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Holck A, Movahed P, Westrin Å, Wolkowitz OM, Lindqvist D, Asp M. Peripheral serotonin levels as a predictor of antidepressant treatment response: A systematic review. Prog Neuropsychopharmacol Biol Psychiatry 2024; 133:111031. [PMID: 38762162 DOI: 10.1016/j.pnpbp.2024.111031] [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: 03/18/2024] [Revised: 05/08/2024] [Accepted: 05/14/2024] [Indexed: 05/20/2024]
Abstract
There are currently no reliable biomarkers to predict clinical response to pharmacological treatments of depressive disorders. Peripheral blood 5-hydroxytryptamine (5-HT; serotonin) has been suggested as a biomarker of antidepressant treatment response, but there has not been an attempt to systematically summarize and evaluate the scientific evidence of this hypothesis. In this systematic review we searched MEDLINE, Embase, PsycINFO, and the Cochrane Central Register of Controlled Trials. Twenty-six relevant studies investigating peripheral 5-HT as an antidepressant biomarker were identified. In all, we did not find robust support for an association between baseline 5-HT and treatment response. Several larger studies with lower risk of bias, however, showed that higher baseline 5-HT was associated with a greater antidepressant response to SSRIs, prompting future studies to investigate this hypothesis. Our results also confirm previous reports that SSRI treatment is associated with a decrease in peripheral 5-HT levels; however, we were not able to confirm that larger decreases of 5-HT are associated with better treatment outcome as results were inconclusive.
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Affiliation(s)
- Amanda Holck
- Unit for Biological and Precision Psychiatry, Department of Clinical Sciences Lund, Lund University, Lund, Sweden; Psychiatric Clinic Lund, Lund, Sweden.
| | - Pouya Movahed
- Psychiatric Clinic Lund, Lund, Sweden; Psychiatric Neuromodulation Unit, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Åsa Westrin
- Unit for Clinical Suicide Research, Department of Clinical Sciences Lund, Lund University, Lund, Sweden; The Region Skåne Committee on Psychiatry, Habilitation and Technical Aids, Sweden
| | - Owen M Wolkowitz
- Department of Psychiatry and Behavioral Sciences and Weill Institute for Neurosciences, University of California, San Francisco, School of Medicine, San Francisco, CA, USA
| | - Daniel Lindqvist
- Unit for Biological and Precision Psychiatry, Department of Clinical Sciences Lund, Lund University, Lund, Sweden; Office for Psychiatry, Habilitation and Technical Aids, Psychiatry Research Skåne, Region Skåne, Lund, Sweden
| | - Marie Asp
- Unit for Biological and Precision Psychiatry, Department of Clinical Sciences Lund, Lund University, Lund, Sweden; Psychiatric Clinic Lund, Lund, Sweden
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Liu X, Li M, Jian C, Qin X. Characterization of "microbiome-metabolome-immunity" in depressed rats with divergent responses to Paroxetine. J Affect Disord 2024; 352:201-213. [PMID: 38346646 DOI: 10.1016/j.jad.2024.02.017] [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: 04/23/2023] [Revised: 01/29/2024] [Accepted: 02/07/2024] [Indexed: 02/22/2024]
Abstract
OBJECTIVES Selective serotonin reuptake inhibitors (SSRIs) are the first-line anti-depressants. Unfortunately, about 30 % depressed patients do not effectively respond to SSRIs. It is still unclear that the gastrointestinal characteristics of responders and non-responders, and the differences. METHODS Herein, we characterized gut microbiome and metabolome of depressed rats with differential responses to Paroxetine (PX) by 16S rRNA sequencing and 1H NMR-based metabolomics, respectively. On top of this, we constructed both inter- and inner-layer networks, intuitively showing the correlations among behavioral indicators, immune factors, intestinal bacteria, and differential metabolites. RESULTS Consequently, we found that depressed rats differently responded to PX, which could be divided into PX responsive (PX-R) and non-responsive (PX-N) groups. Firstly, the depressive behaviors of PX-R rats and PX-N rats significantly differed. Meanwhile, inflammatory balance was also characterized for depressed rats with different responses to PX. Overall, PX-R rats and PX-N rats exhibited differential gut microbiome and metabolome, including intestinal structures, intestinal functions, metabolic profiles, metabolites, and metabolic pathways. LIMITATIONS Metabolites that identified by metabolomics based on 1H NMR are not comprehensive enough. CONCLUSIONS Taken together, our study demonstrated that gut microbiome and metabolome, as well as related functions, are of significance in differential responses of depressed rats to PX, which might be novel insights in uncovering the mechanisms of differences in efficacies of antidepressants.
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Affiliation(s)
- Xiaojie Liu
- Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan 030006, China; The Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education, Shanxi University, Taiyuan 030006, China; Key Laboratory of Effective Substances Research and Utilization in TCM of Shanxi Province, Shanxi University, Taiyuan 030006, China.
| | - Mengyu Li
- Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan 030006, China; The Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education, Shanxi University, Taiyuan 030006, China; Key Laboratory of Effective Substances Research and Utilization in TCM of Shanxi Province, Shanxi University, Taiyuan 030006, China
| | - Chen Jian
- Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan 030006, China; The Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education, Shanxi University, Taiyuan 030006, China; Key Laboratory of Effective Substances Research and Utilization in TCM of Shanxi Province, Shanxi University, Taiyuan 030006, China
| | - Xuemei Qin
- Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan 030006, China; The Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education, Shanxi University, Taiyuan 030006, China; Key Laboratory of Effective Substances Research and Utilization in TCM of Shanxi Province, Shanxi University, Taiyuan 030006, China.
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Jian J, He D, Gao S, Tao X, Dong X. Pharmacokinetics in Pharmacometabolomics: Towards Personalized Medication. Pharmaceuticals (Basel) 2023; 16:1568. [PMID: 38004434 PMCID: PMC10675232 DOI: 10.3390/ph16111568] [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: 09/17/2023] [Revised: 10/19/2023] [Accepted: 10/27/2023] [Indexed: 11/26/2023] Open
Abstract
Indiscriminate drug administration may lead to drug therapy results with varying effects on patients, and the proposal of personalized medication can help patients to receive effective drug therapy. Conventional ways of personalized medication, such as pharmacogenomics and therapeutic drug monitoring (TDM), can only be implemented from a single perspective. The development of pharmacometabolomics provides a research method for the realization of precise drug administration, which integrates the environmental and genetic factors, and applies metabolomics technology to study how to predict different drug therapeutic responses of organisms based on baseline metabolic levels. The published research on pharmacometabolomics has achieved satisfactory results in predicting the pharmacokinetics, pharmacodynamics, and the discovery of biomarkers of drugs. Among them, the pharmacokinetics related to pharmacometabolomics are used to explore individual variability in drug metabolism from the level of metabolism of the drugs in vivo and the level of endogenous metabolite changes. By searching for relevant literature with the keyword "pharmacometabolomics" on the two major literature retrieval websites, PubMed and Web of Science, from 2006 to 2023, we reviewed articles in the field of pharmacometabolomics that incorporated pharmacokinetics into their research. This review explains the therapeutic effects of drugs on the body from the perspective of endogenous metabolites and pharmacokinetic principles, and reports the latest advances in pharmacometabolomics related to pharmacokinetics to provide research ideas and methods for advancing the implementation of personalized medication.
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Affiliation(s)
- Jingai Jian
- School of Medicine, Shanghai University, Shanghai 200444, China; (J.J.); (D.H.)
| | - Donglin He
- School of Medicine, Shanghai University, Shanghai 200444, China; (J.J.); (D.H.)
| | - Songyan Gao
- Institute of Translational Medicine, Shanghai University, Shanghai 200444, China;
| | - Xia Tao
- Department of Pharmacy, Changzheng Hospital, Second Military Medical University, Shanghai 200003, China
| | - Xin Dong
- School of Medicine, Shanghai University, Shanghai 200444, China; (J.J.); (D.H.)
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Luo X, Zhu D, Li J, Ren M, Liu Y, Si T, Chen Y. Selection of the optimal dose of sertraline for depression: A dose-response meta-analysis of randomized controlled trials. Psychiatry Res 2023; 327:115391. [PMID: 37557058 DOI: 10.1016/j.psychres.2023.115391] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 07/26/2023] [Accepted: 07/29/2023] [Indexed: 08/11/2023]
Abstract
Sertraline has been shown to be effective in the treatment of depression. However, the relationship between the dosage of sertraline and its efficacy and safety are unclear. We identified RCTs that compared sertraline with placebo for the treatment of depression, conducted conventional meta-analyses on the efficacy and safety of sertraline, and assessed the nonlinear dose-response relationship between sertraline dosage and the changes in HAM-D and CGI-S scores, dropout from care for any reason or due to adverse effects, and the rate of adverse effects, using a 1-stage restricted cubic spline regression model. Twenty-one RCTs involving 4,235 patients were included. The pooled mean differences (MD) in the change in HAM-D total score [MD=-2.34, 95% confidence interval (CI) -2.93, -1.76], CGI-S score and MADRS score, but also the dropout rate for adverse effects, and rate of adverse effects were higher in sertraline group. The therapeutic response of sertraline for treating depression increased with the dosage. Meanwhile, the risk of total adverse reactions slightly decreased between 50 and 150 mg, and increased at doses above 150 mg. The dose-dependence of both efficacy and safety need to be considered when choosing the optimal dosage of sertraline.
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Affiliation(s)
- Xufei Luo
- Evidence-based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China; WHO Collaborating Centre for Guideline Implementation and Knowledge Translation, Lanzhou 730000, China
| | - Di Zhu
- School of Public Health, Lanzhou University, Lanzhou 730000, China
| | - Jitao Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), No. 51 Hua Yuan Bei Road, Haidian District, Beijing 100191, China
| | - Mengjuan Ren
- School of Public Health, Lanzhou University, Lanzhou 730000, China
| | - Yunlan Liu
- School of Public Health, Lanzhou University, Lanzhou 730000, China
| | - Tianmei Si
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), No. 51 Hua Yuan Bei Road, Haidian District, Beijing 100191, China.
| | - Yaolong Chen
- Evidence-based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China; WHO Collaborating Centre for Guideline Implementation and Knowledge Translation, Lanzhou 730000, China; Research Unit of Evidence-Based Evaluation and Guidelines, Chinese Academy of Medical Sciences (2021RU017), School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China; Institute of Health Data Science, Lanzhou University, Lanzhou 730000, China.
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Cai W, Wei XF, Hu C, Ji J, Cui HS, Shen WD. Effects of Electroacupuncture on Gut Microbiota and Fecal Metabolites in Rats with Poststroke Depression. Neuropsychiatr Dis Treat 2023; 19:1581-1592. [PMID: 37465562 PMCID: PMC10350407 DOI: 10.2147/ndt.s415098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 06/21/2023] [Indexed: 07/20/2023] Open
Abstract
Background Poststroke depression (PSD) is the most frequent neuropsychiatric consequence of stroke. Electroacupuncture (EA) has been found to be an effective therapy for treating PSD. However, the underlying mechanisms of EA's efficacy remain unclear. This research aimed to investigate the effects of EA on alterations in gut microbiota and fecal metabolome in PSD rats. Methods Analyses of gut microbiome and fecal metabolome were performed to identify gut microbes and their functional metabolites in a sham group, PSD group, and EA group. We conducted enrichment analysis to identify the differential metabolic pathways in three groups. Correlations between altered gut microbes and differential metabolites after EA treatment were studied. Results PSD showed decreased species-richness/diversity indices of microbial composition, characterized by an increase in Muribaculaceae, Peptostreptococcaceae, Oscillospiraceae, Ruminococcaceae, and Clostridiaceae and a decrease in Lactobacillaceae, Lachnospiraceae, and Bacteroidaceae. Of these, the abundance of Muribaculaceae, Lactobacillaceae, Lachnospiraceae, Peptostreptococcaceae, and Clostridiaceae were reversed by EA. Furthermore, PSD was associated with 34 differential fecal metabolites, mainly belonging to steroid hormone biosynthesis, that could be regulated by EA. Conclusion Regulation of gut microbiome and lipid metabolism could be one of the potential mechanisms for EA treatment for alleviating the depressive behaviors of PSD.
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Affiliation(s)
- Wa Cai
- Department of Acupuncture, Shanghai Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
| | - Xi-Fang Wei
- Department of Acupuncture, Shanghai Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
| | - Chen Hu
- Department of Acupuncture, Shanghai Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
| | - Jun Ji
- Department of Acupuncture Literature, Shanghai Research Institute of Acupuncture and Meridian, Shanghai, People’s Republic of China
| | - Hua Shun Cui
- Department of Acupuncture, Shanghai Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
| | - Wei-Dong Shen
- Department of Acupuncture, Shanghai Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
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Aarsland TIM, Instanes JT, Posserud MBR, Ulvik A, Kessler U, Haavik J. Changes in Tryptophan-Kynurenine Metabolism in Patients with Depression Undergoing ECT-A Systematic Review. Pharmaceuticals (Basel) 2022; 15:1439. [PMID: 36422569 PMCID: PMC9694349 DOI: 10.3390/ph15111439] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 11/03/2022] [Accepted: 11/11/2022] [Indexed: 10/29/2023] Open
Abstract
The kynurenine pathway of tryptophan (Trp) metabolism generates multiple biologically active metabolites (kynurenines) that have been implicated in neuropsychiatric disorders. It has been suggested that modulation of kynurenine metabolism could be involved in the therapeutic effect of electroconvulsive therapy (ECT). We performed a systematic review with aims of summarizing changes in Trp and/or kynurenines after ECT and assessing methodological issues. The inclusion criterium was measures of Trp and/or kynurenines before and after ECT. Animal studies and studies using Trp administration or Trp depletion were excluded. Embase, MEDLINE, PsycInfo and PubMed were searched, most recently in July 2022. Outcomes were levels of Trp, kynurenines and ratios before and after ECT. Data on factors affecting Trp metabolism and ECT were collected for interpretation and discussion of the reported changes. We included 17 studies with repeated measures for a total of 386 patients and 27 controls. Synthesis using vote counting based on the direction of effect found no evidence of effect of ECT on any outcome variable. There were considerable variations in design, patient characteristics and reported items. We suggest that future studies should include larger samples, assess important covariates and determine between- and within-subject variability. PROSPERO (CRD42020187003).
