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Treccani M, Maggioni L, Di Giovanni C, Veschetti L, Cristofalo D, Patuzzo C, Lasalvia A, Ristic B, Kumar R, The PICOS-Veneto Group, Ruggeri M, Bonetto C, Malerba G, Tosato S. A Genome-Wide Association Study of First-Episode Psychosis: A Genetic Exploration in an Italian Cohort. Genes (Basel) 2025; 16:439. [PMID: 40282399 PMCID: PMC12026730 DOI: 10.3390/genes16040439] [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: 03/03/2025] [Revised: 03/29/2025] [Accepted: 04/03/2025] [Indexed: 04/29/2025] Open
Abstract
BACKGROUND Psychosis, particularly schizophrenia (SZ), is influenced by genetic and environmental factors. The neurodevelopmental hypothesis suggests that genetic factors affect neuronal circuit connectivity during perinatal periods, hence causing the onset of the diseases. In this study, we performed a genome-wide association study (GWAS) in a sample of the first episode of psychosis (FEP). METHODS A sample of 147 individuals diagnosed with non-affective psychosis and 102 controls were recruited and assessed. After venous blood and DNA extraction, the samples were genotyped. Genetic data underwent quality controls, genotype imputation, and a case-control genome-wide association study (GWAS). After the GWAS, results were investigated using an in silico functional mapping and annotation approach. RESULTS Our GWAS showed the association of 27 variants across 13 chromosomes at genome-wide significance (p < 1 × 10-7) and a total of 1976 candidate variants across 188 genes at suggestive significance (p < 1 × 10-5), mostly mapping in non-coding or intergenic regions. Gene-based tests reported the association of the SUFU (p = 4.8 × 10-7) and NCAN (p = 1.6 × 10-5) genes. Gene-sets enrichment analyses showed associations in the early stages of life, spanning from 12 to 24 post-conception weeks (p < 1.4 × 10-3) and in the late prenatal period (p = 1.4 × 10-3), in favor of the neurodevelopmental hypothesis. Moreover, several matches with the GWAS Catalog reported associations with strictly related traits, such as SZ, as well as with autism spectrum disorder, which shares some genetic overlap, and risk factors, such as neuroticism and alcohol dependence. CONCLUSIONS The resulting genetic associations and the consequent functional analysis displayed common genetic liability between the non-affective psychosis, related traits, and risk factors. In sum, our investigation provided novel hints supporting the neurodevelopmental hypothesis in SZ and-in general-in non-affective psychoses.
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Affiliation(s)
- Mirko Treccani
- GM Lab, Department of Surgical Sciences, Dentistry, Gynaecology and Paediatrics, University of Verona, 37134 Verona, Italy; (M.T.); (G.M.)
| | - Lucia Maggioni
- Department of Neuroscience, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, 37134 Verona, Italy; (L.M.); (D.C.); (A.L.); (B.R.); (R.K.); (M.R.); (C.B.)
| | - Claudia Di Giovanni
- Department of Diagnostic and Public Health, University of Verona, 37134 Verona, Italy;
| | - Laura Veschetti
- Infections and Cystic Fibrosis Unit, Division of Immunology, Transplantation and Infectious Diseases, IRCCS San Raffaele Scientific Institute, 20123 Milano, Italy;
- Vita-Salute San Raffaele University, 20123 Milano, Italy
| | - Doriana Cristofalo
- Department of Neuroscience, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, 37134 Verona, Italy; (L.M.); (D.C.); (A.L.); (B.R.); (R.K.); (M.R.); (C.B.)
| | - Cristina Patuzzo
- Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy;
| | - Antonio Lasalvia
- Department of Neuroscience, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, 37134 Verona, Italy; (L.M.); (D.C.); (A.L.); (B.R.); (R.K.); (M.R.); (C.B.)
| | - Branko Ristic
- Department of Neuroscience, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, 37134 Verona, Italy; (L.M.); (D.C.); (A.L.); (B.R.); (R.K.); (M.R.); (C.B.)
| | - Roushan Kumar
- Department of Neuroscience, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, 37134 Verona, Italy; (L.M.); (D.C.); (A.L.); (B.R.); (R.K.); (M.R.); (C.B.)
| | | | - Mirella Ruggeri
- Department of Neuroscience, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, 37134 Verona, Italy; (L.M.); (D.C.); (A.L.); (B.R.); (R.K.); (M.R.); (C.B.)
| | - Chiara Bonetto
- Department of Neuroscience, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, 37134 Verona, Italy; (L.M.); (D.C.); (A.L.); (B.R.); (R.K.); (M.R.); (C.B.)
| | - Giovanni Malerba
- GM Lab, Department of Surgical Sciences, Dentistry, Gynaecology and Paediatrics, University of Verona, 37134 Verona, Italy; (M.T.); (G.M.)
| | - Sarah Tosato
- Department of Neuroscience, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, 37134 Verona, Italy; (L.M.); (D.C.); (A.L.); (B.R.); (R.K.); (M.R.); (C.B.)
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Wang S, Dong Y, Qiu Y, Sun X, Jiang C, Su Q, Li M, Li J. Prediction of treatment response in drug-naïve schizophrenia patients from the perspective of targeted metabolomics. Schizophr Res 2025; 278:9-16. [PMID: 40081292 DOI: 10.1016/j.schres.2025.03.016] [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: 11/29/2024] [Revised: 02/02/2025] [Accepted: 03/07/2025] [Indexed: 03/15/2025]
Abstract
BACKGROUND Schizophrenia (SZ) is a severe and chronic mental illness affecting approximately 1 % of the global population. Although antipsychotic medications can alleviate some symptoms, 20--30 % of patients exhibit resistance to available treatments. Therefore, identifying objective biomarkers related to treatment efficacy is crucial. METHODS A total of 56 drug-naïve SZ patients were recruited, and after 8 weeks of antipsychotic medication, they were classified as treatment responders (30) and non-responders (26) based on the improvement of their symptoms. Baseline plasma metabolites were measured by targeted metabolomics Biocrates MxP® Quant 500 Kit. RESULTS A total of 271 metabolites were identified, among which 31 exhibited significant differences between responders and non-responders, including phosphatidylcholine (PC) (14), sphingomyelin (8), ceramide (6), cholesteryl ester (2), and sarcosine (1), which were mainly concentrated in the sphingolipid metabolic pathway. Notably, key differential metabolites included phosphatidylcholine, sphingomyelin, and ceramide, which were predominantly enriched in the sphingolipid metabolism pathway. Through logistic regression analysis, sarcosine, PC aa C28:1, PC ae C34:2, and PC ae C36:3 emerged as significant predictors, yielding a combined area under the curve (AUC) of 0.877 for effectively distinguishing treatment responders from non-responders. CONCLUSION Our findings suggest that the combination of sarcosine, PC aa C28:1, PC ae C34:2, and PC ae C36:3 could serve as biomarkers for prediction of treatment response in patients with drug-naïve SZ.
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Affiliation(s)
- Shuo Wang
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Yeqing Dong
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Yuying Qiu
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Xiaoxiao Sun
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Changyong Jiang
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Qiao Su
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Meijuan Li
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China.
| | - Jie Li
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China.
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Yao G, Zeng J, Huang Y, Lu H, Ping J, Wan J, Jiang T, Deng F, Li C, Liu X, Tang C, Lu L. Discovery of biological markers for schizophrenia based on metabolomics: a systematic review. Front Psychiatry 2025; 16:1540260. [PMID: 40225847 PMCID: PMC11985778 DOI: 10.3389/fpsyt.2025.1540260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2024] [Accepted: 02/27/2025] [Indexed: 04/15/2025] Open
Abstract
Introduction and methods To discover biomarkers for schizophrenia (SCZ) at the metabolomics level, we registered this systematic review (CRD42024572133 (https://www.crd.york.ac.uk/PROSPERO/home)) including 56 qualified articles, and we identified the characteristics of metabolites, metabolite combinations, and metabolic pathways associated with SCZ. Results Our findings showed that decreased arachidonic acid, arginine, and aspartate levels, and the increased levels of glucose 6-phosphate and glycylglycine were associated with the onset of SCZ. Metabolites such as carnitine and methionine sulfoxide not only helped to identify SCZ in Miao patients, but also were different between Miao patients and Han patients. The decrease in benzoic acid and betaine and the increase in creatine were the notable metabolic characteristics of first-episode schizophrenia (FESCZ). The metabolite combination formed by metabolites such as methylamine, dimethylamine and other metabolites had the best diagnostic effect. Arginine and proline metabolism and arginine biosynthesis had a clear advantage in identifying SCZ and acute SCZ. Butanoate metabolism played an important role in identifying SCZ, toxoplasma infection and SCZ comorbidity. Biosynthesis of unsaturated fatty acids was also significantly enriched in the diagnosis and treatment of SCZ. Discussion This study summarizes the current progress in clinical metabolomic research related to SCZ, deepens understanding of the pathogenesis of SCZ, and lays a foundation for subsequent research on SCZ-related metabolites. Systematic review registration https://www.crd.york.ac.uk/PROSPERO/home, identifier CRD42024572133.
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Affiliation(s)
- Gaolei Yao
- Clinical Research and Big Data Laboratory, South China Research Center for Acupuncture and Moxibustion, Medical College of Acu-Moxi and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Jingchun Zeng
- Rehabilitation Centre, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
- Rehabilitation Centre, Guangdong Clinical Research Academy of Chinese Medicine, Guangzhou, China
| | - Yuan Huang
- Department of Acupuncture, Shaoguan Hospital of Traditional Chinese Medicine, Shaoguan, China
| | - Huipeng Lu
- Department of Psychiatry and the Research Laboratory, The Third People’s Hospital of Zhongshan, Zhongshan, China
| | - Junjiao Ping
- Department of Psychiatry and the Research Laboratory, The Third People’s Hospital of Zhongshan, Zhongshan, China
| | - Jing Wan
- Department of Psychiatry and the Research Laboratory, The Third People’s Hospital of Zhongshan, Zhongshan, China
| | - Tingyun Jiang
- Department of Psychiatry and the Research Laboratory, The Third People’s Hospital of Zhongshan, Zhongshan, China
| | - Fuyuan Deng
- Clinical Research and Big Data Laboratory, South China Research Center for Acupuncture and Moxibustion, Medical College of Acu-Moxi and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Chenyun Li
- Clinical Research and Big Data Laboratory, South China Research Center for Acupuncture and Moxibustion, Medical College of Acu-Moxi and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Xinxia Liu
- Department of Psychiatry and the Research Laboratory, The Third People’s Hospital of Zhongshan, Zhongshan, China
| | - Chunzhi Tang
- Clinical Research and Big Data Laboratory, South China Research Center for Acupuncture and Moxibustion, Medical College of Acu-Moxi and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Liming Lu
- Clinical Research and Big Data Laboratory, South China Research Center for Acupuncture and Moxibustion, Medical College of Acu-Moxi and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China
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Modesti MN, Arena JF, Del Casale A, Gentile G, Borro M, Parmigiani G, Simmaco M, Guariglia C, Ferracuti S. Lipidomics and genomics in mental health: insights into major depressive disorder, bipolar disorder, schizophrenia, and obsessive-compulsive disorder. Lipids Health Dis 2025; 24:89. [PMID: 40069786 PMCID: PMC11895309 DOI: 10.1186/s12944-025-02512-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2024] [Accepted: 03/01/2025] [Indexed: 03/15/2025] Open
Abstract
INTRODUCTION This systematic review explores the hypothesis that various lipid categories and lipid metabolism-related genomic variations link to mental disorders, seeking potential clinically useful markers. METHODS We searched PubMed, Scopus, and PsycInfo databases until October 12th, 2024, using terms related to lipidomics, lipid-related genomics, and different mental disorders, i.e., Major Depressive Disorder (MDD), Bipolar Disorder (BD), Schizophrenia (SCZ), and Obsessive-Compulsive Disorder (OCD). Eligible studies were assessed. Extracted data included author, year, methodology, outcomes, genes, and lipids linked to disorders. Bias and evidence certainty were evaluated. The systematic review adhered to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and a registered protocol (PROSPERO: CRD42023438862). RESULTS A total of 27 studies were included. SCZ showed alterations in 77 lipids, including triglycerides (TG), ceramides, and phosphatidylcholine, while MDD and BD exhibited 97 and 47 altered lipids, respectively, with overlap among disorders. Shared genes, such as ABCA13, DGKZ, and FADS, and pathways involving inflammation, lipid metabolism, and mitochondrial function were identified. OCD was associated with sphingolipid signaling and peroxisomal metabolism. DISCUSSION Lipid signatures in MDD, BD, and SCZ shed light on underlying processes. Further research is needed to validate biomarkers and refine their clinical applications in precision psychiatry.
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Affiliation(s)
- Martina Nicole Modesti
- Department of Psychology, Faculty of Medicine and Psychology, Sapienza University of Rome, Rome, Italy.
| | - Jan Francesco Arena
- Department of Dynamic and Clinical Psychology and Health Studies, Faculty of Medicine and Psychology, Sapienza University of Rome, Rome, Italy
| | - Antonio Del Casale
- Department of Dynamic and Clinical Psychology and Health Studies, Faculty of Medicine and Psychology, Sapienza University of Rome, Rome, Italy
| | - Giovanna Gentile
- Department of Neuroscience, Mental Health, and Sensory Organs (NESMOS), Faculty of Medicine and Psychology, Sapienza University of Rome, Rome, Italy
- Laboratory of Clinical Biochemistry, Advanced Molecular Diagnostic Unit, Sant 'Andrea University Hospital, Rome, Italy
| | - Marina Borro
- Department of Neuroscience, Mental Health, and Sensory Organs (NESMOS), Faculty of Medicine and Psychology, Sapienza University of Rome, Rome, Italy
- Laboratory of Clinical Biochemistry, Advanced Molecular Diagnostic Unit, Sant 'Andrea University Hospital, Rome, Italy
| | | | - Maurizio Simmaco
- Department of Neuroscience, Mental Health, and Sensory Organs (NESMOS), Faculty of Medicine and Psychology, Sapienza University of Rome, Rome, Italy
- Laboratory of Clinical Biochemistry, Advanced Molecular Diagnostic Unit, Sant 'Andrea University Hospital, Rome, Italy
| | - Cecilia Guariglia
- Department of Psychology, Faculty of Medicine and Psychology, Sapienza University of Rome, Rome, Italy
- Cognitive and Motor Rehabilitation and Neuroimaging Unit, "Santa Lucia" Scientific Institute for Research, Hospitalization and Healthcare (IRCCS), Rome, Italy
| | - Stefano Ferracuti
- Department of Human Neuroscience, Faculty of Medicine and Dentistry, Sapienza, University of Rome, Rome, Italy
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Xu CX, Huang W, Shi XJ, Du Y, Liang JQ, Fang X, Chen HY, Cheng Y. Dysregulation of Serum Exosomal Lipid Metabolism in Schizophrenia: A Biomarker Perspective. Mol Neurobiol 2025; 62:3556-3567. [PMID: 39312067 DOI: 10.1007/s12035-024-04477-x] [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: 03/16/2024] [Accepted: 09/01/2024] [Indexed: 02/04/2025]
Abstract
Exosomes, crucial extracellular vesicles, have emerged as potential biomarkers for neurological conditions, including schizophrenia (SCZ). However, the exploration of exosomal lipids in the context of SCZ remains scarce, necessitating in-depth investigation. Leveraging ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), this study aimed to characterize the lipidomic profile of serum exosomes from SCZ patients, assessing their potential as novel biomarkers for SCZ diagnosis through absolute quantitative lipidomics. Our comprehensive lipidomic analysis unveiled 39 serum exosomal lipids that were differentially expressed between SCZ patients (n = 20) and healthy controls (HC, n = 20). These findings revealed a profound dysregulation in lipid metabolism pathways, notably in sphingolipid metabolism, glycerophospholipid metabolism, and linoleic acid metabolism. Among these, seven exosomal lipids stood out for their diagnostic potential, exhibiting remarkable ability to differentiate SCZ patients from HCs with an unparalleled classification performance, evidenced by an area under the curve (AUC) of 0.94 (95% CI, 0.82-1.00). These lipids included specific ceramides and phosphoethanolamines, pointing to a distinct lipid metabolic fingerprint associated with SCZ. Furthermore, bioinformatic analyses reinforced the pivotal involvement of these lipids in SCZ-related lipid metabolic processes, suggesting their integral role in the disorder's pathophysiology. This study significantly advances our understanding of SCZ by pinpointing dysregulated exosomal lipid metabolism as a key factor in its pathology. The identified serum exosome-derived lipids emerge as compelling biomarkers for SCZ diagnosis, offering a promising avenue towards the development of objective and reliable diagnostic tools.
