia were investigated in cortical tissue and synaptosomes from the cortex by reverse transcriptase-quantitative polymerase chain reaction and Western blot.

RESULTS

Transcriptome analysis revealed 92 genes differentially expressed in microglia isolated from GM, but none in microglia from white matter in donors with MDD, compared with control donors. Of these, 81 genes were less abundantly expressed in GM in MDD, including CD163, MKI67, SPP1, CD14, FCGR1A/C, and C1QA/B/C. Accordingly, pathways related to effector mechanisms, such as the complement system and phagocytosis, were differentially regulated in GM microglia in MDD. Immunohistochemistry staining revealed significantly lower expression of CD163 protein in MDD. Whole tissue analysis showed an increase in CD200 (p = .0009) and CD47 (p = .068) messenger RNA, and CD47 protein was significantly elevated (p = .0396) in synaptic fractions of MDD cases.

CONCLUSIONS

Transcriptional profiling indicates an immune-suppressed microglial phenotype in MDD that is possibly caused by neuronal regulation.

Prospective associations between hand grip strength and subsequent depressive symptoms in men and women aged 50 years and older: insights from the Survey of Health, Aging, and Retirement in Europe

Introduction

In previous cross-sectional and longitudinal studies, depressive symptoms have been associated with lower hand grip strength (HGS), which is a convenient measure of overall muscular strength and serves as a marker of poor health. Most studies have considered low sample sizes or highly selective patient cohorts.

Methods

We studied the association between depressive symptoms (EURO-D) and HGS in three waves from the cross-national panel dataset Survey of Health, Aging, and Retirement in Europe (SHARE). Linear regressions and Generalized Estimating Equations (GEE) were conducted to determine factors associated with depressive symptoms and investigate whether HGS predicts future depressive symptoms.

Results

Cross-sectional HGS explained 7.0% (Wave 4), 5.7% (Wave 5), and 6.4% (Wave 6) of the EURO-D variance. In the GEE, we analyzed people without depression in Wave 4 (N = 39,572). HGS predicted future EURO-D (B = -0.21, OR = 0.979, 95%CI (0.979, 0.980), p < 0.001) and remained a significant predictor of future depressive symptoms after adjustment for age, sex, psychosocial and physical covariates.

Discussion

Muscle strength is a known marker for physical health, but a relation with mental health has also been proposed previously. This study confirmed the link between HGS and depressive symptoms in men and women aged ≥50 years in a large longitudinal dataset. Further research is required to understand the mechanisms behind this link to determine whether HGS can serve as a specific marker of depressive symptomology, or whether they coexist due to common underlying disease processes.

Integrative bioinformatics and artificial intelligence analyses of transcriptomics data identified genes associated with major depressive disorders including NRG1

Major depressive disorder (MDD) is a common mental disorder and is amongst the most prevalent psychiatric disorders. MDD remains challenging to diagnose and predict its onset due to its heterogeneous phenotype and complex etiology. Hence, early detection using diagnostic biomarkers is critical for rapid intervention. In this study, a mixture of AI and bioinformatics were used to mine transcriptomic data from publicly available datasets including 170 MDD patients and 121 healthy controls. Bioinformatics analysis using gene set enrichment analysis (GSEA) and machine learning (ML) algorithms were applied. The GSEA revealed that differentially expressed genes in MDD patients are mainly enriched in pathways related to immune response, inflammatory response, neurodegeneration pathways and cerebellar atrophy pathways. Feature selection methods and ML provided predicted models based on MDD-altered genes with ≥75% of accuracy. The integrative analysis between the bioinformatics and ML approaches identified ten key MDD-related biomarkers including NRG1, CEACAM8, CLEC12B, DEFA4, HP, LCN2, OLFM4, SERPING1, TCN1 and THBS1. Among them, NRG1, active in synaptic plasticity and neurotransmission, was the most robust and reliable to distinguish between MDD patients and healthy controls amongst independent external datasets consisting of a mixture of populations. Further evaluation using saliva samples from an independent cohort of MDD and healthy individuals confirmed the upregulation of NRG1 in patients with MDD compared to healthy controls. Functional mapping to the human brain regions showed NRG1 to have high expression in the main subcortical limbic brain regions implicated in depression. In conclusion, integrative bioinformatics and ML approaches identified putative non-invasive diagnostic MDD-related biomarkers panel for the onset of depression.

