Blood biomarkers and treatment response in major depression

Cognitive and metabolic signatures of early and late-onset depression: A comparative study

BACKGROUND

Early-onset depression (EOD) and late-onset depression (LOD) are prevalent subtypes of major depressive disorder (MDD), but the clinical distinction between EOD and LOD remains blurred due to nonspecific symptoms and lack of biomarkers. This study aims to elucidate the characteristics in cognitive function and biochemical metabolism of EOD and LOD, and to identify biological factors influencing age of onset (AOO).

METHODS

Seventy patients with MDD (40 with EOD and 30 with LOD) and sixty-eight age-matched healthy controls (HC) were included in this study. Participants were evaluated for clinical features, cognitive function, and serum trace elements levels. Proton magnetic resonance spectroscopy (1H-MRS) was employed to quantify neurometabolites levels, including N-acetyl aspartate (NAA), choline (Cho), and creatine (Cr).

RESULTS

Patients with LOD experienced more episodes and severe depressive symptoms than those with EOD (p = 0.025, p < 0.001). EOD patients performed significantly worse than LOD patients on social cognition (p = 0.005), while LOD patients performed worse than EOD patients on reasoning and problem solving (p = 0.005). Additionally, LOD patients displayed higher ceruloplasmin (Cp) levels compared to EOD patients (p = 0.004), but no difference was found in neurometabolic levels between EOD and LOD. Multiple linear regression indicated a positive correlation between serum Cp levels and AOO of depression (p < 0.001), while bilateral thalamic NAA/Cr showed a negative correlation with AOO (p = 0.012, p = 0.016).

CONCLUSIONS

Patients with EOD were characterized by social cognition impairments, while patients with LOD were marked by reasoning and problem-solving deficits. Serum Cp levels demonstrated an AOO-related effect and served as a positive predictor for the AOO of depression. Furthermore, a negative correlation has been established between bilateral thalamic NAA/Cr and the AOO of MDD.

LIMITATIONS

The limited sample size and the challenge in distinguishing whether observed results are attributed to age or AOO effects.

Antidepressant-like effects of the aqueous lyophilizate of the stems and leaves of Momordica foetida (Cucurbitaceae) in rats

M. foetida (Cucurbitaceae) is a perennial climbing herb, known in traditional medicine for the treatment of certain diseases, such as malaria, headaches, skin-related problems and many others. The objective of this work was to evaluate the antidepressant effect of the aqueous lyophilisate of the mixture of leaves and stem of M. foetida. The antidepressant effect of the aqueous lyophilisate of M. foetida at different doses (25 mg/kg, 50 mg/kg and 75 mg/kg) was evaluated in Wistar rats of both sexes submitted to chronic restriction for 14 days, using the forced swimming test, open field test and sucrose preference test. One hour following the last behavioural test, animals were sacrificed and their hippocampi were collected for biochemical assessment of oxidative parameters, including malondialdehyde (MDA), reduced Glutathione (GSH), Catalase activity, superoxide dismutase (SOD) and nitric oxide (NO) as well as monoamines levels including serotonin, noradrenaline and dopamine. The aqueous lyophilisate of M. foetida significantly decreased the immobility time and significantly increased sucrose consumption (P < 0.001), with no alteration of locomotor activity. The aqueous lyophilisate of M. foetida significantly increased the concentrations of GSH, SOD, as well as catalase activity, while reducing the concentrations of MDA and NO at all doses (P < 0.001). M. foetida at the doses 25 mg/kg and 50 mg/kg significantly increased the concentration of serotonin and dopamine. Only the dose 75 mg/kg significantly increased the concentration of noradrenaline (p < 0.001). These results suggest that M. foetida exerts antidepressant-like effects through the modulation of oxidative stress and monoaminergic pathways.

Sex-specific differences in peripheral blood metabolites and biological functions in major depressive disorder: A systematic review and meta-analysis

To explore the sex-specific peripheral blood metabolites and biological functions altered in patients with major depressive disorder (MDD). A search was conducted on PubMed, Cochrane, Embase, Web of Science, and other databases published up to 11/2023. To maximize the search, we also reviewed systematic reviews and meta-analyses on the same topic. We included studies that conducted metabolic characterizations during current depressive episodes or after antidepressant treatments, with all data stratified by sex. Fifty-eight studies involving 83 cohorts with 5285 MDD participants were included in this meta-analysis. Random effects meta-analysis was conducted for data from ≥3 cohorts. We identified 5 sex-specific metabolites from 22 candidate peripheral blood metabolites. In males with MDD, we observed lower levels of estradiol and progesterone, alongside higher levels of androstenedione, dihydrotestosterone, and uric acid compared with female MDD patients. In addition, steroid hormone biosynthesis has been identified as a potentially sex-specific pathway. Our findings highlight significant evidence for targeting sex hormones as a broad understanding of MDD, providing potentially objective diagnostic and therapeutic insights.

Genetic association and drug target exploration of inflammation-related proteins with risk of major depressive disorder

BACKGROUND

In numerous observational studies, circulating inflammation-related proteins have been linked with major depressive disorder (MDD), yet the precise causal direction of this relationship remains unclear. This study aims to investigate the potential causal link between inflammation-related proteins and the risk of developing MDD.

METHODS

We utilized summary data from a genome-wide association study (GWAS) of 91 circulating inflammation-associated proteins in 14,824 individuals of European descent. Additionally, we incorporated findings from a substantial GWAS on MDD, which included 294,322 cases and 741,438 controls. Our analysis employed a two-sample bidirectional Mendelian randomization (MR) approach, with inverse variance weighting (IVW) as the primary method. We augmented this with two supplementary techniques (MR-Egger and weighted median approaches) to detect and address potential pleiotropy. Furthermore, to identify and evaluate possible drug targets, we conducted a thorough search within the Drug-Gene Interaction Database (DGIdb).

RESULTS

Analysis using MR unveiled significant and causative associations between genetically determined CASP-8 (odds ratio (OR): 0.97), CD40 (OR: 0.96), IL-18 (OR: 0.98), SLAMF1 (OR: 0.97), and uPA (OR: 0.98) with MDD. Conversely, reverse MR analysis indicated causal associations between MDD and CCL19 (OR: 1.15), HGF (OR: 1.15), IL-8 (OR: 1.10), IL-18 (OR: 1.11), IL20RA (OR: 1.12), TGFA (OR: 1.12) and TNFSF14 (OR: 1.16). Notably, a significant bidirectional causal link was observed between IL-18 and MDD. Gene-drug analysis identified CD40, HGF, IL-8, IL-18, SLAMF1, and TGFA as potential therapeutic targets.

CONCLUSIONS

We've pinpointed causal links between inflammation-related proteins and MDD, offering compelling and innovative evidence to enhance our understanding of the inflammatory mechanisms involved in MDD and to investigate potential targets for anti-MDD medications.