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Affiliation(s)
| | | | - Maj-Britt Rocio Posserud
- Department of Clinical Medicine, University of Bergen, 5020 Bergen, Norway
- Division of Psychiatry, Haukeland University Hospital, 5021 Bergen, Norway
| | - Arve Ulvik
- Bevital A/S, Laboratoriebygget, 5020 Bergen, Norway
| | - Ute Kessler
- Department of Clinical Medicine, University of Bergen, 5020 Bergen, Norway
- Division of Psychiatry, Haukeland University Hospital, 5021 Bergen, Norway
| | - Jan Haavik
- Department of Biomedicine, University of Bergen, 5020 Bergen, Norway
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Raghavan R, Anand NS, Wang G, Hong X, Pearson C, Zuckerman B, Xie H, Wang X. Association between cord blood metabolites in tryptophan pathway and childhood risk of autism spectrum disorder and attention-deficit hyperactivity disorder. Transl Psychiatry 2022; 12:270. [PMID: 35810183 PMCID: PMC9271093 DOI: 10.1038/s41398-022-01992-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 05/20/2022] [Accepted: 05/25/2022] [Indexed: 11/16/2022] Open
Abstract
Alterations in tryptophan and serotonin have been implicated in various mental disorders; but studies are limited on child neurodevelopmental disabilities such as autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD). This prospective cohort study examined the associations between levels of tryptophan and select metabolites (5-methoxytryptophol (5-MTX), 5-hydroxytryptophan (5-HTP), serotonin, N-acetyltrytophan) in cord plasma (collected at birth) and physician-diagnosed ASD, ADHD and other developmental disabilities (DD) in childhood. The study sample (n = 996) derived from the Boston Birth Cohort, which included 326 neurotypical children, 87 ASD, 269 ADHD, and 314 other DD children (mutually exclusive). These participants were enrolled at birth and followed-up prospectively (from October 1, 1998 to June 30, 2018) at the Boston Medical Center. Higher levels of cord 5-MTX was associated with a lower risk of ASD (aOR: 0.56, 95% CI: 0.41, 0.77) and ADHD (aOR: 0.79, 95% CI: 0.65, 0.96) per Z-score increase, after adjusting for potential confounders. Similarly, children with cord 5-MTX ≥ 25th percentile (vs. <25th percentile) had a reduction in ASD (aOR: 0.27, 95% CI: 0.14, 0.49) and ADHD risks (aOR: 0.45, 95% CI: 0.29, 0.70). In contrast, higher levels of cord tryptophan, 5-HTP and N-acetyltryptophan were associated with higher risk of ADHD, with aOR: 1.25, 95% CI: 1.03, 1.51; aOR: 1.32, 95% CI: 1.08, 1.61; and aOR: 1.27, 95% CI: 1.05, 1.53, respectively, but not with ASD and other DD. Cord serotonin was not associated with ASD, ADHD, and other DD. Most findings remained statistically significant in the sensitivity and subgroup analyses.
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Affiliation(s)
- Ramkripa Raghavan
- grid.21107.350000 0001 2171 9311Center on Early Life Origins of Disease, Department of Population, Family and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD USA
| | - Neha S. Anand
- grid.21107.350000 0001 2171 9311Center on Early Life Origins of Disease, Department of Population, Family and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD USA
| | - Guoying Wang
- grid.21107.350000 0001 2171 9311Center on Early Life Origins of Disease, Department of Population, Family and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD USA
| | - Xiumei Hong
- grid.21107.350000 0001 2171 9311Center on Early Life Origins of Disease, Department of Population, Family and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD USA
| | - Colleen Pearson
- grid.189504.10000 0004 1936 7558Department of Pediatrics, Boston University School of Medicine and Boston Medical Center, Boston, MA USA
| | - Barry Zuckerman
- grid.189504.10000 0004 1936 7558Department of Pediatrics, Boston University School of Medicine and Boston Medical Center, Boston, MA USA
| | - Hehuang Xie
- Department of Biomedical Sciences & Pathobiology, Fralin Life Sciences Institute at Virginia Technology, Blacksburg, VA USA
| | - Xiaobin Wang
- Center on Early Life Origins of Disease, Department of Population, Family and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA. .,Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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Badamasi IM, Maulidiani M, Lye MS, Ibrahim N, Shaari K, Stanslas J. A Preliminary Nuclear Magnetic Resonance Metabolomics Study Identifies Metabolites that Could Serve as Diagnostic Markers of Major Depressive Disorder. Curr Neuropharmacol 2022; 20:965-982. [PMID: 34126904 PMCID: PMC9881106 DOI: 10.2174/1570159x19666210611095320] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 04/17/2021] [Accepted: 05/28/2021] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND The evaluation of metabolites that are directly involved in the physiological process, few steps short of phenotypical manifestation, remains vital for unravelling the biological moieties involved in the development of the (MDD) and in predicting its treatment outcome. METHODOLOGY Eight (8) urine and serum samples each obtained from consenting healthy controls (HC), twenty-five (25) urine and serum samples each from first episode treatment naïve MDD (TNMDD) patients, and twenty (22) urine and serum samples each s from treatment naïve MDD patients 2 weeks after SSRI treatment (TWMDD) were analysed for metabolites using proton nuclear magnetic resonance (1HNMR) spectroscopy. The evaluation of patients' samples was carried out using Partial Least Squares Discriminant Analysis (PLS-DA) and Orthogonal Partial Least Square- Discriminant Analysis (OPLSDA) models. RESULTS In the serum, decreased levels of lactate, glucose, glutamine, creatinine, acetate, valine, alanine, and fatty acid and an increased level of acetone and choline in TNMDD or TWMDD irrespective of whether an OPLSDA or PLSDA evaluation was used were identified. A test for statistical validations of these models was successful. CONCLUSION Only some changes in serum metabolite levels between HC and TNMDD identified in this study have potential values in the diagnosis of MDD. These changes included decreased levels of lactate, glutamine, creatinine, valine, alanine, and fatty acid, as well as an increased level of acetone and choline in TNMDD. The diagnostic value of these changes in metabolites was maintained in samples from TWMDD patients, thus reaffirming the diagnostic nature of these metabolites for MDD.
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Affiliation(s)
- Ibrahim Mohammed Badamasi
- Pharmacotherapeutics Unit, Department of Medicine, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Selangor, Malaysia;
| | - Maulidiani Maulidiani
- Laboratory of Natural Products Institute of Bioscience, Universiti Putra Malaysia, Selangor, Malaysia; ,Present address of this author: Faculty of Science and Marine Environment, Universiti Malaysia Terengganu
| | - Munn Sann Lye
- Department of Community Health, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Selangor, Malaysia;
| | | | - Khozirah Shaari
- Laboratory of Natural Products Institute of Bioscience, Universiti Putra Malaysia, Selangor, Malaysia;
| | - Johnson Stanslas
- Pharmacotherapeutics Unit, Department of Medicine, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Selangor, Malaysia; ,Address correspondence to this author at the Pharmacotherapeutics Unit, Department of Medicine, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Selangor, Malaysia; E-mails: ,
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F. Guerreiro Costa LN, Carneiro BA, Alves GS, Lins Silva DH, Faria Guimaraes D, Souza LS, Bandeira ID, Beanes G, Miranda Scippa A, Quarantini LC. Metabolomics of Major Depressive Disorder: A Systematic Review of Clinical Studies. Cureus 2022; 14:e23009. [PMID: 35415046 PMCID: PMC8993993 DOI: 10.7759/cureus.23009] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/09/2022] [Indexed: 11/24/2022] Open
Abstract
Although the understanding of the pathophysiology of major depressive disorder (MDD) has advanced greatly, this has not been translated into improved outcomes. To date, no biomarkers have been identified for the diagnosis, prognosis, and therapeutic management of MDD. Thus, we aim to review the biomarkers that are differentially expressed in MDD. A systematic review was conducted in January 2022 in the PubMed/MEDLINE, Scopus, Embase, PsycINFO, and Gale Academic OneFile databases for clinical studies published from January 2001 onward using the following terms: “Depression” OR “Depressive disorder” AND “Metabolomic.” Multiple metabolites were found at altered levels in MDD, demonstrating the involvement of cellular signaling metabolites, components of the cell membrane, neurotransmitters, inflammatory and immunological mediators, hormone activators and precursors, and sleep controllers. Kynurenine and acylcarnitine were identified as consistent with depression and response to treatment. The most consistent evidence found was regarding kynurenine and acylcarnitine. Although the data obtained allow us to identify how metabolic pathways are affected in MDD, there is still not enough evidence to propose changes to current diagnostic and therapeutic actions. Some limitations are the heterogeneity of studies on metabolites, methods for detection, analyzed body fluids, and treatments used. The experiments contemplated in the review identified increased or reduced levels of metabolites, but not necessarily increased or reduced the activity of the associated pathways. The information acquired through metabolomic analyses does not specify whether the changes identified in the metabolites are a cause or a consequence of the pathology.
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Gbaoui L, Fachet M, Lüno M, Meyer-Lotz G, Frodl T, Hoeschen C. Breathomics profiling of metabolic pathways affected by major depression: Possibilities and limitations. Front Psychiatry 2022; 13:1061326. [PMID: 36590606 PMCID: PMC9795849 DOI: 10.3389/fpsyt.2022.1061326] [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: 10/04/2022] [Accepted: 11/24/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Major depressive disorder (MDD) is one of the most common psychiatric disorders with multifactorial etiologies. Metabolomics has recently emerged as a particularly potential quantitative tool that provides a multi-parametric signature specific to several mechanisms underlying the heterogeneous pathophysiology of MDD. The main purpose of the present study was to investigate possibilities and limitations of breath-based metabolomics, breathomics patterns to discriminate MDD patients from healthy controls (HCs) and identify the altered metabolic pathways in MDD. METHODS Breath samples were collected in Tedlar bags at awakening, 30 and 60 min after awakening from 26 patients with MDD and 25 HCs. The non-targeted breathomics analysis was carried out by proton transfer reaction mass spectrometry. The univariate analysis was first performed by T-test to rank potential biomarkers. The metabolomic pathway analysis and hierarchical clustering analysis (HCA) were performed to group the significant metabolites involved in the same metabolic pathways or networks. Moreover, a support vector machine (SVM) predictive model was built to identify the potential metabolites in the altered pathways and clusters. The accuracy of the SVM model was evaluated by receiver operating characteristics (ROC) analysis. RESULTS A total of 23 differential exhaled breath metabolites were significantly altered in patients with MDD compared with HCs and mapped in five significant metabolic pathways including aminoacyl-tRNA biosynthesis (p = 0.0055), branched chain amino acids valine, leucine and isoleucine biosynthesis (p = 0.0060), glycolysis and gluconeogenesis (p = 0.0067), nicotinate and nicotinamide metabolism (p = 0.0213) and pyruvate metabolism (p = 0.0440). Moreover, the SVM predictive model showed that butylamine (p = 0.0005, pFDR=0.0006), 3-methylpyridine (p = 0.0002, pFDR = 0.0012), endogenous aliphatic ethanol isotope (p = 0.0073, pFDR = 0.0174), valeric acid (p = 0.005, pFDR = 0.0162) and isoprene (p = 0.038, pFDR = 0.045) were potential metabolites within identified clusters with HCA and altered pathways, and discriminated between patients with MDD and non-depressed ones with high sensitivity (0.88), specificity (0.96) and area under curve of ROC (0.96). CONCLUSION According to the results of this study, the non-targeted breathomics analysis with high-throughput sensitive analytical technologies coupled to advanced computational tools approaches offer completely new insights into peripheral biochemical changes in MDD.
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Affiliation(s)
- Laila Gbaoui
- Chair of Medical Systems Technology, Institute for Medical Technology, Otto von Guericke University, Magdeburg, Germany
| | - Melanie Fachet
- Chair of Medical Systems Technology, Institute for Medical Technology, Otto von Guericke University, Magdeburg, Germany
| | - Marian Lüno
- Department for Psychiatry and Psychotherapy, Medical Faculty, Otto von Guericke University, Magdeburg, Germany
| | - Gabriele Meyer-Lotz
- Department for Psychiatry and Psychotherapy, Medical Faculty, Otto von Guericke University, Magdeburg, Germany
| | - Thomas Frodl
- Department for Psychiatry and Psychotherapy, Medical Faculty, Otto von Guericke University, Magdeburg, Germany.,Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital, RWTH Aachen, Aachen, Germany
| | - Christoph Hoeschen
- Chair of Medical Systems Technology, Institute for Medical Technology, Otto von Guericke University, Magdeburg, Germany
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Cai W, Wang XF, Wei XF, Zhang JR, Hu C, Ma W, Shen WD. Does urinary metabolite signature act as a biomarker of post-stroke depression? Front Psychiatry 2022; 13:928076. [PMID: 36090365 PMCID: PMC9448878 DOI: 10.3389/fpsyt.2022.928076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 07/14/2022] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND It is difficult to conduct the precise diagnosis of post-stroke depression (PSD) in clinical practice due to the complex psychopathology of depressive disorder. Several studies showed that gas chromatography-mass spectrometry (GC-MS)-identified urinary metabolite biomarkers could significantly discriminate PSD from stroke survivors. METHODS A systematic review was performed for the keywords of "urinary metabolite" and "PSD" using Medline, Cochrane Library, Embase, Web of Science, PsycINFO, Wanfang, CNKI, CBM, and VIP database from inception to 31 March 2022. RESULTS Four related studies were included in the review. Differential urinary metabolites including lactic acid, palmitic acid, azelaic acid, and tyrosine were identified in all the included studies. As a significant deviation in the metabolite biomarker panel, glyceric acid, azelaic acid, phenylalanine, palmitic acid, pseudouridine, and tyrosine were found in at least 2 included studies, which indicated good potential for the differentiation of PSD. CONCLUSION The systematic review provided evidence that differential urinary metabolites analyzed by the GC-MS-based approach might be used as a biomarker for the diagnosis and prognosis of PSD.
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Affiliation(s)
- Wa Cai
- Department of Acupuncture, Shanghai Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xia-Fei Wang
- Department of Neurology, Seventh People's Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xi-Fang Wei
- Department of Acupuncture, Shanghai Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jing-Ruo Zhang
- Department of Acupuncture, Shanghai Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Chen Hu
- Department of Acupuncture, Shanghai Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Wen Ma
- Department of Acupuncture, Shanghai Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Wei-Dong Shen
- Department of Acupuncture, Shanghai Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
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12
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Pathak N, Vimal SK, Tandon I, Agrawal L, Hongyi C, Bhattacharyya S. Neurodegenerative Disorders of Alzheimer, Parkinsonism, Amyotrophic Lateral Sclerosis and Multiple Sclerosis: An Early Diagnostic Approach for Precision Treatment. Metab Brain Dis 2022; 37:67-104. [PMID: 34719771 DOI: 10.1007/s11011-021-00800-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 07/11/2021] [Indexed: 12/21/2022]
Abstract
Neurodegenerative diseases (NDs) are characterised by progressive dysfunction of synapses, neurons, glial cells and their networks. Neurodegenerative diseases can be classified according to primary clinical features (e.g., dementia, parkinsonism, or motor neuron disease), anatomic distribution of neurodegeneration (e.g., frontotemporal degenerations, extrapyramidal disorders, or spinocerebellar degenerations), or principal molecular abnormalities. The most common neurodegenerative disorders are amyloidosis, tauopathies, a-synucleinopathy, and TAR DNA-binding protein 43 (TDP-43) proteopathy. The protein abnormalities in these disorders have abnormal conformational properties along with altered cellular mechanisms, and they exhibit motor deficit, mitochondrial malfunction, dysfunctions in autophagic-lysosomal pathways, synaptic toxicity, and more emerging mechanisms such as the roles of stress granule pathways and liquid-phase transitions. Finally, for each ND, microglial cells have been reported to be implicated in neurodegeneration, in particular, because the microglial responses can shift from neuroprotective to a deleterious role. Growing experimental evidence suggests that abnormal protein conformers act as seed material for oligomerization, spreading from cell to cell through anatomically connected neuronal pathways, which may in part explain the specific anatomical patterns observed in brain autopsy sample. In this review, we mention the human pathology of select neurodegenerative disorders, focusing on how neurodegenerative disorders (i.e., Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and multiple sclerosis) represent a great healthcare problem worldwide and are becoming prevalent because of the increasing aged population. Despite many studies have focused on their etiopathology, the exact cause of these diseases is still largely unknown and until now with the only available option of symptomatic treatments. In this review, we aim to report the systematic and clinically correlated potential biomarker candidates. Although future studies are necessary for their use in early detection and progression in humans affected by NDs, the promising results obtained by several groups leads us to this idea that biomarkers could be used to design a potential therapeutic approach and preclinical clinical trials for the treatments of NDs.
