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Wood AJ, Carroll AR, Shinn AK, Ongur D, Lewandowski KE. Diagnostic Stability of Primary Psychotic Disorders in a Research Sample. Front Psychiatry 2021; 12:734272. [PMID: 34777044 PMCID: PMC8580873 DOI: 10.3389/fpsyt.2021.734272] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 10/01/2021] [Indexed: 12/03/2022] Open
Abstract
Psychiatric diagnosis is often treated as a stable construct both clinically and in research; however, some evidence suggests that diagnostic change may be common, which may impact research validity and clinical care. In the present study we examined diagnostic stability in individuals with psychosis over time. Participants with a diagnosis of any psychotic disorder (n = 142) were assessed at two timepoints using the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders. We found a 25.4% diagnostic change rate across the total sample. People with an initial diagnosis of psychosis not otherwise specified and schizophreniform disorder had the highest rates of change, followed by those with schizophrenia and schizoaffective disorder; people with bipolar disorder had the lowest change rate. Most participants with an unstable initial diagnosis of schizophrenia, schizophreniform disorder, bipolar disorder, or psychosis not otherwise specified converted to a final diagnosis of schizoaffective disorder. Participants with an unstable initial diagnosis of schizoaffective disorder most frequently converted to a diagnosis of schizophrenia. Our findings suggest that diagnostic change is relatively common, occurring in approximately a quarter of patients. People with an initial diagnosis of schizophrenia-spectrum disorder were more likely to have a diagnostic change, suggesting a natural stability of some diagnoses more so than others.
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Affiliation(s)
- Andrea J Wood
- Schizophrenia and Bipolar Disorder Research Program, McLean Hospital, Belmont, MA, United States
| | - Amber R Carroll
- Schizophrenia and Bipolar Disorder Research Program, McLean Hospital, Belmont, MA, United States
| | - Ann K Shinn
- Schizophrenia and Bipolar Disorder Research Program, McLean Hospital, Belmont, MA, United States.,Department of Psychiatry, Harvard Medical School, Boston, MA, United States
| | - Dost Ongur
- Schizophrenia and Bipolar Disorder Research Program, McLean Hospital, Belmont, MA, United States.,Department of Psychiatry, Harvard Medical School, Boston, MA, United States
| | - Kathryn E Lewandowski
- Schizophrenia and Bipolar Disorder Research Program, McLean Hospital, Belmont, MA, United States.,Department of Psychiatry, Harvard Medical School, Boston, MA, United States
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Ahmed AT, MahmoudianDehkordi S, Bhattacharyya S, Arnold M, Liu D, Neavin D, Moseley MA, Thompson JW, Williams LSJ, Louie G, Skime MK, Wang L, Riva-Posse P, McDonald WM, Bobo WV, Craighead WE, Krishnan R, Weinshilboum RM, Dunlop BW, Millington DS, Rush AJ, Frye MA, Kaddurah-Daouk R. Acylcarnitine metabolomic profiles inform clinically-defined major depressive phenotypes. J Affect Disord 2020; 264:90-97. [PMID: 32056779 PMCID: PMC7024064 DOI: 10.1016/j.jad.2019.11.122] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Revised: 10/17/2019] [Accepted: 11/29/2019] [Indexed: 01/24/2023]
Abstract
BACKGROUND Acylcarnitines have important functions in mitochondrial energetics and β-oxidation, and have been implicated to play a significant role in metabolic functions of the brain. This retrospective study examined whether plasma acylcarnitine profiles can help biochemically distinguish the three phenotypic subtypes of major depressive disorder (MDD): core depression (CD+), anxious depression (ANX+), and neurovegetative symptoms of melancholia (NVSM+). METHODS Depressed outpatients (n = 240) from the Mayo Clinic Pharmacogenomics Research Network were treated with citalopram or escitalopram for eight weeks. Plasma samples collected at baseline and after eight weeks of treatment with citalopram or escitalopram were profiled for short-, medium- and long-chain acylcarnitine levels using AbsoluteIDQ®p180-Kit and LC-MS. Linear mixed effects models were used to examine whether acylcarnitine levels discriminated the clinical phenotypes at baseline or eight weeks post-treatment, and whether temporal changes in acylcarnitine profiles differed between groups. RESULTS Compared to ANX+, CD+ and NVSM+ had significantly lower concentrations of short- and long-chain acylcarnitines at both baseline and week 8. In NVSM+, the medium- and long-chain acylcarnitines were also significantly lower in NVSM+ compared to ANX+. Short-chain acylcarnitine levels increased significantly from baseline to week 8 in CD+ and ANX+, whereas medium- and long-chain acylcarnitines significantly decreased in CD+ and NVSM+. CONCLUSIONS In depressed patients treated with SSRIs, β-oxidation and mitochondrial energetics as evaluated by levels and changes in acylcarnitines may provide the biochemical basis of the clinical heterogeneity of MDD, especially when combined with clinical characteristics.
