Metabolomics approach revealed robust changes in amino acid and biogenic amine signatures in patients with schizophrenia in the early course of the disease

Integrative metabolomics-genomics analysis identifies key networks in a stem cell-based model of schizophrenia

Schizophrenia (SCZ) is a neuropsychiatric disorder, caused by a combination of genetic and environmental factors. The etiology behind the disorder remains elusive although it is hypothesized to be associated with the aberrant response to neurotransmitters, such as dopamine and glutamate. Therefore, investigating the link between dysregulated metabolites and distorted neurodevelopment holds promise to offer valuable insights into the underlying mechanism of this complex disorder. In this study, we aimed to explore a presumed correlation between the transcriptome and the metabolome in a SCZ model based on patient-derived induced pluripotent stem cells (iPSCs). For this, iPSCs were differentiated towards cortical neurons and samples were collected longitudinally at various developmental stages, reflecting neuroepithelial-like cells, radial glia, young and mature neurons. The samples were analyzed by both RNA-sequencing and targeted metabolomics and the two modalities were used to construct integrative networks in silico. This multi-omics analysis revealed significant perturbations in the polyamine and gamma-aminobutyric acid (GABA) biosynthetic pathways during rosette maturation in SCZ lines. We particularly observed the downregulation of the glutamate decarboxylase encoding genes GAD1 and GAD2, as well as their protein product GAD65/67 and their biochemical product GABA in SCZ samples. Inhibition of ornithine decarboxylase resulted in further decrease of GABA levels suggesting a compensatory activation of the ornithine/putrescine pathway as an alternative route for GABA production. These findings indicate an imbalance of cortical excitatory/inhibitory dynamics occurring during early neurodevelopmental stages in SCZ. Our study supports the hypothesis of disruption of inhibitory circuits to be causative for SCZ and establishes a novel in silico approach that enables for integrative correlation of metabolic and transcriptomic data of psychiatric disease models.

Asparagine reduces the risk of schizophrenia: a bidirectional two-sample mendelian randomization study of aspartate, asparagine and schizophrenia

BACKGROUND

Despite ongoing research, the underlying causes of schizophrenia remain unclear. Aspartate and asparagine, essential amino acids, have been linked to schizophrenia in recent studies, but their causal relationship is still unclear. This study used a bidirectional two-sample Mendelian randomization (MR) method to explore the causal relationship between aspartate and asparagine with schizophrenia.

METHODS

This study employed summary data from genome-wide association studies (GWAS) conducted on European populations to examine the correlation between aspartate and asparagine with schizophrenia. In order to investigate the causal effects of aspartate and asparagine on schizophrenia, this study conducted a two-sample bidirectional MR analysis using genetic factors as instrumental variables.

RESULTS

No causal relationship was found between aspartate and schizophrenia, with an odds ratio (OR) of 1.221 (95%CI: 0.483-3.088, P-value = 0.674). Reverse MR analysis also indicated that no causal effects were found between schizophrenia and aspartate, with an OR of 0.999 (95%CI: 0.987-1.010, P-value = 0.841). There is a negative causal relationship between asparagine and schizophrenia, with an OR of 0.485 (95%CI: 0.262-0.900, P-value = 0.020). Reverse MR analysis indicates that there is no causal effect between schizophrenia and asparagine, with an OR of 1.005(95%CI: 0.999-1.011, P-value = 0.132).

CONCLUSION

This study suggests that there may be a potential risk reduction for schizophrenia with increased levels of asparagine, while also indicating the absence of a causal link between elevated or diminished levels of asparagine in individuals diagnosed with schizophrenia. There is no potential causal relationship between aspartate and schizophrenia, whether prospective or reverse MR. However, it is important to note that these associations necessitate additional research for further validation.

Metabolomics, Lipidomics, and Antipsychotics: A Systematic Review

Antipsychotics are an important pharmacotherapy option for the treatment of many mental illnesses. Unfortunately, selecting antipsychotics is often a trial-and-error process due to a lack of understanding as to which medications an individual patient will find most effective and best tolerated. Metabolomics, or the study of small molecules in a biosample, is an increasingly used omics platform that has the potential to identify biomarkers for medication efficacy and toxicity. This systematic review was conducted to identify metabolites and metabolomic pathways associated with antipsychotic use in humans. Ultimately, 42 studies were identified for inclusion in this review, with all but three studies being performed in blood sources such as plasma or serum. A total of 14 metabolite classes and 12 lipid classes were assessed across studies. Although the studies were highly heterogeneous in approach and mixed in their findings, increases in phosphatidylcholines, decreases in carboxylic acids, and decreases in acylcarnitines were most consistently noted as perturbed in patients exposed to antipsychotics. Furthermore, for the targeted metabolomic and lipidomic studies, seven metabolites and three lipid species had findings that were replicated. The most consistent finding for targeted studies was an identification of a decrease in aspartate with antipsychotic treatment. Studies varied in depth of detail provided for their study participants and in study design. For example, in some cases, there was a lack of detail on specific antipsychotics used or concomitant medications, and the depth of detail on sample handling and analysis varied widely. The conclusions here demonstrate that there is a large foundation of metabolomic work with antipsychotics that requires more complete reporting so that an objective synthesis such as a meta-analysis can take place. This will then allow for validation and clinical application of the most robust findings to move the field forward. Future studies should be carefully controlled to take advantage of the sensitivity of metabolomics while limiting potential confounders that may result from participant heterogeneity and varied analysis approaches.