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Affiliation(s)
- Nishit Pathak
- Department of Pharmaceutical Sciences and Chinese Traditional Medicine, Southwest University, Beibei, Chongqing, 400715, People's Republic of China
| | - Sunil Kumar Vimal
- Department of Pharmaceutical Sciences and Chinese Traditional Medicine, Southwest University, Beibei, Chongqing, 400715, People's Republic of China
| | - Ishi Tandon
- Amity University Jaipur, Rajasthan, Jaipur, Rajasthan, India
| | - Lokesh Agrawal
- Graduate School of Comprehensive Human Sciences, Kansei Behavioural and Brain Sciences, University of Tsukuba, 1-1-1, Tennodai, Tsukuba, Ibaraki, 305-8577, Japan
| | - Cao Hongyi
- Department of Pharmaceutical Sciences and Chinese Traditional Medicine, Southwest University, Beibei, Chongqing, 400715, People's Republic of China
| | - Sanjib Bhattacharyya
- Department of Pharmaceutical Sciences and Chinese Traditional Medicine, Southwest University, Beibei, Chongqing, 400715, People's Republic of China.
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13
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Li R, Yang L, Guan S, Lin M, Lai H, Liu K, Liu Z, Zhang X. UPLC-MS-Based Serum Metabolic Profiling Reveals Potential Biomarkers for Predicting Propofol Responsiveness in Females. J Proteome Res 2021; 20:4578-4588. [PMID: 34384217 DOI: 10.1021/acs.jproteome.1c00554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Although previous studies have shown that certain factors interfere with the sensitivity of propofol, the mechanisms for interindividual variability in response to propofol remain unclear. This study aimed to screen the metabolites to predict patients' sensitivity to propofol and to identify metabolic pathways to explore possible mechanisms associated with propofol resistance. Sera from 40 female patients undergoing elective hysteroscopic surgery in a prospective cohort propofol study were obtained before the administration of propofol. The patients' responsiveness to propofol was differentiated based on propofol effect-site concentration. Serum samples from two sets, a discovery set (n = 24) and an independent validation set (n = 16), were analyzed using ultraperformance liquid chromatography coupled with mass spectrometry based untargeted metabolomics. In the discovery set, 494 differential metabolites were screened out, and then 391 potential candidate biomarkers with the area under receiver operating characteristic curve >0.80 were selected. Pathway analysis showed that the pathway of glycerophospholipid metabolism was the most influential pathway. In the independent validation set, six potential biomarkers enabled the discrimination of poor responders from good and intermediate responders, which might be applied to predict propofol sensitivity. The mass spectrometry data are available via MetaboLights (http://www.ebi.ac.uk/metabolights/login) with the identifier MTBLS2311.
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Affiliation(s)
- Ruiyun Li
- Department of Anesthesiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China
| | - Lu Yang
- Department of Anesthesiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China
| | - Su Guan
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China
| | - Ming Lin
- Department of Anesthesiology, Guangdong Provincial Hospital of Traditional Chinese Medicine, Guangzhou 510120, China
| | - Hanjin Lai
- Department of Critical Care Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China
| | - Kun Liu
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China
| | - Zimeng Liu
- Department of Critical Care Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China
| | - Xuyu Zhang
- Department of Anesthesiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China
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14
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Metabolomics-based discrimination of patients with remitted depression from healthy controls using 1H-NMR spectroscopy. Sci Rep 2021; 11:15608. [PMID: 34341439 PMCID: PMC8329159 DOI: 10.1038/s41598-021-95221-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 07/13/2021] [Indexed: 11/24/2022] Open
Abstract
The aim of the study was to investigate differences in metabolic profiles between patients with major depressive disorder (MDD) with full remission (FR) and healthy controls (HCs). A total of 119 age-matched MDD patients with FR (n = 47) and HCs (n = 72) were enrolled and randomly split into training and testing sets. A 1H-nuclear magnetic resonance (NMR) spectroscopy-based metabolomics approach was used to identify differences in expressions of plasma metabolite biomarkers. Eight metabolites, including histidine, succinic acid, proline, acetic acid, creatine, glutamine, glycine, and pyruvic acid, were significantly differentially-expressed in the MDD patients with FR in comparison with the HCs. Metabolic pathway analysis revealed that pyruvate metabolism via the tricarboxylic acid cycle linked to amino acid metabolism was significantly associated with the MDD patients with FR. An algorithm based on these metabolites employing a linear support vector machine differentiated the MDD patients with FR from the HCs with a predictive accuracy, sensitivity, and specificity of nearly 0.85. A metabolomics-based approach could effectively differentiate MDD patients with FR from HCs. Metabolomic signatures might exist long-term in MDD patients, with metabolic impacts on physical health even in patients with FR.
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15
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MahmoudianDehkordi S, Ahmed AT, Bhattacharyya S, Han X, Baillie RA, Arnold M, Skime MK, John-Williams LS, Moseley MA, Thompson JW, Louie G, Riva-Posse P, Craighead WE, McDonald W, Krishnan R, Rush AJ, Frye MA, Dunlop BW, Weinshilboum RM, Kaddurah-Daouk R. Alterations in acylcarnitines, amines, and lipids inform about the mechanism of action of citalopram/escitalopram in major depression. Transl Psychiatry 2021; 11:153. [PMID: 33654056 PMCID: PMC7925685 DOI: 10.1038/s41398-020-01097-6] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Revised: 10/01/2020] [Accepted: 10/26/2020] [Indexed: 12/11/2022] Open
Abstract
Selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for major depressive disorder (MDD), yet their mechanisms of action are not fully understood and their therapeutic benefit varies among individuals. We used a targeted metabolomics approach utilizing a panel of 180 metabolites to gain insights into mechanisms of action and response to citalopram/escitalopram. Plasma samples from 136 participants with MDD enrolled into the Mayo Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) were profiled at baseline and after 8 weeks of treatment. After treatment, we saw increased levels of short-chain acylcarnitines and decreased levels of medium-chain and long-chain acylcarnitines, suggesting an SSRI effect on β-oxidation and mitochondrial function. Amines-including arginine, proline, and methionine sulfoxide-were upregulated while serotonin and sarcosine were downregulated, suggesting an SSRI effect on urea cycle, one-carbon metabolism, and serotonin uptake. Eighteen lipids within the phosphatidylcholine (PC aa and ae) classes were upregulated. Changes in several lipid and amine levels correlated with changes in 17-item Hamilton Rating Scale for Depression scores (HRSD17). Differences in metabolic profiles at baseline and post-treatment were noted between participants who remitted (HRSD17 ≤ 7) and those who gained no meaningful benefits (<30% reduction in HRSD17). Remitters exhibited (a) higher baseline levels of C3, C5, alpha-aminoadipic acid, sarcosine, and serotonin; and (b) higher week-8 levels of PC aa C34:1, PC aa C34:2, PC aa C36:2, and PC aa C36:4. These findings suggest that mitochondrial energetics-including acylcarnitine metabolism, transport, and its link to β-oxidation-and lipid membrane remodeling may play roles in SSRI treatment response.
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Affiliation(s)
- Siamak MahmoudianDehkordi
- grid.26009.3d0000 0004 1936 7961Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, Durham, NC USA
| | - Ahmed T. Ahmed
- grid.66875.3a0000 0004 0459 167XDepartment of Neurology, Mayo Clinic, Rochester, MN USA
| | - Sudeepa Bhattacharyya
- grid.252381.f0000 0001 2169 5989Department of Biological Sciences and Arkansas Biosciences Institute, Arkansas State University, Jonesboro, AR USA
| | - Xianlin Han
- grid.267309.90000 0001 0629 5880University of Texas Health Science Center at San Antonio, San Antonio, TX USA
| | | | - Matthias Arnold
- grid.26009.3d0000 0004 1936 7961Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, Durham, NC USA ,grid.4567.00000 0004 0483 2525Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Michelle K. Skime
- grid.66875.3a0000 0004 0459 167XDepartment of Psychiatry and Psychology, Mayo Clinic, Rochester, MN USA
| | - Lisa St. John-Williams
- grid.26009.3d0000 0004 1936 7961Proteomics and Metabolomics Shared Resource, Center for Genomic and Computational Biology, Duke University, Durham, NC 27710 USA
| | - M. Arthur Moseley
- grid.26009.3d0000 0004 1936 7961Proteomics and Metabolomics Shared Resource, Center for Genomic and Computational Biology, Duke University, Durham, NC 27710 USA
| | - J. Will Thompson
- grid.26009.3d0000 0004 1936 7961Proteomics and Metabolomics Shared Resource, Center for Genomic and Computational Biology, Duke University, Durham, NC 27710 USA
| | - Gregory Louie
- grid.26009.3d0000 0004 1936 7961Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, Durham, NC USA
| | - Patricio Riva-Posse
- grid.189967.80000 0001 0941 6502Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA USA
| | - W. Edward Craighead
- grid.189967.80000 0001 0941 6502Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA USA
| | - William McDonald
- grid.189967.80000 0001 0941 6502Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA USA
| | - Ranga Krishnan
- grid.262743.60000000107058297Department of Psychiatry, Rush Medical College, Chicago, IL USA
| | - A. John Rush
- grid.26009.3d0000 0004 1936 7961Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, Durham, NC USA ,grid.26009.3d0000 0004 1936 7961Professor Emeritus, Department of Pediatrics, Duke University School of Medicine, Durham, NC USA ,grid.416992.10000 0001 2179 3554Department of Psychiatry, Texas Tech University, Health Sciences Center, Permian Basin, TX USA
| | - Mark A. Frye
- grid.66875.3a0000 0004 0459 167XDepartment of Psychiatry and Psychology, Mayo Clinic, Rochester, MN USA
| | - Boadie W. Dunlop
- grid.189967.80000 0001 0941 6502Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA USA
| | - Richard M. Weinshilboum
- grid.66875.3a0000 0004 0459 167XDepartment of Molecular Pharmacology & Experimental Therapeutics, Mayo Clinic, Rochester, MN USA
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, Durham, NC, USA. .,Department of Medicine, Duke University, Durham, NC, USA. .,Duke Institute of Brain Sciences, Duke University, Durham, NC, USA.
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16
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A metabolome-wide association study in the general population reveals decreased levels of serum laurylcarnitine in people with depression. Mol Psychiatry 2021; 26:7372-7383. [PMID: 34088979 PMCID: PMC8873015 DOI: 10.1038/s41380-021-01176-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Revised: 05/07/2021] [Accepted: 05/17/2021] [Indexed: 02/05/2023]
Abstract
Depression constitutes a leading cause of disability worldwide. Despite extensive research on its interaction with psychobiological factors, associated pathways are far from being elucidated. Metabolomics, assessing the final products of complex biochemical reactions, has emerged as a valuable tool for exploring molecular pathways. We conducted a metabolome-wide association analysis to investigate the link between the serum metabolome and depressed mood (DM) in 1411 participants of the KORA (Cooperative Health Research in the Augsburg Region) F4 study (discovery cohort). Serum metabolomics data comprised 353 unique metabolites measured by Metabolon. We identified 72 (5.1%) KORA participants with DM. Linear regression tests were conducted modeling each metabolite value by DM status, adjusted for age, sex, body-mass index, antihypertensive, cardiovascular, antidiabetic, and thyroid gland hormone drugs, corticoids and antidepressants. Sensitivity analyses were performed in subcohorts stratified for sex, suicidal ideation, and use of antidepressants. We replicated our results in an independent sample of 968 participants of the SHIP-Trend (Study of Health in Pomerania) study including 52 (5.4%) individuals with DM (replication cohort). We found significantly lower laurylcarnitine levels in KORA F4 participants with DM after multiple testing correction according to Benjamini/Hochberg. This finding was replicated in the independent SHIP-Trend study. Laurylcarnitine remained significantly associated (p value < 0.05) with depression in samples stratified for sex, suicidal ideation, and antidepressant medication. Decreased blood laurylcarnitine levels in depressed individuals may point to impaired fatty acid oxidation and/or mitochondrial function in depressive disorders, possibly representing a novel therapeutic target.
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Saigusa D, Matsukawa N, Hishinuma E, Koshiba S. Identification of biomarkers to diagnose diseases and find adverse drug reactions by metabolomics. Drug Metab Pharmacokinet 2020; 37:100373. [PMID: 33631535 DOI: 10.1016/j.dmpk.2020.11.008] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 11/24/2020] [Accepted: 11/25/2020] [Indexed: 12/12/2022]
Abstract
Metabolomics has been widely used for investigating the biological functions of disease expression and has the potential to discover biomarkers in circulating biofluids or tissue extracts that reflect in phenotypic changes. Metabolic profiling has advantages because of the use of unbiased techniques, including multivariate analysis, and has been applied in pharmacological studies to predict therapeutic and adverse reactions of drugs, which is called pharmacometabolomics (PMx). Nuclear magnetic resonance (NMR)- and mass spectrometry (MS)-based metabolomics has contributed to the discovery of recent disease biomarkers; however, the optimal strategy for the study purpose must be selected from many established protocols, methodologies and analytical platforms. Additionally, information on molecular localization in tissue is essential for further functional analyses related to therapeutic and adverse effects of drugs in the process of drug development. MS imaging (MSI) is a promising technology that can visualize molecules on tissue surfaces without labeling and thus provide localized information. This review summarizes recent uses of MS-based global and wide-targeted metabolomics technologies and the advantages of the MSI approach for PMx and highlights the PMx technique for the biomarker discovery of adverse drug effects.
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Affiliation(s)
- Daisuke Saigusa
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan.
| | - Naomi Matsukawa
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan.
| | - Eiji Hishinuma
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
| | - Seizo Koshiba
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan; Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
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18
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Erabi H, Okada G, Shibasaki C, Setoyama D, Kang D, Takamura M, Yoshino A, Fuchikami M, Kurata A, Kato TA, Yamawaki S, Okamoto Y. Kynurenic acid is a potential overlapped biomarker between diagnosis and treatment response for depression from metabolome analysis. Sci Rep 2020; 10:16822. [PMID: 33033336 PMCID: PMC7545168 DOI: 10.1038/s41598-020-73918-z] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Accepted: 09/24/2020] [Indexed: 02/06/2023] Open
Abstract
Since optimal treatment at an early stage leads to remission of symptoms and recovery of function, putative biomarkers leading to early diagnosis and prediction of therapeutic responses are desired. The current study aimed to use a metabolomic approach to extract metabolites involved in both the diagnosis of major depressive disorder (MDD) and the prediction of therapeutic response for escitalopram. We compared plasma metabolites of MDD patients (n = 88) with those in healthy participants (n = 88) and found significant differences in the concentrations of 20 metabolites. We measured the Hamilton Rating Scale for Depression (HRSD) on 62 patients who completed approximately six-week treatment with escitalopram before and after treatment and found that kynurenic acid and kynurenine were significantly and negatively associated with HRSD reduction. Only one metabolite, kynurenic acid, was detected among 73 metabolites for overlapped biomarkers. Kynurenic acid was lower in MDD, and lower levels showed a better therapeutic response to escitalopram. Kynurenic acid is a metabolite in the kynurenine pathway that has been widely accepted as being a major mechanism in MDD. Overlapping biomarkers that facilitate diagnosis and prediction of the treatment response may help to improve disease classification and reduce the exposure of patients to less effective treatments in MDD.