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Affiliation(s)
- Ahmed T Ahmed
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States.
| | - Siamak MahmoudianDehkordi
- 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 of Brain Sciences, Duke University, Durham, NC, United States.
| | - Sudeepa Bhattacharyya
- Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, United States.
| | - Matthias Arnold
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States; 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, United States.
| | - Drew Neavin
- Department of Molecular Pharmacology & Experimental Therapeutics, Mayo Clinic, Rochester, MN, United States.
| | - M Arthur Moseley
- Duke Proteomics and Metabolomics Shared Resource, Center for Genomic and Computational Biology, Durham, NC, United States.
| | - J Will Thompson
- Duke Proteomics and Metabolomics Shared Resource, Center for Genomic and Computational Biology, Durham, NC, United States.
| | - Lisa St John Williams
- Duke Proteomics and Metabolomics Shared Resource, Center for Genomic and Computational Biology, Durham, NC, United States.
| | - Gregory Louie
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States.
| | - Michelle K Skime
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States.
| | - Liewei Wang
- Department of Molecular Pharmacology & Experimental Therapeutics, Mayo Clinic, Rochester, MN, United States.
| | - Patricio Riva-Posse
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States.
| | - William M McDonald
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States.
| | - William V Bobo
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States.
| | - W Edward Craighead
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States.
| | - Ranga Krishnan
- Department of Psychiatry, Rush Medical College, Chicago, IL, United States.
| | - Richard M Weinshilboum
- Department of Molecular Pharmacology & Experimental Therapeutics, Mayo Clinic, Rochester, MN, United States.
| | - Boadie W Dunlop
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States.
| | - David S Millington
- Professor Emeritus, Department of Pediatrics, Duke University School of Medicine, Durham, NC, United States.
| | - A John Rush
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States; Department of Psychiatry, Health Sciences Center, Texas Tech University, Permian Basin, TX, United States; Duke-National University of Singapore, Singapore
| | - Mark A Frye
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, 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 of Brain Sciences, Duke University, Durham, NC, United States.
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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: 60] [Impact Index Per Article: 10.0] [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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Abstract
This chapter provides a synopsis of the clinically relevant findings derived from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study and selected ancillary studies appended to the primary trial. The chapter describes the participants, their recruitment and treatment, and the study design, primary outcomes, and clinically informative results. In particular, the chapter describes acute phase response and remission rates from each of the five treatment steps which entail antidepressant monotherapies and combinations, and psychotherapy alone or in combination with an antidepressant. In addition, longer-term outcomes beyond the 12 week acute trial are described for each treatment step. The treatment challenges described include patient retention and relapse, and longer-term follow-up. The chapter discusses the use of measurement-based care for delivering high-quality care, describes "treatment-resistant" depression and discusses its implications for clinical practice, and discusses the contributions of STAR*D to patient-oriented research and patient care.
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