Advances and challenges in development of precision psychiatry through clinical metabolomics on mood and psychotic disorders

The researcher's guide to selecting biomarkers in mental health studies

Clinical mental health researchers may understandably struggle with how to incorporate biological assessments in clinical research. The options are numerous and are described in a vast and complex body of literature. Here we provide guidelines to assist mental health researchers seeking to include biological measures in their studies. Apart from a focus on behavioral outcomes as measured via interviews or questionnaires, we advocate for a focus on biological pathways in clinical trials and epidemiological studies that may help clarify pathophysiology and mechanisms of action, delineate biological subgroups of participants, mediate treatment effects, and inform personalized treatment strategies. With this paper we aim to bridge the gap between clinical and biological mental health research by (1) discussing the clinical relevance, measurement reliability, and feasibility of relevant peripheral biomarkers; (2) addressing five types of biological tissues, namely blood, saliva, urine, stool and hair; and (3) providing information on how to control sources of measurement variability.

Probiotic Lactobacillus plantarum 299v supplementation in patients with major depression in a double-blind, randomized, placebo-controlled trial: A metabolomics study

BACKGROUND

Understanding the multifactorial nature of major depressive disorder (MDD) is crucial for tailoring treatments. However, the complex interplay of various factors underlying the development and progression of MDD poses significant challenges. Our previous study demonstrated improvements in cognitive functions in MDD patients undergoing treatment with selective serotonin reuptake inhibitors (SSRIs) supplemented with Lactobacillus plantarum 299v (LP299v).

METHODS

To elucidate the biochemical mechanisms underlying cognitive functions improvements, we explored underlying metabolic changes. We employed multi-platform metabolomics, including LC-QTOF-MS and CE-TOF-MS profiling, alongside chiral LC-QqQ-MS analysis for amino acids.

RESULTS

Supplementation of SSRI treatment with LP299v intensified the reduction of long-chain acylcarnitines, potentially indicating improved mitochondrial function. LP299v supplementation reduced N-acyl taurines more than four times compared to the placebo, suggesting a substantial impact on restoring biochemical balance. The LP299v-supplemented group showed increased levels of oxidized glycerophosphocholine (oxPC). Additionally, LP299v supplementation led to higher levels of sphingomyelins, L-histidine, D-valine, and p-cresol.

LIMITATIONS

This exploratory study suggests potential metabolic pathways influenced by LP299v supplementation. However, the need for further research hinders the ability to draw definitive conclusions.

CONCLUSIONS

Observed metabolic changes were linked to mitochondrial dysfunction, inflammation, oxidative stress, and gut microbiota disruption. Despite the subtle nature of this alterations, our research successfully detected these differences and connected them to the metabolic disruptions associated with MDD. Our findings emphasise the intricate relationship between metabolism, gut microbiota, and mental health prompting further research into the mechanisms of action of probiotics in MDD treatment.

Peering into the mind: unraveling schizophrenia's secrets using models

Schizophrenia (SCZ) is a complex mental disorder characterized by a range of symptoms, including positive and negative symptoms, as well as cognitive impairments. Despite the extensive research, the underlying neurobiology of SCZ remain elusive. To overcome this challenge, the use of diverse laboratory modeling techniques, encompassing cellular and animal models, and innovative approaches like induced pluripotent stem cell (iPSC)-derived neuronal cultures or brain organoids and genetically engineered animal models, has been crucial. Immortalized cellular models provide controlled environments for investigating the molecular and neurochemical pathways involved in neuronal function, while iPSCs and brain organoids, derived from patient-specific sources, offer significant advantage in translational research by facilitating direct comparisons of cellular phenotypes between patient-derived neurons and healthy-control neurons. Animal models can recapitulate the different psychopathological aspects that should be modeled, offering valuable insights into the neurobiology of SCZ. In addition, invertebrates' models are genetically tractable and offer a powerful approach to dissect the core genetic underpinnings of SCZ, while vertebrate models, especially mammals, with their more complex nervous systems and behavioral repertoire, provide a closer approximation of the human condition to study SCZ-related traits. This narrative review provides a comprehensive overview of the diverse modeling approaches, critically evaluating their strengths and limitations. By synthesizing knowledge from these models, this review offers a valuable source for researchers, clinicians, and stakeholders alike. Integrating findings across these different models may allow us to build a more holistic picture of SCZ pathophysiology, facilitating the exploration of new research avenues and informed decision-making for interventions.

