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Zhang Q, Du Y, Bao C, Hua L, Yan R, Dai Z, Xia Y, Zou H, He C, Sun H, Lu Q, Yao Z. Aberrant high-beta band functional connectivity during reward processing in melancholic major depressive disorder: An MEG study. Neuroimage Clin 2024; 43:103666. [PMID: 39232415 PMCID: PMC11404173 DOI: 10.1016/j.nicl.2024.103666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2024] [Revised: 08/18/2024] [Accepted: 08/30/2024] [Indexed: 09/06/2024]
Abstract
OBJECTIVE To identify the spatial-temporal pattern variation of whole-brain functional connectivity (FC) during reward processing in melancholic major depressive disorder (MDD) patients, and to determine the clinical correlates of connectomic differences. METHODS 61 MDD patients and 32 healthy controls were enrolled into the study. During magnetoencephalography (MEG) scanning, all participants completed the facial emotion recognition task. The MDD patients were further divided into two groups: melancholic (n = 31) and non-melancholic (n = 30), based on the Mini International Neuropsychiatric Interview (M.I.N.I.) assessment. Melancholic symptoms were examined by using the 6-item melancholia subscale from the Hamilton Depression Rating Scale (HAM-D6). The whole-brain orthogonalized power envelope connections in the high-beta band (20-35 Hz) were constructed in each period after the happy emotional stimuli (0-200 ms, 100-300 ms, 200-400 ms, 300-500 ms, and 400-600 ms). Then, the network-based statistic (NBS) was used to determine the specific abnormal connection patterns in melancholic MDD patients. RESULTS The NBS identified a sub-network difference at the mid-late period (300-500 ms) in response to happy faces among the three groups (corrected P = 0.035). Then, the post hoc and correlation analyses found five FCs were decreased in melancholic MDD patients and were related to HAM-D6 score, including FCs of left fusiform gyrus-right orbital inferior frontal gyrus (r = -0.52, P < 0.001), left fusiform gyrus-left amygdala (r = -0.26, P = 0.049), left posterior cingulate gyrus-right precuneus (r = -0.32, P = 0.025), left precuneus-right precuneus (r = -0.27, P = 0.049), and left precuneus-left inferior occipital gyrus (r = -0.32, P = 0.025). CONCLUSION In response to happy faces, melancholic MDD patients demonstrated a disrupted functional connective pattern (20-35 Hz, 300-500 ms), which involved brain regions in visual information processing and the limbic system. The aberrant functional connective pattern in reward processing might be a biomarker of melancholic MDD.
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Affiliation(s)
- Qiaoyang Zhang
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China; Department of Psychology, the Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou 213000, China
| | - Yishan Du
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Ciqing Bao
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Lingling Hua
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Rui Yan
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Zhongpeng Dai
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Yi Xia
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Haowen Zou
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Chen He
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Hao Sun
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Qing Lu
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Southeast University, Nanjing 210096, China.
| | - Zhijian Yao
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China; Nanjing Brain Hospital, Clinical Teaching Hospital of Medical School, Nanjing University, Nanjing, 210093, China..
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2
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Yang T, Ou Y, Li H, Liu F, Li P, Xie G, Zhao J, Cui X, Guo W. Neural substrates of predicting anhedonia symptoms in major depressive disorder via connectome-based modeling. CNS Neurosci Ther 2024; 30:e14871. [PMID: 39037006 PMCID: PMC11261463 DOI: 10.1111/cns.14871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 06/23/2024] [Accepted: 07/09/2024] [Indexed: 07/23/2024] Open
Abstract
MAIN PROBLEM Anhedonia is a critical diagnostic symptom of major depressive disorder (MDD), being associated with poor prognosis. Understanding the neural mechanisms underlying anhedonia is of great significance for individuals with MDD, and it encourages the search for objective indicators that can reliably identify anhedonia. METHODS A predictive model used connectome-based predictive modeling (CPM) for anhedonia symptoms was developed by utilizing pre-treatment functional connectivity (FC) data from 59 patients with MDD. Node-based FC analysis was employed to compare differences in FC patterns between melancholic and non-melancholic MDD patients. The support vector machines (SVM) method was then applied for classifying these two subtypes of MDD patients. RESULTS CPM could successfully predict anhedonia symptoms in MDD patients (positive network: r = 0.4719, p < 0.0020, mean squared error = 23.5125, 5000 iterations). Compared to non-melancholic MDD patients, melancholic MDD patients showed decreased FC between the left cingulate gyrus and the right parahippocampus gyrus (p_bonferroni = 0.0303). This distinct FC pattern effectively discriminated between melancholic and non-melancholic MDD patients, achieving a sensitivity of 93.54%, specificity of 67.86%, and an overall accuracy of 81.36% using the SVM method. CONCLUSIONS This study successfully established a network model for predicting anhedonia symptoms in MDD based on FC, as well as a classification model to differentiate between melancholic and non-melancholic MDD patients. These findings provide guidance for clinical treatment.
