Metabolomic and inflammatory signatures of symptom dimensions in major depression

Association between atherogenic index of plasma and depressive symptoms in US adults: Results from the National Health and Nutrition Examination Survey 2005 to 2018

OBJECTIVE

This study, utilizing data from the U.S. National Health and Nutrition Examination Survey (NHANES) between 2005 and 2018, investigates the association between the atherogenic index of plasma (AIP), a lipid biomarker, and symptoms of depression in American adults.

METHODS

In this cross-sectional study of 12,534 adults aged 20 years and older, depressive symptoms were measured utilizing the Patient Health Questionnaire-9 (PHQ-9) scale. Weighted logistic regression models were employed to scrutinize the independent relationship between AIP levels and the likelihood of developing such symptoms. Moreover, a series of subgroup analyses were conducted to delve deeper into these relationships.

RESULTS

Following adjustment for confounders, logistic regression by grouping AIP into quartiles revealed a significant association between AIP and an augmented likelihood of self-reported depression. Participants in the fourth quartile (Q4) exhibited a higher odds ratio (OR = 1.34, 95 % CI: 1.02-1.75, p < 0.05) compared to those in the first quartile (Q1). Notably, subgroup analysis unveiled significant interactions involving the smoking and diabetes subgroups, indicating that smoking status and diabetes may modify the relationship between AIP and depression incidence.

CONCLUSION

This study reveals a positive correlation between AIP and the self-reported likelihood of depression among US adults, thereby underscoring AIP's potential clinical utility as a biomarker for depressive disorders. Our findings emphasize the necessity to consider and optimize cardiovascular health factors within depression management strategies and offer fresh insights into the development of risk stratification and intervention methods for psychiatric conditions.

NEFA can serve as good biological markers for the diagnosis of depression in adolescents

BACKGROUND

The incidence of adolescent depression has markedly risen in recent years, with a high recurrence rate into adulthood. Diagnosis in adolescents is challenging due to subjective factors, highlighting the crucial need for objective diagnostic markers.

METHODS

Our study enrolled 204 participants, including healthy controls (n = 88) and first-episode adolescent depression patients (n = 116). Serum samples underwent gas chromatography-mass spectrometry (GC-MS) analysis to assess non-esterified fatty acids (NEFA) expression. Machine learning and ROC analysis were employed to identify potential biomarkers, followed by bioinformatics analysis to explore underlying mechanisms.

RESULTS

Nearly all differentially expressed NEFA exhibited significant downregulation. Notably, nonanoic acid, cis-10-pentadecenoic acid, cis-10-carboenoic acid, and cis-11-eicosenoic acid demonstrated excellent performance in distinguishing adolescent depression patients. Metabolite-gene interaction analysis revealed these NEFAs interacted with multiple genes. KEGG pathway analysis on these genes suggested that differentially expressed NEFA may impact PPAR and cAMP signaling pathways.

LIMITATIONS

Inclusion of diverse populations for evaluation is warranted. Biomarkers identified in this study require samples that are more in line with the experimental design for external validation, and further basic research is necessary to validate the potential depressive mechanisms of NEFA.

CONCLUSIONS

The overall reduction in NEFA expression in first-episode adolescent depression patients suggests a potential mediation of depression symptoms through cAMP and PPAR signaling pathways. NEFA levels show promise as a diagnostic tool for identifying first-episode adolescent depression patients.

Abnormal energy metabolism, oxidative stress, and polyunsaturated fatty acid metabolism in depressed adolescents associated with childhood maltreatment: A targeted metabolite analysis

The purpose of this study was to explore the metabolomic differences between Major depressive disorder (MDD) and healthy individuals among adolescents and the association between childhood maltreatment (CM) and differentially abundant metabolites. The exploratory study included 40 first-episode drug-naïve adolescents with MDD and 20 healthy volunteers. We used the Beck Depression Inventory (BDI-13) to assess the severity of depression and the Childhood Trauma Questionnaire (CTQ) to assess the presence of childhood maltreatment. The plasma samples from all participants were collected for targeted metabolomics analysis using ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC‒MS/MS) methods. Spearman correlation was applied to analyse the correlations between clinical variables and metabolites. We found 11 increased metabolites and 37 decreased metabolites that differed between adolescents with MDD and healthy individuals. Pathway enrichment analysis of differentially abundant metabolites showed abnormalities in energy metabolism and oxidative stress in MDD. Importantly, we found that creatine, valine, isoleucine, glutamic acid and pyroglutamic acid were negatively correlated with the BDI-13, while isocitric acid, fatty acid and acylcarnitine were negatively associated with CTQ, and 4-hydroxyproline was positively related to CTQ in adolescents with MDD. These studies provide new ideas for the pathogenesis and potential treatment of adolescents with MDD.

Microglial MyD88-dependent pathways are regulated in a sex specific manner in the context of HMGB1-induced anxiety

Chronic stress is a major risk factor for development and recurrence of anxiety disorders. Chronic stress has been shown to impact the immune system, causing microglial activation in the medial prefrontal cortex (mPFC), a brain region involved in the pathogenesis of anxiety. HMGB1 is both an established modulator of neuronal firing and a potent pro-inflammatory stimulus that is released from neuronal and non-neuronal cells following stress. HMGB1 in the context of stress acts as a danger associated molecular pattern (DAMP) instigating robust proinflammatory responses throughout the brain; so much so, that localized drug delivery of HMGB1 alters behavior in the absence of any other forms of stress i.e. social isolation, or behavioral stress models. Few studies have investigated the molecular mechanisms which underlie HMGB1 associated behavioral effects in a cell-specific manner. The aim of this study is to investigate cellular and molecular mechanisms underlying HMGB1 induced behavioral dysfunction with regards to cell-type specificity and potential sex differences. Here, we report that both male and female mice exhibited anxiety-like behavior following increased HMGB1 in the mPFC as well as changes in microglial morphology. However, only female mice showed microglial activation characterized by increased phagocytic capacity and decreased Tmem119 expression. Moreover, when measuring RNA from isolated microglia and non-microglial cells from the frontal cortex we found that female HMGB1 treated mice displayed a robust increase of RAGE and MyD88. Given these findings, to further investigate the underlying molecular mechanisms associated with HMGB1 induced anxiety-like behavior and microglia activation in mice, we used cKO (conditional knockout) mice with conditional deletion of MyD88 in microglia and repeated the paradigm. For males, we saw that the genetic manipulation did not prevent behavioral deficits in response to HMGB1 treatment. However, female cKO mice were protected from HMGB1- induced behavioral deficits. This study supports the hypothesis that the MyD88 signaling in microglia may be a crucial mediator of stress response in adult female mice.

