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Ye J, Chen H, Wang Y, Chen H, Huang J, Yang Y, Feng Z, Li W. A preliminary metabolomics study of the database for biological samples of schizophrenia among Chinese ethnic minorities. BMC Psychiatry 2024; 24:262. [PMID: 38594695 PMCID: PMC11003042 DOI: 10.1186/s12888-024-05660-z] [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: 01/07/2024] [Accepted: 03/05/2024] [Indexed: 04/11/2024] Open
Abstract
BACKGROUND Schizophrenia (SCZ) is a profound mental disorder with a multifactorial etiology, including genetics, environmental factors, and demographic influences such as ethnicity and geography. Among these, the studies of SCZ also shows racial and regional differences. METHODS We first established a database of biological samples for SCZ in China's ethnic minorities, followed by a serum metabolomic analysis of SCZ patients from various ethnic groups within the same region using the LC-HRMS platform. RESULTS Analysis identified 47 metabolites associated with SCZ, with 46 showing significant differences between Miao and Han SCZ patients. These metabolites, primarily fatty acids, amino acids, benzene, and derivatives, are involved in fatty acid metabolism pathways. Notably, L-Carnitine, L-Cystine, Aspartylphenylalanine, and Methionine sulfoxide demonstrated greater diagnostic efficacy in Miao SCZ patients compared to Han SCZ patients. CONCLUSION Preliminary findings suggest that there are differences in metabolic levels among SCZ patients of different ethnicities in the same region, offering insights for developing objective diagnostic or therapeutic monitoring strategies that incorporate ethnic considerations of SCZ.
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Affiliation(s)
- Jun Ye
- Department of Clinical Laboratory, The Second Affiliated Hospital of Guizhou Medical University, 556000, Guizhou, China
| | - Haixia Chen
- Department of Clinical Biochemistry and Laboratory Medicine, Guizhou Medical University, 550001, Guizhou, China
| | - Yang Wang
- Shandong Yingsheng Biotechnology Co., Ltd., 250101, Jinan, Shandong, China
| | - Haini Chen
- Department of Clinical Laboratory, The Second Affiliated Hospital of Guizhou Medical University, 556000, Guizhou, China
| | - Jiang Huang
- Department of Psychiatry, The Second Affiliated Hospital of Guizhou Medical University, Kangfu Road, 556000, Guizhou, China
| | - Yixia Yang
- Department of Clinical Laboratory, The Second Affiliated Hospital of Guizhou Medical University, 556000, Guizhou, China
| | - Zhen Feng
- Shandong Yingsheng Biotechnology Co., Ltd., 250101, Jinan, Shandong, China.
| | - Wenfeng Li
- Department of Psychiatry, The Second Affiliated Hospital of Guizhou Medical University, Kangfu Road, 556000, Guizhou, China.
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Krzyściak W, Szwajca M, Śmierciak N, Chrzan R, Turek A, Karcz P, Bryll A, Pilecki M, Morava E, Ligęzka A, Kozicz T, Mazur P, Batko B, Skalniak A, Popiela T. From periphery immunity to central domain through clinical interview as a new insight on schizophrenia. Sci Rep 2024; 14:5755. [PMID: 38459093 PMCID: PMC10923880 DOI: 10.1038/s41598-024-56344-3] [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: 11/18/2023] [Accepted: 03/05/2024] [Indexed: 03/10/2024] Open
Abstract
Identifying disease predictors through advanced statistical models enables the discovery of treatment targets for schizophrenia. In this study, a multifaceted clinical and laboratory analysis was conducted, incorporating magnetic resonance spectroscopy with immunology markers, psychiatric scores, and biochemical data, on a cohort of 45 patients diagnosed with schizophrenia and 51 healthy controls. The aim was to delineate predictive markers for diagnosing schizophrenia. A logistic regression model was used, as utilized to analyze the impact of multivariate variables on the prevalence of schizophrenia. Utilization of a stepwise algorithm yielded a final model, optimized using Akaike's information criterion and a logit link function, which incorporated eight predictors (White Blood Cells, Reactive Lymphocytes, Red Blood Cells, Glucose, Insulin, Beck Depression score, Brain Taurine, Creatine and Phosphocreatine concentration). No single factor can reliably differentiate between healthy patients and those with schizophrenia. Therefore, it is valuable to simultaneously consider the values of multiple factors and classify patients using a multivariate model.
