Branched-Chain Amino Acids as New Biomarkers of Major Depression - A Novel Neurobiology of Mood Disorder

A Plasma Metabolite Score Related to Psychological Distress and Diabetes Risk: A Nested Case-control Study in US Women

CONTEXT

Psychological distress has been linked to diabetes risk. Few population-based, epidemiologic studies have investigated the potential molecular mechanisms (eg, metabolic dysregulation) underlying this association.

OBJECTIVE

To evaluate the association between a metabolomic signature for psychological distress and diabetes risk.

METHODS

We conducted a nested case-control study of plasma metabolomics and diabetes risk in the Nurses' Health Study, including 728 women (mean age: 55.2 years) with incident diabetes and 728 matched controls. Blood samples were collected between 1989 and 1990 and incident diabetes was diagnosed between 1992 and 2008. Based on our prior work, we calculated a weighted plasma metabolite-based distress score (MDS) comprised of 19 metabolites. We used conditional logistic regression accounting for matching factors and other diabetes risk factors to estimate odds ratios (OR) and 95% confidence intervals (CI) for diabetes risk according to MDS.

RESULTS

After adjusting for sociodemographic factors, family history of diabetes, and health behaviors, the OR (95% CI) for diabetes risk across quintiles of the MDS was 1.00 (reference) for Q1, 1.16 (0.77, 1.73) for Q2, 1.30 (0.88, 1.91) for Q3, 1.99 (1.36, 2.92) for Q4, and 2.47 (1.66, 3.67) for Q5. Each SD increase in MDS was associated with 36% higher diabetes risk (95% CI: 1.21, 1.54; P-trend <.0001). This association was moderately attenuated after additional adjustment for body mass index (comparable OR: 1.17; 95% CI: 1.02, 1.35; P-trend = .02). The MDS explained 17.6% of the association between self-reported psychological distress (defined as presence of depression or anxiety symptoms) and diabetes risk (P = .04).

CONCLUSION

MDS was significantly associated with diabetes risk in women. These results suggest that differences in multiple lipid and amino acid metabolites may underlie the observed association between psychological distress and diabetes risk.

Maternal serum amino acids and hydroxylated sphingomyelins at pregnancy are associated with anxiety symptoms during pregnancy and throughout the first year after delivery

BACKGROUND

Studies suggest an interplay between maternal metabolome and mental health.

OBJECTIVE

We investigated the association of maternal serum metabolome at pregnancy with anxiety scores during pregnancy and throughout the first year postpartum.

METHODS

A prospective cohort of Brazilian women collected 119 serum metabolome at pregnancy (28-38 weeks) and anxiety scores measured by the State-Trait Anxiety Inventory (STAI) at pregnancy (n = 118), 1 (n = 83), 6 (n = 68), and 12 (n = 57) months postpartum. Targeted metabolomics quantified metabolites belonging to amino acids (AA), biogenic amines/amino acid-related compounds, acylcarnitines, lysophosphatidylcholines, diacyl phosphatidylcholines, alkyl:acyl phosphatidylcholines, non-hydroxylated and hydroxylated sphingomyelins [SM(OH)], and hexoses classes. Linear mixed-effect models were used to evaluate the association of metabolites and STAI scores. Hierarchical clustering and principal component analyses were employed to identify clusters and metabolites, which drove their main differences. Multiple comparison-adjusted p-values (q-value) ≤ 0.05 were considered significant.

RESULTS

AA (β = -1.44) and SM(OH) (β = -1.49) classes showed an association with STAI scores trajectory (q-value = 0.047). Two clusters were identified based on these classes. Women in cluster 2 had decreased AA and SM(OH) concentrations and higher STAI scores (worse symptoms) trajectory (β = 2.28; p-value = 0.041). Isoleucine, leucine, valine, SM(OH) 22:1, 22:2, and 24:1 drove the main differences between the clusters.

LIMITATIONS

The target semiquantitative metabolome analysis and small sample size limited our conclusions.

CONCLUSIONS

Our results suggest that AA and SM(OH) during pregnancy play a role in anxiety symptoms throughout the first year postpartum.

Metabolomics Signatures of serotonin reuptake inhibitor (Escitalopram), serotonin norepinephrine reuptake inhibitor (Duloxetine) and Cognitive Behavior Therapy on Key Neurotransmitter Pathways in Major Depressive Disorder

Metabolomics provides powerful tools that can inform about heterogeneity in disease and response to treatments. In this study, we employed an electrochemistry-based targeted metabolomics platform to assess the metabolic effects of three randomly-assigned treatments: escitalopram, duloxetine, and Cognitive Behavior Therapy (CBT) in 163 treatment-naïve outpatients with major depressive disorder. Serum samples from baseline and 12 weeks post-treatment were analyzed using targeted liquid chromatography-electrochemistry for metabolites related to tryptophan, tyrosine metabolism and related pathways. Changes in metabolite concentrations related to each treatment arm were identified and compared to define metabolic signatures of exposure. In addition, association between metabolites and depressive symptom severity (assessed with the 17-item Hamilton Rating Scale for Depression [HRSD17]) and anxiety symptom severity (assessed with the 14-item Hamilton Rating Scale for Anxiety [HRSA14]) were evaluated, both at baseline and after 12 weeks of treatment. Significant reductions in serum serotonin level and increases in tryptophan-derived indoles that are gut bacterially derived were observed with escitalopram and duloxetine arms but not in CBT arm. These include indole-3-propionic acid (I3PA), indole-3-lactic acid (I3LA) and Indoxyl sulfate (IS), a uremic toxin. Purine-related metabolites were decreased across all arms. Different metabolites correlated with improved symptoms in the different treatment arms revealing potentially different mechanisms between response to antidepressant medications and to CBT.

Using an Interpretable Amino Acid-Based Machine Learning Method to Enhance the Diagnosis of Major Depressive Disorder

Background: Major depressive disorder (MDD) is a leading cause of disability worldwide. At present, however, there are no established biomarkers that have been validated for diagnosing and treating MDD. This study sought to assess the diagnostic and predictive potential of the differences in serum amino acid concentration levels between MDD patients and healthy controls (HCs), integrating them into interpretable machine learning models. Methods: In total, 70 MDD patients and 70 HCs matched in age, gender, and ethnicity were recruited for the study. Serum amino acid profiling was conducted by means of chromatography-mass spectrometry. A total of 21 metabolites were analysed, with 17 from a preset amino acid panel and the remaining 4 from a preset kynurenine panel. Logistic regression was applied to differentiate MDD patients from HCs. Results: The best-performing model utilised both feature selection and hyperparameter optimisation and yielded a moderate area under the receiver operating curve (AUC) classification value of 0.76 on the testing data. The top five metabolites identified as potential biomarkers for MDD were 3-hydroxy-kynurenine, valine, kynurenine, glutamic acid, and xanthurenic acid. Conclusions: Our study highlights the potential of using an interpretable machine learning analysis model based on amino acids to aid and increase the diagnostic accuracy of MDD in clinical practice.

Metabolite Biomarkers of Prolonged and Intensified Pain and Distress in Head and Neck Cancer Patients Undergoing Radio- or Chemoradiotherapy by Means of NMR-Based Metabolomics-A Preliminary Study

Treatment of head and neck squamous cell carcinoma (HNSCC) has a detrimental impact on patient quality of life. The rate of recognized distress/depression among HNSCC patients ranges from 9.8% to 83.8%, and the estimated prevalence of depression among patients receiving radiotherapy is 63%. Shorter overall survival also occurs in preexisting depression or depressive conditions. The present study analyzes the nuclear magnetic resonance (NMR) blood serum metabolic profiles during radio-/chemoradiotherapy and correlates the detected alterations with pain and/or distress accumulated with the disease and its treatment. NMR spectra were acquired on a Bruker 400 MHz spectrometer and analyzed using multivariate methods. The results indicate that distress and/or pain primarily affect the serum lipids and metabolites of energy (glutamine, glucose, lactate, acetate) and one-carbon (glycine, choline, betaine, methanol, threonine, serine, histidine, formate) metabolism. Sparse disturbances in the branched-chain amino acids (BCAA) and in the metabolites involved in protein metabolism (lysine, tyrosine, phenylalanine) are also observed. Depending on the treatment modality-radiotherapy or concurrent chemoradiotherapy-there are some differences in the altered metabolites.

Plasma amino acids in major depressive disorder: between pathology to pharmacology

Addressing the formidable challenge posed by the development of effective and personalized interventions for major depressive disorder (MDD) necessitates a comprehensive comprehension of the intricate role that plasma amino acids play and their implications in MDD pathology and pharmacology. Amino acids, owing to their indispensable functions in neurotransmission, metabolism, and immune regulation, emerge as pivotal entities in this intricate disorder. Our primary objective entails unraveling the underlying mechanisms and unveiling tailored treatments through a meticulous investigation into the interplay between plasma amino acids, MDD, and pharmacological strategies. By conducting a thorough and exhaustive review of the existing literature, we have identified pertinent studies on plasma amino acids in MDD, thereby uncovering noteworthy disturbances in the profiles of amino acids among individuals afflicted by MDD when compared to their healthy counterparts. Specifically, disruptions in the metabolism of tryptophan, phenylalanine, and tyrosine, which serve as precursors to essential neurotransmitters, have emerged as prospective biomarkers and critical contributors to the pathophysiology of depression. Amnio acids play an essential role in MDD and could represent an attractive pharmacological target, more studies are further required to fully reveal their underlying mechanisms.