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Affiliation(s)
- Hisayuki Erabi
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Go Okada
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Chiyo Shibasaki
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Daiki Setoyama
- Department of Clinical Chemistry and Laboratory Medicine, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi Higashi-Ku, Fukuoka, 812-8582, Japan
| | - Dongchon Kang
- Department of Clinical Chemistry and Laboratory Medicine, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi Higashi-Ku, Fukuoka, 812-8582, Japan
| | - Masahiro Takamura
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Atsuo Yoshino
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Manabu Fuchikami
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Akiko Kurata
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Takahiro A Kato
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi Higashi-Ku, Fukuoka, 812-8582, Japan
| | - Shigeto Yamawaki
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Yasumasa Okamoto
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan.
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Kubacka J, Stefańska A, Sypniewska G. Kynurenine pathway: the link between depressive disorders and inflammation. POSTEP HIG MED DOSW 2020. [DOI: 10.5604/01.3001.0014.3454] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Depression is highly prevalent worldwide and the leading cause of disability. It is believed that currently more than 300 million people of all ages suffer from depression. However, the unambiguous cause of the depression remains unknown. It is suggested that the occurrence of this disease is primarily affected by genetic factors, psychological factors and atypical brain structure or function. Recently, an increasingly important role is attributed to the inflammatory response, which is considered to be the main cause of depression. Activation of the kynurenine pathway (KP) is one of the described mechanisms by which inflammation can induce depression. Kynurenine pathway activation is associated with several neuropsychiatric diseases, including major depression disorder (MDD). The imbalance between the neuroprotective and neurotoxic metabolites in the kynurenine pathway and the associated serotonin and melatonin deficiency, may contribute to the manifestation of depressive symptoms. In this review we discuss the role of the major enzymes of the tryptophan KP: tryptophan 2,3-dioxygenase (TDO) and indoleamine 2,3-dioxygenase (IDO) and the role of selected kynurenic metabolites in the depressive disorders. Particular attention was also paid to the genetic basis of depressive disorders and to the summary of current knowledge on the effectiveness of treatment and supplementation with tryptophan and 5-hydroxytryptophan in depression.
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Affiliation(s)
- Justyna Kubacka
- Department of Laboratory Medicine, Ludwik Rydygier Collegium Medicum in Bydgoszcz Nicolaus Copernicus University in Toruń, Bydgoszcz, Poland
| | - Anna Stefańska
- Department of Laboratory Medicine, Ludwik Rydygier Collegium Medicum in Bydgoszcz Nicolaus Copernicus University in Toruń, Bydgoszcz, Poland
| | - Grażyna Sypniewska
- Department of Laboratory Medicine, Ludwik Rydygier Collegium Medicum in Bydgoszcz Nicolaus Copernicus University in Toruń, Bydgoszcz, Poland
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20
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Duan J, Xie P. The potential for metabolomics in the study and treatment of major depressive disorder and related conditions. Expert Rev Proteomics 2020; 17:309-322. [DOI: 10.1080/14789450.2020.1772059] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Affiliation(s)
- Jiajia Duan
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, Chongqing Medical University, Chongqing, China
- The M.O.E. Key Laboratory of Laboratory Medical Diagnostics, The College of Laboratory Medicine, Chongqing Medical University, Chongqing, China
| | - Peng Xie
- NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, Chongqing Medical University, Chongqing, China
- The M.O.E. Key Laboratory of Laboratory Medical Diagnostics, The College of Laboratory Medicine, Chongqing Medical University, Chongqing, China
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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Steen NE, Dieset I, Hope S, Vedal TSJ, Smeland OB, Matson W, Kaddurah-Daouk R, Agartz I, Melle I, Djurovic S, Jönsson EG, Bogdanov M, Andreassen OA. Metabolic dysfunctions in the kynurenine pathway, noradrenergic and purine metabolism in schizophrenia and bipolar disorders. Psychol Med 2020; 50:595-606. [PMID: 30867076 DOI: 10.1017/s0033291719000400] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
BACKGROUND We aimed at exploring potential pathophysiological processes across psychotic disorders, applying metabolomics in a large and well-characterized sample of patients and healthy controls. METHODS Patients with schizophrenia and bipolar disorders (N = 212) and healthy controls (N = 68) had blood sampling with subsequent metabolomics analyses using electrochemical coulometric array detection. Concentrations of 52 metabolites including tyrosine, tryptophan and purine pathways were compared between patients and controls while controlling for demographic and clinical characteristics. Significant findings were further tested in medication-free subsamples. RESULTS Significantly decreased plasma concentrations in patients compared to healthy controls were found for 3-hydroxykynurenine (3OHKY, p = 0.0008), xanthurenic acid (XANU, p = 1.5×10-5), vanillylmandelic acid (VMA, p = 4.5×10-5) and metanephrine (MN, p = 0.0001). Plasma concentration of xanthine (XAN) was increased in the patient group (p = 3.5×10-5). Differences of 3OHKY, XANU, VMA and XAN were replicated across schizophrenia spectrum disorders and bipolar disorders subsamples of medication-free individuals. CONCLUSIONS Although prone to residual confounding, the present results suggest the kynurenine pathway of tryptophan metabolism, noradrenergic and purinergic system dysfunction as trait factors in schizophrenia spectrum and bipolar disorders. Of special interest is XANU, a metabolite previously not found to be associated with bipolar disorders.
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Affiliation(s)
- Nils Eiel Steen
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ingrid Dieset
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Sigrun Hope
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Neurohabilitation, Oslo University Hospital, Oslo, Norway
| | - Trude S J Vedal
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Olav B Smeland
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Neuroscience, University of California San Diego, La Jolla, CA92093, USA
| | | | - Rima Kaddurah-Daouk
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA
- Duke Institute of Brain Sciences, Duke University, Durham, NC, USA
- Department of Medicine, Duke University, Durham, NC, USA
| | - Ingrid Agartz
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Ingrid Melle
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Srdjan Djurovic
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Erik G Jönsson
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Clinical Neuroscience, Centre for Psychiatric Research, Karolinska Institutet, Stockholm, Sweden
| | | | - Ole A Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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22
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Twayej AJ, Al-Hakeim HK, Al-Dujaili AH, Maes M. Lowered zinc and copper levels in drug-naïve patients with major depression: Effects of antidepressants, ketoprofen and immune activation. World J Biol Psychiatry 2020; 21:127-138. [PMID: 31062629 DOI: 10.1080/15622975.2019.1612090] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Objectives: The aim of the present work is to examine the effects of treatment with sertraline with and without ketoprofen on serum levels of zinc and copper in association with immune-inflammatory biomarkers in drug-naïve major depressed patients.Methods: We measured serum zinc and copper, interleukin (IL)-1β, IL-4, IL-6, IL-18, interferon-γ, and transforming growth factor-β1 in 40 controls and 133 depressed patients. The clinical efficacy of the treatment was measured using the Beck Depression Inventory-II (BDI-II) at baseline and 8 weeks later.Results: We found significantly reduced serum zinc and copper in association with upregulation of all cytokines, indicating activation of the immune-inflammatory responses system (IRS) and the compensatory immune regulatory system (CIRS). Treatment with sertraline significantly increased zinc and decreased copper. During treatment, there was a significant inverse association between serum zinc and immune activation. The improvement in the BDI-II during treatment was significantly associated with increments in serum zinc coupled with attenuation of the IRS/CIRS.Conclusions: Lower zinc is a hallmark of depression, while increments in serum zinc and attenuation of the immune-inflammatory response during treatment appear to play a role in the clinical efficacy of sertraline.
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Affiliation(s)
- Ahmed Jasim Twayej
- Pathological Analysis Department, College of Health and Medical Techniques, Al-Kafeel University, Najaf, Iraq
| | | | | | - Michael Maes
- Department of Psychiatry, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.,Department of Psychiatry, Medical University of Plovdiv, Plovdiv, Bulgaria.,School of Medicine, IMPACT Strategic Research Centre, Deakin University, Geelong, Australia
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23
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Colle R, Masson P, Verstuyft C, Fève B, Werner E, Boursier-Neyret C, Walther B, David DJ, Boniface B, Falissard B, Chanson P, Corruble E, Becquemont L. Peripheral tryptophan, serotonin, kynurenine, and their metabolites in major depression: A case-control study. Psychiatry Clin Neurosci 2020; 74:112-117. [PMID: 31599111 DOI: 10.1111/pcn.12944] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Revised: 09/23/2019] [Accepted: 10/04/2019] [Indexed: 12/13/2022]
Abstract
AIM Tryptophan is the sole precursor of both peripherally and centrally produced serotonin and kynurenine. In depressed patients, tryptophan, serotonin, kynurenine, and their metabolite levels remain unclear. Therefore, peripheral tryptophan and metabolites of serotonin and kynurenine were investigated extensively in 173 patients suffering from a current major depressive episode (MDE) and compared to 214 healthy controls (HC). METHODS Fasting plasma levels of 11 peripheral metabolites were quantified: tryptophan, serotonin pathway (serotonin, its precursor 5-hydroxytryptophan and its metabolite 5-hydroxyindoleacetic acid), and kynurenine pathway (kynurenine and six of its metabolites: anthranilic acid, kynurenic acid, nicotinamide, picolinic acid, xanthurenic acid, and 3-hydroxyanthranilic acid). RESULTS Sixty (34.7%) patients were antidepressant-drug free. Tryptophan levels did not differ between MDE patients and HC. Serotonin and its precursor (5-hydroxytryptophan) levels were lower in MDE patients than in HC, whereas, its metabolite (5-hydroxyindoleacetic acid) levels were within the standard range. Kynurenine and four of its metabolites (kynurenic acid, nicotinamide, picolinic acid, and xanthurenic acid) were lower in MDE patients. CONCLUSION Whilst the results of this study demonstrate an association between the metabolites studied and depression, conclusions about causality cannot be made. This study uses the largest ever sample of MDE patients, with an extensive assessment of peripheral tryptophan metabolism in plasma. These findings provide new insights into the peripheral signature of MDE. The reasons for these changes should be further investigated. These results might suggest new antidepressant therapeutic strategies.
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Affiliation(s)
- Romain Colle
- INSERM UMR-1178, CESP, Faculté de Médecine Paris-Sud, Paris-Saclay University, Le Kremlin Bicêtre, France.,Service Hospitalo-Universitaire de Psychiatrie, Assistance Publique-Hôpitaux de Paris, Hôpitaux Universitaires Paris-Sud, Hôpital de Bicêtre, Le Kremlin Bicêtre, France
| | - Perrine Masson
- Pharmacokinetics Center, Technologie Servier, Orléans, France
| | - Céline Verstuyft
- INSERM UMR-1178, CESP, Faculté de Médecine Paris-Sud, Paris-Saclay University, Le Kremlin Bicêtre, France.,Service de Génétique moléculaire, Pharmacogénétique et Hormonologie, Assistance Publique-Hôpitaux de Paris, Hôpitaux Universitaires Paris-Sud, Hôpital de Bicêtre, Le Kremlin Bicêtre, France
| | - Bruno Fève
- Service d'endocrinologie, Hôpital Saint-Antoine, Assistance Publique Hôpitaux de Paris, Paris, France.,Sorbonne Université, INSERM UMR S_938, Centre de Recherche Saint-Antoine, Paris, France
| | - Erwan Werner
- Pharmacokinetics Center, Technologie Servier, Orléans, France
| | | | - Bernard Walther
- Pharmacokinetics Center, Technologie Servier, Orléans, France
| | - Denis J David
- INSERM UMR-1178, CESP, Faculté de Médecine Paris-Sud, Paris-Saclay University, Le Kremlin Bicêtre, France
| | - Bruno Boniface
- INSERM UMR-1178, CESP, Faculté de Médecine Paris-Sud, Paris-Saclay University, Le Kremlin Bicêtre, France
| | - Bruno Falissard
- INSERM UMR-1178, CESP, Faculté de Médecine Paris-Sud, Paris-Saclay University, Le Kremlin Bicêtre, France.,Département de Biostatistiques, Paris-Sud University, Hôpital Paul Brousse, Assistance Publique Hôpitaux de Paris, Villejuif, France
| | - Philippe Chanson
- Assistance Publique-Hôpitaux de Paris, Hôpital de Bicêtre, Service d'Endocrinologie et des Maladies de la Reproduction, Centre de Référence des Maladies Rares de l'Hypophyse, Le Kremlin Bicêtre, F-94275, and INSERM 1185, Faculté de Médecine Paris-Sud, Paris-Sud University, Paris-Saclay University, Le Kremlin-Bicêtre, France
| | - Emmanuelle Corruble
- INSERM UMR-1178, CESP, Faculté de Médecine Paris-Sud, Paris-Saclay University, Le Kremlin Bicêtre, France.,Service Hospitalo-Universitaire de Psychiatrie, Assistance Publique-Hôpitaux de Paris, Hôpitaux Universitaires Paris-Sud, Hôpital de Bicêtre, Le Kremlin Bicêtre, France
| | - Laurent Becquemont
- INSERM UMR-1178, CESP, Faculté de Médecine Paris-Sud, Paris-Saclay University, Le Kremlin Bicêtre, France.,Service de Génétique moléculaire, Pharmacogénétique et Hormonologie, Assistance Publique-Hôpitaux de Paris, Hôpitaux Universitaires Paris-Sud, Hôpital de Bicêtre, Le Kremlin Bicêtre, France
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24
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Bhattacharyya S, Dunlop BW, Mahmoudiandehkordi S, Ahmed AT, Louie G, Frye MA, Weinshilboum RM, Krishnan RR, Rush AJ, Mayberg HS, Craighead WE, Kaddurah-Daouk R. Pilot Study of Metabolomic Clusters as State Markers of Major Depression and Outcomes to CBT Treatment. Front Neurosci 2019; 13:926. [PMID: 31572108 PMCID: PMC6751322 DOI: 10.3389/fnins.2019.00926] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Accepted: 08/19/2019] [Indexed: 11/16/2022] Open
Abstract
Major depressive disorder (MDD) is a common and disabling syndrome with multiple etiologies that is defined by clinically elicited signs and symptoms. In hopes of developing a list of candidate biological measures that reflect and relate closely to the severity of depressive symptoms, so-called “state-dependent” biomarkers of depression, this pilot study explored the biochemical underpinnings of treatment response to cognitive behavior therapy (CBT) in medication-free MDD outpatients. Plasma samples were collected at baseline and week 12 from a subset of MDD patients (N = 26) who completed a course of CBT treatment as part of the Predictors of Remission in Depression to Individual and Combined Treatments (PReDICT) study. Targeted metabolomic profiling using the AbsoluteIDQ® p180 Kit and LC-MS identified eight “co-expressed” metabolomic modules. Of these eight, three were significantly associated with change in depressive symptoms over the course of the 12-weeks. Metabolites found to be most strongly correlated with change in depressive symptoms were branched chain amino acids, acylcarnitines, methionine sulfoxide, and α-aminoadipic acid (negative correlations with symptom change) as well as several lipids, particularly the phosphatidlylcholines (positive correlation). These results implicate disturbed bioenergetics as an important state marker in the pathobiology of MDD. Exploratory analyses contrasting remitters to CBT versus those who failed the treatment further suggest these metabolites may serve as mediators of recovery during CBT treatment. Larger studies examining metabolomic change patterns in patients treated with pharmacotherapy or psychotherapy will be necessary to elucidate the biological underpinnings of MDD and the -specific biologies of treatment response.