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Affiliation(s)
- Wirginia Krzyściak
- Department of Medical Diagnostic, Faculty of Pharmacy, Jagiellonian University Medical College, 30-688, Krakow, Poland.
| | - Marta Szwajca
- Department of Child and Adolescent Psychiatry, Faculty of Medicine, Jagiellonian University Medical College, 31-501, Krakow, Poland
| | - Natalia Śmierciak
- Department of Child and Adolescent Psychiatry, Faculty of Medicine, Jagiellonian University Medical College, 31-501, Krakow, Poland
| | - Robert Chrzan
- Department of Radiology, Faculty of Medicine, Jagiellonian University Medical College, 31-503, Krakow, Poland
| | - Aleksander Turek
- Department of Child and Adolescent Psychiatry, Faculty of Medicine, Jagiellonian University Medical College, 31-501, Krakow, Poland
| | - Paulina Karcz
- Department of Electroradiology, Faculty of Health Sciences, Jagiellonian University Medical College, 31-126, Krakow, Poland
| | - Amira Bryll
- Department of Radiology, Faculty of Medicine, Jagiellonian University Medical College, 31-503, Krakow, Poland
| | - Maciej Pilecki
- Department of Child and Adolescent Psychiatry, Faculty of Medicine, Jagiellonian University Medical College, 31-501, Krakow, Poland
| | - Eva Morava
- Department of Clinical Genomics, Mayo Clinic, Rochester, MN, USA
| | - Anna Ligęzka
- Department of Research Immunology, Mayo Clinic, Arizona, USA
| | - Tamas Kozicz
- Department of Clinical Genomics, Mayo Clinic, Rochester, MN, USA
| | - Paulina Mazur
- Department of Medical Diagnostic, Faculty of Pharmacy, Jagiellonian University Medical College, 30-688, Krakow, Poland
| | - Bogna Batko
- Department of Child and Adolescent Psychiatry, Faculty of Medicine, Jagiellonian University Medical College, 31-501, Krakow, Poland
| | - Anna Skalniak
- Division of Molecular Biology and Clinical Genetics, Department of Medicine, Jagiellonian University Medical College, Skawińska 8, 31-066, Krakow, Poland
| | - Tadeusz Popiela
- Department of Radiology, Faculty of Medicine, Jagiellonian University Medical College, 31-503, Krakow, Poland
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Krzyściak W, Bystrowska B, Karcz P, Chrzan R, Bryll A, Turek A, Mazur P, Śmierciak N, Szwajca M, Donicz P, Furman K, Pilato F, Kozicz T, Popiela T, Pilecki M. Association of Blood Metabolomics Biomarkers with Brain Metabolites and Patient-Reported Outcomes as a New Approach in Individualized Diagnosis of Schizophrenia. Int J Mol Sci 2024; 25:2294. [PMID: 38396971 PMCID: PMC10888632 DOI: 10.3390/ijms25042294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 02/06/2024] [Accepted: 02/10/2024] [Indexed: 02/25/2024] Open
Abstract
Given its polygenic nature, there is a need for a personalized approach to schizophrenia. The aim of the study was to select laboratory biomarkers from blood, brain imaging, and clinical assessment, with an emphasis on patients' self-report questionnaires. Metabolomics studies of serum samples from 51 patients and 45 healthy volunteers, based on the liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS/MS), led to the identification of 3 biochemical indicators (cortisol, glutamate, lactate) of schizophrenia. These metabolites were sequentially correlated with laboratory tests results, imaging results, and clinical assessment outcomes, including patient self-report outcomes. The hierarchical cluster analysis on the principal components (HCPC) was performed to identify the most homogeneous clinical groups. Significant correlations were noted between blood lactates and 11 clinical and 10 neuroimaging parameters. The increase in lactate and cortisol were significantly associated with a decrease in immunological parameters, especially with the level of reactive lymphocytes. The strongest correlations with the level of blood lactate and cortisol were demonstrated by brain glutamate, N-acetylaspartate and the concentrations of glutamate and glutamine, creatine and phosphocreatine in the prefrontal cortex. Metabolomics studies and the search for associations with brain parameters and self-reported outcomes may provide new diagnostic evidence to specific schizophrenia phenotypes.