Plasma metabolomics reveals the intervention mechanism of different types of exercise on chronic unpredictable mild stress-induced depression rat model

OBJECTIVE

To study the effects of different types of exercise on the plasma metabolomics of chronic unpredictable mild stress (CUMS)-induced depressed rats based on 1H-NMR metabolomics techniques, and to explore the potential mechanisms of exercise for the treatment of depression. Rats were randomly divided into blank control group (C), CUMS control group (D), pre-exercise with CUMS group (P), CUMS with aerobic exercise group, CUMS with resistance exercise group (R), and CUMS with aerobic + resistance exercise group (E). The corresponding protocol intervention was applied to each group of rats. Body weight, sucrose preference and open field tests were performed weekly during the experiment to evaluate the extent of depression in rats. Plasma samples from each group of rats were collected at the end of the experiment, and then the plasma was analyzed by 1H-NMR metabolomics combined with multivariate statistical analysis methods to identify differential metabolites and perform metabolic pathway analysis. (1) Compared with the group D, the body weight, sucrose preference rate, and the number of crossings and standings in the different types of exercise groups were significantly improved (p < 0.05 or p < 0.01). (2) Compared to group C, a total of 15 differential metabolites associated with depression were screened in the plasma of rats in group D, involving 6 metabolic pathways. Group P can regulate the levels of 6 metabolites: valine, lactate, inositol, glucose, phosphocreatine, acetoacetic acid. Group A can regulate the levels of 6 metabolites: N-acetylglycoprotein, leucine, lactate, low density lipoprotein, glucose and acetoacetic acid. Group R can regulate the levels of 6 metabolites: choline, lactate, inositol, glucose, phosphocreatine and acetoacetic acid. Group E can regulate the levels of 5 metabolites: choline, citric acid, glucose, acetone and acetoacetic acid. The different types of exercise groups can improve the depressive symptoms in CUMS rats, and there are common metabolites and metabolic pathways for their mechanism of effects. This study provides a powerful analytical tool to study the mechanism of the antidepressant effect of exercise, and provides an important method and basis for the early diagnosis, prevention and treatment of depression.

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.

Metabolomic disorders: confirmed presence of potentially treatable abnormalities in patients with treatment refractory depression and suicidal behavior

BACKGROUND

Refractory depression is a devastating condition with significant morbidity, mortality, and societal cost. Approximately 15% of patients with major depressive disorder are refractory to currently available treatments. We hypothesized metabolic abnormalities contributing to treatment refractory depression are associated with distinct findings identifiable in the cerebrospinal fluid (CSF). Our hypothesis was confirmed by a previous small case-controlled study. Here we present a second, larger replication study.

METHODS

We conducted a case-controlled, targeted, metabolomic evaluation of 141 adolescent and adult patients with well-characterized history of depression refractory to three maximum-dose, adequate-duration medication treatments, and 36 healthy controls. Plasma, urine, and CSF metabolic profiling were performed by coupled gas chromatography/mass spectrometry, and high-performance liquid chromatography, electrospray ionization, tandem mass spectrometry.

RESULTS

Abnormalities were identified in 67 of 141 treatment refractory depression participants. The CSF abnormalities included: low cerebral folate (n = 20), low tetrahydrobiopterin intermediates (n = 11), and borderline low-tetrahydrobiopterin intermediates (n = 20). Serum abnormalities included abnormal acylcarnitine profile (n = 12) and abnormal serum amino acids (n = 20). Eighteen patients presented with two or more abnormal metabolic findings. Sixteen patients with cerebral folate deficiency and seven with low tetrahydrobiopterin intermediates in CSF showed improvement in depression symptom inventories after treatment with folinic acid and sapropterin, respectively. No healthy controls had a metabolite abnormality.

CONCLUSIONS

Examination of metabolic disorders in treatment refractory depression identified an unexpectedly large proportion of patients with potentially treatable abnormalities. The etiology of these abnormalities and their potential roles in pathogenesis remain to be determined.

The role of gut microbiota in the pathogenesis and treatment of postpartum depression

Postpartum depression (PPD) is a common complication of pregnancy in women, and its pathogenesis mainly involves disturbances of the neuroendocrine regulation, immune system, neurotransmitters, hormone secretion, and the gut microbiome. Gut microbes play essential physiological and pathological roles in the gut-brain axis' pathways which are involved in various central nervous system (CNS) and psychiatric disorders, including PPD. Numerous studies have identified the fundamental role of the gut-brain axis in the pathogenesis and treatment of PPD patients and also correlates with other pathogenic mechanisms of PPD. Disturbances in gut microbes are associated with the disruption of multiple signaling pathways and systems that ultimately lead to PPD development. This review aimed to elucidate the potential connections between gut microbes and the established PPD network, and this might serve as a guide for the development of new efficient diagnostic, therapeutic, and prognostic strategies in the management of PPD.

Dynamic Interplay between Social Brain Development and Nutrient Intake in Young Children

Myelination of the brain structures underlying social behavior in humans is a dynamic process that parallels the emergence of social-emotional development and social skills in early life. Of the many genetic and environmental factors regulating the myelination processes, nutrition is considered as a critical and modifiable early-life factor for establishing healthy social brain networks. However, the impact of nutrition on the longitudinal development of social brain myelination remains to be fully understood. This study examined the interplay between childhood nutrient intake and social brain development across the first 5 years of life. Myelin-sensitive neuroimaging and food-intake data were analyzed in 293 children, 0.5 to 5 years of age, and explored for dynamic patterns of nutrient-social brain myelin associations. We found three data-driven age windows with specific nutrient correlation patterns, 63 individual nutrient-myelin correlations, and six nutrient combinations with a statistically significant predictive value for social brain myelination. These results provide novel insights into the impact of specific nutrient intakes on early brain development, in particular social brain regions, and suggest a critical age-sensitive opportunity to impact these brain regions for potential longer-term improvements in socio-emotional development and related executive-function and critical-thinking skills.

Effects of Fructose and Palmitic Acid on Gene Expression in Drosophila melanogaster Larvae: Implications for Neurodegenerative Diseases

One of the largest health problems worldwide is the development of chronic noncommunicable diseases due to the consumption of hypercaloric diets. Among the most common alterations are cardiovascular diseases, and a high correlation between overnutrition and neurodegenerative diseases has also been found. The urgency in the study of specific damage to tissues such as the brain and intestine led us to use Drosophila melanogaster to study the metabolic effects caused by the consumption of fructose and palmitic acid in specific tissues. Thus, third instar larvae (96 ± 4 h) of the wild Canton-S strain of D. melanogaster were used to perform transcriptomic profiling in brain and midgut tissues to test for the potential metabolic effects of a diet supplemented with fructose and palmitic acid. Our data infer that this diet can alter the biosynthesis of proteins at the mRNA level that participate in the synthesis of amino acids, as well as fundamental enzymes for the dopaminergic and GABAergic systems in the midgut and brain. These also demonstrated alterations in the tissues of flies that may help explain the development of various reported human diseases associated with the consumption of fructose and palmitic acid in humans. These studies will not only help to better understand the mechanisms by which the consumption of these alimentary products is related to the development of neuronal diseases but may also contribute to the prevention of these conditions.

Maternal and Child Health, Non-Communicable Diseases and Metabolites

Mothers influence the health and disease trajectories of their children, particularly during the critical developmental windows of fetal and neonatal life reflecting the gestational-fetal and lactational-neonatal phases. As children grow and develop, they are exposed to various stimuli and insults, such as metabolites, that shape their physiology and metabolism to impact their health. Non-communicable diseases, such as diabetes, cardiovascular disease, cancer and mental illness, have high global prevalence and are increasing in incidence. Non-communicable diseases often overlap with maternal and child health. The maternal milieu shapes progeny outcomes, and some diseases, such as gestational diabetes and preeclampsia, have gestational origins. Metabolite aberrations occur from diets and physiological changes. Differential metabolite profiles can predict the onset of non-communicable diseases and therefore inform prevention and/or better treatment. In mothers and children, understanding the metabolite influence on health and disease can provide insights for maintaining maternal physiology and sustaining optimal progeny health over the life course. The role and interplay of metabolites on physiological systems and signaling pathways in shaping health and disease present opportunities for biomarker discovery and identifying novel therapeutic agents, particularly in the context of maternal and child health, and non-communicable diseases.