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Affiliation(s)
- Chen-Xi Xu
- Center on Translational Neuroscience, College of Life and Environmental Sciences, Minzu University of China, No. 27, South Street of Zhongguancun, Haidian District, Beijing, 100081, China
| | - Wei Huang
- The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Xiao-Jie Shi
- Key Laboratory of Ethnomedicine of Ministry of Education, School of Pharmacy, Minzu University of China, Beijing, China
| | - Yang Du
- Henan Mental Hospital, the Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
| | - Jia-Quan Liang
- The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Xuan Fang
- Center on Translational Neuroscience, College of Life and Environmental Sciences, Minzu University of China, No. 27, South Street of Zhongguancun, Haidian District, Beijing, 100081, China
| | - He-Yuan Chen
- Center on Translational Neuroscience, College of Life and Environmental Sciences, Minzu University of China, No. 27, South Street of Zhongguancun, Haidian District, Beijing, 100081, China
| | - Yong Cheng
- Center on Translational Neuroscience, College of Life and Environmental Sciences, Minzu University of China, No. 27, South Street of Zhongguancun, Haidian District, Beijing, 100081, China.
- Key Laboratory of Ethnomedicine of Ministry of Education, School of Pharmacy, Minzu University of China, Beijing, China.
- Institute of National Security, Minzu University of China, Beijing, China.
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Yin J, Gan Y, Jiang C, Wang J, Zhou Z. Disturbance of neurotransmitter metabolites in peripheral blood of schizophrenia patients treated with olanzapine: a preliminary targeted metabolomic study. BMC Psychiatry 2025; 25:142. [PMID: 39966737 PMCID: PMC11837362 DOI: 10.1186/s12888-025-06584-y] [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: 06/03/2024] [Accepted: 02/05/2025] [Indexed: 02/20/2025] Open
Abstract
BACKGROUND The aim of this research was to characterize changes in peripheral blood neurotransmitter metabolites in olanzapine-treated schizophrenia (SCZ) and to identify potential biomarkers for SCZ. Concurrently, the relationship between these differential neurotransmitters and cognitive function is explored. METHODS We recruited 40 SCZ treated with single-agent olanzapine and 40 healthy controls (HC). Cognitive function and psychopathology were assessed using the MCCB and PANSS, respectively. Neurotransmitter levels were determined by targeted metabolomics approach using liquid chromatography-mass spectrometry (LC/MS). RESULTS SCZ showed cognitive impairment in all domains of the MCCB compared to HC. Interestingly, a 4-neurotransmitter panel consisting of 3-Methoxytyramine hydrochloride (3-MT), 3,4-Dihydroxyphenylacetate (DOPAC), arginine, and r-aminobutyric acid (GABA) illustrated the highest determinative score between SCZ and HC. Arginine was positively correlated with PANSS general psychopathology scores. 3-MT independently predicted the verbal learning scores only in SCZ, whereas GABA independently predicted the social cognition scores only. Furthermore, GABA independently predicted the working memory scores only in HC. CONCLUSIONS The collective assessment of these four neurotransmitters (3-MT, DOPAC, arginine, and GABA) holds considerable promise as potential biomarkers for SCZ. Moreover, 3-MT and GABA may enhance our understanding of cognitive dysfunction in SCZ, particularly in areas of verbal learning and social cognitive dysfunction.
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Affiliation(s)
- Jiajun Yin
- Department of Psychiatry, The Affiliated Mental Health Center of Jiangnan University, Wuxi City, 214151, China
| | - Yansha Gan
- Department of Psychiatry, The Affiliated Mental Health Center of Jiangnan University, Wuxi City, 214151, China
| | - Chenguang Jiang
- Department of Psychosomatics and Psychiatry, ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Jun Wang
- Department of Psychiatry, The Affiliated Mental Health Center of Jiangnan University, Wuxi City, 214151, China.
| | - Zhenhe Zhou
- Department of Psychiatry, The Affiliated Mental Health Center of Jiangnan University, Wuxi City, 214151, China.
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Song YN, Xia S, Sun Z, Chen YC, Jiao L, Wan WH, Zhang HW, Guo X, Guo H, Jia SF, Li XX, Cao SX, Fu LB, Liu MM, Zhou T, Zhang LF, Jia QQ. Metabolic pathway modulation by olanzapine: Multitarget approach for treating violent aggression in patients with schizophrenia. World J Psychiatry 2025; 15:101186. [PMID: 39831024 PMCID: PMC11684224 DOI: 10.5498/wjp.v15.i1.101186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2024] [Revised: 11/05/2024] [Accepted: 12/05/2024] [Indexed: 12/18/2024] Open
Abstract
BACKGROUND The use of network pharmacology and blood metabolomics to study the pathogenesis of violent aggression in patients with schizophrenia and the related drug mechanisms of action provides new directions for reducing the risk of violent aggression and optimizing treatment plans. AIM To explore the metabolic regulatory mechanism of olanzapine in treating patients with schizophrenia with a moderate to high risk of violent aggression. METHODS Metabolomic technology was used to screen differentially abundant metabolites in patients with schizophrenia with a moderate to high risk of violent aggression before and after olanzapine treatment, and the related metabolic pathways were identified. Network pharmacology was used to establish protein-protein interaction networks of the core targets of olanzapine. Gene Ontology functional analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were subsequently performed. RESULTS Compared with the healthy group, the patients with schizophrenia group presented significant changes in the levels of 24 metabolites related to the disruption of 9 metabolic pathways, among which the key pathways were the alanine, aspartate and glutamate metabolism and arginine biosynthesis pathways. After treatment with olanzapine, the levels of 10 differentially abundant metabolites were significantly reversed in patients with schizophrenia. Olanzapine effectively regulated six metabolic pathways, among which the key pathways were alanine, aspartate and glutamate metabolism and arginine biosynthesis pathways. Ten core targets of olanzapine were involved in several key pathways. CONCLUSION The metabolic pathways of alanine, aspartate, and glutamate metabolism and arginine biosynthesis are the key pathways involved in olanzapine treatment for aggressive schizophrenia.
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Affiliation(s)
- Yan-Ning Song
- Department of Pharmacy, The Affiliated Encephalopathy Hospital of Zhengzhou University (Zhumadian Second People's Hospital), Zhumadian 463000, Henan Province, China
| | - Shuang Xia
- Department of Pharmacy, The Affiliated Encephalopathy Hospital of Zhengzhou University (Zhumadian Second People's Hospital), Zhumadian 463000, Henan Province, China
| | - Zhi Sun
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China
| | - Yong-Chao Chen
- Department of Pharmacy, Zhumadian First People's Hospital, Zhumadian 463000, Henan Province, China
| | - Lu Jiao
- Department of Pharmacy, The Affiliated Encephalopathy Hospital of Zhengzhou University (Zhumadian Second People's Hospital), Zhumadian 463000, Henan Province, China
| | - Wen-Hua Wan
- Department of Pharmacy, The Affiliated Encephalopathy Hospital of Zhengzhou University (Zhumadian Second People's Hospital), Zhumadian 463000, Henan Province, China
| | - Hong-Wei Zhang
- Scientific Education Section, The Affiliated Encephalopathy Hospital of Zhengzhou University (Zhumadian Second People's Hospital), Zhumadian 463000, Henan Province, China
| | - Xiao Guo
- Department of Psychiatry, The Affiliated Encephalopathy Hospital of Zhengzhou University (Zhumadian Second People's Hospital), Zhumadian 463000, Henan Province, China
| | - Hua Guo
- Department of Psychiatry, The Affiliated Encephalopathy Hospital of Zhengzhou University (Zhumadian Second People's Hospital), Zhumadian 463000, Henan Province, China
| | - Shou-Feng Jia
- Department of Psychiatry, The Affiliated Encephalopathy Hospital of Zhengzhou University (Zhumadian Second People's Hospital), Zhumadian 463000, Henan Province, China
| | - Xiao-Xin Li
- Department of Pharmacy, The Affiliated Encephalopathy Hospital of Zhengzhou University (Zhumadian Second People's Hospital), Zhumadian 463000, Henan Province, China
| | - Shi-Xian Cao
- Department of Pharmacy, The Affiliated Encephalopathy Hospital of Zhengzhou University (Zhumadian Second People's Hospital), Zhumadian 463000, Henan Province, China
| | - Li-Bin Fu
- Department of Pharmacy, The Affiliated Encephalopathy Hospital of Zhengzhou University (Zhumadian Second People's Hospital), Zhumadian 463000, Henan Province, China
| | - Meng-Meng Liu
- Clinical Laboratory, The Affiliated Encephalopathy Hospital of Zhengzhou University (Zhumadian Second People's Hospital), Zhumadian 463000, Henan Province, China
| | - Tian Zhou
- Publicity Division, The Affiliated Encephalopathy Hospital of Zhengzhou University (Zhumadian Second People's Hospital), Zhumadian 463000, Henan Province, China
| | - Lv-Feng Zhang
- Department of Psychiatry, The Affiliated Encephalopathy Hospital of Zhengzhou University (Zhumadian Second People's Hospital), Zhumadian 463000, Henan Province, China
| | - Qing-Quan Jia
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China
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Godzien J, Kalaska B, Rudzki L, Barbas-Bernardos C, Swieton J, Lopez-Gonzalvez A, Ostrowska L, Szulc A, Waszkiewicz N, Ciborowski M, García A, Kretowski A, Barbas C, Pawlak D. Probiotic Lactobacillus plantarum 299v supplementation in patients with major depression in a double-blind, randomized, placebo-controlled trial: A metabolomics study. J Affect Disord 2025; 368:180-190. [PMID: 39271063 DOI: 10.1016/j.jad.2024.09.058] [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: 03/10/2024] [Revised: 06/19/2024] [Accepted: 09/10/2024] [Indexed: 09/15/2024]
Abstract
BACKGROUND Understanding the multifactorial nature of major depressive disorder (MDD) is crucial for tailoring treatments. However, the complex interplay of various factors underlying the development and progression of MDD poses significant challenges. Our previous study demonstrated improvements in cognitive functions in MDD patients undergoing treatment with selective serotonin reuptake inhibitors (SSRIs) supplemented with Lactobacillus plantarum 299v (LP299v). METHODS To elucidate the biochemical mechanisms underlying cognitive functions improvements, we explored underlying metabolic changes. We employed multi-platform metabolomics, including LC-QTOF-MS and CE-TOF-MS profiling, alongside chiral LC-QqQ-MS analysis for amino acids. RESULTS Supplementation of SSRI treatment with LP299v intensified the reduction of long-chain acylcarnitines, potentially indicating improved mitochondrial function. LP299v supplementation reduced N-acyl taurines more than four times compared to the placebo, suggesting a substantial impact on restoring biochemical balance. The LP299v-supplemented group showed increased levels of oxidized glycerophosphocholine (oxPC). Additionally, LP299v supplementation led to higher levels of sphingomyelins, L-histidine, D-valine, and p-cresol. LIMITATIONS This exploratory study suggests potential metabolic pathways influenced by LP299v supplementation. However, the need for further research hinders the ability to draw definitive conclusions. CONCLUSIONS Observed metabolic changes were linked to mitochondrial dysfunction, inflammation, oxidative stress, and gut microbiota disruption. Despite the subtle nature of this alterations, our research successfully detected these differences and connected them to the metabolic disruptions associated with MDD. Our findings emphasise the intricate relationship between metabolism, gut microbiota, and mental health prompting further research into the mechanisms of action of probiotics in MDD treatment.
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Affiliation(s)
- Joanna Godzien
- Metabolomics and Proteomics Laboratory, Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
| | - Bartlomiej Kalaska
- Department of Pharmacodynamics, Medical University of Bialystok, Bialystok, Poland.
| | - Leszek Rudzki
- Psychiatry-UK, 3b Fore Street, Camelford PL32 9PG, UK
| | - Cecilia Barbas-Bernardos
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, 28660 Boadilla del Monte, Spain
| | - Justyna Swieton
- Department of Pharmacodynamics, Medical University of Bialystok, Bialystok, Poland
| | - Angeles Lopez-Gonzalvez
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, 28660 Boadilla del Monte, Spain
| | - Lucyna Ostrowska
- Department of Dietetics and Clinical Nutrition, Medical University of Bialystok, Bialystok, Poland
| | - Agata Szulc
- Department of Psychiatry, Medical University of Warsaw, Warsaw, Poland
| | | | - Michal Ciborowski
- Metabolomics and Proteomics Laboratory, Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
| | - Antonia García
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, 28660 Boadilla del Monte, Spain
| | - Adam Kretowski
- Metabolomics and Proteomics Laboratory, Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland; Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, Bialystok, Poland
| | - Coral Barbas
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, 28660 Boadilla del Monte, Spain
| | - Dariusz Pawlak
- Department of Pharmacodynamics, Medical University of Bialystok, Bialystok, Poland
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9
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Dong D, Wang Y, Zhou F, Chang X, Qiu J, Feng T, He Q, Lei X, Chen H. Functional Connectome Hierarchy in Schizotypy and Its Associations With Expression of Schizophrenia-Related Genes. Schizophr Bull 2024; 51:145-158. [PMID: 38156676 PMCID: PMC11661955 DOI: 10.1093/schbul/sbad179] [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] [Indexed: 01/03/2024]
Abstract
BACKGROUND AND HYPOTHESIS Schizotypy has been conceptualized as a continuum of symptoms with marked genetic, neurobiological, and sensory-cognitive overlaps to schizophrenia. Hierarchical organization represents a general organizing principle for both the cortical connectome supporting sensation-to-cognition continuum and gene expression variability across the cortex. However, a mapping of connectome hierarchy to schizotypy remains to be established. Importantly, the underlying changes of the cortical connectome hierarchy that mechanistically link gene expressions to schizotypy are unclear. STUDY DESIGN The present study applied novel connectome gradient on resting-state fMRI data from 1013 healthy young adults to investigate schizotypy-associated sensorimotor-to-transmodal connectome hierarchy and assessed its similarity with the connectome hierarchy of schizophrenia. Furthermore, normative and differential postmortem gene expression data were utilized to examine transcriptional profiles linked to schizotypy-associated connectome hierarchy. STUDY RESULTS We found that schizotypy was associated with a compressed functional connectome hierarchy. Moreover, the pattern of schizotypy-related hierarchy exhibited a positive correlation with the connectome hierarchy observed in schizophrenia. This pattern was closely colocated with the expression of schizophrenia-related genes, with the correlated genes being enriched in transsynaptic, receptor signaling and calcium ion binding. CONCLUSIONS The compressed connectome hierarchy suggests diminished functional system differentiation, providing a novel and holistic system-level basis for various sensory-cognition deficits in schizotypy. Importantly, its linkage with schizophrenia-altered hierarchy and schizophrenia-related gene expression yields new insights into the neurobiological continuum of psychosis. It also provides mechanistic insight into how gene variation may drive alterations in functional hierarchy, mediating biological vulnerability of schizotypy to schizophrenia.
