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Foong YH, Caldwell B, Thorvaldsen JL, Krapp C, Mesaros CA, Zhou W, Kohli RM, Bartolomei MS. TET1 displays catalytic and non-catalytic functions in the adult mouse cortex. Epigenetics 2024; 19:2374979. [PMID: 38970823 PMCID: PMC11229741 DOI: 10.1080/15592294.2024.2374979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 06/26/2024] [Indexed: 07/08/2024] Open
Abstract
TET1/2/3 dioxygenases iteratively demethylate 5-methylcytosine, beginning with the formation of 5-hydroxymethylcytosine (5hmC). The post-mitotic brain maintains higher levels of 5hmC than most peripheral tissues, and TET1 ablation studies have underscored the critical role of TET1 in brain physiology. However, deletion of Tet1 precludes the disentangling of the catalytic and non-catalytic functions of TET1. Here, we dissect these functions of TET1 by comparing adult cortex of Tet1 wildtype (Tet1 WT), a novel Tet1 catalytically dead mutant (Tet1 HxD), and Tet1 knockout (Tet1 KO) mice. Using DNA methylation array, we uncover that Tet1 HxD and KO mutations perturb the methylation status of distinct subsets of CpG sites. Gene ontology (GO) analysis on specific differential 5hmC regions indicates that TET1's catalytic activity is linked to neuronal-specific functions. RNA-Seq further shows that Tet1 mutations predominantly impact the genes that are associated with alternative splicing. Lastly, we performed High-performance Liquid Chromatography Mass-Spectrometry lipidomics on WT and mutant cortices and uncover accumulation of lysophospholipids lysophosphatidylethanolamine and lysophosphatidylcholine in Tet1 HxD cortex. In summary, we show that Tet1 HxD does not completely phenocopy Tet1 KO, providing evidence that TET1 modulates distinct cortical functions through its catalytic and non-catalytic roles.
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Affiliation(s)
- Yee Hoon Foong
- Department of Cell and Developmental Biology, Perelman School of Medicine, Smilow Center for Translational Research, Philadelphia, PA, USA
| | - Blake Caldwell
- Department of Cell and Developmental Biology, Perelman School of Medicine, Smilow Center for Translational Research, Philadelphia, PA, USA
- Department of Biological Sciences, Virginia Tech, Blacksburg, Virginia, USA
| | - Joanne L. Thorvaldsen
- Department of Cell and Developmental Biology, Perelman School of Medicine, Smilow Center for Translational Research, Philadelphia, PA, USA
| | - Christopher Krapp
- Department of Cell and Developmental Biology, Perelman School of Medicine, Smilow Center for Translational Research, Philadelphia, PA, USA
| | - Clementina A. Mesaros
- Translational Biomarkers Core, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center of Excellence in Environmental Toxicology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Wanding Zhou
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Children’s Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA, USA
- Penn Epigenetics Institute, Smilow Center for Translational Rsearch, Philadelphia, PA, USA
| | - Rahul M. Kohli
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Epigenetics Institute, Smilow Center for Translational Rsearch, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Marisa S. Bartolomei
- Department of Cell and Developmental Biology, Perelman School of Medicine, Smilow Center for Translational Research, Philadelphia, PA, USA
- Penn Epigenetics Institute, Smilow Center for Translational Rsearch, Philadelphia, PA, USA
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Jieu B, Sykorova EB, Rohleder C, Marcolini E, Hoffmann AE, Koethe D, Leweke FM, Couttas TA. Alterations to sphingolipid metabolism from antipsychotic administration in healthy volunteers are restored following the use of cannabidiol. Psychiatry Res 2024; 339:116005. [PMID: 38950483 DOI: 10.1016/j.psychres.2024.116005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 05/06/2024] [Accepted: 06/01/2024] [Indexed: 07/03/2024]
Abstract
Randomized clinical trials substantiate cannabidiol (CBD) as a next-generation antipsychotic, effective in alleviating positive and negative symptoms associated with psychosis, while minimising the adverse effects seen with established treatments. Although the mechanisms remain debated, CBD is known to induce drug-responsive changes in lipid-based retrograde neurotransmitters. Lipid aberrations are also frequently observed with antipsychotics, which may contribute to their efficacy or increase the risk of undesirables, including metabolic dysfunction, obesity and dyslipidaemia. Our study investigated CBD's impact following lipid responses triggered by interaction with second-generation antipsychotics (SGA) in a randomized phase I safety study. Untargeted mass spectrometry assessed the lipidomic profiles of human sera, collected from 38 healthy volunteers. Serum samples were obtained prior to commencement of any medication (t = 0), 3 days after consecutive administration of one of the five, placebo-controlled, treatment arms designed to achieve steady-state concentrations of each SGA (amisulpride, 150 mg/day; quetiapine, 300 mg/day; olanzapine 10 mg/day; risperidone, 3 mg/day), and after six successive days of SGA treatment combined with CBD (800 mg/day). Receiver operating characteristics (ROC) refined 3712 features to a putative list of 15 lipids significantly altered (AUC > 0.7), classified into sphingolipids (53 %), glycerolipids (27 %) and glycerophospholipids (20 %). Targeted mass spectrometry confirmed reduced sphingomyelin and ceramide levels with antipsychotics, which mapped along their catabolic pathway and were restored by CBD. These sphingolipids inversely correlated with body weight after olanzapine, quetiapine, and risperidone treatment, where CBD appears to have arrested or attenuated these effects. Herein, we propose CBD may alleviate aberrant sphingolipid metabolism and that further investigation into sphingolipids as markers for monitoring side effects of SGAs and efficacy of CBD is warranted.
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Affiliation(s)
- Beverly Jieu
- Brain and Mind Centre, The University of Sydney, Sydney, Australia
| | - Eliska B Sykorova
- Dept. of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Cathrin Rohleder
- Brain and Mind Centre, The University of Sydney, Sydney, Australia; Dept. of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany; Endosane Pharmaceuticals GmbH, Berlin, Germany
| | - Elisabeth Marcolini
- Dept. of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Anna E Hoffmann
- Brain and Mind Centre, The University of Sydney, Sydney, Australia
| | - Dagmar Koethe
- Brain and Mind Centre, The University of Sydney, Sydney, Australia; Dept. of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - F Markus Leweke
- Brain and Mind Centre, The University of Sydney, Sydney, Australia; Dept. of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany; Endosane Pharmaceuticals GmbH, Berlin, Germany
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Liu Y, Lin H, Liu M, Lin L, Wen Y. Establishment of a Mitochondrial Metabolism-Related Diagnostic Model in Schizophrenia Based on LASSO Algorithm. Psychiatry Investig 2024; 21:618-628. [PMID: 38960439 PMCID: PMC11222072 DOI: 10.30773/pi.2024.0011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 03/18/2024] [Accepted: 03/25/2024] [Indexed: 07/05/2024] Open
Abstract
OBJECTIVE Schizophrenia is a common mental disorder, and mitochondrial function represents a potential therapeutic target for psychiatric diseases. The role of mitochondrial metabolism-related genes (MRGs) in the diagnosis of schizophrenia remains unknown. This study aimed to identify candidate genes that may influence the diagnosis and treatment of schizophrenia based on MRGs. METHODS Three schizophrenia datasets were obtained from the Gene Expression Omnibus database. MRGs were collected from relevant literature. The differentially expressed genes between normal samples and schizophrenia samples were screened using the limma package. Venn analysis was performed to identify differentially expressed MRGs (DEMRGs) in schizophrenia. Based on the STRING database, hub genes in DEMRGs were identified using the MCODE algorithm in Cytoscape. A diagnostic model containing hub genes was constructed using LASSO regression and logistic regression analysis. The relationship between hub genes and drug sensitivity was explored using the DSigDB database. An interaction network between miRNA-transcription factor (TF)-hub genes was created using the Network-Analyst website. RESULTS A total of 1,234 MRGs, 172 DEMRGs, and 6 hub genes with good diagnostic performance were identified. Ten potential candidate drugs (rifampicin, fulvestrant, pentadecafluorooctanoic acid, etc.) were selected. Thirty-four miRNAs targeting genes in the diagnostic model (ANGPTL4, CPT2, GLUD1, MED1, and MED20), as well as 137 TFs, were identified. CONCLUSION Six potential candidate genes showed promising diagnostic significance. rifampicin, fulvestrant, and pentadecafluorooctanoic acid were potential drugs for future research in the treatment of schizophrenia. These findings provided valuable evidence for the understanding of schizophrenia pathogenesis, diagnosis, and drug treatment.
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Affiliation(s)
- Yinfang Liu
- Department of Pharmacy, The Third Hospital of Longyan, Longyan, China
| | - Han Lin
- Department of Pharmacy, The Third Hospital of Longyan, Longyan, China
| | - Meicen Liu
- Department of Pharmacy, The First Hospital of Longyan, Longyan, China
| | - Liping Lin
- Department of Pharmacy, The Third Hospital of Longyan, Longyan, China
| | - Yaohui Wen
- Department of Laboratory Medicine, The Third Hospital of Longyan, Longyan, China
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Yan H, Li G, Zhang X, Zhang C, Li M, Qiu Y, Sun W, Dong Y, Li S, Li J. Targeted metabolomics-based understanding of the sleep disturbances in drug-naïve patients with schizophrenia. BMC Psychiatry 2024; 24:355. [PMID: 38741058 DOI: 10.1186/s12888-024-05805-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 04/30/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND Sleep disturbances are a common occurrence in patients with schizophrenia, yet the underlying pathogenesis remain poorly understood. Here, we performed a targeted metabolomics-based approach to explore the potential biological mechanisms contributing to sleep disturbances in schizophrenia. METHODS Plasma samples from 59 drug-naïve patients with schizophrenia and 36 healthy controls were subjected to liquid chromatography-mass spectrometry (LC-MS) targeted metabolomics analysis, allowing for the quantification and profiling of 271 metabolites. Sleep quality and clinical symptoms were assessed using the Pittsburgh Sleep Quality Index (PSQI) and the Positive and Negative Symptom Scale (PANSS), respectively. Partial correlation analysis and orthogonal partial least squares discriminant analysis (OPLS-DA) model were used to identify metabolites specifically associated with sleep disturbances in drug-naïve schizophrenia. RESULTS 16 characteristic metabolites were observed significantly associated with sleep disturbances in drug-naïve patients with schizophrenia. Furthermore, the glycerophospholipid metabolism (Impact: 0.138, p<0.001), the butanoate metabolism (Impact: 0.032, p=0.008), and the sphingolipid metabolism (Impact: 0.270, p=0.104) were identified as metabolic pathways associated with sleep disturbances in drug-naïve patients with schizophrenia. CONCLUSIONS Our study identified 16 characteristic metabolites (mainly lipids) and 3 metabolic pathways related to sleep disturbances in drug-naïve schizophrenia. The detection of these distinct metabolites provide valuable insights into the underlying biological mechanisms associated with sleep disturbances in schizophrenia.
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Affiliation(s)
- Huiming Yan
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
| | - Gang Li
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
- Chifeng Anding Hospital, NO.18 Gongger Street, Hongshan District, Chifeng City, 024000, Inner Mongolia Autonomous Region, China
| | - Xue Zhang
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
- Chifeng Anding Hospital, NO.18 Gongger Street, Hongshan District, Chifeng City, 024000, Inner Mongolia Autonomous Region, China
| | - Chuhao Zhang
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
| | - Meijuan Li
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
| | - Yuying Qiu
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
| | - Wei Sun
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
| | - Yeqing Dong
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
| | - Shen Li
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China.
| | - Jie Li
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China.
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Zhao S, Chen J, Zhong C, Meng L, Wang Y. Nontargeted metabolomic insights into the behavioral effects of 5-MeO-MiPT in zebrafish (Danio rerio). ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 272:116044. [PMID: 38295732 DOI: 10.1016/j.ecoenv.2024.116044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 01/02/2024] [Accepted: 01/27/2024] [Indexed: 02/25/2024]
Abstract
5-Methoxy-N-methyl-N-isopropyltryptamine (5-MeO-MiPT) is a novel psychoactive substance exhibiting a tryptamine structure. Despite its increasing prevalence, the environmental impact of 5-MeO-MiPT remains unexplored. Our prior investigation revealed that 5-MeO-MiPT induced inhibited spontaneous movement and prompted anxiety-like behavior in adult zebrafish-a validated toxicological model. To elucidate this phenomenon and establish a correlation between metabolomics and behavioral changes induced by 5-MeO-MiPT, zebrafish were administered varying drug concentrations. Zebrafishes were subjected to injections of different 5-MeO-MiPT concentrations. Subsequent metabolomic analysis of endogenous metabolites affected by the drug unveiled substantial variations in metabolic levels between the control group and the drug-injected cohorts. A total of 22 distinct metabolites emerged as potential biomarkers. Further scrutiny identified seven pathways significantly influenced by 5-MeO-MiPT. A focused exploration into amino acid metabolism, lipid metabolism, and energy metabolism unveiled that the metabolic repercussions of 5-MeO-MiPT on zebrafish resulted in observable brain damage. Notably, the study identified a consequential disruption in the liver-brain pathway. The comprehensive metabolomic approach employed herein effectively discerned the impact of 5-MeO-MiPT on zebrafish metabolism. This approach also shed light on the mechanism underpinning the anxiety-like behavior observed in zebrafish post-drug injection. Specifically, our findings indicate that 5-MeO-MiPT induces brain damage, particularly within the liver-brain pathway.
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Affiliation(s)
- Sen Zhao
- College of Environment, Zhejiang University of Technology, Hangzhou 310014, PR China; Zhejiang Police College, Key Laboratory of Drug Prevention and Control Technology of Zhejiang Province, Hangzhou 310053, PR China
| | - Jinyuan Chen
- College of Environment, Zhejiang University of Technology, Hangzhou 310014, PR China
| | - Chenhao Zhong
- College of Environment, Zhejiang University of Technology, Hangzhou 310014, PR China
| | - Liang Meng
- Department of Forensic Science, Fujian Police College, Fuzhou 350007, PR China
| | - Yanjiao Wang
- Binjiang Institute of Zhejiang University, Hangzhou, Zhejiang 310053, PR China.