Anti-Bordetella bronchiseptica effects of targeted bacteriophages via microbiome and metabolic mediated mechanisms

Bordetella bronchiseptica poses a significant challenge in the context of respiratory infections, particularly in weanling pigs. In this study, we investigated the impact of a novel targeted bacteriophage in controlling B. bronchiseptica challenge (BBC) in an experimental design involving five distinct treatment groups: NC (no challenge), PC (BBC challenge), BF (108 pfu bacteriophage/kg diet + BBC), BN (2 × 107 pfu/day bacteriophage by nasal spray + BBC), and AT (antibiotic + BBC). The experiment was conducted for 2 weeks. The highest turbinate score was observed in the PC. The BF treatment showed higher plasma IL (interleukine)-1β and IL-6 compared with the BN and AT treatments. Plasma concentrations of IL-1β were increased in the BF pigs compared with the BN, AT, and NC. Among the BBC groups, the PC treatment exhibited a higher abundance of Staphylococcus. aureus and B. bronchiseptica in the lung. A lower S. aureus, Streptococcus. suis, and B. bronchiseptica colonization was detected in the AT compared with the BF and BN treatments. The BF showed lower plasma zonulin compared with the BN and AT. A higher plasma concentration of superoxide dismutase was observed in the BF and AT compared with PC and BN. The BN influenced the glycine, serine-threonine metabolism; glycerolipid metabolism; glyoxylate-dicarboxylate metabolism; and arachidonic acid metabolism compared with the NC. In conclusion, nasal-sprayed bacteriophage effectively controlled B. bronchiseptica infection, however, their efficiency was lower than the antibiotic.

Multivariate analyses of immune markers reveal increases in plasma EN-RAGE in first-episode psychosis patients

Immune cells and cytokines are largely recognized as significant factors in the pathophysiology of neuropsychiatric disorders. The possible role of other blood cells such as leukocytes in events of acute psychosis is in contrast only emerging. To study blood-born markers in acute psychosis we here evaluated plasma proteins in drug-naive first-episode psychosis (FEP) patients and healthy controls using a multiplex proximity extension assay technique. We analyzed a panel of 92 immune markers and plasma samples from 60 FEP patients and 50 controls and evaluated the changes obtained using multivariate statistical methods followed by protein pathway analyses. Data showed that 11 proteins are significantly different between FEP patients and healthy controls We observed increases in pro-inflammatory proteins such as interleukin-6, oncostatin-M, and transforming growth factor-alpha in FEP patients compared with controls. Likewise, the extracellular newly identified RAGE-binding protein (EN-RAGE) that regulates the expression of various cytokines was also elevated in the plasma of FEP patients. The results indicate that neutrophil-derived EN-RAGE could play an important role during the early phase of acute psychosis by stimulating cytokines and the immune response targeting thereby likely also the brain vasculature.

Kynurenine pathway dynamics in patients with schizophrenia spectrum disorders across the disease trajectory

The aim of this study was to evaluate how schizophrenia spectrum disorders (SSD) and applied long-term (5.1 years) antipsychotic (AP) treatment affect the serum levels of tryptophan (Trp) metabolites. A total of 112 adults (54 first-episode psychosis [FEP] patients and 58 control subjects [CSs]) participated in the study. The investigated changes in the metabolite levels appeared against a background of persistent increase in BMI and waist circumference among the patients. Regarding the kynurenine (KYN) pathway, the strongest changes were seen in AP-naïve FEP patients. Trp, KYN, kynurenic acid (KYNA), and anthranilic acid (ANT) levels were significantly reduced in blood samples from patients in the early stage of the disease. Furthermore, 3-OH-kynurenine (3-HK) and quinolinic acid (QUIN) levels were somewhat lower in these patients. Most of these changes in the KYN pathway became weaker with AP treatment. The levels of serotonin and its metabolite 5-HIAA tended to be higher at 5.1 years in patients showing the relation of elevated serotonin turnover to increased BMI and waist circumference. The similar trend was evident for the ratio between xanthurenic acid (XA) and KYNA with strong link to the elevated BMI. Altogether, the present study supports the role of Trp-metabolites in the development of obesity and metabolic syndrome in SSD patients.

Alterations in inflammasome-related immunometabolites in individuals with severe psychiatric disorders

INTRODUCTION

Psychiatric disorders are common and significantly impact the quality of life. Inflammatory processes are proposed to contribute to the emergence of psychiatric disorders. In addition to inflammation, disturbances in metabolic pathways have been observed in individuals with different psychiatric disorders. A suggested key player in the interaction between inflammation and metabolism is the Nod-like receptor 3 (NLRP3) inflammasome, and NLRP3 is known to react to a number of specific metabolites. However, little is known about the interplay between these immunometabolites and the NLRP3 inflammasome in mental health disorders.

AIM

To assess the interplay between immunometabolites and inflammasome function in a transdiagnostic cohort of individuals with severe mental disorders.

METHODS

Mass spectrometry-based analysis of selected immunometabolites, previously known to affect inflammasome function, were performed in plasma from low-functioning individuals with severe mental disorders (n = 39) and sex and aged-matched healthy controls (n = 39) using a transdiagnostic approach. Mann Whitney U test was used to test differences in immunometabolites between psychiatric patients and controls. To assess the relationship between inflammasome parameters, disease severity, and the immunometabolites, Spearman's rank-order correlation test was used. Conditional logistic regression was used to control for potential confounding variables. Principal component analysis was performed to explore immunometabolic patterns.

