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Chen J, Amdanee N, Zuo X, Wang Y, Gong M, Yang Y, Li H, Zhang X, Zhang C. Biomarkers of bipolar disorder based on metabolomics: A systematic review. J Affect Disord 2024; 350:492-503. [PMID: 38218254 DOI: 10.1016/j.jad.2024.01.033] [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: 05/22/2023] [Revised: 12/05/2023] [Accepted: 01/03/2024] [Indexed: 01/15/2024]
Abstract
Bipolar disorder (BD) is a severe affective disorder characterized by recurrent episodes of depression or mania/hypomania, which significantly impair cognitive function, life skills, and social abilities of patients. There is little understanding of the neurobiological mechanisms of BD. The diagnosis of BD is primarily based on clinical assessment and psychiatric examination, highlighting the urgent need for objective markers to facilitate the diagnosis of BD. Metabolomics can be used as a diagnostic tool for disease identification and evaluation. This study summarized the altered metabolites in BD and analyzed aberrant metabolic pathways, which might contribute to the diagnosis of BD. Search of PubMed and Web of science for human BD studies related to metabolism to identify articles published up to November 19, 2022 yielded 987 articles. After screening and applying the inclusion and exclusion criteria, 16 untargeted and 11 targeted metabolomics studies were included. Pathway analysis of the potential differential biometabolic markers was performed using the Kyoto encyclopedia of genes and genomes (KEGG). There were 72 upregulated and 134 downregulated biomarkers in the untargeted metabolomics studies using blood samples. Untargeted metabolomics studies utilizing urine specimens revealed the presence of 78 upregulated and 54 downregulated metabolites. The targeted metabolomics studies revealed abnormalities in the metabolism of glutamate and tryptophan. Enrichment analysis revealed that the differential metabolic pathways were mainly involved in the metabolism of glucose, amino acid and fatty acid. These findings suggested that certain metabolic biomarkers or metabolic biomarker panels might serve as a reference for the diagnosis of BD.
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Affiliation(s)
- Jin Chen
- Department of Psychiatry, The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, Xuzhou, Jiangsu,221004, China; Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu,210000, China
| | - Nousayhah Amdanee
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu,210000, China
| | - Xiaowei Zuo
- Department of Psychiatry, The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, Xuzhou, Jiangsu,221004, China
| | - Yu Wang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu,210000, China
| | - Muxin Gong
- Department of Psychiatry, The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, Xuzhou, Jiangsu,221004, China
| | - Yujing Yang
- Department of Psychiatry, The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, Xuzhou, Jiangsu,221004, China
| | - Hao Li
- Department of Psychiatry, The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, Xuzhou, Jiangsu,221004, China
| | - Xiangrong Zhang
- Department of Psychiatry, The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, Xuzhou, Jiangsu,221004, China; Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu,210000, China.
| | - Caiyi Zhang
- Department of Psychiatry, The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, Xuzhou, Jiangsu,221004, China.
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Hiller JK, Jangmo A, Tesli MS, Jaholkowski PP, Hoseth EZ, Steen NE, Haram M. Lipid Biomarker Research in Bipolar Disorder: A Scoping Review of Trends, Challenges, and Future Directions. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2023; 3:594-604. [PMID: 37881590 PMCID: PMC10593953 DOI: 10.1016/j.bpsgos.2023.07.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 07/10/2023] [Accepted: 07/13/2023] [Indexed: 10/27/2023] Open
Abstract
Bipolar disorder (BD) is a disabling disorder with heterogeneous symptom profiles and trajectories. Like many other neuropsychiatric disorders, clinical decision making related to diagnoses and choice of treatment is based on clinical assessments alone, and risk prediction for treatment success or resistance at an individual level remains sparse. An enormous effort to add biological markers to this risk prediction is ongoing. The role of lipids in normal brain functioning is well established, and several hypotheses about the role of lipids in the pathogenesis of neuropsychiatric disorders, including BD, have been made. The frequent comorbidity between neuropsychiatric disorders and cardiovascular disease, the genetic overlap of risk genes for severe mental disorders and genes involved in lipid regulation, and the lipid-altering effects of antipsychotics and mood stabilizers indicate that lipids could hold promise as biomarkers for neuropsychiatric disorders, including BD. To date, reviews of lipid biomarkers in schizophrenia and major depression have noted caveats for future investigations, while reviews of lipid biomarker research in BD is missing. In the current scoping review, we present a comprehensive overview of trends in previous research on lipid biomarkers in BD. The current literature varies greatly in the phenotypes investigated and study designs, leading to divergent findings. Small sample size; potential confounders related to physical activity, nutritional status, and medication use; and cross-sectional designs were frequently reported limitations. Future research may benefit from pivoting toward utilization of newer laboratory techniques such as lipidomics, but consistent use of study methods across cohorts is also needed.