Unveiling the Mechanisms of a Remission in Major Depressive Disorder (MDD)-like Syndrome: The Role of Hippocampal Palmitoyltransferase Expression and Stress Susceptibility

Post-translational modifications of proteins via palmitoylation, a thioester linkage of a 16-carbon fatty acid to a cysteine residue, reversibly increases their affinity for cholesterol-rich lipid rafts in membranes, changing their function. Little is known about how altered palmitoylation affects function at the systemic level and contributes to CNS pathology. However, recent studies suggested a role for the downregulation of palmitoyl acetyltransferase (DHHC) 21 gene expression in the development of Major Depressive Disorder (MDD)-like syndrome. Here, we sought to investigate how susceptibility (sucrose preference below 65%) or resilience (sucrose preference > 65%) to stress-induced anhedonia affects DHHC gene expression in the hippocampus of C57BL/6J mice during the phase of spontaneous recovery from anhedonia. Because MDD is a recurrent disorder, it is important to understand the molecular mechanisms underlying not only the symptomatic phase of the disease but also a state of temporary remission. Indeed, molecular changes associated with the application of pharmacotherapy at the remission stage are currently not well understood. Therefore, we used a mouse model of chronic stress to address these questions. The stress protocol consisted of rat exposure, social defeat, restraint stress, and tail suspension. Mice from the stress group were not treated, received imipramine via drinking water (7 mg/kg/day), or received intraperitoneal injections of dicholine succinate (DS; 25 mg/kg/day) starting 7 days prior to stress and continuing during a 14-day stress procedure. Controls were either untreated or treated with either of the two drugs. At the 1st after-stress week, sucrose preference, forced swim, novel cage, and fear-conditioning tests were carried out; the sucrose test and 5-day Morris water maze test followed by a sacrifice of mice on post-stress day 31 for all mice were performed. Transcriptome Illumina analysis of hippocampi was carried out. Using the RT-PCR, the hippocampal gene expression of Dhhc3, Dhhc7, Dhhc8, Dhhc13, Dhhc14, and Dhhc21 was studied. We found that chronic stress lowered sucrose preference in a subgroup of mice that also exhibited prolonged floating behavior, behavioral invigoration, and impaired contextual fear conditioning, while auditory conditioning was unaltered. At the remission phase, no changes in the sucrose test were found, and the acquisition of the Morris water maze was unchanged in all groups. In anhedonic, but not resilient animals, Dhhc8 expression was lowered, and the expression of Dhhc14 was increased. Antidepressant treatment with either drug partially preserved gene expression changes and behavioral abnormalities. Our data suggest that Dhhc8 and Dhhc14 are likely to be implicated in the mechanisms of depression at the remission stage, serving as targets for preventive therapy.

The Role of HSP90 Molecular Chaperones in Depression: Potential Mechanisms

Major depressive disorder (MDD) is characterized by high rates of disability and death and has become a public health problem that threatens human life and health worldwide. HPA axis disorder and neuroinflammation are two common biological abnormalities in MDD patients. Hsp90 is an important molecular chaperone that is widely distributed in the organism. Hsp90 binds to the co-chaperone and goes through a molecular chaperone cycle to complete its regulation of the client protein. Numerous studies have demonstrated that Hsp90 regulates how the HPA axis reacts to stress and how GR, the HPA axis' responsive substrate, matures. In addition, Hsp90 exhibits pro-inflammatory effects that are closely related to neuroinflammation in MDD. Currently, Hsp90 inhibitors have made some progress in the treatment of a variety of human diseases, but they still need to be improved. Further insight into the role of Hsp90 in MDD provides new ideas for the development of new antidepressant drugs targeting Hsp90.

Epigenome-Wide DNA Methylation in Unipolar Depression: Predictive Biomarker of Antidepressant Treatment Response?

BACKGROUND

Despite the well-documented efficacy of antidepressant agents for the treatment of major depressive disorder (MDD), initial treatment nonresponse rates are high. Recent years have seen an increase in research into predictive biomarkers toward improving diagnosis and individualized treatment. Among those, epigenetic mechanisms such as DNA methylation constitute promising candidate markers in predicting antidepressant treatment response in MDD. The present study sought to address epigenome-wide DNA methylation as a predictor of antidepressant treatment response in the largest sample to date of patients with MDD.

METHODS

Epigenome-wide DNA methylation was analyzed using the Infinium MethylationEPIC BeadChip in peripheral blood of n = 230 Caucasian patients with MDD receiving 6-week antidepressant treatment in a naturalistic in-patient setting as well as in a subsample of n = 107 patients primarily receiving continuous treatment with serotonin reuptake inhibitors or serotonin and norepinephrine reuptake inhibitors. Treatment response was assessed by means of the Hamilton Depression Scale.

RESULTS

No genome-wide significant hits were observed. Suggestive (P < 1E-5) epigenome-wide evidence was discerned for altered DNA methylation at 6 CpG sites (LOC102724467, LOC100506023, RSPO2, SAG, IL16, PRKCI) to predict response to naturalistic antidepressant treatment. In patients treated with serotonin reuptake inhibitors or serotonin and norepinephrine reuptake inhibitors, differential DNA methylation at 11 CpGs, for example, mapping to the TIMP2, VDAC1, or SORL1 genes, was suggestively associated with treatment response.

CONCLUSIONS

The present results provide preliminary evidence for altered DNA methylation patterns to be associated with antidepressant treatment response in MDD. Provided significant replication in independent and larger samples, the present findings might in the future aid in clinical decision-making toward more individualized and thus more efficacious treatments of MDD.

Identification of molecular targets of Hypericum perforatum in blood for major depressive disorder: a machine-learning pharmacological study

BACKGROUND

Major depressive disorder (MDD) is one of the most common psychiatric disorders worldwide. Hypericum perforatum (HP) is a traditional herb that has been shown to have antidepressant effects, but its mechanism is unclear. This study aims to identify the molecular targets of HP for the treatment of MDD.

METHODS

We performed differential analysis and weighted gene co-expression network analysis (WGCNA) with blood mRNA expression cohort of MDD and healthy control to identify DEGs and significant module genes (gene list 1). Three databases, CTD, DisGeNET, and GeneCards, were used to retrieve MDD-related gene intersections to obtain MDD-predicted targets (gene list 2). The validated targets were retrieved from the TCMSP database (gene list 3). Based on these three gene lists, 13 key pathways were identified. The PPI network was constructed by extracting the intersection of genes and HP-validated targets on all key pathways. Key therapeutic targets were obtained using MCODE and machine learning (LASSO, SVM-RFE). Clinical diagnostic assessments (Nomogram, Correlation, Intergroup expression), and gene set enrichment analysis (GSEA) were performed for the key targets. In addition, immune cell analysis was performed on the blood mRNA expression cohort of MDD to explore the association between the key targets and immune cells. Finally, molecular docking prediction was performed for the targets of HP active ingredients on MDD.

RESULTS

Differential expression analysis and WGCNA module analysis yielded 933 potential targets for MDD. Three disease databases were intersected with 982 MDD-predicted targets. The TCMSP retrieved 275 valid targets for HP. Separate enrichment analysis intersected 13 key pathways. Five key targets (AKT1, MAPK1, MYC, EGF, HSP90AA1) were finally screened based on all enriched genes and HP valid targets. Combined with the signaling pathway and immune cell analysis suggested the effect of peripheral immunity on MDD and the important role of neutrophils in immune inflammation. Finally, the binding of HP active ingredients (quercetin, kaempferol, and luteolin) and all 5 key targets were predicted based on molecular docking.

CONCLUSIONS

The active constituents of Hypericum perforatum can act on MDD and key targets and pathways of this action were identified.

Machine learning for antidepressant treatment selection in depression

Finding the right antidepressant for the individual patient with major depressive disorder can be a difficult endeavor and is mostly based on trial-and-error. Machine learning (ML) is a promising tool to personalize antidepressant prescription. In this review, we summarize the current evidence of ML in the selection of antidepressants and conclude that its value for clinical practice is still limited. Apart from the current focus on effectiveness, several other factors should be taken into account to make ML-based prediction models useful for clinical application.