Higher immune-related gene expression in major depression is independent of CRP levels: results from the BIODEP study

Compelling evidence demonstrates that some individuals suffering from major depressive disorder (MDD) exhibit increased levels of inflammation. Most studies focus on inflammation-related proteins, such as serum or plasma C-reactive protein (CRP). However, the immune-related modifications associated with MDD may be not entirely captured by CRP alone. Analysing mRNA gene expression levels, we aimed to identify broader molecular immune-related phenotypes of MDD. We examined 168 individuals from the non-interventional, case-control, BIODEP study, 128 with a diagnosis of MDD and 40 healthy controls. Individuals with MDD were further divided according to serum high-sensitivity (hs)CRP levels (n = 59 with CRP <1, n = 33 with CRP 1-3 and n = 36 with CRP >3 mg/L). We isolated RNA from whole blood and performed gene expression analyses using RT-qPCR. We measured the expression of 16 immune-related candidate genes: A2M, AQP4, CCL2, CXCL12, CRP, FKBP5, IL-1-beta, IL-6, ISG15, MIF, GR, P2RX7, SGK1, STAT1, TNF-alpha and USP18. Nine of the 16 candidate genes were differentially expressed in MDD cases vs. controls, with no differences between CRP-based groups. Only CRP mRNA was clearly associated with serum CRP. In contrast, plasma (proteins) IL-6, IL-7, IL-8, IL-10, IL-12/IL-23p40, IL-16, IL-17A, IFN-gamma and TNF-alpha, and neutrophils counts, were all differentially regulated between CRP-based groups (higher in CRP >3 vs. CRP <1 and/or controls), reflecting the gradient of CRP values. Secondary analyses on MDD individuals and controls with CRP values <1 mg/L (usually interpreted as 'no inflammation') confirmed MDD cases still had significantly different mRNA expression of immune-related genes compared with controls. These findings corroborate an immune-related molecular activation in MDD, which appears to be independent of serum CRP levels. Additional biological mechanisms may then be required to translate this mRNA signature into inflammation at protein and cellular levels. Understanding these mechanisms will help to uncover the true immune abnormalities in depression, opening new paths for diagnosis and treatment.

Genetic Factors Associated with Suicidal Behaviors and Alcohol Use Disorders in an American Indian Population

American Indians (AI) demonstrate the highest rates of both suicidal behaviors (SB) and alcohol use disorders (AUD) among all ethnic groups in the US. Rates of suicide and AUD vary substantially between tribal groups and across different geographical regions, underscoring a need to delineate more specific risk and resilience factors. Using data from over 740 AI living within eight contiguous reservations, we assessed genetic risk factors for SB by investigating: (1) possible genetic overlap with AUD, and (2) impacts of rare and low frequency genomic variants. Suicidal behaviors included lifetime history of suicidal thoughts and acts, including verified suicide deaths, scored using a ranking variable for the SB phenotype (range 0-4). We identified five loci significantly associated with SB and AUD, two of which are intergenic and three intronic on genes AACSP1, ANK1, and FBXO11. Nonsynonymous rare mutations in four genes including SERPINF1 (PEDF), ZNF30, CD34, and SLC5A9, and non-intronic rare mutations in genes OPRD1, HSD17B3 and one lincRNA were significantly associated with SB. One identified pathway related to hypoxia-inducible factor (HIF) regulation, whose 83 nonsynonymous rare variants on 10 genes were significantly linked to SB as well. Four additional genes, and two pathways related to vasopressin-regulated water metabolism and cellular hexose transport, also were strongly associated with SB. This study represents the first investigation of genetic factors for SB in an American Indian population that has high risk for suicide. Our study suggests that bivariate association analysis between comorbid disorders can increase statistical power; and rare variant analysis in a high-risk population enabled by whole-genome sequencing has the potential to identify novel genetic factors. Although such findings may be population specific, rare functional mutations relating to PEDF and HIF regulation align with past reports and suggest a biological mechanism for suicide risk and a potential therapeutic target for intervention.

Long-term consequences of COVID-19 on mental health and the impact of a physically active lifestyle: a narrative review

BACKGROUND

Coronavirus-19 disease (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Respiratory viruses damage not only the upper respiratory tract in humans, but also several different organs such as the brain. Some of the neurological consequences of COVID-19 reported are anosmia, headache, stroke, declined cognitive function, and impaired mental health, among others. People who had COVID-19 have a higher risk of sequelae in the central nervous system (CNS). However, it is not known which are all possible sequelae and how long will last the long-term effects of the COVID-19 pandemic on behavioral patterns and quality of life.

AIM

We intend to address the long-term impacts of COVID-19 on mental health and the relevance of physical exercise during the pandemic.

METHODS

We conducted a literature search using PubMed to find the articles that were related to these themes.