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Zorkina Y, Ushakova V, Ochneva A, Tsurina A, Abramova O, Savenkova V, Goncharova A, Alekseenko I, Morozova I, Riabinina D, Kostyuk G, Morozova A. Lipids in Psychiatric Disorders: Functional and Potential Diagnostic Role as Blood Biomarkers. Metabolites 2024; 14:80. [PMID: 38392971 PMCID: PMC10890164 DOI: 10.3390/metabo14020080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 12/07/2023] [Accepted: 12/19/2023] [Indexed: 02/25/2024] Open
Abstract
Lipids are a crucial component of the human brain, serving important structural and functional roles. They are involved in cell function, myelination of neuronal projections, neurotransmission, neural plasticity, energy metabolism, and neuroinflammation. Despite their significance, the role of lipids in the development of mental disorders has not been well understood. This review focused on the potential use of lipids as blood biomarkers for common mental illnesses, such as major depressive disorder, anxiety disorders, bipolar disorder, and schizophrenia. This review also discussed the impact of commonly used psychiatric medications, such as neuroleptics and antidepressants, on lipid metabolism. The obtained data suggested that lipid biomarkers could be useful for diagnosing psychiatric diseases, but further research is needed to better understand the associations between blood lipids and mental disorders and to identify specific biomarker combinations for each disease.
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Affiliation(s)
- Yana Zorkina
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia
- Department of Basic and Applied Neurobiology, V. Serbsky Federal Medical Research Centre of Psychiatry and Narcology, Kropotkinsky per. 23, 119034 Moscow, Russia
| | - Valeria Ushakova
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia
- Department of Basic and Applied Neurobiology, V. Serbsky Federal Medical Research Centre of Psychiatry and Narcology, Kropotkinsky per. 23, 119034 Moscow, Russia
| | - Aleksandra Ochneva
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia
- Department of Basic and Applied Neurobiology, V. Serbsky Federal Medical Research Centre of Psychiatry and Narcology, Kropotkinsky per. 23, 119034 Moscow, Russia
| | - Anna Tsurina
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia
| | - Olga Abramova
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia
- Department of Basic and Applied Neurobiology, V. Serbsky Federal Medical Research Centre of Psychiatry and Narcology, Kropotkinsky per. 23, 119034 Moscow, Russia
| | - Valeria Savenkova
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia
| | - Anna Goncharova
- Moscow Center for Healthcare Innovations, 123473 Moscow, Russia
| | - Irina Alekseenko
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academi of Science, 142290 Moscow, Russia
- Russia Institute of Molecular Genetics of National Research Centre "Kurchatov Institute", 2, Kurchatov Square, 123182 Moscow, Russia
| | - Irina Morozova
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia
| | - Daria Riabinina
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia
| | - Georgy Kostyuk
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia
| | - Anna Morozova
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia
- Department of Basic and Applied Neurobiology, V. Serbsky Federal Medical Research Centre of Psychiatry and Narcology, Kropotkinsky per. 23, 119034 Moscow, Russia
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7
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Pan LA, Naviaux JC, Wang L, Li K, Monk JM, Lingampelly SS, Segreti AM, Bloom K, Vockley J, Tarnopolsky MA, Finegold DN, Peters DG, Naviaux RK. Metabolic features of treatment-refractory major depressive disorder with suicidal ideation. Transl Psychiatry 2023; 13:393. [PMID: 38097555 PMCID: PMC10721812 DOI: 10.1038/s41398-023-02696-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 10/18/2023] [Accepted: 11/29/2023] [Indexed: 12/17/2023] Open
Abstract
Peripheral blood metabolomics was used to gain chemical insight into the biology of treatment-refractory Major Depressive Disorder with suicidal ideation, and to identify individualized differences for personalized care. The study cohort consisted of 99 patients with treatment-refractory major depressive disorder and suicidal ideation (trMDD-SI n = 52 females and 47 males) and 94 age- and sex-matched healthy controls (n = 48 females and 46 males). The median age was 29 years (IQR 22-42). Targeted, broad-spectrum metabolomics measured 448 metabolites. Fibroblast growth factor 21 (FGF21) and growth differentiation factor 15 (GDF15) were measured as biomarkers of mitochondrial dysfunction. The diagnostic accuracy of plasma metabolomics was over 90% (95%CI: 0.80-1.0) by area under the receiver operator characteristic (AUROC) curve analysis. Over 55% of the metabolic impact in males and 75% in females came from abnormalities in lipids. Modified purines and pyrimidines from tRNA, rRNA, and mRNA turnover were increased in the trMDD-SI group. FGF21 was increased in both males and females. Increased lactate, glutamate, and saccharopine, and decreased cystine provided evidence of reductive stress. Seventy-five percent of the metabolomic abnormalities found were individualized. Personalized deficiencies in CoQ10, flavin adenine dinucleotide (FAD), citrulline, lutein, carnitine, or folate were found. Pathways regulated by mitochondrial function dominated the metabolic signature. Peripheral blood metabolomics identified mitochondrial dysfunction and reductive stress as common denominators in suicidal ideation associated with treatment-refractory major depressive disorder. Individualized metabolic differences were found that may help with personalized management.
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Affiliation(s)
- Lisa A Pan
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
- School of Public Health, Department of Human Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
- Panomics Mental Health Initiative, Pittsburgh, PA, USA.
- New Hope Molecular, LLC, Pittsburgh, PA, USA.
- New Hope Molecular, LLC, 750 Washington Rd, Suite 19, Pittsburgh, PA, 15228, USA.
| | - Jane C Naviaux
- The Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, San Diego, CA, USA
- Department of Neurosciences, University of California, San Diego School of Medicine, San Diego, CA, USA
| | - Lin Wang
- The Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, San Diego, CA, USA
- Department of Medicine, University of California, San Diego School of Medicine, San Diego, CA, USA
| | - Kefeng Li
- The Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, San Diego, CA, USA
- Department of Medicine, University of California, San Diego School of Medicine, San Diego, CA, USA
| | - Jonathan M Monk
- The Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, San Diego, CA, USA
- Department of Medicine, University of California, San Diego School of Medicine, San Diego, CA, USA
| | - Sai Sachin Lingampelly
- The Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, San Diego, CA, USA
- Department of Medicine, University of California, San Diego School of Medicine, San Diego, CA, USA
| | - Anna Maria Segreti
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Kaitlyn Bloom
- Department of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jerry Vockley
- Department of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Mark A Tarnopolsky
- Department of Pediatrics, McMaster University, Hamilton, Ontario, Canada
| | - David N Finegold
- School of Public Health, Department of Human Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Panomics Mental Health Initiative, Pittsburgh, PA, USA
- New Hope Molecular, LLC, Pittsburgh, PA, USA
| | - David G Peters
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- School of Public Health, Department of Human Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Panomics Mental Health Initiative, Pittsburgh, PA, USA
- Department of Obstetrics, Gynecology & Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - Robert K Naviaux
- The Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, San Diego, CA, USA.
- Department of Medicine, University of California, San Diego School of Medicine, San Diego, CA, USA.
- Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, CA, USA.
- Department of Pathology, University of California, San Diego School of Medicine, San Diego, CA, USA.
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8
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Theriault JE, Shaffer C, Dienel GA, Sander CY, Hooker JM, Dickerson BC, Barrett LF, Quigley KS. A functional account of stimulation-based aerobic glycolysis and its role in interpreting BOLD signal intensity increases in neuroimaging experiments. Neurosci Biobehav Rev 2023; 153:105373. [PMID: 37634556 PMCID: PMC10591873 DOI: 10.1016/j.neubiorev.2023.105373] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 07/28/2023] [Accepted: 08/23/2023] [Indexed: 08/29/2023]
Abstract
In aerobic glycolysis, oxygen is abundant, and yet cells metabolize glucose without using it, decreasing their ATP per glucose yield by 15-fold. During task-based stimulation, aerobic glycolysis occurs in localized brain regions, presenting a puzzle: why produce ATP inefficiently when, all else being equal, evolution should favor the efficient use of metabolic resources? The answer is that all else is not equal. We propose that a tradeoff exists between efficient ATP production and the efficiency with which ATP is spent to transmit information. Aerobic glycolysis, despite yielding little ATP per glucose, may support neuronal signaling in thin (< 0.5 µm), information-efficient axons. We call this the efficiency tradeoff hypothesis. This tradeoff has potential implications for interpretations of task-related BOLD "activation" observed in fMRI. We hypothesize that BOLD "activation" may index local increases in aerobic glycolysis, which support signaling in thin axons carrying "bottom-up" information, or "prediction error"-i.e., the BIAPEM (BOLD increases approximate prediction error metabolism) hypothesis. Finally, we explore implications of our hypotheses for human brain evolution, social behavior, and mental disorders.
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Affiliation(s)
- Jordan E Theriault
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
| | - Clare Shaffer
- Northeastern University, Department of Psychology, Boston, MA, USA
| | - Gerald A Dienel
- Department of Neurology, University of Arkansas for Medical Sciences, Little Rock, AR, USA; Department of Cell Biology and Physiology, University of New Mexico, Albuquerque, NM, USA
| | - Christin Y Sander
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Jacob M Hooker
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Bradford C Dickerson
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA; Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Lisa Feldman Barrett
- Northeastern University, Department of Psychology, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Karen S Quigley
- Northeastern University, Department of Psychology, Boston, MA, USA; VA Bedford Healthcare System, Bedford, MA, USA
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Su Q, Bi F, Yang S, Yan H, Sun X, Wang J, Qiu Y, Li M, Li S, Li J. Identification of Plasma Biomarkers in Drug-Naïve Schizophrenia Using Targeted Metabolomics. Psychiatry Investig 2023; 20:818-825. [PMID: 37794663 PMCID: PMC10555515 DOI: 10.30773/pi.2023.0121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 06/05/2023] [Accepted: 06/14/2023] [Indexed: 10/06/2023] Open
Abstract
OBJECTIVE Schizophrenia (SCZ) is a severe psychiatric disorder with unknown etiology and lacking specific biomarkers. Herein, we aimed to explore plasma biomarkers relevant to SCZ using targeted metabolomics. METHODS Sixty drug-naïve SCZ patients and 36 healthy controls were recruited. Psychotic symptoms were assessed using the Positive and Negative Syndrome Scale. We analyzed the levels of 271 metabolites in plasma samples from all subjects using targeted metabolomics, and identified metabolites that differed significantly between the two groups. Then we evaluated the diagnostic power of the metabolites based on receiver operating characteristic curves, and explored metabolites associated with the psychotic symptoms in SCZ patients. RESULTS Twenty-six metabolites showed significant differences between SCZ patients and healthy controls. Among them, 12 metabolites were phosphatidylcholines and cortisol, ceramide (d18:1/22:0), acetylcarnitine, and γ-aminobutyric acid, which could significantly distinguish SCZ from healthy controls with the area under the curve (AUC) above 0.7. Further, a panel consisting of the above 4 metabolites had an excellent performance with an AUC of 0.867. In SCZ patients, phosphatidylcholines were positively related with positive symptoms, and cholic acid was positively associated with negative symptoms. CONCLUSION Our study provides insights into the metabolite alterations associated with SCZ and potential biomarkers for its diagnosis and symptom severity assessment.
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Affiliation(s)
- Qiao Su
- Tianjin Mental Health Institute, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Fuyou Bi
- Tianjin Mental Health Institute, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Shu Yang
- Tianjin Mental Health Institute, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Huiming Yan
- Tianjin Mental Health Institute, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Xiaoxiao Sun
- Tianjin Mental Health Institute, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Jiayue Wang
- Tianjin Mental Health Institute, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Yuying Qiu
- Tianjin Mental Health Institute, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Meijuan Li
- Tianjin Mental Health Institute, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Shen Li
- Tianjin Mental Health Institute, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
| | - Jie Li
- Tianjin Mental Health Institute, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, China
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Song M, Liu Y, Zhou J, Shi H, Su X, Shao M, Yang Y, Wang X, Zhao J, Guo D, Liu Q, Zhang L, Zhang Y, Lv L, Li W. Potential plasma biomarker panels identification for the diagnosis of first-episode schizophrenia and monitoring antipsychotic monotherapy with the use of metabolomics analyses. Psychiatry Res 2023; 321:115070. [PMID: 36706560 DOI: 10.1016/j.psychres.2023.115070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Revised: 01/17/2023] [Accepted: 01/22/2023] [Indexed: 01/25/2023]
Abstract
Schizophrenia (SCZ) is a severe mental disorder. Using liquid chromatography mass spectrometry, we performed comprehensive metabolomics analyses of plasma samples from healthy controls (HC) and first episode SCZ patients before and after an acute period of medication. Ten lipid metabolites and 27 soluble small molecules were identified as potential biomarkers associated with the diagnosis and treatment of SCZ. These metabolites were significantly reduced in SCZ, and lipids and sulfate were significantly increased after treatment. Of the metabolites identified, four showed significant correlations with the Positive and Negative Syndrome Scale total scores. A biomarker panel composed of alpha-dimorphecolic, Phosphatidylcholine (PC) (16:0/18:1(11Z)), 1-methylnicotinamide, Phosphatidylethanolamine (PE) (20:2(11Z,14Z)/18:2(9Z,12Z)), sulfate, and L-tryptophan was selected to distinguish SCZ from HC; this provided the maximum classification performance with an AUC of 0.972. A biomarker panel including C16 sphinganine, gamma-linolenic acid, linoleic acid, PC(16:0/18:1(11Z)), PE(20:2(11Z,14Z)/18:2(9Z,12Z)), and sulfate, was selected for discrimination between SCZ before and after medication, and produced the optimal classification performance with an AUC of 0.905. Disturbances in lipid metabolism, sulfation modification, tryptophan metabolism, anti-inflammatory and antioxidant systems, and unsaturated fatty acids metabolism, were identified in SCZ. Our findings could facilitate the development of objective diagnostic or drug treatment monitoring tools for schizophrenia.
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Affiliation(s)
- Meng Song
- The Second Affiliated Hospital of Xinxiang Medical University, Henan Mental Hospital, Xinxiang, Henan, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, Henan, China.
| | - Ya Liu
- The Second Affiliated Hospital of Xinxiang Medical University, Henan Mental Hospital, Xinxiang, Henan, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, Henan, China
| | - Jiahui Zhou
- The Second Affiliated Hospital of Xinxiang Medical University, Henan Mental Hospital, Xinxiang, Henan, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, Henan, China
| | - Han Shi
- The Second Affiliated Hospital of Xinxiang Medical University, Henan Mental Hospital, Xinxiang, Henan, China
| | - Xi Su
- The Second Affiliated Hospital of Xinxiang Medical University, Henan Mental Hospital, Xinxiang, Henan, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, Henan, China
| | - Minglong Shao
- The Second Affiliated Hospital of Xinxiang Medical University, Henan Mental Hospital, Xinxiang, Henan, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, Henan, China
| | - Yongfeng Yang
- The Second Affiliated Hospital of Xinxiang Medical University, Henan Mental Hospital, Xinxiang, Henan, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, Henan, China
| | - Xiujuan Wang
- The Second Affiliated Hospital of Xinxiang Medical University, Henan Mental Hospital, Xinxiang, Henan, China
| | - Jingyuan Zhao
- The Second Affiliated Hospital of Xinxiang Medical University, Henan Mental Hospital, Xinxiang, Henan, China
| | - Dong Guo
- The Second Affiliated Hospital of Xinxiang Medical University, Henan Mental Hospital, Xinxiang, Henan, China
| | - Qing Liu
- The Second Affiliated Hospital of Xinxiang Medical University, Henan Mental Hospital, Xinxiang, Henan, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, Henan, China
| | - Luwen Zhang
- The Second Affiliated Hospital of Xinxiang Medical University, Henan Mental Hospital, Xinxiang, Henan, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, Henan, China
| | - Yan Zhang
- The Second Affiliated Hospital of Xinxiang Medical University, Henan Mental Hospital, Xinxiang, Henan, China
| | - Luxian Lv
- The Second Affiliated Hospital of Xinxiang Medical University, Henan Mental Hospital, Xinxiang, Henan, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, Henan, China.
| | - Wenqiang Li
- The Second Affiliated Hospital of Xinxiang Medical University, Henan Mental Hospital, Xinxiang, Henan, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, Henan, China.