MDDOmics: multi-omics resource of major depressive disorder

Major depressive disorder (MDD) is a pressing global health issue. Its pathogenesis remains elusive, but numerous studies have revealed its intricate associations with various biological factors. Consequently, there is an urgent need for a comprehensive multi-omics resource to help researchers in conducting multi-omics data analysis for MDD. To address this issue, we constructed the MDDOmics database (Major Depressive Disorder Omics, (https://www.csuligroup.com/MDDOmics/), which integrates an extensive collection of published multi-omics data related to MDD. The database contains 41 222 entries of MDD research results and several original datasets, including Single Nucleotide Polymorphisms, genes, non-coding RNAs, DNA methylations, metabolites and proteins, and offers various interfaces for searching and visualization. We also provide extensive downstream analyses of the collected MDD data, including differential analysis, enrichment analysis and disease-gene prediction. Moreover, the database also incorporates multi-omics data for bipolar disorder, schizophrenia and anxiety disorder, due to the challenge in differentiating MDD from similar psychiatric disorders. In conclusion, by leveraging the rich content and online interfaces from MDDOmics, researchers can conduct more comprehensive analyses of MDD and its similar disorders from various perspectives, thereby gaining a deeper understanding of potential MDD biomarkers and intricate disease pathogenesis. Database URL: https://www.csuligroup.com/MDDOmics/.

The role of SKA2 on affective disorder, post-traumatic stress disorder and suicide behavior: systematic review and in silico analysis

Genes involved in the hypothalamic-pituitary-adrenal axis may be a robust biomarker of psychiatric disorders. Genetic polymorphisms of the SKA2 gene are associated with several behavioral disorders. In this study, we embarked on a systematic search of all possible reports of genetic association with SKA2 and affective disorder, post-traumatic stress disorder, and suicide behavior; the functional consequences of nsSNPs were explored through computational tools with an in silico analysis. Eight eligible articles were included. Our study identified that SKA2 did not show association with risk of Major Depression Disorder. Epigenetic variation at SKA2 mediates vulnerability to Post-Traumatic Stress Disorder. Studies provide strong preliminary evidence that alterations at the SKA2 gene covary with types of suicide behavior, including suicidal ideation, attempts, and completions. Results from in silico analysis predicted that I22S, I22G, I78T, A15L, D18R, R25L, N42I, Y21S, K14I, K14L, and L60R were the most structurally and functionally significant nsSNPs in SKA2. Amino acid conservation analysis revealed that the amino acids were highly conserved and some dissimilarities of mutant type amino acids from wild-type amino acids such as charge, size, and hydrophobicity were observed. In the future, SKA2 gene have the potential to be evaluated as prognostic biomarkers for diagnosis and research.

Moderate Alcohol Consumption Increases the Risk of Clinical Relapse in Male Depressed Patients Treated with Serotonin-Norepinephrine Reuptake Inhibitors

BACKGROUND

While depression can be associated with multiple comorbidities, the association between depression and liver injury significantly increases the mortality risk. The aim of this study was to evaluate if moderate alcohol intake affects the rate of clinical relapses in patients treated with antidepressants as monotherapy.

METHODS

We assessed, over a period of 30 months, the clinical records of 254 patients with depressive disorder, of either gender, without additional pathologies, receiving monotherapy treatment with antidepressants. Thirty-three patients with alcohol abuse, alcoholism or significant cognitive impairment were excluded. The medical and psychiatric history, medication and liver enzyme values were collected and analyzed.

RESULTS

Out of the 221 patients who met the inclusion criteria, 78 experienced relapses of depression. The rate of relapse did not correlate with the levels of liver enzymes. Alcohol consumption, as objectified based on GGT levels and the AST/ALT ratio, suggested that men had higher alcohol intake compared to women. Patients treated with serotonin-norepinephrine reuptake inhibitors (SNRIs) with elevated AST levels were approximately 9 times more likely to relapse, while the ones with elevated GGT had a 5.34 times higher risk. While GGT levels remained a marker for relapse in men with elevated GGT, ALT and not AST proved to be a better risk indicator for relapses in male patients.

CONCLUSION

The use of SNRIs in depressed male patients with moderate alcohol intake should be carefully considered, as they might be susceptible to higher risks of relapse compared to alternative antidepressant therapies.

TheMarker: a comprehensive database of therapeutic biomarkers

Distinct from the traditional diagnostic/prognostic biomarker (adopted as the indicator of disease state/process), the therapeutic biomarker (ThMAR) has emerged to be very crucial in the clinical development and clinical practice of all therapies. There are five types of ThMAR that have been found to play indispensable roles in various stages of drug discovery, such as: Pharmacodynamic Biomarker essential for guaranteeing the pharmacological effects of a therapy, Safety Biomarker critical for assessing the extent or likelihood of therapy-induced toxicity, Monitoring Biomarker indispensable for guiding clinical management by serially measuring patients' status, Predictive Biomarker crucial for maximizing the clinical outcome of a therapy for specific individuals, and Surrogate Endpoint fundamental for accelerating the approval of a therapy. However, these data of ThMARs has not been comprehensively described by any of the existing databases. Herein, a database, named 'TheMarker', was therefore constructed to (a) systematically offer all five types of ThMAR used at different stages of drug development, (b) comprehensively describe ThMAR information for the largest number of drugs among available databases, (c) extensively cover the widest disease classes by not just focusing on anticancer therapies. These data in TheMarker are expected to have great implication and significant impact on drug discovery and clinical practice, and it is freely accessible without any login requirement at: https://idrblab.org/themarker.

Reduced urine pregnenolone concentration after clinical response in patients with depression: An open-label short-term prospective study

BACKGROUND

Identifying biological alterations in patients with depression, particularly those that differ between responders and non-responders, is of interest to clinical practice. Biomarker candidates involve neuroactive steroids, including pregnenolone (PREG) and allopregnanolone (ALLO). However, alterations in PREG and ALLO associated with treatment response are understudied. This study's main aim was to evaluate the effects of antidepressant treatment, clinical response, and treatment duration on PREG and ALLO in depression.

MATERIALS AND METHODS

In a 4-week, open-label trial, participants were allocated randomly to the venlafaxine (n = 27) or mirtazapine (n = 30) group. Urine concentrations of PREG and ALLO were assessed through gas chromatography-mass spectrometry. Participants collected night urine between 10:30 p.m. and 8:00 a.m. Two primary outcomes were analyzed. Firstly, the effect of treatment (mirtazapine or venlafaxine), clinical response (operationalized through the Hamilton Depression Rating Scale), and time (baseline compared to 28 days) on the urine concentrations of PREG or ALLO in depression. Finally, the effect of clinical response and time on the urine concentration of PREG or ALLO, independently of the antidepressant given (mirtazapine or venlafaxine). Linear mixed models were carried out.

RESULTS

There was no significant difference in PREG and ALLO concentrations between baseline and 28 days in responders and non-responders when investigating the venlafaxine or the mirtazapine group. However, we found a significant reduction of urine PREG concentration after 28 days of treatment in responders who received either venlafaxine or mirtazapine (estimate = -0.56; p = 0.016; 95CI [-1.003; -0.115]; Cohen's d = -0.61).

CONCLUSIONS

Our main results indicate that responders in depression show reduced urinary PREG concentrations after 4-weeks of therapy, independently of the antidepressant used. More studies are needed to confirm these findings.

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.

Combined influence of depression and low-grade inflammation on mortality in peritoneal dialysis patients

BACKGROUND

The relationship between depression and systemic inflammation as risk factors for mortality is not well understood and requires further investigation.

METHODS

Patients undergoing continuous ambulatory peritoneal dialysis (CAPD) between July 01, 2015 to December 31, 2019, were analyzed and followed up until December 31, 2020. According to their status of depression (PHQ-9 score ≥ 5) and low-grade inflammation (hs-CRP level ≥ 3 mg/L), patients were divided into four groups (G1, without depression, nor inflammation; G2, with depression, without inflammation; G3, with inflammation, without depression; G4, with both depression and inflammation). We performed Kaplan-Meier and multivariable Cox proportional analyses of mortality for the combined influence of depression and systemic inflammation in this cohort.