RESULTS

We found 23,489 papers initially, and then we applied the inclusion/exclusion criteria to narrow down our search to 3617 articles and selected 1380 eligible articles after a thorough reading of titles and abstracts. The findings indicated that COVID-19 impacted general mental health and led many not only hospitalized patients to develop cognitive decline, memory impairment, anxiety, sleep alterations, and depressive-like behavior. Furthermore, the fear of vaccines and their effects had negatively affected mental health and directly impacted mortality rates in unvaccinated COVID-19 patients.

CONCLUSIONS

Preventive measures must be undertaken, such as the vaccination of the entire population, vaccination hesitancy discouragement by creating awareness among individuals, and people's engagement in a physically active lifestyle, since being physically active is a low-cost and effective measure to restore or inhibit the negative outcomes from COVID-19 on mental health.

Integrating genetics and transcriptomics to study major depressive disorder: a conceptual framework, bioinformatic approaches, and recent findings

Major depressive disorder (MDD) is a complex and heterogeneous psychiatric syndrome with genetic and environmental influences. In addition to neuroanatomical and circuit-level disturbances, dysregulation of the brain transcriptome is a key phenotypic signature of MDD. Postmortem brain gene expression data are uniquely valuable resources for identifying this signature and key genomic drivers in human depression; however, the scarcity of brain tissue limits our capacity to observe the dynamic transcriptional landscape of MDD. It is therefore crucial to explore and integrate depression and stress transcriptomic data from numerous, complementary perspectives to construct a richer understanding of the pathophysiology of depression. In this review, we discuss multiple approaches for exploring the brain transcriptome reflecting dynamic stages of MDD: predisposition, onset, and illness. We next highlight bioinformatic approaches for hypothesis-free, genome-wide analyses of genomic and transcriptomic data and their integration. Last, we summarize the findings of recent genetic and transcriptomic studies within this conceptual framework.

A Review of Research on the Association between Neuron-Astrocyte Signaling Processes and Depressive Symptoms

Depression is a mental illness that has a serious negative impact on physical and mental health. The pathophysiology of depression is still unknown, and therapeutic medications have drawbacks, such as poor effectiveness, strong dependence, adverse drug withdrawal symptoms, and harmful side effects. Therefore, the primary purpose of contemporary research is to understand the exact pathophysiology of depression. The connection between astrocytes, neurons, and their interactions with depression has recently become the focus of great research interest. This review summarizes the pathological changes of neurons and astrocytes, and their interactions in depression, including the alterations of mid-spiny neurons and pyramidal neurons, the alterations of astrocyte-related biomarkers, and the alterations of gliotransmitters between astrocytes and neurons. In addition to providing the subjects of this research and suggestions for the pathogenesis and treatment techniques of depression, the intention of this article is to more clearly identify links between neuronal-astrocyte signaling processes and depressive symptoms.

The Melanocortin System: A Promising Target for the Development of New Antidepressant Drugs

Major depression is one of the most prevalent mental disorders, causing significant human suffering and socioeconomic loss. Since conventional antidepressants are not sufficiently effective, there is an urgent need to develop new antidepressant medications. Despite marked advances in the neurobiology of depression, the etiology and pathophysiology of this disease remain poorly understood. Classical and newer hypotheses of depression suggest that an imbalance of brain monoamines, dysregulation of the hypothalamic-pituitary-adrenal axis (HPAA) and immune system, or impaired hippocampal neurogenesis and neurotrophic factors pathways are cause of depression. It is assumed that conventional antidepressants improve these closely related disturbances. The purpose of this review was to discuss the possibility of affecting these disturbances by targeting the melanocortin system, which includes adrenocorticotropic hormone-activated receptors and their peptide ligands (melanocortins). The melanocortin system is involved in the regulation of various processes in the brain and periphery. Melanocortins, including peripherally administered non-corticotropic agonists, regulate HPAA activity, exhibit anti-inflammatory effects, stimulate the levels of neurotrophic factors, and enhance hippocampal neurogenesis and neurotransmission. Therefore, endogenous melanocortins and their analogs are able to complexly affect the functioning of those body’s systems that are closely related to depression and the effects of antidepressants, thereby demonstrating a promising antidepressant potential.