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11
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Tkachev A, Stekolshchikova E, Vanyushkina A, Zhang H, Morozova A, Zozulya S, Kurochkin I, Anikanov N, Egorova A, Yushina E, Vogl T, Senner F, Schaupp SK, Reich-Erkelenz D, Papiol S, Kohshour MO, Klöhn-Saghatolislam F, Kalman JL, Heilbronner U, Heilbronner M, Gade K, Comes AL, Budde M, Anderson-Schmidt H, Adorjan K, Wiltfang J, Reininghaus EZ, Juckel G, Dannlowski U, Fallgatter A, Spitzer C, Schmauß M, von Hagen M, Zorkina Y, Reznik A, Barkhatova A, Lisov R, Mokrov N, Panov M, Zubkov D, Petrova D, Zhou C, Liu Y, Pu J, Falkai P, Kostyuk G, Klyushnik T, Schulze TG, Xie P, Schulte EC, Khaitovich P. Lipid Alteration Signature in the Blood Plasma of Individuals With Schizophrenia, Depression, and Bipolar Disorder. JAMA Psychiatry 2023; 80:250-259. [PMID: 36696101 PMCID: PMC9878436 DOI: 10.1001/jamapsychiatry.2022.4350] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 10/31/2022] [Indexed: 01/26/2023]
Abstract
Importance No clinically applicable diagnostic test exists for severe mental disorders. Lipids harbor potential as disease markers. Objective To define a reproducible profile of lipid alterations in the blood plasma of patients with schizophrenia (SCZ) independent of demographic and environmental variables and to investigate its specificity in association with other psychiatric disorders, ie, major depressive disorder (MDD) and bipolar disorder (BPD). Design, Setting, and Participants This was a multicohort case-control diagnostic analysis involving plasma samples from psychiatric patients and control individuals collected between July 17, 2009, and May 18, 2018. Study participants were recruited as consecutive and volunteer samples at multiple inpatient and outpatient mental health hospitals in Western Europe (Germany and Austria [DE-AT]), China (CN), and Russia (RU). Individuals with DSM-IV or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnoses of SCZ, MDD, BPD, or a first psychotic episode, as well as age- and sex-matched healthy controls without a mental health-related diagnosis were included in the study. Samples and data were analyzed from January 2018 to September 2020. Main Outcomes and Measures Plasma lipidome composition was assessed using liquid chromatography coupled with untargeted mass spectrometry. Results Blood lipid levels were assessed in 980 individuals (mean [SD] age, 36 [13] years; 510 male individuals [52%]) diagnosed with SCZ, BPD, MDD, or those with a first psychotic episode and in 572 controls (mean [SD] age, 34 [13] years; 323 male individuals [56%]). A total of 77 lipids were found to be significantly altered between those with SCZ (n = 436) and controls (n = 478) in all 3 sample cohorts. Alterations were consistent between cohorts (CN and RU: [Pearson correlation] r = 0.75; DE-AT and CN: r = 0.78; DE-AT and RU: r = 0.82; P < 10-38). A lipid-based predictive model separated patients with SCZ from controls with high diagnostic ability (area under the receiver operating characteristic curve = 0.86-0.95). Lipidome alterations in BPD and MDD, assessed in 184 and 256 individuals, respectively, were found to be similar to those of SCZ (BPD: r = 0.89; MDD: r = 0.92; P < 10-79). Assessment of detected alterations in individuals with a first psychotic episode, as well as patients with SCZ not receiving medication, demonstrated only limited association with medication restricted to particular lipids. Conclusions and Relevance In this study, SCZ was accompanied by a reproducible profile of plasma lipidome alterations, not associated with symptom severity, medication, and demographic and environmental variables, and largely shared with BPD and MDD. This lipid alteration signature may represent a trait marker of severe psychiatric disorders, indicating its potential to be transformed into a clinically applicable testing procedure.
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Affiliation(s)
- Anna Tkachev
- Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, Russia
- Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, Russia
| | - Elena Stekolshchikova
- Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Anna Vanyushkina
- Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Hanping Zhang
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Anna Morozova
- Department Basic and Applied Neurobiology, V. Serbsky Federal Medical Research Centre of Psychiatry and Narcology, Moscow, Russia
- Moscow Psychiatric Hospital No. 1, named after N.A. Alekseev, Moscow, Russia
| | | | - Ilia Kurochkin
- Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Nickolay Anikanov
- Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Alina Egorova
- Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Ekaterina Yushina
- Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, Russia
- FSBSI N.P. Bochkov Research Center of Medical Genetics, Moscow, Russia
| | - Thomas Vogl
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Fanny Senner
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Sabrina K. Schaupp
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Daniela Reich-Erkelenz
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Sergi Papiol
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Mojtaba Oraki Kohshour
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
- Department of Immunology, Faculty of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Farahnaz Klöhn-Saghatolislam
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Janos L. Kalman
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Urs Heilbronner
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Maria Heilbronner
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Katrin Gade
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Ashley L. Comes
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Monika Budde
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Heike Anderson-Schmidt
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Kristina Adorjan
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
- German Center for Neurodegenerative Diseases, Göttingen, Germany
- Neurosciences and Signaling Group, Institute of Medicine, Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
| | - Eva Z. Reininghaus
- Department of Psychiatry and Psychotherapeutic Medicine, Research Unit for Neurobiology and Anthropometrics in Bipolar Affective Disorder, Medical University of Graz, Graz, Austria
| | - Georg Juckel
- Department of Psychiatry, Ruhr University Bochum, LWL University Hospital, Bochum, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Andreas Fallgatter
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University Tübingen, Tübingen, Germany
| | - Carsten Spitzer
- Department of Psychosomatic Medicine and Psychotherapy, University Medical Center Rostock, Rostock, Germany
| | - Max Schmauß
- Department of Psychiatry and Psychotherapy, Bezirkskrankenhaus Augsburg, Augsburg, Germany
| | - Martin von Hagen
- Clinic for Psychiatry and Psychotherapy, Clinical Center Werra-Meißner, Eschwege, Germany
| | - Yana Zorkina
- Department Basic and Applied Neurobiology, V. Serbsky Federal Medical Research Centre of Psychiatry and Narcology, Moscow, Russia
- Moscow Psychiatric Hospital No. 1, named after N.A. Alekseev, Moscow, Russia
| | - Alexander Reznik
- Moscow Psychiatric Hospital No. 1, named after N.A. Alekseev, Moscow, Russia
- Moscow State University of Food Production, Moscow, Russia
| | | | - Roman Lisov
- Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, Russia
- Moscow Institute of Physics and Technology, Dolgoprudny, Russia
| | - Nikita Mokrov
- Moscow Institute of Physics and Technology, Dolgoprudny, Russia
- Center for Artificial Intelligence Technologies, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Maxim Panov
- Technology Innovation Institute, Abu Dhabi, United Arab Emirates
| | - Dmitri Zubkov
- Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Daria Petrova
- Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Chanjuan Zhou
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Department of Neurology, Yongchuan Hospital of Chongqing Medical University, Chongqing, China
| | - Yiyun Liu
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Juncai Pu
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Georgiy Kostyuk
- Moscow Psychiatric Hospital No. 1, named after N.A. Alekseev, Moscow, Russia
| | | | - Thomas G. Schulze
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, New York
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, Maryland
| | - Peng Xie
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Neurobiology, Chongqing, China
| | - Eva C. Schulte
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital Bonn, medical Faculty University of Bonn, Bonn, Germany
| | - Philipp Khaitovich
- Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, Russia
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Zhou Y, Zou X, Feng R, Zhan X, Hong H, Luo Y, Tan Y. Improvement of Spatial Memory and Cognitive Function in Mice via the Intervention of Milk Fat Globule Membrane. Nutrients 2023; 15:nu15030534. [PMID: 36771241 PMCID: PMC9921783 DOI: 10.3390/nu15030534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 01/12/2023] [Accepted: 01/16/2023] [Indexed: 01/20/2023] Open
Abstract
With the improvement of living standards, dietary interventions have become an appropriate approach to enhance memory and cognitive performance. The present study investigated the potential mechanisms of spatial memory and cognitive function improvement with the milk fat globule membrane (MFGM) intervention in mice. The Morris water maze experiment revealed that the trajectories of mice in group M were more disordered. Also, the immunohistochemical results demonstrated a significantly higher number of neurons in group M compared with group C, especially in the hippocampal dentate gyrus (DG) area. It is suggested that MFGM enhanced mice's spatial memory and cognition from macroscopic behavior and microscopic cytology, respectively. Meanwhile, 47 differentially expressed proteins (DEPs) were identified, including 20 upregulated and 27 downregulated proteins. Upregulated (Sorbs 2, Rab 39, and Cacna 1e) and downregulated (Hp and Lrg 1) DEPs may improve spatial memory and cognition in mice by promoting synapse formation and increasing neurotransmitter receptors. KEGG enrichment analysis of the DEPs identified seven signaling pathways that were significantly enriched (p < 0.05). One of these pathways was neuroactive ligand-receptor interactions, which are strongly associated with improved spatial memory and cognitive performance. These findings give some new insights and references to the potential mechanisms of spatial memory and cognitive enhancement by MFGM.
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Affiliation(s)
- Yongjie Zhou
- Beijing Laboratory for Food Quality and Safety, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China
| | - Xiaoxiao Zou
- Beijing Laboratory for Food Quality and Safety, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China
| | - Ruifang Feng
- Beijing Laboratory for Food Quality and Safety, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China
| | - Xin Zhan
- Department of Product and Development, Heibei Dongkang Dairy Co., Ltd., Shijiazhuang 052165, China
| | - Hui Hong
- Beijing Laboratory for Food Quality and Safety, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China
| | - Yongkang Luo
- Beijing Laboratory for Food Quality and Safety, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China
| | - Yuqing Tan
- Beijing Laboratory for Food Quality and Safety, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China
- Correspondence:
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13
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Hawe JS, Saha A, Waldenberger M, Kunze S, Wahl S, Müller-Nurasyid M, Prokisch H, Grallert H, Herder C, Peters A, Strauch K, Theis FJ, Gieger C, Chambers J, Battle A, Heinig M. Network reconstruction for trans acting genetic loci using multi-omics data and prior information. Genome Med 2022; 14:125. [PMID: 36344995 PMCID: PMC9641770 DOI: 10.1186/s13073-022-01124-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 10/11/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Molecular measurements of the genome, the transcriptome, and the epigenome, often termed multi-omics data, provide an in-depth view on biological systems and their integration is crucial for gaining insights in complex regulatory processes. These data can be used to explain disease related genetic variants by linking them to intermediate molecular traits (quantitative trait loci, QTL). Molecular networks regulating cellular processes leave footprints in QTL results as so-called trans-QTL hotspots. Reconstructing these networks is a complex endeavor and use of biological prior information can improve network inference. However, previous efforts were limited in the types of priors used or have only been applied to model systems. In this study, we reconstruct the regulatory networks underlying trans-QTL hotspots using human cohort data and data-driven prior information. METHODS We devised a new strategy to integrate QTL with human population scale multi-omics data. State-of-the art network inference methods including BDgraph and glasso were applied to these data. Comprehensive prior information to guide network inference was manually curated from large-scale biological databases. The inference approach was extensively benchmarked using simulated data and cross-cohort replication analyses. Best performing methods were subsequently applied to real-world human cohort data. RESULTS Our benchmarks showed that prior-based strategies outperform methods without prior information in simulated data and show better replication across datasets. Application of our approach to human cohort data highlighted two novel regulatory networks related to schizophrenia and lean body mass for which we generated novel functional hypotheses. CONCLUSIONS We demonstrate that existing biological knowledge can improve the integrative analysis of networks underlying trans associations and generate novel hypotheses about regulatory mechanisms.
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Affiliation(s)
- Johann S Hawe
- Institute of Computational Biology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany.,German Heart Centre Munich, Department of Cardiology, Technical University Munich, Munich, Germany.,Department of Informatics, Technical University of Munich, Garching, Germany
| | - Ashis Saha
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany
| | - Sonja Kunze
- Research Unit of Molecular Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany
| | - Simone Wahl
- Research Unit of Molecular Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany.,IBE, Faculty of Medicine, LMU Munich, 81377, Munich, Germany.,Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany.,Department of Internal Medicine I (Cardiology), Hospital of the Ludwig-Maximilians-University (LMU) Munich, Munich, Germany
| | - Holger Prokisch
- Institute of Human Genetics, School of Medicine, Technische Universität München, Munich, Germany
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany.,Institute of Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany.,German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Christian Herder
- German Center for Diabetes Research (DZD), Neuherberg, Germany.,Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany.,Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Annette Peters
- Institute of Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany.,Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany.,Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, Germany
| | - Fabian J Theis
- Department of Informatics, Technical University of Munich, Garching, Germany.,Department of Mathematics, Technical University of Munich, Garching, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany.,Institute of Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany.,German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - John Chambers
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK.,Lee Kong Chian School of Medicine, Nanyang Technological University, 308232, Singapore, Singapore
| | - Alexis Battle
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA.,Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Matthias Heinig
- Institute of Computational Biology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany. .,Department of Informatics, Technical University of Munich, Garching, Germany. .,Munich Heart Association, Partner Site Munich, DZHK (German Centre for Cardiovascular Research), 10785, Berlin, Germany.