Gut microbiome in atypical depression

BACKGROUND

Recent studies showed that immunometabolic dysregulation is related to unipolar major depressive disorder (MDD) and that it more consistently maps to MDD patients endorsing an atypical symptom profile, characterized by energy-related symptoms including increased appetite, weight gain, and hypersomnia. Despite the documented influence of the microbiome on immune regulation and energy homeostasis, studies have not yet investigated microbiome differences among clinical groups in individuals with MDD.

METHODS

Fifteen MDD patients with atypical features according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5)-5, forty-four MDD patients not fulfilling the DSM-5 criteria for the atypical subtype, and nineteen healthy controls were included in the study. Participants completed detailed clinical assessment and stool samples were collected. Samples were sequenced for the prokaryotic 16S rRNA gene, in the V3-V4 variable regions. Only samples with no antibiotic exposure in the previous 12 months and a minimum of >2000 quality-filtered reads were included in the analyses.

RESULTS

There were no statistically significant differences in alpha- and beta-diversity between the MDD groups and healthy controls. However, within the atypical MDD group, there was an increase in the Verrucomicrobiota phylum, with Akkermansia as the predominant bacterial genus.

LIMITATIONS

Cross-sectional data, modest sample size, and significantly increased body mass index in the atypical MDD group.

CONCLUSIONS

There were no overall differences among the investigated groups. However, differences were found at several taxonomic levels. Studies in larger longitudinal samples with relevant confounders are needed to advance the understanding of the microbial influences on the clinical heterogeneity of depression.

Dysregulated cerebral blood flow, rather than gray matter Volume, exhibits stronger correlations with blood inflammatory and lipid markers in depression

Arterial spin labeling (ASL) can be used to detect differences in perfusion for multiple brain regions thought to be important in major depressive disorder (MDD). However, the potential of cerebral blood flow (CBF) to predict MDD and its correlations between the blood lipid levels and immune markers, which are closely related to MDD and brain function change, remain unclear. The 451 individuals - 298 with MDD and 133 healthy controls who underwent MRI at a single time point with arterial spin labelling and a high resolution T1-weighted structural scan. A proportion of MDD also provided blood samples for analysis of lipid and immune markers. We performed CBF case-control comparisons, random forest model construction, and exploratory correlation analyses. Moreover, we investigated the relationship between gray matter volume (GMV), blood lipids, and the immune system within the same sample to assess the differences in CBF and GMV. We found that the left inferior parietal but supramarginal and angular gyrus were significantly different between the MDD patients and HCs (voxel-wise P < 0.001, cluster-wise FWE correction). And bilateral inferior temporal (ITG), right middle temporal gyrus and left precentral gyrus CBF predict MDD (the area under the receiver operating characteristic curve of the random forest model is 0.717) and that CBF is a more sensitive predictor of MDD than GMV. The left ITG showed a positive correlation trend with immunoglobulin G (r = 0.260) and CD4 counts (r = 0.283). The right ITG showed a correlation trend with Total Cholesterol (r = -0.249) and tumour necrosis factor-alpha (r = -0.295). Immunity and lipids were closely related to CBF change, with the immunity relationship potentially playing a greater role. The interactions between CBF, plasma lipids and immune index could therefore represent an MDD pathophysiological mechanism. The current findings provide evidence for targeted regulation of CBF or immune properties in MDD.

Acylcarnitines metabolism in depression: association with diagnostic status, depression severity and symptom profile in the NESDA cohort

Background

Acylcarnitines (ACs) are involved in bioenergetics processes that may play a role in the pathophysiology of depression. Studies linking AC levels to depression are few and provide mixed findings. We examined the association of circulating ACs levels with Major Depressive Disorder (MDD) diagnosis, overall depression severity and specific symptom profiles.

Methods

The sample from the Netherlands Study of Depression and Anxiety included participants with current (n=1035) or remitted (n=739) MDD and healthy controls (n=800). Plasma levels of four ACs (short-chain: acetylcarnitine C2 and propionylcarnitine C3; medium-chain: octanoylcarnitine C8 and decanoylcarnitine C10) were measured. Overall depression severity as well as atypical/energy-related (AES), anhedonic and melancholic symptom profiles were derived from the Inventory of Depressive Symptomatology.

Results

As compared to healthy controls, subjects with current or remitted MDD presented similarly lower mean C2 levels (Cohen's d=0.2, p≤1e-4). Higher overall depression severity was significantly associated with higher C3 levels (ß=0.06, SE=0.02, p=1.21e-3). No associations were found for C8 and C10. Focusing on symptom profiles, only higher AES scores were linked to lower C2 (ß=-0.05, SE=0.02, p=1.85e-2) and higher C3 (ß=0.08, SE=0.02, p=3.41e-5) levels. Results were confirmed in analyses pooling data with an additional internal replication sample from the same subjects measured at 6-year follow-up (totaling 4195 observations).

Conclusions

Small alterations in levels of short-chain acylcarnitine levels were related to the presence and severity of depression, especially for symptoms reflecting altered energy homeostasis. Cellular metabolic dysfunctions may represent a key pathway in depression pathophysiology potentially accessible through AC metabolism.

Mood and microbes: a comprehensive review of intestinal microbiota's impact on depression

Depression is considered a multifaceted and intricate mental disorder of growing concern due to its significant impact on global health issues. The human gut microbiota, also known as the "second brain," has an important role in the CNS by regulating it through chemical, immunological, hormonal, and neurological processes. Various studies have found a significant bidirectional link between the brain and the gut, emphasizing the onset of depression therapies. The biological and molecular processes underlying depression and microbiota are required, as the bidirectional association may represent a novel study. However, profound insights into the stratification and diversity of the gut microbiota are still uncommon. This article investigates the emerging evidence of a bacterial relationship between the gut and the brain's neurological system and its potential pathogenicity and relevance. The interplay of microbiota, immune system, nervous system neurotransmitter synthesis, and neuroplasticity transitions is also widely studied. The consequences of stress, dietary fibers, probiotics, prebiotics, and antibiotics on the GB axis are being studied. Multiple studies revealed the processes underlying this axis and led to the development of effective microbiota-based drugs for both prevention and treatment. Therefore, the results support the hypothesis that gut microbiota influences depression and provide a promising area of research for an improved knowledge of the etiology of the disease and future therapies.