Molecular genetic analysis of candidate genes for glutaric aciduria type II in a cohort of patients from Queensland, Australia

Glutaric aciduria type II (GAII) is a heterogeneous genetic disorder affecting mitochondrial fatty acid, amino acid and choline oxidation. Clinical manifestations vary across the lifespan and onset may occur at any time from the early neonatal period to advanced adulthood. Historically, some patients, in particular those with late onset disease, have experienced significant benefit from riboflavin supplementation. GAII has been considered an autosomal recessive condition caused by pathogenic variants in the gene encoding electron-transfer flavoprotein ubiquinone-oxidoreductase (ETFDH) or in the genes encoding electron-transfer flavoprotein subunits A and B (ETFA and ETFB respectively). Variants in genes involved in riboflavin metabolism have also been reported. However, in some patients, molecular analysis has failed to reveal diagnostic molecular results. In this study, we report the outcome of molecular analysis in 28 Australian patients across the lifespan, 10 paediatric and 18 adult, who had a diagnosis of glutaric aciduria type II based on both clinical and biochemical parameters. Whole genome sequencing was performed on 26 of the patients and two neonatal onset patients had targeted sequencing of candidate genes. The two patients who had targeted sequencing had biallelic pathogenic variants (in ETFA and ETFDH). None of the 26 patients whose whole genome was sequenced had biallelic variants in any of the primary candidate genes. Interestingly, nine of these patients (34.6%) had a monoallelic pathogenic or likely pathogenic variant in a single primary candidate gene and one patient (3.9%) had a monoallelic pathogenic or likely pathogenic variant in two separate genes within the same pathway. The frequencies of the damaging variants within ETFDH and FAD transporter gene SLC25A32 were significantly higher than expected when compared to the corresponding allele frequencies in the general population. The remaining 16 patients (61.5%) had no pathogenic or likely pathogenic variants in the candidate genes. Ten (56%) of the 18 adult patients were taking the selective serotonin reuptake inhibitor antidepressant sertraline, which has been shown to produce a GAII phenotype, and another two adults (11%) were taking a serotonin-norepinephrine reuptake inhibitor antidepressant, venlafaxine or duloxetine, which have a mechanism of action overlapping that of sertraline. Riboflavin deficiency can also mimic both the clinical and biochemical phenotype of GAII. Several patients on these antidepressants showed an initial response to riboflavin but then that response waned. These results suggest that the GAII phenotype can result from a complex interaction between monoallelic variants and the cellular environment. Whole genome or targeted gene panel analysis may not provide a clear molecular diagnosis.

Multiscale metabolomics techniques: Insights into neuroscience research

The field of metabolomics examines the overall composition and dynamic patterns of metabolites in living organisms. The primary methods used in metabolomics include liquid chromatography (LC), nuclear magnetic resonance (NMR), and mass spectrometry (MS) analysis. These methods enable the identification and examination of metabolite types and contents within organisms, as well as modifications to metabolic pathways and their connection to the emergence of diseases. Research in metabolomics has extensive value in basic and applied sciences. The field of metabolomics is growing quickly, with the majority of studies concentrating on biomedicine, particularly early disease diagnosis, therapeutic management of human diseases, and mechanistic knowledge of biochemical processes. Multiscale metabolomics is an approach that integrates metabolomics techniques at various scales, including the holistic, tissue, cellular, and organelle scales, to enable more thorough and in-depth studies of metabolic processes in organisms. Multiscale metabolomics can be combined with methods from systems biology and bioinformatics. In recent years, multiscale metabolomics approaches have become increasingly important in neuroscience research due to the nervous system's high metabolic demands. Multiscale metabolomics can offer novel concepts and approaches for the diagnosis, treatment, and development of medication for neurological illnesses in addition to a more thorough understanding of brain metabolism and nervous system function. In this review, we summarize the use of multiscale metabolomics techniques in neuroscience, address the promise and constraints of these techniques, and provide an overview of the metabolome and its applications in neuroscience.