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

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

Depression and Its Phytopharmacotherapy-A Narrative Review

Depression is a mental health disorder that develops as a result of complex psycho-neuro-immuno-endocrinological disturbances. This disease presents with mood disturbances, persistent sadness, loss of interest and impaired cognition, which causes distress to the patient and significantly affects the ability to function and have a satisfying family, social and professional life. Depression requires comprehensive management, including pharmacological treatment. Because pharmacotherapy of depression is a long-term process associated with the risk of numerous adverse drug effects, much attention is paid to alternative therapy methods, including phytopharmacotherapy, especially in treating mild or moderate depression. Preclinical studies and previous clinical studies confirm the antidepressant activity of active compounds in plants, such as St. John's wort, saffron crocus, lemon balm and lavender, or less known in European ethnopharmacology, roseroot, ginkgo, Korean ginseng, borage, brahmi, mimosa tree and magnolia bark. The active compounds in these plants exert antidepressive effects in similar mechanisms to those found in synthetic antidepressants. The description of phytopharmacodynamics includes inhibiting monoamine reuptake and monoamine oxidase activity and complex, agonistic or antagonistic effects on multiple central nervous system (CNS) receptors. Moreover, it is noteworthy that the anti-inflammatory effect is also important to the antidepressant activity of the plants mentioned above in light of the hypothesis that immunological disorders of the CNS are a significant pathogenetic factor of depression. This narrative review results from a traditional, non-systematic literature review. It briefly discusses the pathophysiology, symptomatology and treatment of depression, with a particular focus on the role of phytopharmacology in its treatment. It provides the mechanisms of action revealed in experimental studies of active ingredients isolated from herbal antidepressants and presents the results of selected clinical studies confirming their antidepressant effectiveness.

Beyond monoamines: I. Novel targets and radiotracers for Positron emission tomography imaging in psychiatric disorders

With the emergence of positron emission tomography (PET) in the late 1970s, psychiatry had access to a tool capable of non-invasive assessment of human brain function. Early applications in psychiatry focused on identifying characteristic brain blood flow and metabolic derangements using radiotracers such as [¹⁵ O]H₂ O and [¹⁸ F]FDG. Despite the success of these techniques, it became apparent that more specific probes were needed to understand the neurochemical bases of psychiatric disorders. The first neurochemical PET imaging probes targeted sites of action of neuroleptic (dopamine D₂ receptors) and psychoactive (serotonin receptors) drugs. Based on the centrality of monoamine dysfunction in psychiatric disorders and the measured success of monoamine-enhancing drugs in treating them, the next 30 years witnessed the development of an armamentarium of PET radiopharmaceuticals and imaging methodologies for studying monoamines. Continued development of monoamine-enhancing drugs over this time however was less successful, realizing only modest gains in efficacy and tolerability. As patent protection for many widely prescribed and profitable psychiatric drugs lapsed, drug development pipelines shifted away from monoamines in search of novel targets with the promises of improved efficacy, or abandoned altogether. Over this period, PET radiopharmaceutical development activities closely paralleled drug development priorities resulting in the development of new PET imaging agents for non-monoamine targets. Part one of this review will briefly survey novel PET imaging targets with relevance to the field of psychiatry, which include the metabotropic glutamate receptor type 5 (mGluR5), purinergic P₂ X₇ receptor, type 1 cannabinoid receptor (CB₁ ), phosphodiesterase 10A (PDE10A), and describe radiotracers developed for these and other targets that have matured to human subject investigations. Current limitations of the targets and techniques will also be discussed.

Astrocyte regulation of synaptic signaling in psychiatric disorders

Over the last 15 years, the field of neuroscience has evolved toward recognizing the critical role of astroglia in shaping neuronal synaptic activity and along with the pre- and postsynapse is now considered an equal partner in tripartite synaptic transmission and plasticity. The relative youth of this recognition and a corresponding deficit in reagents and technologies for quantifying and manipulating astroglia relative to neurons continues to hamper advances in understanding tripartite synaptic physiology. Nonetheless, substantial advances have been made and are reviewed herein. We review the role of astroglia in synaptic function and regulation of behavior with an eye on how tripartite synapses figure into brain pathologies underlying behavioral impairments in psychiatric disorders, both from the perspective of measures in postmortem human brains and more subtle influences on tripartite synaptic regulation of behavior in animal models of psychiatric symptoms. Our goal is to provide the reader a well-referenced state-of-the-art understanding of current knowledge and predict what we may discover with deeper investigation of tripartite synapses using reagents and technologies not yet available.