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Affiliation(s)
- Debo Dong
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Yulin Wang
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
- Sleep and NeuroImaging Center, Faculty of Psychology, Southwest University, Chongqing, China
| | - Feng Zhou
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Xuebin Chang
- Department of Information Sciences, School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, China
| | - Jiang Qiu
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
- Southwest University Branch, Collaborative Innovation Center of Assessment Toward Basic Education Quality at Beijing Normal University, Chongqing, China
| | - Tingyong Feng
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
- Research Center of Psychology and Social Development, Faculty of Psychology, Southwest University, Chongqing, China
| | - Qinghua He
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
- Southwest University Branch, Collaborative Innovation Center of Assessment Toward Basic Education Quality at Beijing Normal University, Chongqing, China
| | - Xu Lei
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
- Sleep and NeuroImaging Center, Faculty of Psychology, Southwest University, Chongqing, China
| | - Hong Chen
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
- Research Center of Psychology and Social Development, Faculty of Psychology, Southwest University, Chongqing, China
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10
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Lakhawat SS, Mech P, Kumar A, Malik N, Kumar V, Sharma V, Bhatti JS, Jaswal S, Kumar S, Sharma PK. Intricate mechanism of anxiety disorder, recognizing the potential role of gut microbiota and therapeutic interventions. Metab Brain Dis 2024; 40:64. [PMID: 39671133 DOI: 10.1007/s11011-024-01453-1] [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: 02/21/2024] [Accepted: 09/29/2024] [Indexed: 12/14/2024]
Abstract
Anxiety is a widespread psychological disorder affecting both humans and animals. It is a typical stress reaction; however, its longer persistence can cause severe health disorders affecting the day-to-day life activities of individuals. An intriguing facet of the anxiety-related disorder can be addressed better by investigating the role of neurotransmitters in regulating emotions, provoking anxiety, analyzing the cross-talks between neurotransmitters, and, most importantly, identifying the biomarkers of the anxiety. Recent years have witnessed the potential role of the gut microbiota in human health and disorders, including anxiety. Animal models are commonly used to study anxiety disorder as they offer a simpler and more controlled environment than humans. Ultimately, developing new strategies for diagnosing and treating anxiety is of paramount interest to medical scientists. Altogether, this review article shall highlight the intricate mechanisms of anxiety while emphasizing the emerging role of gut microbiota in regulating metabolic pathways through various interaction networks in the host. In addition, the review will foster information about the therapeutic interventions of the anxiety and related disorder.
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Affiliation(s)
- Sudarshan Singh Lakhawat
- Amity Institute of Biotechnology, Amity University Rajasthan, SP-1, Kant Kalwar, RIICO Industrial Area, NH-11C, Jaipur, Rajasthan, 303002, India
| | - Priyanka Mech
- Amity Institute of Biotechnology, Amity University Rajasthan, SP-1, Kant Kalwar, RIICO Industrial Area, NH-11C, Jaipur, Rajasthan, 303002, India
| | - Akhilesh Kumar
- Amity Institute of Biotechnology, Amity University Rajasthan, SP-1, Kant Kalwar, RIICO Industrial Area, NH-11C, Jaipur, Rajasthan, 303002, India
| | - Naveen Malik
- Amity Institute of Biotechnology, Amity University Rajasthan, SP-1, Kant Kalwar, RIICO Industrial Area, NH-11C, Jaipur, Rajasthan, 303002, India
| | - Vikram Kumar
- Amity Institute of Pharmacy, Amity University Rajasthan, SP-1, Kant Kalwar, RIICO Industrial Area, NH-11C, Jaipur, Rajasthan, India
| | - Vinay Sharma
- Amity Institute of Biotechnology, Amity University Rajasthan, SP-1, Kant Kalwar, RIICO Industrial Area, NH-11C, Jaipur, Rajasthan, 303002, India
| | - Jasvinder Singh Bhatti
- Department of Environmental Sciences, Himachal Pradesh University, Summer Hill, Shimla, 171005, India
| | - Sunil Jaswal
- Department of Human Genetics and Molecular Medicine Central University Punjab, Bathinda, 151401, India
| | - Sunil Kumar
- Amity Institute of Biotechnology, Amity University Rajasthan, SP-1, Kant Kalwar, RIICO Industrial Area, NH-11C, Jaipur, Rajasthan, 303002, India
| | - Pushpender Kumar Sharma
- Amity Institute of Biotechnology, Amity University Rajasthan, SP-1, Kant Kalwar, RIICO Industrial Area, NH-11C, Jaipur, Rajasthan, 303002, India.
- Amity Centre for Nanobiotechnology and Nanomedicine, Amity University Rajasthan, SP-1, Kant Kalwar, RIICO Industrial Area, NH-11C, Jaipur, Rajasthan, 303002, India.
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11
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Tkachev A, Stekolshchikova E, Golubova A, Serkina A, Morozova A, Zorkina Y, Riabinina D, Golubeva E, Ochneva A, Savenkova V, Petrova D, Andreyuk D, Goncharova A, Alekseenko I, Kostyuk G, Khaitovich P. Screening for depression in the general population through lipid biomarkers. EBioMedicine 2024; 110:105455. [PMID: 39571307 PMCID: PMC11617895 DOI: 10.1016/j.ebiom.2024.105455] [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: 03/25/2024] [Revised: 10/29/2024] [Accepted: 10/31/2024] [Indexed: 12/08/2024] Open
Abstract
BACKGROUND Anxiety and depression significantly contribute to the overall burden of mental disorders, with depression being one of the leading causes of disability. Despite this, no biochemical test has been implemented for the diagnosis of these mental disorders, while recent studies have highlighted lipids as potential biomarkers. METHODS Using a streamlined high-throughput lipidome analysis method, direct-infusion mass spectrometry, we evaluated blood plasma lipid levels in 604 individuals from a general urban population and analysed their association with self-reported anxiety and depression symptoms. We also assessed lipidome profiles in 32 patients with clinical depression, matched to 21 healthy controls. FINDINGS We found a significant correlation between lipid abundances and the severity of self-reported depression symptoms. Moreover, lipid alterations detected in high scoring volunteers mirrored the lipidome profiles identified in patients with clinical depression included in our study. Based on these findings, we developed a lipid-based predictive model distinguishing individuals reporting severe depressive symptoms from non-depressed subjects with high accuracy. INTERPRETATION This study demonstrates the possibility of generalizing lipid alterations from a clinical cohort to the general population and underscores the potential of lipid-based biomarkers in assessing depressive states. FUNDING This study was sponsored by the Moscow Center for Innovative Technologies in Healthcare, №2707-2, №2102-11.
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Affiliation(s)
- Anna Tkachev
- Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, 121205, Russia; LLC NeurOmix, Moscow, 119571, Russia
| | - Elena Stekolshchikova
- Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, 121205, Russia
| | - Anastasia Golubova
- Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, 121205, Russia
| | - Anna Serkina
- Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, 121205, Russia
| | - Anna Morozova
- Mental-health Clinic No. 1, Named After N.A. Alekseev, Moscow, 117152, Russia; Department of Basic and Applied Neurobiology, V. Serbsky Federal Medical Research Centre of Psychiatry and Narcology, 119034, Moscow, Russia
| | - Yana Zorkina
- Mental-health Clinic No. 1, Named After N.A. Alekseev, Moscow, 117152, Russia; Department of Basic and Applied Neurobiology, V. Serbsky Federal Medical Research Centre of Psychiatry and Narcology, 119034, Moscow, Russia
| | - Daria Riabinina
- Mental-health Clinic No. 1, Named After N.A. Alekseev, Moscow, 117152, Russia
| | - Elizaveta Golubeva
- Mental-health Clinic No. 1, Named After N.A. Alekseev, Moscow, 117152, Russia
| | - Aleksandra Ochneva
- Mental-health Clinic No. 1, Named After N.A. Alekseev, Moscow, 117152, Russia; Department of Basic and Applied Neurobiology, V. Serbsky Federal Medical Research Centre of Psychiatry and Narcology, 119034, Moscow, Russia
| | - Valeria Savenkova
- Mental-health Clinic No. 1, Named After N.A. Alekseev, Moscow, 117152, Russia
| | - Daria Petrova
- Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, 121205, Russia
| | - Denis Andreyuk
- Mental-health Clinic No. 1, Named After N.A. Alekseev, Moscow, 117152, Russia; Economy Faculty, M.V. Lomonosov Moscow State University, 119991, Moscow, Russia
| | - Anna Goncharova
- Moscow Center for Healthcare Innovations, Moscow, 123473, Russia
| | - Irina Alekseenko
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Science, Moscow Region, 142290, Russia
| | - Georgiy Kostyuk
- Mental-health Clinic No. 1, Named After N.A. Alekseev, Moscow, 117152, Russia.
| | - Philipp Khaitovich
- Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, 121205, Russia; LLC NeurOmix, Moscow, 119571, Russia.
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12
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Zinellu A, Tommasi S, Carru C, Sotgia S, Mangoni AA. A systematic review and meta-analysis of nitric oxide-associated arginine metabolites in schizophrenia. Transl Psychiatry 2024; 14:439. [PMID: 39414767 PMCID: PMC11484908 DOI: 10.1038/s41398-024-03157-7] [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: 06/24/2023] [Revised: 10/07/2024] [Accepted: 10/09/2024] [Indexed: 10/18/2024] Open
Abstract
There is increasing interest in the pathophysiological role of arginine metabolism in schizophrenia, particularly in relation to the modulation of the endogenous messenger nitric oxide (NO). The assessment of specific arginine metabolites that, unlike NO, are stable can provide useful insights into NO regulatory enzymes such as isoform 1 of dimethylarginine dimethylaminohydrolase (DDAH1) and arginase. We investigated the role of arginine metabolomics in schizophrenia by conducting a systematic review and meta-analysis of the circulating concentrations of arginine metabolites associated with DDAH1, arginase, and NO synthesis [arginine, citrulline, asymmetric dimethylarginine (ADMA), symmetric dimethylarginine (SDMA), dimethylamine, and ornithine] in this patient group. We searched PubMed, Scopus, and Web of Science from inception to the 31st of May 2023 for studies investigating arginine metabolites in patients with schizophrenia and healthy controls. The JBI Critical Appraisal Checklist for analytical studies and GRADE were used to assess the risk of bias and the certainty of evidence, respectively (PROSPERO registration number: CRD42023433000). Twenty-one studies were identified for analysis. There were no significant between-group differences in arginine, citrulline, and SDMA. By contrast, patients with schizophrenia had significantly higher ADMA (DDAH1 substrate, standard mean difference, SMD = 1.23, 95% CI 0.86-1.61, p < 0.001; moderate certainty of evidence), dimethylamine (DDAH1 product, SMD = 0.47, 95% CI 0.24-0.70, p < 0.001; very low certainty of evidence), and ornithine concentrations (arginase product, SMD = 0.32, 95% CI 0.16-0.49, p < 0.001; low certainty of evidence). In subgroup analysis, the pooled SMD for ornithine was significantly different in studies of untreated, but not treated, patients. Our study suggests that DDAH1 and arginase are dysregulated in schizophrenia. Further studies are warranted to investigate the expression/activity of these enzymes in the brain of patients with schizophrenia and the effects of targeted treatments.
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Affiliation(s)
- Angelo Zinellu
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy
| | - Sara Tommasi
- Department of Clinical Pharmacology, Flinders Medical Centre, Southern Adelaide Local Health Network, Adelaide, SA, Australia
| | - Ciriaco Carru
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy
- Quality Control Unit, University Hospital of Sassari (AOU), Sassari, Italy
| | - Salvatore Sotgia
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy
| | - Arduino A Mangoni
- Department of Clinical Pharmacology, Flinders Medical Centre, Southern Adelaide Local Health Network, Adelaide, SA, Australia.
- Discipline of Clinical Pharmacology, College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia.
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13
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Varathan A, Senthooran S, Jeyananthan P. Role of different omics data in the diagnosis of schizophrenia disorder: A machine learning study. Schizophr Res 2024; 271:38-46. [PMID: 39003990 DOI: 10.1016/j.schres.2024.07.026] [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: 12/05/2023] [Revised: 06/19/2024] [Accepted: 07/07/2024] [Indexed: 07/16/2024]
Abstract
Schizophrenia is a serious mental disorder that affects millions of people worldwide. This disorder slowly disintegrates thinking ability and changes behaviours of patients. These patients will show some psychotic symptoms such as hallucinations, delusions, thought disorder and movement disorder. These symptoms are in common with some other psychiatric disorders such as bipolar disorder, major depressive disorder and mood spectrum disorder. As patients would require immediate treatment, an on-time diagnosis is critical. This study explores the use of omics data in diagnosis of schizophrenia. Transcriptome, miRNA and epigenome data are used in diagnosis of patients with schizophrenia with the aid of machine learning algorithms. As the data is in high dimension, mutual information and feature importance are independently used for selecting relevant features for the study. Selected sets of features (biomarkers) are individually used with different machine learning algorithms and their performances are compared to select the best-performing model. This study shows that the top 140 miRNA features selected using mutual information along with support vector machines give the highest accuracy (0.86 ± 0.07) in the diagnosis of schizophrenia. All reported accuracies are validated using 5-fold cross validation. They are further validated using leave one out cross validation and the accuracies are reported in the supplementary material.
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Affiliation(s)
- Aarthy Varathan
- Department of Computer Engineering, Faculty of Engineering, University of Jaffna, Sri Lanka.
| | | | - Pratheeba Jeyananthan
- Department of Computer Engineering, Faculty of Engineering, University of Jaffna, Sri Lanka.
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14
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Wu S, Panganiban KJ, Lee J, Li D, Smith EC, Maksyutynska K, Humber B, Ahmed T, Agarwal SM, Ward K, Hahn M. Peripheral Lipid Signatures, Metabolic Dysfunction, and Pathophysiology in Schizophrenia Spectrum Disorders. Metabolites 2024; 14:475. [PMID: 39330482 PMCID: PMC11434505 DOI: 10.3390/metabo14090475] [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: 07/21/2024] [Revised: 08/19/2024] [Accepted: 08/21/2024] [Indexed: 09/28/2024] Open
Abstract
Metabolic dysfunction is commonly observed in schizophrenia spectrum disorders (SSDs). The causes of metabolic comorbidity in SSDs are complex and include intrinsic or biological factors linked to the disorder, which are compounded by antipsychotic (AP) medications. The exact mechanisms underlying SSD pathophysiology and AP-induced metabolic dysfunction are unknown, but dysregulated lipid metabolism may play a role. Lipidomics, which detects lipid metabolites in a biological sample, represents an analytical tool to examine lipid metabolism. This systematic review aims to determine peripheral lipid signatures that are dysregulated among individuals with SSDs (1) with minimal exposure to APs and (2) during AP treatment. To accomplish this goal, we searched MEDLINE, Embase, and PsychINFO databases in February 2024 to identify all full-text articles written in English where the authors conducted lipidomics in SSDs. Lipid signatures reported to significantly differ in SSDs compared to controls or in relation to AP treatment and the direction of dysregulation were extracted as outcomes. We identified 46 studies that met our inclusion criteria. Most of the lipid metabolites that significantly differed in minimally AP-treated patients vs. controls comprised glycerophospholipids, which were mostly downregulated. In the AP-treated group vs. controls, the significantly different metabolites were primarily fatty acyls, which were dysregulated in conflicting directions between studies. In the pre-to-post AP-treated patients, the most impacted metabolites were glycerophospholipids and fatty acyls, which were found to be primarily upregulated and conflicting, respectively. These lipid metabolites may contribute to SSD pathophysiology and metabolic dysfunction through various mechanisms, including the modulation of inflammation, cellular membrane permeability, and metabolic signaling pathways.