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Affiliation(s)
- Sudeepa Bhattacharyya
- Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Boadie W Dunlop
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States
| | - Siamak Mahmoudiandehkordi
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States
| | - Ahmed T Ahmed
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
| | - Gregory Louie
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States.,Department of Medicine, Duke University, Durham, NC, United States.,Duke Institute for Brain Sciences, Duke University, Durham, NC, United States
| | - Mark A Frye
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
| | - Richard M Weinshilboum
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, United States
| | - Ranga R Krishnan
- Department of Psychiatry, Rush University Medical Center, Chicago, IL, United States
| | - A John Rush
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States.,Department of Psychiatry, Texas Tech University, Health Sciences Center, Permian Basin, TX, United States.,Duke-NUS Medical School, Singapore, Singapore
| | - Helen S Mayberg
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States.,Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - W Edward Craighead
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States.,Department of Medicine, Duke University, Durham, NC, United States.,Duke Institute for Brain Sciences, Duke University, Durham, NC, United States
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25
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Bhattacharyya S, Ahmed AT, Arnold M, Liu D, Luo C, Zhu H, Mahmoudiandehkordi S, Neavin D, Louie G, Dunlop BW, Frye MA, Wang L, Weinshilboum RM, Krishnan RR, Rush AJ, Kaddurah-Daouk R. Metabolomic signature of exposure and response to citalopram/escitalopram in depressed outpatients. Transl Psychiatry 2019; 9:173. [PMID: 31273200 PMCID: PMC6609722 DOI: 10.1038/s41398-019-0507-5] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Revised: 03/29/2019] [Accepted: 04/29/2019] [Indexed: 12/28/2022] Open
Abstract
Metabolomics provides valuable tools for the study of drug effects, unraveling the mechanism of action and variation in response due to treatment. In this study we used electrochemistry-based targeted metabolomics to gain insights into the mechanisms of action of escitalopram/citalopram focusing on a set of 31 metabolites from neurotransmitter-related pathways. Overall, 290 unipolar patients with major depressive disorder were profiled at baseline, after 4 and 8 weeks of drug treatment. The 17-item Hamilton Depression Rating Scale (HRSD17) scores gauged depressive symptom severity. More significant metabolic changes were found after 8 weeks than 4 weeks post baseline. Within the tryptophan pathway, we noted significant reductions in serotonin (5HT) and increases in indoles that are known to be influenced by human gut microbial cometabolism. 5HT, 5-hydroxyindoleacetate (5HIAA), and the ratio of 5HIAA/5HT showed significant correlations to temporal changes in HRSD17 scores. In the tyrosine pathway, changes were observed in the end products of the catecholamines, 3-methoxy-4-hydroxyphenylethyleneglycol and vinylmandelic acid. Furthermore, two phenolic acids, 4-hydroxyphenylacetic acid and 4-hydroxybenzoic acid, produced through noncanconical pathways, were increased with drug exposure. In the purine pathway, significant reductions in hypoxanthine and xanthine levels were observed. Examination of metabolite interactions through differential partial correlation networks revealed changes in guanosine-homogentisic acid and methionine-tyrosine interactions associated with HRSD17. Genetic association studies using the ratios of these interacting pairs of metabolites highlighted two genetic loci harboring genes previously linked to depression, neurotransmission, or neurodegeneration. Overall, exposure to escitalopram/citalopram results in shifts in metabolism through noncanonical pathways, which suggest possible roles for the gut microbiome, oxidative stress, and inflammation-related mechanisms.
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Affiliation(s)
- Sudeepa Bhattacharyya
- Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Ahmed T Ahmed
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Matthias Arnold
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, Durham, NC, USA
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Duan Liu
- Department of Molecular Pharmacology & Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
| | - Chunqiao Luo
- Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | | | - Siamak Mahmoudiandehkordi
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, Durham, NC, USA
| | - Drew Neavin
- Department of Molecular Pharmacology & Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
| | - Gregory Louie
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, Durham, NC, USA
| | - Boadie W Dunlop
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Mark A Frye
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Liewei Wang
- Department of Molecular Pharmacology & Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
| | - Richard M Weinshilboum
- Department of Molecular Pharmacology & Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
| | - Ranga R Krishnan
- Department of Psychiatry, Rush University Medical Center, Chicago, IL, USA
| | - A John Rush
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, Durham, NC, USA
- Texas Tech University, Health Sciences Center, Permian Basin, Odessa, TX, USA
- Duke-National University of Singapore, Singapore, Singapore
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, Durham, NC, USA.
- Department of Medicine, Duke University, Durham, NC, USA.
- Duke Institute of Brain Sciences, Duke University, Durham, NC, USA.
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26
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Napoli E, Schneider A, Wang JY, Trivedi A, Carrillo NR, Tassone F, Rogawski M, Hagerman RJ, Giulivi C. Allopregnanolone Treatment Improves Plasma Metabolomic Profile Associated with GABA Metabolism in Fragile X-Associated Tremor/Ataxia Syndrome: a Pilot Study. Mol Neurobiol 2019; 56:3702-3713. [PMID: 30187385 PMCID: PMC6401336 DOI: 10.1007/s12035-018-1330-3] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Accepted: 08/22/2018] [Indexed: 12/17/2022]
Abstract
Currently, there is no effective treatment for the fragile X-associated tremor/ataxia syndrome (FXTAS), a late-onset neurodegenerative disorder. In this pilot study, we evaluated whether allopregnanolone, a natural neurosteroid that exerts beneficial effects in neurodegenerative diseases, nervous system injury, and peripheral neuropathies, could improve lymphocytic bioenergetics and plasma pharmacometabolomics in six males with FXTAS (68 ± 3 years old; FMR1 CGG repeats 94 ± 4; FXTAS stages ranging from 3 to 5) enrolled in a 12-week open-label intervention study conducted at the University of California Davis from December 2015 through July 2016. Plasma pharmacometabolomics and lymphocytic mitochondria function were assessed at baseline (on the day of the first infusion) and at follow-up (within 48 h from the last infusion). In parallel, quantitative measurements of tremor and ataxia and neuropsychological evaluations of mental state, executive function, learning, memory, and psychological symptoms were assessed at the same time points. Allopregnanolone treatment impacted significantly GABA metabolism, oxidative stress, and some of the mitochondria-related outcomes. Notably, the magnitude of the individual metabolic response, as well as the correlation with some of the behavioral tests, was overwhelmingly carrier-specific. Based on this pilot study, allopregnanolone treatment has the potential for improving cognitive and GABA metabolism in FXTAS aligned with the concept of precision medicine.
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Affiliation(s)
- Eleonora Napoli
- Department of Molecular Biosciences, School of Veterinary Medicine, University of California Davis, Davis, CA, 95616, USA
| | - Andrea Schneider
- Department of Pediatrics, School of Medicine, University of California Davis, Sacramento, CA, USA
- UC Davis Health, UC Davis MIND Institute, Sacramento, CA, USA
| | - Jun Yi Wang
- UC Davis Health, UC Davis MIND Institute, Sacramento, CA, USA
- Department of Biochemistry and Molecular Medicine, School of Medicine, University of California Davis, Sacramento, CA, USA
| | - Aditi Trivedi
- School of Medicine, University of California Davis, Sacramento, CA, USA
| | - Nika Roa Carrillo
- School of Medicine, University of California Davis, Sacramento, CA, USA
| | - Flora Tassone
- UC Davis Health, UC Davis MIND Institute, Sacramento, CA, USA
- Department of Biochemistry and Molecular Medicine, School of Medicine, University of California Davis, Sacramento, CA, USA
| | - Michael Rogawski
- Department of Neurology, School of Medicine, University of California Davis, Sacramento, CA, USA
| | - Randi J Hagerman
- Department of Pediatrics, School of Medicine, University of California Davis, Sacramento, CA, USA
- UC Davis Health, UC Davis MIND Institute, Sacramento, CA, USA
| | - Cecilia Giulivi
- Department of Molecular Biosciences, School of Veterinary Medicine, University of California Davis, Davis, CA, 95616, USA.
- UC Davis Health, UC Davis MIND Institute, Sacramento, CA, USA.
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27
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Hack LM, Fries GR, Eyre HA, Bousman CA, Singh AB, Quevedo J, John VP, Baune BT, Dunlop BW. Moving pharmacoepigenetics tools for depression toward clinical use. J Affect Disord 2019; 249:336-346. [PMID: 30802699 PMCID: PMC6763314 DOI: 10.1016/j.jad.2019.02.009] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Revised: 02/01/2019] [Accepted: 02/05/2019] [Indexed: 12/13/2022]
Abstract
BACKGROUND Major depressive disorder (MDD) is a leading cause of disability worldwide, and over half of patients do not achieve symptom remission following an initial antidepressant course. Despite evidence implicating a strong genetic basis for the pathophysiology of MDD, there are no adequately validated biomarkers of treatment response routinely used in clinical practice. Pharmacoepigenetics is an emerging field that has the potential to combine both genetic and environmental information into treatment selection and further the goal of precision psychiatry. However, this field is in its infancy compared to the more established pharmacogenetics approaches. METHODS We prepared a narrative review using literature searches of studies in English pertaining to pharmacoepigenetics and treatment of depressive disorders conducted in PubMed, Google Scholar, PsychINFO, and Ovid Medicine from inception through January 2019. We reviewed studies of DNA methylation and histone modifications in both humans and animal models of depression. RESULTS Emerging evidence from human and animal work suggests a key role for epigenetic marks, including DNA methylation and histone modifications, in the prediction of antidepressant response. The challenges of heterogeneity of patient characteristics and loci studied as well as lack of replication that have impacted the field of pharmacogenetics also pose challenges to the development of pharmacoepigenetic tools. Additionally, given the tissue specific nature of epigenetic marks as well as their susceptibility to change in response to environmental factors and aging, pharmacoepigenetic tools face additional challenges to their development. LIMITATIONS This is a narrative and not systematic review of the literature on the pharmacoepigenetics of antidepressant response. We highlight key studies pertaining to pharmacoepigenetics and treatment of depressive disorders in humans and depressive-like behaviors in animal models, regardless of sample size or methodology. While we discuss DNA methylation and histone modifications, we do not cover microRNAs, which have been reviewed elsewhere recently. CONCLUSIONS Utilization of genome-wide approaches and reproducible epigenetic assays, careful selection of the tissue assessed, and integration of genetic and clinical information into pharmacoepigenetic tools will improve the likelihood of developing clinically useful tests.
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Affiliation(s)
- Laura M Hack
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Emory University, Atlanta, GA, USA; Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Road, Palo Alto, CA 94305, USA; Sierra Pacific Mental Illness Research Education and Clinical Centers, VA Palo Alto Health Care System, Palo Alto, CA, USA.
| | - Gabriel R Fries
- Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston (UTHealth), Houston, TX, USA
| | - Harris A Eyre
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Road, Palo Alto, CA 94305, USA; Innovation Institute, Texas Medical Center, Houston, TX, USA; IMPACT SRC, School of Medicine, Deakin University, Geelong, Victoria, Australia; Department of Psychiatry, University of Melbourne, Melbourne, Victoria, Australia
| | - Chad A Bousman
- Departments of Medical Genetics, Psychiatry, Physiology & Pharmacology, University of Calgary, Calgary, AB, Canada
| | - Ajeet B Singh
- IMPACT SRC, School of Medicine, Deakin University, Geelong, Victoria, Australia
| | - Joao Quevedo
- Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston (UTHealth), Houston, TX, USA
| | - Vineeth P John
- Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston (UTHealth), Houston, TX, USA
| | - Bernhard T Baune
- Department of Psychiatry, University of Melbourne, Melbourne, Victoria, Australia
| | - Boadie W Dunlop
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Emory University, Atlanta, GA, USA
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28
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Czysz AH, South C, Gadad BS, Arning E, Soyombo A, Bottiglieri T, Trivedi MH. Can targeted metabolomics predict depression recovery? Results from the CO-MED trial. Transl Psychiatry 2019; 9:11. [PMID: 30664617 PMCID: PMC6341111 DOI: 10.1038/s41398-018-0349-6] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Revised: 07/02/2018] [Accepted: 07/14/2018] [Indexed: 12/18/2022] Open
Abstract
Metabolomics is a developing and promising tool for exploring molecular pathways underlying symptoms of depression and predicting depression recovery. The AbsoluteIDQ™ p180 kit was used to investigate whether plasma metabolites (sphingomyelins, lysophosphatidylcholines, phosphatidylcholines, and acylcarnitines) from a subset of participants in the Combining Medications to Enhance Depression Outcomes (CO-MED) trial could act as predictors or biologic correlates of depression recovery. Participants in this trial were assigned to one of three pharmacological treatment arms: escitalopram monotherapy, bupropion-escitalopram combination, or venlafaxine-mirtazapine combination. Plasma was collected at baseline in 159 participants and again 12 weeks later at study exit in 83 of these participants. Metabolite concentrations were measured and combined with clinical and sociodemographic variables using the hierarchical lasso to simultaneously model whether specific metabolites are particularly informative of depressive recovery. Increased baseline concentrations of phosphatidylcholine C38:1 showed poorer outcome based on change in the Quick Inventory of Depressive Symptoms (QIDS). In contrast, an increased ratio of hydroxylated sphingomyelins relative to non-hydroxylated sphingomyelins at baseline and a change from baseline to exit suggested a better reduction of symptoms as measured by QIDS score. All metabolite-based models performed superior to models only using clinical and sociodemographic variables, suggesting that metabolomics may be a valuable tool for predicting antidepressant outcomes.