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14
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Wang F, Guo L, Zhang T, Cui Z, Wang J, Zhang C, Xue F, Zhou C, Li B, Tan Q, Peng Z. Alterations in Plasma Lipidomic Profiles in Adult Patients with Schizophrenia and Major Depressive Disorder. MEDICINA (KAUNAS, LITHUANIA) 2022; 58:medicina58111509. [PMID: 36363466 PMCID: PMC9697358 DOI: 10.3390/medicina58111509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Revised: 10/19/2022] [Accepted: 10/20/2022] [Indexed: 01/25/2023]
Abstract
Background and Objectives: Lipidomics is a pivotal tool for investigating the pathogenesis of mental disorders. However, studies qualitatively and quantitatively analyzing peripheral lipids in adult patients with schizophrenia (SCZ) and major depressive disorder (MDD) are limited. Moreover, there are no studies comparing the lipid profiles in these patient populations. Materials and Method: Lipidomic data for plasma samples from sex- and age-matched patients with SCZ or MDD and healthy controls (HC) were obtained and analyzed by liquid chromatography-mass spectrometry (LC-MS). Results: We observed changes in lipid composition in patients with MDD and SCZ, with more significant alterations in those with SCZ. In addition, a potential diagnostic panel comprising 103 lipid species and another diagnostic panel comprising 111 lipid species could distinguish SCZ from HC (AUC = 0.953) or SCZ from MDD (AUC = 0.920) were identified, respectively. Conclusions: This study provides an increased understanding of dysfunctional lipid composition in the plasma of adult patients with SCZ or MDD, which may lay the foundation for identifying novel clinical diagnostic methods for these disorders.
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Affiliation(s)
- Fei Wang
- Department of Psychiatry, Chang’an Hospital, Xi’an 710000, China
| | - Lin Guo
- Department of Psychiatry, Chang’an Hospital, Xi’an 710000, China
| | - Ting Zhang
- Department of Psychiatry, Chang’an Hospital, Xi’an 710000, China
| | - Zhiquan Cui
- Department of Psychiatry, Chang’an Hospital, Xi’an 710000, China
| | - Jinke Wang
- Department of Psychiatry, Chang’an Hospital, Xi’an 710000, China
| | - Chi Zhang
- Department of Psychiatry, Chang’an Hospital, Xi’an 710000, China
| | - Fen Xue
- Department of Psychiatry, Xijing Hospital, Air Force Medical University, Xi’an 710032, China
| | - Cuihong Zhou
- Department of Psychiatry, Xijing Hospital, Air Force Medical University, Xi’an 710032, China
| | - Baojuan Li
- School of Biomedical Engineering, Air Force Medical University, Xi’an 710032, China
| | - Qingrong Tan
- Department of Psychiatry, Chang’an Hospital, Xi’an 710000, China
- Correspondence: (Q.T.); (Z.P.); Tel.: +86-29-83293951 (Q.T.)
| | - Zhengwu Peng
- Department of Psychiatry, Chang’an Hospital, Xi’an 710000, China
- Correspondence: (Q.T.); (Z.P.); Tel.: +86-29-83293951 (Q.T.)
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15
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Yoon JH, Seo Y, Jo YS, Lee S, Cho E, Cazenave-Gassiot A, Shin YS, Moon MH, An HJ, Wenk MR, Suh PG. Brain lipidomics: From functional landscape to clinical significance. SCIENCE ADVANCES 2022; 8:eadc9317. [PMID: 36112688 PMCID: PMC9481132 DOI: 10.1126/sciadv.adc9317] [Citation(s) in RCA: 52] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 08/01/2022] [Indexed: 05/23/2023]
Abstract
Lipids are crucial components of cellular function owing to their role in membrane formation, intercellular signaling, energy storage, and homeostasis maintenance. In the brain, lipid dysregulations have been associated with the etiology and progression of neurodegeneration and other neurological pathologies. Hence, brain lipids are emerging as important potential targets for the early diagnosis and prognosis of neurological diseases. This review aims to highlight the significance and usefulness of lipidomics in diagnosing and treating brain diseases. We explored lipid alterations associated with brain diseases, paying attention to organ-specific characteristics and the functions of brain lipids. As the recent advances in brain lipidomics would have been impossible without advances in analytical techniques, we provide up-to-date information on mass spectrometric approaches and integrative analysis with other omic approaches. Last, we present the potential applications of lipidomics combined with artificial intelligence techniques and interdisciplinary collaborative research for treating brain diseases with clinical heterogeneities.
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Affiliation(s)
- Jong Hyuk Yoon
- Neurodegenerative Diseases Research Group, Korea Brain Research Institute, Daegu 41062, Republic of Korea
| | - Youngsuk Seo
- Neurodegenerative Diseases Research Group, Korea Brain Research Institute, Daegu 41062, Republic of Korea
| | - Yeon Suk Jo
- Neurodegenerative Diseases Research Group, Korea Brain Research Institute, Daegu 41062, Republic of Korea
- Department of Brain Sciences, Daegu-Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic of Korea
| | - Seulah Lee
- Neurodegenerative Diseases Research Group, Korea Brain Research Institute, Daegu 41062, Republic of Korea
| | - Eunji Cho
- Neurodegenerative Diseases Research Group, Korea Brain Research Institute, Daegu 41062, Republic of Korea
| | - Amaury Cazenave-Gassiot
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore
- Singapore Lipidomics Incubator (SLING), Life Sciences Institute, National University of Singapore, Singapore 119077, Singapore
| | - Yong-Seung Shin
- Laboratory Solutions Sales, Agilent Technologies Korea Ltd., Seoul, 06621, Republic of Korea
| | - Myeong Hee Moon
- Department of Chemistry, Yonsei University, Seoul 03722, Republic of Korea
| | - Hyun Joo An
- Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon 34134, Republic of Korea
| | - Markus R. Wenk
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore
- Singapore Lipidomics Incubator (SLING), Life Sciences Institute, National University of Singapore, Singapore 119077, Singapore
| | - Pann-Ghill Suh
- Korea Brain Research Institute, Daegu 41062, Republic of Korea
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16
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Li M, Gao Y, Wang D, Hu X, Jiang J, Qing Y, Yang X, Cui G, Wang P, Zhang J, Sun L, Wan C. Impaired Membrane Lipid Homeostasis in Schizophrenia. Schizophr Bull 2022; 48:1125-1135. [PMID: 35751100 PMCID: PMC9434453 DOI: 10.1093/schbul/sbac011] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
BACKGROUND AND HYPOTHESIS Multiple lines of clinical, biochemical, and genetic evidence suggest that disturbances of membrane lipids and their metabolism are probably involved in the etiology of schizophrenia (SCZ). Lipids in the membrane are essential to neural development and brain function, however, their role in SCZ remains largely unexplored. STUDY DESIGN Here we investigated the lipidome of the erythrocyte membrane of 80 patients with SCZ and 40 healthy controls using ultra-performance liquid chromatography-mass spectrometry. Based on the membrane lipids profiling, we explored the potential mechanism of membrane phospholipids metabolism. STUDY RESULTS By comparing 812 quantified lipids, we found that in SCZ, membrane phosphatidylcholines and phosphatidylethanolamines, especially the plasmalogen, were significantly decreased. In addition, the total polyunsaturated fatty acids (PUFAs) in the membrane of SCZ were significantly reduced, resulting in a decrease in membrane fluidity. The accumulation of membrane oxidized lipids and the level of peripheral lipid peroxides increased, suggesting an elevated level of oxidative stress in SCZ. Further study of membrane-phospholipid-remodeling genes showed that activation of PLA2s and LPCATs expression in patients, supporting the imbalance of unsaturated and saturated fatty acyl remodeling in phospholipids of SCZ patients. CONCLUSIONS Our results suggest that the mechanism of impaired membrane lipid homeostasis is related to the activated phospholipid remodeling caused by excessive oxidative stress in SCZ. Disordered membrane lipids found in this study may reflect the membrane dysfunction in the central nervous system and impact neurotransmitter transmission in patients with SCZ, providing new evidence for the membrane lipids hypothesis of SCZ.
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Affiliation(s)
- Minghui Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Yan Gao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Dandan Wang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Xiaowen Hu
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Jie Jiang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Ying Qing
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Xuhan Yang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Gaoping Cui
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Pengkun Wang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Juan Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Liya Sun
- To whom correspondence should be addressed; Bio-X Institutes, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China, tel: +86-021-62822491, fax: +86-021-62932059, e-mail: (C.W.), (L.S.)
| | - Chunling Wan
- To whom correspondence should be addressed; Bio-X Institutes, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China, tel: +86-021-62822491, fax: +86-021-62932059, e-mail: (C.W.), (L.S.)
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17
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Yin X, Mongan D, Cannon M, Zammit S, Hyötyläinen T, Orešič M, Brennan L, Cotter DR. Plasma lipid alterations in young adults with psychotic experiences: A study from the Avon Longitudinal Study of Parents and Children cohort. Schizophr Res 2022; 243:78-85. [PMID: 35245705 DOI: 10.1016/j.schres.2022.02.029] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Revised: 01/12/2022] [Accepted: 02/18/2022] [Indexed: 10/19/2022]
Abstract
BACKGROUND Psychotic experiences (PEs) are associated with an increased risk of future psychotic and non-psychotic mental disorders. The identification of biomarkers of PEs may provide insights regarding the underlying pathophysiology. METHODS The current study applied targeted lipidomic approaches to compare plasma lipid profiles in participants from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort who did (n = 206) or did not (n = 206) have PEs when aged approximately 24 years. RESULTS In total, 202 lipids including 8 lipid classes were measured by using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS). Eight lipid clusters were generated. Thirteen individual lipids were nominally significantly higher in the PEs group compared to the control group. After correction for multiple comparisons, 9 lipids comprising 3 lysophosphatidylcholines (LPCs), 2 phosphatidylcholines (PCs) and 4 triacylglycerols (TGs) remained significant. In addition, PEs cases had increased levels of TGs and LPCs with a low double bond count. CONCLUSIONS These findings indicate plasma lipidomic abnormalities in individuals experiencing PEs. The lipidomic profile measures could aid our understanding of the underlying pathophysiological mechanisms.
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Affiliation(s)
- Xiaofei Yin
- Institute of Food and Health, UCD School of Agriculture and Food Science, University College Dublin, Belfield, Dublin, Ireland.
| | - David Mongan
- Department of Psychiatry, Royal College of Surgeons in Ireland, Beaumont Hospital, Dublin, Ireland
| | - Mary Cannon
- Department of Psychiatry, Royal College of Surgeons in Ireland, Beaumont Hospital, Dublin, Ireland
| | - Stanley Zammit
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK; Centre for Academic Mental Health, School of Social & Community Medicine, University of Bristol, Bristol, UK
| | | | - Matej Orešič
- School of Medical Sciences, Örebro University, Örebro, Sweden; Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland
| | - Lorraine Brennan
- Institute of Food and Health, UCD School of Agriculture and Food Science, University College Dublin, Belfield, Dublin, Ireland
| | - David R Cotter
- Department of Psychiatry, Royal College of Surgeons in Ireland, Beaumont Hospital, Dublin, Ireland.
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18
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Fan Y, Gao Y, Ma Q, Yang Z, Zhao B, He X, Yang J, Yan B, Gao F, Qian L, Wang W, Zhu F, Ma X. Multi-Omics Analysis Reveals Aberrant Gut-Metabolome-Immune Network in Schizophrenia. Front Immunol 2022; 13:812293. [PMID: 35309369 PMCID: PMC8927969 DOI: 10.3389/fimmu.2022.812293] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 02/14/2022] [Indexed: 12/16/2022] Open
Abstract
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.
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Affiliation(s)
- Yajuan Fan
- Department of Psychiatry, The First Afffliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Clinical Research Center for Psychiatric Medicine of Shaanxi Province, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Yuan Gao
- Department of Psychiatry, The First Afffliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Clinical Research Center for Psychiatric Medicine of Shaanxi Province, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Qingyan Ma
- Department of Psychiatry, The First Afffliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Clinical Research Center for Psychiatric Medicine of Shaanxi Province, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Zai Yang
- Department of Psychiatry, The First Afffliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Clinical Research Center for Psychiatric Medicine of Shaanxi Province, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Binbin Zhao
- Department of Psychiatry, The First Afffliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Clinical Research Center for Psychiatric Medicine of Shaanxi Province, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Xiaoyan He
- Department of Psychiatry, The First Afffliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Clinical Research Center for Psychiatric Medicine of Shaanxi Province, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Jian Yang
- Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Bin Yan
- Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Fengjie Gao
- Department of Psychiatry, The First Afffliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Clinical Research Center for Psychiatric Medicine of Shaanxi Province, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Li Qian
- Department of Psychiatry, The First Afffliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Clinical Research Center for Psychiatric Medicine of Shaanxi Province, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Wei Wang
- Department of Psychiatry, The First Afffliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Clinical Research Center for Psychiatric Medicine of Shaanxi Province, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Feng Zhu
- Department of Psychiatry, The First Afffliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Clinical Research Center for Psychiatric Medicine of Shaanxi Province, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Translational Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Xiancang Ma
- Department of Psychiatry, The First Afffliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Clinical Research Center for Psychiatric Medicine of Shaanxi Province, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
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19
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Couttas TA, Jieu B, Rohleder C, Leweke FM. Current State of Fluid Lipid Biomarkers for Personalized Diagnostics and Therapeutics in Schizophrenia Spectrum Disorders and Related Psychoses: A Narrative Review. Front Psychiatry 2022; 13:885904. [PMID: 35711577 PMCID: PMC9197191 DOI: 10.3389/fpsyt.2022.885904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 04/27/2022] [Indexed: 11/22/2022] Open
Abstract
Schizophrenia spectrum disorders (SSD) are traditionally diagnosed and categorized through clinical assessment, owing to their complex heterogeneity and an insufficient understanding of their underlying pathology. However, disease progression and accurate clinical diagnosis become problematic when differentiating shared aspects amongst mental health conditions. Hence, there is a need for widely accessible biomarkers to identify and track the neurobiological and pathophysiological development of mental health conditions, including SSD. High-throughput omics applications involving the use of liquid chromatography-mass spectrometry (LC-MS) are driving a surge in biological data generation, providing systems-level insight into physiological and pathogenic conditions. Lipidomics is an emerging subset of metabolomics, largely underexplored amongst the omics systems. Lipid profiles in the brain are highly enriched with well-established functions, including maintenance, support, and signal transduction of neuronal signaling pathways, making them a prospective and exciting source of biological material for neuropsychiatric research. Importantly, changes in the lipid composition of the brain appear to extend into the periphery, as there is evidence that circulating lipid alterations correlate with alterations of psychiatric condition(s). The relative accessibility of fluid lipids offers a unique source to acquire a lipidomic "footprint" of molecular changes, which may support reliable diagnostics even at early disease stages, prediction of treatment response and monitoring of treatment success (theranostics). Here, we summarize the latest fluid lipidomics discoveries in SSD-related research, examining the latest strategies to integrate information into multi-systems overviews that generate new perspectives of SSD-related psychosis identification, development, and treatment.