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Affiliation(s)
- Tingyu Yang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental DisordersThe Second Xiangya Hospital of Central South UniversityChangshaChina
- Department of Child HealthcareHunan Children's HospitalChangshaChina
| | - Yangpan Ou
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental DisordersThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Huabing Li
- Department of RadiologyThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Feng Liu
- Department of RadiologyTianjin Medical University General HospitalTianjinChina
| | - Ping Li
- Department of PsychiatryQiqihar Medical UniversityQiqiharChina
| | - Guangrong Xie
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental DisordersThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Jingping Zhao
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental DisordersThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Xilong Cui
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental DisordersThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Wenbin Guo
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental DisordersThe Second Xiangya Hospital of Central South UniversityChangshaChina
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The Gender-Specific Interaction of DVL3 and GSK3β Polymorphisms on Major Depressive Disorder Susceptibility in a Chinese Han Population: A Case-Control Study. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2022; 2022:2633127. [PMID: 35126809 PMCID: PMC8816570 DOI: 10.1155/2022/2633127] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Accepted: 01/05/2022] [Indexed: 11/17/2022]
Abstract
Based on the “oxidative stress hypothesis” of major depressive disorder (MDD), cells regulate their structure through the Wnt pathway. Little is known regarding the interactions of dishevelled 3 (DVL3) and glycogen synthase kinase 3 beta (GSK3β) polymorphisms with MDD. The aim of the current study was to verify the relationship between DVL3 and GSK3β genetic variants in a Chinese Han population and further to evaluate whether these interactions exhibit gender-specificity. A total of 1136 participants, consisting of 541 MDD patients and 595 healthy subjects, were recruited. Five single-nucleotide polymorphisms (SNPs) of DVL3/GSK3β were selected to assess their interaction by use of a generalized multifactor dimensionality reduction method. The genotype and haplotype frequencies of DVL3/GSK3β polymorphisms were significantly different between patients and controls for DVL3 rs1709642 (
) and GSK3β rs334558, rs6438552, and rs2199503 (
). In addition, our results also showed that there were significant interaction effects between DVL3 and GSK3β polymorphisms and the risk of developing MDD, particularly in women. The interaction between DVL3 (rs1709642) and GSK3β (rs334558, rs6438552) showed a cross-validation (CV) consistency of 10/10, a
value of 0.001, and a testing accuracy of 59.22%, which was considered as the best generalized multifactor dimensionality reduction (GMDR) model. This study reveals the interaction between DVL3 and GSK3β polymorphisms on MDD susceptibility in a female Chinese Han population. The effect of gender should be taken into account in future studies that seek to explore the genetic predisposition to MDD relative to the DVL3 and GSK3β genes.