RESULTS

Among the selected immunometabolites (n = 9), serine, glutamine, and lactic acid were significantly higher in the patient group compared to the controls. After adjusting for confounders, the differences remained significant for all three immunometabolites. No significant correlations were found between immunometabolites and disease severity.

CONCLUSION

Previous research on metabolic changes in mental disorders has not been conclusive. This study shows that severely ill patients have common metabolic perturbations. The changes in serine, glutamine, and lactic acid could constitute a direct contribution to the low-grade inflammation observed in severe psychiatric disorders.

Ketamine as a pharmacological tool for the preclinical study of memory deficit in schizophrenia

Schizophrenia is a serious neuropsychiatric disorder characterized by the presence of positive symptoms (hallucinations, delusions, and disorganization of thought and language), negative symptoms (abulia, alogia, and affective flattening), and cognitive impairment (attention deficit, impaired declarative memory, and deficits in social cognition). Dopaminergic hyperactivity seems to explain the positive symptoms, but it does not completely clarify the appearance of negative and cognitive clinical manifestations. Preclinical data have demonstrated that acute and subchronic treatment with NMDA receptor antagonists such as ketamine (KET) represents a useful model that resembles the schizophrenia symptomatology, including cognitive impairment. This latter has been explained as a hypofunction of NMDA receptors located on the GABA parvalbumin-positive interneurons (near to the cortical pyramidal cells), thus generating an imbalance between the inhibitory and excitatory activity in the corticomesolimbic circuits. The use of behavioral models to explore alterations in different domains of memory is vital to learn more about the neurobiological changes that underlie schizophrenia. Thus, to better understand the neurophysiological mechanisms involved in cognitive impairment related to schizophrenia, the purpose of this review is to analyze the most recent findings regarding the effect of KET administration on these processes.

Exploring the key factors of schizophrenia relapse by integrating LC-MS/1H NMR metabolomics and weighted correlation network analysis

BACKGROUND

Lack of comprehending key factors of schizophrenia relapse has impeded its effective treatment, indicating that the mechanism clarification and available intervention of schizophrenia relapse required further amelioration.

METHOD

Based on the integration of LC-MS and ¹H NMR metabolomics, a weighted correlation network was established to screen pivotal factors of accelerating schizophrenia relapse. Then, the cluster most correlated with schizophrenia relapse was explored, and the biological function of cluster was investigated. Next, the key biomarker related to schizophrenia relapse was obtained through multiple algorithms. Moreover, the Lilikoi algorithm and correlation analysis were implemented to reveal the association between key biomarker and schizophrenia relapse.

RESULT

Results showed that 458 different forms of metabolites were identified for structuring the weighted correlation network. The module-trait correlation indicated that the turquoise module was the most highly correlated with schizophrenia relapse. Further, network analysis revealed that, in turquoise module, cluster 1 composed of 139 metabolites (involved in lipid metabolism and energy metabolism) was the most important subnetwork relevant to schizophrenia relapse. Finally, phenylalanylphenylalanine was recommended as the key biomarker related to schizophrenia relapse. Moreover, the correlation analysis indicated that phenylalanylphenylalanine might affect the progression of schizophrenia by intervening in energy metabolism.

CONCLUSION

In summary, critical factors of schizophrenia relapse have been revealed in our research, expounding the schizophrenia progression more systemically, which could shed some light on improving the intervention of schizophrenia relapse.

A Marked Low-Grade Inflammation and a Significant Deterioration in Metabolic Status in First-Episode Schizophrenia: A Five-Year Follow-Up Study

The objective of this study was to evaluate how schizophrenia spectrum disorders and applied long-term (5.1 years) antipsychotic (AP) treatment affect the serum level of acylcarnitines (ACs), cytokines and metabolic biomarkers and to characterize the dynamics of inflammatory and metabolic changes in the early course of the disorder. A total of 112 adults participated in the study (54 patients with first-episode psychosis (FEP) and 58 control subjects). Biomolecule profiles were measured at the onset of first-episode psychosis and 0.6 years and 5.1 years after the initiation of APs. The results of the present study confirmed that specific metabolic-inflammatory imbalance characterizes AP-naïve patients. Short-term (0.6-years) AP treatment has a favourable effect on psychotic symptoms, as well as the recovery of metabolic flexibility and resolution of low-level inflammation. However, 5.1 years of AP treatment resulted in weight gain and increased serum levels of interleukin (IL)-2, IL-4, IL-6, IL-10, interferon-γ, hexoses, acetylcarnitine, short-chain ACs (C3, C4) and long-chain ACs (C16:2, C18:1, C18:2). In conclusion, despite the improvement in psychotic symptoms, 5.1 years of AP treatment was accompanied by a pronounced metabolic-inflammatory imbalance, which was confirmed by the presence of enhanced pro-inflammatory activity and increased obesity with changes in the metabolism of carbohydrates, lipids, and their metabolites.

Effects of Taurine in Mice and Zebrafish Behavioral Assays With Translational Relevance to Schizophrenia

BACKGROUND

Altered redox state and developmental abnormalities in glutamatergic and GABAergic transmission during development are linked to the behavioral changes associated with schizophrenia. As an amino acid that exerts antioxidant and inhibitory actions in the brain, taurine is a potential candidate to modulate biological targets relevant to this disorder. Here, we investigated in mice and zebrafish assays whether taurine prevents the behavioral changes induced by acute administration of MK-801 (dizocilpine), a glutamate N-methyl-D-aspartate (NMDA) receptor antagonist.