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Affiliation(s)
- Timothy A Couttas
- Brain and Mind Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Beverly Jieu
- Brain and Mind Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Cathrin Rohleder
- Brain and Mind Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.,Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - F Markus Leweke
- Brain and Mind Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.,Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
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20
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Okamoto L, Watanabe S, Deno S, Nie X, Maruyama J, Tomita M, Hatano A, Yugi K. Meta-analysis of transcriptional regulatory networks for lipid metabolism in neural cells from schizophrenia patients based on an open-source intelligence approach. Neurosci Res 2021; 175:82-97. [PMID: 34979163 DOI: 10.1016/j.neures.2021.12.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 12/23/2021] [Accepted: 12/23/2021] [Indexed: 01/13/2023]
Abstract
There have been a number of reports about the transcriptional regulatory networks in schizophrenia. However, most of these studies were based on a specific transcription factor or a single dataset, an approach that is inadequate to understand the diverse etiology and underlying common characteristics of schizophrenia. Here we reconstructed and compared the transcriptional regulatory network for lipid metabolism enzymes using 15 public transcriptome datasets of neural cells from schizophrenia patients. Since many of the well-known schizophrenia-related SNPs are in enhancers, we reconstructed a network including enhancer-dependent regulation and found that 53.3 % of the total number of edges (7,577 pairs) involved regulation via enhancers. By examining multiple datasets, we found common and unique transcriptional modes of regulation. Furthermore, enrichment analysis of SNPs that were connected with genes in the transcriptional regulatory networks by eQTL suggested an association with hematological cell counts and some other traits/diseases, whose relationship to schizophrenia was either not or insufficiently reported in previous studies. Based on these results, we suggest that in future studies on schizophrenia, information on genotype, comorbidities and hematological cell counts should be included, along with the transcriptome, for a more detailed genetic stratification and mechanistic exploration of schizophrenia.
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Affiliation(s)
- Lisa Okamoto
- Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan; Institute for Advanced Biosciences, Keio University, Fujisawa, 252-0882, Japan; Systems Biology Program, Graduate School of Media and Governance, Keio University, Fujisawa, 252-0882, Japan
| | - Soyoka Watanabe
- Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan; Institute for Advanced Biosciences, Keio University, Fujisawa, 252-0882, Japan
| | - Senka Deno
- Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan; Institute for Advanced Biosciences, Keio University, Fujisawa, 252-0882, Japan; Systems Biology Program, Graduate School of Media and Governance, Keio University, Fujisawa, 252-0882, Japan
| | - Xiang Nie
- Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
| | - Junichi Maruyama
- Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
| | - Masaru Tomita
- Institute for Advanced Biosciences, Keio University, Fujisawa, 252-0882, Japan; Systems Biology Program, Graduate School of Media and Governance, Keio University, Fujisawa, 252-0882, Japan
| | - Atsushi Hatano
- Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan; Department of Omics and Systems Biology, Niigata University Graduate School of Medical and Dental Sciences, 757 Ichibancho, Asahimachi-dori, Chuo Ward, Niigata City, 951-8510, Japan
| | - Katsuyuki Yugi
- Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan; Institute for Advanced Biosciences, Keio University, Fujisawa, 252-0882, Japan; Department of Biological Sciences, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan; PRESTO, Japan Science and Technology Agency, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan.
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21
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Ding Y, Pei C, Shu W, Wan J. Inorganic Matrices Assisted Laser Desorption/Ionization Mass Spectrometry for Metabolic Analysis in Bio-fluids. Chem Asian J 2021; 17:e202101310. [PMID: 34964274 DOI: 10.1002/asia.202101310] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 12/23/2021] [Indexed: 11/12/2022]
Abstract
Metabolic analysis in bio-fluids interprets the end products in the bio-process, emerging as an irreplaceable disease diagnosis and monitoring platform. Laser desorption/ionization mass spectrometry (LDI MS) based metabolic analysis exhibits great potential for clinical applications in terms of high throughput, rapid signal readout, and minimal sample preparation. There are two essential elements to construct the LDI MS-based metabolic analysis: 1) well-designed nanomaterials as matrices; 2) machine learning algorithms for data analysis. This review highlights the development of various inorganic matrices to comprehend the advantages of LDI MS in metabolite detection and the recent diagnostic applications based on target metabolite detection and untargeted metabolic fingerprints in biological fluids.
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Affiliation(s)
- Yajie Ding
- East China Normal University, School of Chemistry and Molecular Engineering, CHINA
| | - Congcong Pei
- East China Normal University, School of Chemistry and Molecular Engineering, CHINA
| | - Weikang Shu
- East China Normal University, School of Chemistry and Molecular Engineering, CHINA
| | - Jingjing Wan
- East China Normal University, School of Chemistry and Molecular Engineering, No.500, Dongchuan Road, Minghang District, 200241, Shanghai, CHINA
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22
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Juchnowicz D, Dzikowski M, Rog J, Waszkiewicz N, Zalewska A, Maciejczyk M, Karakuła-Juchnowicz H. Oxidative Stress Biomarkers as a Predictor of Stage Illness and Clinical Course of Schizophrenia. Front Psychiatry 2021; 12:728986. [PMID: 34867519 PMCID: PMC8636114 DOI: 10.3389/fpsyt.2021.728986] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 10/06/2021] [Indexed: 12/17/2022] Open
Abstract
Pro/antioxidant imbalance has been reported in schizophrenia (SZ). However, the results of studies are inconsistent and usually do not include other factors that are highly affected by oxidative stress (OS).This cross-sectional study aimed to determine the serum levels of OS markers and their potential connection with schizophrenia. The total sample comprised 147: 98 individuals with SZ -47 first-episode (FS) and 49 chronic patients (CS)-and 49 healthy individuals (HC) as a control group. The examination included clinical variables and serum levels of antioxidants and oxidative damage products. The significant changes were observed in concentrations of all examined markers, without any specific direction of the pro/antioxidant balance shift between SZ and HC. In the regression model adjusted for cofounders, catalase: OR = 0.81 (95%CI: 0.74-0.88); glutathione peroxidase: OR = 1.06 (95%CI: 1.02-1.10); total antioxidant capacity: OR = 0.85 (95%CI: 0.75-0.98); oxidative stress index: OR = 1.25 (95%CI: 1.03-1.52); ferric reducing ability of plasma: OR = 0.79 (95%CI: 0.69-0.89); advanced glycation end products: OR = 1.03 (95%CI: 1.01-1.04); and advanced oxidation protein products (AOPP): OR = 1.05 (95%CI: 1.03-1.07) turned out to be significant predictors of schizophrenia. In the multiple stepwise regression model, pro/antioxidant status and their interaction with the duration of illness-related factors affected schizophrenia symptoms: positive symptoms (FRAPxKYN), negative (DITYR, FRAP, CAT), general (KYN), and over-all psychopathology (KYNxNFK). The results confirm differences in serum levels of oxidative biomarkers between SZ patients and healthy individuals. The pro/antioxidant status could be considered a predictor of schizophrenia and the factor affects patients' symptom severity.
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Affiliation(s)
- Dariusz Juchnowicz
- Department of Psychiatric Nursing, Medical University of Lublin, Lublin, Poland
| | - Michał Dzikowski
- Department of Psychiatry, Psychotherapy and Early Intervention, Medical University of Lublin, Lublin, Poland
| | - Joanna Rog
- Department of Psychiatry, Psychotherapy and Early Intervention, Medical University of Lublin, Lublin, Poland
| | | | - Anna Zalewska
- Experimental Dentistry Laboratory and Department of Restorative Dentistry, Medical University of Bialystok, Bialystok, Poland
| | - Mateusz Maciejczyk
- Department of Hygiene, Epidemiology and Ergonomics, Medical University of Bialystok, Bialystok, Poland
| | - Hanna Karakuła-Juchnowicz
- Department of Psychiatry, Psychotherapy and Early Intervention, Medical University of Lublin, Lublin, Poland
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23
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Tkachev AI, Stekolshchikova EA, Morozova AY, Anikanov NA, Zorkina YA, Alekseyeva PN, Khobta EB, Andreyuk DS, Zozulya SA, Barkhatova AN, Klyushnik TP, Reznik AM, Kostyuk GP, Khaitovich PE. Ceramides: Shared Lipid Biomarkers of Cardiovascular Disease and Schizophrenia. CONSORTIUM PSYCHIATRICUM 2021; 2:35-43. [PMID: 39044755 PMCID: PMC11262249 DOI: 10.17816/cp101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 09/08/2021] [Indexed: 11/08/2022] Open
Abstract
INTRODUCTION Schizophrenia, although a debilitating mental illness, greatly affects individuals' physical health as well. One of the leading somatic comorbidities associated with schizophrenia is cardiovascular disease, which has been estimated to be one of the leading causes of excess mortality in patients diagnosed with schizophrenia. Although the shared susceptibility to schizophrenia and cardiovascular disease is well established, the mechanisms linking these two disorders are not well understood. Genetic studies have hinted toward shared lipid metabolism abnormalities co-occurring in the two disorders, while lipid compounds have emerged as prognostic markers for cardiovascular disease. In particular, three ceramide species in the blood plasma, Cer(d18:1/16:0), Cer(d18:1/18:0), and Cer(d18:1/24:1), have been robustly linked to the latter disorder. AIM We aimed to assess the differences in abundances of Cer(d18:1/16:0), Cer(d18:1/18:0), and Cer(d18:1/24:1) in the blood plasma of schizophrenia patients compared to healthy controls. METHODS We measured the abundances of Cer(d18:1/16:0), Cer(d18:1/18:0), and Cer(d18:1/24:1) in a cohort of 82 patients with schizophrenia and 138 controls without a psychiatric diagnosis and validated the results using an independent cohort of 26 patients with schizophrenia, 55 control individuals, and 19 patients experiencing a first psychotic episode. RESULTS We found significant alterations for all three ceramide species Cer(d18:1/16:0), Cer(d18:1/18:0), and Cer(d18:1/24:1) and a particularly strong difference in concentrations between psychiatric patients and controls for the ceramide species Cer(d18:1/18:0). CONCLUSIONS The alteration of Cer(d18:1/16:0), Cer(d18:1/18:0), and Cer(d18:1/24:1) levels in the blood plasma might be a manifestation of metabolic abnormalities common to both schizophrenia and cardiovascular disease.
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24
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Łuczaj W, Jastrząb A, do Rosário Domingues M, Domingues P, Skrzydlewska E. Changes in Phospholipid/Ceramide Profiles and Eicosanoid Levels in the Plasma of Rats Irradiated with UV Rays and Treated Topically with Cannabidiol. Int J Mol Sci 2021; 22:8700. [PMID: 34445404 PMCID: PMC8395479 DOI: 10.3390/ijms22168700] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 07/30/2021] [Accepted: 08/10/2021] [Indexed: 12/14/2022] Open
Abstract
Chronic UV radiation causes oxidative stress and inflammation of skin and blood cells. Therefore, in this study, we assessed the effects of cannabidiol (CBD), a natural phytocannabinoid with antioxidant and anti-inflammatory properties, on the phospholipid (PL) and ceramide (CER) profiles in the plasma of nude rats irradiated with UVA/UVB and treated topically with CBD. The results obtained showed that UVA/UVB radiation increased the levels of phosphatidylcholines, lysophospholipids, and eicosanoids (PGE2, TxB2), while downregulation of sphingomyelins led to an increase in CER[NS] and CER[NDS]. Topical application of CBD to the skin of control rats significantly upregulated plasma ether-linked phosphatidylethanolamines (PEo) and ceramides. However, CBD administered to rats irradiated with UVA/UVB promoted further upregulation of CER and PEo and led to significant downregulation of lysophospholipids. This was accompanied by the anti-inflammatory effect of CBD, manifested by a reduction in the levels of proinflammatory PGE2 and TxB2 and a dramatic increase in the level of anti-inflammatory LPXA4. It can therefore be suggested that topical application of CBD to the skin of rats exposed to UVA/UVB radiation prevents changes in plasma phospholipid profile resulting in a reduction of inflammation by reducing the level of LPE and LPC species and increasing antioxidant capacity due to upregulation of PEo species.
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Affiliation(s)
- Wojciech Łuczaj
- Department of Analytical Chemistry, Medical University of Bialystok, Mickiewicza 2d, 15-222 Bialystok, Poland; (A.J.); (E.S.)
| | - Anna Jastrząb
- Department of Analytical Chemistry, Medical University of Bialystok, Mickiewicza 2d, 15-222 Bialystok, Poland; (A.J.); (E.S.)
| | - Maria do Rosário Domingues
- Mass Spectrometry Center, LAQV, Department of Chemistry, Campus Universitário de Santiago, University of Aveiro, 3810-193 Aveiro, Portugal; (M.d.R.D.); (P.D.)
- CESAM, Department of Chemistry, Campus Universitário de Santiago, University of Aveiro, 3810-193 Aveiro, Portugal
| | - Pedro Domingues
- Mass Spectrometry Center, LAQV, Department of Chemistry, Campus Universitário de Santiago, University of Aveiro, 3810-193 Aveiro, Portugal; (M.d.R.D.); (P.D.)
| | - Elżbieta Skrzydlewska
- Department of Analytical Chemistry, Medical University of Bialystok, Mickiewicza 2d, 15-222 Bialystok, Poland; (A.J.); (E.S.)
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25
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Li R, Zhou Y, Liu C, Pei C, Shu W, Zhang C, Liu L, Zhou L, Wan J. Design of Multi‐Shelled Hollow Cr
2
O
3
Spheres for Metabolic Fingerprinting. Angew Chem Int Ed Engl 2021. [DOI: 10.1002/ange.202101007] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Rongxin Li
- School of Chemistry and Molecular Engineering East China Normal University Shanghai 200241 P. R. China
| | - Yongjie Zhou
- Department of Psychiatric Rehabilitation Shenzhen Kangning Hospital Shenzhen Guangdong 518118 P. R. China
| | - Chao Liu
- School of Chemistry and Molecular Engineering East China Normal University Shanghai 200241 P. R. China
| | - Congcong Pei
- School of Chemistry and Molecular Engineering East China Normal University Shanghai 200241 P. R. China
| | - Weikang Shu
- School of Chemistry and Molecular Engineering East China Normal University Shanghai 200241 P. R. China
| | - Chaoqi Zhang
- School of Chemistry and Molecular Engineering East China Normal University Shanghai 200241 P. R. China
| | - Lianzhong Liu
- Wuhan Mental Health Center Tongji Medical College of Huazhong University of Science and Technology Wuhan Hubei 430032 P. R. China
| | - Liang Zhou
- State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of Technology Wuhan Hubei 430070 P. R. China
| | - Jingjing Wan
- School of Chemistry and Molecular Engineering East China Normal University Shanghai 200241 P. R. China
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26
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Tkachev A, Stekolshchikova E, Anikanov N, Zozulya S, Barkhatova A, Klyushnik T, Petrova D. Shorter Chain Triglycerides Are Negatively Associated with Symptom Improvement in Schizophrenia. Biomolecules 2021; 11:biom11050720. [PMID: 34064997 PMCID: PMC8151512 DOI: 10.3390/biom11050720] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Revised: 04/30/2021] [Accepted: 05/08/2021] [Indexed: 12/29/2022] Open
Abstract
Schizophrenia is a serious mental disorder requiring lifelong treatment. While medications are available that are effective in treating some patients, individual treatment responses can vary, with some patients exhibiting resistance to one or multiple drugs. Currently, little is known about the causes of the difference in treatment response observed among individuals with schizophrenia, and satisfactory markers of poor response are not available for clinical practice. Here, we studied the changes in the levels of 322 blood plasma lipids between two time points assessed in 92 individuals diagnosed with schizophrenia during their inpatient treatment and their association with the extent of symptom improvement. We found 20 triglyceride species increased in individuals with the least improvement in Positive and Negative Syndrome Scale (PANSS) scores, but not in those with the largest reduction in PANSS scores. These triglyceride species were distinct from the rest of the triglyceride species present in blood plasma. They contained a relatively low number of carbons in their fatty acid residues and were relatively low in abundance compared to the principal triglyceride species of blood plasma.