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Dold M, Bartova L, Fugger G, Kautzky A, Mitschek MMM, Fabbri C, Montgomery S, Zohar J, Souery D, Mendlewicz J, Serretti A, Kasper S. Melancholic features in major depression - a European multicenter study. Prog Neuropsychopharmacol Biol Psychiatry 2021; 110:110285. [PMID: 33609603 DOI: 10.1016/j.pnpbp.2021.110285] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 01/31/2021] [Accepted: 02/12/2021] [Indexed: 10/22/2022]
Abstract
There is still a debate, if melancholic symptoms can be seen rather as a more severe subtype of major depressive disorder (MDD) or as a separate diagnostic entity. The present European multicenter study comprising altogether 1410 MDD in- and outpatients sought to investigate the influence of the presence of melancholic features in MDD patients. Analyses of covariance, chi-squared tests, and binary logistic regression analyses were accomplished to determine differences in socio-demographic and clinical variables between MDD patients with and without melancholia. We found a prevalence rate of 60.71% for melancholic features in MDD. Compared to non-melancholic MDD patients, they were characterized by a significantly higher likelihood for higher weight, unemployment, psychotic features, suicide risk, inpatient treatment, severe depressive symptoms, receiving add-on medication strategies in general, and adjunctive treatment with antidepressants, antipsychotics, benzodiazepine (BZD)/BZD-like drugs, low-potency antipsychotics, and pregabalin in particular. With regard to the antidepressant pharmacotherapy, we found a less frequent prescription of selective serotonin reuptake inhibitors (SSRIs) in melancholic MDD. No significant between-group differences were found for treatment response, non-response, and resistance. In summary, we explored primarily variables to be associated with melancholia which can be regarded as parameters for the presence of severe/difficult-to treat MDD conditions. Even if there is no evidence to realize any specific treatment strategy in melancholic MDD patients, their prescribed medication strategies were different from those for patients without melancholia.
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Affiliation(s)
- Markus Dold
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Lucie Bartova
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Gernot Fugger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Alexander Kautzky
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Marleen M M Mitschek
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Chiara Fabbri
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom
| | | | - Joseph Zohar
- Psychiatric Division, Chaim Sheba Medical Center, Tel Hashomer, Israel
| | - Daniel Souery
- School of Medicine, Free University of Brussels, Brussels, Belgium; Psy Pluriel - European Centre of Psychological Medicine, Brussels, Belgium
| | | | - Alessandro Serretti
- Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy
| | - Siegfried Kasper
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria; Center for Brain Research, Medical University of Vienna, Vienna, Austria.
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Liu X, Wang Y, Peng D, Zhang H, Zheng Y, Wu Y, Su YA, Liu M, Ma X, Li Y, Shi J, Cheng X, Rong H, Fang Y. The Developmental and Translational Study on Biomarkers and Clinical Characteristics-based Diagnostic and Therapeutic Identification of Major Depressive Disorder: Study Protocol for a Multicenter Randomized Controlled Trial in China. Neuropsychiatr Dis Treat 2020; 16:2343-2351. [PMID: 33116533 PMCID: PMC7553657 DOI: 10.2147/ndt.s271842] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2020] [Accepted: 08/31/2020] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Major depressive disorder (MDD) is a heterogeneous mental disease that encompasses different subtypes and specifiers. Clinically targeted treatments have not been identified yet, although standardized strategies are recommended by several clinical guidelines. The main aim of this study is to respectively identify the precise treatment for three different subtypes of MDD (ie, melancholic, atypical, and anxious). METHODS An 8-to-12-week, multicenter randomized controlled trial (RCT) with a parallel group design will be conducted to determine the most effective and appropriate treatment. A total of 750 adults diagnosed with MDD will be recruited, categorized into melancholic, atypical or anxious type based on the assessment of the Inventory of Depressive Symptomatology (IDS30) and the Hamilton Anxiety Scale (HAMA), and 1:1 randomly assigned to different intervention groups. Blood draw, EEG test, and MRI scan will be performed at baseline and endpoint. Clinical symptom and side-effects will be evaluated at critical decision points (CDP) including weeks two, four, six, eight, and 12 after treatment. The primary outcome is total score and reduction rate of the 17-Hamilton Depression Rating Scale (17-HDRS). The secondary outcomes include the scores of the Quick Inventory of Depressive Symptomatology-self-report (QIDS-SR), IDS30, HAMA and the Treatment Emergent Symptom Scale (TESS). All the data will be analyzed by SAS software. DISCUSSION The study commenced recruitment in August 2017 and is currently ongoing. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT03219008 (July 17, 2017).