Transcriptomic Studies of Antidepressant Action in Rodent Models of Depression: A First Meta-Analysis

Antidepressants (ADs) are, for now, the best everyday treatment we have for moderate to severe major depressive episodes (MDEs). ADs are among the most prescribed drugs in the Western Hemisphere; however, the trial-and-error prescription strategy and side-effects leave a lot to be desired. More than 60% of patients suffering from major depression fail to respond to the first AD they are prescribed. For those who respond, full response is only observed after several weeks of treatment. In addition, there are no biomarkers that could help with therapeutic decisions; meanwhile, this is already true in cancer and other fields of medicine. For years, many investigators have been working to decipher the underlying mechanisms of AD response. Here, we provide the first systematic review of animal models. We thoroughly searched all the studies involving rodents, profiling transcriptomic alterations consecutive to AD treatment in naïve animals or in animals subjected to stress-induced models of depression. We have been confronted by an important heterogeneity regarding the drugs and the experimental settings. Thus, we perform a meta-analysis of the AD signature of fluoxetine (FLX) in the hippocampus, the most studied target. Among genes and pathways consistently modulated across species, we identify both old players of AD action and novel transcriptional biomarker candidates that warrant further investigation. We discuss the most prominent transcripts (immediate early genes and activity-dependent synaptic plasticity pathways). We also stress the need for systematic studies of AD action in animal models that span across sex, peripheral and central tissues, and pharmacological classes.

Neuropathology of depression in non-demented older adults: A large postmortem study of 741 individuals

Associations between age-related neuropathological lesions and adult-onset lifetime major depressive disorder (a-MDD), late-life MDD (LLD), or depressive symptoms close to death (DS) were examined in a large community sample of non-demented older adults. Seven hundred forty-one individuals (age at death = 72.2 ± 11.7 years) from the Biobank for Aging Studies were analyzed. a-MDD was present in 54 (7.3%) participants, LLD in 80 (10.8%), and DS in 168 (22.7%). After adjustment for covariates and compared to controls, a-MDD, LDD and DS were associated with small vessel disease (p = 0.039, p = 0.003, and p = 0.003 respectively); LLD, and DS were associated with brain infarcts (p = 0.012, p = 0.018, respectively) and Lewy body disease (p = 0.043, p = 0.002, respectively). DS was associated with beta-amyloid plaque burden (p = 0.027) and cerebral amyloid angiopathy (p = 0.035) in cognitively normal individuals (Clinical Dementia Rating scale = 0). Vascular brain pathology was the strongest correlate of clinical depictions of depression in the absence of dementia, corroborating the vascular hypothesis of depression. Lewy body pathology underlay DS. An older adult with DS or LLD should be monitored for possible cognitive decline or neurodegenerative disorders.

Effects of Two Distinct Psychoactive Microbes, Lacticaseibacillus rhamnosus JB-1 and Limosilactobacillus reuteri 6475, on Circulating and Hippocampal mRNA in Male Mice

Discovery of the microbiota-gut–brain axis has led to proposed microbe-based therapeutic strategies in mental health, including the use of mood-altering bacterial species, termed psychobiotics. However, we still have limited understanding of the key signaling pathways engaged by specific organisms in modulating brain function, and evidence suggests that bacteria with broadly similar neuroactive and immunomodulatory actions can drive different behavioral outcomes. We sought to identify pathways distinguishing two psychoactive bacterial strains that seemingly engage similar gut–brain signaling pathways but have distinct effects on behaviour. We used RNAseq to identify mRNAs differentially expressed in the blood and hippocampus of mice following Lacticaseibacillus rhamnosus JB-1, and Limosilactobacillus reuteri 6475 treatment and performed Gene Set Enrichment Analysis (GSEA) to identify enrichment in pathway activity. L. rhamnosus, but not L. reuteri treatment altered several pathways in the blood and hippocampus, and the rhamnosus could be clearly distinguished based on mRNA profile. In particular, L. rhamnosus treatment modulated the activity of interferon signaling, JAK/STAT, and TNF-alpha via NF-KB pathways. Our results highlight that psychobiotics can induce complex changes in host gene expression, andin understanding these changes, we may help fine-tune selection of psychobiotics for treating mood disorders.