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Affiliation(s)
- Andrew H. Czysz
- 0000 0000 9482 7121grid.267313.2Department of Psychiatry, University of Texas Southwestern, Dallas, TX 75390 USA
| | - Charles South
- 0000 0000 9482 7121grid.267313.2Department of Psychiatry, University of Texas Southwestern, Dallas, TX 75390 USA
| | - Bharathi S. Gadad
- 0000 0000 9482 7121grid.267313.2Department of Psychiatry, University of Texas Southwestern, Dallas, TX 75390 USA
| | - Erland Arning
- 0000 0004 4685 2620grid.486749.0Center of Metabolomics, Institute of Metabolic Disease, Baylor Scott and White Research Institute, 3812 Elm Street, Dallas, TX 75226 USA
| | - Abigail Soyombo
- 0000 0000 9482 7121grid.267313.2Department of Psychiatry, University of Texas Southwestern, Dallas, TX 75390 USA
| | - Teodoro Bottiglieri
- 0000 0004 4685 2620grid.486749.0Center of Metabolomics, Institute of Metabolic Disease, Baylor Scott and White Research Institute, 3812 Elm Street, Dallas, TX 75226 USA
| | - Madhukar H. Trivedi
- 0000 0000 9482 7121grid.267313.2Department of Psychiatry, University of Texas Southwestern, Dallas, TX 75390 USA
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Everett JR. Pharmacometabonomics: The Prediction of Drug Effects Using Metabolic Profiling. Handb Exp Pharmacol 2019; 260:263-299. [PMID: 31823071 DOI: 10.1007/164_2019_316] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Metabonomics, also known as metabolomics, is concerned with the study of metabolite profiles in humans, animals, plants and other systems in order to assess their health or other status and their responses to experimental interventions. Metabonomics is thus widely used in disease diagnosis and in understanding responses to therapies such as drug administration. Pharmacometabonomics, also known as pharmacometabolomics, is a related methodology but with a prognostic as opposed to diagnostic thrust. Pharmacometabonomics aims to predict drug effects including efficacy, safety, metabolism and pharmacokinetics, prior to drug administration, via an analysis of pre-dose metabolite profiles. This article will review the development of pharmacometabonomics as a new field of science that has much promise in helping to deliver more effective personalised medicine, a major goal of twenty-first century healthcare.
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Affiliation(s)
- Jeremy R Everett
- Medway Metabonomics Research Group, University of Greenwich, Kent, UK.
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Metabolomics Biomarkers for Precision Psychiatry. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1161:101-113. [PMID: 31562625 DOI: 10.1007/978-3-030-21735-8_10] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
The treatment of psychiatric disorders remains a significant challenge in part due to imprecise diagnostic criteria and incomplete understanding of the molecular pathology involved. Current diagnostic and pharmacological treatment guidelines use a uniform approach to address each disorder even though psychiatric clinical presentation and prognosis within a disorder are known to be heterogeneous. Limited therapeutic success highlights the need for a precision medicine approach in psychiatry, termed precision psychiatry. To practice precision psychiatry, it is essential to research and develop multiple omics-based biomarkers that consider environmental factors and careful phenotype determination. Metabolomics, which lies at the endpoint of the "omics cascade," allows for detection of alterations in systems-level metabolites within biological pathways, thereby providing insights into the mechanisms that underlie various physiological conditions and pathologies. The eicosanoids, a family of metabolites derived from oxygenated polyunsaturated fatty acids, play a key role in inflammatory mechanisms and have been implicated in psychiatric disorders such as anorexia nervosa and depression. This review (1) provides background on the current clinical challenges of psychiatric disorders, (2) gives an overview of metabolomics application as a tool to develop improved biomarkers for precision psychiatry, and (3) summarizes current knowledge on metabolomics and lipidomic findings in common psychiatric disorders, with a focus on eicosanoids. Metabolomics is a promising tool for precision psychiatry. This research has great potential for both discovering biomarkers and elucidating molecular mechanisms underlying psychiatric disorders.
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Analytical Methods for Mass Spectrometry-Based Metabolomics Studies. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1140:635-647. [DOI: 10.1007/978-3-030-15950-4_38] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
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Differentially expressed genes related to major depressive disorder and antidepressant response: genome-wide gene expression analysis. Exp Mol Med 2018; 50:1-11. [PMID: 30076325 PMCID: PMC6076250 DOI: 10.1038/s12276-018-0123-0] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2018] [Revised: 03/25/2018] [Accepted: 04/17/2018] [Indexed: 12/15/2022] Open
Abstract
Treatment response to antidepressants is limited and varies among patients with major depressive disorder (MDD). To discover genes and mechanisms related to the pathophysiology of MDD and antidepressant treatment response, we performed gene expression analyses using peripheral blood specimens from 38 MDD patients and 14 healthy individuals at baseline and at 6 weeks after the initiation of either selective serotonin reuptake inhibitor (SSRI) or mirtazapine treatment. The results were compared with results from public microarray data. Seven differentially expressed genes (DEGs) between MDD patients and controls were identified in our study and in the public microarray data: CD58, CXCL8, EGF, TARP, TNFSF4, ZNF583, and ZNF587. CXCL8 was among the top 10 downregulated genes in both studies. Eight genes related to SSRI responsiveness, including BTNL8, showed alterations in gene expression in MDD. The expression of the FCRL6 gene differed between SSRI responders and nonresponders and changed after SSRI treatment compared to baseline. In evaluating the response to mirtazapine, 21 DEGs were identified when comparing MDD patients and controls and responders and nonresponders. These findings suggest that the pathophysiology of MDD and treatment response to antidepressants are associated with a number of processes, including DNA damage and apoptosis, that can be induced by immune activation and inflammation. Differences in the expression of several genes before and after different antidepressant treatments were found in patients with major depressive disorder (MDD), and may help identify patients most likely to benefit from specific drugs. Researchers in South Korea led by Doh Kwan Kim and Soo-Youn Lee at Samsung Medical Center, Seoul, examined gene expression across the 28,869 genes in 38 patients with MDD and 14 healthy individuals. They also validated their findings using existing databases of gene expression in patients with MDD and healthy controls. The research suggests that genes involved in the immune response and inflammation are significantly alternated in MDD and are predictable in which patients respond well to antidepressants. These findings may help develop new approaches to antidepressant therapies, and assist tailoring of treatment to the specific needs of different patients.
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Insights into myalgic encephalomyelitis/chronic fatigue syndrome phenotypes through comprehensive metabolomics. Sci Rep 2018; 8:10056. [PMID: 29968805 PMCID: PMC6030047 DOI: 10.1038/s41598-018-28477-9] [Citation(s) in RCA: 66] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2017] [Accepted: 06/25/2018] [Indexed: 12/12/2022] Open
Abstract
The pathogenesis of ME/CFS, a disease characterized by fatigue, cognitive dysfunction, sleep disturbances, orthostatic intolerance, fever, irritable bowel syndrome (IBS), and lymphadenopathy, is poorly understood. We report biomarker discovery and topological analysis of plasma metabolomic, fecal bacterial metagenomic, and clinical data from 50 ME/CFS patients and 50 healthy controls. We confirm reports of altered plasma levels of choline, carnitine and complex lipid metabolites and demonstrate that patients with ME/CFS and IBS have increased plasma levels of ceramide. Integration of fecal metagenomic and plasma metabolomic data resulted in a stronger predictive model of ME/CFS (cross-validated AUC = 0.836) than either metagenomic (cross-validated AUC = 0.745) or metabolomic (cross-validated AUC = 0.820) analysis alone. Our findings may provide insights into the pathogenesis of ME/CFS and its subtypes and suggest pathways for the development of diagnostic and therapeutic strategies.
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Mora C, Zonca V, Riva MA, Cattaneo A. Blood biomarkers and treatment response in major depression. Expert Rev Mol Diagn 2018; 18:513-529. [DOI: 10.1080/14737159.2018.1470927] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Cristina Mora
- Biological Psychiatry Unit, IRCCS Fatebenefratelli S. Giovanni di Dio, Brescia, Italy
| | - Valentina Zonca
- Biological Psychiatry Unit, IRCCS Fatebenefratelli S. Giovanni di Dio, Brescia, Italy
- Department of Pharmacological and Biomolecular Sciences, University of Milan, Milan, Italy
| | - Marco A. Riva
- Department of Pharmacological and Biomolecular Sciences, University of Milan, Milan, Italy
| | - Annamaria Cattaneo
- Biological Psychiatry Unit, IRCCS Fatebenefratelli S. Giovanni di Dio, Brescia, Italy
- Stress, Psychiatry and Immunology Laboratory, Department of Psychological Medicine, Institute of Psychiatry, King’s College, London, UK
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Peripheral biomarkers of major depression and antidepressant treatment response: Current knowledge and future outlooks. J Affect Disord 2018; 233:3-14. [PMID: 28709695 PMCID: PMC5815949 DOI: 10.1016/j.jad.2017.07.001] [Citation(s) in RCA: 99] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2017] [Revised: 06/19/2017] [Accepted: 07/03/2017] [Indexed: 12/28/2022]
Abstract
BACKGROUND In recent years, we have accomplished a deeper understanding about the pathophysiology of major depressive disorder (MDD). Nevertheless, this improved comprehension has not translated to improved treatment outcome, as identification of specific biologic markers of disease may still be crucial to facilitate a more rapid, successful treatment. Ongoing research explores the importance of screening biomarkers using neuroimaging, neurophysiology, genomics, proteomics, and metabolomics measures. RESULTS In the present review, we highlight the biomarkers that are differentially expressed in MDD and treatment response and place a particular emphasis on the most recent progress in advancing technology which will continue the search for blood-based biomarkers. LIMITATIONS Due to space constraints, we are unable to detail all biomarker platforms, such as neurophysiological and neuroimaging markers, although their contributions are certainly applicable to a biomarker review and valuable to the field. CONCLUSIONS Although the search for reliable biomarkers of depression and/or treatment outcome is ongoing, the rapidly-expanding field of research along with promising new technologies may provide the foundation for identifying key factors which will ultimately help direct patients toward a quicker and more effective treatment for MDD.
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Martínez-Ávila JC, García Bartolomé A, García I, Dapía I, Tong HY, Díaz L, Guerra P, Frías J, Carcás Sansuan AJ, Borobia AM. Pharmacometabolomics applied to zonisamide pharmacokinetic parameter prediction. Metabolomics 2018; 14:70. [PMID: 30830352 DOI: 10.1007/s11306-018-1365-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Accepted: 04/25/2018] [Indexed: 10/16/2022]
Abstract
INTRODUCTION Zonisamide is a new-generation anticonvulsant antiepileptic drug metabolized primarily in the liver, with subsequent elimination via the renal route. OBJECTIVES Our objective was to evaluate the utility of pharmacometabolomics in the detection of zonisamide metabolites that could be related to its disposition and therefore, to its efficacy and toxicity. METHODS This study was nested to a bioequivalence clinical trial with 28 healthy volunteers. Each participant received a single dose of zonisamide on two separate occasions (period 1 and period 2), with a washout period between them. Blood samples of zonisamide were obtained from all patients at baseline for each period, before volunteers were administered any medication, for metabolomics analysis. RESULTS After a Lasso regression was applied, age, height, branched-chain amino acids, steroids, triacylglycerols, diacyl glycerophosphoethanolamine, glycerophospholipids susceptible to methylation, phosphatidylcholines with 20:4 FA (arachidonic acid) and cholesterol ester and lysophosphatidylcholine were obtained in both periods. CONCLUSION To our knowledge, this is the only research study to date that has attempted to link basal metabolomic status with pharmacokinetic parameters of zonisamide.
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Affiliation(s)
- J C Martínez-Ávila
- Clinical Pharmacology Department, La Paz University Hospital, School of Medicine, IdiPAZ, Autonomous University of Madrid, Madrid, Spain.
| | - A García Bartolomé
- Clinical Pharmacology Department, La Paz University Hospital, School of Medicine, IdiPAZ, Autonomous University of Madrid, Madrid, Spain
| | - I García
- Clinical Pharmacology Department, La Paz University Hospital, School of Medicine, IdiPAZ, Autonomous University of Madrid, Madrid, Spain
| | - I Dapía
- Medical and Molecular Genetics Institute (INGEMM), La Paz University Hospital, Rare Diseases Networking Biomedical Research Center (CIBERER), ISCIII, Madrid, Spain
| | - Hoi Y Tong
- Clinical Pharmacology Department, La Paz University Hospital, School of Medicine, IdiPAZ, Autonomous University of Madrid, Madrid, Spain
| | - L Díaz
- Clinical Pharmacology Department, La Paz University Hospital, School of Medicine, IdiPAZ, Autonomous University of Madrid, Madrid, Spain
| | - P Guerra
- Clinical Pharmacology Department, La Paz University Hospital, School of Medicine, IdiPAZ, Autonomous University of Madrid, Madrid, Spain
| | - J Frías
- Clinical Pharmacology Department, La Paz University Hospital, School of Medicine, IdiPAZ, Autonomous University of Madrid, Madrid, Spain
| | - A J Carcás Sansuan
- Clinical Pharmacology Department, La Paz University Hospital, School of Medicine, IdiPAZ, Autonomous University of Madrid, Madrid, Spain.
| | - A M Borobia
- Clinical Pharmacology Department, La Paz University Hospital, School of Medicine, IdiPAZ, Autonomous University of Madrid, Madrid, Spain
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Miolo G, Muraro E, Caruso D, Crivellari D, Ash A, Scalone S, Lombardi D, Rizzolio F, Giordano A, Corona G. Pharmacometabolomics study identifies circulating spermidine and tryptophan as potential biomarkers associated with the complete pathological response to trastuzumab-paclitaxel neoadjuvant therapy in HER-2 positive breast cancer. Oncotarget 2018; 7:39809-39822. [PMID: 27223427 PMCID: PMC5129972 DOI: 10.18632/oncotarget.9489] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2015] [Accepted: 04/28/2016] [Indexed: 01/09/2023] Open
Abstract
Defining biomarkers that predict therapeutic effects and adverse events is a crucial mandate to guide patient selection for personalized cancer treatments. In the present study, we applied a pharmacometabolomics approach to identify biomarkers potentially associated with pathological complete response to trastuzumab-paclitaxel neoadjuvant therapy in HER-2 positive breast cancer patients. Based on histological response the 34 patients enrolled in the study were subdivided into two groups: good responders (n = 15) and poor responders (n = 19). The pre-treatment serum targeted metabolomics profile of all patients were analyzed by liquid chromatography tandem mass spectrometry and the differences in the metabolomics profile between the two groups was investigated by multivariate partial least squares discrimination analysis. The most relevant metabolites that differentiate the two groups of patients were spermidine and tryptophan. The Good responders showed higher levels of spermidine and lower amounts of tryptophan compared with the poor responders (p < 0.001, q < 0.05). The serum level of these two metabolites identified patients who achieved a pathological complete response with a sensitivity of 90% [0.79–1.00] and a specificity of 0.87% [0.67–1.00]. These preliminary results support the role played by the individual patients' metabolism in determining the response to cancer treatments and may be a useful tool to select patients that are more likely to benefit from the trastuzumab-paclitaxel treatment.