METHODS

C57BL/6 mice were i.p. administered with saline or taurine (50, 100, and 200 mg/kg) followed by MK-801 (0.15 mg/kg). Locomotor activity, social interaction, and prepulse inhibition of the acoustic startle reflex were then assessed in different sets of animals. Zebrafish were exposed to tank water or taurine (42, 150, and 400 mg/L) followed by MK-801 (5 µM); social preference and locomotor activity were evaluated in the same test.

RESULTS

MK-801 induced hyperlocomotion and disrupted sensorimotor gating in mice; in zebrafish, it reduced sociability and increased locomotion. Taurine was mostly devoid of effects and did not counteract NMDA antagonism in mice or zebrafish.

DISCUSSION

Contradicting previous clinical and preclinical data, taurine did not show antipsychotic-like effects in the present study. However, it still warrants consideration as a preventive intervention in animal models relevant to the prodromal phase of schizophrenia; further studies are thus necessary to evaluate whether and how taurine might benefit patients.

Differential patterns of cross-reactive antibody response against SARS-CoV-2 spike protein detected for chronically ill and healthy COVID-19 naïve individuals

Immunity to previously encountered viruses can alter response to unrelated pathogens. We reasoned that similar mechanism may also involve SARS-CoV-2 and thereby affect the specificity and the quality of the immune response against the virus. Here, we employed high-throughput next generation phage display method to explore the link between antibody immune response to previously encountered antigens and spike (S) glycoprotein. By profiling the antibody response in COVID-19 naïve individuals with a diverse clinical history (including cardiovascular, neurological, or oncological diseases), we identified 15 highly antigenic epitopes on spike protein that showed cross-reactivity with antigens of seasonal, persistent, latent or chronic infections from common human viruses. We observed varying degrees of cross-reactivity of different viral antigens with S in an epitope-specific manner. The data show that pre-existing SARS-CoV-2 S1 and S2 cross-reactive serum antibody is readily detectable in pre-pandemic cohort. In the severe COVID-19 cases, we found differential antibody response to the 15 defined antigenic and cross-reactive epitopes on spike. We also noted that despite the high mutation rates of Omicron (B.1.1.529) variants of SARS-CoV-2, some of the epitopes overlapped with the described mutations. Finally, we propose that the resolved epitopes on spike if targeted by re-called antibody response from SARS-CoV-2 infections or vaccinations can function in chronically ill COVID-19 naïve/unvaccinated individuals as immunogenic targets to boost antibodies augmenting the chronic conditions. Understanding the relationships between prior antigen exposure at the antibody epitope level and the immune response to subsequent infections with viruses from a different strain is paramount to guiding strategies to exit the COVID-19 pandemic.

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

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

Interactions between dopamine transporter and N-methyl-d-aspartate receptor-related amino acids on cognitive impairments in schizophrenia

BACKGROUND

Cognitive impairments, the main determinants of functional outcomes in schizophrenia, had limited treatment responses and need a better understanding of the mechanisms. Dysfunctions of the dopamine system and N-methyl-d-aspartate receptor (NMDAR), the primary pathophysiologies of schizophrenia, may impair cognition. This study explored the effects and interactions of striatal dopamine transporter (DAT) and plasma NMDAR-related amino acids on cognitive impairments in schizophrenia.

METHODS

We recruited 36 schizophrenia patients and 36 age- and sex-matched healthy controls (HC). All participants underwent cognitive assessments of attention, memory, and executive function. Single-photon emission computed tomography with 99mTc-TRODAT and ultra-performance liquid chromatography were applied to determine DAT availability and plasma concentrations of eight amino acids, respectively.

RESULTS

Compared with HC, schizophrenia patients had lower cognitive performance, higher methionine concentrations, decreased concentrations of glutamic acid, cysteine, aspartic acid, arginine, the ratio of glutamic acid to gamma-aminobutyric acid (Glu/GABA), and DAT availability in the left caudate nucleus (CN) and putamen. Regarding memory scores, Glu/GABA and the DAT availability in left CN and putamen exhibited positive relationships, while methionine concentrations showed negative associations in all participants. The DAT availability in left CN mediated the methionine-memory relationship. An exploratory backward stepwise regression analysis for the four biological markers associated with memory indicated that DAT availability in left CN and Glu/GABA remained in the final model.

CONCLUSIONS

This study demonstrated the interactions of striatal DAT and NMDAR-related amino acids on cognitive impairments in schizophrenia. Future studies to comprehensively evaluate their complex interactions and treatment implications are warranted.

Markers of Schizophrenia—A Critical Narrative Update

Schizophrenia is a long-term mental disease, associated with functional impairment. Therefore, it is important to make an accurate diagnosis and implement the proper treatment. Biomarkers may be a potential tool for these purposes. Regarding advances in biomarker studies in psychosis, the current symptom-based criteria seem to be no longer sufficient in clinical settings. This narrative review describes biomarkers of psychosis focusing on the biochemical (peripheral and central), neurophysiological, neuropsychological and neuroimaging findings as well as the multimodal approach related with them. Endophenotype markers (especially neuropsychological and occulomotor disturbances) can be currently used in a clinical settings, whereas neuroimaging glutamate/glutamine and D2/D3 receptor density changes, as well as immunological Th2 and PRL levels, seem to be potential biomarkers that need further accuracy tests. When searching for biochemical/immunological markers in the diagnosis of psychosis, the appropriate time of body fluid collection needs to be considered to minimize the influence of the stress axis on their concentrations. In schizophrenia diagnostics, a multimodal approach seems to be highly recommended.