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Affiliation(s)
- Sally Wu
- Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, ON M6J 1H3, Canada (T.A.)
- Institute of Medical Sciences, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Kristoffer J. Panganiban
- Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, ON M6J 1H3, Canada (T.A.)
- Institute of Medical Sciences, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Jiwon Lee
- Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, ON M6J 1H3, Canada (T.A.)
- Institute of Medical Sciences, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Dan Li
- Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, ON M6J 1H3, Canada (T.A.)
| | - Emily C.C. Smith
- Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, ON M6J 1H3, Canada (T.A.)
- Institute of Medical Sciences, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Kateryna Maksyutynska
- Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, ON M6J 1H3, Canada (T.A.)
- Institute of Medical Sciences, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Bailey Humber
- Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, ON M6J 1H3, Canada (T.A.)
- Institute of Medical Sciences, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Tariq Ahmed
- Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, ON M6J 1H3, Canada (T.A.)
- Institute of Medical Sciences, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Sri Mahavir Agarwal
- Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, ON M6J 1H3, Canada (T.A.)
- Institute of Medical Sciences, University of Toronto, Toronto, ON M5T 1R8, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
- Banting and Best Diabetes Centre, University of Toronto, Toronto, ON M5G 2C4,Canada
| | - Kristen Ward
- Clinical Pharmacy Department, College of Pharmacy, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Pharmacy, Michigan Medicine Health System, Ann Arbor, MI 48109, USA
| | - Margaret Hahn
- Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, ON M6J 1H3, Canada (T.A.)
- Institute of Medical Sciences, University of Toronto, Toronto, ON M5T 1R8, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
- Banting and Best Diabetes Centre, University of Toronto, Toronto, ON M5G 2C4,Canada
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15
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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 PMCID: PMC11089724 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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16
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Yin B, Cai Y, Teng T, Wang X, Liu X, Li X, Wang J, Wu H, He Y, Ren F, Kou T, Zhu ZJ, Zhou X. Identifying plasma metabolic characteristics of major depressive disorder, bipolar disorder, and schizophrenia in adolescents. Transl Psychiatry 2024; 14:163. [PMID: 38531835 DOI: 10.1038/s41398-024-02886-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 03/14/2024] [Accepted: 03/19/2024] [Indexed: 03/28/2024] Open
Abstract
Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are classified as major mental disorders and together account for the second-highest global disease burden, and half of these patients experience symptom onset in adolescence. Several studies have reported both similar and unique features regarding the risk factors and clinical symptoms of these three disorders. However, it is still unclear whether these disorders have similar or unique metabolic characteristics in adolescents. We conducted a metabolomics analysis of plasma samples from adolescent healthy controls (HCs) and patients with MDD, BD, and SCZ. We identified differentially expressed metabolites between patients and HCs. Based on the differentially expressed metabolites, correlation analysis, metabolic pathway analysis, and potential diagnostic biomarker identification were conducted for disorders and HCs. Our results showed significant changes in plasma metabolism between patients with these mental disorders and HCs; the most distinct changes were observed in SCZ patients. Moreover, the metabolic differences in BD patients shared features with those in both MDD and SCZ, although the BD metabolic profile was closer to that of MDD than to SCZ. Additionally, we identified the metabolites responsible for the similar and unique metabolic characteristics in multiple metabolic pathways. The similar significant differences among the three disorders were found in fatty acid, steroid-hormone, purine, nicotinate, glutamate, tryptophan, arginine, and proline metabolism. Interestingly, we found unique characteristics of significantly altered glycolysis, glycerophospholipid, and sphingolipid metabolism in SCZ; lysine, cysteine, and methionine metabolism in MDD and BD; and phenylalanine, tyrosine, and aspartate metabolism in SCZ and BD. Finally, we identified five panels of potential diagnostic biomarkers for MDD-HC, BD-HC, SCZ-HC, MDD-SCZ, and BD-SCZ comparisons. Our findings suggest that metabolic characteristics in plasma vary across psychiatric disorders and that critical metabolites provide new clues regarding molecular mechanisms in these three psychiatric disorders.
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Affiliation(s)
- Bangmin Yin
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yuping Cai
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China
| | - Teng Teng
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xiaolin Wang
- Health Management Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xueer Liu
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xuemei Li
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Jie Wang
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Hongyan Wu
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yuqian He
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Fandong Ren
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China
| | - Tianzhang Kou
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China
| | - Zheng-Jiang Zhu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China.
- Shanghai Key Laboratory of Aging Studies, Shanghai, China.
| | - Xinyu Zhou
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
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17
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Boiko DI, Chopra H, Bilal M, Kydon PV, Herasymenko LO, Rud VO, Bodnar LA, Vasylyeva GY, Isakov RI, Zhyvotovska LV, Mehta A, Skrypnikov AM. Schizophrenia and disruption of circadian rhythms: An overview of genetic, metabolic and clinical signs. Schizophr Res 2024; 264:58-70. [PMID: 38101179 DOI: 10.1016/j.schres.2023.12.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 07/15/2023] [Accepted: 12/05/2023] [Indexed: 12/17/2023]
Abstract
A molecular clock in the suprachiasmatic nucleus of the anterior hypothalamus, which is entrained by the dark-light cycle and controls the sleep-wake cycle, regulates circadian rhythms. The risk of developing mental disorders, such as schizophrenia, has long been linked to sleep abnormalities. Additionally, a common aspect of mental disorders is sleep disturbance, which has a direct impact on the intensity of the symptoms and the quality of life of the patient. This relationship can be explained by gene alterations such as CLOCK in schizophrenia which are also important components of the physiological circadian rhythm. The function of dopamine and adenosine in circadian rhythm should also be noted, as these hypotheses are considered to be the most popular theories explaining schizophrenia pathogenesis. Therefore, determining the presence of a causal link between the two can be key to identifying new potential targets in schizophrenia therapy, which can open new avenues for clinical research as well as psychiatric care. We review circadian disruption in schizophrenia at the genetic, metabolic, and clinical levels. We summarize data about clock and clock-controlled genes' alterations, neurotransmitter systems' impairments, and association with chronotype in schizophrenia patients. Our findings demonstrate that in schizophrenia either homeostatic or circadian processes of sleep regulation are disturbed. Also, we found an insufficient number of studies aimed at studying the relationship between known biological phenomena of circadian disorders and clinical signs of schizophrenia.
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Affiliation(s)
- Dmytro I Boiko
- Department of Psychiatry, Narcology and Medical Psychology, Poltava State Medical University, Poltava, Ukraine.
| | - Hitesh Chopra
- Department of Biosciences, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai-602105, Tamil Nadu, India
| | - Muhammad Bilal
- College of Pharmacy, Liaquat University of Medical and Health Sciences, Jamshoro, Pakistan
| | - Pavlo V Kydon
- Department of Psychiatry, Narcology and Medical Psychology, Poltava State Medical University, Poltava, Ukraine
| | - Larysa O Herasymenko
- Department of Psychiatry, Narcology and Medical Psychology, Poltava State Medical University, Poltava, Ukraine
| | - Vadym O Rud
- Department of Psychiatry, Narcology and Medical Psychology, Poltava State Medical University, Poltava, Ukraine
| | - Lesia A Bodnar
- Department of Psychiatry, Narcology and Medical Psychology, Poltava State Medical University, Poltava, Ukraine
| | - Ganna Yu Vasylyeva
- Department of Psychiatry, Narcology and Medical Psychology, Poltava State Medical University, Poltava, Ukraine
| | - Rustam I Isakov
- Department of Psychiatry, Narcology and Medical Psychology, Poltava State Medical University, Poltava, Ukraine
| | - Liliia V Zhyvotovska
- Department of Psychiatry, Narcology and Medical Psychology, Poltava State Medical University, Poltava, Ukraine
| | - Aashna Mehta
- University of Debrecen, Faculty of Medicine, Debrecen, Hungary
| | - Andrii M Skrypnikov
- Department of Psychiatry, Narcology and Medical Psychology, Poltava State Medical University, Poltava, Ukraine
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18
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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; (V.U.); (A.O.); (A.T.); (O.A.); (V.S.); (I.M.); (D.R.); (G.K.); (A.M.)
- 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; (V.U.); (A.O.); (A.T.); (O.A.); (V.S.); (I.M.); (D.R.); (G.K.); (A.M.)
- 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; (V.U.); (A.O.); (A.T.); (O.A.); (V.S.); (I.M.); (D.R.); (G.K.); (A.M.)
- 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; (V.U.); (A.O.); (A.T.); (O.A.); (V.S.); (I.M.); (D.R.); (G.K.); (A.M.)
| | - Olga Abramova
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (V.U.); (A.O.); (A.T.); (O.A.); (V.S.); (I.M.); (D.R.); (G.K.); (A.M.)
- 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; (V.U.); (A.O.); (A.T.); (O.A.); (V.S.); (I.M.); (D.R.); (G.K.); (A.M.)
| | - 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; (V.U.); (A.O.); (A.T.); (O.A.); (V.S.); (I.M.); (D.R.); (G.K.); (A.M.)
| | - Daria Riabinina
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (V.U.); (A.O.); (A.T.); (O.A.); (V.S.); (I.M.); (D.R.); (G.K.); (A.M.)
| | - Georgy Kostyuk
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (V.U.); (A.O.); (A.T.); (O.A.); (V.S.); (I.M.); (D.R.); (G.K.); (A.M.)
| | - Anna Morozova
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (V.U.); (A.O.); (A.T.); (O.A.); (V.S.); (I.M.); (D.R.); (G.K.); (A.M.)
- 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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19
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Burghardt KJ, Kajy M, Ward KM, Burghardt PR. Metabolomics, Lipidomics, and Antipsychotics: A Systematic Review. Biomedicines 2023; 11:3295. [PMID: 38137517 PMCID: PMC10741000 DOI: 10.3390/biomedicines11123295] [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: 11/08/2023] [Revised: 12/06/2023] [Accepted: 12/09/2023] [Indexed: 12/24/2023] Open
Abstract
Antipsychotics are an important pharmacotherapy option for the treatment of many mental illnesses. Unfortunately, selecting antipsychotics is often a trial-and-error process due to a lack of understanding as to which medications an individual patient will find most effective and best tolerated. Metabolomics, or the study of small molecules in a biosample, is an increasingly used omics platform that has the potential to identify biomarkers for medication efficacy and toxicity. This systematic review was conducted to identify metabolites and metabolomic pathways associated with antipsychotic use in humans. Ultimately, 42 studies were identified for inclusion in this review, with all but three studies being performed in blood sources such as plasma or serum. A total of 14 metabolite classes and 12 lipid classes were assessed across studies. Although the studies were highly heterogeneous in approach and mixed in their findings, increases in phosphatidylcholines, decreases in carboxylic acids, and decreases in acylcarnitines were most consistently noted as perturbed in patients exposed to antipsychotics. Furthermore, for the targeted metabolomic and lipidomic studies, seven metabolites and three lipid species had findings that were replicated. The most consistent finding for targeted studies was an identification of a decrease in aspartate with antipsychotic treatment. Studies varied in depth of detail provided for their study participants and in study design. For example, in some cases, there was a lack of detail on specific antipsychotics used or concomitant medications, and the depth of detail on sample handling and analysis varied widely. The conclusions here demonstrate that there is a large foundation of metabolomic work with antipsychotics that requires more complete reporting so that an objective synthesis such as a meta-analysis can take place. This will then allow for validation and clinical application of the most robust findings to move the field forward. Future studies should be carefully controlled to take advantage of the sensitivity of metabolomics while limiting potential confounders that may result from participant heterogeneity and varied analysis approaches.
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Affiliation(s)
- Kyle J. Burghardt
- Department of Pharmacy Practice, Eugene Applebaum College of Pharmacy and Health Sciences, Wayne State University Detroit, Detroit, MI 48201, USA;
| | - Megan Kajy
- Department of Pharmacy Practice, Eugene Applebaum College of Pharmacy and Health Sciences, Wayne State University Detroit, Detroit, MI 48201, USA;
| | - Kristen M. Ward
- Department of Clinical Pharmacy, College of Pharmacy, University of Michigan Ann Arbor, Detroit, MI 48109, USA;
| | - Paul R. Burghardt
- Department of Nutrition and Food Science, Wayne State University Detroit, Detroit, MI 48201, USA;
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20
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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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21
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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: 22] [Impact Index Per Article: 11.0] [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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22
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Ma Q, Gao F, Zhou L, Fan Y, Zhao B, Xi W, Wang C, Zhu F, Ma X, Wang W, Wang Y. Characterizing serum amino acids in schizophrenic patients: Correlations with gut microbes. J Psychiatr Res 2022; 153:125-133. [PMID: 35810602 DOI: 10.1016/j.jpsychires.2022.07.006] [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: 03/06/2022] [Revised: 06/02/2022] [Accepted: 07/01/2022] [Indexed: 10/17/2022]
Abstract
Amino acid abnormalities have been suggested to be a key pathophysiological mechanism in schizophrenia (SZ). Recently, gut microbes were found to be critically involved in mental and metabolic diseases. However, the relationship between serum amino acid levels and gut microbes in SZ is rarely studied. Here, we analyzed serum amino acid levels in 76 untreated SZ patients and 79 healthy controls (HC). Serum levels of 10 amino acids were significantly altered in patients with SZ. We further classified the cut-off values for serum arginine, leucine, glutamine, and methionine levels to distinguish SZ patients from controls. These classifiers were shown to be effective in another validation cohort (49 SZ and 48 HC). The correlation between serum amino acids and clinical symptoms and cognitive functions was also analyzed. Arginine, leucine, glutamine, and methionine levels were significantly correlated with clinical symptoms and cognitive impairments in SZ patients. By metagenome shotgun sequencing of fecal samples, we found that patients with SZ with a low level of serum amino acids have higher richness and evenness of the gut microbiota. At the genus level, the abundances of Mitsuokella and Oscillibacter are significantly abnormal. At the mOTU level, 15 mOTUs in the low-level SZ group were significantly different from the HC group. In addition, Mitsuokella multacida was correlated with glutamine and methionine, respectively. Our research revealed that alterations in serum amino acid levels are critically related to changes in gut microbiota composition in SZ patients. These findings may shed light on new strategies for the diagnosis and treatment of SZ.