Metabolic Profiling of Aromatic Compounds

Metabolic profiling is a powerful modern tool in searching for novel biomarkers and indicators of normal or pathological processes in the body [...].

Inferior social hierarchy is vulnerable to anxiety-like behavior in chronic pain mice: Potential role of gut microbiota and metabolites

Social dominance is a universal phenomenon among grouped animals that profoundly affects survival, health, and reproductive success by determining access to resources, and exerting a powerful influence on subsequent behavior. However, the understanding of pain and anxiety comorbidities in dominant or subordinate animals suffering from chronic pain is not well-defined. Here, we provide evidence that subordinate mice are more susceptible to pain-induced anxiety compared to dominant mice. We propose that the gut microbiota may play a mediating role in this mechanism. Our findings demonstrate that transplantation of fecal microbiota from subordinate mice with chronic inflammatory pain, but not dominant mice, into antibiotics-treated pseudo-germ-free mice significantly amplifies anxiety-like phenotypes, highlighting the critical involvement of gut microbiota in this behavioral response. Using chronic inflammatory pain model, we carried out 16S rRNA sequencing and untargeted metabolomic analyses to explore the relationship between microbiota and metabolites in a stable social hierarchy of mice. Interestingly, anxiety-like behaviors were directly associated with some microbial genera and metabolites, especially bile acid metabolism. Overall, we have demonstrated a close relationship between social status and anxiety susceptibility, highlighting the contributions of gut microbiota and the associated metabolites in the high-anxiety state of subordinate mice with chronic inflammatory pain.

TGR5 deficiency-induced anxiety and depression-like behaviors: The role of gut microbiota dysbiosis

BACKGROUND AND PURPOSE

Anxiety and depression have been associated with imbalances in the gut microbiota and bile acid metabolism. Takeda G protein-coupled receptor 5 (TGR5), a bile acid receptor involved in metabolism, is influenced by the gut microbiota. This study aimed to investigate the relationship between anxiety, depression, and microbiota using TGR5 knockout mice.

METHODS

We employed the following methods: (1) Assessment of behavioral changes, (2) Measurement of 5-HT levels and protein expression, (3) Analysis of stool samples, (4) Utilization of gene sequencing and statistical analysis to identify microbial signatures, (5) Examination of correlations between microbial signatures and 5-HT levels, and (6) Fecal microbiota transplantation experiments of TGR5-/- mice.

RESULTS

The deletion of TGR5 was found to result in increased anxiety- and depression-like behaviors in mice. TGR5 knockout mice exhibited significant reductions in 5-hydroxytryptamine (5-HT) levels in both serum and hippocampus, accompanied by a decrease in the expression of 5-HT1A receptor in the hippocampus. Moreover, TGR5 deficiency was associated with a decrease in the species richness of the gut microbiota. Specifically, the gut microbiota compositions of TGR5 knockout mice displayed distinct differences compared to their littermates, characterized by higher abundances of Anaeroplasma, Prevotella, Staphylococcus, Jeotgalicoccus, and Helicobacter, and a lower abundance of Bifidobacterium. Notably, a strong association between Jeotgalicoccus as well as Staphylococcus and serum 5-HT levels was observed in co-occurrence network. Furthermore, mice that received fecal microbiota transplants from TGR5-/- mice displayed anxiety and depression -like behaviors, accompanied by alterations in 5-HT levels in the hippocampus and serum.

LIMITATIONS

Study limitations for gut bacteria were analyzed at the genus level only.

CONCLUSION

TGR5 deletion in mice induces anxiety and depression-like behaviors, linked to reduced 5-HT levels in serum and the hippocampus. Gut microbiota changes play a direct role in these behaviors and serotonin alterations. This implicates TGR5 and gut bacteria in mood regulation, with potential therapeutic implications.

A Machine Learning Analysis of Big Metabolomics Data for Classifying Depression: Model Development and Validation

BACKGROUND

Many metabolomics studies of depression have been performed, but these have been limited by their scale. A comprehensive in silico analysis of global metabolite levels in large populations could provide robust insights into the pathological mechanisms underlying depression and candidate clinical biomarkers.

METHODS

Depression-associated metabolomics was studied in 2 datasets from the UK Biobank database: participants with lifetime depression (N = 123,459) and participants with current depression (N = 94,921). The Whitehall II cohort (N = 4744) was used for external validation. CatBoost machine learning was used for modeling, and Shapley additive explanations were used to interpret the model. Fivefold cross-validation was used to validate model performance, training the model on 3 of the 5 sets with the remaining 2 sets for validation and testing, respectively. Diagnostic performance was assessed using the area under the receiver operating characteristic curve.

RESULTS

In the lifetime depression and current depression datasets and sex-specific analyses, 24 significantly associated metabolic biomarkers were identified, 12 of which overlapped in the 2 datasets. The addition of metabolic features slightly improved the performance of a diagnostic model using traditional (nonmetabolomics) risk factors alone (lifetime depression: area under the curve 0.655 vs. 0.658 with metabolomics; current depression: area under the curve 0.711 vs. 0.716 with metabolomics).

CONCLUSIONS

The machine learning model identified 24 metabolic biomarkers associated with depression. If validated, metabolic biomarkers may have future clinical applications as supplementary information to guide early and population-based depression detection.

Recent Progress in Mass Spectrometry-Based Metabolomics in Major Depressive Disorder Research

Major depressive disorder (MDD) is a serious mental illness with a heavy social burden, but its underlying molecular mechanisms remain unclear. Mass spectrometry (MS)-based metabolomics is providing new insights into the heterogeneous pathophysiology, diagnosis, treatment, and prognosis of MDD by revealing multi-parametric biomarker signatures at the metabolite level. In this comprehensive review, recent developments of MS-based metabolomics in MDD research are summarized from the perspective of analytical platforms (liquid chromatography-MS, gas chromatography-MS, supercritical fluid chromatography-MS, etc.), strategies (untargeted, targeted, and pseudotargeted metabolomics), key metabolite changes (monoamine neurotransmitters, amino acids, lipids, etc.), and antidepressant treatments (both western and traditional Chinese medicines). Depression sub-phenotypes, comorbid depression, and multi-omics approaches are also highlighted to stimulate further advances in MS-based metabolomics in the field of MDD research.