Multi-Omics Analysis Reveals Aberrant Gut-Metabolome-Immune Network in Schizophrenia

Schizophrenia (SCZ) is associated with several immune dysfunctions, including elevated levels of pro-inflammatory cytokines. Microorganisms and their metabolites have been found to regulate the immune system, and that intestinal microbiota is significantly disturbed in schizophrenic patients. To systematically investigate aberrant gut-metabolome-immune network in schizophrenia, we performed an integrative analysis of intestinal microbiota, serum metabolome, and serum inflammatory cytokines in 63 SCZ patients and 57 healthy controls using a multi-omics strategy. Eighteen differentially abundant metabolite clusters were altered in patients displayed higher cytokine levels, with a significant increase in pro-inflammatory metabolites and a significant decrease in anti-inflammatory metabolites (such as oleic acid and linolenic acid). The bacterial co-abundance groups in the gut displayed more numerous and stronger correlations with circulating metabolites than with cytokines. By integrating these data, we identified that certain bacteria might affect inflammatory cytokines by modulating host metabolites, such as amino acids and fatty acids. A random forest model was constructed based on omics data, and seven serum metabolites significantly associated with cytokines and α-diversity of intestinal microbiota were able to accurately distinguish the cases from the controls with an area under the receiver operating characteristic curve of 0.99. Our results indicated aberrant gut-metabolome-immune network in SCZ and gut microbiota may influence immune responses by regulating host metabolic processes. These findings suggest a mechanism by which microbial-derived metabolites regulated inflammatory cytokines and insights into the diagnosis and treatment of mental disorders from the microbial-immune system in the future.

Multi-Omics Characterization of Early- and Adult-Onset Major Depressive Disorder

Age at depressive onset (AAO) corresponds to unique symptomatology and clinical outcomes. Integration of genome-wide association study (GWAS) results with additional “omic” measures to evaluate AAO has not been reported and may reveal novel markers of susceptibility and/or resistance to major depressive disorder (MDD). To address this gap, we integrated genomics with metabolomics using data-driven network analysis to characterize and differentiate MDD based on AAO. This study first performed two GWAS for AAO as a continuous trait in (a) 486 adults from the Pharmacogenomic Research Network-Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS), and (b) 295 adults from the Combining Medications to Enhance Depression Outcomes (CO-MED) study. Variants from top signals were integrated with 153 p180-assayed metabolites to establish multi-omics network characterizations of early (<age 18) and adult-onset depression. The most significant variant (p = 8.77 × 10−8) localized to an intron of SAMD3. In silico functional annotation of top signals (p < 1 × 10−5) demonstrated gene expression enrichment in the brain and during embryonic development. Network analysis identified differential associations between four variants (in/near INTU, FAT1, CNTN6, and TM9SF2) and plasma metabolites (phosphatidylcholines, carnitines, biogenic amines, and amino acids) in early- compared with adult-onset MDD. Multi-omics integration identified differential biosignatures of early- and adult-onset MDD. These biosignatures call for future studies to follow participants from childhood through adulthood and collect repeated -omics and neuroimaging measures to validate and deeply characterize the biomarkers of susceptibility and/or resistance to MDD development.

The Expanded Endocannabinoid System Contributes to Metabolic and Body Mass Shifts in First-Episode Schizophrenia: A 5-Year Follow-Up Study

Alterations in the expanded endocannabinoid system (eECS) and cell membrane composition have been implicated in the pathophysiology of schizophrenia spectrum disorders. We enrolled 54 antipsychotic (AP)-naïve first-episode psychosis (FEP) patients and 58 controls and applied a targeted metabolomics approach followed by multivariate data analysis to investigate the profile changes in the serum levels of endocannabinoids: 2-arachidonoylglycerol (2-AG) and anandamide, endocannabinoids-like N-acylethanolamines (NAEs: linoleoylethanolamide, oleoylethanolamide, and palmitoylethanolamide), and their dominating lipid precursor’s phosphatidylcholines. Biomolecule profiles were measured at the onset of first-episode psychosis (FEP) and 0.6 years and 5.1 years after the initiation of AP treatment. The results indicated that FEP might be characterized by elevated concentrations of NAEs and by decreased 2-AG levels. At this stage of the disease, the NAE-mediated upregulation of peroxisome proliferator-activated receptors (PPARs) manifested themselves in energy expenditure. A 5-year disease progression and AP treatment adverse effects led to a robust increase in 2-AG levels, which contributed to strengthened cannabinoid (CB1) receptor-mediated effects, which manifested in obesity. Dynamic 2-AG, NAEs, and their precursors in terms of phosphatidylcholines are relevant to the description of the metabolic shifts resulting from the altered eECS function during and after FEP.