miR-218: A Stress-Responsive Epigenetic Modifier

Understanding the epigenetic role of microRNAs (miRNAs) has been a critical development in the field of neuropsychiatry and in understanding their underlying pathophysiology. Abnormalities in miRNA expression are often seen as key to the pathogenesis of many stress-associated mental disorders, including major depressive disorder (MDD). Recent advances in omics biology have further contributed to this understanding and expanded the role of miRNAs in networking a diverse array of molecular pathways, which are essentially related to the stress adaptivity of a healthy brain. Studies have highlighted the role of many such miRNAs in causing maladaptive changes in the brain's stress axis. One such miRNA is miR-218, which is debated as a critical candidate for increased stress susceptibility. miR-218 is expressed throughout the brain, notably in the hippocampus and prefrontal cortex (PFC). It is expressed at various levels through life stages, as seen by adolescent and adult animal models. Until now, a minimal number of studies have been conducted on human subjects to understand its role in stress-related abnormalities in brain circuits. However, several studies, including animal and cell-culture models, have been used to understand the impact of miR-218 on stress response and hypothalamic-pituitary-adrenal (HPA) axis function. So far, expression changes in this miRNA have been found to regulate signaling pathways such as glucocorticoid signaling, serotonergic signaling, and glutamatergic signaling. Recently, the developmental role of miR-218 has generated interest, given its increasing expression from adolescence to adulthood and targeting the Netrin-1/DCC signaling pathway. Since miR-218 expression affects neuronal development and plasticity, it is expected that a change in miR-218 expression levels over the course of development may negatively impact the process and make individuals stress-susceptible in adulthood. In this review, we describe the role of miR-218 in stress-induced neuropsychiatric conditions with an emphasis on stress-related disorders.

Depression in Adolescence and Brain-Derived Neurotrophic Factor

The incidence of depression among adolescents has been rapidly increasing in recent years. Environmental and genetic factors have been identified as important risk factors for adolescent depression. However, the mechanisms underlying the development of adolescent depression that are triggered by these risk factors are not well understood. Clinical and preclinical studies have focused more on adult depression, and differences in depressive symptoms between adolescents and adults make it difficult to adequately diagnose and treat adolescent depression. Brain-derived neurotrophic factor (BDNF) is known to play a critical role in the pathophysiology of many psychiatric disorders, including depression. However, there are still few studies on adolescent depression. Therefore, in this review paper, the causes and treatment of adolescent depression and the function of BDNF are investigated.

Cause or consequence? Understanding the role of cortisol in the increased inflammation observed in depression

Glucocorticoids such as cortisol are a class of steroid hormones that play an important role in co-ordinating the body's response to stress. Elevated cortisol levels and increased inflammation have frequently been reported in patients with depression. The currently accepted "glucocorticoid resistance" model posits this increased inflammation as a consequence of reduced sensitivity to cortisol's putative anti-inflammatory action. However, opposing evidence has accumulated that supports a more recent model, which instead proposes that cortisol possesses immune potentiating properties and may thus directly cause the increased inflammation seen in depression. Despite all of this, a clear explanation of the neuroendocrine mechanism that contributes to the development of depression is still lacking and thus requires further investigation in improved future studies.

Biomarkers common for inflammatory periodontal disease and depression: A systematic review

Background

Dysregulated immune response arising in the periphery can induce depressive symptoms through neuroimmune interactions. Inflammatory oral pathology can be a potent inducer of chronic neuroimmune response relevant to depression. We aimed to synthesize available evidence for the association between inflammatory periodontal diseases (IPD) and major depression (MD) in relation to a broad range of biomarkers.

Methods

Medline, Embase, PsycInfo, Cochrane Library, Web of Science and Scopus databases were searched from inception until January 27, 2022. Search terms included subject headings and synonyms for inflammatory periodontal disease and depression. Studies that reported data on both depression and inflammatory periodontal disease as categories along with measurement of a biomarker were considered. Two reviewers independently selected the articles for inclusion, extracted data and assessed the quality of each study. The protocol for this study was registered with PROSPERO, CRD42021215524.

Results

Twenty-eight studies were included in the final review-eleven cross-sectional studies, seven case-control studies, and six prospective cohort studies conducted in humans; the remaining four were experimental animal studies. Eighteen studies including all animal studies reported a positive association between depression and periodontal disease; one study reported a negative association and another nine studies found no such associations. Twenty studies reported mixed associations between IPD and biomarkers (i.e, salivary, serum, urine or gingival crevicular fluid cortisol, C reactive protein, cytokines, etc.). Biomarkers related to depression were gingival crevicular fluid cortisol, interleukin 6 (IL-6), Il-1β, immunoglobulin G against Bacterioides forsythus; root canal lipopolysaccharides; blood IL-6, IL-1β, cortisol, advanced oxidation protein products, nitric oxide metabolites, lipid hydroperoxides and trapping antioxidant parameter; whereas five studies found no associations between depression and a biomarker. Although animal studies showed interaction of immune, inflammatory and neurotrophic biomarkers in the relationship between depression and periodontal disease, human studies showed mixed findings. In most studies, there were risks of bias due to the sample selection and assessment protocol. Study heterogeneity and limited number of comparable studies reporting on shared biomarkers precluded a meta-analysis.

Conclusion

Immune-inflammatory contribution to depression was evident in the context of inflammatory periodontal diseases, but whether biomarkers mediate the associations between IPD and MD needs to be tested through methodologically rigorous studies aiming specifically at this hypothesis.