Metabolomic analysis of swainsonine poisoning in renal tubular epithelial cells

Locoweed is a poisonous plant widely present in grasslands around the world. Swainsonine (SW), an indole alkaloid that, is the main toxic component of the locoweed. To understand the mechanism of SW-induced toxicity and to delineate the metabolic profile of locoweed poisoning we performed the LC-MS/MS untargeted metabolomic study to analyze metabolites in SW-treated renal tubular epithelial cells (0.8 mg/mL, 12 h) and in order to identify the SW-induced metabolomic changes. The analysis identified 2,563 metabolites in positive ion mode and 1,990 metabolites in negative ion mode. Our results showed that the metabolites were mainly benzenoids, lipids and lipid-like molecules, nucleosides, nucleotides, and analogs, organic acids, and derivatives. The differential metabolites were primarily enriched in pathways involving bile secretion, primary bile acid biosynthesis, riboflavin metabolism, ferroptosis, drug metabolism-cytochrome P450, and primidine metabolism. We have screened out substances such as swainsonine, 3alpha,7alpha-Dihydroxy-5beta-cholestanate, 2-Hydroxyiminostilbene, and glycochenodeoxycholate, which may have the potential to serve as biomarkers for swainsonine poisoning. This study provides insights into the types of metabolomic alteration in renal tubular epithelial cells induced by swainsonine.

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.

Precision psychiatry and Research Domain Criteria: Implications for clinical trials and future practice

Psychiatric disorders are associated with significant social and economic burdens, many of which are related to issues with current diagnosis and treatments. The coronavirus (COVID-19) pandemic is estimated to have increased the prevalence and burden of major depressive and anxiety disorders, indicating an urgent need to strengthen mental health systems globally. To date, current approaches adopted in drug discovery and development for psychiatric disorders have been relatively unsuccessful. Precision psychiatry aims to tailor healthcare more closely to the needs of individual patients and, when informed by neuroscience, can offer the opportunity to improve the accuracy of disease classification, treatment decisions, and prevention efforts. In this review, we highlight the growing global interest in precision psychiatry and the potential for the National Institute of Health-devised Research Domain Criteria (RDoC) to facilitate the implementation of transdiagnostic and improved treatment approaches. The need for current psychiatric nosology to evolve with recent scientific advancements and increase awareness in emerging investigators/clinicians of the value of this approach is essential. Finally, we examine current challenges and future opportunities of adopting the RDoC-associated translational and transdiagnostic approaches in clinical studies, acknowledging that the strength of RDoC is that they form a dynamic framework of guiding principles that is intended to evolve continuously with scientific developments into the future. A collaborative approach that recruits expertise from multiple disciplines, while also considering the patient perspective, is needed to pave the way for precision psychiatry that can improve the prognosis and quality of life of psychiatric patients.

Metabolomics and Self-Reported Depression, Anxiety, and Phobic Symptoms in the VA Normative Aging Study

Traditional approaches to understanding metabolomics in mental illness have focused on investigating a single disorder or comparisons between diagnoses, but a growing body of evidence suggests substantial mechanistic overlap in mental disorders that could be reflected by the metabolome. In this study, we investigated associations between global plasma metabolites and abnormal scores on the depression, anxiety, and phobic anxiety subscales of the Brief Symptom Inventory (BSI) among 405 older males who participated in the Normative Aging Study (NAS). Our analysis revealed overlapping and distinct metabolites associated with each mental health dimension subscale and four metabolites belonging to xenobiotic, carbohydrate, and amino acid classes that were consistently associated across all three symptom dimension subscales. Furthermore, three of these four metabolites demonstrated a higher degree of alteration in men who reported poor scores in all three dimensions compared to men with poor scores in only one, suggesting the potential for shared underlying biology but a differing degree of perturbation when depression and anxiety symptoms co-occur. Our findings implicate pathways of interest relevant to the overlap of mental health conditions in aging veterans and could represent clinically translatable targets underlying poor mental health in this high-risk population.