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Affiliation(s)
- Qingyan Ma
- Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Clinical Research Center for Psychiatric Medicine of Shaanxi Province, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China
| | - Fengjie Gao
- Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Clinical Research Center for Psychiatric Medicine of Shaanxi Province, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China
| | - Lina Zhou
- Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Clinical Research Center for Psychiatric Medicine of Shaanxi Province, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China
| | - Yajuan Fan
- Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Clinical Research Center for Psychiatric Medicine of Shaanxi Province, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China
| | - Binbin Zhao
- Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Clinical Research Center for Psychiatric Medicine of Shaanxi Province, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China
| | - Wenyu Xi
- Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Clinical Research Center for Psychiatric Medicine of Shaanxi Province, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China
| | - Chuyao Wang
- Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Clinical Research Center for Psychiatric Medicine of Shaanxi Province, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China
| | - Feng Zhu
- Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Clinical Research Center for Psychiatric Medicine of Shaanxi Province, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Center for Translational Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China
| | - Xiancang Ma
- Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Clinical Research Center for Psychiatric Medicine of Shaanxi Province, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China
| | - Wei Wang
- Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Clinical Research Center for Psychiatric Medicine of Shaanxi Province, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China.
| | - Yunpeng Wang
- Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China; Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Xi'an, 710061, China.
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23
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Yue W, Huang H, Duan J. Potential diagnostic biomarkers for schizophrenia. MEDICAL REVIEW (BERLIN, GERMANY) 2022; 2:385-416. [PMID: 37724326 PMCID: PMC10388817 DOI: 10.1515/mr-2022-0009] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 06/20/2022] [Indexed: 09/20/2023]
Abstract
Schizophrenia (SCH) is a complex and severe mental disorder with high prevalence, disability, mortality and carries a heavy disease burden, the lifetime prevalence of SCH is around 0.7%-1.0%, which has a profound impact on the individual and society. In the clinical practice of SCH, key problems such as subjective diagnosis, experiential treatment, and poor overall prognosis are still challenging. In recent years, some exciting discoveries have been made in the research on objective biomarkers of SCH, mainly focusing on genetic susceptibility genes, metabolic indicators, immune indices, brain imaging, electrophysiological characteristics. This review aims to summarize the biomarkers that may be used for the prediction and diagnosis of SCH.
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Affiliation(s)
- Weihua Yue
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, China
- National Clinical Research Center for Mental Disorders & NHC Key Laboratory of Mental Health (Peking University) and Chinese Academy of Medical Sciences Research Unit, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Hailiang Huang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Jubao Duan
- Center for Psychiatric Genetics, NorthShore University Health System, Evanston, IL, USA
- Department of Psychiatry and Behavioral Neurosciences, University of Chicago, Chicago, IL, USA
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24
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Kuan PF, Yang X, Kotov R, Clouston S, Bromet E, Luft BJ. Metabolomics analysis of post-traumatic stress disorder symptoms in World Trade Center responders. Transl Psychiatry 2022; 12:174. [PMID: 35484105 PMCID: PMC9050707 DOI: 10.1038/s41398-022-01940-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 04/14/2022] [Accepted: 04/20/2022] [Indexed: 11/08/2022] Open
Abstract
Metabolomics has yielded promising insights into the pathophysiology of post-traumatic stress disorder (PTSD). The current study expands understanding of the systems-level effects of metabolites by using global metabolomics and complex lipid profiling in plasma samples from 124 World Trade Center responders (56 PTSD, 68 control) on 1628 metabolites. Differential metabolomics analysis identified hexosylceramide HCER(26:1) associated with PTSD at FDR < 0.1. The multi-metabolite composite score achieved an AUC of 0.839 for PTSD versus unaffected control classification. Independent component analysis identified three metabolomic modules significantly associated with PTSD. These modules were significantly enriched in bile acid metabolism, fatty acid metabolism and pregnenolone steroids, which are involved in innate immunity, inflammatory process and neuronal excitability, respectively. Integrative analysis of metabolomics and our prior proteomics datasets on subsample of 96 responders identified seven proteomic modules significantly correlated with metabolic modules. Overall, our findings shed light on the molecular alterations and identify metabolomic-proteomic signatures associated with PTSD by using machine learning and network approaches to enhance understanding of the pathways implicated in PTSD. If present results are confirmed in follow-up studies, they may inform development of novel treatments.
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Affiliation(s)
- Pei-Fen Kuan
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA.
| | - Xiaohua Yang
- Department of Medicine, Stony Brook University, Stony Brook, NY, USA
| | - Roman Kotov
- Department of Psychiatry, Stony Book University, Stony Brook, NY, USA
| | - Sean Clouston
- Department of Family, Population and Preventive Medicine, Stony Book University, Stony Brook, NY, USA
| | - Evelyn Bromet
- Department of Psychiatry, Stony Book University, Stony Brook, NY, USA
| | - Benjamin J Luft
- Department of Medicine, Stony Brook University, Stony Brook, NY, USA.
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25
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Kim S, Okazaki S, Otsuka I, Shinko Y, Horai T, Shimmyo N, Hirata T, Yamaki N, Tanifuji T, Boku S, Sora I, Hishimoto A. Searching for biomarkers in schizophrenia and psychosis: Case-control study using capillary electrophoresis and liquid chromatography time-of-flight mass spectrometry and systematic review for biofluid metabolites. Neuropsychopharmacol Rep 2022; 42:42-51. [PMID: 34889082 PMCID: PMC8919119 DOI: 10.1002/npr2.12223] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 11/20/2021] [Accepted: 11/27/2021] [Indexed: 11/10/2022] Open
Abstract
Metabolomics has been attracting attention in recent years as an objective method for diagnosing schizophrenia. In this study, we analyzed 378 metabolites in the serum of schizophrenia patients using capillary electrophoresis- and liquid chromatography-time-of-flight mass spectrometry. Using multivariate analysis with the orthogonal partial least squares method, we observed significantly higher levels of alanine, glutamate, lactic acid, ornithine, and serine and significantly lower levels of urea, in patients with chronic schizophrenia compared to healthy controls. Additionally, levels of fatty acids (15:0), (17:0), and (19:1), cis-11-eicosenoic acid, and thyroxine were significantly higher in patients with acute psychosis than in those in remission. Moreover, we conducted a systematic review of comprehensive metabolomics studies on schizophrenia over the last 20 years and observed consistent trends of increase in some metabolites such as glutamate and glucose, and decrease in citrate in schizophrenia patients across several studies. Hence, we provide substantial evidence for metabolic biomarkers in schizophrenia patients through our metabolomics study.
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Affiliation(s)
- Saehyeon Kim
- Department of PsychiatryKobe University Graduate School of MedicineKobeJapan
| | - Satoshi Okazaki
- Department of PsychiatryKobe University Graduate School of MedicineKobeJapan
| | - Ikuo Otsuka
- Department of PsychiatryKobe University Graduate School of MedicineKobeJapan
| | - Yutaka Shinko
- Department of PsychiatryKobe University Graduate School of MedicineKobeJapan
| | - Tadasu Horai
- Department of PsychiatryKobe University Graduate School of MedicineKobeJapan
| | - Naofumi Shimmyo
- Department of PsychiatryKobe University Graduate School of MedicineKobeJapan
| | - Takashi Hirata
- Department of PsychiatryKobe University Graduate School of MedicineKobeJapan
| | - Naruhisa Yamaki
- Department of PsychiatryKobe University Graduate School of MedicineKobeJapan
| | - Takaki Tanifuji
- Department of PsychiatryKobe University Graduate School of MedicineKobeJapan
| | - Shuken Boku
- Department of PsychiatryKobe University Graduate School of MedicineKobeJapan
- Department of NeuropsychiatryFaculty of Life SciencesKumamoto UniversityKumamotoJapan
| | - Ichiro Sora
- Department of PsychiatryKobe University Graduate School of MedicineKobeJapan
| | - Akitoyo Hishimoto
- Department of PsychiatryKobe University Graduate School of MedicineKobeJapan
- Department of PsychiatryYokohama City University Graduate School of MedicineYokohamaJapan
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26
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Serum Metabolomic Analysis of Male Patients with Cannabis or Amphetamine Use Disorder. Metabolites 2022; 12:metabo12020179. [PMID: 35208253 PMCID: PMC8879674 DOI: 10.3390/metabo12020179] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 02/01/2022] [Accepted: 02/08/2022] [Indexed: 02/04/2023] Open
Abstract
Studies have demonstrated that chronic consumption of abused drugs induces alterations in several proteins that regulate metabolism. For instance, methamphetamine exposure reduces glucose levels. Fatty and amino acid levels were altered in groups exposed to abused drugs. Therefore, in our study, we investigated the serum metabolomic profile of patients diagnosed with cannabis and/or amphetamine use disorders. Blood was obtained from subjects (control, amphetamine, and cannabis). Detection of serum metabolites was performed using gas chromatography. The ratio peak areas for metabolites were analyzed across the three groups. Both cannabis and amphetamine groups showed higher d-erythrotetrafuranose, octadecanoic acid, hexadecenoic acid, trans-9-octadecanoic acid, lactic acid and methyl thio hydantoin metabolites compared with the control group. Moreover, cannabis patients were found to possess higher glycine, 9,12 octadecanoic acid malonic acid, phosphoric acid and prostaglandin F1a than controls. Our analysis showed that the identified metabolic profile of cannabis or amphetamine use disorder patients was different than control group. Our data indicated that chronic exposure to cannabis or amphetamine dysregulated metabolites in the serum. Future studies are warranted to explore the effects of these abused drugs on the metabolic proteins.
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27
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Liang Y, Shi X, Shen Y, Huang Z, Wang J, Shao C, Chu Y, Chen J, Yu J, Kang Y. Enhanced intestinal protein fermentation in schizophrenia. BMC Med 2022; 20:67. [PMID: 35135531 PMCID: PMC8827269 DOI: 10.1186/s12916-022-02261-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Accepted: 01/17/2022] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Emerging findings highlighted the associations of mental illness to nutrition and dysbiosis in the intestinal microbiota, but the underlying mechanisms, especially in schizophrenia (SZ), remain unclarified. METHODS We conducted a case-control study of SZ patients (case to control=100:52) by performing sequencing of the gut metagenome; measurement of fecal and plasma non-targeted metabolome; including short-, medium-, and long-chain fatty acids; and targeted metabolites, along with recorded details of daily intakes of food. RESULTS The metagenome analysis uncovered enrichment of asaccharolytic species and reduced abundance of carbohydrate catabolism pathways and enzymes in the gut of SZ patients, but increased abundance of peptidases in contrast to their significantly reduced protein intake. Fecal metabolome analysis identified increased concentrations of many protein catabolism products, including amino acids (AAs), urea, branched short-chain fatty acids, and various nitrogenous derivates of aromatic AAs in SZ patients. Protein synthesis, represented by the abundance of AA-biosynthesis pathways and aminoacyl-tRNA transferases in metagenome, was significantly decreased. The AUCs (area under the curve) of the diagnostic random forest models based on their abundance achieved 85% and 91%, respectively. The fecal levels of AA-fermentative enzymes and products uniformly showed positive correlations with the severity of psychiatric symptoms. CONCLUSIONS Our findings revealed apparent dysbiosis in the intestinal microbiome of SZ patients, where microbial metabolism is dominated by protein fermentation and shift from carbohydrate fermentation and protein synthesis in healthy conditions. The aberrant macronutrient metabolism by gut microbes highlights the importance of nutrition care and the potential for developing microbiota-targeted therapeutics in SZ.
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Affiliation(s)
- Ying Liang
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Xing Shi
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China.,The First Affiliated Hospital (Shenzhen People's Hospital), Southern University of Science and Technology, Shenzhen, 518055, China
| | - Yang Shen
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Zhuoran Huang
- School of Life Sciences, Huaibei Normal University, Huaibei, ,235000, Anhui, China
| | - Jian Wang
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China.,China National Center for Bioinformation, Beijing, 100101, China
| | - Changjun Shao
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China.,China National Center for Bioinformation, Beijing, 100101, China
| | - Yanan Chu
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China.,China National Center for Bioinformation, Beijing, 100101, China
| | - Jing Chen
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China.,China National Center for Bioinformation, Beijing, 100101, China
| | - Jun Yu
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China.,China National Center for Bioinformation, Beijing, 100101, China.,University of Chinese Academy of Sciences, No.19 Yuquan Road, Shijingshan District, Beijing, 100049, China
| | - Yu Kang
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China. .,China National Center for Bioinformation, Beijing, 100101, China.
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28
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Ferguson LB, Roberts AJ, Mayfield RD, Messing RO. Blood and brain gene expression signatures of chronic intermittent ethanol consumption in mice. PLoS Comput Biol 2022; 18:e1009800. [PMID: 35176017 PMCID: PMC8853518 DOI: 10.1371/journal.pcbi.1009800] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 01/03/2022] [Indexed: 02/03/2023] Open
Abstract
Alcohol Use Disorder (AUD) is a chronic, relapsing syndrome diagnosed by a heterogeneous set of behavioral signs and symptoms. There are no laboratory tests that provide direct objective evidence for diagnosis. Microarray and RNA-Seq technologies enable genome-wide transcriptome profiling at low costs and provide an opportunity to identify biomarkers to facilitate diagnosis, prognosis, and treatment of patients. However, access to brain tissue in living patients is not possible. Blood contains cellular and extracellular RNAs that provide disease-relevant information for some brain diseases. We hypothesized that blood gene expression profiles can be used to diagnose AUD. We profiled brain (prefrontal cortex, amygdala, and hypothalamus) and blood gene expression levels in C57BL/6J mice using RNA-seq one week after chronic intermittent ethanol (CIE) exposure, a mouse model of alcohol dependence. We found a high degree of preservation (rho range: [0.50, 0.67]) between blood and brain transcript levels. There was small overlap between blood and brain DEGs, and considerable overlap of gene networks perturbed after CIE related to cell-cell signaling (e.g., GABA and glutamate receptor signaling), immune responses (e.g., antigen presentation), and protein processing / mitochondrial functioning (e.g., ubiquitination, oxidative phosphorylation). Blood gene expression data were used to train classifiers (logistic regression, random forest, and partial least squares discriminant analysis), which were highly accurate at predicting alcohol dependence status (maximum AUC: 90.1%). These results suggest that gene expression profiles from peripheral blood samples contain a biological signature of alcohol dependence that can discriminate between CIE and Air subjects.