A network analysis of depressive symptoms and metabolomics

BACKGROUND

Depression is associated with metabolic alterations including lipid dysregulation, whereby associations may vary across individual symptoms. Evaluating these associations using a network perspective yields a more complete insight than single outcome-single predictor models.

METHODS

We used data from the Netherlands Study of Depression and Anxiety (N = 2498) and leveraged networks capturing associations between 30 depressive symptoms (Inventory of Depressive Symptomatology) and 46 metabolites. Analyses involved 4 steps: creating a network with Mixed Graphical Models; calculating centrality measures; bootstrapping for stability testing; validating central, stable associations by extra covariate-adjustment; and validation using another data wave collected 6 years later.

RESULTS

The network yielded 28 symptom-metabolite associations. There were 15 highly-central variables (8 symptoms, 7 metabolites), and 3 stable links involving the symptoms Low energy (fatigue), and Hypersomnia. Specifically, fatigue showed consistent associations with higher mean diameter for VLDL particles and lower estimated degree of (fatty acid) unsaturation. These remained present after adjustment for lifestyle and health-related factors and using another data wave.

CONCLUSIONS

The somatic symptoms Fatigue and Hypersomnia and cholesterol and fatty acid measures showed central, stable, and consistent relationships in our network. The present analyses showed how metabolic alterations are more consistently linked to specific symptom profiles.

Pentadecanoic Acid (C15:0), an Essential Fatty Acid, Shares Clinically Relevant Cell-Based Activities with Leading Longevity-Enhancing Compounds

Pentadecanoic acid (C15:0) is an essential odd-chain saturated fatty acid with broad activities relevant to protecting cardiometabolic, immune, and liver health. C15:0 activates AMPK and inhibits mTOR, both of which are core components of the human longevity pathway. To assess the potential for C15:0 to enhance processes associated with longevity and healthspan, we used human cell-based molecular phenotyping assays to compare C15:0 with three longevity-enhancing candidates: acarbose, metformin, and rapamycin. C15:0 (n = 36 activities in 10 of 12 cell systems) and rapamycin (n = 32 activities in 12 of 12 systems) had the most clinically relevant, dose-dependent activities. At their optimal doses, C15:0 (17 µM) and rapamycin (9 µM) shared 24 activities across 10 cell systems, including anti-inflammatory (e.g., lowered MCP-1, TNFα, IL-10, IL-17A/F), antifibrotic, and anticancer activities, which are further supported by previously published in vitro and in vivo studies. Paired with prior demonstrated abilities for C15:0 to target longevity pathways, hallmarks of aging, aging rate biomarkers, and core components of type 2 diabetes, heart disease, cancer, and nonalcoholic fatty liver disease, our results support C15:0 as an essential nutrient with activities equivalent to, or surpassing, leading longevity-enhancing candidate compounds.

Individuals with depression exhibiting a pro-inflammatory phenotype receiving omega-3 polyunsaturated fatty acids experience improved motivation-related cognitive function: Preliminary results from a randomized controlled trial

Cognitive impairment related to major depressive disorder (MDD) is highly prevalent, debilitating and is lacking in effective treatments; dysregulated inflammatory physiology is a putative mechanism and may represent a therapeutic target. In depressed individuals exhibiting a pro-inflammatory phenotype who were enrolled in a 12-week randomized placebo-controlled trial of 3 doses of omega-3 polyunsaturated fatty acids (ω-3-FA), we examined: (i) the relationship between dysregulated inflammatory physiology and baseline cognitive impairment; (ii) improvement in cognitive impairment following treatment; and (iii) the association between baseline inflammatory biomarkers and change in cognitive impairment for those receiving treatment. We randomized 61 unmedicated adults aged 45.50 years (75% female) with DSM-5 MDD, body mass index >25 kg/m², and C-reactive protein (CRP) ≥3.0 mg/L to three doses of ω-3-FA (1, 2, or 4 g daily) or matching placebo. Analyses focused on 45 study completers who had inflammatory biomarkers assessed [circulating CRP, interleukin-6 (IL-6) and tumor necrosis factor-α (TNFα) as well as lipopolysaccharide (LPS)-stimulated concentrations of IL-6 and TNFα in peripheral blood mononuclear cells (PBMC)] and on the highest dose ω-3-FA (4 g daily; n = 11) compared to placebo (n = 10). Impairment in motivational symptoms (e.g., alertness, energy, enthusiasm) and higher-order cognitive functions (e.g., word-finding, memory) were assessed by a validated self-report measure. Among all 45 participants at baseline, lower concentrations of IL-6 in LPS-stimulated PBMC were associated with greater impairment in higher-order cognitive functions (r = -0.35, p = .02). Based on hierarchical linear modeling, individuals receiving 4 g/day of ω-3-FA reported significant improvement in motivational symptoms compared to placebo (B = -0.07, p = .03); in the 4 g/day group, lower baseline concentrations of TNFα in LPS-stimulated PBMC were associated with significant improvement in motivational symptoms (Ρ = .71, p = .02) following treatment. In this exploratory clinical trial, daily supplementation with 4 g of ω-3-FA improves motivational symptoms in depressed individuals exhibiting an inflammatory phenotype.