NMR Metabolomics in Serum Fingerprinting of Schizophrenia Patients in a Serbian Cohort

Schizophrenia is a widespread mental disorder that leads to significant functional impairments and premature death. The state of the art indicates gaps in the understanding and diagnosis of this disease, but also the need for personalized and precise approaches to patients through customized medical treatment and reliable monitoring of treatment response. In order to fulfill existing gaps, the establishment of a universal set of disorder biomarkers is a necessary step. Metabolomic investigations of serum samples of Serbian patients with schizophrenia (51) and healthy controls (39), based on NMR analyses associated with chemometrics, led to the identification of 26 metabolites/biomarkers for this disorder. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models with prediction accuracies of 0.9718 and higher were accomplished during chemometric analysis. The established biomarker set includes aspartate/aspartic acid, lysine, 2-hydroxybutyric acid, and acylglycerols, which are identified for the first time in schizophrenia serum samples by NMR experiments. The other 22 identified metabolites in the Serbian samples are in accordance with the previously established NMR-based serum biomarker sets of Brazilian and/or Chinese patient samples. Thirteen metabolites (lactate/lactic acid, threonine, leucine, isoleucine, valine, glutamine, asparagine, alanine, gamma-aminobutyric acid, choline, glucose, glycine and tyrosine) that are common for three different ethnic and geographic origins (Serbia, Brazil and China) could be a good start point for the setup of a universal NMR serum biomarker set for schizophrenia.

Searching for biomarkers in schizophrenia and psychosis: Case-control study using capillary electrophoresis and liquid chromatography time-of-flight mass spectrometry and systematic review for biofluid metabolites

Metabolomics has been attracting attention in recent years as an objective method for diagnosing schizophrenia. In this study, we analyzed 378 metabolites in the serum of schizophrenia patients using capillary electrophoresis- and liquid chromatography-time-of-flight mass spectrometry. Using multivariate analysis with the orthogonal partial least squares method, we observed significantly higher levels of alanine, glutamate, lactic acid, ornithine, and serine and significantly lower levels of urea, in patients with chronic schizophrenia compared to healthy controls. Additionally, levels of fatty acids (15:0), (17:0), and (19:1), cis-11-eicosenoic acid, and thyroxine were significantly higher in patients with acute psychosis than in those in remission. Moreover, we conducted a systematic review of comprehensive metabolomics studies on schizophrenia over the last 20 years and observed consistent trends of increase in some metabolites such as glutamate and glucose, and decrease in citrate in schizophrenia patients across several studies. Hence, we provide substantial evidence for metabolic biomarkers in schizophrenia patients through our metabolomics study.

Metabolomics changes after rTMS intervention reveal potential peripheral biomarkers in methamphetamine dependence

Methamphetamine is one of the most commonly used drugs around the world, leading to serious public health and psychiatric problems. Due to the lackness of objective laboratory evaluation indicators, the molecular mechanisms of methamphetamine dependence still remain unclear. Previous evidence demonstrated that repetitive transcranial magnetic stimulation (rTMS) may be useful in treating drug addiction. The aim of this study was to identify and validate plasma metabolomics biomarkers in patients with methamphetamine use disorder before and after rTMS intervention. An untargeted gas chromatography-time-of-flight mass spectrometry (GC-TOFMS) based metabolomics approach was applied to characterize the metabolic profile of forty methamphetamine dependent subjects and thirty-eight healthy controls in peripheral blood mononuclear cells (PBMCs). Patients were randomized to receive either rTMS or sham over the DLPFC for four weeks (20 daily sessions, 900 pulses per day). Cognitive function were assessed before and after rTMS intervention. Eight PBMC metabolites responsible for distinguishing real rTMS from sham treatment were identified. These metabolites were mainly involved in energy metabolism and oxidative stress. Compared with baseline, the expression of three metabolites was reversed after rTMS intervention: alpha-tocopherol, glyceric acid and fumaric acid. Changes of the alpha-tocopherol were associated with cognitive function improvement following rTMS. These findings suggest that energy metabolism and oxidative stress system may be associated with the effect of rTMS on cognitive function in methamphetamine dependence, and warrant further investigation.