RESULTS

During the mean follow-up of 36.3 ± 14.8 months, 73 deaths were recorded in 358 participants. Compared with patients in group G1, patients in group G2 and G3 carried 137% {hazard ratio (HR): 2.37, 95% confidence interval (CI): 1.06-5.23, p = 0.035} and 140% (HR: 2.40, 95% CI: 1.01-5.69, p = 0.048) higher risk of mortality. Patients in group G4 (with both depression and inflammation) showed the highest risks of all-cause mortality with 276% higher mortality risk (HR: 3.76, 95% CI: 1.73-8.15, p = 0.001), respectively.

CONCLUSION

The combined of depression and inflammation is associated with all-cause mortality in peritoneal dialysis patients, suggesting a need for further study of depression and low-grade inflammation in PD patients and potential relationship between them.

Functional connectivity analysis on electroencephalography signals reveals potential biomarkers for treatment response in major depression

BACKGROUND

The treatment efficacy varies across individual patients with major depressive disorder (MDD). It lacks robust electroencephalography (EEG) markers for an antidepressant-responsive phenotype.

METHOD

This is an observational study enrolling 28 patients with MDD and 33 healthy controls (mean age of 40.7 years, and 71.4% were women). Patients underwent EEG exams at baseline (week0) and week1, while controls' EEG recordings were acquired only at week0. A resting eye-closing EEG segment was analyzed for functional connectivity (FC). Four parameters were used in FC analysis: (1) node strength (NS), (2) global efficiency (GE), (3) clustering coefficient (CC), and (4) betweenness centrality (BC).

RESULTS

We found that controls had higher values in delta wave in the indices of NS, GE, BC, and CC than MDD patients at baseline. After treatment with antidepressants, patients' FC indices improved significantly, including GE, mean CC, and mean NS in the delta wave. The FC in the alpha and beta bands of the responders were higher than those of the non-responders.

CONCLUSIONS

The FC of the MDD patients at baseline without treatment was worse than that of controls. After treatment, the FC improved and was close to the values of controls. Responders showed better FC in the high-frequency bands than non-responders, and this feature exists in both pre-treatment and post-treatment EEG.

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.

Chronobiological parameters as predictors of early treatment response in major depression

BACKGROUND

Alterations in circadian system organization have been related to major depressive disorder manifestations. This study aimed to evaluate chronobiological parameters, such as sleep, levels of 6-sulfatoxymelatonin, and others derived from actimetry as potential predictors of adequate treatment response in MDD.

METHODS

98 adult women with confirmed diagnosis of MDD were included. Participants completed standard questionnaires (Hamilton Depression Rating Scale - HAM-D; Munich Chronotype Questionnaire - MCTQ) at baseline and after 4 weeks of treatment. Urinary samples for assessing 6-sulfatoxymelatonin were collected on the day before and immediately after pharmacological treatment administration, and 28 continuous days of actigraphy data were collected during the protocol. Participants were classified into Responder (R) or Non-responder (NR) to antidepressant treatment in 4 weeks (early responder), which was characterized by a ≥50 % decrease in the HAM-D score.

RESULTS

The following biological rhythms variables significantly predicted a better treatment response in a model controlling for age, sex, and previous treatments: higher levels of activity (M10 - average activity in the 10 most active hours within the 24 h-day) and an earlier center of the 10 most active hours (M10c), as well as lower intradaily variability (IV) of light exposure. Sleep parameters and 6-sulfatoxymelatonin levels did not associate with treatment response prediction.

LIMITATION

Actimetry data were not assessed before changing in the treatment plan.

CONCLUSION

Different patterns in activity and light exposure might be linked to early antidepressant response.

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.

Predicting treatment outcome in depression: an introduction into current concepts and challenges

Improving response and remission rates in major depressive disorder (MDD) remains an important challenge. Matching patients to the treatment they will most likely respond to should be the ultimate goal. Even though numerous studies have investigated patient-specific indicators of treatment efficacy, no (bio)markers or empirical tests for use in clinical practice have resulted as of now. Therefore, clinical decisions regarding the treatment of MDD still have to be made on the basis of questionnaire- or interview-based assessments and general guidelines without the support of a (laboratory) test. We conducted a narrative review of current approaches to characterize and predict outcome to pharmacological treatments in MDD. We particularly focused on findings from newer computational studies using machine learning and on the resulting implementation into clinical decision support systems. The main issues seem to rest upon the unavailability of robust predictive variables and the lacking application of empirical findings and predictive models in clinical practice. We outline several challenges that need to be tackled on different stages of the translational process, from current concepts and definitions to generalizable prediction models and their successful implementation into digital support systems. By bridging the addressed gaps in translational psychiatric research, advances in data quantity and new technologies may enable the next steps toward precision psychiatry.

The Association of Biochemical and Genetic Biomarkers in VEGF Pathway with Depression

VEGF is an important neurotrophic and vascular factor involved in mental disorders. The objective of this study was to verify the effect of genetic polymorphisms in the VEGF pathway on the risk for depression, symptom intensity, and suicide attempts. To examine the association between the VEGF pathway and depression, we genotyped polymorphisms and measured the plasma concentrations of VEGF, KDR, and FLT1 proteins. The participants were 160 patients with depression and 114 healthy controls. The questionnaires that assessed the clinical profile of the patients were the MINI-International Neuropsychiatric Interview, GRID-HAMD21, CTQ, BSI, and the number of suicide attempts. Genotyping of participants was performed using the real-time PCR and protein measurements were performed using the enzyme-linked immunosorbent assay (ELISA). VEGF and its inhibitors were reduced in depression. Individuals with depression and displaying the homozygous AA of the rs699947 polymorphism had higher plasma concentrations of VEGF (p-value = 0.006) and were associated with a greater number of suicide attempts (p-value = 0.041). Individuals with depression that were homozygous for the G allele of the FLT1 polymorphism rs7993418 were associated with lower symptom severity (p-value = 0.040). Our results suggest that VEGF pathway polymorphisms are associated with the number of suicide attempts and the severity of depressive symptoms.

Moderators of ayahuasca's biological antidepressant action

Introduction

The understanding of biological responses to psychedelics with antidepressant potential is imperative. Here we report how a set of acute parameters, namely emotional (depressive symptoms), cognitive (psychedelic experience), and physiological (salivary cortisol), recorded during an ayahuasca dosing session, modulated serum brain-derived neurotrophic factor (BDNF), serum cortisol (SC), serum interleukin 6 (IL-6), plasma C-reactive protein (CRP), and salivary cortisol awakening response (CAR).

Methods

Results were analyzed 2 days after the psychedelic intervention (ayahuasca) versus placebo in both patients with treatment-resistant depression and healthy volunteers. These measures were assessed as part of a randomized double-blinded, placebo-controlled trial (n = 72).

Results

Results revealed that larger reductions of depressive symptoms during the dosing session significantly moderated higher levels of SC in patients. Whereas lesser changes in salivary cortisol levels during the ayahuasca intervention were related to higher BDNF levels in patients with a larger clinical response in the reduction in depressive symptoms. No moderator was found for patient's CAR, IL-6, and CRP responses to ayahuasca and for all biomarker responses to ayahuasca in healthy controls and in the placebo group.

Discussion

In summary, some specific emotional and physiological parameters during experimental ayahuasca session were revealed as critical moderators of the improvement of major depression biomarkers, mainly BDNF and SC two days after ayahuasca intake. These findings contribute to paving the way for future studies investigating the biological antidepressant response to psychedelic therapy.

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.

Transcriptomics and miRNomics data integration in lymphoblastoid cells highlights the key role of immune-related functions in lithium treatment response in Bipolar disorder

BACKGROUND

Bipolar Disorder (BD) is a complex mental disease characterized by recurrent episodes of mania and depression. Lithium (Li) represents the mainstay of BD pharmacotherapy, despite the narrow therapeutic index and the high variability in treatment response. However, although several studies have been conducted, the molecular mechanisms underlying Li therapeutic effects remain unclear.