Rehman A, Morris DW. Major Depressive Disorder: Existing Hypotheses about Pathophysiological Mechanisms and New Genetic Findings

Major depressive disorder (MDD) is a common mental disorder generally characterized by symptoms associated with mood, pleasure and effectiveness in daily life activities. MDD is ranked as a major contributor to worldwide disability. The complex pathogenesis of MDD is not yet understood, and this is a major cause of failure to develop new therapies and MDD recurrence. Here we summarize the literature on existing hypotheses about the pathophysiological mechanisms of MDD. We describe the different approaches undertaken to understand the molecular mechanism of MDD using genetic data. Hundreds of loci have now been identified by large genome-wide association studies (GWAS). We describe these studies and how they have provided information on the biological processes, cell types, tissues and druggable targets that are enriched for MDD risk genes. We detail our understanding of the genetic correlations and causal relationships between MDD and many psychiatric and non-psychiatric disorders and traits. We highlight the challenges associated with genetic studies, including the complexity of MDD genetics in diverse populations and the need for a study of rare variants and new studies of gene-environment interactions.

Metabolizing status of CYP2C19 in response and side effects to medications for depression: Results from a naturalistic study

Major depressive disorder (MDD) is one of the leading causes of disability worldwide. Polymorphisms in cytochrome P450 genes (CYP450) were demonstrated to play a significant role in antidepressant response and side effects, but their effect in real-world clinical practice is poorly known. We determined the metabolic status of CYP2C19 based on the combination of *1, *2, *3 and *17 alleles extracted from genome-wide data in 1239 patients with MDD, pharmacologically treated in a naturalistic setting. Symptom improvement and side effects were assessed using the Montgomery and Åsberg Depression Rating Scale and the Udvalg for Kliniske Undersøgelse scale, respectively. We tested if symptom improvement, response and side effects were associated with CYP2C19 metabolic status adjusting for potential confounders. We considered patients treated with drugs for depression having CYP2C19 genotyping recommended by guidelines (T1 Drugs); secondarily, with all psychotropic drugs having CYP2C19 as relevant metabolic path (T2 Drugs). In the group treated with T1 drugs (n = 540), poor metabolizers (PMs) showed higher response and higher symptom improvement compared to normal metabolizers (p = 0.023 and p = 0.009, respectively), but also higher risk of autonomic and neurological side effects (p = 0.022 and p = 0.022 respectively). In patients treated with T2 drugs (n = 801), similar results were found. No associations between metabolizer status and other types of side effects were found (psychic and other side effects). Our study suggests potential advantages of CYP2C19 pharmacogenetic testing to guide treatment prescription, that may not be limited to the drugs currently recommended by guidelines.

Genetically regulated multi-omics study for symptom clusters of posttraumatic stress disorder highlights pleiotropy with hematologic and cardio-metabolic traits

Posttraumatic stress disorder (PTSD) is a psychiatric disorder that may arise in response to severe traumatic event and is diagnosed based on three main symptom clusters (reexperiencing, avoidance, and hyperarousal) per the Diagnostic Manual of Mental Disorders (version DSM-IV-TR). In this study, we characterized the biological heterogeneity of PTSD symptom clusters by performing a multi-omics investigation integrating genetically regulated gene, splicing, and protein expression in dorsolateral prefrontal cortex tissue within a sample of US veterans enrolled in the Million Veteran Program (N total = 186,689). We identified 30 genes in 19 regions across the three PTSD symptom clusters. We found nine genes to have cell-type specific expression, and over-representation of miRNA-families - miR-148, 30, and 8. Gene-drug target prioritization approach highlighted cyclooxygenase and acetylcholine compounds. Next, we tested molecular-profile based phenome-wide impact of identified genes with respect to 1678 phenotypes derived from the Electronic Health Records of the Vanderbilt University biorepository (N = 70,439). Lastly, we tested for local genetic correlation across PTSD symptom clusters which highlighted metabolic (e.g., obesity, diabetes, vascular health) and laboratory traits (e.g., neutrophil, eosinophil, tau protein, creatinine kinase). Overall, this study finds comprehensive genomic evidence including clinical and regulatory profiles between PTSD, hematologic and cardiometabolic traits, that support comorbidities observed in epidemiologic studies of PTSD.

Preventive strategies for adolescent depression: What are we missing? A focus on biomarkers

Adolescent depression is an important global issue with several unmet needs that still must be addressed and, to date, there are only few effective preventive strategies to reduce the burden of this disorder worldwide. In this mini-review, the evidence and potential ways to improve an early detection will be discussed as well as prompt interventions by focusing on a better understanding of the risks underlying the developing of adolescent depression from both a sociodemographic and a biological perspective.

