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Gammoh O, Aljabali AAA, Tambuwala MM. Plasma amino acids in major depressive disorder: between pathology to pharmacology. EXCLI JOURNAL 2024; 23:62-78. [PMID: 38357097 PMCID: PMC10864705 DOI: 10.17179/excli2023-6767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 11/23/2023] [Indexed: 02/16/2024]
Abstract
Addressing the formidable challenge posed by the development of effective and personalized interventions for major depressive disorder (MDD) necessitates a comprehensive comprehension of the intricate role that plasma amino acids play and their implications in MDD pathology and pharmacology. Amino acids, owing to their indispensable functions in neurotransmission, metabolism, and immune regulation, emerge as pivotal entities in this intricate disorder. Our primary objective entails unraveling the underlying mechanisms and unveiling tailored treatments through a meticulous investigation into the interplay between plasma amino acids, MDD, and pharmacological strategies. By conducting a thorough and exhaustive review of the existing literature, we have identified pertinent studies on plasma amino acids in MDD, thereby uncovering noteworthy disturbances in the profiles of amino acids among individuals afflicted by MDD when compared to their healthy counterparts. Specifically, disruptions in the metabolism of tryptophan, phenylalanine, and tyrosine, which serve as precursors to essential neurotransmitters, have emerged as prospective biomarkers and critical contributors to the pathophysiology of depression. Amnio acids play an essential role in MDD and could represent an attractive pharmacological target, more studies are further required to fully reveal their underlying mechanisms.
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Affiliation(s)
- Omar Gammoh
- Department of Clinical Pharmacy and Pharmacy Practice; Faculty of Pharmacy, Yarmouk University Irbid 21163, PO BOX 566, Jordan
| | - Alaa A. A. Aljabali
- Department of Pharmaceutics and Pharmaceutical Technology; Faculty of Pharmacy, Yarmouk University Irbid 21163, PO BOX 566, Jordan
| | - Murtaza M. Tambuwala
- Lincoln Medical School, University of Lincoln, Brayford Pool Campus, Lincoln LN6 7TS, United Kingdom
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Herman S, Arvidsson McShane S, Zjukovskaja C, Khoonsari PE, Svenningsson A, Burman J, Spjuth O, Kultima K. Disease phenotype prediction in multiple sclerosis. iScience 2023; 26:106906. [PMID: 37332601 PMCID: PMC10275960 DOI: 10.1016/j.isci.2023.106906] [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: 11/23/2022] [Revised: 03/09/2023] [Accepted: 05/12/2023] [Indexed: 06/20/2023] Open
Abstract
Progressive multiple sclerosis (PMS) is currently diagnosed retrospectively. Here, we work toward a set of biomarkers that could assist in early diagnosis of PMS. A selection of cerebrospinal fluid metabolites (n = 15) was shown to differentiate between PMS and its preceding phenotype in an independent cohort (AUC = 0.93). Complementing the classifier with conformal prediction showed that highly confident predictions could be made, and that three out of eight patients developing PMS within three years of sample collection were predicted as PMS at that time point. Finally, this methodology was applied to PMS patients as part of a clinical trial for intrathecal treatment with rituximab. The methodology showed that 68% of the patients decreased their similarity to the PMS phenotype one year after treatment. In conclusion, the inclusion of confidence predictors contributes with more information compared to traditional machine learning, and this information is relevant for disease monitoring.