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Affiliation(s)
- Laura B. Ferguson
- Waggoner Center for Alcohol and Addiction Research, University of Texas at Austin, Austin, Texas, United States of America
- Department of Neurology, Dell Medical School, University of Texas at Austin, Austin, Texas, United States of America
- Department of Neuroscience, University of Texas at Austin, Austin, Texas, United States of America
| | - Amanda J. Roberts
- Animal Models Core Facility, The Scripps Research Institute, San Diego, California, United States of America
| | - R. Dayne Mayfield
- Waggoner Center for Alcohol and Addiction Research, University of Texas at Austin, Austin, Texas, United States of America
- Department of Neuroscience, University of Texas at Austin, Austin, Texas, United States of America
| | - Robert O. Messing
- Waggoner Center for Alcohol and Addiction Research, University of Texas at Austin, Austin, Texas, United States of America
- Department of Neurology, Dell Medical School, University of Texas at Austin, Austin, Texas, United States of America
- Department of Neuroscience, University of Texas at Austin, Austin, Texas, United States of America
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29
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Lin C, Hu Q, Dong J, Wei Z, Li J, Chen Z. Serum metabolic signatures of schizophrenia patients complicated with hepatitis B virus infection: A 1H NMR-based metabolomics study. Front Psychiatry 2022; 13:998709. [PMID: 36620683 PMCID: PMC9810819 DOI: 10.3389/fpsyt.2022.998709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 11/30/2022] [Indexed: 12/24/2022] Open
Abstract
INTRODUCTION Schizophrenia (SZ) is a severe chronic mental disorder with increased risk of hepatitis B virus (HBV) infection, which is incurable currently and induces various negative emotions and psychological pressures in patients to exacerbate mental disorders. To facilitate the therapeutic design for SZ patients complicated with HBV infection (SZ + HBV), it is helpful to first elucidate the metabolic perturbations in SZ + HBV patients. METHODS In this study, metabolic profiles of the serum samples from four groups of participants comprising healthy controls (HC, n = 72), HBV infection (n = 52), SZ patients (n = 37), and SZ + HBV (n = 41) patients were investigated using a high-resolution 1H NMR-based metabolomics approach. RESULTS AND DISCUSSION Distinguishable metabolic profiles were found in the four groups. In comparison with HC, HBV infection induced increased levels of citrate and succinate to perturbate the tricarboxylic acid cycle and succinate-related pathways. Similar to SZ cases, SZ + HBV patients exhibited decreased glucose but increased citrate, pyruvate, and lactate, suggesting the occurrence of disturbance in glucose metabolism. Moreover, in comparison with HC, several serum amino acid levels in SZ + HBV patients were significantly altered. Our findings suggest that Warburg effect, energy metabolism disorders, neurotransmitter metabolism abnormalities, mitochondrial dysfunction and several disturbed pathways in relation to tyrosine and choline appear to play specific and central roles in the pathophysiology of SZ + HBV. Apart from replicating metabolic alterations induced by SZ and HBV separately (e.g., in energy metabolism and Warburg effect), the specific metabolic abnormalities in the SZ + HBV group (e.g., several tyrosine- and choline-related pathways) highlighted the existence of a synergistic action between SZ and HBV pathologies. Current study revealed the metabolic alterations specific to the interaction between SZ and HBV pathologies, and may open important perspectives for designing precise therapies for SZ + HBV patients beyond the simple combination of two individual treatments.
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Affiliation(s)
- Caigui Lin
- Fujian Provincial Key Laboratory for Plasma and Magnetic Resonance, Department of Electronic Science, Xiamen University, Xiamen, Fujian, China.,National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, Fujian, China
| | - Qing Hu
- Xiamen Xianyue Hospital, Xiamen, Fujian, China
| | - Jiyang Dong
- Fujian Provincial Key Laboratory for Plasma and Magnetic Resonance, Department of Electronic Science, Xiamen University, Xiamen, Fujian, China
| | - Zhiliang Wei
- Department of Radiology, Johns Hopkins University, Baltimore, MD, United States
| | - Jie Li
- Department of Hepatobiliary Surgery, Zhongshan Hospital of Xiamen University, Xiamen, Fujian, China
| | - Zhong Chen
- Fujian Provincial Key Laboratory for Plasma and Magnetic Resonance, Department of Electronic Science, Xiamen University, Xiamen, Fujian, China
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Li Z, Zhang T, Xu L, Wei Y, Cui H, Tang Y, Liu X, Qian Z, Zhang H, Liu P, Li C, Wang J. Plasma metabolic alterations and potential biomarkers in individuals at clinical high risk for psychosis. Schizophr Res 2022; 239:19-28. [PMID: 34800912 DOI: 10.1016/j.schres.2021.11.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 10/21/2021] [Accepted: 11/08/2021] [Indexed: 01/10/2023]
Abstract
BACKGROUND Early identification and treatment of clinical high-risk for psychosis (CHRP) are critical to prevent the onset of psychosis, but there is no objective biomarker for CHR-P diagnosis. METHODS Ninety medication naïve CHR-P subjects and eighty-six healthy controls (HCs) were recruited. The metabolic profiles of plasma samples were acquired using an untargeted metabolomics approach based on ultra-high-performance liquid chromatography equipped with quadrupole time-of-flight mass spectrometry. The obtained data were further mapped on the Kyoto Encyclopedia of Genes and Genomes for pathway analysis, and an ensemble learning method was applied to identify diagnostic biomarkers. Bayesian linear regression model was then used to explore predicative biomarkers of conversion to psychosis. Receiver-operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic or predicative value of potential biomarkers. RESULTS A total of one hundred and four differential metabolites and forty-eight differential pathways were identified. A panel of five metabolites was found that could effectively discriminate CHR-P from HCs with area under the ROC curve of 1 in the training set (70% of the samples) and 0.997 in the testing set (30% of the samples). The biosynthesis of unsaturated fatty acids pathway perturbed most significantly in CHR-P subjects. Twenty-three CHR-P subjects converted to psychotic disorders during two-year follow-up, and increased 1-stearoyl-2-arachidonoyl-sn-glycerol in plasma was potentially associated with the higher risk of conversion to psychosis. CONCLUSIONS These findings demonstrate the alterations of plasma metabolic profiles in CHR-P population, which may deliver valuable biomarkers for early identification and outcome prediction of CHR-P.
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Affiliation(s)
- Zhixing Li
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
| | - Tianhong Zhang
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China.
| | - Lihua Xu
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
| | - Yanyan Wei
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
| | - Huiru Cui
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
| | - Yingying Tang
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
| | - Xiaohua Liu
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
| | - Zhenying Qian
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
| | - Hu Zhang
- School of Pharmacy, Brain Health Research Centre, Brain Research New Zealand, University of Otago, Dunedin, New Zealand
| | - Ping Liu
- Department of Anatomy, School of Biomedical Sciences, Brain Health Research Centre, Brain Research New Zealand, University of Otago, Dunedin, New Zealand.
| | - Chunbo Li
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
| | - Jijun Wang
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China; CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, Shanghai 200031, PR China; Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai 200030, PR China.
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Avigdor BE, Yang K, Shinder I, Orsburn BC, Rais R, Kano SI, Sawa A, Pevsner J. Characterization of antipsychotic medications, amino acid signatures, and platelet-activating factor in first-episode psychosis. Biomark Neuropsychiatry 2021. [DOI: 10.1016/j.bionps.2021.100045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
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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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Wagh VV, Vyas P, Agrawal S, Pachpor TA, Paralikar V, Khare SP. Peripheral Blood-Based Gene Expression Studies in Schizophrenia: A Systematic Review. Front Genet 2021; 12:736483. [PMID: 34721526 PMCID: PMC8548640 DOI: 10.3389/fgene.2021.736483] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 08/31/2021] [Indexed: 12/19/2022] Open
Abstract
Schizophrenia is a disorder that is characterized by delusions, hallucinations, disorganized speech or behavior, and socio-occupational impairment. The duration of observation and variability in symptoms can make the accurate diagnosis difficult. Identification of biomarkers for schizophrenia (SCZ) can help in early diagnosis, ascertaining the diagnosis, and development of effective treatment strategies. Here we review peripheral blood-based gene expression studies for identification of gene expression biomarkers for SCZ. A literature search was carried out in PubMed and Web of Science databases for blood-based gene expression studies in SCZ. A list of differentially expressed genes (DEGs) was compiled and analyzed for overlap with genetic markers, differences based on drug status of the participants, functional enrichment, and for effect of antipsychotics. This literature survey identified 61 gene expression studies. Seventeen out of these studies were based on expression microarrays. A comparative analysis of the DEGs (n = 227) from microarray studies revealed differences between drug-naive and drug-treated SCZ participants. We found that of the 227 DEGs, 11 genes (ACOT7, AGO2, DISC1, LDB1, RUNX3, SIGIRR, SLC18A1, NRG1, CHRNB2, PRKAB2, and ZNF74) also showed genetic and epigenetic changes associated with SCZ. Functional enrichment analysis of the DEGs revealed dysregulation of proline and 4-hydroxyproline metabolism. Also, arginine and proline metabolism was the most functionally enriched pathway for SCZ in our analysis. Follow-up studies identified effect of antipsychotic treatment on peripheral blood gene expression. Of the 27 genes compiled from the follow-up studies AKT1, DISC1, HP, and EIF2D had no effect on their expression status as a result of antipsychotic treatment. Despite the differences in the nature of the study, ethnicity of the population, and the gene expression analysis method used, we identified several coherent observations. An overlap, though limited, of genetic, epigenetic and gene expression changes supports interplay of genetic and environmental factors in SCZ. The studies validate the use of blood as a surrogate tissue for biomarker analysis. We conclude that well-designed cohort studies across diverse populations, use of high-throughput sequencing technology, and use of artificial intelligence (AI) based computational analysis will significantly improve our understanding and diagnostic capabilities for this complex disorder.
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Affiliation(s)
- Vipul Vilas Wagh
- Symbiosis School of Biological Sciences, Symbiosis International (Deemed University), Pune, India
| | - Parin Vyas
- Symbiosis School of Biological Sciences, Symbiosis International (Deemed University), Pune, India
| | - Suchita Agrawal
- The Psychiatry Unit, KEM Hospital and KEM Hospital Research Centre, Pune, India
| | | | - Vasudeo Paralikar
- The Psychiatry Unit, KEM Hospital and KEM Hospital Research Centre, Pune, India
| | - Satyajeet P Khare
- Symbiosis School of Biological Sciences, Symbiosis International (Deemed University), Pune, India
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Ong SK, Husain SF, Wee HN, Ching J, Kovalik JP, Cheng MS, Schwarz H, Tang TB, Ho CS. Integration of the Cortical Haemodynamic Response Measured by Functional Near-Infrared Spectroscopy and Amino Acid Analysis to Aid in the Diagnosis of Major Depressive Disorder. Diagnostics (Basel) 2021; 11:1978. [PMID: 34829325 PMCID: PMC8617819 DOI: 10.3390/diagnostics11111978] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 10/22/2021] [Accepted: 10/22/2021] [Indexed: 01/02/2023] Open
Abstract
BACKGROUND Major depressive disorder (MDD) is a debilitating condition with a high disease burden and medical comorbidities. There are currently few to no validated biomarkers to guide the diagnosis and treatment of MDD. In the present study, we evaluated the differences between MDD patients and healthy controls (HCs) in terms of cortical haemodynamic responses during a verbal fluency test (VFT) using functional near-infrared spectroscopy (fNIRS) and serum amino acid profiles, and ascertained if these parameters were correlated with clinical characteristics. METHODS Twenty-five (25) patients with MDD and 25 age-, gender-, and ethnicity-matched HCs were recruited for the study. Real-time monitoring of the haemodynamic response during completion of a VFT was quantified using a 52-channel NIRS system. Serum samples were analysed and quantified by liquid chromatography-mass spectrometry for amino acid profiling. Receiver-operating characteristic (ROC) curves were used to classify potential candidate biomarkers. RESULTS The MDD patients had lower prefrontal and temporal activation during completion of the VFT than HCs. The MDD patients had lower mean concentrations of oxy-Hb in the left orbitofrontal cortex (OFC), and lower serum histidine levels. When the oxy-haemoglobin response was combined with the histidine concentration, the sensitivity and specificity of results improved significantly from 66.7% to 73.3% and from 65.0% to 90.0% respectively, as compared to results based only on the NIRS response. CONCLUSIONS These findings demonstrate the use of combination biomarkers to aid in the diagnosis of MDD. This technique could be a useful approach to detect MDD with greater precision, but additional studies are required to validate the methodology.
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Affiliation(s)
- Samantha K. Ong
- Department of Psychological Medicine, National University Health System, Singapore 119228, Singapore;
| | - Syeda F. Husain
- Institute for Health Innovation and Technology (iHealthtech), National University of Singapore, Singapore 119276, Singapore;
| | - Hai Ning Wee
- Cardiovascular and Metabolic Disorders Programme, Duke-NUS Graduate Medical School, Singapore 169609, Singapore; (H.N.W.); (J.C.); (J.-P.K.)
| | - Jianhong Ching
- Cardiovascular and Metabolic Disorders Programme, Duke-NUS Graduate Medical School, Singapore 169609, Singapore; (H.N.W.); (J.C.); (J.-P.K.)
| | - Jean-Paul Kovalik
- Cardiovascular and Metabolic Disorders Programme, Duke-NUS Graduate Medical School, Singapore 169609, Singapore; (H.N.W.); (J.C.); (J.-P.K.)
| | - Man Si Cheng
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117593, Singapore; (M.S.C.); (H.S.)
| | - Herbert Schwarz
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117593, Singapore; (M.S.C.); (H.S.)
| | - Tong Boon Tang
- Centre for Intelligent Signal and Imaging Research (CISIR), University Teknologi PETRONAS, Bandar Seri Iskandar 32610, Perak, Malaysia;
| | - Cyrus S. Ho
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
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Liu J, Xiu M, Liu H, Wang J, Li X. Plasma Lysophosphatidylcholine and Lysophosphatidylethanolamine Levels Were Associated With the Therapeutic Response to Olanzapine in Female Antipsychotics-naïve First-episode Patients With Schizophrenia. Front Pharmacol 2021; 12:735196. [PMID: 34603051 PMCID: PMC8481943 DOI: 10.3389/fphar.2021.735196] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 09/06/2021] [Indexed: 01/31/2023] Open
Abstract
Background: Accumulating studies have shown that the pathophysiology of schizophrenia may be associated with aberrant lysophospolipid metabolism in the early stage of brain development. Recent evidence demonstrates that antipsychotic medication can regulate the phospholipase activity. However, it remains unclear whether lysophospolipid is associated with the therapeutic response to antipsychotic medication in schizophrenia. This study aimed to investigate the influence of olanzapine monotherapy on lysophosphatidylcholine (LPC) and lysophosphatidylethanolamine (LPE) and the association between symptom improvement and changes of LPC and LPE levels during treatment in antipsychotic-naïve first-episode (ANFE) patients. Materials and Methods: The psychotic symptoms were evaluated by the Positive and Negative Syndrome Scale (PANSS). 25 ANFE patients were treated with olanzapine for 1 mo. The levels of LPC and LPE were determined and psychotic symptoms were assessed at baseline and at 1-mo follow-up. Results: Relative to baseline, the psychotic symptoms were significantly reduced after olanzapine treatment, except for negative symptoms. Moreover, the levels of most LPC and LPE increased after treatment. Interestingly, increased LPC(18:3) and LPC(20:2) levels were positively associated with the reduction rates of PANSS positive subscore. In addition, baseline levels of LPE(20:5), LPE(18:3) and LPE(22:5) were predictors for the reduction of positive symptoms. Conclusion: Our study reveals that the levels of lysophospolipid are associated with the improvement of positive symptoms, indicating that LPC may be a potential therapeutic target for olanzapine in schizophrenia. Moreover, baseline LPE levels were predictive biomarkers for the therapeutic response to olanzapine in the early stage of treatment in ANFE patients.