The alteration of gut microbiota in venlafaxine-ameliorated chronic unpredictable mild stress-induced depression in mice

Depression is associated with intestinal dysbiosis. Venlafaxine is a commonly used antidepressant in clinical practice as a serotonin and noradrenaline reuptake inhibitor. However, its effects on gut bacteria in depression remain unclear. Here, we established a mouse model of depression induced by chronic unpredictable mild stress (CUMS), and investigated the alterations of venlafaxine on the gut microbiota and potential key bacteria. Our data show that venlafaxine exerts antidepressant effects by restoring the serotonin (5-HT) system and glutamate (Glu) levels in CUMS mice. Moreover, we revealed that venlafaxine altered the diversity of gut bacteria in CUMS mice, and at genus level, Blautia, Oscillibacter, Tyzzerella, Butyricicoccus, and Enterorhabdus are the key bacteria responsible for venlafaxine-ameliorated depression in mice. Among these potential key bacteria, Blautia, Oscillibacter, and Butyricicoccus are correlated significantly with the 5-HT and 5-hydroxyindoleacetic acid levels; while Tyzzerella is correlated markedly with Glu levels. We further show that venlafaxine affected multiple functional metabolic pathways of gut bacteria in mice with CUMS-induced depression. Our results suggest that venlafaxine possibly ameliorates depression via modulating gut bacteria, and found the potential targets of its antidepressant effects.

The Role of the Gut Microbiome in Bipolar Disorder and its Common Comorbidities

Bipolar disorder is a decidedly heterogeneous and multifactorial disease, with significant psychosocial and medical disease burden. Much difficulty has been encountered in developing novel therapeutics and objective biomarkers for clinical use in this population. In that regard, gut-microbial homeostasis appears to modulate several key pathways relevant to a variety of psychiatric, metabolic, and inflammatory disorders. Microbial impact on immune, endocrine, endocannabinoid, kynurenine, and other pathways are discussed throughout this review. Emphasis is placed on this system's relevance to current pharmacology, diet, and comorbid illness in bipolar disorder. Despite the high level of optimism promoted in many reviews on this topic, substantial obstacles exist before any microbiome-related findings can provide meaningful clinical utility. Beyond a comprehensive overview of pathophysiology, this review hopes to highlight several key areas where progress is needed. As well, novel microbiome-associated suggestions are presented for future research.

Association between Possible Sarcopenia and Depressive Symptoms in Korean Older Adults: Results from the Korea National Health and Nutrition Examination Survey in 2018

BACKGROUND

Despite increased clinical and research interest in sarcopenia, even in Asia, not much is known about the association between sarcopenia and depressive symptoms. Sarcopenia and depressive symptoms are associated with several health problems in older adults; therefore, we investigated the association between sarcopenia and depression in Korean older adults.

METHODS

The study sample included 1,929 participants aged over 60 years (44.6% men; mean age, 69.7 years) from nationally representative data of the 2018 Korea National Health and Nutrition Examination survey. Possible sarcopenia was defined according to the diagnostic algorithm of the Asian Working Group for Sarcopenia 2019; however, we measured only hand-grip strength (kg) in this study. Patient Health Questionnaire-9 was used for screening for symptoms of depression. A cross-sectional analysis was used to examine the relationship between possible sarcopenia and depressive symptoms.

RESULTS

Possible sarcopenia and depressive symptoms were identified in 538 (27.9%) and 97 (5.0%) participants, respectively. After adjusting for age, sex, and other potential covariates, possible sarcopenia was positively associated with higher odds of depressive symptoms (odds ratio, 2.06; 95% confidence interval, 1.36-3.11; P<0.001).

CONCLUSION

Possible sarcopenia was significantly associated with depressive symptoms in Korean older adults. Early interventions for possible sarcopenia and depressive symptoms in routine clinical practice could help Korean older adults to have healthy aging. Future studies are required to explore any causal relationship between possible sarcopenia and depressive symptoms in Korean older adults.

Metabolic and Transcriptomic Signatures of the Acute Psychological Stress Response in the Mouse Brain

Acute stress response triggers various physiological responses such as energy mobilization to meet metabolic demands. However, the underlying molecular changes in the brain remain largely obscure. Here, we used a brief water avoidance stress (WAS) to elicit an acute stress response in mice. By employing RNA-sequencing and metabolomics profiling, we investigated the acute stress-induced molecular changes in the mouse whole brain. The aberrant expression of 60 genes was detected in the brain tissues of WAS-exposed mice. Functional analyses showed that the aberrantly expressed genes were enriched in various processes such as superoxide metabolism. In our global metabolomic profiling, a total of 43 brain metabolites were significantly altered by acute WAS. Metabolic pathways upregulated from WAS-exposed brain tissues relative to control samples included lipolysis, eicosanoid biosynthesis, and endocannabinoid synthesis. Acute WAS also elevated the levels of branched-chain amino acids, 5-aminovalerates, 4-hydroxy-nonenal-glutathione as well as mannose, suggesting complex metabolic changes in the brain. The observed molecular events in the present study provide a valuable resource that can help us better understand how acute psychological stress impacts neural functions.

Metabolic and Transcriptomic Changes in the Mouse Brain in Response to Short-Term High-Fat Metabolic Stress

The chronic consumption of diets rich in saturated fats leads to obesity and associated metabolic disorders including diabetes and atherosclerosis. Intake of a high-fat diet (HFD) is also recognized to dysregulate neural functions such as cognition, mood, and behavior. However, the effects of short-term high-fat diets on the brain are elusive. Here, we investigated molecular changes in the mouse brain following an acute HFD for 10 days by employing RNA sequencing and metabolomics profiling. Aberrant expressions of 92 genes were detected in the brain tissues of acute HFD-exposed mice. The differentially expressed genes were enriched for various pathways and processes such as superoxide metabolism. In our global metabolomic profiling, a total of 59 metabolites were significantly altered by the acute HFD. Metabolic pathways upregulated from HFD-exposed brain tissues relative to control samples included oxidative stress, oxidized polyunsaturated fatty acids, amino acid metabolism (e.g., branched-chain amino acid catabolism, and lysine metabolism), and the gut microbiome. Acute HFD also elevated levels of N-acetylated amino acids, urea cycle metabolites, and uracil metabolites, further suggesting complex changes in nitrogen metabolism. The observed molecular events in the present study provide a valuable resource that can help us better understand how acute HFD stress impacts brain homeostasis.

Decreased β-hydroxybutyrate and ketogenic amino acid levels in depressed human adults

β-hydroxybutyrate (BHB) is a major ketone body synthesized mainly in the liver mitochondria and is associated with stress and severity of depression in humans. It is known to alleviate depressive-like behaviors in mouse models of depression. In this study, plasma BHB, ketogenic and glucogenic amino acids selected from the Tohoku Medical Megabank Project Community-Based Cohort Study were analysed and measured using nuclear magnetic resonance spectroscopy. The Center for Epidemiologic Studies Depression Scale (CES-D) was utilized to select adult participants with depressive symptoms (CES-D ≥ 16; n = 5722) and control participants (CES-D < 16; n = 18,150). We observed significantly reduced plasma BHB, leucine, and tryptophan levels in participants with depressive symptoms. Using social defeat stress (SDS) mice models, we found that BHB levels in mice sera increased after acute SDS, but showed no change after chronic SDS, which differed from human plasma results. Furthermore, acute SDS increased mitochondrial BHB levels in the prefrontal cortex at 6 h. In contrast, chronic SDS significantly increased the amount of food intake but reduced hepatic mitochondrial BHB levels in mice. Moreover, gene transcriptions of voltage-dependent anion-selective channel 1 (Vdac1) and monocarboxylic acid transporter 1 (Mct1), major molecules relevant to mitochondrial biogenesis and BHB transporter, significantly decreased in the liver and PFC after chronic SDS exposure. These results provide evidence that hepatic and prefrontal mitochondrial biogenesis plays an important role in BHB synthesis under chronic stress and in humans with depressive symptoms.

Gut microbiota: A new target for traditional Chinese medicine in the treatment of depression

ETHNIC PHARMACOLOGICAL RELEVANCE

The causes of depression are complex. Many factors are involved in its pathogenesis, including the individual's biological and social environment. Although numerous studies have reported that the gut microbiota plays a significant role in depression, drugs that regulate the gut microbiota to treat depression have not yet been comprehensively reviewed. At the same time, more and more attention has been paid to the characteristics of traditional Chinese medicine (TCM) in improving depression by regulating gut microbiota. In ancient times, fecal microbiota transplantation was recorded in TCM for the treatment of severe diseases. There are also records in Chinese ancient books about the use of TCM to adjust gut microbiota to treat diseases, which has opened up a unique research field in TCM. Therefore, this article focuses on the pharmacological effects, targets, and mechanisms of TCM in improving depression by mediating the influence of gut microbiota.

AIM OF THIS REVIEW

To summarize the role the gut microbiota plays in depression, highlight potential regulatory targets, and elucidate the anti-depression mechanisms of TCMs through regulation of the gut microbiota.

METHODS

A systematic review of 256 clinical trials and pharmaceutical studies published until June 2022 was conducted in eight electronic databases (Web of Science, PubMed, SciFinder, Research Gate, ScienceDirect, Google Scholar, Scopus, and China Knowledge Infrastructure), according to the implemented PRISMA criteria, using the search terms "traditional Chinese medicine," "depression," and "gut microbiota."