METHODS

In order to identify molecular signatures and biological pathways associated with Li treatment response, we conducted transcriptome and miRNome microarray analyses on lymphoblastoid cell lines (LCLs) from 20 patients diagnosed with BD classified as Li responders (n = 11) or non-responders (n = 9).

RESULTS

We found 335 mRNAs and 77 microRNAs (miRNAs) significantly modulated in BD responders versus non-responders. Interestingly, pathway and network analyses on these differentially expressed molecules suggested a modulatory effect of Li on several immune-related functions. Indeed, among the functional molecular nodes, we found NF-κB and TNF. Moreover, networks related to these molecules resulted overall inhibited in BD responder patients, suggesting anti-inflammatory properties of Li. From the integrative analysis between transcriptomics and miRNomics data carried out using miRComb R package on the same samples from patients diagnosed with BD, we found 97 significantly and negatively correlated mRNA-miRNA pairs, mainly involved in inflammatory/immune response.

CONCLUSIONS

Our results highlight that Li exerts modulatory effects on immune-related functions and that epigenetic mechanisms, especially miRNAs, can influence the modulation of different genes and pathways involved in Li response. Moreover, our data suggest the potentiality to integrate data coming from different high-throughput approaches as a tool to prioritize genes and pathways.

Retinal markers of therapeutic responses in major depressive disorder: Effects of antidepressants on retinal function

BACKGROUND

One goal of research into major depressive disorder (MDD) is to develop markers to predict and monitor the response to psychotropic treatments. The retina is endowed with a complex neurotransmission system, composed of the main neurotransmitters involved in the pathophysiology of MDD. The retina is therefore a relevant site of investigation for the identification of reliable and robust markers. However, the effects of antidepressants on the human retina are poorly studied. Here, we seek to study the potential specific effects of various antidepressants on retinal function in MDD patients.

METHODS

We assessed retinal function using flash (fERG), pattern (PERG) and multifocal (mfERG) electroretinogram in 19 MDD patients treated using antidepressants at baseline and at weeks 4, 8 and 12.

RESULTS

We observed reduced b-wave amplitude of photopic fERG 3.0 in patients treated with Selective Serotonin Reuptake Inhibitor (SSRI) in comparison with patients treated with Serotonin-Norepinephrine Reuptake Inhibitor (SNRI) or Tricyclic Antidepressant (TCAD). We also showed that SNRIs were associated both with a decrease in PERG P50 implicit time and an increase in fERG 3.0 b-wave amplitude. TCADs were associated with an increase in fERG flicker 3.0 a- and b-wave amplitude.

CONCLUSIONS

This is the first study in real-life conditions to show a specific effect of various antidepressants on retinal function evaluated by electroretinogram. Further investigations should be led to specify the effects of antidepressants on ERG in order to isolate reliable and reproducible markers for predicting and monitoring the response to antidepressants.

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.

Neural circuits underpinning face tuning in male depression

Reading bodies and faces is essential for efficient social interactions, though it may be thought-provoking for individuals with depression. Yet aberrations in the face sensitivity and underwriting neural circuits are not well understood, in particular, in male depression. Here, we use cutting-edge analyses of time course and dynamic topography of gamma oscillatory neuromagnetic cortical activity during administration of a task with Arcimboldo-like images. No difference in face tuning was found between individuals with depression and their neurotypical peers. Furthermore, this behavioral outcome nicely dovetails with magnetoencephalographic data: at early processing stages, the gamma oscillatory response to images resembling a face was rather similar in patients and controls. These bursts originated primarily from the right medioventral occipital cortex and lateral occipital cortex. At later processing stages, however, its topography altered remarkably in depression with profound engagement of the frontal circuits. Yet the primary difference in depressive individuals as compared with their neurotypical peers occurred over the left middle temporal cortices, a part of the social brain, engaged in feature integration and meaning retrieval. The outcome suggests compensatory recruitment of neural resources in male depression.

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.

The pharmacogenomics of selective serotonin reuptake inhibitors

Antidepressant medications are frequently used as the first line of treatment for depression. However, their effectiveness is highly variable and influenced by genetic factors. Recently, pharmacogenetic studies, including candidate-gene, genome-wide association studies or polygenic risk scores, have attempted to uncover the genetic architecture of antidepressant response. Genetic variants in at least 27 genes are linked to antidepressant treatment response in both coding and non-coding genomic regions, but evidence is largely inconclusive due to the high polygenicity of the trait and limited cohort sizes in published studies. Future studies should increase the number and diversity of participants to yield sufficient statistical power to characterize the genetic underpinnings and biological mechanisms of treatment response, improve results generalizability and reduce racial health-related inequities.

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.

Prediction of Antidepressant Efficacy by Cognitive Function in First-Episode Late-Life Depression: A Pilot Study

The response rate of treatment for late-life depression (LLD) is only 25-60%. The cognitive impairment associated with LLD often affects the effectiveness of antidepressants and may has the potential ability to predict response. This study seeks a biomarker for baseline cognitive function to predict efficacy of antidepressants. Sixty patients diagnosed with LLD received escitalopram or sertraline treatment for 8 weeks. Clinical symptom was measured using Hamilton Depression Rating Scale-17 (HAMD-17) and cognitive function was measured using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), Trail Making Test (TMT) before and after 8-week treatment. Patients were divided into treatment effective group (TE) and treatment ineffective group (TI) according to reduction rate in scores of HAMD-17 after treatment. Thirty-eight matched healthy controls (HC) were assessed using RBANS and TMT. There was significant decrease of score of RBANS and increase of score of TMT in patients with LLD compared with HC. Regression analysis revealed that change in HAMD-17 score was significantly positively associated with baseline score of picture naming, figure copy, digit span, and delayed memory. The preliminary findings suggested that working memory, attention, visuospatial, language function, and delayed memory should be examined further as a means of providing the useful objective biomarkers of treatment response.

CLINICAL TRIALS REGISTRATION

[www.ClinicalTrials.gov], identifier [ChiCTR2100042370].

Sex differences in the blood-brain barrier: Implications for mental health

Prevalence of mental disorders, including major depressive disorder (MDD), bipolar disorder (BD) and schizophrenia (SZ) are increasing at alarming rates in our societies. Growing evidence points toward major sex differences in these conditions, and high rates of treatment resistance support the need to consider novel biological mechanisms outside of neuronal function to gain mechanistic insights that could lead to innovative therapies. Blood-brain barrier alterations have been reported in MDD, BD and SZ. Here, we provide an overview of sex-specific immune, endocrine, vascular and transcriptional-mediated changes that could affect neurovascular integrity and possibly contribute to the pathogenesis of mental disorders. We also identify pitfalls in current literature and highlight promising vascular biomarkers. Better understanding of how these adaptations can contribute to mental health status is essential not only in the context of MDD, BD and SZ but also cardiovascular diseases and stroke which are associated with higher prevalence of these conditions.

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.