Treatment-resistant depression: definition, prevalence, detection, management, and investigational interventions

Treatment-resistant depression (TRD) is common and associated with multiple serious public health implications. A consensus definition of TRD with demonstrated predictive utility in terms of clinical decision-making and health outcomes does not currently exist. Instead, a plethora of definitions have been proposed, which vary significantly in their conceptual framework. The absence of a consensus definition hampers precise estimates of the prevalence of TRD, and also belies efforts to identify risk factors, prevention opportunities, and effective interventions. In addition, it results in heterogeneity in clinical practice decision-making, adversely affecting quality of care. The US Food and Drug Administration (FDA) and the European Medicines Agency (EMA) have adopted the most used definition of TRD (i.e., inadequate response to a minimum of two antidepressants despite adequacy of the treatment trial and adherence to treatment). It is currently estimated that at least 30% of persons with depression meet this definition. A significant percentage of persons with TRD are actually pseudo-resistant (e.g., due to inadequacy of treatment trials or non-adherence to treatment). Although multiple sociodemographic, clinical, treatment and contextual factors are known to negatively moderate response in persons with depression, very few factors are regarded as predictive of non-response across multiple modalities of treatment. Intravenous ketamine and intranasal esketamine (co-administered with an antidepressant) are established as efficacious in the management of TRD. Some second-generation antipsychotics (e.g., aripiprazole, brexpiprazole, cariprazine, quetiapine XR) are proven effective as adjunctive treatments to antidepressants in partial responders, but only the olanzapine-fluoxetine combination has been studied in FDA-defined TRD. Repetitive transcranial magnetic stimulation (TMS) is established as effective and FDA-approved for individuals with TRD, with accelerated theta-burst TMS also recently showing efficacy. Electroconvulsive therapy is regarded as an effective acute and maintenance intervention in TRD, with preliminary evidence suggesting non-inferiority to acute intravenous ketamine. Evidence for extending antidepressant trial, medication switching and combining antidepressants is mixed. Manual-based psychotherapies are not established as efficacious on their own in TRD, but offer significant symptomatic relief when added to conventional antidepressants. Digital therapeutics are under study and represent a potential future clinical vista in this population.

Chronic inflammation, neuroglial dysfunction, and plasmalogen deficiency as a new pathobiological hypothesis addressing the overlap between post-COVID-19 symptoms and myalgic encephalomyelitis/chronic fatigue syndrome

After five waves of coronavirus disease 2019 (COVID-19) outbreaks, it has been recognized that a significant portion of the affected individuals developed long-term debilitating symptoms marked by chronic fatigue, cognitive difficulties ("brain fog"), post-exertional malaise, and autonomic dysfunction. The onset, progression, and clinical presentation of this condition, generically named post-COVID-19 syndrome, overlap significantly with another enigmatic condition, referred to as myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Several pathobiological mechanisms have been proposed for ME/CFS, including redox imbalance, systemic and central nervous system inflammation, and mitochondrial dysfunction. Chronic inflammation and glial pathological reactivity are common hallmarks of several neurodegenerative and neuropsychiatric disorders and have been consistently associated with reduced central and peripheral levels of plasmalogens, one of the major phospholipid components of cell membranes with several homeostatic functions. Of great interest, recent evidence revealed a significant reduction of plasmalogen contents, biosynthesis, and metabolism in ME/CFS and acute COVID-19, with a strong association to symptom severity and other relevant clinical outcomes. These bioactive lipids have increasingly attracted attention due to their reduced levels representing a common pathophysiological manifestation between several disorders associated with aging and chronic inflammation. However, alterations in plasmalogen levels or their lipidic metabolism have not yet been examined in individuals suffering from post-COVID-19 symptoms. Here, we proposed a pathobiological model for post-COVID-19 and ME/CFS based on their common inflammation and dysfunctional glial reactivity, and highlighted the emerging implications of plasmalogen deficiency in the underlying mechanisms. Along with the promising outcomes of plasmalogen replacement therapy (PRT) for various neurodegenerative/neuropsychiatric disorders, we sought to propose PRT as a simple, effective, and safe strategy for the potential relief of the debilitating symptoms associated with ME/CFS and post-COVID-19 syndrome.

The changes in metabolomics profile induced by intermittent theta burst stimulation in major depressive disorder: an exploratory study

BACKGROUND

Recently, there has been an ongoing interest in the mechanism of intermittent theta burst stimulation (iTBS) in major depressive disorder. Studying the metabolite changes induced by iTBS may help to understand the mechanism.

METHODS

Eleven participants with major depressive disorder received 10 days iTBS treatment. Magnetic resonance imaging (MRI) was used to target the region of the left dorsolateral prefrontal cortex (DLPFC) in each participant. We analyzed the effects of iTBS on metabolites using high-throughput profiling and assessed its impact on depressive symptoms. These analyses were considered exploratory, and no correction for multiple comparisons was applied.

RESULTS

Among the 318 measured metabolites, a significant increase in cystine, asymmetric dimethylarginine (ADMA), 1-methylhistidine, indoleacetic acid (IAA), diethanolamine (DEA), dopa, riboflavin-5'-monophosphate (FMN), and a significant decrease in alphalinolenic acid (ALA), gamma-linolenic acid (GLA), serotonin, linoleic acid (LA) (p < 0.05) were detected in the patients after iTBS treatment. In Pearson correlation analysis, the plasma levels of LA, FMN and ADMA at baseline were significantly related to the reduction rate of the 17-item Hamilton Depression Rating Scale and the Patient Health Questionnaire-9 scores (p < 0.05).

CONCLUSIONS

Our study highlights that LA, FMN, ADMA and their relationship with oxidative stress, may be key factors in the antidepressant efficacy of iTBS.

Metabolomics signatures of depression: the role of symptom profiles

Depression shows a metabolomic signature overlapping with that of cardiometabolic conditions. Whether this signature is linked to specific depression profiles remains undetermined. Previous research suggested that metabolic alterations cluster more consistently with depressive symptoms of the atypical spectrum related to energy alterations, such as hyperphagia, weight gain, hypersomnia, fatigue and leaden paralysis. We characterized the metabolomic signature of an "atypical/energy-related" symptom (AES) profile and evaluated its specificity and consistency. Fifty-one metabolites measured using the Nightingale platform in 2876 participants from the Netherlands Study of Depression and Anxiety were analyzed. An 'AES profile' score was based on five items of the Inventory of Depressive Symptomatology (IDS) questionnaire. The AES profile was significantly associated with 31 metabolites including higher glycoprotein acetyls (β = 0.13, p = 1.35*10^-12), isoleucine (β = 0.13, p = 1.45*10^-10), very-low-density lipoproteins cholesterol (β = 0.11, p = 6.19*10^-9) and saturated fatty acid levels (β = 0.09, p = 3.68*10^-10), and lower high-density lipoproteins cholesterol (β = -0.07, p = 1.14*10^-4). The metabolites were not significantly associated with a summary score of all other IDS items not included in the AES profile. Twenty-five AES-metabolites associations were internally replicated using data from the same subjects (N = 2015) collected at 6-year follow-up. We identified a specific metabolomic signature-commonly linked to cardiometabolic disorders-associated with a depression profile characterized by atypical, energy-related symptoms. The specific clustering of a metabolomic signature with a clinical profile identifies a more homogenous subgroup of depressed patients at higher cardiometabolic risk, and may represent a valuable target for interventions aiming at reducing depression's detrimental impact on health.