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Affiliation(s)
- Xiaohua Liu
- Department of Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.,Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Yun Wang
- Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Daihui Peng
- Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Huifeng Zhang
- Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Yanqun Zheng
- Department of Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Yan Wu
- Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Yun-Ai Su
- Department of Psychiatry, Peking University Sixth Hospital, Peking, People's Republic of China
| | - Ming Liu
- Department of Psychiatry, Harbin First Specific Hospital, Harbin, People's Republic of China
| | - Xiancang Ma
- Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, People's Republic of China
| | - Yi Li
- Department of Psychiatry, Wuhan Mental Health Center, Wuhan, People's Republic of China
| | - Jianfei Shi
- Department of Psychiatry, Hangzhou Seventh People's Hospital, Hangzhou, People's Republic of China
| | - Xiaojing Cheng
- Department of Psychiatry, Shandong Mental Health Center, Shandong, People's Republic of China
| | - Han Rong
- Department of Psychiatry, Shenzhen Kangning Hospital, Shenzhen, People's Republic of China
| | - Yiru Fang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.,Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.,CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai, People's Republic of China
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6
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Dreimüller N, Wagner S, Engel A, Braus DF, Roll SC, Elsner S, Tadić A, Lieb K. Predictors of the effectiveness of an early medication change strategy in patients with major depressive disorder. BMC Psychiatry 2019; 19:24. [PMID: 30642308 PMCID: PMC6332626 DOI: 10.1186/s12888-019-2014-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Accepted: 01/04/2019] [Indexed: 01/23/2023] Open
Abstract
BACKGROUND Patients with Major Depressive Disorder (MDD) who are non-improvers after two weeks of antidepressant treatment have a high risk of treatment failure. Recently, we did not find differences in outcomes in non-improvers randomized to an early medication change (EMC) strategy compared to treatment as usual (TAU). This secondary analysis investigated possible predictors of higher remission rates in the EMC strategy. METHODS Of 192 non-improvers (i.e. decrease of ≤20% on the HAMD-17 depression scale) after a two-week treatment with escitalopram, n = 97 were randomized to EMC (immediate switch to high doses of venlafaxine XR) and n = 95 to TAU (continued escitalopram until day 28 with non-responders switched to venlafaxine XR). We first analyzed patient characteristics, psychopathological features and subtypes of MDD by logistic regression analyses as possible predictors of remission rates. In a second investigation, we analyzed the predictors, which showed a significant association in the first analysis before Bonferroni-Holm correction by chi-squared tests separated for treatment groups. All analyses were corrected by Bonferroni-Holm method. RESULTS The first analyses yielded no statistically significant results after correction for multiple testing. In the second analyses, however, patients with prior medication at study entry showed higher remission rates in EMC than in TAU (24.2% versus 8.6%, p = 0.017; Bonferroni-Holm corrected significance level: p = 0.025.). Furthermore, patients with a recurrent course of MDD benefited less from treatment as usual (p = 0.009; Bonferroni-Holm corrected significance level: p = 0.025). Age, sex, age of onset, psychiatric or somatic comorbidities, and other subtypes of MDD did not predict remission rates. CONCLUSIONS Although in our first analysis we found statistically non-significant results, the second analysis showed significant differences in remission rates between patients with or without previous medication and in patients with recurrent MDD or the first depressive episode. It would therefore be valuable to examine in larger and prospective studies whether remission rates can be increased by quick escalation of treatment in certain subgroups of patients. Promising subgroups to be tested are patients who were previously medicated, and who show a recurrent course of MDD. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00974155 . Registered at the 10th of September 2009. Retrospectively registered.
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Affiliation(s)
- Nadine Dreimüller
- Department of Psychiatry and Psychotherapy, University Medical Center of the Johannes Gutenberg-University Mainz, Untere Zahlbacher Straße 8, D-55131, Mainz, Germany.