Comparison of Peripheral Biomarkers and Reduction of Stress Response in Patients With Major Depressive Disorders vs. Panic Disorder

Alteration in stress response seems to affect the development of psychiatric disorders. In this study, we aimed to investigate whether baseline peripheral biomarkers could predict the reduction of stress response among patients with major depressive disorder (MDD) and panic disorder (PD). Patients with MDD (n = 41) and PD (n = 52) and healthy controls (HC, n = 59) were selected and regularly followed up with five visits for 12 weeks. The severity of stress at every visit was assessed using the Stress Response Inventory (SRI), and peripheral biomarkers were measured by blood tests at baseline and 2, 4, 8, and 12 weeks. Interleukin (IL)-6, IL-10, tumor necrosis factor (TNF)-α, interferon (IFN)-γ, C-reactive protein (CRP), adiponectin, and leptin levels were analyzed using enzyme-linked immunosorbent assays. Reduction of stress response was defined as the difference in SRI score between baseline and 12 weeks divided by the baseline score. SRI scores were significantly (p < 0.0001) higher in patients with MDD and PD than in HC at every visit after adjusting for variables. In multivariable linear regression, adiponectin levels at baseline were significantly associated with reduction of stress response in patients with PD. When adiponectin increased 1 mg/l, stress response decreased 0.781 points (β = -0.781, S.E. = 0.220, p = 0.001). Among the subscales of SRI, somatization had a moderate negative correlation with adiponectin levels (r = -0.469). There was no significant association between baseline peripheral biomarkers and reduction of stress response in patients with MDD. Our study showed an inverse association between baseline adiponectin levels and stress response changes in patients with PD, but not in patients with MDD. Thus, differentiated approaches for assessing and treating stress responses of patients with PD and MDD might be helpful. Larger and longitudinal studies are necessary to establish the role and mechanism of action of adiponectin in regulating stress responses in PD.

Circulating Nucleic Acid-Based Biomarkers of Type 2 Diabetes

Type 2 diabetes (T2D) is a deficiency in how the body regulates glucose. Uncontrolled T2D will result in chronic high blood sugar levels, eventually resulting in T2D complications. These complications, such as kidney, eye, and nerve damage, are even harder to treat. Identifying individuals at high risk of developing T2D and its complications is essential for early prevention and treatment. Numerous studies have been done to identify biomarkers for T2D diagnosis and prognosis. This review focuses on recent T2D biomarker studies based on circulating nucleic acids using different omics technologies: genomics, transcriptomics, and epigenomics. Omics studies have profiled biomarker candidates from blood, urine, and other non-invasive samples. Despite methodological differences, several candidate biomarkers were reported for the risk and diagnosis of T2D, the prognosis of T2D complications, and pharmacodynamics of T2D treatments. Future studies should be done to validate the findings in larger samples and blood-based biomarkers in non-invasive samples to support the realization of precision medicine for T2D.

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.

Hypothalamus volume and DNA methylation of stress axis genes in major depressive disorder: A CAN-BIND study report

Dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis is considered one of the mechanisms underlying the development of major depressive disorder (MDD), but the exact nature of this dysfunction is unknown. We investigated the relationship between hypothalamus volume (HV) and blood-derived DNA methylation in MDD. We obtained brain MRI, clinical and molecular data from 181 unmedicated MDD and 90 healthy control (HC) participants. MDD participants received a 16-week standardized antidepressant treatment protocol, as part of the first Canadian Biomarker Integration Network in Depression (CAN-BIND) study. We collected bilateral HV measures via manual segmentation by two independent raters. DNA methylation and RNA sequencing were performed for three key HPA axis-regulating genes coding for the corticotropin-binding protein (CRHBP), glucocorticoid receptor (NR3C1) and FK506 binding protein 5 (FKBP5). We used elastic net regression to perform variable selection and assess predictive ability of methylation variables on HV. Left HV was negatively associated with duration of current episode (ρ = -0.17, p = 0.035). We did not observe significant differences in HV between MDD and HC or any associations between HV and treatment response at weeks 8 or 16, overall depression severity, illness duration or childhood maltreatment. We also did not observe any differentially methylated CpG sites between MDD and HC groups. After assessing functionality by correlating methylation levels with RNA expression of the respective genes, we observed that the number of functionally relevant CpG sites differed between MDD and HC groups in FKBP5 (χ² = 77.25, p < 0.0001) and NR3C1 (χ² = 7.29, p = 0.007). Cross-referencing functionally relevant CpG sites to those that were highly ranked in predicting HV in elastic net modeling identified one site from FKBP5 (cg03591753) and one from NR3C1 (cg20728768) within the MDD group. Stronger associations between DNA methylation, gene expression and HV in MDD suggest a novel putative molecular pathway of stress-related sensitivity in depression. Future studies should consider utilizing the epigenome and ultra-high field MR data which would allow the investigation of HV sub-fields.

Faster speed of onset of the depressive episode is associated with lower cytokine serum levels (IL-2, -4, -6, -10, TNF-α and IFN-γ) in patients with major depression

INTRODUCTION

Cytokines might play a key role in the pathophysiology of major depressive disorder (MDD). The speed of onset of depressive episodes has been discussed as an important clinical parameter in MDD. The aim of this study was to investigate a potential influence of the speed of onset of the depressive episode on cytokine serum levels.

METHOD

Serum level of the cytokines interleukin (IL)-2, IL-4, IL-6, IL-8, IL-10, tumor necrosis factor alpha (TNF-α), interferon-gamma (IFN-γ) granulocyte and monocyte colony stimulating factor (GM-CSF) were measured in a total of 92 patients with MDD that did not respond to at least one previous antidepressant treatment. Patients were retrospectively divided in two groups: Faster (≤4 weeks) and slower (>4 weeks) onset of the depressive episode defined as the time passing from the first depressive symptoms to a full-blown depressive episode by using information from a clinical interview.

RESULTS

We found significantly lower serum levels of IL-2, IL-4, IL-6, IL-10, TNF-α and IFN-γ in patients with a faster onset compared to patients with a slower onset of the depressive episodes. Furthermore, lower cytokine serum levels of IL-2, IL-8, IL-10 and IFN-γ were found in patients with a shorter duration (less than 6 months) compared to a longer duration (6-24 months) of the current depressive episode. This effect on cytokines was independent from the effect of the speed of onset of the depressive episode.

CONCLUSIONS

Patients with faster onset of the depressive episode might represent a biological subtype of MDD with lower serum levels of IL-2, IL-4, IL-6, IL-10, TNF-α and IFN-γ.

Pathophysiology of Major Depression by Clinical Stages

The comprehension of the pathophysiology of the major depressive disorder (MDD) is essential to the strengthening of precision psychiatry. In order to determine the relationship between the pathophysiology of the MDD and its clinical progression, analyzed by severity of the depressive symptoms and sleep quality, we conducted a study assessing different peripheral molecular biomarkers, including the levels of plasma C-reactive protein (CRP), serum mature brain-derived neurotrophic factor (mBDNF), serum cortisol (SC), and salivary cortisol awakening response (CAR), of patients with MDD (n = 58) and a control group of healthy volunteers (n = 62). Patients with the first episode of MDD (n = 30) had significantly higher levels of CAR and SC than controls (n = 32) and similar levels of mBDNF of controls. Patients with treatment-resistant depression (TRD, n = 28) presented significantly lower levels of SC and CAR, and higher levels of mBDNF and CRP than controls (n = 30). An increased severity of depressive symptoms and worse sleep quality were correlated with levels low of SC and CAR, and with high levels of mBDNF. These results point out a strong relationship between the stages clinical of MDD and changes in a range of relevant biological markers. This can assist in the development of precision psychiatry and future research on the biological tests for depression.

Factors related to retinal nerve fiber layer thickness in bipolar disorder patients and major depression patients

BACKGROUND

We analyzed the correlation of the clinical data with retinal nerve fiber layer (RNFL) thickness and macular thickness in bipolar disorder patients and major depression patients. The aim of this study is to explore factors that affect RNFL thickness in bipolar disorder patients and major depression patients, with a view to providing a new diagnostic strategy.

METHODS

Eighty-two bipolar disorder patients, 35 major depression patients and 274 people who were age and gender matched with the patients were enrolled. Demographic information and metabolic profile of all participants were collected. Best-corrected visual acuity of each eye, intraocular pressure (IOP), fundus examination was performed. RNFL and macular thickness were measured by optical coherence tomography (OCT). Correlations between RNFL and macular thickness and other data were analyzed.