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Affiliation(s)
| | - Andreas Jangmo
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Martin Steen Tesli
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- Centre for Research and Education in Forensic Psychiatry, Department of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Piotr Pawel Jaholkowski
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Eva Zsuzsanna Hoseth
- Clinic of Mental Health and Addiction, Møre and Romsdal Health Trust, Kristiansund, Norway
| | - Nils Eiel Steen
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Marit Haram
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
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Ribeiro HC, Zandonadi FDS, Sussulini A. An overview of metabolomic and proteomic profiling in bipolar disorder and its clinical value. Expert Rev Proteomics 2023; 20:267-280. [PMID: 37830362 DOI: 10.1080/14789450.2023.2267756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 09/12/2023] [Indexed: 10/14/2023]
Abstract
INTRODUCTION Bipolar disorder (BD) is a complex psychiatric disease characterized by alternating mood episodes. As for any other psychiatric illness, currently there is no biochemical test that is able to support diagnosis or therapeutic decisions for BD. In this context, the discovery and validation of biomarkers are interesting strategies that can be achieved through proteomics and metabolomics. AREAS COVERED In this descriptive review, a literature search including original articles and systematic reviews published in the last decade was performed with the objective to discuss the results of BD proteomic and metabolomic profiling analyses and indicate proteins and metabolites (or metabolic pathways) with potential clinical value. EXPERT OPINION A large number of proteins and metabolites have been reported as potential BD biomarkers; however, most studies do not reach biomarker validation stages. An effort from the scientific community should be directed toward the validation of biomarkers and the development of simplified bioanalytical techniques or protocols to determine them in biological samples, in order to translate proteomic and metabolomic findings into clinical routine assays.
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Affiliation(s)
- Henrique Caracho Ribeiro
- Laboratory of Bioanalytics and Integrated Omics (LaBIOmics), Department of Analytical Chemistry, Institute of Chemistry, Universidade Estadual de Campinas(UNICAMP), Campinas, SP, Brazil
| | - Flávia da Silva Zandonadi
- Laboratory of Bioanalytics and Integrated Omics (LaBIOmics), Department of Analytical Chemistry, Institute of Chemistry, Universidade Estadual de Campinas(UNICAMP), Campinas, SP, Brazil
| | - Alessandra Sussulini
- Laboratory of Bioanalytics and Integrated Omics (LaBIOmics), Department of Analytical Chemistry, Institute of Chemistry, Universidade Estadual de Campinas(UNICAMP), Campinas, SP, Brazil
- Instituto Nacional de Ciência e Tecnologia de Bioanalítica (INCTBio), Institute of Chemistry, Universidade Estadual de Campinas (UNICAMP), Campinas, SP, Brazil
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Costa AC, Riça LB, van de Bilt M, Zandonadi FS, Gattaz WF, Talib LL, Sussulini A. Application of Lipidomics in Psychiatry: Plasma-Based Potential Biomarkers in Schizophrenia and Bipolar Disorder. Metabolites 2023; 13:metabo13050600. [PMID: 37233641 DOI: 10.3390/metabo13050600] [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: 03/31/2023] [Revised: 04/19/2023] [Accepted: 04/24/2023] [Indexed: 05/27/2023] Open
Abstract
In this study, we obtained a lipidomic profile of plasma samples from drug-naïve patients with schizophrenia (SZ) and bipolar disorder (BD) in comparison to healthy controls. The sample cohort consisted of 30 BD and 30 SZ patients and 30 control individuals. An untargeted lipidomics strategy using liquid chromatography coupled with high-resolution mass spectrometry was employed to obtain the lipid profiles. Data were preprocessed, then univariate (t-test) and multivariate (principal component analysis and orthogonal partial least squares discriminant analysis) statistical tools were applied to select differential lipids, which were putatively identified. Afterward, multivariate receiver operating characteristic tests were performed, and metabolic pathway networks were constructed, considering the differential lipids. Our results demonstrate alterations in distinct lipid pathways, especially in glycerophospholipids, sphingolipids and glycerolipids, between SZ and BD patients. The results obtained in this study may serve as a basis for differential diagnosis, which is crucial for effective treatment and improving the quality of life of patients with psychotic disorders.
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Affiliation(s)
- Alana C Costa
- Laboratory of Neuroscience (LIM-27), Department and Institute of Psychiatry, University of Sao Paulo Medical School, Sao Paulo 05403903, Brazil
- Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBioN), Conselho Nacional de Desenvolvimento Científico e Tecnológico, Sao Paulo 05403903, Brazil
| | - Larissa B Riça
- Laboratory of Bioanalytics and Integrated Omics (LaBIOmics), Institute of Chemistry, University of Campinas (UNICAMP), Campinas 13083970, Brazil
| | - Martinus van de Bilt
- Laboratory of Neuroscience (LIM-27), Department and Institute of Psychiatry, University of Sao Paulo Medical School, Sao Paulo 05403903, Brazil
- Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBioN), Conselho Nacional de Desenvolvimento Científico e Tecnológico, Sao Paulo 05403903, Brazil
| | - Flávia S Zandonadi
- Laboratory of Bioanalytics and Integrated Omics (LaBIOmics), Institute of Chemistry, University of Campinas (UNICAMP), Campinas 13083970, Brazil
| | - Wagner F Gattaz
- Laboratory of Neuroscience (LIM-27), Department and Institute of Psychiatry, University of Sao Paulo Medical School, Sao Paulo 05403903, Brazil
- Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBioN), Conselho Nacional de Desenvolvimento Científico e Tecnológico, Sao Paulo 05403903, Brazil
| | - Leda L Talib
- Laboratory of Neuroscience (LIM-27), Department and Institute of Psychiatry, University of Sao Paulo Medical School, Sao Paulo 05403903, Brazil
- Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBioN), Conselho Nacional de Desenvolvimento Científico e Tecnológico, Sao Paulo 05403903, Brazil
| | - Alessandra Sussulini
- Laboratory of Bioanalytics and Integrated Omics (LaBIOmics), Institute of Chemistry, University of Campinas (UNICAMP), Campinas 13083970, Brazil
- Instituto Nacional de Ciência e Tecnologia de Bioanalítica (INCTBio), Institute of Chemistry, University of Campinas (UNICAMP), Campinas 13083970, Brazil
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