New perspectives on the role of the neurosteroid pregnenolone as an endogenous regulator of type-1 cannabinoid receptor (CB1R) activity and function

Pregnenolone is a steroid with specific characteristics, being the first steroid to be synthesised from cholesterol at all sites of steroidogenesis, including the brain. For many years, pregnenolone was defined as an inactive precursor of all steroids because no specific target had been discovered. However, over the last decade, it has become a steroid of interest because it has been recognised as being a biomarker for brain-related disorders through the development of metabolomic approaches and advanced analytical methods. In addition, physiological roles for pregnenolone emerged when specific targets were discovered. In this review, we highlight the discovery of the selective interaction of pregnenolone with the type-1 cannabinoid receptor (CB1R). After describing the specific characteristic of CB1Rs, we discuss the newly discovered mechanisms of their regulation by pregnenolone. In particular, we describe the action of pregnenolone as a negative allosteric modulator and a specific signalling inhibitor of the CB1R. These particular characteristics of pregnenolone provide a great strategic opportunity for therapeutic development in CB1-related disorders. Finally, we outline new perspectives using innovative genetic tools for the discovery of original regulatory mechanisms of pregnenolone on CB1-related functions.

Alterations in Glycerolipid and Fatty Acid Metabolic Pathways in Alzheimer's Disease Identified by Urinary Metabolic Profiling: A Pilot Study

An easily accessible and non-invasive biomarker for the early detection of Alzheimer's disease (AD) is needed. Evidence suggests that metabolic dysfunction underlies the pathophysiology of AD. While urine is a non-invasively collectable biofluid and a good source for metabolomics analysis, it is not yet widely used for this purpose. This small-scale pilot study aimed to examine whether the metabolic profile of urine from AD patients reflects the metabolic dysfunction reported to underlie AD pathology, and to identify metabolites that could distinguish AD patients from cognitively healthy controls. Spot urine of 18 AD patients (AD group) and 18 age- and sex-matched, cognitively normal controls (control group) were analyzed by mass spectrometry (MS). Capillary electrophoresis time-of-flight MS and liquid chromatography–Fourier transform MS were used to cover a larger range of molecules with ionic as well as lipid characteristics. A total of 304 ionic molecules and 81 lipid compounds of 12 lipid classes were identified. Of these, 26 molecules showed significantly different relative concentrations between the AD and control groups (Wilcoxon's rank-sum test). Moreover, orthogonal partial least-squares discriminant analysis revealed significant discrimination between the two groups. Pathway searches using the KEGG database, and pathway enrichment and topology analysis using Metaboanalyst software, suggested alterations in molecules relevant to pathways of glycerolipid and glycerophospholipid metabolism, thermogenesis, and caffeine metabolism in AD patients. Further studies of urinary metabolites will contribute to the early detection of AD and understanding of its pathogenesis.

A system biology approach based on metabolic biomarkers and protein-protein interactions for identifying pathways underlying schizophrenia and bipolar disorder

Mental disorders (MDs), including schizophrenia (SCZ) and bipolar disorder (BD), have attracted special attention from scientists due to their high prevalence and significantly debilitating clinical features. The diagnosis of MDs is still essentially based on clinical interviews, and intensive efforts to introduce biochemical based diagnostic methods have faced several difficulties for implementation in clinics, due to the complexity and still limited knowledge in MDs. In this context, aiming for improving the knowledge in etiology and pathophysiology, many authors have reported several alterations in metabolites in MDs and other brain diseases. After potentially fishing all metabolite biomarkers reported up to now for SCZ and BD, we investigated here the proteins related to these metabolites in order to construct a protein-protein interaction (PPI) network associated with these diseases. We determined the statistically significant clusters in this PPI network and, based on these clusters, we identified 28 significant pathways for SCZ and BDs that essentially compose three groups representing three major systems, namely stress response, energy and neuron systems. By characterizing new pathways with potential to innovate the diagnosis and treatment of psychiatric diseases, the present data may also contribute to the proposal of new intervention for the treatment of still unmet aspects in MDs.