RESULTS

Numerous studies reported the effects of different gut bacteria on depression and that antidepressants work through the gut microbiota. TCM preparations based on compound Chinese medicine, the Chinese Materia Medica, and major bioactive components exerted antidepressant-like effects by improving levels of neurotransmitters, short-chain fatty acids, brain-derived neurotrophic factor, kynurenine, and cytokines via regulation of the gut microbiota.

CONCLUSION

This review summarized the anti-depression effects of TCM on the gut microbiota, providing evidence that TCMs are safe and effective in the treatment of depression and may provide a new therapeutic approach.

Metabolomic Footprint of Disrupted Energetics and Amino Acid Metabolism in Neurodegenerative Diseases: Perspectives for Early Diagnosis and Monitoring of Therapy

The prevalence of neurodegenerative diseases (NDs) is increasing due to the aging population and improved longevity. They are characterized by a range of pathological hallmarks, including protein aggregation, mitochondrial dysfunction, and oxidative stress. The aim of this review is to summarize the alterations in brain energy and amino acid metabolism in Alzheimer’s disease (AD), Parkinson’s disease (PD), and Huntington’s disease (HD). Based on our findings, we proposed a group of selected metabolites related to disturbed energy or mitochondrial metabolism as potential indicators or predictors of disease. We also discussed the hidden challenges of metabolomics studies in NDs and proposed future directions in this field. We concluded that biochemical parameters of brain energy metabolism disruption (obtained with metabolomics) may have potential application as a diagnostic tool for the diagnosis, prediction, and monitoring of the effectiveness of therapies for NDs. However, more studies are needed to determine the sensitivity of the proposed candidates. We suggested that the most valuable biomarkers for NDs studies could be groups of metabolites combined with other neuroimaging or molecular techniques. To attain clinically applicable results, the integration of metabolomics with other “omic” techniques might be required.

Centella asiatica (L.) Urb. Extract ameliorates branched-chain amino acid (BCAA) metabolism in acute reserpine-induced stress zebrafish model via 1H Nuclear Magnetic Resonance (NMR)-based metabolomics approach

Depression is a common mental disorder that can adversely affect psychosocial function and quality of life. However, the exact aetiology and pathogenesis of depression are still unclear. Stress plays a major role in the pathogenesis of depression. The use of currently prescribed antidepressants has many side effects. Centella asiatica (C. asiatica) has shown promising antidepressant activity in rodent models. Here, we developed a reserpine-induced zebrafish stress-like model and performed behavioural analysis, cortisol measurement and ¹H-Nuclear Magnetic Resonance (¹H NMR) spectroscopy-based metabolomics analysis to test the anti-stress activity of ethanolic extract of C. asiatica (RECA). A significant increase in total distance travelled (F_(8,8) = 8.905, p = 0.0054) and a reduction in freezing duration (F_{(9, 9)} = 10.38, p = 0.0018) were found in the open field test (OFT). Asiaticoside, one of tested C.asiatica's triterpenoid gives a significant increase in contact duration (F_(5,5) = 142.3, (p = 0.0330) at 2.5 mg/kg). Eight biomarkers were found, i.e. ß-hydroxyisovaleric acid, leucine, threonine, scylloinositol, lactate, betaine, valine, choline and l-fucose, to be responsible for the class separation between stress and RECA-treated groups. Metabolic pathway alteration in zebrafish brain upon treatment with RECA was identified as valine, leucine and isoleucine biosynthesis, while alanine, aspartate, glutamate and glycerophospholipid metabolism was involved after fluoxetine treatment.

The Utility of Amino Acid Metabolites in the Diagnosis of Major Depressive Disorder and Correlations with Depression Severity

Major depressive disorder (MDD) is a highly prevalent and disabling condition with a high disease burden. There are currently no validated biomarkers for the diagnosis and treatment of MDD. This study assessed serum amino acid metabolite changes between MDD patients and healthy controls (HCs) and their association with disease severity and diagnostic utility. In total, 70 MDD patients and 70 HCs matched in age, gender, and ethnicity were recruited for the study. For amino acid profiling, serum samples were analysed and quantified by liquid chromatography-mass spectrometry (LC-MS). Receiver-operating characteristic (ROC) curves were used to classify putative candidate biomarkers. MDD patients had significantly higher serum levels of glutamic acid, aspartic acid and glycine but lower levels of 3-Hydroxykynurenine; glutamic acid and phenylalanine levels also correlated with depression severity. Combining these four metabolites allowed for accurate discrimination of MDD patients and HCs, with 65.7% of depressed patients and 62.9% of HCs correctly classified. Glutamic acid, aspartic acid, glycine and 3-Hydroxykynurenine may serve as potential diagnostic biomarkers, whereas glutamic acid and phenylalanine may be markers for depression severity. To elucidate the association between these indicators and clinical features, it is necessary to conduct additional studies with larger sample sizes that involve a spectrum of depressive symptomatology.

Circulating metabolites and depression: a bidirectional Mendelian randomization

Background

Studies have shown an association between depression and circulating metabolites, but the causal relationship between them has not been elucidated. The purpose of this study was to elucidate the causal relationship between circulating metabolites and depression and to explore the role of circulating metabolites in depression.

Methods

In this study, the top single-nucleotide polymorphisms (SNPs) associated with circulating metabolites (n = 24,925) and depression (n = 322,580) were obtained based on the publicly available genome-wide association study using two-sample Mendelian randomization (MR). SNP estimates were summarized through inverse variance weighted, MR Egger, weighted median, MR pleiotropy residual sum and outlier, and "leave-one-out" methods.

Results

Apolipoprotein A-I (OR 0.990, 95% CI 981-0.999) and glutamine (OR 0.985, 95% CI 0.972-0.997) had protective causal effects on depression, whereas acetoacetate (OR 1.021, 95% CI 1.009-1.034), glycoproteins (OR 1.005, 95% CI 1.000-1.009), isoleucine (OR 1.013, 95% CI 1.002-1.024), and urea (OR 1.020, 95% CI 1.000-1.039) had an anti-protective effect on depression. Reversed MR showed no effect of depression on the seven circulating metabolites.

Conclusion

In this study, MR analysis showed that apolipoprotein A-I and glutamine had a protective effect on depression, and acetoacetate, glycoprotein, isoleucine, glucose, and urea may be risk factors for depression. Therefore, further research must be conducted to translate the findings into practice.

Branched-chain amino acids linked to depression in young adults

Depression is a heterogeneous mental health problem affecting millions worldwide, but a majority of individuals with depression do not experience relief from initial treatments. Therefore, we need to improve our understanding of the biology of depression. Metabolomic approaches, especially untargeted ones, can suggest new hypotheses for further exploring biological mechanisms. Using the FinnTwin12 cohort, a longitudinal Finnish population-based twin cohort, with data collected in adolescence and young adulthood including 725 blood plasma samples, we investigated associations between depression and 11 low–molecular weight metabolites (amino acids and ketone bodies). In linear regression models with the metabolite (measured at age 22) as the dependent variable and depression ratings (measured at age 12, 14, 17, or 22 from multiple raters) as independent variables [adjusted first for age, sex, body mass index (BMI), and additional covariates (later)], we initially identified a significant negative association of valine with depression. Upon further analyses, valine remained significantly negatively associated with depression cross-sectionally and over time [meta-analysis beta = −13.86, 95% CI (−18.48 to −9.25)]. Analyses of the other branched-chain amino acids showed a significant negative association of leucine with depression [meta-analysis beta = −9.24, 95% CI (−14.53 to −3.95)], while no association was observed between isoleucine and depression [meta-analysis beta = −0.95, 95% CI (−6.00 to 4.11)]. These exploratory epidemiologic findings support further investigations into the role of branched-chain amino acids in depression.

Effects of Branched-Chain Amino Acids on Skeletal Muscle, Glycemic Control, and Neuropsychological Performance in Elderly Persons with Type 2 Diabetes Mellitus: An Exploratory Randomized Controlled Trial

Although branched-chain amino acids (BCAA) are known to stimulate myofibrillar protein synthesis and affect insulin signaling and kynurenine metabolism (the latter being a metabolite of tryptophan associated with depression and dementia), the effects of BCAA supplementation on type 2 diabetes (T2D) are not clear. Therefore, a 24-week, prospective randomized open blinded-endpoint trial was conducted to evaluate the effects of supplementation of 8 g of BCAA or 7.5 g of soy protein on skeletal muscle and glycemic control as well as adverse events in elderly individuals with T2D. Thirty-six participants were randomly assigned to the BCAA group (n = 21) and the soy protein group (n = 15). Skeletal muscle mass and HbA1c, which were primary endpoints, did not change over time or differ between groups. However, knee extension muscle strength was significantly increased in the soy protein group and showed a tendency to increase in the BCAA group. Homeostasis model assessment for insulin resistance did not significantly change during the trial. Depressive symptoms were significantly improved in the BCAA group but the difference between groups was not significant. Results suggested that BCAA supplementation may not affect skeletal muscle mass and glycemic control and may improve depressive symptoms in elderly individuals with T2D.