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Affiliation(s)
- Wirginia Krzyściak
- Department of Medical Diagnostics, Jagiellonian University Medical College, Faculty of Pharmacy, 30-688 Krakow, Poland;
| | - Beata Bystrowska
- Department of Biochemical Toxicology, Jagiellonian University Medical College, Faculty of Pharmacy, 30-688 Krakow, Poland;
| | - Paulina Karcz
- Department of Electroradiology, Jagiellonian University Medical College, Faculty of Health Sciences, 31-126 Krakow, Poland;
| | - Robert Chrzan
- Department of Radiology, Jagiellonian University Medical College, Faculty of Medicine, 31-503 Krakow, Poland; (R.C.); (A.B.); (T.P.)
| | - Amira Bryll
- Department of Radiology, Jagiellonian University Medical College, Faculty of Medicine, 31-503 Krakow, Poland; (R.C.); (A.B.); (T.P.)
| | - Aleksander Turek
- Department of Child and Adolescent Psychiatry and Psychotherapy, Faculty of Medicine, Jagiellonian University Medical College, 31-501 Krakow, Poland; (A.T.); (N.Ś.); (M.S.); (P.D.); (K.F.); (M.P.)
| | - Paulina Mazur
- Department of Medical Diagnostics, Jagiellonian University Medical College, Faculty of Pharmacy, 30-688 Krakow, Poland;
| | - Natalia Śmierciak
- Department of Child and Adolescent Psychiatry and Psychotherapy, Faculty of Medicine, Jagiellonian University Medical College, 31-501 Krakow, Poland; (A.T.); (N.Ś.); (M.S.); (P.D.); (K.F.); (M.P.)
| | - Marta Szwajca
- Department of Child and Adolescent Psychiatry and Psychotherapy, Faculty of Medicine, Jagiellonian University Medical College, 31-501 Krakow, Poland; (A.T.); (N.Ś.); (M.S.); (P.D.); (K.F.); (M.P.)
| | - Paulina Donicz
- Department of Child and Adolescent Psychiatry and Psychotherapy, Faculty of Medicine, Jagiellonian University Medical College, 31-501 Krakow, Poland; (A.T.); (N.Ś.); (M.S.); (P.D.); (K.F.); (M.P.)
| | - Katarzyna Furman
- Department of Child and Adolescent Psychiatry and Psychotherapy, Faculty of Medicine, Jagiellonian University Medical College, 31-501 Krakow, Poland; (A.T.); (N.Ś.); (M.S.); (P.D.); (K.F.); (M.P.)
| | - Fabio Pilato
- Neurology, Neurophysiology and Neurobiology Unit, Department of Medicine, Università Campus Bio-Medico di Roma, 00128 Rome, Italy;
| | - Tamas Kozicz
- Department of Clinical Genomics, Center for Individualized Medicine, Mayo Clinic, Rochester, MN 55905, USA;
| | - Tadeusz Popiela
- Department of Radiology, Jagiellonian University Medical College, Faculty of Medicine, 31-503 Krakow, Poland; (R.C.); (A.B.); (T.P.)
| | - Maciej Pilecki
- Department of Child and Adolescent Psychiatry and Psychotherapy, Faculty of Medicine, Jagiellonian University Medical College, 31-501 Krakow, Poland; (A.T.); (N.Ś.); (M.S.); (P.D.); (K.F.); (M.P.)
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