RESULTS

RNFL and macula lutea in bipolar dipolar patients and major depression patients are thinner than normal people. Triglyceride and UA levels are the highest in the bipolar disorder group, while alanine aminotransferase (ALT) and glutamic oxalacetic transaminase (AST) levels in the depression group are the highest. Age onset and ALT are positively while uric acid (UA) is negatively correlated with RNFL thickness in bipolar dipolar patients. Cholesterol level is positively correlated with RNFL thickness while the duration of illness is correlated with RNFL thickness of left eye in major depression patients.

CONCLUSIONS

RNFL and macula lutea in bipolar dipolar patients and major depression patients are thinner than normal people. In bipolar disorder patients, age-onset and ALT are potential protective factors in the progress of RNFL thinning, while UA is the pathological factor.

Comorbid Chronic Pain and Depression: Shared Risk Factors and Differential Antidepressant Effectiveness

The bidirectional relationship between depression and chronic pain is well-recognized, but their clinical management remains challenging. Here we characterize the shared risk factors and outcomes for their comorbidity in the Australian Genetics of Depression cohort study (N = 13,839). Participants completed online questionnaires about chronic pain, psychiatric symptoms, comorbidities, treatment response and general health. Logistic regression models were used to examine the relationship between chronic pain and clinical and demographic factors. Cumulative linked logistic regressions assessed the effect of chronic pain on treatment response for 10 different antidepressants. Chronic pain was associated with an increased risk of depression (OR = 1.86 [1.37-2.54]), recent suicide attempt (OR = 1.88 [1.14-3.09]), higher use of tobacco (OR = 1.05 [1.02-1.09]) and misuse of painkillers (e.g., opioids; OR = 1.31 [1.06-1.62]). Participants with comorbid chronic pain and depression reported fewer functional benefits from antidepressant use and lower benefits from sertraline (OR = 0.75 [0.68-0.83]), escitalopram (OR = 0.75 [0.67-0.85]) and venlafaxine (OR = 0.78 [0.68-0.88]) when compared to participants without chronic pain. Furthermore, participants taking sertraline (OR = 0.45 [0.30-0.67]), escitalopram (OR = 0.45 [0.27-0.74]) and citalopram (OR = 0.32 [0.15-0.67]) specifically for chronic pain (among other indications) reported lower benefits compared to other participants taking these same medications but not for chronic pain. These findings reveal novel insights into the complex relationship between chronic pain and depression. Treatment response analyses indicate differential effectiveness between particular antidepressants and poorer functional outcomes for these comorbid conditions. Further examination is warranted in targeted interventional clinical trials, which also include neuroimaging genetics and pharmacogenomics protocols. This work will advance the delineation of disease risk indicators and novel aetiological pathways for therapeutic intervention in comorbid pain and depression as well as other psychiatric comorbidities.

Depression and metabolic syndrome in participants of the "Seguimiento Universidad de Navarra" (SUN) cohort study

BACKGROUND

Depression is a major public health concern worldwide and its association with metabolic syndrome (MetS) remains unclear. Thus, we prospectively examined the association between depression and the risk of MetS, according to different diagnosis criteria.

METHODS

This study included 9,237 participants of a Spanish dynamic prospective cohort of adult university graduates [mean (SD) age: 36.7 year (10.7)], initially free of any specific criterion of MetS, who were followed-up for a median of 8.3 years. The exposure variables were medical diagnosis of depression at baseline or in the first 2-year follow-up questionnaire. The outcome variable was the incidence of MetS, assessed according to each of three different criteria proposed by: International Diabetes Federation (IDF); National Cholesterol Education Program's Adult Treatment Panel III (NCEP-ATP III); IDF/NCEP-ATP III (updated harmonizing definition). Multivariable-adjusted Relative Risks (RR) of new-onset MetS and their 95% Confidence Intervals (95% CI) were estimated, using Poisson regression models.

RESULTS

The cumulative incidences of MetS were 475 cases (IDF definition), 288 cases (NCEP-ATP III definition) and 492 cases (update harmonized definition). No association was observed between baseline depression and incidence of MetS, but the presence of depression after 2-years of follow-up was significantly associated with a higher risk of new-onset MetS, according to NCEP-ATP III definition (multivariable-adjusted RR, 2.46; 95% CI, 1.06-5.67).

LIMITATIONS

Diagnosis of depression and MetS were self-reported.

CONCLUSIONS

In this large prospective cohort of Spanish middle-aged adult university graduates, a direct association between depression and the risk of MetS according to NCEP-ATP III definition was found.

Neuro-dermatological association between psoriasis and depression: an immune-mediated inflammatory process validating skin-brain axis theory

Objective

Our study's motive was to recognize various immune-mediated inflammatory processes involved in the pathogenesis of depression and psoriasis and interlink between them based on inflammatory mediators.

Methods

A careful and comprehensive literature search was done through various databases like PubMed, Google Scholar, and EBSCO. A total of 56 studies were included in our study after careful screening.

Results

The immune-mediated inflammatory process was significantly associated with the pathogenesis of both depression and psoriasis. Most of the inflammatory markers involved in Psoriasis (TNF-α, IL-2, IL-6, IL-23, IL-1β, IL-10), and increased serotonin transporters (5-HTT) were also found in the pathogenesis of depression, showing the immune-inflammatory linkage between psoriasis and major depression. Based on immune chemistry, the levels of CD2⁺, CD4⁺, CD8⁺ T-lymphocytes were also found to be raised in both depression and psoriasis, validating their relationship. Hyperactivity of HPA-axis was also found another interlink between them along with reduced melatonin amount.

Conclusions

According to various studies, the neuro-dermatological association between psoriasis and depression is significant. Different immune markers involved in the pathogenesis of depression and psoriasis also show the bidirectional association between them. However, this association between psoriasis and depression is positively correlated, but more work is required to answer why all depressed patients fail to develop psoriasis and why all psoriatic patients fail to develop depression.

Assessing the links between childhood trauma, C-reactive protein and response to antidepressant treatment in patients with affective disorders

Adverse Childhood Experiences (ACE) are a well-known risk-factor for depression. Additionally, (high-sensitive) C-reactive Protein (hsCRP) is elevated in subgroups of depressed patients and high following ACE. In this context the literature considers hsCRP and ACE to be associated with treatment resistant depression. With the data being heterogenous, this study aimed to explore the associations of ACE, hsCRP levels and response to antidepressant treatment in uni- and bipolar depression. N = 76 patients diagnosed with uni- or bipolar depression and N = 53 healthy controls were included. Treatment was over 6 weeks in an inpatient psychiatric setting within an observatory study design. Depressive symptoms were assessed by the Montgomery-Asberg Depression Rating Scale (MADRS), ACE were assessed by the Childhood Trauma Questionnaire (CTQ); the body-mass-index (BMI) and hsCRP were measured. HsCRP levels did not differ between the study population and the healthy controls. While the depressive symptoms decreased, the hsCRP levels increased. Sexual abuse was associated with significant higher and emotional abuse with lower levels of hsCRP after 6 weeks. The baseline hsCRP levels and the ACE subgroups did not show significant associations with the treatment response in unipolar depressed patients. The long-lasting effects of specific forms of ACE may have relevant impact on inflammation, supporting hsCRP to be a suitable biomarker. With ACE and hsCRP not showing any significant associations with treatment response in the unipolar depressed subgroup, a more differentiate research concerning biomarkers and treatment regimens is needed when talking about treatment response.