Molecular mediators of the association between child obesity and mental health

Biological mechanisms underlying the association between obesity and depression remain unclear. We investigated the role of metabolites and DNA methylation as mediators of the relationship between childhood obesity and subsequent poor mental health in the English Avon Longitudinal Study of Parents and Children. Obesity was defined according to United Kingdom Growth charts at age 7 years and mental health through the Short Mood and Feelings Questionnaire (SMFQ) completed at age 11 years. Metabolites and DNA methylation were measured by nuclear magnetic resonance spectroscopy and Illumina array in blood at the age of 7 years. The associations between obesity and SMFQ score, as continuous count data or using cut-offs to define depressive symptoms (SMFQ >7) or depression (SMFQ >11), were tested using adjusted Poisson and logistic regression. Candidate metabolite mediators were identified through metabolome-wide association scans for obesity and SMFQ score, correcting for false-discovery rate. Candidate DNA methylation mediators were identified through testing the association of putative BMI-associated CpG sites with SMFQ scores, correcting for look-up false-discovery rate. Mediation by candidate molecular markers was tested. Two-sample Mendelian randomization (MR) analyses were additionally applied to test causal associations of metabolites with depression in independent adult samples. 4,018 and 768 children were included for metabolomics and epigenetics analyses, respectively. Obesity at 7 years was associated with a 14% increase in SMFQ score (95% CI: 1.04, 1.25) and greater odds of depression (OR: 1.46 (95% CI: 0.78, 2.38) at 11 years. Natural indirect effects (mediating pathways) between obesity and depression for tyrosine, leucine and conjugated linoleic acid were 1.06 (95% CI: 1.00, 1.13, proportion mediated (PM): 15%), 1.04 (95% CI: 0.99, 1.10, PM: 9.6%) and 1.06 (95% CI: 1.00, 1.12, PM: 13.9%) respectively. In MR analysis, one unit increase in tyrosine was associated with 0.13 higher log odds of depression (p = 0.1). Methylation at cg17128312, located in the FBXW9 gene, had a natural indirect effect of 1.05 (95% CI: 1.01,1.13, PM: 27%) as a mediator of obesity and SMFQ score. Potential biologically plausible mechanisms involving these identified molecular features include neurotransmitter regulation, inflammation, and gut microbiome modulation. These results require replication in further observational and mechanistic studies.

Unlocking the Potential of the Human Microbiome for Identifying Disease Diagnostic Biomarkers

The human microbiome encodes more than three million genes, outnumbering human genes by more than 100 times, while microbial cells in the human microbiota outnumber human cells by 10 times. Thus, the human microbiota and related microbiome constitute a vast source for identifying disease biomarkers and therapeutic drug targets. Herein, we review the evidence backing the exploitation of the human microbiome for identifying diagnostic biomarkers for human disease. We describe the importance of the human microbiome in health and disease and detail the use of the human microbiome and microbiota metabolites as potential diagnostic biomarkers for multiple diseases, including cancer, as well as inflammatory, neurological, and metabolic diseases. Thus, the human microbiota has enormous potential to pave the road for a new era in biomarker research for diagnostic and therapeutic purposes. The scientific community needs to collaborate to overcome current challenges in microbiome research concerning the lack of standardization of research methods and the lack of understanding of causal relationships between microbiota and human disease.

Associations Between Disordered Microbial Metabolites and Changes of Neurotransmitters in Depressed Mice

Backgrounds

Many pieces of evidence demonstrated that there were close relationships between gut microbiota and depression. However, the specific molecular mechanisms were still unknown. Here, using targeted metabolomics, this study was conducted to explore the relationships between microbial metabolites in feces and neurotransmitters in prefrontal cortex of depressed mice.

Methods

Chronic unpredictable mild stress (CUMS) model of depression was built in this study. Targeted liquid chromatography-mass spectrometry analysis was used to detect the microbial metabolites in feces and neurotransmitters in prefrontal cortex of mice. Both univariate and multivariate statistical analyses were applied to identify the differential microbial metabolites and neurotransmitters and explore relationships between them.

Results

Ninety-eight differential microbial metabolites (mainly belonged to amino acids, fatty acids, and bile acids) and 11 differential neurotransmitters (belonged to tryptophan pathway, GABAergic pathway, and catecholaminergic pathway) were identified. Five affected amino acid-related metabolic pathways were found in depressed mice. The 19 differential microbial metabolites and 10 differential neurotransmitters were found to be significantly correlated with depressive-like behaviors. The two differential neurotransmitters (tyrosine and glutamate) and differential microbial metabolites belonged to amino acids had greater contributions to the overall correlations between microbial metabolites and neurotransmitters. In addition, the significantly decreased L-tyrosine as microbial metabolites and tyrosine as neurotransmitter had the significantly positive correlation (r = 0.681, p = 0.0009).

Conclusions

These results indicated that CUMS-induced disturbances of microbial metabolites (especially amino acids) might affect the levels of neurotransmitters in prefrontal cortex and then caused the onset of depression. Our findings could broaden the understanding of how gut microbiota was involved in the onset of depression.

Comparative metabolomic analysis in plasma and cerebrospinal fluid of humans and in plasma and brain of mice following antidepressant-dose ketamine administration

Subanesthetic-dose racemic (R,S)-ketamine (ketamine) produces rapid, robust, and sustained antidepressant effects in major depressive disorder (MDD) and bipolar disorder (BD) and has also been shown to effectively treat neuropathic pain, complex regional pain syndrome, and post-traumatic stress disorder (PTSD). However, to date, its mechanism of action remains unclear. Preclinical studies found that (2 R,6 R;2 S,6 S)-hydroxynorketamine (HNK), a major circulating metabolite of ketamine, elicits antidepressant effects similar to those of ketamine. To help determine how (2 R,6 R)-HNK contributes to ketamine's mechanism of action, an exploratory, targeted, metabolomic analysis was carried out on plasma and CSF of nine healthy volunteers receiving a 40-minute ketamine infusion (0.5 mg/kg). A parallel targeted metabolomic analysis in plasma, hippocampus, and hypothalamus was carried out in mice receiving either 10 mg/kg of ketamine, 10 mg/kg of (2 R,6 R)-HNK, or saline. Ketamine and (2 R,6 R)-HNK both affected multiple pathways associated with inflammatory conditions. In addition, several changes were unique to either the healthy human volunteers and/or the mouse arm of the study, indicating that different pathways may be differentially involved in ketamine's effects in mice and humans. Mechanisms of action found to consistently underlie the effects of ketamine and/or (2 R,6 R)-HNK across both the human metabolome in plasma and CSF and the mouse arm of the study included LAT1, IDO1, NAD+, the nitric oxide (NO) signaling pathway, and sphingolipid rheostat.

Serum metabolomic responses to aerobic exercise in rats under chronic unpredictable mild stress

This study analyzed the effects of aerobic exercise on endogenous serum metabolites in response to chronic unpredictable mild stress (CUMS) using a rat model, aiming to identify the metabolic regulatory pathways involved in the antidepressant effect resulted from a 28-day treadmill aerobic exercise intervention. The animals were randomly divided into four groups (n = 8): normal control, normal with aerobic exercise, CUMS control, and CUMS with aerobic exercise. Body weight, sucrose preference and open field tests were performed weekly during the intervention period for changes in depressant symptoms. Serum metabolic profiles obtained by using the LC-MS/MS metabolomics were analyzed to explore the regulatory mechanism for the effect of the aerobic exercise on depression. Behavior tests showed that the aerobic exercise resulted in a significant improvement in depression-like behavior in the CUMS rats. A total of 21 differential metabolites were identified as being associated with depression in serum metabolic profile, of which the aerobic exercise significantly modulated 15, mainly related to amino acid metabolism and energy metabolism. Collectively, this is the first study that LC-MS/MS techniques were used to reveal the modulatory effects of aerobic exercise on the serum metabolic profile of depressed rats and the findings further enriched our understanding of potential mechanisms of aerobic exercise interventions on depression.

Breathomics profiling of metabolic pathways affected by major depression: Possibilities and limitations

BACKGROUND

Major depressive disorder (MDD) is one of the most common psychiatric disorders with multifactorial etiologies. Metabolomics has recently emerged as a particularly potential quantitative tool that provides a multi-parametric signature specific to several mechanisms underlying the heterogeneous pathophysiology of MDD. The main purpose of the present study was to investigate possibilities and limitations of breath-based metabolomics, breathomics patterns to discriminate MDD patients from healthy controls (HCs) and identify the altered metabolic pathways in MDD.

METHODS

Breath samples were collected in Tedlar bags at awakening, 30 and 60 min after awakening from 26 patients with MDD and 25 HCs. The non-targeted breathomics analysis was carried out by proton transfer reaction mass spectrometry. The univariate analysis was first performed by T-test to rank potential biomarkers. The metabolomic pathway analysis and hierarchical clustering analysis (HCA) were performed to group the significant metabolites involved in the same metabolic pathways or networks. Moreover, a support vector machine (SVM) predictive model was built to identify the potential metabolites in the altered pathways and clusters. The accuracy of the SVM model was evaluated by receiver operating characteristics (ROC) analysis.