| | - Stefanie Wagner
- grid.410607.4Department of Psychiatry and Psychotherapy, University Medical Center of the Johannes Gutenberg-University Mainz, Untere Zahlbacher Straße 8, D-55131 Mainz, Germany
| | - Alice Engel
- grid.410607.4Department of Psychiatry and Psychotherapy, University Medical Center of the Johannes Gutenberg-University Mainz, Untere Zahlbacher Straße 8, D-55131 Mainz, Germany
| | - Dieter F. Braus
- grid.491861.3Department for Psychiatry and Psychotherapy, HELIOS Dr. Horst Schmidt Kliniken, Wiesbaden, Germany
| | - Sibylle C. Roll
- Hospital for Psychiatry and Psychotherapy, Vitos Rheingau, Eltville, Germany
| | - Stefan Elsner
- Hospital for Psychiatry and Psychotherapy, Andernach, Germany
| | - André Tadić
- grid.410607.4Department of Psychiatry and Psychotherapy, University Medical Center of the Johannes Gutenberg-University Mainz, Untere Zahlbacher Straße 8, D-55131 Mainz, Germany ,Agaplesion Elisabethenstift, Department of Psychiatry, Psychosomatics and Psychotherapy, Darmstadt, Germany
| | - Klaus Lieb
- grid.410607.4Department of Psychiatry and Psychotherapy, University Medical Center of the Johannes Gutenberg-University Mainz, Untere Zahlbacher Straße 8, D-55131 Mainz, Germany
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Medium- and high-intensity rTMS reduces psychomotor agitation with distinct neurobiologic mechanisms. Transl Psychiatry 2018; 8:126. [PMID: 29976924 PMCID: PMC6033856 DOI: 10.1038/s41398-018-0129-3] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2017] [Revised: 12/20/2017] [Accepted: 02/18/2018] [Indexed: 12/21/2022] Open
Abstract
Definitive data are lacking on the mechanism of action and biomarkers of repetitive transcranial magnetic stimulation (rTMS) for the treatment of depression. Low-intensity rTMS (LI-rTMS) has demonstrated utility in preclinical models of rTMS treatments but the effects of LI-rTMS in murine models of depression are unknown. We examined the behavioral and neurobiologic changes in olfactory bulbectomy (OB) mice with medium-intensity rTMS (MI-rTMS) treatment and fluoxetine hydrochloride. We then compared 10-Hz rTMS sessions for 3 min at intensities (measured at the cortical surface) of 4 mT (LI-rTMS), 50 mT (medium-intensity rTMS [MI-rTMS]), or 1 T (high-intensity rTMS [HI-rTMS]) 5 days per week over 4 weeks in an OB model of agitated depression. Behavioral effects were assessed with forced swim test; neurobiologic effects were assessed with brain levels of 5-hydroxytryptamine, brain-derived neurotrophic factor (BDNF), and neurogenesis. Peripheral metabolomic changes induced by OB and rTMS were monitored through enzyme-linked immunosorbent assay and ultrapressure liquid chromatography-driven targeted metabolomics evaluated with ingenuity pathway analysis (IPA). MI-rTMS and HI-rTMS attenuated psychomotor agitation but only MI-rTMS increased BDNF and neurogenesis levels. HI-rTMS normalized the plasma concentration of α-amino-n-butyric acid and 3-methylhistidine. IPA revealed significant changes in glutamine processing and glutamate signaling in the OB model and following MI-rTMS and HI-rTMS treatment. The present findings suggest that MI-rTMS and HI-rTMS induce differential neurobiologic changes in a mouse model of agitated depression. Further, α-amino-n-butyric acid and 3-methylhistidine may have utility as biomarkers to objectively monitor the response to rTMS treatment of depression.
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Valerio MP, Szmulewicz AG, Martino DJ. A quantitative review on outcome-to-antidepressants in melancholic unipolar depression. Psychiatry Res 2018; 265:100-110. [PMID: 29702301 DOI: 10.1016/j.psychres.2018.03.088] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Revised: 03/26/2018] [Accepted: 03/31/2018] [Indexed: 10/17/2022]
Abstract
The aim of this study was to explore outcome to antidepressants profile in melancholic unipolar depression. We conducted a systematic review of electronic databases and meta-analysis of randomized and nonrandomized trials comparing: 1) outcome to antidepressants and placebo between melancholic and non-melancholic depression; 2) outcome to different antidepressant classes in melancholic depression. Two outcomes were considered: clinical remission and response. Significant lower odds of remission to antidepressants in melancholic than in non-melancholic depressions were found. Although no significant differences were observed in the response to antidepressants between both subtypes of depression, those with melancholic features had lower odds of response to placebo. Finally, treatment of melancholic depression with serotonin reuptake inhibitors was associated with lower odds of remission compared with tricyclic antidepressants, and similar outcome compared with venlafaxine. Melancholia seems to show a differential pattern of outcome to antidepressants, which could be clinically valuable for a better implementation of personalized medicine of depression. Due to several limitations, further research is needed to support these preliminary findings.