Associations between individual depressive symptoms and immunometabolic characteristics in major depression

Inflammation and metabolic dysregulations are likely to underlie atypical, energy-related depressive symptoms such as appetite and sleep alterations. Indeed, increased appetite was previously identified as a core symptom of an immunometabolic subtype of depression. The aim of this study was 1) to replicate the associations between individual depressive symptoms and immunometabolic markers, 2) to extend previous findings with additional markers, and 3) to evaluate the relative contribution of these markers to depressive symptoms. We analyzed data from 266 persons with major depressive disorder (MDD) in the last 12 months from the German Health Interview and Examination Survey for Adults and its mental health module. Diagnosis of MDD and individual depressive symptoms were determined by the Composite International Diagnostic Interview. Associations were analyzed using multivariable regression models, adjusting for depression severity, sociodemographic/behavioral variables, and medication use. Increased appetite was associated with higher body mass index (BMI), waist circumference (WC), insulin, and lower high-density lipoprotein. In contrast, decreased appetite was associated with lower BMI, WC, and fewer metabolic syndrome (MetS) components. Insomnia was associated with higher BMI, WC, number of MetS components, triglycerides, insulin, and lower albumin, while hypersomnia was associated with higher insulin. Suicidal ideation was associated with higher number of MetS components, glucose, and insulin. None of the symptoms were associated with C-reactive protein after adjustment. Appetite alterations and insomnia were most important symptoms associated with metabolic markers. Longitudinal studies should investigate whether the candidate symptoms identified here are predicted by or predict the development of metabolic pathology in MDD.

Microbiome and immuno-metabolic dysregulation in patients with major depressive disorder with atypical clinical presentation

Depression is highly prevalent (6% 1-year prevalence) and is the second leading cause of disability worldwide. Available treatment options for depression are far from optimal, with response rates only around 50%. This is most likely related to a heterogeneous clinical presentation of major depression disorder (MDD), suggesting different manifestations of underlying pathophysiological mechanisms. Poorer treatment outcomes to first-line antidepressants were reported in MDD patients endorsing an "atypical" symptom profile that is characterized by preserved reactivity in mood, increased appetite, hypersomnia, a heavy sensation in the limbs, and interpersonal rejection sensitivity. In recent years, evidence has emerged that immunometabolic biological dysregulation is an important underlying pathophysiological mechanism in depression, which maps more consistently to atypical features. In the last few years human microbial residents have emerged as a key influencing variable associated with immunometabolic dysregulations in depression. The microbiome plays a critical role in the training and development of key components of the host's innate and adaptive immune systems, while the immune system orchestrates the maintenance of key features of the host-microbe symbiosis. Moreover, by being a metabolically active ecosystem commensal microbes may have a huge impact on signaling pathways, involved in underlying mechanisms leading to atypical depressive symptoms. In this review, we discuss the interplay between the microbiome and immunometabolic imbalance in the context of atypical depressive symptoms. Although research in this field is in its infancy, targeting biological determinants in more homogeneous clinical presentations of MDD may offer new avenues for the development of novel therapeutic strategies for treatment-resistant depression.

Banxia Xiexin decoction alleviates AS co-depression disease by regulating the gut microbiome-lipid metabolic axis

ETHNOPHARMACOLOGICAL RELEVANCE

Banxia Xiexin decoction (BXD) is a classic Chinese herbal formulation consisting of 7 herbs including Pinelliae Rhizoma, Scutellariae Radix, Zingiberis Rhizoma, Ginseng Radix, Glycyrrhizae Radix, Coptidis Rhizoma, and Jujubae Fructus, which can exert effects on lowering lipids and alleviating depressive mood disorders via affecting gastrointestinal tract.

AIM OF THE STUDY

The pathogenesis of atherosclerosis (AS) co-depression disease has not been well studied, and the current clinical treatment strategies are not satisfactory. As a result, it is critical to find novel methods of treatment. Based on the hypothesis that the gut microbiome may promote the development of AS co-depression disease by regulating host lipid metabolism, this study sought to evaluate the effectiveness and action mechanism of BXD in regulation of the gut microbiome via an intervention in AS co-depression mice.

MATERIALS AND METHODS

To determine the primary constituents of BXD, UPLC-Q/TOF-MS analysis was carried out. Sixteen C56BL/6 mice were fed normal chow as a control group; 64 ApoE^-/- mice were randomized into four groups (model group and three treatment groups) and fed high-fat chow combined with daily bind stimulation for sixteen weeks to develop the AS co-depression mouse model and were administered saline or low, medium or high concentrations of BXD during the experimental modeling period. The antidepressant efficacy of BXD was examined by weighing, a sucrose preference test, an open field test, and a tail suspension experiment. The effectiveness of BXD as an anti-AS treatment was evaluated by means of biochemical indices, the HE staining method, and the Oil red O staining method. The impacts of BXD on the gut microbiome structure and brain (hippocampus and prefrontal cortex tissue) lipids in mice with the AS co-depression model were examined by 16S rDNA sequencing combined with lipidomics analysis.

RESULTS

The main components of BXD include baicalin, berberine, ginsenoside Rb1, and 18 other substances. BXD could improve depression-like behavioral characteristics and AS-related indices in AS co-depression mice; BXD could regulate the abundance of some flora (phylum level: reduced abundance of Proteobacteria and Deferribacteres; genus level: reduced abundance of Clostridium_IV, Helicobacter, and Pseudoflavonifractor, Acetatifactor, Oscillibacter, which were significantly different). The lipidomics analysis showed that the differential lipids between the model and gavaged high-dose BXD (BXH) groups were enriched in glycerophospholipid metabolism, and lysophosphatidylcholine (LPC(20:3)(rep)(rep)) in the hippocampus and LPC(20:4)(rep) in the prefrontal cortex both showed downregulation in BXH. The correlation analysis illustrated that the screened differential lipids were mainly linked to Deferribacteres and Actinobacteria.