RESULTS

A total of 23 differential exhaled breath metabolites were significantly altered in patients with MDD compared with HCs and mapped in five significant metabolic pathways including aminoacyl-tRNA biosynthesis (p = 0.0055), branched chain amino acids valine, leucine and isoleucine biosynthesis (p = 0.0060), glycolysis and gluconeogenesis (p = 0.0067), nicotinate and nicotinamide metabolism (p = 0.0213) and pyruvate metabolism (p = 0.0440). Moreover, the SVM predictive model showed that butylamine (p = 0.0005, p_FDR=0.0006), 3-methylpyridine (p = 0.0002, p_FDR = 0.0012), endogenous aliphatic ethanol isotope (p = 0.0073, p_FDR = 0.0174), valeric acid (p = 0.005, p_FDR = 0.0162) and isoprene (p = 0.038, p_FDR = 0.045) were potential metabolites within identified clusters with HCA and altered pathways, and discriminated between patients with MDD and non-depressed ones with high sensitivity (0.88), specificity (0.96) and area under curve of ROC (0.96).

CONCLUSION

According to the results of this study, the non-targeted breathomics analysis with high-throughput sensitive analytical technologies coupled to advanced computational tools approaches offer completely new insights into peripheral biochemical changes in MDD.

Disturbances in branched-chain amino acid profile and poor daily functioning in mildly depressed chronic obstructive pulmonary disease patients

BACKGROUND

Depression is one of the most common and untreated comorbidities in chronic obstructive pulmonary disease (COPD), and is associated with poor health outcomes (e.g. increased hospitalization/exacerbation rates). Although metabolic disturbances have been suggested in depressed non-diseased conditions, comprehensive metabolic phenotyping has never been conducted in those with COPD. We examined whether depressed COPD patients have certain clinical/functional features and exhibit a specific amino acid phenotype which may guide the development of targeted (nutritional) therapies.

METHODS

Seventy-eight outpatients with moderate to severe COPD (GOLD II-IV) were stratified based on presence of depression using a validated questionnaire. Lung function, disease history, habitual physical activity and protein intake, body composition, cognitive and physical performance, and quality of life were measured. Comprehensive metabolic flux analysis was conducted by pulse stable amino acid isotope administration. We obtained blood samples to measure postabsorptive kinetics (production and clearance rates) and plasma concentrations of amino acids by LC-MS/MS. Data are expressed as mean [95% CI]. Stats were done by graphpad Prism 9.1.0. ɑ < 0.05.

RESULTS

The COPD depressed (CD, n = 27) patients on average had mild depression, were obese (BMI: 31.7 [28.4, 34.9] kg/m2), and were characterized by shorter 6-min walk distance (P = 0.055), physical inactivity (P = 0.03), and poor quality of life (P = 0.01) compared to the non-depressed COPD (CN, n = 51) group. Lung function, disease history, body composition, cognitive performance, and daily protein intake were not different between the groups. In the CD group, plasma branched chain amino acid concentration (BCAA) was lower (P = 0.02), whereas leucine (P = 0.01) and phenylalanine (P = 0.003) clearance rates were higher. Reduced values were found for tyrosine plasma concentration (P = 0.005) even after adjustment for the large neutral amino acid concentration (= sum BCAA, tyrosine, phenylalanine and tryptophan) as a marker of dopamine synthesis (P = 0.048).

CONCLUSION

Mild depression in COPD is associated with poor daily performance and quality of life, and a set of metabolic changes in depressed COPD that include perturbation of large neutral amino acids, specifically the BCAAs. Trial registration clinicaltrials.gov: NCT01787682, 11 February 2013-Retrospectively registered; NCT02770092, 12 May 2016-Retrospectively registered; NCT02780219, 23 May 2016-Retrospectively registered; NCT03796455, 8 January 2019-Retrospectively registered.

Deficiency in the Essential Amino Acids l-Isoleucine, l-Leucine and l-Histidine and Clinical Measures as Predictors of Moderate Depression in Elderly Women: A Discriminant Analysis Study

Increases in depression are common in some elderly women. Elderly women often show moderate depressive symptoms, while others display minimal depressive symptoms. These discrepancies have produced contradictory and inconclusive outcomes, which have not been explained entirely by deficits in neurotransmitter precursors. Deficiency in some amino acids have been implicated in major depression, but its role in non-clinical elderly women is not well known. An analysis of essential amino acids, depression and the use of discriminant analysis can help to clarify the variation in depressive symptoms exhibited by some elderly women. The aim was to investigate the relationship of essential amino acids with affective, cognitive and comorbidity measures in elderly women without major depression nor severe mood disorders or psychosis, specifically thirty-six with moderate depressive symptoms and seventy-one with minimal depressive symptoms. The plasma concentrations of nineteen amino acids, Beck Depression Inventory (BDI) scores, Geriatric Depression Scale (GDS) scores, global cognitive scores and comorbidities were submitted to stepwise discriminant analysis to identify predictor variables. Seven predictors arose as important for belong to the group based on amino acid concentrations, with the moderate depressive symptoms group characterized by higher BDI, GDS and cognitive scores; fewer comorbidities; and lower levels of l-histidine, l-isoleucine and l-leucine. These findings suggest that elderly women classified as having moderate depressive symptoms displayed a deficiency in essential amino acids involved in metabolism, protein synthesis, inflammation and neurotransmission.

IBD metabonomics predicts phenotype, disease course, and treatment response

Metabonomics in inflammatory bowel disease (IBD) characterizes the effector molecules of biological systems and thus aims to describe the molecular phenotype, generate insight into the pathology, and predict disease course and response to treatment. Nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry (MS), and integrated NMR and MS platforms coupled with multivariate analyses have been applied to create such metabolic profiles. Recent advances have identified quiescent ulcerative colitis as a distinct molecular phenotype and demonstrated metabonomics as a promising clinical tool for predicting relapse and response to treatment with biologics as well as fecal microbiome transplantation, thus facilitating much needed precision medicine. However, understanding this complex research field and how it translates into clinical settings is a challenge. This review aims to describe the current workflow, analytical strategies, and associated bioinformatics, and translate current IBD metabonomic knowledge into new potential clinically applicable treatment strategies, and outline future key translational perspectives.

Study on antidepressant mechanism of Radix Bupleuri-Radix Paeoniae Alba herb pair by metabonomics combined with 1H nuclear magnetic resonance and ultra-high-performance liquid chromatography-tandem mass spectrometry detection technology

OBJECTIVES

Radix Bupleuri-Radix Paeoniae Alba (BP), a traditional Chinese medicine herb pair, has treated depression by coordinating the liver in Chinese classical medicine books and modern research. This study aims to verify the antidepressant effect of BP by behavioural examination, and reveal the underlying antidepressant mechanisms of BP.

METHODS

The antidepressant effects in chronic unpredictable mild stress (CUMS) of BP were observed by behavioural indicators and 1H nuclear magnetic resonance (1H-NMR) and ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) metabonomics techniques combined with the related analysis platforms.

KEY FINDINGS

BP could significantly improve the depressive behaviour of CUMS rats. Compared with the model group, body weight (P < 0.05), the number of crossing (P < 0.001) and rearing (P < 0.01) and sucrose preference rate (P < 0.01) were significantly enhanced, and the immobility time was shortened in the forced swimming test (P < 0.001) of the BP group. In metabonomics study, 35 depression-related metabolites were identified by 1H NMR and UHPLC-MS/MS metabonomics by comparing model and control groups. BP could significantly retrieve 17 depression-related metabolites. Thirteen depression-related metabolic pathways were found through Met-PA and BP could regulate seven metabolic pathways.

CONCLUSIONS

BP herb pair had significantly antidepressant effect, which provides a basis for further finding drug targets.

Baicalein Delays H2O2-Induced Astrocytic Senescence through Inhibition of Senescence-Associated Secretory Phenotype (SASP), Suppression of JAK2/STAT1/NF-κB Pathway, and Regulation of Leucine Metabolism

Baicalein is an active ingredient extracted from the dried roots of the Scutellaria baicalensis Georgi. It has been demonstrated to improve memory impairment in multiple animal models; however, the underlying mechanisms remain ambiguous. The accumulation of senescent astrocytes and senescence-associated secretory phenotype (SASP) secreted by senescent astrocytes has been deemed as potential contributors to neurodegenerative diseases. Therefore, this study explored the protective effects of baicalein against astrocyte senescence and investigated the molecular mechanisms and metabolic mechanisms of baicalein against astrocyte senescence. Our results demonstrated that treatment with baicalein protects T98G cells from H₂O₂-induced damage, delays cell senescence, inhibits the secretion of SASP (IL-6, IL-8, TNF-α, CXCL1, and MMP-1), and inhibits SASP-related pathways NF-κB and JAK2/STAT1. ¹H NMR metabolomics analysis and correlation analysis revealed that leucine was significantly correlated with SASP factors. Further study demonstrated that supplement with leucine could restrain SASP secretion, and baicalein could significantly increase leucine level through down-regulation of BCAT1 and up-regulation of SLC7A5 expression. The above results revealed that baicalein exerted protective and antisenescence effects in H₂O₂-induced T98G cells possibly through inhibition of SASP, suppression of JAK2/STAT1/NF-κB pathway, and regulation of leucine metabolism. Consistent results were obtained in primary astrocytes of newborn SD rats, which suggests that baicalein significantly increases viabilities, delays senescence, inhibits IL-6 secretion, and increases leucine level in H₂O₂-induced primary astrocytes.