A High-Methionine Diet for One-Week Induces a High Accumulation of Methionine in the Cerebrospinal Fluid and Confers Bipolar Disorder-like Behavior in Mice

Methionine (Met) is considered the most toxic amino acid in mammals. Here, we investigated biochemical and behavioral impacts of ad libitum one-week feeding of high-Met diets on mice. Adult male mice were fed the standard rodent diet that contained 0.44% Met (1×) or a diet containing 16 graded Met doses (1.2×–13×). High-Met diets for one-week induced a dose-dependent decrease in body weight and an increase in serum Met levels with a 2.55 mM peak (versus basal 53 µM) on the 12×Met diet. Total homocysteine (Hcy) levels were also upregulated while concentrations of other amino acids were almost maintained in serum. Similarly, levels of Met and Hcy (but not the other amino acids) were highly elevated in the cerebrospinal fluids of mice on the 10×Met diet; the Met levels were much higher than Hcy and the others. In a series of behavioral tests, mice on the 10×Met diet displayed increased anxiety and decreased traveled distances in an open-field test, increased activity to escape from water soaking and tail hanging, and normal learning/memory activity in a Y-maze test, which were reflections of negative/positive symptoms and normal cognitive function, respectively. These results indicate that high-Met ad libitum feeding even for a week can induce bipolar disorder-like disease models in mice.

Plasma metabolic alterations and potential biomarkers in individuals at clinical high risk for psychosis

BACKGROUND

Early identification and treatment of clinical high-risk for psychosis (CHRP) are critical to prevent the onset of psychosis, but there is no objective biomarker for CHR-P diagnosis.

METHODS

Ninety medication naïve CHR-P subjects and eighty-six healthy controls (HCs) were recruited. The metabolic profiles of plasma samples were acquired using an untargeted metabolomics approach based on ultra-high-performance liquid chromatography equipped with quadrupole time-of-flight mass spectrometry. The obtained data were further mapped on the Kyoto Encyclopedia of Genes and Genomes for pathway analysis, and an ensemble learning method was applied to identify diagnostic biomarkers. Bayesian linear regression model was then used to explore predicative biomarkers of conversion to psychosis. Receiver-operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic or predicative value of potential biomarkers.

RESULTS

A total of one hundred and four differential metabolites and forty-eight differential pathways were identified. A panel of five metabolites was found that could effectively discriminate CHR-P from HCs with area under the ROC curve of 1 in the training set (70% of the samples) and 0.997 in the testing set (30% of the samples). The biosynthesis of unsaturated fatty acids pathway perturbed most significantly in CHR-P subjects. Twenty-three CHR-P subjects converted to psychotic disorders during two-year follow-up, and increased 1-stearoyl-2-arachidonoyl-sn-glycerol in plasma was potentially associated with the higher risk of conversion to psychosis.

CONCLUSIONS

These findings demonstrate the alterations of plasma metabolic profiles in CHR-P population, which may deliver valuable biomarkers for early identification and outcome prediction of CHR-P.

An integrated pathological research for precise diagnosis of schizophrenia combining LC-MS/1H NMR metabolomics and transcriptomics

BACKGROUND

Lack of clinically specific biomarkers has impeded the precise diagnosis of schizophrenia, meanwhile, limited comprehending of pathogenesis for schizophrenia has restricted the effective treatment.

METHOD

An integrated multi-omic approach, combining metabolomic platform (LC-MS and ¹H NMR) and transcriptomic platform, was established to differentiate healthy subjects from schizophrenia patients. Based on filtered metabolites and genes, characteristic spectrums were further built. Then, representative metabolites and genes were screened out through Boruta algorithm. Moreover, characteristic diagnostic formulas were established via LASSO regression analysis.

RESULT

As a result, 86 differential metabolites (in line with amino acid metabolism, etc.) and 189 differential expression genes (involving in amino acid metabolic process, etc.) were obtained as potential biomarkers for schizophrenia. The latent interaction between metabolites with genes, such as HMGCLL1 with energy metabolism, etc., was further studied through the analysis of pathway-based integration. Moreover, fine predictive ability was attributed to characteristic metabolomic/transcriptomic diagnostic spectrums/formulas.

CONCLUSION

The functional relationships of filtered metabolites and genes were studied, which could elaborate the pathological process of schizophrenia more systemically, supplying more precise information on mechanism description and diagnostic evidence of schizophrenia.

Crossroad between current knowledge and new perspective of diagnostic and therapy of late-onset schizophrenia and very late-onset schizophrenia-like psychosis: An update

Schizophrenia is a chronic, highly individualized disease with many symptoms that can occur with varying severity in different patients. Schizophrenia affects 1% of the population, but occurs in almost 20% of patients after 40 years of age. It should be noted that the next peak in the incidence of schizophrenia occurs at the age of 60 years, affects mostly females, and is closely associated with a high risk of developing memory disorders. Therefore, postadolescent schizophrenia includes two distinct groups of patients: those whose symptoms onset at the age of 45 or 60. The purposes of this literature review were as follows: (1) synthetically characterize the clinical manifestations of schizophrenia; (2) discuss difficulties in the diagnosis of schizophrenia, especially in patients over 40 years of age; (3) discuss the clinical utility of different classes of marker in diagnostic and differentiating schizophrenia from neurodegenerative diseases in elderly people; (4) discuss therapeutic options for schizophrenia, pharmacotherapy, and psychotherapy, emphasizing the role of caregivers of people with psychosis in therapy, in preadolescence and postadolescence schizophrenia. We have tried to primarily discuss the findings of original articles from the last 10 years with an indication of their clinical implications with the issues discussed in the various subsections. Moreover, despite many years of research, no specific, precise algorithm has been developed that can be used in clinical practice during the diagnosis of schizophrenia. For this reason, the diagnosis of schizophrenia is primarily based on an interview with the patient and his family, as well as on the experience of a psychiatrist. It also seems that schizophrenia treatment should be carried out holistically, including pharmacotherapy, psychotherapy, and the support of caregivers of patients who have this psychosis, which increases the achievement of therapeutic success. Finally, we must be aware of the difficulties in diagnosing schizophrenia in the elderly and the need to modify pharmacological treatment. Currently, no guidelines have been developed for the differentiation of negative symptoms in elderly patients with schizophrenia from amotivation/avolition/apathy symptoms in elderly patients with neurodegenerative disorders.