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Affiliation(s)
- Anna Tkachev
- V. Zelman Center for Neurobiology and Brain Restoration, Skolkovo Institute of Science and Technology, 121205 Moscow, Russia; (E.S.); (N.A.); (D.P.)
- Correspondence:
| | - Elena Stekolshchikova
- V. Zelman Center for Neurobiology and Brain Restoration, Skolkovo Institute of Science and Technology, 121205 Moscow, Russia; (E.S.); (N.A.); (D.P.)
| | - Nickolay Anikanov
- V. Zelman Center for Neurobiology and Brain Restoration, Skolkovo Institute of Science and Technology, 121205 Moscow, Russia; (E.S.); (N.A.); (D.P.)
| | - Svetlana Zozulya
- Mental Health Research Center, 115522 Moscow, Russia; (S.Z.); (A.B.); (T.K.)
| | | | - Tatiana Klyushnik
- Mental Health Research Center, 115522 Moscow, Russia; (S.Z.); (A.B.); (T.K.)
| | - Daria Petrova
- V. Zelman Center for Neurobiology and Brain Restoration, Skolkovo Institute of Science and Technology, 121205 Moscow, Russia; (E.S.); (N.A.); (D.P.)
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27
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Li M, Yang X, Sun L, Qing Y, Hu X, Jiang J, Wang D, Cui G, Gao Y, Zhang E, Zhang J, Yang Y, Wan C. Decreased serum apolipoprotein A4 as a potential peripheral biomarker for patients with schizophrenia. J Psychiatr Res 2021; 137:14-21. [PMID: 33640722 DOI: 10.1016/j.jpsychires.2021.02.016] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 01/15/2021] [Accepted: 02/08/2021] [Indexed: 10/22/2022]
Abstract
Recent evidence supports an association between lipid metabolism dysfunction and the pathology of schizophrenia which has led to the search for peripheral blood-based biomarkers. The purpose of this study was to investigate the proteins involved in lipid metabolism (especially apolipoprotein) and to explore their potential as biomarkers for schizophrenia. Using multiple reaction monitoring mass spectrometry (MRM-MS), we quantified 22 proteins in serum samples of 109 healthy controls (HCs) and 111 patients with schizophrenia (SCZ), who were divided into discovery and validation sets. We found serum apolipoprotein A4 (ApoA4) to be significantly decreased in SCZ patients compared to HCs (p=1.61E-05). Moreover, the serum ApoA4 level served as an effective diagnostic tool, achieving area under the receiver operating characteristic curves (AUROC) of 0.840 in the discovery set and 0.791 in the validation set. Additionally, apolipoprotein F (ApoF), angiotensinogen (AGT), and alpha1-antichymotrypsin (ACT) levels were significantly higher in patients with schizophrenia than in healthy controls. These proteins combined with ApoA4, provided higher diagnostic accuracy for schizophrenia in the discovery set (AUROC=0.901) and in the validation set (AUROC=0.879). Our results suggest that the serum level of ApoA4 is a novel potential biomarker for schizophrenia. The proteins identified in this study expand the pool of biomarker candidates for schizophrenia and may be linked to the underlying mechanism of the disease.
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Affiliation(s)
- Minghui Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Xuhan Yang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Liya Sun
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Ying Qing
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Xiaowen Hu
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Jie Jiang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Dandan Wang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Gaoping Cui
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Yan Gao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - En Zhang
- The Fourth People's Hospital of Wuhu, Wuhu, China
| | - Juan Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Yong Yang
- Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, Suzhou, China.
| | - Chunling Wan
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China; Shanghai Mental Health Center, Shanghai Key Laboratory of Psychiatry Disorders, Shanghai Jiao Tong University, Shanghai, China.
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28
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Li R, Zhou Y, Liu C, Pei C, Shu W, Zhang C, Liu L, Zhou L, Wan J. Design of Multi-Shelled Hollow Cr 2 O 3 Spheres for Metabolic Fingerprinting. Angew Chem Int Ed Engl 2021; 60:12504-12512. [PMID: 33721392 DOI: 10.1002/anie.202101007] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 03/08/2021] [Indexed: 12/15/2022]
Abstract
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.
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Affiliation(s)
- Rongxin Li
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241, P. R. China
| | - Yongjie Zhou
- Department of Psychiatric Rehabilitation, Shenzhen Kangning Hospital, Shenzhen, Guangdong, 518118, P. R. China
| | - Chao Liu
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241, P. R. China
| | - Congcong Pei
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241, P. R. China
| | - Weikang Shu
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241, P. R. China
| | - Chaoqi Zhang
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241, P. R. China
| | - Lianzhong Liu
- Wuhan Mental Health Center, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, 430032, P. R. China
| | - Liang Zhou
- State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology, Wuhan, Hubei, 430070, P. R. China
| | - Jingjing Wan
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241, P. R. China
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29
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Wang D, Sun X, Maziade M, Mao W, Zhang C, Wang J, Cao B. Characterising phospholipids and free fatty acids in patients with schizophrenia: A case-control study. World J Biol Psychiatry 2021; 22:161-174. [PMID: 32677491 DOI: 10.1080/15622975.2020.1769188] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
OBJECTIVES Previous studies have indicated that schizophrenia (SCZ) is linked to abnormal phospholipid and fatty acid metabolism. However, comprehensive analysis of phospholipids and free fatty acids (FFAs) for SCZ is very limited. Herein, we sought to compare serum levels of phospholipids and FFAs between patients with SCZ and healthy controls (HCs). METHODS One hundred and nineteen SCZ patients and 109 HCs were enrolled in the study. The levels of 177 phospholipids and FFAs were measured in serum samples using a targeted liquid chromatography-mass spectrometry (LC-MS)-based platform. RESULTS One hundred and ten metabolites, including 16 FFAs, 25 phosphatidylcholines, 23 lysophosphatidylcholines, 11 phosphatidylcholine plasmalogens, 7 phosphatidylethanolamines, 9 lysophosphatidylethanolamines, 6 phosphatidylethanolamine plasmalogens, and 13 sphingomyelins, were observed to be significantly altered in SCZ patients compared to HCs. These disturbances may represent underlying pathophysiology, including but not limited to altered activity of phospholipases and acyltransferases, increased oxidative stress, dysfunctional oligodendrocyte glycosynapses, and elevated lipid mobilisation and β-oxidation. CONCLUSIONS Our findings suggest that complex lipid profile abnormalities are associated with SCZ. This study may contribute to investigating the role of phospholipid and FFA alterations in the pathoetiology of SCZ.
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Affiliation(s)
- Dongfang Wang
- Institute of Blood Transfusion, Chongqing Blood Center, Chongqing, P. R. China.,Department of Laboratorial Science and Technology, School of Public Health, Peking University, Beijing, P. R. China
| | - Xiaoyu Sun
- Department of Laboratorial Science and Technology, School of Public Health, Peking University, Beijing, P. R. China
| | - Michel Maziade
- Centre de recherche CERVO, Centre Intégré Universitaire de Santé et des Services Sociaux de la Capitale-Nationale, Québec, Canada.,Département de Psychiatrie et Neurosciences, Faculté de Médecine, Université Laval, Québec, Canada
| | - Wei Mao
- Institute of Blood Transfusion, Chongqing Blood Center, Chongqing, P. R. China
| | - Chuanbo Zhang
- Psychiatric Department, Weifang Mental Health Center, Weifang, P. R. China
| | - Jingyu Wang
- Department of Laboratorial Science and Technology, School of Public Health, Peking University, Beijing, P. R. China.,Peking University Medical and Health Analysis Center, Peking University, Beijing, P. R. China.,Vaccine Research Center, School of Public Health, Peking University, Beijing, P. R. China
| | - Bing Cao
- School of Psychology and Key Laboratory of Cognition and Personality (Ministry of Education), Southwest University, Chongqing, P. R. China
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30
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Panyard DJ, Kim KM, Darst BF, Deming YK, Zhong X, Wu Y, Kang H, Carlsson CM, Johnson SC, Asthana S, Engelman CD, Lu Q. Cerebrospinal fluid metabolomics identifies 19 brain-related phenotype associations. Commun Biol 2021; 4:63. [PMID: 33437055 PMCID: PMC7803963 DOI: 10.1038/s42003-020-01583-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 12/09/2020] [Indexed: 02/07/2023] Open
Abstract
The study of metabolomics and disease has enabled the discovery of new risk factors, diagnostic markers, and drug targets. For neurological and psychiatric phenotypes, the cerebrospinal fluid (CSF) is of particular importance. However, the CSF metabolome is difficult to study on a large scale due to the relative complexity of the procedure needed to collect the fluid. Here, we present a metabolome-wide association study (MWAS), which uses genetic and metabolomic data to impute metabolites into large samples with genome-wide association summary statistics. We conduct a metabolome-wide, genome-wide association analysis with 338 CSF metabolites, identifying 16 genotype-metabolite associations (metabolite quantitative trait loci, or mQTLs). We then build prediction models for all available CSF metabolites and test for associations with 27 neurological and psychiatric phenotypes, identifying 19 significant CSF metabolite-phenotype associations. Our results demonstrate the feasibility of MWAS to study omic data in scarce sample types.
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Grants
- R01 AG037639 NIA NIH HHS
- UL1 TR000427 NCATS NIH HHS
- T15 LM007359 NLM NIH HHS
- T32 LM012413 NLM NIH HHS
- RF1 AG027161 NIA NIH HHS
- T32 AG000213 NIA NIH HHS
- P2C HD047873 NICHD NIH HHS
- UL1 TR002373 NCATS NIH HHS
- P30 AG062715 NIA NIH HHS
- P50 AG033514 NIA NIH HHS
- R01 AG027161 NIA NIH HHS
- R01 AG054047 NIA NIH HHS
- P30 AG017266 NIA NIH HHS
- R21 AG067092 NIA NIH HHS
- U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
- U.S. Department of Health & Human Services | NIH | Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)
- U.S. Department of Health & Human Services | NIH | U.S. National Library of Medicine (NLM)
- NSF | Directorate for Mathematical & Physical Sciences | Division of Mathematical Sciences (DMS)
- U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences (NCATS)
- This research is supported by National Institutes of Health (NIH) grants R01AG27161 (Wisconsin Registry for Alzheimer Prevention: Biomarkers of Preclinical AD), R01AG054047 (Genomic and Metabolomic Data Integration in a Longitudinal Cohort at Risk for Alzheimer’s Disease), R21AG067092 (Identifying Metabolomic Risk Factors in Plasma and Cerebrospinal Fluid for Alzheimer’s Disease), R01AG037639 (White Matter Degeneration: Biomarkers in Preclinical Alzheimer’s Disease), P30AG017266 (Center for Demography of Health and Aging), and P50AG033514 and P30AG062715 (Wisconsin Alzheimer’s Disease Research Center Grant), the Helen Bader Foundation, Northwestern Mutual Foundation, Extendicare Foundation, State of Wisconsin, the Clinical and Translational Science Award (CTSA) program through the NIH National Center for Advancing Translational Sciences (NCATS) grant UL1TR000427, and the University of Wisconsin-Madison Office of the Vice Chancellor for Research and Graduate Education with funding from the Wisconsin Alumni Research Foundation. This research was supported in part by the Intramural Research Program of the National Institute on Aging. Computational resources were supported by a core grant to the Center for Demography and Ecology at the University of Wisconsin-Madison (P2CHD047873). Author DJP was supported by an NLM training grant to the Bio-Data Science Training Program (T32LM012413). Author BFD was supported by an NLM training grant to the Computation and Informatics in Biology and Medicine Training Program (NLM 5T15LM007359). Author YKD was supported by a training grant from the National Institute on Aging (T32AG000213). Author HK was supported by National Science Foundation (NSF) grant DMS-1811414 (Theory and Methods for Inferring Causal Effects with Mendelian Randomization).
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Affiliation(s)
- Daniel J Panyard
- Department of Population Health Sciences, University of Wisconsin-Madison, 610 Walnut Street, 707 WARF Building, Madison, WI, 53726, USA
| | - Kyeong Mo Kim
- Department of Biotechnology, Yonsei University, 50 Yonsei-ro Seodaemun-gu, Seoul, 03722, Republic of Korea
| | - Burcu F Darst
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, 1450 Biggy Street, Los Angeles, CA, 90033, USA
| | - Yuetiva K Deming
- Department of Population Health Sciences, University of Wisconsin-Madison, 610 Walnut Street, 707 WARF Building, Madison, WI, 53726, USA
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, 600 Highland Avenue, J5/1 Mezzanine, Madison, WI, 53792, USA
- Department of Medicine, University of Wisconsin-Madison, 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI, 53705, USA
| | - Xiaoyuan Zhong
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, WARF Room 201, 610 Walnut Street, Madison, WI, 53726, USA
| | - Yuchang Wu
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, WARF Room 201, 610 Walnut Street, Madison, WI, 53726, USA
| | - Hyunseung Kang
- Department of Statistics, University of Wisconsin-Madison, 1300 University Avenue, Madison, WI, 53706, USA
| | - Cynthia M Carlsson
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, 600 Highland Avenue, J5/1 Mezzanine, Madison, WI, 53792, USA
- Department of Medicine, University of Wisconsin-Madison, 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI, 53705, USA
- William S. Middleton Memorial Veterans Hospital, 2500 Overlook Terrace, Madison, WI, 53705, USA
| | - Sterling C Johnson
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, 600 Highland Avenue, J5/1 Mezzanine, Madison, WI, 53792, USA
- Department of Medicine, University of Wisconsin-Madison, 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI, 53705, USA
- William S. Middleton Memorial Veterans Hospital, 2500 Overlook Terrace, Madison, WI, 53705, USA
| | - Sanjay Asthana
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison, 600 Highland Avenue, J5/1 Mezzanine, Madison, WI, 53792, USA
- Department of Medicine, University of Wisconsin-Madison, 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI, 53705, USA
- William S. Middleton Memorial Veterans Hospital, 2500 Overlook Terrace, Madison, WI, 53705, USA
| | - Corinne D Engelman
- Department of Population Health Sciences, University of Wisconsin-Madison, 610 Walnut Street, 707 WARF Building, Madison, WI, 53726, USA
| | - Qiongshi Lu
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, WARF Room 201, 610 Walnut Street, Madison, WI, 53726, USA.