Emerging application of metabolomics on Chinese herbal medicine for depressive disorder

Depressive disorder is a kind of emotional disorder that is mainly manifested with spontaneous and persistent low mood. Its etiology is complex and still not fully understood. Metabolomics, an important part of system biology characterized by its integrity and systematicness, analyzes endogenous metabolites of small molecules in vivo and examines the metabolic status of the organism. It is widely used in the field of disease research for its unique advantage in the disease molecular marker discovering Due to fewer adverse reactions and high safety, Chinese herbal medicine (CHM) has great advantages in the treatment of chronic diseases including depression. Metabolomics has been gradually applied to the efficacy evaluation of CHM in treatment of depression and the metabolomics analysis exhibits a systemic metabolic shift in amino acids (such as alanine, glutamic acid, valine, etc.), organic acids (lactic acid, citric acid, stearic acid, palmitic acid, etc.), and sugars, amines, etc. These differential metabolites are mainly involved in energy metabolism, amino acid metabolism, lipid metabolism, etc. In this review, we have exemplified the study of CHM in animals or clinics on the depression, and revealed that CHM treatment has significantly changed the metabolic disorders associated with depression, promoting metabolic network reorganization through restoring of key metabolites, and metabolic pathways, which may be the main mechanism basis of CHM's treatment on depression. Besides, we further envisioned the future application of metabolomics in the study of CHM treatment of depression.

Metabolomic Characterization of Pediatric Acute-Onset Neuropsychiatric Syndrome (PANS)

Introduction

PANS is a controversial clinical entity, consisting of a complex constellation of psychiatric symptoms, adventitious changes, and expression of various serological alterations, likely sustained by an autoimmune/inflammatory disease. Detection of novel biomarkers of PANS is highly desirable for both diagnostic and therapeutic management of affected patients. Analysis of metabolites has proven useful in detecting biomarkers for other neuroimmune-psychiatric diseases. Here, we utilize the metabolomics approach to determine whether it is possible to define a specific metabolic pattern in patients affected by PANS compared to healthy subjects.

Design

This observational case-control study tested consecutive patients referred for PANS between June 2019 to May 2020. A PANS diagnosis was confirmed according to the PANS working criteria (National Institute of Mental Health [NIMH], 2010). Healthy age and sex-matched subjects were recruited as controls.

Methods

Thirty-four outpatients referred for PANS (mean age 9.5 years; SD 2.9, 71% male) and 25 neurotypical subjects matched for age and gender, were subjected to metabolite analysis. Serum samples were obtained from each participant and were analyzed using Nuclear Magnetic Resonance (NMR) spectroscopy. Subsequently, multivariate and univariate statistical analyses and Receiver Operator Curves (ROC) were performed.

Results

Separation of the samples, in line with the presence of PANS diagnosis, was observed by applying a supervised model (R²X = 0.44, R²Y = 0.54, Q² = 0.44, p-value < 0.0001). The significantly altered variables were 2-Hydroxybutyrate, glycine, glutamine, histidine, tryptophan. Pathway analysis indicated that phenylalanine, tyrosine, and tryptophan metabolism, as well as glutamine and glutamate metabolism, exhibited the largest deviations from neurotypical controls.

Conclusion

We found a unique plasma metabolic profile in PANS patients, significantly differing from that of healthy children, that suggests the involvement of specific patterns of neurotransmission (tryptophan, glycine, histamine/histidine) as well as a more general state of neuroinflammation and oxidative stress (glutamine, 2-Hydroxybutyrate, and tryptophan-kynurenine pathway) in the disorder. This metabolomics study offers new insights into biological mechanisms underpinning the disorder and supports research of other potential biomarkers implicated in PANS.