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.

In this study, we analyzed 378 metabolites in the serum of schizophrenia patients using CE and LC‐TOFMS. With a systematic review, here we provide substantial evidence for metabolic biomarkers in schizophrenia patients through our metabolomics study.

Peripheral Blood-Based Gene Expression Studies in Schizophrenia: A Systematic Review

Schizophrenia is a disorder that is characterized by delusions, hallucinations, disorganized speech or behavior, and socio-occupational impairment. The duration of observation and variability in symptoms can make the accurate diagnosis difficult. Identification of biomarkers for schizophrenia (SCZ) can help in early diagnosis, ascertaining the diagnosis, and development of effective treatment strategies. Here we review peripheral blood-based gene expression studies for identification of gene expression biomarkers for SCZ. A literature search was carried out in PubMed and Web of Science databases for blood-based gene expression studies in SCZ. A list of differentially expressed genes (DEGs) was compiled and analyzed for overlap with genetic markers, differences based on drug status of the participants, functional enrichment, and for effect of antipsychotics. This literature survey identified 61 gene expression studies. Seventeen out of these studies were based on expression microarrays. A comparative analysis of the DEGs (n = 227) from microarray studies revealed differences between drug-naive and drug-treated SCZ participants. We found that of the 227 DEGs, 11 genes (ACOT7, AGO2, DISC1, LDB1, RUNX3, SIGIRR, SLC18A1, NRG1, CHRNB2, PRKAB2, and ZNF74) also showed genetic and epigenetic changes associated with SCZ. Functional enrichment analysis of the DEGs revealed dysregulation of proline and 4-hydroxyproline metabolism. Also, arginine and proline metabolism was the most functionally enriched pathway for SCZ in our analysis. Follow-up studies identified effect of antipsychotic treatment on peripheral blood gene expression. Of the 27 genes compiled from the follow-up studies AKT1, DISC1, HP, and EIF2D had no effect on their expression status as a result of antipsychotic treatment. Despite the differences in the nature of the study, ethnicity of the population, and the gene expression analysis method used, we identified several coherent observations. An overlap, though limited, of genetic, epigenetic and gene expression changes supports interplay of genetic and environmental factors in SCZ. The studies validate the use of blood as a surrogate tissue for biomarker analysis. We conclude that well-designed cohort studies across diverse populations, use of high-throughput sequencing technology, and use of artificial intelligence (AI) based computational analysis will significantly improve our understanding and diagnostic capabilities for this complex disorder.

Evaluation of the Differences in the Expression of Biogenic Amine-Related mRNAs and Proteins in Endometrioid Endometrial Cancer

Biogenic amines, such as adrenaline, noradrenaline, histamine, dopamine, and serotonin are important neurotransmitters that also regulate cell viability. Their detection and analysis are helpful in the diagnosis of many diseases, including cancer. The aim of this study was to determine the expression profile of the biogenic amine-related genes and proteins in endometrioid endometrial cancer compared to the control group. The material consisted of endometrial tissue samples and whole blood collected from 30 endometrioid endometrial cancer patients and 30 cancer-free patients. The gene expression was determined by the mRNA microarrays and validated by qRT-PCR. Protein levels were determined in the serum by the enzyme-linked immunosorbent assay (ELISA). Overexpression of histamine H1–H3 receptors and early growth response 1 and silencing of calmodulin, the histamine H4 receptor, and the dopamine D5 receptor have been reported in endometrioid endometrial cancer. The obtained results indicate disturbances in the signaling activated by histamine and dopamine receptors, which could potentially contribute to the progression of endometrioid endometrial cancer.

Metabolomic connections between schizophrenia, antipsychotic drugs and metabolic syndrome: A variety of players

BACKGROUND

Diagnosis of schizophrenia lacks of reliable medical diagnostic tests and robust biomarkers applied to clinical practice. Schizophrenic patients undergoing treatment with antipsychotics suffer a reduced life expectancy due to metabolic disarrangements that co-exist with their mental illness and predispose them to develop metabolic syndrome, also exacerbated by medication. Metabolomics is an emerging and potent technology able to accelerate this biomedical research. <P> Aim: This review focus on a detailed vision of the molecular mechanisms involved both in schizophrenia and antipsychotic-induced metabolic syndrome, based on innovative metabolites that consistently change in nascent metabolic syndrome, drug-naïve, first episode psychosis and/or schizophrenic patients compared to healthy subjects. <P> Main lines: Supported by metabolomic approaches, although not exclusively, noteworthy variations are reported mainly through serum samples of patients and controls in several scenes: 1) alterations in fatty acids, inflammatory response indicators, amino acids and biogenic amines, biometals and gut microbiota metabolites (schizophrenia); 2) alterations in metabolites involved in carbohydrate and gut microbiota metabolism, inflammation and oxidative stress (metabolic syndrome), some of them shared with the schizophrenia scene; 3) alterations of cytokines secreted by adipose tissue, phosphatidylcholines, acylcarnitines, Sirtuin 1, orexin-A and changes in microbiota composition (antipsychotic-induced metabolic syndrome). <P> Conclusion: Novel insights into the pathogenesis of schizophrenia and metabolic side-effects associated to its antipsychotic treatment, represent an urgent request for scientifics and clinicians. Leptin, carnitines, adiponectin, insulin or interleukin-6 represent some examples of candidate biomarkers. Cutting-edge technologies like metabolomics have the power of strengthen research for achieving preventive, diagnostic and therapeutical solutions for schizophrenia.