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Affiliation(s)
- Marina P Valerio
- National Council of Scientific and Technical Research (CONICET), Argentina; Psychiatric Emergencies Hospital Torcuato de Alvear, Buenos Aires, Argentina
| | - Alejandro G Szmulewicz
- Bipolar Disorder Program, Institute of Neurosciences, Favaloro University, Buenos Aires, Argentina; Pharmacology Department, University of Buenos Aires School of Medicine, Buenos Aires, Argentina
| | - Diego J Martino
- National Council of Scientific and Technical Research (CONICET), Argentina; Bipolar Disorder Program, Institute of Neurosciences, Favaloro University, Buenos Aires, Argentina; Institute of Cognitive and Translational Neuroscience (INCyT), INECO Foundation, Favaloro University, Buenos Aires, Argentina.
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9
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Tonon AC, Fuchs DFP, Barbosa Gomes W, Levandovski R, Pio de Almeida Fleck M, Hidalgo MPL, da Silva Alencastro L. Nocturnal motor activity and light exposure: Objective actigraphy-based marks of melancholic and non-melancholic depressive disorder. Brief report. Psychiatry Res 2017; 258:587-590. [PMID: 28844556 DOI: 10.1016/j.psychres.2017.08.025] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Revised: 08/09/2017] [Accepted: 08/14/2017] [Indexed: 10/19/2022]
Abstract
Differentiation of melancholic (MEL) and non-melancholic (N-MEL) depression results from subjective assessment of psychomotor disturbance, which obscures their accurate diagnosis. CORE instrument assigned participants with severe or refractory depression to MEL or N-MEL group. Participants underwent 7 days of actigraphy. Data was fitted to a cosinusoidal curve corresponding to a 24-h rhythm. Nocturnal activity was significantly higher in N-MEL. ROC curve shows that average night activity discriminate participants with 71% sensitivity and 100% specificity (area under the curve = 0.84). Actigraphy contribute to the objective differentiation of depression subtypes, and have implications for research on their neurobiology and clinical management.
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Affiliation(s)
- André Comiran Tonon
- Laboratório de Cronobiologia e Sono, Hospital de Clínicas de Porto Alegre (HCPA), Federal University of Rio Grande do Sul (UFRGS), Rua Ramiro Barcelos, 2350, Porto Alegre, RS, Brazil.
| | - Daniel Fernando Paludo Fuchs
- Laboratório de Cronobiologia e Sono, Hospital de Clínicas de Porto Alegre (HCPA), Federal University of Rio Grande do Sul (UFRGS), Rua Ramiro Barcelos, 2350, Porto Alegre, RS, Brazil
| | - William Barbosa Gomes
- Laboratório de Fenomenologia Experimental e Cognição, Instituto de Psicologia, Psicologia, Federal University of Rio Grande do Sul (UFRGS), Rua Ramiro Barcelos, 2600, Porto Alegre, RS, Brazil
| | - Rosa Levandovski
- Laboratório de Cronobiologia e Sono, Hospital de Clínicas de Porto Alegre (HCPA), Federal University of Rio Grande do Sul (UFRGS), Rua Ramiro Barcelos, 2350, Porto Alegre, RS, Brazil
| | - Marcelo Pio de Almeida Fleck
- Programa de Transtornos de Humor do Hospital de Clínicas de Porto Alegre (HCPA), Rua Ramiro Barcelos, 2350, Porto Alegre, RS, Brazil
| | - Maria Paz Loayza Hidalgo
- Laboratório de Cronobiologia e Sono, Hospital de Clínicas de Porto Alegre (HCPA), Federal University of Rio Grande do Sul (UFRGS), Rua Ramiro Barcelos, 2350, Porto Alegre, RS, Brazil
| | - Luciano da Silva Alencastro
- Laboratório de Fenomenologia Experimental e Cognição, Instituto de Psicologia, Psicologia, Federal University of Rio Grande do Sul (UFRGS), Rua Ramiro Barcelos, 2600, Porto Alegre, RS, Brazil
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Abbott CC, Khafaja M. Editorial Comment: Stress and Late-Life Depression. Am J Geriatr Psychiatry 2017; 25:978-979. [PMID: 28602383 PMCID: PMC8344408 DOI: 10.1016/j.jagp.2017.05.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2017] [Accepted: 05/11/2017] [Indexed: 11/16/2022]
Affiliation(s)
- Christopher C Abbott
- Department of Psychiatry, University of New Mexico School of Medicine, Albuquerque, NM.