Design of Multi-Shelled Hollow Cr2 O3 Spheres for Metabolic Fingerprinting

Schizophrenia (SZ) detection enables effective treatment to improve the clinical outcome, but objective and reliable SZ diagnostics are still limited. An ideal diagnosis of SZ suited for robust clinical screening must address detection throughput, low invasiveness, and diagnosis accuracy. Herein, we built a multi-shelled hollow Cr₂ O₃ spheres (MHCSs) assisted laser desorption/ionization mass spectrometry (LDI MS) platform for the direct metabolic profiling of biofluids towards SZ diagnostics. The MHCSs displayed strong light absorption for enhanced ionization and microscale surface roughness with stability for the effective LDI of metabolites. We profiled urine and serum metabolites (≈1 μL) with the enhanced LDI efficacy in seconds. We discriminated SZ patients (SZs) from healthy controls (HCs) with the highest area under the curve (AUC) value of 1.000 for the blind test. We identified four compounds with optimal diagnostic power as a simplified metabolite panel for SZ and demonstrated the metabolite quantification for clinic use. Our approach accelerates the growth of new platforms toward a precision diagnosis in the near future.

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.

Plasma Metabolomics Profiling of Metabolic Pathways Affected by Major Depressive Disorder

Background: Major depressive disorder (MDD) is a common disease which is complicated by metabolic disorder. Although MDD has been studied relatively intensively, its metabolism is yet to be elucidated. Methods: To profile the global pathophysiological processes of MDD patients, we used metabolomics to identify differential metabolites and applied a new database Metabolite set enrichment analysis (MSEA) to discover dysfunctions of metabolic pathways of this disease. Hydrophilic metabolomics were applied to identify metabolites by profiling the plasma from 55 MDD patients and 100 sex-, gender-, BMI-matched healthy controls. The metabolites were then analyzed in MSEA in an attempt to discover different metabolic pathways. To investigate dysregulated pathways, we further divided MDD patients into two cohorts: (1) MDD patients with anxiety symptoms and (2) MDD patients without anxiety symptoms. Results: Metabolites which were hit in those pathways correlated with depressive and anxiety symptoms. Altogether, 17 metabolic pathways were enriched in MDD patients, and 23 metabolites were hit in those pathways. Three metabolic pathways were enriched in MDD patients without anxiety, including glycine and serine metabolism, arginine and proline metabolism, and phenylalanine and tyrosine metabolism. In addition, L-glutamic acid was positively correlated with the severity of depression and retardation if hit in MDD patients without anxiety symptoms. Conclusions: Different kinds of metabolic pathophysiological processes were found in MDD patients. Disorder of glycine and serine metabolism was observed in both MDD patients with anxiety and those without.

A metabolome-wide association study in the general population reveals decreased levels of serum laurylcarnitine in people with depression

Depression constitutes a leading cause of disability worldwide. Despite extensive research on its interaction with psychobiological factors, associated pathways are far from being elucidated. Metabolomics, assessing the final products of complex biochemical reactions, has emerged as a valuable tool for exploring molecular pathways. We conducted a metabolome-wide association analysis to investigate the link between the serum metabolome and depressed mood (DM) in 1411 participants of the KORA (Cooperative Health Research in the Augsburg Region) F4 study (discovery cohort). Serum metabolomics data comprised 353 unique metabolites measured by Metabolon. We identified 72 (5.1%) KORA participants with DM. Linear regression tests were conducted modeling each metabolite value by DM status, adjusted for age, sex, body-mass index, antihypertensive, cardiovascular, antidiabetic, and thyroid gland hormone drugs, corticoids and antidepressants. Sensitivity analyses were performed in subcohorts stratified for sex, suicidal ideation, and use of antidepressants. We replicated our results in an independent sample of 968 participants of the SHIP-Trend (Study of Health in Pomerania) study including 52 (5.4%) individuals with DM (replication cohort). We found significantly lower laurylcarnitine levels in KORA F4 participants with DM after multiple testing correction according to Benjamini/Hochberg. This finding was replicated in the independent SHIP-Trend study. Laurylcarnitine remained significantly associated (p value < 0.05) with depression in samples stratified for sex, suicidal ideation, and antidepressant medication. Decreased blood laurylcarnitine levels in depressed individuals may point to impaired fatty acid oxidation and/or mitochondrial function in depressive disorders, possibly representing a novel therapeutic target.