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Affiliation(s)
- Stephanie Herman
- Department of Medical Sciences, Clinical Chemistry, Uppsala University, Uppsala, Sweden
- Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
| | | | | | - Payam Emami Khoonsari
- Department of Medical Sciences, Clinical Chemistry, Uppsala University, Uppsala, Sweden
- Department of Biochemistry and Biophysics, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Stockholm University, Box 1031, 17121 Solna, Sweden
| | - Anders Svenningsson
- Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden
| | - Joachim Burman
- Department of Neuroscience, Neurology, Uppsala University, Uppsala, Sweden
| | - Ola Spjuth
- Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
| | - Kim Kultima
- Department of Medical Sciences, Clinical Chemistry, Uppsala University, Uppsala, Sweden
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Puranik N, Yadav D, Song M. Insight into Early Diagnosis of Multiple Sclerosis by Targeting Prognostic Biomarkers. Curr Pharm Des 2023; 29:2534-2544. [PMID: 37921136 DOI: 10.2174/0113816128247471231018053737] [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: 03/09/2023] [Revised: 08/04/2023] [Accepted: 09/06/2023] [Indexed: 11/04/2023]
Abstract
Multiple sclerosis (MS) is a central nervous system (CNS) immune-mediated disease that mainly strikes young adults and leaves them disabled. MS is an autoimmune illness that causes the immune system to attack the brain and spinal cord. The myelin sheaths, which insulate the nerve fibers, are harmed by our own immune cells, and this interferes with brain signal transmission. Numbness, tingling, mood swings, memory problems, exhaustion, agony, vision problems, and/or paralysis are just a few of the symptoms. Despite technological advancements and significant research efforts in recent years, diagnosing MS can still be difficult. Each patient's MS is distinct due to a heterogeneous and complex pathophysiology with diverse types of disease courses. There is a pressing need to identify markers that will allow for more rapid and accurate diagnosis and prognosis assessments to choose the best course of treatment for each MS patient. The cerebrospinal fluid (CSF) is an excellent source of particular indicators associated with MS pathology. CSF contains molecules that represent pathological processes such as inflammation, cellular damage, and loss of blood-brain barrier integrity. Oligoclonal bands, neurofilaments, MS-specific miRNA, lncRNA, IgG-index, and anti-aquaporin 4 antibodies are all clinically utilised indicators for CSF in MS diagnosis. In recent years, a slew of new possible biomarkers have been presented. In this review, we look at what we know about CSF molecular markers and how they can aid in the diagnosis and differentiation of different MS forms and treatment options, and monitoring and predicting disease progression, therapy response, and consequences during such opportunistic infections.
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Affiliation(s)
- Nidhi Puranik
- Biological Sciences Department, Bharathiar University, Coimbatore, Tamil Nadu, 641046, India
| | - Dhananjay Yadav
- Department of Life Science, Yeungnam University, Gyeongsan 38541, Korea
| | - Minseok Song
- Department of Life Science, Yeungnam University, Gyeongsan 38541, Korea
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Siamakpour-Reihani S, Cao F, Lyu J, Ren Y, Nixon AB, Xie J, Bush AT, Starr MD, Bain JR, Muehlbauer MJ, Ilkayeva O, Byers Kraus V, Huebner JL, Chao NJ, Sung AD. Evaluating immune response and metabolic related biomarkers pre-allogenic hematopoietic stem cell transplant in acute myeloid leukemia. PLoS One 2022; 17:e0268963. [PMID: 35700185 PMCID: PMC9197059 DOI: 10.1371/journal.pone.0268963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 05/05/2022] [Indexed: 01/08/2023] Open
Abstract
Although hematopoietic stem cell transplantation (HCT) is the only curative treatment for acute myeloid leukemia (AML), it is associated with significant treatment related morbidity and mortality. There is great need for predictive biomarkers associated with overall survival (OS) and clinical outcomes. We hypothesized that circulating metabolic, inflammatory, and immune molecules have potential as predictive biomarkers for AML patients who receive HCT treatment. This retrospective study was designed with an exploratory approach to comprehensively characterize immune, inflammatory, and metabolomic biomarkers. We identified patients with AML who underwent HCT and had existing baseline plasma samples. Using those samples (n = 34), we studied 65 blood based metabolomic and 61 immune/inflammatory related biomarkers, comparing patients with either long-term OS (≥ 3 years) or short-term OS (OS ≤ 1 years). We also compared the immune/inflammatory response and metabolomic biomarkers in younger vs. older AML patients (≤30 years vs. ≥ 55 years old). In addition, the biomarker profiles were analyzed for their association with clinical outcomes, namely OS, chronic graft versus host disease (cGVHD), acute graft versus host disease (aGVHD), infection and relapse. Several baseline biomarkers were elevated in older versus younger patients, and baseline levels were lower for three markers (IL13, SAA, CRP) in patients with OS ≥ 3 years. We also identified immune/inflammatory response markers associated with aGVHD (IL-9, Eotaxin-3), cGVHD (Flt-1), infection (D-dimer), or relapse (IL-17D, bFGF, Eotaxin-3). Evaluation of metabolic markers demonstrated higher baseline levels of medium- and long-chain acylcarnitines (AC) in older patients, association with aGVHD (lactate, long-chain AC), and cGVHD (medium-chain AC). These differentially expressed profiles merit further evaluation as predictive biomarkers.