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.

A Metabolomics Study of Serum in Hospitalized Patients With Chronic Schizophrenia

Purpose: Metabolomics has attracted attention as a new method for understanding the molecular mechanisms of psychiatric disorders. Current metabolomics technology allows us to measure over hundreds of metabolites at a time and is a useful indicator of the consequences of complex and continuous changes in metabolic profiles due to the execution of genomic information and external factors of biological activity. Therefore, metabolomics is imperative to the discovery of biomarkers and mechanisms associated with pathophysiological processes. In this study, we investigated metabolites changes in hospitalized patients with chronic schizophrenia compared to that in healthy controls, and examined the correlations between the metabolites and psychiatric symptoms. Patients and Methods: Thirty patients with schizophrenia and ten healthy controls participated in this study between September 2019 and June 2020. The mean duration of disease in patients with schizophrenia was 26 years. Clinical and neuropsychiatric symptoms of patients with schizophrenia were assessed using the Positive and Negative Syndrome Scale (PANSS). Metabolomics was conducted using Capillary Electrophoresis Fourier Transform Mass Spectrometry (CE-FTMS), using serum samples from patients with schizophrenia and healthy controls. Metabolomics assigned a candidate compound to the 446 (cation 279, anion 167) peaks. Hierarchical cluster analysis (HCA), principal component analysis (PCA), logistic regression analysis, receiver operating characteristic (ROC) analysis, and linear regression analysis were used to analyze the metabolites changes, identifying the disease and the relationship between metabolites and psychiatric symptoms. Results: HCA showed that approximately 60% of metabolites had lower peak values in patients with schizophrenia than in healthy controls. Glutamate metabolism and the urea cycle had the highest proportions in the metabolic pathway, which decreased in patients with schizophrenia. PCA showed a clear separation between patients with schizophrenia and healthy controls in the first principal component (the contribution ratio of the first principal component was 15.9%). Logistic regression analysis suggested that the first principal component was a predictor of disease (odds = 1.36, 95%CI = 1.11-1.67, p = 0.0032). ROC analysis showed a sensitivity of 93% and a specificity of 100% for the diagnosis of schizophrenia with a cut-off value of the first principal component; -3.33 (AUC = 0.95). We extracted the high factor loading for the first principal component. Gamma-glutamyl-valine (γ-Glu-Val) was significantly negatively correlated with PANSS total scores (r = -0.45, p = 0.012) and PANSS general scores (r = -0.49, p = 0.0055). Gamma-glutamyl-phenylalanine (γ-Glu-Phe) was significantly negatively correlated with PANSS total score (r = -0.40, p = 0.031) and PANSS general score (r = -0.41, p = 0.025). Tetrahydrouridine was significantly positively correlated with PANSS negative scores (r = 0.53, p = 0.0061). Conclusion: Metabolites changes in hospitalized patients with chronic schizophrenia showed extensive and generalized declines. Glutamate metabolism and the urea cycle had the highest proportions in the metabolic pathway, which decreased in the schizophrenia group. Metabolomic analysis was useful to identify chronic schizophrenia. Some glutamate compound metabolites had a relationship with psychiatric symptoms.

Plasma amino acids profile in first-episode psychosis, unaffected siblings and community-based controls

Investigations of plasma amino acids in early psychosis and their unaffected siblings are rare. We measured plasma amino acids involved in the co-activation of dopaminergic, GABAergic, glutamatergic, and serotoninergic neurotransmitters in first-episode psychosis (FEP) patients (n = 166), unaffected siblings (n = 76), and community-based controls (n = 166) included in a cross-sectional study. Plasma levels of glutamic acid (GLU), glutamine, glycine, proline (PRO), tryptophan (TRP), tyrosine, serine and GABA were quantified by gas-chromatography-mass spectrometry. We used the generalized linear model adjusted by sex, age, and body mass index for group comparison and paired t-test for FEP-Sibling pairs. FEP had reduced GABA plasma levels compared to siblings and controls (p < 0.05 for both). Siblings had lower GLU, Glx and PRO (p < 0.05 for all) but increased TRP compared to patients and controls (p < 0.05 for both). FEP patients with longer duration of pharmacological treatment and medicated only with antipsychotics had increased GLU compared to FEP with shorter periods, or with those treated with a combination of medications (p < 0.05 for both). Finally, FEP patients treated only with antipsychotics presented higher Glx compared to those with mixed medications (p = 0.026). Our study suggests that FEP have low a GABA plasma profile. Unaffected siblings may be a possible risk group for metabolic abnormalities.