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Affiliation(s)
- Jiahong Liu
- The Affiliated Kangning Hospital of Wenzhou Medical University, Wenzhou, China
| | - Meihong Xiu
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, China
| | - Haixia Liu
- Department of Psychiatry, Shandong Mental Health Center, Jinan, China
| | - Jun Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, China
| | - Xirong Li
- Department of Psychiatry, Shandong Mental Health Center, Jinan, China
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Molina JD, Avila S, Rubio G, López-Muñoz F. Metabolomic connections between schizophrenia, antipsychotic drugs and metabolic syndrome: A variety of players. Curr Pharm Des 2021; 27:4049-4061. [PMID: 34348619 DOI: 10.2174/1381612827666210804110139] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 07/02/2021] [Indexed: 12/08/2022]
Abstract
BACKGROUND Diagnosis of schizophrenia lacks of reliable medical diagnostic tests and robust biomarkers applied to clinical practice. Schizophrenic patients undergoing treatment with antipsychotics suffer a reduced life expectancy due to metabolic disarrangements that co-exist with their mental illness and predispose them to develop metabolic syndrome, also exacerbated by medication. Metabolomics is an emerging and potent technology able to accelerate this biomedical research. <P> Aim: This review focus on a detailed vision of the molecular mechanisms involved both in schizophrenia and antipsychotic-induced metabolic syndrome, based on innovative metabolites that consistently change in nascent metabolic syndrome, drug-naïve, first episode psychosis and/or schizophrenic patients compared to healthy subjects. <P> Main lines: Supported by metabolomic approaches, although not exclusively, noteworthy variations are reported mainly through serum samples of patients and controls in several scenes: 1) alterations in fatty acids, inflammatory response indicators, amino acids and biogenic amines, biometals and gut microbiota metabolites (schizophrenia); 2) alterations in metabolites involved in carbohydrate and gut microbiota metabolism, inflammation and oxidative stress (metabolic syndrome), some of them shared with the schizophrenia scene; 3) alterations of cytokines secreted by adipose tissue, phosphatidylcholines, acylcarnitines, Sirtuin 1, orexin-A and changes in microbiota composition (antipsychotic-induced metabolic syndrome). <P> Conclusion: Novel insights into the pathogenesis of schizophrenia and metabolic side-effects associated to its antipsychotic treatment, represent an urgent request for scientifics and clinicians. Leptin, carnitines, adiponectin, insulin or interleukin-6 represent some examples of candidate biomarkers. Cutting-edge technologies like metabolomics have the power of strengthen research for achieving preventive, diagnostic and therapeutical solutions for schizophrenia.
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Affiliation(s)
- Juan D Molina
- Clinical Management Area of Psychiatry and Mental Health, Psychiatric Service, 12 de Octubre University Hospital, Madrid. Spain
| | - Sonia Avila
- Department of Psychiatry, Faculty of Medicine, Complutense University of Madrid. Spain
| | - Gabriel Rubio
- Clinical Management Area of Psychiatry and Mental Health, Psychiatric Service, 12 de Octubre University Hospital, Madrid. Spain
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Liu JH, Chen N, Guo YH, Guan XN, Wang J, Wang D, Xiu MH. Metabolomics-based understanding of the olanzapine-induced weight gain in female first-episode drug-naïve patients with schizophrenia. J Psychiatr Res 2021; 140:409-415. [PMID: 34144444 DOI: 10.1016/j.jpsychires.2021.06.001] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 05/30/2021] [Accepted: 06/04/2021] [Indexed: 12/22/2022]
Abstract
Previous studies have demonstrated that patients with schizophrenia (SZ) have greater rate of metabolic disorder as compared with the control population, which likely be the consequence of use of atypical antipsychotics. Olanzapine is a widely used antipsychotic, which increases the weight of SZ patients. However, the underlying mechanism remains poorly understood. Here we report the metabolomics-based understanding of the weight gain induced by olanzapine. 57 first-episode drug-naïve patients (FEDN) were recruited, of whom 27 patients completed a 4-week clinical trial. We then profiled the metabolomes of their plasma with the LC-MS-based nontargeted metabolomics approach at the baseline and after olanzapine monotherapy for 4 weeks. We observed that the plasma of the olanzapine-treated patient had significantly higher lysophosphatidylcholine (LysoPC), lysophosphatidylethanolamine (LysoPE) and lower carnitine as compared with that of the baseline plasma samples. Moreover, regression analyses indicated that the change of LysoPC(14:0) level was an independent contributor to the olanzapine-induced weight gain. Our study suggests that the metabolomics-based approach may facilitate the identification of biomarkers associated with the metabolic disorder causing by antipsychotic in schizophrenia patients.
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Affiliation(s)
- Jia Hong Liu
- The Affiliated Kangning Hospital of Wenzhou Medical University, Wenzhou, China
| | - Nan Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, China
| | - Yan Hong Guo
- Qingdao Mental Health Center, Qingdao University, Qingdao, China
| | - Xiao Ni Guan
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, China
| | - Jun Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, China
| | - Dong Wang
- Department of Clinical Psychology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
| | - Mei Hong Xiu
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, China.
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Altaf-Ul-Amin M, Hirose K, Nani JV, Porta LC, Tasic L, Hossain SF, Huang M, Ono N, Hayashi MAF, Kanaya S. A system biology approach based on metabolic biomarkers and protein-protein interactions for identifying pathways underlying schizophrenia and bipolar disorder. Sci Rep 2021; 11:14450. [PMID: 34262063 PMCID: PMC8280132 DOI: 10.1038/s41598-021-93653-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Accepted: 06/28/2021] [Indexed: 11/10/2022] Open
Abstract
Mental disorders (MDs), including schizophrenia (SCZ) and bipolar disorder (BD), have attracted special attention from scientists due to their high prevalence and significantly debilitating clinical features. The diagnosis of MDs is still essentially based on clinical interviews, and intensive efforts to introduce biochemical based diagnostic methods have faced several difficulties for implementation in clinics, due to the complexity and still limited knowledge in MDs. In this context, aiming for improving the knowledge in etiology and pathophysiology, many authors have reported several alterations in metabolites in MDs and other brain diseases. After potentially fishing all metabolite biomarkers reported up to now for SCZ and BD, we investigated here the proteins related to these metabolites in order to construct a protein-protein interaction (PPI) network associated with these diseases. We determined the statistically significant clusters in this PPI network and, based on these clusters, we identified 28 significant pathways for SCZ and BDs that essentially compose three groups representing three major systems, namely stress response, energy and neuron systems. By characterizing new pathways with potential to innovate the diagnosis and treatment of psychiatric diseases, the present data may also contribute to the proposal of new intervention for the treatment of still unmet aspects in MDs.
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Affiliation(s)
- Md Altaf-Ul-Amin
- Nara Institute of Science and Technology, Ikoma, Nara, 630-0192, Japan.
| | - Kazuhisa Hirose
- Nara Institute of Science and Technology, Ikoma, Nara, 630-0192, Japan
| | - João V Nani
- Department of Pharmacology, Escola Paulista de Medicina (EPM), Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil
- National Institute for Translational Medicine (INCT-TM, CNPq/FAPESP/CAPES), Ribeirão Preto, Brazil
| | - Lucas C Porta
- Department of Pharmacology, Escola Paulista de Medicina (EPM), Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil
| | - Ljubica Tasic
- Chemical Biology Laboratory, Department of Organic Chemistry, Institute of Chemistry, Universidade Estadual de Campinas (Unicamp), Campinas, SP, Brazil
| | | | - Ming Huang
- Nara Institute of Science and Technology, Ikoma, Nara, 630-0192, Japan
| | - Naoaki Ono
- Nara Institute of Science and Technology, Ikoma, Nara, 630-0192, Japan
| | - Mirian A F Hayashi
- Department of Pharmacology, Escola Paulista de Medicina (EPM), Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil.
- National Institute for Translational Medicine (INCT-TM, CNPq/FAPESP/CAPES), Ribeirão Preto, Brazil.
| | - Shigehiko Kanaya
- Nara Institute of Science and Technology, Ikoma, Nara, 630-0192, Japan
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Murgia F, Gagliano A, Tanca MG, Or-Geva N, Hendren A, Carucci S, Pintor M, Cera F, Cossu F, Sotgiu S, Atzori L, Zuddas A. Metabolomic Characterization of Pediatric Acute-Onset Neuropsychiatric Syndrome (PANS). Front Neurosci 2021; 15:645267. [PMID: 34121984 PMCID: PMC8194687 DOI: 10.3389/fnins.2021.645267] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 04/27/2021] [Indexed: 01/21/2023] Open
Abstract
Introduction PANS is a controversial clinical entity, consisting of a complex constellation of psychiatric symptoms, adventitious changes, and expression of various serological alterations, likely sustained by an autoimmune/inflammatory disease. Detection of novel biomarkers of PANS is highly desirable for both diagnostic and therapeutic management of affected patients. Analysis of metabolites has proven useful in detecting biomarkers for other neuroimmune-psychiatric diseases. Here, we utilize the metabolomics approach to determine whether it is possible to define a specific metabolic pattern in patients affected by PANS compared to healthy subjects. Design This observational case-control study tested consecutive patients referred for PANS between June 2019 to May 2020. A PANS diagnosis was confirmed according to the PANS working criteria (National Institute of Mental Health [NIMH], 2010). Healthy age and sex-matched subjects were recruited as controls. Methods Thirty-four outpatients referred for PANS (mean age 9.5 years; SD 2.9, 71% male) and 25 neurotypical subjects matched for age and gender, were subjected to metabolite analysis. Serum samples were obtained from each participant and were analyzed using Nuclear Magnetic Resonance (NMR) spectroscopy. Subsequently, multivariate and univariate statistical analyses and Receiver Operator Curves (ROC) were performed. Results Separation of the samples, in line with the presence of PANS diagnosis, was observed by applying a supervised model (R2X = 0.44, R2Y = 0.54, Q2 = 0.44, p-value < 0.0001). The significantly altered variables were 2-Hydroxybutyrate, glycine, glutamine, histidine, tryptophan. Pathway analysis indicated that phenylalanine, tyrosine, and tryptophan metabolism, as well as glutamine and glutamate metabolism, exhibited the largest deviations from neurotypical controls. Conclusion We found a unique plasma metabolic profile in PANS patients, significantly differing from that of healthy children, that suggests the involvement of specific patterns of neurotransmission (tryptophan, glycine, histamine/histidine) as well as a more general state of neuroinflammation and oxidative stress (glutamine, 2-Hydroxybutyrate, and tryptophan-kynurenine pathway) in the disorder. This metabolomics study offers new insights into biological mechanisms underpinning the disorder and supports research of other potential biomarkers implicated in PANS.
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Affiliation(s)
- Federica Murgia
- Clinical Metabolomics Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
| | - Antonella Gagliano
- Child and Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy.,Child and Adolescent Neuropsychiatry Unit, "A. Cao" Peditric Hosptal, "G. Brotzu" Hospital Trust, Cagliari, Italy
| | - Marcello G Tanca
- Child and Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
| | - Noga Or-Geva
- Interdepartmental Program in Immunology, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Aran Hendren
- Clinical Metabolomics Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy.,Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom
| | - Sara Carucci
- Child and Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy.,Child and Adolescent Neuropsychiatry Unit, "A. Cao" Peditric Hosptal, "G. Brotzu" Hospital Trust, Cagliari, Italy
| | - Manuela Pintor
- Child and Adolescent Neuropsychiatry Unit, "A. Cao" Peditric Hosptal, "G. Brotzu" Hospital Trust, Cagliari, Italy
| | - Francesca Cera
- Child and Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
| | - Fausto Cossu
- Paediatric Clinic, "A. Cao" Hospital, Cagliari, Italy
| | - Stefano Sotgiu
- Child Neuropsychiatry Unit, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy
| | - Luigi Atzori
- Clinical Metabolomics Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
| | - Alessandro Zuddas
- Child and Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy.,Child and Adolescent Neuropsychiatry Unit, "A. Cao" Peditric Hosptal, "G. Brotzu" Hospital Trust, Cagliari, Italy
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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: 4] [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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Correia BSB, Nani JV, Waladares Ricardo R, Stanisic D, Costa TBBC, Hayashi MAF, Tasic L. Effects of Psychostimulants and Antipsychotics on Serum Lipids in an Animal Model for Schizophrenia. Biomedicines 2021; 9:235. [PMID: 33652776 PMCID: PMC7996855 DOI: 10.3390/biomedicines9030235] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 02/01/2021] [Accepted: 02/02/2021] [Indexed: 02/06/2023] Open
Abstract
Schizophrenia (SCZ) treatment is essentially limited to the use of typical or atypical antipsychotic drugs, which suppress the main symptoms of this mental disorder. Metabolic syndrome is often reported in patients with SCZ under long-term drug treatment, but little is known about the alteration of lipid metabolism induced by antipsychotic use. In this study, we evaluated the blood serum lipids of a validated animal model for SCZ (Spontaneously Hypertensive Rat, SHR), and a normal control rat strain (Normotensive Wistar Rat, NWR), after long-term treatment (30 days) with typical haloperidol (HAL) or atypical clozapine (CLZ) antipsychotics. Moreover, psychostimulants, amphetamine (AMPH) or lisdexamfetamine (LSDX), were administered to NWR animals aiming to mimic the human first episode of psychosis, and the effects on serum lipids were also evaluated. Discrepancies in lipids between SHR and NWR animals, which included increased total lipids and decreased phospholipids in SHR compared with NWR, were similar to the differences previously reported for SCZ patients relative to healthy controls. Administration of psychostimulants in NWR decreased omega-3, which was also decreased in the first episode of psychosis of SCZ. Moreover, choline glycerophospholipids allowed us to distinguish the effects of CLZ in SHR. Thus, changes in the lipid metabolism in SHR seem to be reversed by the long-term treatment with the atypical antipsychotic CLZ, which was under the same condition described to reverse the SCZ-like endophenotypes of this validated animal model for SCZ. These data open new insights for understanding the potential influence of the treatment with typical or atypical antipsychotics on circulating lipids. This may represent an outcome effect from metabolic pathways that regulate lipids synthesis and breakdown, which may be reflecting a cell lipids dysfunction in SCZ.
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Affiliation(s)
- Banny Silva Barbosa Correia
- Instituto de Química, Universidade Estadual de Campinas (UNICAMP), Campinas 13083-970, Brazil; (B.S.B.C.); (R.W.R.); (D.S.); (T.B.B.C.C.)
| | - João Victor Nani
- Departamento de Farmacologia, Escola Paulista de Medicina (EPM), Universidade Federal de São Paulo (UNIFESP), São Paulo 04044-020, Brazil;
- National Institute for Translational Medicine (INCT-TM, CNPq), Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (FMRP-USP), São Paulo 14049-900, Brazil
| | - Raniery Waladares Ricardo
- Instituto de Química, Universidade Estadual de Campinas (UNICAMP), Campinas 13083-970, Brazil; (B.S.B.C.); (R.W.R.); (D.S.); (T.B.B.C.C.)
| | - Danijela Stanisic
- Instituto de Química, Universidade Estadual de Campinas (UNICAMP), Campinas 13083-970, Brazil; (B.S.B.C.); (R.W.R.); (D.S.); (T.B.B.C.C.)
| | | | - Mirian A. F. Hayashi
- Departamento de Farmacologia, Escola Paulista de Medicina (EPM), Universidade Federal de São Paulo (UNIFESP), São Paulo 04044-020, Brazil;
- National Institute for Translational Medicine (INCT-TM, CNPq), Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (FMRP-USP), São Paulo 14049-900, Brazil
| | - Ljubica Tasic
- Instituto de Química, Universidade Estadual de Campinas (UNICAMP), Campinas 13083-970, Brazil; (B.S.B.C.); (R.W.R.); (D.S.); (T.B.B.C.C.)
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Amino Acid and Acylcarnitine Levels in Chronic Patients with Schizophrenia: A Preliminary Study. Metabolites 2021; 11:metabo11010034. [PMID: 33466490 PMCID: PMC7824812 DOI: 10.3390/metabo11010034] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 12/29/2020] [Accepted: 12/31/2020] [Indexed: 11/16/2022] Open
Abstract
Amino acids and acylcarnitines play an important role as substrates and intermediate products in most of pathways involved in schizophrenia development such as mitochondrial dysfunction, inflammation, lipid oxidation, DNA damage, oxidative stress, and apoptosis. It seems relevant to use an integrated approach with 'omics' technology to study their contribution. The aim of our study was to investigate serum amino acid and acylcarnitine levels in antipsychotics-treated patients with chronic schizophrenia compared with healthy donors. We measured serum levels of 15 amino acids and 30 acylcarnitines in 37 patients with schizophrenia and 36 healthy donors by means of tandem mass spectrometry. In summary, patients with chronic schizophrenia had an altered concentration of a few amino acids and acylcarnitines in comparison to the healthy probands. Further research is needed to assess and understand the identified changes.