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Affiliation(s)
- Sharareh Siamakpour-Reihani
- Division of Hematologic Malignancies and Cellular Therapy, Duke University School of Medicine, Durham, North Carolina, United States of America
| | - Felicia Cao
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States of America
| | - Jing Lyu
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States of America
| | - Yi Ren
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina, United States of America
| | - Andrew B. Nixon
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States of America
| | - Jichun Xie
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina, United States of America
| | - Amy T. Bush
- Division of Hematologic Malignancies and Cellular Therapy, Duke University School of Medicine, Durham, North Carolina, United States of America
| | - Mark D. Starr
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States of America
| | - James R. Bain
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States of America
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, North Carolina, United States of America
| | - Michael J. Muehlbauer
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, North Carolina, United States of America
| | - Olga Ilkayeva
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, North Carolina, United States of America
| | - Virginia Byers Kraus
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States of America
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, North Carolina, United States of America
| | - Janet L. Huebner
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, North Carolina, United States of America
| | - Nelson J. Chao
- Division of Hematologic Malignancies and Cellular Therapy, Duke University School of Medicine, Durham, North Carolina, United States of America
| | - Anthony D. Sung
- Division of Hematologic Malignancies and Cellular Therapy, Duke University School of Medicine, Durham, North Carolina, United States of America
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Yang F, Wu SC, Ling ZX, Chao S, Zhang LJ, Yan XM, He L, Yu LM, Zhao LY. Altered Plasma Metabolic Profiles in Chinese Patients With Multiple Sclerosis. Front Immunol 2021; 12:792711. [PMID: 34975894 PMCID: PMC8715987 DOI: 10.3389/fimmu.2021.792711] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 11/25/2021] [Indexed: 11/13/2022] Open
Abstract
Multiple sclerosis (MS) is an autoimmune disease that leads to the demyelination of nerve axons. An increasing number of studies suggest that patients with MS exhibit altered metabolic profiles, which might contribute to the course of MS. However, the alteration of metabolic profiles in Chinese patients with MS and their potential roles in regulating the immune system remain elusive. In this study, we performed a global untargeted metabolomics approach in plasma samples from 22 MS-affected Chinese patients and 21 healthy subjects. A total of 42 differentially abundant metabolites (DAMs) belonging to amino acids, lipids, and carbohydrates were identified in the plasma of MS patients and compared with those in healthy controls. We observed an evident reduction in the levels of amino acids, such as L-tyrosine, L-isoleucine, and L-tryptophan, whereas there was a great increase in the levels of L-glutamic acid and L-valine in MS-affected patients. The levels of lipid and carbohydrate metabolites, such as sphingosine 1-phosphate and myo-inositol, were also reduced in patients with MS. In addition, the concentrations of proinflammatory cytokines, such as IL-17 and TNF-α, were significantly increased, whereas those of several anti-inflammatory cytokines and chemokines, such as IL-1ra, IL-7, and MIP-1α, were distinctly reduced in the plasma of MS patients compared with those in healthy subjects. Interestingly, some DAMs, such as L-tryptophan and sphingosine 1-phosphate, showed an evident negative correlation with changes in the level of TNF-α and IL-17, while tightly positively correlating with altered concentrations of anti-inflammatory cytokines and chemokines, such as MIP-1α and RANTES. Our results revealed that altered metabolomic profiles might contribute to the pathogenesis and course of MS disease by modulating immuno-inflammatory responses in the peripheral system, which is essential for eliciting autoimmune responses in the central nervous system, thus resulting in the progression of MS. This study provides potential clues for developing therapeutic strategies for MS in the near future.
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Affiliation(s)
- Fan Yang
- Key Laboratory of Cell Engineering in Guizhou Province, Affiliated Hospital of Zunyi Medical University, Zunyi, China
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
- Institutes for Shanghai Pudong Decoding Life, Research Center for Lin He Academician New Medicine, Shanghai, China
| | - Shao-chang Wu
- Department of Geriatrics and Clinical Laboratory, Lishui Second People’s Hospital, Lishui, China
| | - Zong-xin Ling
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
- Institute of Microbe & Host Health, Linyi University, Linyi, China
| | - Shan Chao
- Institutes for Shanghai Pudong Decoding Life, Research Center for Lin He Academician New Medicine, Shanghai, China
| | - Li-juan Zhang
- Department of Geriatrics and Clinical Laboratory, Lishui Second People’s Hospital, Lishui, China
| | - Xiu-mei Yan
- Department of Geriatrics and Clinical Laboratory, Lishui Second People’s Hospital, Lishui, China
| | - Lin He
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Li-mei Yu
- Key Laboratory of Cell Engineering in Guizhou Province, Affiliated Hospital of Zunyi Medical University, Zunyi, China
- *Correspondence: Long-you Zhao, ; Li-mei Yu,
| | - Long-you Zhao
- Department of Geriatrics and Clinical Laboratory, Lishui Second People’s Hospital, Lishui, China
- *Correspondence: Long-you Zhao, ; Li-mei Yu,
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