Allostatic load, emotional hyper-reactivity, and functioning in individuals with bipolar disorder

OBJECTIVES

Diagnosis and management of bipolar disorder (BD) are limited by the absence of available biomarkers. Allostatic load (AL) represents the strain that stress, including the effects of acute phases and inter-episode chronic mood instability, exerts on interconnected biological systems. This study aimed to operationalize an AL index and explore whether it could be relevant to better characterize BD patients with and without emotional hyper-reactivity particularly those at higher risk of immune-cardiometabolic dysregulation and functional impairment.

METHODS

Levels of biomarkers of chronic inflammation (hsCRP and albumin), cardiovascular (systolic/diastolic blood pressure) and metabolic functions (fasting glucose, glycosylated hemoglobin, total cholesterol, LDL, HDL, and triglycerides) were measured in 1072 adult BD outpatients. Patients were classified in two groups (with/without emotional hyper-reactivity) assessed by the Multidimensional Assessment of Thymic States scale. An Allostatic Load Index for BD (BALLI), comprising six biomarkers, was constructed using data-driven biomarker selection.

RESULTS

BALLI showed 81.1% accuracy with good sensitivity (81%) and specificity (81.2%) for characterizing BD patients presenting emotional hyper-reactivity, elevated risk of inflammation (increased hsCRP, hypoalbuminemia) and cardiometabolic disturbances (hypertension, hyperglycemia, and hypertriglyceridemia). Patients classified by the BALLI as presenting emotional hyper-reactivity had significantly lower global and cognitive functioning than those without emotional hyper-reactivity (P < .0001).

CONCLUSIONS

A multidimensional approach based on a simple AL score (eg, BALLI) and dimensions of behavior (eg, emotional hyper-reactivity) alongside mood is clinically relevant. AL index could be a useful tool to detect multisystemic physiological dysregulations in BD patients with/without emotional hyper-reactivity particularly those at higher risk of immune-cardiometabolic disturbances and functional impairment.

Association of alkali metals and Alkaline-earth metals with the risk of schizophrenia in a Chinese population: A Case-Control study

Alkali metals (AMs) and alkali earth metals (AEMs) affect levels and signaling of neurotransmitters, which potentially play a role in the etiology of schizophrenia (SCZ). The current case-control study aims to explore how AMs [i.e. Potassium (K), sodium (Na), rubidium (Rb), cesium (Cs)] and AEMs [i.e. magnesium (Mg), calcium (Ca), strontium (Sr), barium (Ba)] in serum could associate with SCZ. One hundred and five inpatients with SCZ and 106 age- and sex-matched healthy controls (HCs) were recruited from Weifang, China. Inductively Coupled Plasma-Atomic Emission Spectrometry (ICP-AES) was used to evaluate serum concentrations of Na, K, Ca, Mg and Inductively Coupled Plasma Mass Spectrometry (ICP-MS) was for Rb, Cs, Sr, Ba. Subjects with SCZ had significantly higher Mg and Sr serum concentrations than HCs (20.86 vs. 19.73 μg/mL of Mg, p < 0.001; 53.14 vs. 42.26 ng/mL of Sr, p < 0.001). After adjusting for confounders, the odds ratio of Mg and Sr remain significantly higher in the SCZ group (Mg: OR = 2.538, 95 % CI: 1.254-5.136, p=0.010; Sr: OR = 3.798, 95 % CI: 1.769-8.153, p = 0.001). No significant differences between SCZ subjects and HCs were observed for other AMs and AEMs. Higher serum concentrations of Mg and Sr were associated with SCZ. Studies are suggested to find the related mechanisms and provide clues for pathogenesis of SCZ, which would impact prevention and treatments of SCZ.