- Department of Statistics, University of Wisconsin-Madison, 1300 University Avenue, Madison, WI, 53706, USA.
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Mocking RJT, Naviaux JC, Li K, Wang L, Monk JM, Bright AT, Figueroa CA, Schene AH, Ruhé HG, Assies J, Naviaux RK. Metabolic features of recurrent major depressive disorder in remission, and the risk of future recurrence. Transl Psychiatry 2021; 11:37. [PMID: 33431800 PMCID: PMC7801396 DOI: 10.1038/s41398-020-01182-w] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2020] [Revised: 12/08/2020] [Accepted: 12/15/2020] [Indexed: 01/29/2023] Open
Abstract
Recurrent major depressive disorder (rMDD) is a relapsing-remitting disease with high morbidity and a 5-year risk of recurrence of up to 80%. This was a prospective pilot study to examine the potential diagnostic and prognostic value of targeted plasma metabolomics in the care of patients with rMDD in remission. We used an established LC-MS/MS platform to measure 399 metabolites in 68 subjects with rMDD (n = 45 females and 23 males) in antidepressant-free remission and 59 age- and sex-matched controls (n = 40 females and 19 males). Patients were then followed prospectively for 2.5 years. Metabolomics explained up to 43% of the phenotypic variance. The strongest biomarkers were gender specific. 80% of the metabolic predictors of recurrence in both males and females belonged to 6 pathways: (1) phospholipids, (2) sphingomyelins, (3) glycosphingolipids, (4) eicosanoids, (5) microbiome, and (6) purines. These changes traced to altered mitochondrial regulation of cellular redox, signaling, energy, and lipid metabolism. Metabolomics identified a chemical endophenotype that could be used to stratify rrMDD patients at greatest risk for recurrence with an accuracy over 0.90 (95%CI = 0.69-1.0). Power calculations suggest that a validation study of at least 198 females and 198 males (99 cases and 99 controls each) will be needed to confirm these results. Although a small study, these results are the first to show the potential utility of metabolomics in assisting with the important clinical challenge of prospectively identifying the patients at greatest risk of recurrence of a depressive episode and those who are at lower risk.
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Affiliation(s)
- Roel J T Mocking
- Department of Psychiatry, Amsterdam UMC, Academic Medical Center, University of Amsterdam, Meibergdreef 5, 1105 AZ, Amsterdam, The Netherlands.
| | - Jane C Naviaux
- The Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA, 92103-8467, USA
- Department of Neurosciences, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA, 92103-8467, USA
| | - Kefeng Li
- The Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA, 92103-8467, USA
- Department of Medicine, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA, 92103-8467, USA
| | - Lin Wang
- The Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA, 92103-8467, USA
- Department of Medicine, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA, 92103-8467, USA
| | - Jonathan M Monk
- The Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA, 92103-8467, USA
- Department of Medicine, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA, 92103-8467, USA
| | - A Taylor Bright
- The Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA, 92103-8467, USA
- Department of Medicine, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA, 92103-8467, USA
- Colt Neck Labs, 838 E High St 202., Lexington, KY, 40503, USA
| | - Caroline A Figueroa
- Department of Psychiatry, Amsterdam UMC, Academic Medical Center, University of Amsterdam, Meibergdreef 5, 1105 AZ, Amsterdam, The Netherlands
- School of Social Welfare, University of California, Berkeley, CA, 94720, USA
| | - Aart H Schene
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, the Netherlands
- Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, Nijmegen, the Netherlands
| | - Henricus G Ruhé
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, the Netherlands
- Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, Nijmegen, the Netherlands
| | - Johanna Assies
- Department of Psychiatry, Amsterdam UMC, Academic Medical Center, University of Amsterdam, Meibergdreef 5, 1105 AZ, Amsterdam, The Netherlands.
| | - Robert K Naviaux
- The Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA, 92103-8467, USA.
- Department of Medicine, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA, 92103-8467, USA.
- Department of Pediatrics, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA, 92103-8467, USA.
- Department of Pathology, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, San Diego, CA, 92103-8467, USA.
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Okamoto N, Ikenouchi A, Watanabe K, Igata R, Fujii R, Yoshimura R. A Metabolomics Study of Serum in Hospitalized Patients With Chronic Schizophrenia. Front Psychiatry 2021; 12:763547. [PMID: 34975570 PMCID: PMC8714673 DOI: 10.3389/fpsyt.2021.763547] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 11/15/2021] [Indexed: 12/18/2022] Open
Abstract
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.
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Affiliation(s)
- Naomichi Okamoto
- Medical Center for Dementia, University Hospital, University of Occupational and Environmental Health, Kitakyushu, Japan.,Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Atsuko Ikenouchi
- Medical Center for Dementia, University Hospital, University of Occupational and Environmental Health, Kitakyushu, Japan.,Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Keita Watanabe
- Open Innovation Laboratory, Kyoto University, Kyoto, Japan
| | - Ryohei Igata
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Rintaro Fujii
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Reiji Yoshimura
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
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Hylén U, McGlinchey A, Orešič M, Bejerot S, Humble MB, Särndahl E, Hyötyläinen T, Eklund D. Potential Transdiagnostic Lipid Mediators of Inflammatory Activity in Individuals With Serious Mental Illness. Front Psychiatry 2021; 12:778325. [PMID: 34899431 PMCID: PMC8661474 DOI: 10.3389/fpsyt.2021.778325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 10/21/2021] [Indexed: 11/28/2022] Open
Abstract
Mental disorders are heterogeneous and psychiatric comorbidities are common. Previous studies have suggested a link between inflammation and mental disorders. This link can manifest as increased levels of proinflammatory mediators in circulation and as signs of neuroinflammation. Furthermore, there is strong evidence that individuals suffering from psychiatric disorders have increased risk of developing metabolic comorbidities. Our group has previously shown that, in a cohort of low-functioning individuals with serious mental disorders, there is increased expression of genes associated with the NLRP3 inflammasome, a known sensor of metabolic perturbations, as well as increased levels of IL-1-family cytokines. In the current study, we set out to explore the interplay between disease-specific changes in lipid metabolism and known markers of inflammation. To this end, we performed mass spectrometry-based lipidomic analysis of plasma samples from low-functioning individuals with serious mental disorders (n = 39) and matched healthy controls (n = 39). By identifying non-spurious immune-lipid associations, we derived a partial correlation network of inflammatory markers and molecular lipids. We identified levels of lipids as being altered between individuals with serious mental disorders and controls, showing associations between lipids and inflammatory mediators, e.g., osteopontin and IL-1 receptor antagonist. These results indicate that, in low-functioning individuals with serious mental disorders, changes in specific lipids associate with immune mediators that are known to affect neuroinflammatory diseases.
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Affiliation(s)
- Ulrika Hylén
- University Health Care Research Center, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.,School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.,Inflammatory Response and Infection Susceptibility Centre, Örebro University, Örebro, Sweden
| | - Aidan McGlinchey
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Matej Orešič
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Susanne Bejerot
- University Health Care Research Center, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.,School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.,Inflammatory Response and Infection Susceptibility Centre, Örebro University, Örebro, Sweden
| | - Mats B Humble
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.,Inflammatory Response and Infection Susceptibility Centre, Örebro University, Örebro, Sweden
| | - Eva Särndahl
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.,Inflammatory Response and Infection Susceptibility Centre, Örebro University, Örebro, Sweden
| | - Tuulia Hyötyläinen
- Man-Technology-Environment Research Centre, School of Science and Technology, Örebro University, Örebro, Sweden
| | - Daniel Eklund
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.,Inflammatory Response and Infection Susceptibility Centre, Örebro University, Örebro, Sweden
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Dey M, Gunn-Moore FJ, Platt B, Smith TK. Brain region-specific lipid alterations in the PLB4 hBACE1 knock-in mouse model of Alzheimer's disease. Lipids Health Dis 2020; 19:201. [PMID: 32867761 PMCID: PMC7457777 DOI: 10.1186/s12944-020-01367-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Accepted: 08/10/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Lipid dysregulation is associated with several key characteristics of Alzheimer's disease (AD), including amyloid-β and tau neuropathology, neurodegeneration, glucose hypometabolism, as well as synaptic and mitochondrial dysfunction. The β-site amyloid precursor protein cleavage enzyme 1 (BACE1) is associated with increased amyloidogenesis, and has been affiliated with diabetes via its role in metabolic regulation. METHODS The research presented herein investigates the role of hBACE1 in lipid metabolism and whether specific brain regions show increased vulnerability to lipid dysregulation. By utilising advanced mass spectrometry techniques, a comprehensive, quantitative lipidomics analysis was performed to investigate the phospholipid, sterol, and fatty acid profiles of the brain from the well-known PLB4 hBACE1 knock-in mouse model of AD, which also shows a diabetic phenotype, to provide insight into regional alterations in lipid metabolism. RESULTS Results show extensive region - specific lipid alterations in the PLB4 brain compared to the wild-type, with decreases in the phosphatidylethanolamine content of the cortex and triacylglycerol content of the hippocampus and hypothalamus, but increases in the phosphatidylcholine, phosphatidylinositol, and diacylglycerol content of the hippocampus. Several sterol and fatty acids were also specifically decreased in the PLB4 hippocampus. CONCLUSION Collectively, the lipid alterations observed in the PLB4 hBACE1 knock-in AD mouse model highlights the regional vulnerability of the brain, in particular the hippocampus and hypothalamus, to lipid dysregulation, hence supports the premise that metabolic abnormalities have a central role in both AD and diabetes.
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Affiliation(s)
- Madhurima Dey
- School of Biology, University of St. Andrews, Medical & Biological Sciences Building, St. Andrews, Fife, Scotland
| | - Frank J Gunn-Moore
- School of Biology, University of St. Andrews, Medical & Biological Sciences Building, St. Andrews, Fife, Scotland
| | - Bettina Platt
- School of Medicine, Medical Sciences & Nutrition, University of Aberdeen, Institute of Medical Sciences, Aberdeen, Scotland
| | - Terry K Smith
- Biomedical Science Research Complex, University of St. Andrews, St. Andrews, Fife, Scotland.
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35
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Horska K, Kotolova H, Karpisek M, Babinska Z, Hammer T, Prochazka J, Stark T, Micale V, Ruda-Kucerova J. Metabolic profile of methylazoxymethanol model of schizophrenia in rats and effects of three antipsychotics in long-acting formulation. Toxicol Appl Pharmacol 2020; 406:115214. [PMID: 32866524 DOI: 10.1016/j.taap.2020.115214] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 08/20/2020] [Accepted: 08/22/2020] [Indexed: 12/15/2022]
Abstract
Mortality in psychiatric patients with severe mental illnesses reaches a 2-3 times higher mortality rate compared to the general population, primarily due to somatic comorbidities. A high prevalence of cardiovascular morbidity can be attributed to the adverse metabolic effects of atypical antipsychotics (atypical APs), but also to metabolic dysregulation present in drug-naïve patients. The metabolic aspects of neurodevelopmental schizophrenia-like models are understudied. This study evaluated the metabolic phenotype of a methylazoxymethanol (MAM) schizophrenia-like model together with the metabolic effects of three APs [olanzapine (OLA), risperidone (RIS) and haloperidol (HAL)] administered via long-acting formulations for 8 weeks in female rats. Body weight, feed efficiency, serum lipid profile, gastrointestinal and adipose tissue-derived hormones (leptin, ghrelin, glucagon and glucagon-like peptide 1) were determined. The lipid profile was assessed in APs-naïve MAM and control cohorts of both sexes. Body weight was not altered by the MAM model, though cumulative food intake and feed efficiency was lowered in the MAM compared to CTR animals. The effect of the APs was also present; body weight gain was increased by OLA and RIS, while OLA induced lower weight gain in the MAM rats. Further, the MAM model showed lower abdominal adiposity, while OLA increased it. Serum lipid profile revealed MAM model-induced alterations in both sexes; total, HDL and LDL cholesterol levels were increased. The MAM model did not exert significant alterations in hormonal parameters except for elevation in leptin level. The results support intrinsic metabolic dysregulation in the MAM model in both sexes, but the MAM model did not manifest higher sensitivity to metabolic effects induced by antipsychotic treatment.
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Affiliation(s)
- Katerina Horska
- Department of Human Pharmacology and Toxicology, Faculty of Pharmacy, University of Veterinary and Pharmaceutical Sciences, Palackeho trida 1946/1, 612 00 Brno, Czech Republic; Department of Human Pharmacology and Toxicology, Faculty of Pharmacy, Masaryk University, Palackeho trida 1946/1, 612 00 Brno, Czech Republic
| | - Hana Kotolova
- Department of Human Pharmacology and Toxicology, Faculty of Pharmacy, University of Veterinary and Pharmaceutical Sciences, Palackeho trida 1946/1, 612 00 Brno, Czech Republic; Department of Human Pharmacology and Toxicology, Faculty of Pharmacy, Masaryk University, Palackeho trida 1946/1, 612 00 Brno, Czech Republic
| | - Michal Karpisek
- Department of Human Pharmacology and Toxicology, Faculty of Pharmacy, University of Veterinary and Pharmaceutical Sciences, Palackeho trida 1946/1, 612 00 Brno, Czech Republic; Department of Human Pharmacology and Toxicology, Faculty of Pharmacy, Masaryk University, Palackeho trida 1946/1, 612 00 Brno, Czech Republic; R&D Department, Biovendor - Laboratorni Medicina, Karasek 1, 621 00 Brno, Czech Republic
| | - Zuzana Babinska
- Department of Pharmacology, Faculty of Medicine, Masaryk University, Kamenice 5, 62500 Brno, Czech Republic
| | - Tomas Hammer
- Department of Human Pharmacology and Toxicology, Faculty of Pharmacy, University of Veterinary and Pharmaceutical Sciences, Palackeho trida 1946/1, 612 00 Brno, Czech Republic; Department of Human Pharmacology and Toxicology, Faculty of Pharmacy, Masaryk University, Palackeho trida 1946/1, 612 00 Brno, Czech Republic
| | - Jiri Prochazka
- Department of Human Pharmacology and Toxicology, Faculty of Pharmacy, University of Veterinary and Pharmaceutical Sciences, Palackeho trida 1946/1, 612 00 Brno, Czech Republic; Department of Human Pharmacology and Toxicology, Faculty of Pharmacy, Masaryk University, Palackeho trida 1946/1, 612 00 Brno, Czech Republic
| | - Tibor Stark
- Department of Pharmacology, Faculty of Medicine, Masaryk University, Kamenice 5, 62500 Brno, Czech Republic; Department of Stress Neurobiology and Neurogenetics, Neuronal Plasticity Group, Max Planck Institute of Psychiatry, Kraepelinstrasse 2-10, 80804 Munich, Germany
| | - Vincenzo Micale
- Department of Biomedical and Biotechnological Sciences, Section of Pharmacology, University of Catania, Via Santa Sofia 97, I-95123 Catania, Italy; National Institute of Mental Health, Topolova 748, 250 67 Klecany, Czech Republic
| | - Jana Ruda-Kucerova
- Department of Pharmacology, Faculty of Medicine, Masaryk University, Kamenice 5, 62500 Brno, Czech Republic.