CONCLUSION

BXD may exert an anti-AS co-depression therapeutic effect by modulating the abundance of some flora and thus intervening in peripheral lipid and brain lipid metabolism (via downregulation of LPC levels).

Serum metabolomic profiling revealed potential diagnostic biomarkers in patients with panic disorder

BACKGROUND

Currently, specific metabolites and diagnostic biomarkers of panic disorder (PD) patients have not been identified in clinical practice. The aim of this study was to explore metabolites and metabolic pathways in serum through a metabolomics method.

METHODS

Fifty-five PD patients who completed 2 weeks of inpatient treatment and 55 healthy control subjects (HCs) matched for age, sex and BMI were recruited. Ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) was used to detect metabolites in serum. Multivariate Statistical Analysis was used to identify differential metabolites. The relevant biometabolic pathways were further identified by the online tool MetaboAnalyst 5.0.

RESULTS

43 different metabolites in PD patients compared to HCs (P < 0.05) were screened. Pathway analysis showed that these small molecules were mainly associated with amino acid metabolism. 14 metabolites were significantly changed after 2 weeks of drug treatment (P < 0.05), which were mainly associated with tryptophan metabolism.

CONCLUSION

In conclusion, our analysis of metabolomics of PD patients at baseline and two weeks after treatment screened for differential metabolites that could be potential diagnostic biomarkers involved in PD pathogenesis and influence some biometabolic pathways such as phenylalanine metabolism and tryptophan metabolism. In the future, we can summarize and observe the dynamic changes of differential metabolites that appear more frequently in similar studies to further explore the underlying mechanisms of PD evolution.

Role of the Intestinal Microbiota in the Genesis of Major Depression and the Response to Antidepressant Drug Therapy: A Narrative Review

A major depressive disorder is a serious mental illness characterized by a pervasive low mood that negatively concerns personal life, work life, or education, affecting millions of people worldwide. To date, due to the complexity of the disease, the most common and effective treatments consist of a multi-therapy approach, including psychological, social, and pharmacological support with antidepressant drugs. In general, antidepressants are effective in correcting chemical imbalances of neurotransmitters in the brain, but recent evidence has underlined the pivotal role of gut microbiota (GM) also in the regulation of their pharmacokinetics/pharmacodynamics, through indirect or direct mechanisms. The study of these complex interactions between GM and drugs is currently under the spotlight, and it has been recently named "pharmacomicrobiomics". Hence, the purpose of this review is to summarize the contribution of GM and its metabolites in depression, as well as their role in the metabolism and activity of antidepressant drugs, in order to pave the way for the personalized administration of antidepressant therapies.

Associations of white blood cell and platelet counts with specific depressive symptom dimensions in patients with bipolar disorder: Analysis of data from the FACE-BD cohort

Evidences suggest that inflammation is increased in a subgroup of patients with depression. Moreover, increased peripheral inflammatory markers (cells and proteins) are associated with some, but not all depressive symptoms. On the other hand, similar studies on bipolar disorders mainly focused on blood cytokines. Here, we analysed data from a large (N = 3440), well-characterized cohort of individuals with bipolar disorder using Kendall partial rank correlation, multivariate linear regression, and network analyses to determine whether peripheral blood cell counts are associated with depression severity, its symptoms, and dimensions. Based on the self-reported 16-Item Quick Inventory of Depressive Symptomatology questionnaire scores, we preselected symptom dimensions based on literature and data-driven principal component analysis. We found that the counts of all blood cell types were only marginally associated with depression severity. Conversely, white blood cell count was significantly associated with the sickness dimension and its four components (anhedonia, slowing down, fatigue, and appetite loss). Platelet count was associated with the insomnia/restlessness dimension and its components (initial, middle, late insomnia and restlessness). Principal component analyses corroborated these results. Platelet count was also associated with suicidal ideation. In analyses stratified by sex, the white blood cell count-sickness dimension association remained significant only in men, and the platelet count-insomnia/restlessness dimension association only in women. Without implying causation, these results suggest that peripheral blood cell counts might be associated with different depressive symptoms in individuals with bipolar disorder, and that white blood cells might be implicated in sickness symptoms and platelets in insomnia/agitation and suicidal ideation.

The association between adiposity and atypical energy-related symptoms of depression: A role for metabolic dysregulations

BACKGROUND

Adiposity has been shown to be linked with atypical energy-related symptoms (AES) of depression. We used genomics to separate the effect of adiposity from that of metabolic dysregulations to examine whether the link between obesity and AES is dependent on the presence of metabolic dysregulations.

METHOD

Data were from NEO (n = 5734 individuals) and NESDA (n = 2238 individuals) cohorts, in which the Inventory of Depressive Symptomatology (IDS-SR30) was assessed. AES profile was based on four symptoms: increased appetite, increased weight, low energy level, and leaden paralysis. We estimated associations between AES and two genetic risk scores (GRS) indexing increasing total body fat with (metabolically unhealthy adiposity, GRS-MUA) and without (metabolically healthy adiposity, GRS-MHA) metabolic dysregulations.

RESULTS

We validated that both GRS-MUA and GRS-MHA were associated with higher total body fat in NEO study, but divergently associated with biomarkers of metabolic health (e.g., fasting glucose and HDL-cholesterol) in both cohorts. In the pooled results, per standard deviation, GRS-MUA was specifically associated with a higher AES score (β = 0.03, 95%CI: 0.01; 0.05), while there was no association between GRS-MHA and AES (β = -0.01, 95%CI: -0.03; 0.01).

CONCLUSION

These results suggest that the established link between adiposity and AES profile emerges in the presence of metabolic dysregulations, which may represent the connecting substrate between the two conditions.