Energy metabolism in major depressive disorder: Recent advances from omics technologies and imaging

Major depressive disorder (MDD) is a serious psychiatric disorder that associated with high rate of disability and increasing suicide rate, and the pathogenesis is still unclear. Many researches showed that the energy metabolism of patients with depression is impaired, which may be the direction of depression treatment. In this review, we focus on the "omics" technologies such as genomics, proteomics, transcriptomics and metabolomics, as well as imaging, and the progress on energy metabolism of MDD. These findings indicate that abnormal energy metabolism is one of the important mechanisms for the occurrence and development of depression. Although the research on various mechanisms of depression is still ongoing, the rapid development of new technologies and the joint use of various technologies will help to clarify the pathogenesis of depression and explore efficient diagnosis and treatment methods.

Alterations in acylcarnitines, amines, and lipids inform about the mechanism of action of citalopram/escitalopram in major depression

Selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for major depressive disorder (MDD), yet their mechanisms of action are not fully understood and their therapeutic benefit varies among individuals. We used a targeted metabolomics approach utilizing a panel of 180 metabolites to gain insights into mechanisms of action and response to citalopram/escitalopram. Plasma samples from 136 participants with MDD enrolled into the Mayo Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) were profiled at baseline and after 8 weeks of treatment. After treatment, we saw increased levels of short-chain acylcarnitines and decreased levels of medium-chain and long-chain acylcarnitines, suggesting an SSRI effect on β-oxidation and mitochondrial function. Amines-including arginine, proline, and methionine sulfoxide-were upregulated while serotonin and sarcosine were downregulated, suggesting an SSRI effect on urea cycle, one-carbon metabolism, and serotonin uptake. Eighteen lipids within the phosphatidylcholine (PC aa and ae) classes were upregulated. Changes in several lipid and amine levels correlated with changes in 17-item Hamilton Rating Scale for Depression scores (HRSD₁₇). Differences in metabolic profiles at baseline and post-treatment were noted between participants who remitted (HRSD₁₇≤ 7) and those who gained no meaningful benefits (<30% reduction in HRSD₁₇). Remitters exhibited (a) higher baseline levels of C3, C5, alpha-aminoadipic acid, sarcosine, and serotonin; and (b) higher week-8 levels of PC aa C34:1, PC aa C34:2, PC aa C36:2, and PC aa C36:4. These findings suggest that mitochondrial energetics-including acylcarnitine metabolism, transport, and its link to β-oxidation-and lipid membrane remodeling may play roles in SSRI treatment response.

Alterations in Fecal Microbiomes and Serum Metabolomes of Fatigued Patients With Quiescent Inflammatory Bowel Diseases

BACKGROUND & AIMS

Fatigue is frequent and disabling in patients with inflammatory bowel diseases (IBD) but its mechanisms are poorly understood. We investigated alterations in fecal microbiomes and serum metabolomes and proteomes in patients with quiescent IBD, with vs without fatigue.

METHODS

We performed a prospective observational study of patients (44% women; mean age, 39.8 y) with clinically and endoscopically quiescent Crohn's disease (n = 106) or ulcerative colitis (n = 60) at a tertiary hospital, from March 2016 through December 2018. Fatigue was assessed using the functional assessment of chronic illness therapy-fatigue scoring system and defined as a score of 43 or less. We performed metabolomic analysis of serum samples using liquid chromatography-mass spectrometry methods and proteomic analysis using multiplex proximity extension assay (PEA) technology. Stool samples were obtained from 50 patients and analyzed by shotgun metagenomic sequencing on Illumina HiSeq platform.

RESULTS

Of the 166 study participants, 91 (55%) were fatigued. Serum samples from patients with fatigue (n = 59) did not have significant increases in levels of inflammatory cytokines compared with serum samples from nonfatigued patients (n = 72). We found a statistically significant difference in a cluster of 18 serum metabolites between patients with fatigue (n = 84) vs without fatigue (n = 72) (P = .033); serum samples from patients with fatigue had significant reductions in levels of methionine (P = .020), tryptophan (P = .042), proline (P = .017), and sarcosine (P = .047). Fecal samples from patients with fatigue had a less diverse gut microbiome, with significant reductions in butyrate-producing bacteria, including Faecalibacterium prausnitzii (P = .0002, q =.007) and Roseburia hominis (P = .0079, q = 0.105). This fatigue-like microbiome was associated with fatigue scales and correlated with progressive depletion of metabolites from serum samples.

CONCLUSIONS

In an analysis of fecal and serum samples from 166 patients with IBD, we found alterations in serum metabolites and fecal microbes that were associated with fatigue.

3-(4-Carboxybenzoyl)quinoline-2-carboxaldehyde labeling for direct analysis of amino acids in plasma is not suitable for simultaneous quantification of tryptophan, tyrosine, valine, and isoleucine by CE/fluorescence

Capillary electrophoresis coupled to LED-induced fluorescence detection is a robust and sensitive technique used for amino acids (AA) analysis in biological media, after labeling with 3-(4-carboxybenzoyl)quinoline-2-carboxaldehyde (CBQCA). We wanted to quantitate in plasma tryptophan (Trp), tyrosine (Tyr), valine (Val), and isoleucine (Ile). Among the different labeled AA-CBQCA, Trp has the lowest fluorescence yield, which makes its detection and quantification very difficult in biological samples such as plasma. We tried to improve Trp analysis by CE/LED-induced fluorescence detection to its maximal sensitivity by using large volume sample stacking as a preconcentration step in our analytical protocol. At pH 9.5, this step caused a drop in resolution during the separation of the four AAs and it was therefore necessary to work at pH 10. We have found that Tyr, Val, Ile, and Trp are detected and well separated from the other AAs, but Trp cannot be quantified in plasma samples, mainly because of the low fluorescence yield of the Trp-CBQCA derivative. The recorded LOD is 0.18 μM for Trp-CBQCA in standard solution with a resolution between Trp and Tyr of 1.2, while the LOD is 6 μM in plasma with the same resolution. Trp, Tyr, Val, and Ile are, however, efficiently quantified when using a 3 M acetic acid electrolyte and CE associated with capacitively coupled contactless conductivity detection, which also has the advantage of not requiring derivatization or large volume sample stacking. This article demonstrates, for the CE user, that quantitative analysis of these four AA in mouse plasma can be performed by CE-fluorescence after CBQCA labeling, with the exception of Trp. It can be advantageously replaced by CE/capacitively coupled contactless conductivity detection, the only efficient one for Trp, Tyr, Val, and Ile quantification. In this case, the LOD for Trp is 2 μM. The four AAs are separated with resolution with neighbors above 1.5.

Dietary intake of branched-chain amino acids in relation to depression, anxiety and psychological distress

BACKGROUND

There is no previous study that examined the association between branched-chain amino acids (BCAAs) intake and odds of psychological disorders. The aim of this study was to investigate the association between dietary BCAAs and odds of psychological disorders including depression, anxiety, and psychological distress in a large sample of Iranian adults.

METHODS

In this cross-sectional study on 3175 Iranian adults aged 18-55 years, a validated food frequency questionnaire was used to assess dietary intakes. BCAAs intake was computed by summing up the amount of valine, leucine, and isoleucine intake from all food items in the questionnaire. Psychological health was examined through the use of Iranian validated version of the Hospital Anxiety and Depression Scale (HADS). Psychological distress was assessed using General Health Questionnaire (GHQ). For depression and anxiety, scores of 8 or more on either subscale were considered as psychological disorders and scores of 0-7 were defined as "normal". In terms of psychological distress, the score of 4 or more was defined as psychological distress.

RESULTS

Mean age of study participants was 36.2 ± 7.8 years. Overall, 26.4% (n = 837) of study subjects had depression, 11.9% (n = 378) had anxiety and 20.9% (n = 665) were affected by psychological distress. After controlling for potential confounders, participants in the highest tertile of total BCAAs intake had lower odds of depression (OR: 0.76; 95% CI: 0.60-0.96) and anxiety (OR: 0.66; 95% CI: 0.47-0.91) compared with those in the lowest tertile. Participants in the top tertile of valine intake had a lower odds of depression (OR: 0.76; 95% CI: 0.60-0.96) and anxiety (OR: 0.65; 95% CI: 0.47-0.90) compared with those in the bottom tertile. A significant inverse association was also seen between leucine intake and depression (OR: 0.77; 95% CI: 0.61-0.98) and anxiety (OR: 0.66; 95% CI: 0.47-0.91). In addition, a significant inverse association was observed between isoleucine intake and odds of depression (OR: 0.75; 95% CI: 0.59-0.95) and anxiety (OR: 0.62; 95% CI: 0.45-0.86). There was no significant association between isoleucine intake and odds of psychological distress.

CONCLUSION

Evidence indicating an inverse association between dietary intake of BCAAs and odds of depression and anxiety was found. Prospective studies are required to confirm these findings.