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Affiliation(s)
- Gianmaria Miolo
- Department of Medical Oncology, IRCCS-National Cancer Institute, Aviano, Italy
| | - Elena Muraro
- Department of Translational Research, IRCCS-National Cancer Institute, Aviano, Italy
| | - Donatella Caruso
- Department of Pharmacological and Bimolecular Science, University of Milan, Milan, Italy
| | - Diana Crivellari
- Department of Medical Oncology, IRCCS-National Cancer Institute, Aviano, Italy
| | - Anthony Ash
- Department of Biological Chemistry, Norwich Research Park, Norwich, United Kingdom
| | - Simona Scalone
- Department of Medical Oncology, IRCCS-National Cancer Institute, Aviano, Italy
| | - Davide Lombardi
- Department of Medical Oncology, IRCCS-National Cancer Institute, Aviano, Italy
| | - Flavio Rizzolio
- Department of Translational Research, IRCCS-National Cancer Institute, Aviano, Italy
| | - Antonio Giordano
- Sbarro Institute for Cancer Research and Molecular Medicine, Center for Biotechnology, College of Science and Technology, Temple University, Philadelphia, PA, USA
| | - Giuseppe Corona
- Department of Translational Research, IRCCS-National Cancer Institute, Aviano, Italy
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Beta-defensin 1, aryl hydrocarbon receptor and plasma kynurenine in major depressive disorder: metabolomics-informed genomics. Transl Psychiatry 2018; 8:10. [PMID: 29317604 PMCID: PMC5802574 DOI: 10.1038/s41398-017-0056-8] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2017] [Accepted: 10/01/2017] [Indexed: 02/08/2023] Open
Abstract
Major depressive disorder (MDD) is a heterogeneous disease. Efforts to identify biomarkers for sub-classifying MDD and antidepressant therapy by genome-wide association studies (GWAS) alone have generally yielded disappointing results. We applied a metabolomics-informed genomic research strategy to study the contribution of genetic variation to MDD pathophysiology by assaying 31 metabolites, including compounds from the tryptophan, tyrosine, and purine pathways, in plasma samples from 290 MDD patients. Associations of metabolite concentrations with depressive symptoms were determined, followed by GWAS for selected metabolites and functional validation studies of the genes identified. Kynurenine (KYN), the baseline plasma metabolite that was most highly associated with depressive symptoms, was negatively correlated with severity of those symptoms. GWAS for baseline plasma KYN concentrations identified SNPs across the beta-defensin 1 (DEFB1) and aryl hydrocarbon receptor (AHR) genes that were cis-expression quantitative trait loci (eQTLs) for DEFB1 and AHR mRNA expression, respectively. Furthermore, the DEFB1 locus was associated with severity of MDD symptoms in a larger cohort of 803 MDD patients. Functional studies demonstrated that DEFB1 could neutralize lipopolysaccharide-stimulated expression of KYN-biosynthesizing enzymes in monocytic cells, resulting in altered KYN concentrations in the culture media. In addition, we demonstrated that AHR was involved in regulating the expression of enzymes in the KYN pathway and altered KYN biosynthesis in cell lines of hepatocyte and astrocyte origin. In conclusion, these studies identified SNPs that were cis-eQTLs for DEFB1 and AHR and, which were associated with variation in plasma KYN concentrations that were related to severity of MDD symptoms.
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Chaves Filho AJM, Lima CNC, Vasconcelos SMM, de Lucena DF, Maes M, Macedo D. IDO chronic immune activation and tryptophan metabolic pathway: A potential pathophysiological link between depression and obesity. Prog Neuropsychopharmacol Biol Psychiatry 2018; 80:234-249. [PMID: 28595944 DOI: 10.1016/j.pnpbp.2017.04.035] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Revised: 04/03/2017] [Accepted: 04/10/2017] [Indexed: 12/12/2022]
Abstract
Obesity and depression are among the most pressing health problems in the contemporary world. Obesity and depression share a bidirectional relationship, whereby each condition increases the risk of the other. By inference, shared pathways may underpin the comorbidity between obesity and depression. Activation of cell-mediated immunity (CMI) is a key factor in the pathophysiology of depression. CMI cytokines, including IFN-γ, TNFα and IL-1β, induce the catabolism of tryptophan (TRY) by stimulating indoleamine 2,3-dioxygenase (IDO) resulting in the synthesis of kynurenine (KYN) and other tryptophan catabolites (TRYCATs). In the CNS, TRYCATs have been related to oxidative damage, inflammation, mitochondrial dysfunction, cytotoxicity, excitotoxicity, neurotoxicity and lowered neuroplasticity. The pathophysiology of obesity is also associated with a state of aberrant inflammation that activates aryl hydrocarbon receptor (AHR), a pathway involved in the detection of intracellular or environmental changes as well as with increases in the production of TRYCATs, being KYN an agonists of AHR. Both AHR and TRYCATS are involved in obesity and related metabolic disorders. These changes in the TRYCAT pathway may contribute to the onset of neuropsychiatric symptoms in obesity. This paper reviews the role of immune activation, IDO stimulation and increased TRYCAT production in the pathophysiology of depression and obesity. Here we suggest that increased synthesis of detrimental TRYCATs is implicated in comorbid obesity and depression and is a new drug target to treat both diseases.
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Affiliation(s)
- Adriano José Maia Chaves Filho
- Neuropsychopharmacology Laboratory, Drug Research and Development Center, Faculty of Medicine, Universidade Federal do Ceará, Fortaleza, CE, Brazil; Department of Physiology and Pharmacology, Faculty of Medicine, Universidade Federal do Ceará, Fortaleza, CE, Brazil
| | - Camila Nayane Carvalho Lima
- Neuropsychopharmacology Laboratory, Drug Research and Development Center, Faculty of Medicine, Universidade Federal do Ceará, Fortaleza, CE, Brazil; Department of Physiology and Pharmacology, Faculty of Medicine, Universidade Federal do Ceará, Fortaleza, CE, Brazil
| | - Silvânia Maria Mendes Vasconcelos
- Neuropsychopharmacology Laboratory, Drug Research and Development Center, Faculty of Medicine, Universidade Federal do Ceará, Fortaleza, CE, Brazil; Department of Physiology and Pharmacology, Faculty of Medicine, Universidade Federal do Ceará, Fortaleza, CE, Brazil
| | - David Freitas de Lucena
- Neuropsychopharmacology Laboratory, Drug Research and Development Center, Faculty of Medicine, Universidade Federal do Ceará, Fortaleza, CE, Brazil; Department of Physiology and Pharmacology, Faculty of Medicine, Universidade Federal do Ceará, Fortaleza, CE, Brazil
| | - Michael Maes
- Impact Strategic Research Center, Deakin University, Geelong, Australia; Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; Health Sciences Graduate Program, Health Sciences Center, State University of Londrina, Londrina, Brazil
| | - Danielle Macedo
- Neuropsychopharmacology Laboratory, Drug Research and Development Center, Faculty of Medicine, Universidade Federal do Ceará, Fortaleza, CE, Brazil; Department of Physiology and Pharmacology, Faculty of Medicine, Universidade Federal do Ceará, Fortaleza, CE, Brazil.
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Everett JR. NMR-based pharmacometabonomics: A new paradigm for personalised or precision medicine. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2017; 102-103:1-14. [PMID: 29157489 DOI: 10.1016/j.pnmrs.2017.04.003] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2017] [Revised: 04/23/2017] [Accepted: 04/24/2017] [Indexed: 06/07/2023]
Abstract
Metabolic profiling by NMR spectroscopy or hyphenated mass spectrometry, known as metabonomics or metabolomics, is an important tool for systems-based approaches in biology and medicine. The experiments are typically done in a diagnostic fashion where changes in metabolite profiles are interpreted as a consequence of an intervention or event; be that a change in diet, the administration of a drug, physical exertion or the onset of a disease. By contrast, pharmacometabonomics takes a prognostic approach to metabolic profiling, in order to predict the effects of drug dosing before it occurs. Differences in pre-dose metabolite profiles between groups of subjects are used to predict post-dose differences in response to drug administration. Thus the paradigm is inverted and pharmacometabonomics is the metabolic equivalent of pharmacogenomics. Although the field is still in its infancy, it is expected that pharmacometabonomics, alongside pharmacogenomics, will assist with the delivery of personalised or precision medicine to patients, which is a critical goal of 21st century healthcare.
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Affiliation(s)
- Jeremy R Everett
- Medway Metabonomics Group, University of Greenwich, Chatham Maritime, Kent ME4 4TB, UK.
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Novel Applications of Metabolomics in Personalized Medicine: A Mini-Review. Molecules 2017; 22:molecules22071173. [PMID: 28703775 PMCID: PMC6152045 DOI: 10.3390/molecules22071173] [Citation(s) in RCA: 62] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2017] [Revised: 07/10/2017] [Accepted: 07/11/2017] [Indexed: 12/20/2022] Open
Abstract
Interindividual variability in drug responses and disease susceptibility is common in the clinic. Currently, personalized medicine is highly valued, the idea being to prescribe the right medicine to the right patient. Metabolomics has been increasingly applied in evaluating the therapeutic outcomes of clinical drugs by correlating the baseline metabolic profiles of patients with their responses, i.e., pharmacometabonomics, as well as prediction of disease susceptibility among population in advance, i.e., patient stratification. The accelerated advance in metabolomics technology pinpoints the huge potential of its application in personalized medicine. In current review, we discussed the novel applications of metabolomics with typical examples in evaluating drug therapy and patient stratification, and underlined the potential of metabolomics in personalized medicine in the future.
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Umehara H, Numata S, Watanabe SY, Hatakeyama Y, Kinoshita M, Tomioka Y, Nakahara K, Nikawa T, Ohmori T. Altered KYN/TRP, Gln/Glu, and Met/methionine sulfoxide ratios in the blood plasma of medication-free patients with major depressive disorder. Sci Rep 2017; 7:4855. [PMID: 28687801 PMCID: PMC5501805 DOI: 10.1038/s41598-017-05121-6] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2016] [Accepted: 05/24/2017] [Indexed: 12/19/2022] Open
Abstract
Capillary electrophoresis-time-of-flight mass spectrometry (CE-TOFMS) is a comprehensive, quantitative, and high throughput tool used to analyze metabolite profiles. In the present study, we used CE-TOFMS to profile metabolites found in the blood plasma of 33 medication-free patients with major depressive disorder (MDD) and 33 non-psychiatric control subjects. We then investigated changes which occurred in the metabolite levels during an 8-week treatment period. The medication-free MDD patients and control subjects showed significant differences in their mean levels of 33 metabolites, including kynurenine (KYN), glutamate (Glu), glutamine (Gln), methionine sulfoxide, and methionine (Met). In particular, the ratios of KYN to tryptophan (TRP), Gln to Glu, and Met to methionine sulfoxide were all significantly different between the two groups. Among the 33 metabolites with altered levels in MDD patients, the levels of KYN and Gln, as well as the ratio of Gln to Glu, were significantly normalized after treatment. Our findings suggest that imbalances in specific metabolite levels may be involved in the pathogenesis of MDD, and provide insight into the mechanisms by which antidepressant agents work in MDD patients.
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Affiliation(s)
- Hidehiro Umehara
- Department of Psychiatry, Graduate School of Biomedical Sciences, Tokushima University, Tokushima, Japan
| | - Shusuke Numata
- Department of Psychiatry, Graduate School of Biomedical Sciences, Tokushima University, Tokushima, Japan.
| | - Shin-Ya Watanabe
- Department of Psychiatry, Graduate School of Biomedical Sciences, Tokushima University, Tokushima, Japan
| | - Yutaka Hatakeyama
- Center of Medical Information Science, Kochi Medical School, Kochi University, Kohasu, Oko-cho, Nankoku, Japan
| | - Makoto Kinoshita
- Department of Psychiatry, Graduate School of Biomedical Sciences, Tokushima University, Tokushima, Japan
| | - Yukiko Tomioka
- Department of Psychiatry, Graduate School of Biomedical Sciences, Tokushima University, Tokushima, Japan
| | - Kiyoshi Nakahara
- Research Institute, Kochi University of Technology, 185 Miyanokuchi, Tosayamada-cho, Kami-shi, Kochi, Japan
| | - Takeshi Nikawa
- Department of Nutritional Physiology, Institute of Medical Nutrition, Tokushima University Graduate School, Tokushima, Japan
| | - Tetsuro Ohmori
- Department of Psychiatry, Graduate School of Biomedical Sciences, Tokushima University, Tokushima, Japan
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Metabolomics biomarkers to predict acamprosate treatment response in alcohol-dependent subjects. Sci Rep 2017; 7:2496. [PMID: 28566752 PMCID: PMC5451388 DOI: 10.1038/s41598-017-02442-4] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2016] [Accepted: 04/12/2017] [Indexed: 01/25/2023] Open
Abstract
Precision medicine for alcohol use disorder (AUD) allows optimal treatment of the right patient with the right drug at the right time. Here, we generated multivariable models incorporating clinical information and serum metabolite levels to predict acamprosate treatment response. The sample of 120 patients was randomly split into a training set (n = 80) and test set (n = 40) five independent times. Treatment response was defined as complete abstinence (no alcohol consumption during 3 months of acamprosate treatment) while nonresponse was defined as any alcohol consumption during this period. In each of the five training sets, we built a predictive model using a least absolute shrinkage and section operator (LASSO) penalized selection method and then evaluated the predictive performance of each model in the corresponding test set. The models predicted acamprosate treatment response with a mean sensitivity and specificity in the test sets of 0.83 and 0.31, respectively, suggesting our model performed well at predicting responders, but not non-responders (i.e. many non-responders were predicted to respond). Studies with larger sample sizes and additional biomarkers will expand the clinical utility of predictive algorithms for pharmaceutical response in AUD.
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Eskelund A, Li Y, Budac DP, Müller HK, Gulinello M, Sanchez C, Wegener G. Drugs with antidepressant properties affect tryptophan metabolites differently in rodent models with depression-like behavior. J Neurochem 2017; 142:118-131. [DOI: 10.1111/jnc.14043] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2016] [Revised: 03/28/2017] [Accepted: 04/04/2017] [Indexed: 12/17/2022]
Affiliation(s)
| | - Yan Li
- Lundbeck Research US; Paramus New Jersey USA
| | | | | | - Maria Gulinello
- Behavioral Core Facility; Department of Neuroscience; Albert Einstein College of Medicine; Bronx New York USA
| | - Connie Sanchez
- Translational Neuropsychiatry Unit; Risskov Denmark
- Lundbeck Research US; Paramus New Jersey USA
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Kantae V, Krekels EHJ, Esdonk MJV, Lindenburg P, Harms AC, Knibbe CAJ, Van der Graaf PH, Hankemeier T. Integration of pharmacometabolomics with pharmacokinetics and pharmacodynamics: towards personalized drug therapy. Metabolomics 2016; 13:9. [PMID: 28058041 PMCID: PMC5165030 DOI: 10.1007/s11306-016-1143-1] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2016] [Accepted: 11/26/2016] [Indexed: 02/05/2023]
Abstract
Personalized medicine, in modern drug therapy, aims at a tailored drug treatment accounting for inter-individual variations in drug pharmacology to treat individuals effectively and safely. The inter-individual variability in drug response upon drug administration is caused by the interplay between drug pharmacology and the patients' (patho)physiological status. Individual variations in (patho)physiological status may result from genetic polymorphisms, environmental factors (including current/past treatments), demographic characteristics, and disease related factors. Identification and quantification of predictors of inter-individual variability in drug pharmacology is necessary to achieve personalized medicine. Here, we highlight the potential of pharmacometabolomics in prospectively informing on the inter-individual differences in drug pharmacology, including both pharmacokinetic (PK) and pharmacodynamic (PD) processes, and thereby guiding drug selection and drug dosing. This review focusses on the pharmacometabolomics studies that have additional value on top of the conventional covariates in predicting drug PK. Additionally, employing pharmacometabolomics to predict drug PD is highlighted, and we suggest not only considering the endogenous metabolites as static variables but to include also drug dose and temporal changes in drug concentration in these studies. Although there are many endogenous metabolite biomarkers identified to predict PK and more often to predict PD, validation of these biomarkers in terms of specificity, sensitivity, reproducibility and clinical relevance is highly important. Furthermore, the application of these identified biomarkers in routine clinical practice deserves notable attention to truly personalize drug treatment in the near future.