Changes in inflammatory biomarkers are related to the antidepressant effects of Ayahuasca

BACKGROUND

Ayahuasca is a traditional Amazon brew and its potential antidepressant properties have recently been explored in scientific settings. We conducted a double-blind placebo-controlled trial of ayahuasca with treatment-resistant depression patients (n = 28) and healthy controls (n = 45).

AIMS

We are evaluating the blood inflammatory biomarkers: C-reactive protein and interleukin 6, as a potential consequence of ayahuasca intake and their correlation with serum cortisol and brain-derived neurotrophic factor levels. Blood samples were collected at pre-treatment and 48 hours after substance ingestion to assess the concentration of inflammatory biomarkers, together with administration of the Montgomery-Åsberg Depression Rating Scale.

RESULTS

At pre-treatment, patients showed higher C-reactive protein levels than healthy controls and a significant negative correlation between C-reactive protein and serum cortisol levels was revealed (rho = -0.40, n = 14). C-reactive protein in those patients was not correlated with Montgomery-Åsberg Depression Rating Scale scores. We observed a significant reduction of C-reactive protein levels across time in both patients and controls treated with ayahuasca, but not with placebo. Patients treated with ayahuasca showed a significant correlation (rho = + 0.57) between larger reductions of C-reactive protein and lower depressive symptoms at 48 hours after substance ingestion (Montgomery-Åsberg Depression Rating Scale). No significant result with respect to interleukin 6 and brain-derived neurotrophic factor was found. Furthermore, these biomarkers did not predict the antidepressant response or remission rates observed.

CONCLUSIONS

These findings enhance the understanding of the biological mechanisms behind the observed antidepressant effects of ayahuasca and encourage further clinical trials in adults with depression.

Analyzing Non-verbal Behavior Throughout Recovery in a Sample of Depressed Patients Receiving Deep Brain Stimulation

BACKGROUND

Traditional rating scales for depression rely heavily on patient self-report, and lack detailed measurement of non-verbal behavior. However, there is evidence that depression is associated with distinct non-verbal behaviors, assessment of which may provide useful information about recovery. This study examines non-verbal behavior in a sample of patients receiving Deep Brain Stimulation (DBS) treatment of depression, with the purpose to investigate the relationship between non-verbal behaviors and reported symptom severity.

METHODS

Videotaped clinical interviews of twelve patients participating in a study of DBS for treatment-resistant depression were analyzed at three time points (before treatment and after 3 months and 6 months of treatment), using an ethogram to assess the frequencies of 42 non-verbal behaviors. The Beck Depression Inventory (BDI) and Hamilton Depression Rating Scale (HDRS-17) were also collected at all time points.

RESULTS

Factor analysis grouped non-verbal behaviors into three factors: react, engage/fidget, and disengage. Two-way repeated measures ANOVA showed that scores on the three factors change differently from each other over time. Mixed effects modelling assessed the relationship between BDI score and frequency of non-verbal behaviors, and provided evidence that the frequency of behaviors related to reactivity and engagement increase as BDI score decreases.

LIMITATIONS

This study assesses a narrow sample of patients with a distinct clinical profile at limited time points.

CONCLUSIONS

Non-verbal behavior provides information about clinical states and may be reliably quantified using ethograms. Non-verbal behavior may provide distinct information compared to self-report.

Associations between systemic inflammation and somatic depressive symptoms: Findings from the Moli-sani study

BACKGROUND

The link between systemic inflammation and depression has been deeply investigated, but relatively few studies explored symptom-specific associations, mostly focusing on common inflammatory biomarkers like C-reactive protein (CRP) levels.

METHODS

We investigated associations of low-grade inflammation with depressive symptoms assessed through a reduced version of Patient Health Questionnaire 9 (PHQ-9) in a large population-based cohort of adult Italians (N = 13 301). We built logistic regressions between each depressive symptom and composite index of systemic inflammation based on four circulating biomarkers, namely CRP, Plt, WBC, and GLR (INFLA)-score, a composite blood-based inflammation index, and with its component biomarkers, namely CRP, platelets count (Plt), white blood cells count (WBC), and granulocyte-to-lymphocyte ratio (GLR).

RESULTS

We observed a strong association of the altered appetite/eating symptom with standardized INFLA-score (OR [95% CI] = 1.19 [1.12-1.26]; corrected p = 3.0 × 10-7 ), CRP (1.28 [1.20-1.36]; p = 1.9 × 10-13 ), and WBC (1.13 [1.06-1.20]; p = 2.3 × 10-3 ), and of tiredness/low energy with GLR (1.11 [1.05-1.17]; p = 9.4 × 10-3 ). These associations remained stable within nondepressed participants (PHQ-9 < 10), and after adjustment for the use of antidepressants, main chronic conditions, and lifestyle factors; while they were notably attenuated within depressed participants (PHQ-9 ≥ 10) and-for altered appetite only-by adjustment for obesity.

CONCLUSIONS

This study provides a robust replication of the association previously reported between CRP and altered appetite in a large US population cohort, and supports a link between systemic inflammation, altered appetite, and tiredness. Moreover, it extends this evidence to inflammatory markers other than CRP and suggests new targets for the treatment of atypical depression.

Protein and gene markers of metabolic dysfunction and inflammation together associate with functional connectivity in reward and motor circuits in depression

Bidirectional relationships between inflammation and metabolic dysfunction may contribute to the pathophysiology of psychiatric illnesses like depression. Metabolic disturbances drive inflammation, which in turn exacerbate metabolic outcomes including insulin resistance. Both inflammatory (e.g. endotoxin, vaccination) and metabolic challenges (e.g. glucose ingestion) have been shown to affect activity and functional connectivity (FC) in brain regions that subserve reward and motor processing. We previously reported relationships between elevated concentrations of endogenous inflammatory markers including C-reactive protein (CRP) and low corticostriatal FC, which correlated with symptoms of anhedonia and motor slowing in major depression (MD). Herein, we examined whether similar relationships were observed between plasma markers related to glucose metabolism (non-fasting concentrations of glucose, insulin, leptin, adiponectin and resistin) in 42 medically-stable, unmedicated MD outpatients who underwent fMRI. A targeted, hypothesis-driven approach was used to assess FC between seeds in subdivisions of the ventral and dorsal striatum and a region in ventromedial prefrontal cortex (VS-vmPFC), which was previously found to correlate with both inflammation and symptoms of anhedonia and motor slowing. Associations between FC and gene expression signatures were also explored. A composite score of all 5 glucose-related markers (with increasing values reflecting higher concentrations) was negatively correlated with both ventral striatum (VS)-vmPFC (r = -0.33, p < 0.05) and dorsal caudal putamen (dcP)-vmPFC (r = -0.51, p < 0.01) FC, and remained significant after adjusting for covariates including body mass index (p < 0.05). Moreover, an interaction between the glucose-related composite score and CRP was observed for these relationships (F[2,33] = 4.3, p < 0.05) whereby significant correlations between the glucose-related metabolic markers and FC was found only in patients with high plasma CRP (>3 mg/L; r = -0.61 to -0.81, p < 0.05). Insulin and resistin were the individual markers most predictive of VS-vmPFC and dcP-mPFC FC, respectively, and insulin, resistin and CRP clustered together and in association with both LV-vmPFC and dcP-vmPFC in principal component analyses. Exploratory whole blood gene expression analyses also confirmed that gene probes negatively associated with FC were enriched for both inflammatory and metabolic pathways (FDR p < 0.05). These results provide preliminary evidence that inflammation and metabolic dysfunction contribute jointly to deficits in reward and motor circuits in MD. Future studies using fasting samples and longitudinal and interventional approaches are required to further elucidate the respective contributions of inflammation and metabolic dysfunction to circuits and symptoms relevant to motivation and motor activity, which may have treatment implications for patients with psychiatric illnesses like depression.