Inflammation and early life stress: An updated review of childhood trauma and inflammatory markers in adulthood

Inflammation, as a neurobiological consequence of childhood trauma, has frequently been reported across research, however, recent investigations suggest this relationship may be dependent on specificities such as type of trauma, type of inflammatory marker, and additional mediatory variables - such as body mass index (BMI), age, and sex. As an updated version of a previous review by Baumeister et al., the current review comprised a search of PubMed, which identified 37 articles that collectively assessed 4 inflammatory markers (CRP, IL-6, TNFα and IL-1β). A review of the studies revealed predominantly non-significant associations between childhood trauma and elevated levels of all inflammatory markers in adulthood. However, in line with previous research, discrepancies in significance arose when considering type of trauma, type of inflammatory marker, and additional variables. Compared to neglect, abuse showed greater significant associations with elevated inflammatory markers in adulthood, though this was dependent on the individual subtypes (emotional, physical or sexual). Mediation analyses reported BMI as a significant mediator, though, when controlled for, no significant differences were found. Sex differences were reported but investigations were sparse. Future research should investigate the mediatory role of sex differences in the inflammatory effects of childhood trauma. Many studies in the review were restricted by use of the same trauma measure - the Childhood Trauma Questionnaire. To assess greater variety of trauma types, future studies should utilize other standardized measures to explore these avenues.

Changes in RNA expression levels during antidepressant treatment: a systematic review

More than a third of patients treated with antidepressants experience treatment resistance. Furthermore, molecular pathways involved in antidepressant effect have yet to be fully understood. Therefore, we performed a systematic review of clinical studies that examined changes in RNA expression levels produced by antidepressant treatment. Literature search was performed through April 2021 for peer-reviewed studies measuring changes in mRNA or non-coding RNA levels before and after antidepressant treatment in human participants following PRISMA guidelines. Thirty-one studies were included in qualitative synthesis. We identified a large amount of heterogeneity between the studies for genes/RNAs measured, antidepressants used, and treatment duration. Of the six RNAs examined by more than one study, expression of the brain-derived neurotrophic factor (BDNF) gene and genes in the inflammation pathway, particularly IL-1β, were consistently reported to be altered by antidepressant treatment. Limitations of this review include heterogeneity of the studies, possibility of positive publication bias, and risk of false-negative findings secondary to small sample sizes. In conclusion, our systematic review provides an updated synthesis of RNA expression changes produced by antidepressant treatment in human participants, where genes in the BDNF and inflammatory pathways were identified as potential targets of antidepressant effect. Importantly, these findings also highlight the need for replication of the included studies in multiple strong, placebo-controlled studies for the identification of evidence-based markers that can be targeted to improve treatment outcomes.

Early Improvement with Vortioxetine Predicts Response and Remission: A Post Hoc Analysis of Data from a Clinical Trial Conducted in Japan

AIM

Several weeks of treatment with an antidepressive agent may be required before efficacy is demonstrated in patients with major depressive disorder. This study investigated the predictive value of early partial improvement with vortioxetine for treatment response and remission.

METHODS

This was a post hoc analysis of an 8-week, randomized, double-blind, placebo-controlled, Phase 3 study of vortioxetine (10 mg or 20 mg) in Japanese patients aged 20-75 years with recurrent major depressive disorder and a Montgomery-Åsberg Depression Rating Scale (MADRS) score of at least 26. The key outcomes were the predictive value of early partial improvement (reduction in MADRS total score of ≥20% from baseline to week 2) with vortioxetine for MADRS response (≥50% decrease in score from baseline) and remission (decrease in score to ≤10) at week 8.

RESULTS

Relevant data were available for 478 patients; 62/158 patients receiving placebo, 71/162 receiving vortioxetine 10 mg, and 66/158 receiving vortioxetine 20 mg were early improvers. Early improvers receiving vortioxetine (10 mg or 20 mg) were more likely than non-early improvers to achieve a week 8 response (71.2-73.2% vs 29.7-38.0%) or remission (50.7-51.5% vs 17.4-18.7%). Positive predictive values for response and remission with vortioxetine were ~70% and ~50%, respectively; negative predictive values were ~70% and ~80%, respectively.

CONCLUSION

Improvement with vortioxetine may be predicted by early partial improvement in MADRS score. Some patients may benefit from longer-term treatment even without early improvement, another finding that may aid clinical decision-making. ClinicalTrials.gov registration for primary study: NCT02389816.