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Affiliation(s)
- Vasudev Kantae
- Division of Analytical Biosciences, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands
| | - Elke H. J. Krekels
- Division of Pharmacology, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Michiel J. Van Esdonk
- Division of Pharmacology, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Peter Lindenburg
- Division of Analytical Biosciences, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands
| | - Amy C. Harms
- Division of Analytical Biosciences, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands
| | - Catherijne A. J. Knibbe
- Division of Pharmacology, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Piet H. Van der Graaf
- Division of Pharmacology, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
- Certara QSP, Canterbury Innovation Centre, Canterbury, UK
| | - Thomas Hankemeier
- Division of Analytical Biosciences, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands
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46
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Gupta M, Neavin D, Liu D, Biernacka J, Hall-Flavin D, Bobo WV, Frye MA, Skime M, Jenkins GD, Batzler A, Kalari K, Matson W, Bhasin SS, Zhu H, Mushiroda T, Nakamura Y, Kubo M, Wang L, Kaddurah-Daouk R, Weinshilboum RM. TSPAN5, ERICH3 and selective serotonin reuptake inhibitors in major depressive disorder: pharmacometabolomics-informed pharmacogenomics. Mol Psychiatry 2016; 21:1717-1725. [PMID: 26903268 PMCID: PMC5003027 DOI: 10.1038/mp.2016.6] [Citation(s) in RCA: 89] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2015] [Revised: 12/07/2015] [Accepted: 01/07/2016] [Indexed: 01/01/2023]
Abstract
Millions of patients suffer from major depressive disorder (MDD), but many do not respond to selective serotonin reuptake inhibitor (SSRI) therapy. We used a pharmacometabolomics-informed pharmacogenomics research strategy to identify genes associated with metabolites that were related to SSRI response. Specifically, 306 MDD patients were treated with citalopram or escitalopram and blood was drawn at baseline, 4 and 8 weeks for blood drug levels, genome-wide single nucleotide polymorphism (SNP) genotyping and metabolomic analyses. SSRI treatment decreased plasma serotonin concentrations (P<0.0001). Baseline and plasma serotonin concentration changes were associated with clinical outcomes (P<0.05). Therefore, baseline and serotonin concentration changes were used as phenotypes for genome-wide association studies (GWAS). GWAS for baseline plasma serotonin concentrations revealed a genome-wide significant (P=7.84E-09) SNP cluster on chromosome four 5' of TSPAN5 and a cluster across ERICH3 on chromosome one (P=9.28E-08) that were also observed during GWAS for change in serotonin at 4 (P=5.6E-08 and P=7.54E-07, respectively) and 8 weeks (P=1.25E-06 and P=3.99E-07, respectively). The SNPs on chromosome four were expression quantitative trait loci for TSPAN5. Knockdown (KD) and overexpression (OE) of TSPAN5 in a neuroblastoma cell line significantly altered the expression of serotonin pathway genes (TPH1, TPH2, DDC and MAOA). Chromosome one SNPs included two ERICH3 nonsynonymous SNPs that resulted in accelerated proteasome-mediated degradation. In addition, ERICH3 and TSPAN5 KD and OE altered media serotonin concentrations. Application of a pharmacometabolomics-informed pharmacogenomic research strategy, followed by functional validation, indicated that TSPAN5 and ERICH3 are associated with plasma serotonin concentrations and may have a role in SSRI treatment outcomes.
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Affiliation(s)
- M Gupta
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
| | - D Neavin
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
| | - D Liu
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
| | - J Biernacka
- Department of Biomedical Statistics and Bioinformatics – Genetics and Bioinformatics, Mayo Clinic, Rochester, MN, USA
| | - D Hall-Flavin
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - W V Bobo
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - M A Frye
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - M Skime
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - G D Jenkins
- Department of Biomedical Statistics and Bioinformatics – Genetics and Bioinformatics, Mayo Clinic, Rochester, MN, USA
| | - A Batzler
- Department of Biomedical Statistics and Bioinformatics – Genetics and Bioinformatics, Mayo Clinic, Rochester, MN, USA
| | - K Kalari
- Department of Biomedical Statistics and Bioinformatics – Genetics and Bioinformatics, Mayo Clinic, Rochester, MN, USA
| | - W Matson
- Bedford VA Medical Center, Bedford, MA, USA
| | - S S Bhasin
- Bedford VA Medical Center, Bedford, MA, USA
| | - H Zhu
- Department of Psychiatry and Behavioral Medicine, Duke Institute for Brain Sciences, Duke University, Durham, NC, USA
| | - T Mushiroda
- RIKEN Center for Genomic Medicine, Yokohama, Japan
| | - Y Nakamura
- Department of Medicine, University of Chicago, Chicago, IL, USA
| | - M Kubo
- RIKEN Center for Genomic Medicine, Yokohama, Japan
| | - L Wang
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
| | - R Kaddurah-Daouk
- Department of Psychiatry and Behavioral Medicine, Duke Institute for Brain Sciences, Duke University, Durham, NC, USA
| | - R M Weinshilboum
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA,Division of Clinical Pharmacology, Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA. E-mail:
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47
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Rotroff DM, Corum DG, Motsinger-Reif A, Fiehn O, Bottrel N, Drevets WC, Singh J, Salvadore G, Kaddurah-Daouk R. Metabolomic signatures of drug response phenotypes for ketamine and esketamine in subjects with refractory major depressive disorder: new mechanistic insights for rapid acting antidepressants. Transl Psychiatry 2016; 6:e894. [PMID: 27648916 PMCID: PMC5048196 DOI: 10.1038/tp.2016.145] [Citation(s) in RCA: 62] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2016] [Accepted: 06/01/2016] [Indexed: 12/22/2022] Open
Abstract
Ketamine, at sub-anesthetic doses, is reported to rapidly decrease depression symptoms in patients with treatment-resistant major depressive disorder (MDD). Many patients do not respond to currently available antidepressants, (for example, serotonin reuptake inhibitors), making ketamine and its enantiomer, esketamine, potentially attractive options for treatment-resistant MDD. Although mechanisms by which ketamine/esketamine may produce antidepressant effects have been hypothesized on the basis of preclinical data, the neurobiological correlates of the rapid therapeutic response observed in patients receiving treatment have not been established. Here we use a pharmacometabolomics approach to map global metabolic effects of these compounds in treatment-refractory MDD patients upon 2 h from infusion with ketamine (n=33) or its S-enantiomer, esketamine (n=20). The effects of esketamine on metabolism were retested in the same subjects following a second exposure administered 4 days later. Two complementary metabolomics platforms were used to provide broad biochemical coverage. In addition, we investigated whether changes in particular metabolites correlated with treatment outcome. Both drugs altered metabolites related to tryptophan metabolism (for example, indole-3-acetate and methionine) and/or the urea cycle (for example, citrulline, arginine and ornithine) at 2 h post infusion (q<0.25). In addition, we observed changes in glutamate and circulating phospholipids that were significantly associated with decreases in depression severity. These data provide new insights into the mechanism underlying the rapid antidepressant effects of ketamine and esketamine, and constitute some of the first detailed metabolomics mapping for these promising therapies.
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Affiliation(s)
- D M Rotroff
- Department of Statistics, North Carolina State University, Raleigh, NC, USA
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA
| | - D G Corum
- Department of Drug Discovery and Biomedical Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - A Motsinger-Reif
- Department of Statistics, North Carolina State University, Raleigh, NC, USA
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA
| | - O Fiehn
- UC Davis Genome Center, University of California Davis, Davis, CA, USA
- Department of Biochemistry, King Abdulaziz University, Jeddah, Saudi Arabia
| | - N Bottrel
- Department of Neuroscience, Janssen Research and Development, Titusville, NJ, USA
| | - W C Drevets
- Department of Neuroscience, Janssen Research and Development, Titusville, NJ, USA
| | - J Singh
- Department of Neuroscience, Janssen Research and Development, San Diego CA, USA
| | - G Salvadore
- Department of Neuroscience, Janssen Research and Development, Titusville, NJ, USA
| | - R Kaddurah-Daouk
- Department of Psychiatry, Duke University Medical Center, Durham NC, USA
- Duke Institute for Brain Sciences, Duke University, Durham, NC, USA
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48
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Everett JR. From Metabonomics to Pharmacometabonomics: The Role of Metabolic Profiling in Personalized Medicine. Front Pharmacol 2016; 7:297. [PMID: 27660611 PMCID: PMC5014868 DOI: 10.3389/fphar.2016.00297] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2016] [Accepted: 08/23/2016] [Indexed: 01/08/2023] Open
Abstract
Variable patient responses to drugs are a key issue for medicine and for drug discovery and development. Personalized medicine, that is the selection of medicines for subgroups of patients so as to maximize drug efficacy and minimize toxicity, is a key goal of twenty-first century healthcare. Currently, most personalized medicine paradigms rely on clinical judgment based on the patient's history, and on the analysis of the patients' genome to predict drug effects i.e., pharmacogenomics. However, variability in patient responses to drugs is dependent upon many environmental factors to which human genomics is essentially blind. A new paradigm for predicting drug responses based on individual pre-dose metabolite profiles has emerged in the past decade: pharmacometabonomics, which is defined as “the prediction of the outcome (for example, efficacy or toxicity) of a drug or xenobiotic intervention in an individual based on a mathematical model of pre-intervention metabolite signatures.” The new pharmacometabonomics paradigm is complementary to pharmacogenomics but has the advantage of being sensitive to environmental as well as genomic factors. This review will chart the discovery and development of pharmacometabonomics, and provide examples of its current utility and possible future developments.
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Affiliation(s)
- Jeremy R Everett
- Medway Metabonomics Research Group, University of Greenwich Kent, UK
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49
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Rotroff DM, Oki NO, Liang X, Yee SW, Stocker SL, Corum DG, Meisner M, Fiehn O, Motsinger-Reif AA, Giacomini KM, Kaddurah-Daouk R. Pharmacometabolomic Assessment of Metformin in Non-diabetic, African Americans. Front Pharmacol 2016; 7:135. [PMID: 27378919 PMCID: PMC4906013 DOI: 10.3389/fphar.2016.00135] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2016] [Accepted: 05/09/2016] [Indexed: 12/20/2022] Open
Abstract
Millions of individuals are diagnosed with type 2 diabetes mellitus (T2D), which increases the risk for a plethora of adverse outcomes including cardiovascular events and kidney disease. Metformin is the most widely prescribed medication for the treatment of T2D; however, its mechanism is not fully understood and individuals vary in their response to this therapy. Here, we use a non-targeted, pharmacometabolomics approach to measure 384 metabolites in 33 non-diabetic, African American subjects dosed with metformin. Three plasma samples were obtained from each subject, one before and two after metformin administration. Validation studies were performed in wildtype mice given metformin. Fifty-four metabolites (including 21 unknowns) were significantly altered upon metformin administration, and 12 metabolites (including six unknowns) were significantly associated with metformin-induced change in glucose (q < 0.2). Of note, indole-3-acetate, a metabolite produced by gut microbes, and 4-hydroxyproline were modulated following metformin exposure in both humans and mice. 2-Hydroxybutanoic acid, a metabolite previously associated with insulin resistance and an early biomarker of T2D, was positively correlated with fasting glucose levels as well as glucose levels following oral glucose tolerance tests after metformin administration. Pathway analysis revealed that metformin administration was associated with changes in a number of metabolites in the urea cycle and in purine metabolic pathways (q < 0.01). Further research is needed to validate the biomarkers of metformin exposure and response identified in this study, and to understand the role of metformin in ammonia detoxification, protein degradation and purine metabolic pathways.
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Affiliation(s)
- Daniel M Rotroff
- Bioinformatics Research Center, North Carolina State UniversityRaleigh, NC, USA; Department of Statistics, North Carolina State UniversityRaleigh, NC, USA
| | - Noffisat O Oki
- Bioinformatics Research Center, North Carolina State University Raleigh, NC, USA
| | - Xiaomin Liang
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco San Francisco, CA, USA
| | - Sook Wah Yee
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco San Francisco, CA, USA
| | - Sophie L Stocker
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco San Francisco, CA, USA
| | - Daniel G Corum
- Department of Regenerative Medicine and Cell Biology, Medical University of South Carolina Charleston, SC, USA
| | - Michele Meisner
- Department of Statistics, North Carolina State University Raleigh, NC, USA
| | - Oliver Fiehn
- UC Davis Genome Center, University of California DavisDavis, CA, USA; Department of Biochemistry, King Abdulaziz UniversityJeddah, Saudi-Arabia
| | - Alison A Motsinger-Reif
- Department of Statistics, North Carolina State UniversityRaleigh, NC, USA; Department of Psychiatry and Behavioral Sciences, Duke UniversityDurham, NC, USA
| | - Kathleen M Giacomini
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco San Francisco, CA, USA
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke UniversityDurham, NC, USA; Duke Institute for Brain Sciences, Duke UniversityDurham, NC, USA
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50
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Shin C, Han C, Pae CU, Patkar AA. Precision medicine for psychopharmacology: a general introduction. Expert Rev Neurother 2016; 16:831-9. [PMID: 27104961 DOI: 10.1080/14737175.2016.1182022] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
INTRODUCTION Precision medicine is an emerging medical model that can provide accurate diagnoses and tailored therapeutic strategies for patients based on data pertaining to genes, microbiomes, environment, family history and lifestyle. AREAS COVERED Here, we provide basic information about precision medicine and newly introduced concepts, such as the precision medicine ecosystem and big data processing, and omics technologies including pharmacogenomics, pharamacometabolomics, pharmacoproteomics, pharmacoepigenomics, connectomics and exposomics. The authors review the current state of omics in psychiatry and the future direction of psychopharmacology as it moves towards precision medicine. Expert commentary: Advances in precision medicine have been facilitated by achievements in multiple fields, including large-scale biological databases, powerful methods for characterizing patients (such as genomics, proteomics, metabolomics, diverse cellular assays, and even social networks and mobile health technologies), and computer-based tools for analyzing large amounts of data.
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Affiliation(s)
- Cheolmin Shin
- a Department of Psychiatry, College of Medicine , Korea University , Seoul , South Korea
| | - Changsu Han
- a Department of Psychiatry, College of Medicine , Korea University , Seoul , South Korea
| | - Chi-Un Pae
- b Department of Psychiatry , Catholic University College of Medicine , Seoul , South Korea
| | - Ashwin A Patkar
- c Department of Psychiatry and Behavioural Sciences , Duke University Medical Center , Durham , NC , USA
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