Photoperiodic changes in hippocampal neurogenesis and plasma metabolomic profiles in relation to depression-like behavior in mice

Photoperiod alters affective behaviors and brain neuroplasticity in several mammalian species. We addressed whether neurogenesis and signaling pathways of insulin-like growth factor-I (IGF-I), a key modulator of neuroplasticity, are regulated by photoperiod in C57BL/6 J mice, a putative model of seasonal affective disorder. We also examined the effects of photoperiod on plasma metabolomic profiles in relation to depression-like behavior to understand a possible linkage between peripheral metabolism and behavior. Mice that were maintained under long-day conditions (LD) exhibited a higher number of 5-bromo-2'-deoxyuridine-positive cells and higher levels of astrocyte marker in the dentate gyrus of the hippocampus compared to that of mice under short-day conditions (SD). Plasma IGF-I levels and levels/expression of IGF-I signaling molecules in the hippocampus (Brn-4, NeuroD1, and phospho-Akt) involved in neuronal proliferation and differentiation were higher in the mice under LD. Metabolome analysis using plasma of the mice under LD and SD identified several metabolites that were highly correlated with immobility in the forced swim test, a depression-like behavior. Negative correlations with behavior occurred in the levels of 23 metabolites, including metabolites related to neurogenesis and antidepressant-like effects of exercise, metabolites in the biosynthesis of arginine, and the occurrence of branched chain amino acids. Three metabolites had positive correlations with the behavior, including guanidinosuccinic acid, a neurotoxin. Taken together, photoperiodic responses of neurogenesis and neuro-glial organization in the hippocampus may be involved in photoperiodic alteration of depression-like behavior, mediated through multiple pathways, including IGF-I and peripheral metabolites.

Branched-chain amino acids are linked with iron metabolism

Background

The branched-chain amino acids (BCAAs) valine, leucine and isoleucine are reported to influence erythropoiesis and the human iron status. Large study cohorts encompassing biomarkers of iron metabolism and BCAAs are still lacking.

Methods

We investigated potential interactions between blood concentrations of all three BCAAs valine, leucine and isoleucine and biomarkers of iron metabolism [i.e., hemoglobin (Hb), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), iron, transferrin, ferritin, transferrin saturation, soluble transferrin receptor (sTfR)] in 430 outpatients referred for a medical health check-up. Linear regression models were performed to assess possible associations between variables.

Results

All three BCAAs were positively correlated with Hb, ferritin and the sTfR (r-values: 0.145–0.382; P values: <0.001–0.003). The strongest correlation was observed between valine and Hb (r=0.382; P value <0.001). Linear regression models showed a statistically significant influence of all three BCAAs on Hb and ferritin (β-coefficients: 0.173–0.351; all P values: <0.001). Seventeen patients with anemia (4%) were found with significantly lower serum BCAA concentrations compared to 413 non-anemic individuals (P<0.05).

Conclusions

These data indicate a pathophysiological link between the three BCAAs valine, leucine and isoleucine and the human iron indicators Hb and ferritin. Further studies are needed to clarify the exact causal mechanisms of these findings.

Gut Microbiome: A Potential Indicator for Differential Diagnosis of Major Depressive Disorder and General Anxiety Disorder

Background: Major depressive disorder (MDD) and general anxiety disorder (GAD) share many common features, leading to numerous challenges in their differential diagnosis. Given the importance of the microbiota-gut-brain axis, we investigated the differences in gut microbiota between representative cases of these two diseases and sought to develop a microbiome-based approach for their differential diagnosis. Methods: We enrolled 23 patients with MDD, 21 with GAD, and 10 healthy subjects (healthy crowd, HC) in the present study. We used 16S rRNA gene-sequencing analysis to determine the microbial compositions of the gut microbiome based on Illumina Miseq and according to the standard protocol. Results: GAD showed a significant difference in microbiota richness and diversity as compared with HC. Additionally, Otu24167, Otu19140, and Otu19751 were significantly decreased in MDD relative to HC, and Otu2581 and Otu10585 were significantly increased in GAD relative to MDD. At the genus level, the abundances of Sutterella and Fusicatenibacter were significantly lower in MDD relative to HC, and the abundances of Fusicatenibacter and Christensenellaceae_R7_group were significantly lower in GAD than in HC. The abundance of Sutterella was significantly higher whereas that of Faecalibacterium was significantly lower in GAD relative to MDD. Moreover, we observed that Christensenellaceae_R7_group negatively correlated with the factor score (Limited to Hopelessness) and total score of HAMD-24 (p < 0.05), whereas Fusicatenibacter negatively correlated with FT4 (p < 0.05). Furthermore, the GAD group showed significant differences at the genus level for Faecalibacterium, which negatively correlated with PTC (p < 0.05). Conclusions: This study elucidated a unique gut-microbiome signature associated with MDD and GAD that could facilitate differential diagnosis and targeted therapy.

Bacterial Metabolites of Human Gut Microbiota Correlating with Depression

Depression is a global threat to mental health that affects around 264 million people worldwide. Despite the considerable evolution in our understanding of the pathophysiology of depression, no reliable biomarkers that have contributed to objective diagnoses and clinical therapy currently exist. The discovery of the microbiota-gut-brain axis induced scientists to study the role of gut microbiota (GM) in the pathogenesis of depression. Over the last decade, many of studies were conducted in this field. The productions of metabolites and compounds with neuroactive and immunomodulatory properties among mechanisms such as the mediating effects of the GM on the brain, have been identified. This comprehensive review was focused on low molecular weight compounds implicated in depression as potential products of the GM. The other possible mechanisms of GM involvement in depression were presented, as well as changes in the composition of the microbiota of patients with depression. In conclusion, the therapeutic potential of functional foods and psychobiotics in relieving depression were considered. The described biomarkers associated with GM could potentially enhance the diagnostic criteria for depressive disorders in clinical practice and represent a potential future diagnostic tool based on metagenomic technologies for assessing the development of depressive disorders.

Metabolomics Profile in Depression: A Pooled Analysis of 230 Metabolic Markers in 5283 Cases With Depression and 10,145 Controls

BACKGROUND

Depression has been associated with metabolic alterations, which adversely impact cardiometabolic health. Here, a comprehensive set of metabolic markers, predominantly lipids, was compared between depressed and nondepressed persons.

METHODS

Nine Dutch cohorts were included, comprising 10,145 control subjects and 5283 persons with depression, established with diagnostic interviews or questionnaires. A proton nuclear magnetic resonance metabolomics platform provided 230 metabolite measures: 51 lipids, fatty acids, and low-molecular-weight metabolites; 98 lipid composition and particle concentration measures of lipoprotein subclasses; and 81 lipid and fatty acids ratios. For each metabolite measure, logistic regression analyses adjusted for gender, age, smoking, fasting status, and lipid-modifying medication were performed within cohort, followed by random-effects meta-analyses.

RESULTS

Of the 51 lipids, fatty acids, and low-molecular-weight metabolites, 21 were significantly related to depression (false discovery rate q < .05). Higher levels of apolipoprotein B, very-low-density lipoprotein cholesterol, triglycerides, diglycerides, total and monounsaturated fatty acids, fatty acid chain length, glycoprotein acetyls, tyrosine, and isoleucine and lower levels of high-density lipoprotein cholesterol, acetate, and apolipoprotein A1 were associated with increased odds of depression. Analyses of lipid composition indicators confirmed a shift toward less high-density lipoprotein and more very-low-density lipoprotein and triglyceride particles in depression. Associations appeared generally consistent across gender, age, and body mass index strata and across cohorts with depressive diagnoses versus symptoms.

CONCLUSIONS

This large-scale meta-analysis indicates a clear distinctive profile of circulating lipid metabolites associated with depression, potentially opening new prevention or treatment avenues for depression and its associated cardiometabolic comorbidity.

Branched-chain amino acids are associated with metabolic parameters in bipolar disorder

Objectives: An important aspect of bipolar disorder (BD) research is the identification of biomarkers pertaining to the somatic health state. The branched-chain essential amino acids (BCAAs), viz valine, leucine and isoleucine, have been proposed as biomarkers of an individual's health state, given their influence on protein synthesis and gluconeogenesis inhibition.Methods: BCAA levels of 141 euthymic/subsyndromal individuals with BD and 141 matched healthy controls (HC) were analysed by high-pressure lipid chromatography and correlated with clinical psychiatric, anthropometric and metabolic parameters.Results: BD and HC did not differ in valine and isoleucine, whereas leucine was significantly lower in BD. Furthermore, correlations were found between BCAAs and anthropometric and glucose metabolism data. All BCAAs correlated with lipid metabolism parameters in females. There were no associations between BCAAs and long-term clinical parameters of BD. A negative correlation was found between valine and Hamilton Depression-Scale, and Beck Depression Inventory II, in male individualsConclusions: Our results indicate the utility of BCAAs as biomarkers for the current state of health, also in BD. As BD individuals have a high risk for overweight/obesity, in association with comorbid medical conditions (e.g. cardiovascular diseases or insulin resistance), health state markers are urgently required. However, no illness-specific associations were found in this euthymic/subsyndromal BD group.