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Seabra G, de Almeida V, Reis-de-Oliveira G, Crunfli F, Antunes ASLM, Martins-de-Souza D. Ubiquitin-proteasome system, lipid metabolism and DNA damage repair are triggered by antipsychotic medication in human oligodendrocytes: implications in schizophrenia. Sci Rep 2020; 10:12655. [PMID: 32724114 PMCID: PMC7387551 DOI: 10.1038/s41598-020-69543-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 07/14/2020] [Indexed: 12/14/2022] Open
Abstract
Schizophrenia is a chronic, severe and disabling psychiatric disorder, whose treatment is based on psychosocial interventions and the use of antipsychotic drugs. While the effects of these drugs are well elucidated in neuronal cells, they are still not so clear in oligodendrocytes, which play a vital role in schizophrenia. Thus, we aimed to characterize biochemical profiles by proteomic analyses of human oligodendrocytes (MO3.13) which were matured using a protocol we developed and treated with either haloperidol (a typical antipsychotic), clozapine (an atypical antipsychotic) or a clozapine + D-serine co-treatment, which has emerged lately as an alternative type of treatment. This was accomplished by employing shotgun proteomics, using nanoESI-LC-MS/MS label-free quantitation. Proteomic analysis revealed biochemical pathways commonly affected by all tested antipsychotics were mainly associated to ubiquitination, proteasome degradation, lipid metabolism and DNA damage repair. Clozapine and haloperidol treatments also affected proteins involved with the actin cytoskeleton and with EIF2 signaling. In turn, metabolic processes, especially the metabolism of nitrogenous compounds, were a predominant target of modulation of clozapine + D-serine treatment. In this context, we seek to contribute to the understanding of the biochemical and molecular mechanisms involved in the action of antipsychotics on oligodendrocytes, along with their possible implications in schizophrenia.
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Affiliation(s)
- Gabriela Seabra
- Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Rua Monteiro Lobato, 255, Campinas, SP, 13083-862, Brazil
| | - Valéria de Almeida
- Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Rua Monteiro Lobato, 255, Campinas, SP, 13083-862, Brazil
| | - Guilherme Reis-de-Oliveira
- Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Rua Monteiro Lobato, 255, Campinas, SP, 13083-862, Brazil
| | - Fernanda Crunfli
- Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Rua Monteiro Lobato, 255, Campinas, SP, 13083-862, Brazil
| | - André Saraiva Leão Marcelo Antunes
- Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Rua Monteiro Lobato, 255, Campinas, SP, 13083-862, Brazil
| | - Daniel Martins-de-Souza
- Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Rua Monteiro Lobato, 255, Campinas, SP, 13083-862, Brazil.
- Experimental Medicine Research Cluster (EMRC), University of Campinas, Campinas, SP, Brazil.
- D'Or Institute for Research and Education (IDOR), São Paulo, Brazil.
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Knuplez E, Marsche G. An Updated Review of Pro- and Anti-Inflammatory Properties of Plasma Lysophosphatidylcholines in the Vascular System. Int J Mol Sci 2020; 21:E4501. [PMID: 32599910 PMCID: PMC7350010 DOI: 10.3390/ijms21124501] [Citation(s) in RCA: 93] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 06/19/2020] [Accepted: 06/23/2020] [Indexed: 12/14/2022] Open
Abstract
Lysophosphatidylcholines are a group of bioactive lipids heavily investigated in the context of inflammation and atherosclerosis development. While present in plasma during physiological conditions, their concentration can drastically increase in certain inflammatory states. Lysophosphatidylcholines are widely regarded as potent pro-inflammatory and deleterious mediators, but an increasing number of more recent studies show multiple beneficial properties under various pathological conditions. Many of the discrepancies in the published studies are due to the investigation of different species or mixtures of lysophatidylcholines and the use of supra-physiological concentrations in the absence of serum or other carrier proteins. Furthermore, interpretation of the results is complicated by the rapid metabolism of lysophosphatidylcholine (LPC) in cells and tissues to pro-inflammatory lysophosphatidic acid. Interestingly, most of the recent studies, in contrast to older studies, found lower LPC plasma levels associated with unfavorable disease outcomes. Being the most abundant lysophospholipid in plasma, it is of utmost importance to understand its physiological functions and shed light on the discordant literature connected to its research. LPCs should be recognized as important homeostatic mediators involved in all stages of vascular inflammation. In this review, we want to point out potential pro- and anti-inflammatory activities of lysophospholipids in the vascular system and highlight recent discoveries about the effect of lysophosphatidylcholines on immune cells at the endothelial vascular interface. We will also look at their potential clinical application as biomarkers.
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Affiliation(s)
- Eva Knuplez
- Division of Pharmacology, Otto Loewi Research Center, Medical University of Graz, 8010 Graz, Austria
| | - Gunther Marsche
- Division of Pharmacology, Otto Loewi Research Center, Medical University of Graz, 8010 Graz, Austria
- BioTechMed-Graz, 8010 Graz, Austria
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38
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Schverer M, O'Mahony SM, O’Riordan KJ, Donoso F, Roy BL, Stanton C, Dinan TG, Schellekens H, Cryan JF. Dietary phospholipids: Role in cognitive processes across the lifespan. Neurosci Biobehav Rev 2020; 111:183-193. [DOI: 10.1016/j.neubiorev.2020.01.012] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 12/16/2019] [Accepted: 01/10/2020] [Indexed: 12/31/2022]
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39
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Joaquim HPG, Costa AC, Talib LL, Dethloff F, Serpa MH, Zanetti MV, van de Bilt M, Turck CW. Plasma Metabolite Profiles in First Episode Psychosis: Exploring Symptoms Heterogeneity/Severity in Schizophrenia and Bipolar Disorder Cohorts. Front Psychiatry 2020; 11:496. [PMID: 32581873 PMCID: PMC7290160 DOI: 10.3389/fpsyt.2020.00496] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Accepted: 05/15/2020] [Indexed: 12/14/2022] Open
Abstract
INTRODUCTION The first symptoms of psychosis are frequently shared amongst several neuropsychiatry disorders, which makes the differentiation by clinical diagnosis challenging. Early recognition of symptoms is important in the management of psychosis. Therefore, the implementation of molecular biomarkers will be crucial for transforming the currently used diagnostic and therapeutic approach, improving insights into the underlying biological processes and clinical management. OBJECTIVES To define a set of metabolites that supports diagnosis or prognosis of schizophrenia (SCZ) and bipolar disorder (BD) at first onset psychosis. METHODS Plasma samples from 55 drug-naïve patients, 28 SCZ and 27 BD, and 42 healthy controls (HC). All participants underwent a seminaturalistic treatment regimen, clinically evaluated on a weekly basis until achieving clinical remission. All clinical or sociodemographic aspects considered for this study were equivalent between the groups at first-onset psychosis time point. The plasma samples were analyzed by untargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) using reversed-phase and hydrophilic interaction chromatography. The acquired molecular features were analyzed with MetaboAnalyst. RESULTS We identified two patient groups with different metabolite profiles. Both groups are composed of SCZ and BD patients. We found differences between these two groups regarding general symptoms of PANSS score after remission (p = 0.008), and the improvement of general symptoms (delta of the score at remission minus the baseline) (-0.50 vs. -0.33, p = 0.019). CONCLUSION Our results suggest that plasma metabolite profiles cluster clinical remission phenotypes based on PANSS general psychopathology scores.
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Affiliation(s)
- Helena P G Joaquim
- Laboratory of Neuroscience LIM-27, Department and Institute of Psychiatry, University of Sao Paulo Medical School, Sao Paulo, Brazil.,Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBioN), Conselho Nacional de Desenvolvimento Científico e Tecnológico, Sao Paulo, Brazil.,Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
| | - Alana C Costa
- Laboratory of Neuroscience LIM-27, Department and Institute of Psychiatry, University of Sao Paulo Medical School, Sao Paulo, Brazil.,Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBioN), Conselho Nacional de Desenvolvimento Científico e Tecnológico, Sao Paulo, Brazil
| | - Leda L Talib
- Laboratory of Neuroscience LIM-27, Department and Institute of Psychiatry, University of Sao Paulo Medical School, Sao Paulo, Brazil.,Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBioN), Conselho Nacional de Desenvolvimento Científico e Tecnológico, Sao Paulo, Brazil
| | - Frederik Dethloff
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
| | - Mauricio H Serpa
- Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBioN), Conselho Nacional de Desenvolvimento Científico e Tecnológico, Sao Paulo, Brazil.,Laboratory of Psychiatric Neuroimaging LIM-21, Department and Institute of Psychiatry, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - Marcus V Zanetti
- Laboratory of Psychiatric Neuroimaging LIM-21, Department and Institute of Psychiatry, University of Sao Paulo Medical School, Sao Paulo, Brazil.,Hospital Sírio-Libanês, São Paulo, Brazil
| | - Martinus van de Bilt
- Laboratory of Neuroscience LIM-27, Department and Institute of Psychiatry, University of Sao Paulo Medical School, Sao Paulo, Brazil.,Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBioN), Conselho Nacional de Desenvolvimento Científico e Tecnológico, Sao Paulo, Brazil
| | - Christoph W Turck
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
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Cao Z, Liu J, Xie X, Zhan S, Song W, Wu S, Sun Z, Dong Y, Tang G, Liu Y, Li L, Shen M, Zhai Y, Zou J, Liu X. Lipidomic profiling of amniotic fluid and its application in fetal lung maturity prediction. J Clin Lab Anal 2019; 34:e23109. [PMID: 31804000 PMCID: PMC7171342 DOI: 10.1002/jcla.23109] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2019] [Revised: 10/15/2019] [Accepted: 10/18/2019] [Indexed: 12/02/2022] Open
Abstract
Background The pulmonary surfactant especially lipids in amniotic fluid can reflect the development stage of fetal lung maturity (FLM). However, the conventional lecithin/sphingomyelin (L/S) ratio method by thin layer chromatography (TLC) is insufficient and inconvenient for FLM prediction in clinical practice. Methods The amniotic fluid samples were collected from the pregnant women in labor or undergoing amniocentesis and analyzed for its lipid contents with the liquid chromatography coupled with high‐resolution mass spectrometry (LC‐HRMS) method and the lamellar body count (LBC) method. To reveal the lipidomic profiling of different FLM stages, three groups of amniotic fluid samples including 8 from premature group (gestational week (GW) < 37), 10 from mature group (GW < 37), and 10 from mature group (GW > 38) were compared with the control group (n = 6) of 18 GWs separately. Results In the FLM prediction study, the sensitivity of the LC‐HRMS method and LBC method was 91% and 73%, respectively; the specificity was 100% and 95%, respectively. The most significant metabolic pathway was linoleic acid metabolism between the premature group and the control group. Both glycerophospholipid metabolism and glycosylphosphatidylinositol‐anchor biosynthesis were enriched in the mature groups. In search of potential FLM prediction markers in amniotic fluid, 8 phosphatidylcholines, 1 sphingomyelin, and 1 phosphatidylethanolamine were significantly increased in the mature groups compared with the premature group. Conclusion An efficient LC‐HRMS method for L/S ratio in predicting FLM was established. The linoleic acid metabolism may play an important role in the fetal lung development.
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Affiliation(s)
- Zheng Cao
- Department of Laboratory Medicine, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China
| | - Jingrui Liu
- Department of Laboratory Medicine, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China
| | - Xin Xie
- Department of Laboratory Medicine, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China
| | - Sien Zhan
- Department of Laboratory Medicine, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China
| | - Wei Song
- Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China
| | - Shaowen Wu
- Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China
| | - Zheng Sun
- Operating Room, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China
| | - Ying Dong
- Department of Laboratory Medicine, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China
| | - Guodong Tang
- Department of Laboratory Medicine, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China.,Prenatal Diagnosis Center, Beijing Haidian Maternal and Child Health Hospital, Beijing, China
| | - Yilin Liu
- Beijing Omics Bio-tech Co., Ltd, Beijing, China
| | - Lin Li
- Central Laboratory, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China
| | - Min Shen
- Reference Laboratory, Medical System Biotechnology Co., Ltd, Ningbo, China
| | - Yanhong Zhai
- Department of Laboratory Medicine, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China
| | - Jihua Zou
- Reference Laboratory, Medical System Biotechnology Co., Ltd, Ningbo, China
| | - Xiaowei Liu
- Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China
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Jasbi P, Mitchell NM, Shi X, Grys TE, Wei Y, Liu L, Lake DF, Gu H. Coccidioidomycosis Detection Using Targeted Plasma and Urine Metabolic Profiling. J Proteome Res 2019; 18:2791-2802. [DOI: 10.1021/acs.jproteome.9b00100] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Paniz Jasbi
- Arizona Metabolomics Laboratory, College of Health Solutions, Arizona State University, Scottsdale, Arizona 85259, United States
| | - Natalie M. Mitchell
- School of Life Sciences, Mayo Clinic Collaborative Research Building, Arizona State University, Scottsdale, Arizona 85259, United States
| | - Xiaojian Shi
- Arizona Metabolomics Laboratory, College of Health Solutions, Arizona State University, Scottsdale, Arizona 85259, United States
| | - Thomas E. Grys
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Phoenix, Arizona 85054, United States
| | - Yiping Wei
- Arizona Metabolomics Laboratory, College of Health Solutions, Arizona State University, Scottsdale, Arizona 85259, United States
| | - Li Liu
- Department of Biomedical Informatics, Arizona State University, Tempe, Arizona 85259, United States
- Department of Neurology, Mayo Clinic, Scottsdale, Arizona 85259, United States
| | - Douglas F. Lake
- School of Life Sciences, Mayo Clinic Collaborative Research Building, Arizona State University, Scottsdale, Arizona 85259, United States
| | - Haiwei Gu
- Arizona Metabolomics Laboratory, College of Health Solutions, Arizona State University, Scottsdale, Arizona 85259, United States
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