| | - Mohamad Khafaja
- Department of Psychiatry, University of New Mexico School of Medicine, Albuquerque, NM
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Lv X, Si T, Wang G, Wang H, Liu Q, Hu C, Wang J, Su Y, Huang Y, Jiang H, Yu X. The establishment of the objective diagnostic markers and personalized medical intervention in patients with major depressive disorder: rationale and protocol. BMC Psychiatry 2016; 16:240. [PMID: 27422150 PMCID: PMC4946102 DOI: 10.1186/s12888-016-0953-z] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2016] [Accepted: 07/01/2016] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Major depressive disorders (MDD) is a common mental disorder with high prevalence, frequent relapse and associated with heavy disease burden. Heritability, environment and their interaction play important roles in the development of MDD. MDD patients usually display a wide variation in clinical symptoms and signs, while the diagnosis of MDD is relatively subjective. The treatment response varies substantially between different subtypes of MDD patients and only half respond adequately to the first antidepressant. This study aims to define subtypes of MDD, develop multi-dimension diagnostic test and combined predictors for improving the diagnostic accuracy and promoting personalized intervention in MDD patients. METHODS/DESIGN This is a multi-center, multi-stage and prospective study. The first stage of this study is a case-control study, aims to explore the risk factors for developing MDD and then define the subtypes of MDD using 1200 MDD patients and 1200 healthy controls with a set of questionnaire. The second stage is a diagnostic test, aims to indentify and replicate the potential indicators to assist MDD diagnosis using 600 MDD patients and 300 healthy controls from the first stage with a set of questionnaire, neuropsychological assessment and a series of biomarkers. The third stage is a 96-week longitudinal study, including 8-week acute period treatment and 88-week stable period treatment, aims to identify overall predictors of treatment effectiveness on MDD at week 8 post treatment and to explore the predictors on MDD prognosis in the following 2 years using 600 MDD patients from the first stage with a set of questionnaire, neuropsychological assessment and a series of biomarkers. The primary outcome measure is the change of the total score of 17-Item Hamilton Rating Scale for Depression. DISCUSSION This study will provide strong and suitable evidence for enhancing the accuracy of MDD diagnosis and promoting personalized treatment for MDD patients in clinical practice. TRIAL REGISTRATION ClinicalTrials.gov: NCT02023567 ; registration date: December 2013.
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Affiliation(s)
- Xiaozhen Lv
- Peking University Sixth Hospital (Institute of Mental Health), Beijing, China ,National Clinical Research Center for Mental Disorders & Key Laboratory for Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Tianmei Si
- Peking University Sixth Hospital (Institute of Mental Health), Beijing, China ,National Clinical Research Center for Mental Disorders & Key Laboratory for Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Gang Wang
- Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Huali Wang
- Peking University Sixth Hospital (Institute of Mental Health), Beijing, China ,National Clinical Research Center for Mental Disorders & Key Laboratory for Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Qi Liu
- Peking University Sixth Hospital (Institute of Mental Health), Beijing, China ,National Clinical Research Center for Mental Disorders & Key Laboratory for Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Changqing Hu
- Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Jing Wang
- Peking University Sixth Hospital (Institute of Mental Health), Beijing, China ,National Clinical Research Center for Mental Disorders & Key Laboratory for Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Yunai Su
- Peking University Sixth Hospital (Institute of Mental Health), Beijing, China ,National Clinical Research Center for Mental Disorders & Key Laboratory for Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Yu Huang
- National Engineering Research Center for Software Engineering, Peking University, Beijing, China
| | - Hui Jiang
- National Engineering Research Center for Software Engineering, Peking University, Beijing, China
| | - Xin Yu
- Peking University Sixth Hospital (Institute of Mental Health), Beijing, China. .,National Clinical Research Center for Mental Disorders & Key Laboratory for Mental Health, Ministry of Health, Peking University, Beijing, China.
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