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Topology predicts long-term functional outcome in early psychosis. Mol Psychiatry 2021; 26:5335-5346. [PMID: 32632207 PMCID: PMC8589664 DOI: 10.1038/s41380-020-0826-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Revised: 06/05/2020] [Accepted: 06/17/2020] [Indexed: 12/02/2022]
Abstract
Early intervention in psychosis is crucial to improving patient response to treatment and the functional deficits that critically affect their long-term quality of life. Stratification tools are needed to personalize functional deficit prevention strategies at an early stage. In the present study, we applied topological tools to analyze symptoms of early psychosis patients, and detected a clear stratification of the cohort into three groups. One of the groups had a significantly better psychosocial outcome than the others after a 3-year clinical follow-up. This group was characterized by a metabolic profile indicative of an activated antioxidant response, while that of the groups with poorer outcome was indicative of oxidative stress. We replicated in a second cohort the finding that the three distinct clinical profiles at baseline were associated with distinct outcomes at follow-up, thus validating the predictive value of this new stratification. This approach could assist in personalizing treatment strategies.
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Liu L, Zhao J, Chen Y, Feng R. Metabolomics strategy assisted by transcriptomics analysis to identify biomarkers associated with schizophrenia. Anal Chim Acta 2020; 1140:18-29. [PMID: 33218480 DOI: 10.1016/j.aca.2020.09.054] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 09/16/2020] [Accepted: 09/25/2020] [Indexed: 12/12/2022]
Abstract
BACKGROUND Metabolomics strategy was perform to identify the novel serum biomarkers linked to schizophrenia with the assistance of transcriptomics analysis. METHODS Two analytical platforms, UPLC-Q-TOF MS/MS and 1H NMR, were used to acquire the serum fingerprinting profiles from a total of 112 participants (57 healthy controls and 55 schizophrenia patients). The differential metabolites were primarily selected after statistical analyses. Meanwhile, GSE17612 dataset downloaded from GEO database was implemented WGCNA analysis to discover crucial genes and corresponding biological processes. Based on metabolomics analysis, the metabolic distinctions were explored under the aid of transcriptomics. Then using Boruta algorithm identified the biomarkers, and LASSO regression analysis and Random Forest algorithm were used to evaluate the performance of the diagnostic model constructed by biomarkers selected. RESULTS A total of four metabolites (α-CEHC, neuraminic acid, glyceraldehyde and asparagine) were selected as the biomarkers to establish diagnosis model. The performance of this model showed a higher accuracy rate to distinguish schizophrenia patients from healthy controls (area under the receive operating characteristic curve, 0.992; precision recall curve, 1.000, the mean accuracy of random forest algorithm, 95.00%). CONCLUSIONS A four-biomarker model (α-CEHC, neuraminic acid, glyceraldehyde and asparagine) seems to be a good model for diagnosing schizophrenia patients. It might be helpful to guide the future studies on permitting early intervention designed to prevent disease progression.
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Affiliation(s)
- Liyan Liu
- Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, PR China
| | - Jinhui Zhao
- Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, PR China
| | - Yang Chen
- Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, PR China
| | - Rennan Feng
- Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, PR China.
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45
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Candidate metabolic biomarkers for schizophrenia in CNS and periphery: Do any possible associations exist? Schizophr Res 2020; 226:95-110. [PMID: 30935700 DOI: 10.1016/j.schres.2019.03.009] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Revised: 03/08/2019] [Accepted: 03/11/2019] [Indexed: 02/07/2023]
Abstract
Due to the limitations of analytical techniques and the complicity of schizophrenia, nowadays it is still a challenge to diagnose and stratify schizophrenia patients accurately. Many attempts have been made to identify and validate available biomarkers for schizophrenia from CSF and/or peripheral blood in clinical studies with consideration to disease stages, antipsychotic effects and even gender differences. However, conflicting results handicap the validation and application of biomarkers for schizophrenia. In view of availability and feasibility, peripheral biomarkers have superior advantages over biomarkers in CNS. Meanwhile, schizophrenia is considered to be a devastating neuropsychiatric disease mainly taking place in CNS featured by widespread defects in multiple metabolic pathways whose dynamic interactions, until recently, have been difficult to difficult to investigate. Evidence for these alterations has been collected piecemeal, limiting the potential to inform our understanding of the interactions among relevant biochemical pathways. Taken these points together, it will be interesting to investigate possible associations of biomarkers between CNS and periphery. Numerous studies have suggested putative correlations within peripheral and CNS systems especially for dopaminergic and glutamatergic metabolic biomarkers. In addition, it has been demonstrated that blood concentrations of BDNF protein can also reflect its changes in the nervous system. In turn, BDNF also interacts with glutamatergic, dopaminergic and serotonergic systems. Therefore, this review will summarize metabolic biomarkers identified both in the CNS (brain tissues and CSF) and peripheral blood. Further, more attentions will be paid to discussing possible physical and functional associations between CNS and periphery, especially with respect to BDNF.
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Lipidomics of the brain, retina, and biofluids: from the biological landscape to potential clinical application in schizophrenia. Transl Psychiatry 2020; 10:391. [PMID: 33168817 PMCID: PMC7653030 DOI: 10.1038/s41398-020-01080-1] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Revised: 06/08/2020] [Accepted: 06/10/2020] [Indexed: 01/10/2023] Open
Abstract
Schizophrenia is a serious neuropsychiatric disorder, yet a clear pathophysiology has not been identified. To date, neither the objective biomarkers for diagnosis nor specific medications for the treatment of schizophrenia are clinically satisfactory. It is well accepted that lipids are essential to maintain the normal structure and function of neurons in the brain and that abnormalities in neuronal lipids are associated with abnormal neurodevelopment in schizophrenia. However, lipids and lipid-like molecules have been largely unexplored in contrast to proteins and their genes in schizophrenia. Compared with the gene- and protein-centric approaches, lipidomics is a recently emerged and rapidly evolving research field with particular importance for the study of neuropsychiatric disorders such as schizophrenia, in which even subtle aberrant alterations in the lipid composition and concentration of the neurons may disrupt brain functioning. In this review, we aimed to highlight the lipidomics of the brain, retina, and biofluids in both human and animal studies, discuss aberrant lipid alterations in correlation with schizophrenia, and propose future directions from the biological landscape towards potential clinical applications in schizophrenia. Recent studies are in support of the concept that aberrations in some lipid species [e.g. phospholipids, polyunsaturated fatty acids (PUFAs)] lead to structural alterations and, in turn, impairments in the biological function of membrane-bound proteins, the disruption of cell signaling molecule accessibility, and the dysfunction of neurotransmitter systems. In addition, abnormal lipidome alterations in biofluids are linked to schizophrenia, and thus they hold promise in the discovery of biomarkers for the diagnosis of schizophrenia.
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47
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Du Y, Chen L, Li XS, Li XL, Xu XD, Tai SB, Yang GL, Tang Q, Liu H, Liu SH, Zhang SY, Cheng Y. Metabolomic Identification of Exosome-Derived Biomarkers for Schizophrenia: A Large Multicenter Study. Schizophr Bull 2020; 47:615-623. [PMID: 33159208 PMCID: PMC8084447 DOI: 10.1093/schbul/sbaa166] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Exosomes have been suggested as promising targets for the diagnosis and treatment of neurological diseases, including schizophrenia (SCZ), but the potential role of exosome-derived metabolites in these diseases was rarely studied. Using ultra-performance liquid chromatography-tandem mass spectrometry, we performed the first metabolomic study of serum-derived exosomes from patients with SCZ. Our sample comprised 385 patients and 332 healthy controls recruited from 3 clinical centers and 4 independent cohorts. We identified 25 perturbed metabolites in patients that can be used to classify samples from patients and control participants with 95.7% accuracy (95% CI: 92.6%-98.9%) in the training samples (78 patients and 66 controls). These metabolites also showed good to excellent performance in differentiating between patients and controls in the 3 test sets of participants, with accuracies 91.0% (95% CI: 85.7%-96.3%; 107 patients and 62 controls), 82.7% (95% CI: 77.6%-87.9%; 104 patients and 142 controls), and 99.0% (95% CI: 97.7%-100%; 96 patients and 62 controls), respectively. Bioinformatic analysis suggested that these metabolites were enriched in pathways implicated in SCZ, such as glycerophospholipid metabolism. Taken together, our findings support a role for exosomal metabolite dysregulation in the pathophysiology of SCZ and indicate a strong potential for exosome-derived metabolites to inform the diagnosis of SCZ.
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Affiliation(s)
- Yang Du
- Key Laboratory of Ethnomedicine of Ministry of Education, Center on Translational Neuroscience, School of Pharmacy, Minzu University of China, Beijing, China
| | - Lei Chen
- College of Life and Environmental Sciences, Minzu University of China, Beijing, China
| | - Xue-Song Li
- Department of Psychiatry, The Third People’s Hospital of Foshan, Foshan, Guangdong, China
| | - Xiao-Lin Li
- Department of Psychiatry, The Third People’s Hospital of Foshan, Foshan, Guangdong, China
| | - Xiang-Dong Xu
- Department of Psychiatry, Urumqi Fourth People’s Hospital, Urumqi, Xinjiang, China
| | - Shao-Bin Tai
- Department of Psychiatry, Huangshan Second People’s Hospital, Huangshan, An Hui, China
| | - Geng-Lin Yang
- Department of Psychiatry, Urumqi Fourth People’s Hospital, Urumqi, Xinjiang, China
| | - Quan Tang
- College of Life and Environmental Sciences, Minzu University of China, Beijing, China
| | - Hua Liu
- Key Laboratory of Ethnomedicine of Ministry of Education, Center on Translational Neuroscience, School of Pharmacy, Minzu University of China, Beijing, China
| | - Shu-Han Liu
- College of Life and Environmental Sciences, Minzu University of China, Beijing, China
| | - Shu-Yao Zhang
- College of Life and Environmental Sciences, Minzu University of China, Beijing, China
| | - Yong Cheng
- Key Laboratory of Ethnomedicine of Ministry of Education, Center on Translational Neuroscience, School of Pharmacy, Minzu University of China, Beijing, China,College of Life and Environmental Sciences, Minzu University of China, Beijing, China,NHC Key Laboratory of Birth Defect Research, Prevention, and Treatment, Hunan Provincial Maternal and Child Health-Care Hospital, Changsha, Hunan, China,To whom correspondence should be addressed; 27 South Zhongguancun Avenue, Beijing 100081, China; tel: 86-10-68931383, fax: 86-10-68936927, e-mail:
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48
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Paley EL. Discovery of Gut Bacteria Specific to Alzheimer's Associated Diseases is a Clue to Understanding Disease Etiology: Meta-Analysis of Population-Based Data on Human Gut Metagenomics and Metabolomics. J Alzheimers Dis 2020; 72:319-355. [PMID: 31561379 DOI: 10.3233/jad-190873] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Alzheimer's disease (AD)-associated sequence (ADAS) of cultured fecal bacteria was discovered in human gut targeted screening. This study provides important information to expand our current understanding of the structure/activity relationship of ADAS and putative inhibitors/activators that are potentially involved in ADAS appearance/disappearance. The NCBI database analysis revealed that ADAS presents at a large proportion in American Indian Oklahoman (C&A) with a high prevalence of obesity/diabetes and in colorectal cancer (CRC) patients from the US and China. An Oklahoman non-native group (NNI) showed no ADAS. Comparison of two large US populations reveals that ADAS is more frequent in individuals aged ≥66 and in females. Prevalence and levels of fecal metabolites are altered in the C&A and CRC groups versus controls. Biogenic amines (histamine, tryptamine, tyramine, phenylethylamine, cadaverine, putrescine, agmatine, spermidine) that present in food and are produced by gut microbiota are significantly higher in C&A (e.g., histamine/histidine 95-fold) versus NNI (histamine/histidine 16-fold). The majority of these bio-amines are cytotoxic at concentrations found in food. Inositol phosphate signaling implicated in AD is altered in C&A and CRC. Tryptamine stimulated accumulation of inositol phosphate. The seizure-eliciting tryptamine induced cytoplasmic vacuolization and vesiculation with cell fragmentation. Present additions of ADAS-carriers at different ages including infants led to an ADAS-comprising human sample size of 2,830 from 27 studies from four continents (North America, Australia, Asia, Europe). Levels of food-derived monoamine oxidase inhibitors and anti-bacterial compounds, the potential modulators of ADAS-bacteria growth and biogenic amine production, were altered in C&A versus NNI. ADAS is attributable to potentially modifiable risk factors of AD associated diseases.
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Affiliation(s)
- Elena L Paley
- Expert Biomed, Inc., Miami, FL, USA.,Stop Alzheimers Corp, Miami, FL, USA
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49
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Rajula HSR, Manchia M, Carpiniello B, Fanos V. Big data in severe mental illness: the role of electronic monitoring tools and metabolomics. Per Med 2020; 18:75-90. [PMID: 33124507 DOI: 10.2217/pme-2020-0033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
There is an increasing interest in the development of effective early detection and intervention strategies in severe mental illness (SMI). Ideally, these efforts should lead to the delineation of accurate staging models of SMI enabling personalized interventions. It is plausible that big data approaches will be instrumental in describing the developmental trajectories of SMI by facilitating the incorporation of data from multiple sources, including those pertaining to the biological make-up of affected subjects. In this review, we first aimed to offer a perspective on how big data are helping the delineation of personalized approaches in SMI, and, second, to offer a quantitative synthesis of big data approaches in metabolomics of SMI. We finally described future directions of this research area.
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Affiliation(s)
- Hema Sekhar Reddy Rajula
- Department of Surgical Sciences, Neonatal Intensive Care Unit, Neonatal Pathology & Neonatal Section, University of Cagliari, Cagliari, Italy
| | - Mirko Manchia
- Department of Medical Science & Public Health, Section of Psychiatry, University of Cagliari, Cagliari, Italy.,Department of Pharmacology, Dalhousie University, Halifax, Nova Scotia B3H4R2, Canada.,Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Bernardo Carpiniello
- Department of Medical Science & Public Health, Section of Psychiatry, University of Cagliari, Cagliari, Italy.,Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Vassilios Fanos
- Department of Surgical Sciences, Neonatal Intensive Care Unit, Neonatal Pathology & Neonatal Section, University of Cagliari, Cagliari, Italy
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50
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Metabolomics Community in Russia: History of Development, Key Participants, and Results. BIOTECH 2020; 9:biotech9040020. [PMID: 35822823 PMCID: PMC9258313 DOI: 10.3390/biotech9040020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2020] [Revised: 10/18/2020] [Accepted: 10/21/2020] [Indexed: 12/05/2022] Open
Abstract
Metabolomics is the latest trend in the “-omics” sciences, of which technologies are widely used today in all life sciences. Metabolomics gave impetus to the description of biochemical processes that occur in many organisms, search for new biomarkers of disease, and laid the foundation for new clinical laboratory diagnostics. The purpose of this review is to show how metabolomics is represented in Russian science, what main research areas were chosen, and to demonstrate the successes and main achievements of Russian scientists in this field. The review is dedicated to the 10th anniversary of Russian metabolomics and also touches on the history of the formation of Russian metabolomics and prospects for the future.
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