Dietary Strawberries Improve Serum Metabolites of Cardiometabolic Risks in Adults with Features of the Metabolic Syndrome in a Randomized Controlled Crossover Trial

Dietary strawberries have been shown to improve cardiometabolic risks in multiple clinical trials. However, no studies have reported effects on serum metabolomic profiles that may identify the target pathways affected by strawberries as underlying mechanisms. We conducted a 14-week randomized, controlled crossover study in which participants with features of metabolic syndrome were assigned to one of the three arms for four weeks separated by a one-week washout period: control powder, 1 serving (low dose: 13 g strawberry powder/day), or 2.5 servings (high dose: 32 g strawberry powder/day). Blood samples, anthropometric measures, blood pressure, and dietary and physical activity data were collected at baseline and at the end of each four-week phase of intervention. Serum samples were analyzed for primary metabolites and complex lipids using different mass spectrometry methods. Mixed-model ANOVA was used to examine differences in the targeted metabolites between treatment phases, and LASSO logistic regression was used to examine differences in the untargeted metabolites at end of the strawberry intervention vs. the baseline. The findings revealed significant differences in the serum branched-chain amino acids valine and leucine following strawberry intervention (high dose) compared with the low-dose and control phases. Untargeted metabolomic profiles revealed several metabolites, including serum phosphate, benzoic acid, and hydroxyphenyl propionic acid, that represented improved energy-metabolism pathways, compliance measures, and microbial metabolism of strawberry polyphenols, respectively. Thus, dietary supplementation of strawberries significantly improves the serum metabolic profiles of cardiometabolic risks in adults.

A role of gut-microbiota-brain axis via subdiaphragmatic vagus nerve in depression-like phenotypes in Chrna7 knock-out mice

The α7 subtype of the nicotinic acetylcholine receptor (α7 nAChR: coded by Chrna7) is known to regulate the cholinergic ascending anti-inflammatory pathway. We previously reported that Chrna7 knock-out (KO) mice show depression-like behaviors through abnormal composition of gut microbiota and systemic inflammation. Given the role of subdiaphragmatic vagus nerve in gut-microbiota-brain axis, we investigated whether subdiaphragmatic vagotomy (SDV) could affect depression-like behaviors, abnormal composition of gut microbiota, and microbes-derived metabolites in Chrna7 KO mice. SDV blocked depression-like behaviors and reduced expression of synaptic proteins in the medial prefrontal cortex (mPFC) of Chrna7 KO mice. LEfSe (linear discriminant analysis effect size) analysis revealed that the species Lactobacillus sp. BL302, the species Lactobacillus hominis, and the species Lactobacillus reuteri, were identified as potential microbial markers in the KO + SDV group. There were several genus and species altered among the three groups [wild-type (WT) + sham group, KO + sham group, KO + SDV group]. Furthermore, there were several plasma metabolites altered among the three groups. Moreover, there were correlations between relative abundance of several microbiome and behavioral data (or synaptic proteins). Network analysis showed correlations between relative abundance of several microbiome and plasma metabolites (or behavioral data). These data suggest that Chrna7 KO mice produce depression-like behaviors and reduced expression of synaptic proteins in the mPFC through gut-microbiota-brain axis via subdiaphragmatic vagus nerve.

Network science approach elucidates integrative genomic-metabolomic signature of antidepressant response and lifetime history of attempted suicide in adults with major depressive disorder

Background: Individuals with major depressive disorder (MDD) and a lifetime history of attempted suicide demonstrate lower antidepressant response rates than those without a prior suicide attempt. Identifying biomarkers of antidepressant response and lifetime history of attempted suicide may help augment pharmacotherapy selection and improve the objectivity of suicide risk assessments. Towards this goal, this study sought to use network science approaches to establish a multi-omics (genomic and metabolomic) signature of antidepressant response and lifetime history of attempted suicide in adults with MDD. Methods: Single nucleotide variants (SNVs) which associated with suicide attempt(s) in the literature were identified and then integrated with a) p180-assayed metabolites collected prior to antidepressant pharmacotherapy and b) a binary measure of antidepressant response at 8 weeks of treatment using penalized regression-based networks in 245 'Pharmacogenomics Research Network Antidepressant Medication Study (PGRN-AMPS)' and 103 'Combining Medications to Enhance Depression Outcomes (CO-MED)' patients with major depressive disorder. This approach enabled characterization and comparison of biological profiles and associated antidepressant treatment outcomes of those with (N = 46) and without (N = 302) a self-reported lifetime history of suicide attempt. Results: 351 SNVs were associated with suicide attempt(s) in the literature. Intronic SNVs in the circadian genes CLOCK and ARNTL (encoding the CLOCK:BMAL1 heterodimer) were amongst the top network analysis features to differentiate patients with and without a prior suicide attempt. CLOCK and ARNTL differed in their correlations with plasma phosphatidylcholines, kynurenine, amino acids, and carnitines between groups. CLOCK and ARNTL-associated phosphatidylcholines showed a positive correlation with antidepressant response in individuals without a prior suicide attempt which was not observed in the group with a prior suicide attempt. Conclusion: Results provide evidence for a disturbance between CLOCK:BMAL1 circadian processes and circulating phosphatidylcholines, kynurenine, amino acids, and carnitines in individuals with MDD who have attempted suicide. This disturbance may provide mechanistic insights for differential antidepressant pharmacotherapy outcomes between patients with MDD with versus without a lifetime history of attempted suicide. Future investigations of CLOCK:BMAL1 metabolic regulation in the context of suicide attempts may help move towards biologically-augmented pharmacotherapy selection and stratification of suicide risk for subgroups of patients with MDD and a lifetime history of attempted suicide.

Plasmalogen in the brain: Effects on cognitive functions and behaviors attributable to its properties

Ether phospholipid compositions are altered in the plasma or brain of patients with brain disorders, such as Alzheimer and Parkinson's disease, including those with psychiatric disorders like schizophrenia and bipolar disorders. Notably, plasmenyl ethanolamine has a unique chemical structure, i.e., a vinyl-ether bond at the sn-1 position, which mainly links with polyunsaturated fatty acids (PUFAs) at the sn-2 position. Those characteristic moieties give plasmalogen molecules unique biophysical and chemical properties that modulate membrane trafficking, lipid rafts, intramolecular PUFA moieties, and oxidative states. Previous reports suggested that a deficiency in plasmenyl ethanolamine leads to disturbances of the myelin structure, synaptic neurotransmission and intracellular signaling, apoptosis of neurons, and neuroinflammation, accompanied by cognitive disturbances and aberrant behaviors like hyperactivity in mice. Therefore, this review summarizes the relationship between the biological functions of plasmalogen. We also proposed biophysical properties that alter brain phospholipid compositions related to aberrant behaviors and cognitive dysfunction. Finally, a brief review of possible remedial plasmalogen replacement therapies for neurological, psychiatric, and developmental disorders attributable to disturbed plasmalogen compositions in the organs and cells was conducted.