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Yu J. Acute hyper-hypoxia accelerates the development of depression in mice via the IL-6/PGC1α/MFN2 signaling pathway. Open Med (Wars) 2024; 19:20241001. [PMID: 39135980 PMCID: PMC11317639 DOI: 10.1515/med-2024-1001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 06/30/2024] [Accepted: 07/03/2024] [Indexed: 08/15/2024] Open
Abstract
Background Neural cell damage is an important cause of exacerbation of depression symptoms caused by hypoxia, but the mechanism behind it is still unclear. The purpose of this study is to elucidate the role of peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1α)/mitofusin-2 (MFN2) signaling axis in the development of depression in mice under hypoxia. Methods Male Institute of Cancer Research mice (age, 6 weeks) were assigned to the normal group, chronic unpredictable mild stress group (CUMS group), or CUMS + hyper-hypoxia group (CUMS + H group). Mice in the CUMS and CUMS + H groups were exposed to CUMS for 28 days. Additionally, mice in the CUMS + H group were exposed to acute hyper-hypoxia from Day 21 for 7 days. After a total of 28 days, behavioral experiments were conducted. All mice were anesthetized and sacrificed. Levels of brain tissue interleukin (IL)-6, reactive oxygen species (ROS), adenosine triphosphate (ATP), and serotonin (5-HT) were analyzed. Results As compared to the CUMS group, mice in the CUMS + H group had increased IL-6 and ROS levels, but lower open-field activity, preference for sucrose, hippocampal neuronal membrane potential, ATP, and 5-HT levels, as well as MFN2 and PGC1α levels. Conclusions Acute hyper-hypoxia plays an important role in the development of depression via the IL-6/PGC1α/MFN2 signaling pathway.
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Affiliation(s)
- Jialu Yu
- Department of Anesthesiology, Guizhou Medical University, Guiyang, China
- Department of Clinical Medicine, Guizhou Medical University, 14 Beijing Road, Guiyang550000, China
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Thai M, Olson EA, Nickels S, Dillon DG, Webb CA, Ren B, Killgore WDS, Rauch SL, Rosso IM, Pizzagalli DA. Neural and behavioral markers of inhibitory control predict symptom improvement during internet-delivered cognitive behavioral therapy for depression. Transl Psychiatry 2024; 14:303. [PMID: 39043642 PMCID: PMC11266709 DOI: 10.1038/s41398-024-03020-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 06/24/2024] [Accepted: 07/10/2024] [Indexed: 07/25/2024] Open
Abstract
Poor inhibitory control contributes to deficits in emotion regulation, which are often targeted by treatments for major depressive disorder (MDD), including cognitive behavioral therapy (CBT). Brain regions that contribute to inhibitory control and emotion regulation overlap; thus, inhibitory control might relate to response to CBT. In this study, we examined whether baseline inhibitory control and resting state functional connectivity (rsFC) within overlapping emotion regulation-inhibitory control regions predicted treatment response to internet-based CBT (iCBT). Participants with MDD were randomly assigned to iCBT (N = 30) or a monitored attention control (MAC) condition (N = 30). Elastic net regression was used to predict post-treatment Patient Health Questionnaire-9 (PHQ-9) scores from baseline variables, including demographic variables, PHQ-9 scores, Flanker effects (interference, sequential dependency, post-error slowing), and rsFC between the dorsal anterior cingulate cortex, bilateral anterior insula (AI), and right temporoparietal junction (TPJ). Essential prognostic predictor variables retained in the elastic net regression included treatment group, gender, Flanker interference response time (RT), right AI-TPJ rsFC, and left AI-right AI rsFC. Prescriptive predictor variables retained included interactions between treatment group and baseline PHQ-9 scores, age, gender, Flanker RT, sequential dependency effects on accuracy, post-error accuracy, right AI-TPJ rsFC, and left AI-right AI rsFC. Inhibitory control and rsFC within inhibitory control-emotion regulation regions predicted reduced symptom severity following iCBT, and these effects were stronger in the iCBT group than in the MAC group. These findings contribute to a growing literature indicating that stronger inhibitory control at baseline predicts better outcomes to psychotherapy, including iCBT.
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Affiliation(s)
- Michelle Thai
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
| | - Elizabeth A Olson
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Stefanie Nickels
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Daniel G Dillon
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Christian A Webb
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Boyu Ren
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Psychiatric Biostatistics Laboratory, McLean Hospital, Belmont, MA, USA
| | - William D S Killgore
- Department of Psychiatry, University of Arizona College of Medicine, Tucson, AZ, USA
| | - Scott L Rauch
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Isabelle M Rosso
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Diego A Pizzagalli
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- McLean Imaging Center, McLean Hospital, Belmont, MA, USA
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Sun S, Yan C, Qu S, Luo G, Liu X, Tian F, Dong Q, Li X, Hu B. Resting-state dynamic functional connectivity in major depressive disorder: A systematic review. Prog Neuropsychopharmacol Biol Psychiatry 2024; 135:111076. [PMID: 38972502 DOI: 10.1016/j.pnpbp.2024.111076] [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: 03/05/2024] [Revised: 06/02/2024] [Accepted: 06/26/2024] [Indexed: 07/09/2024]
Abstract
As a novel measure, dynamic functional connectivity (dFC) provides insight into the dynamic nature of brain networks and their interactions in resting-state, surpassing traditional static functional connectivity in pathological conditions such as depression. Since a comprehensive review is still lacking, we then reviewed forty-five eligible papers to explore pathological mechanisms of major depressive disorder (MDD) from perspectives including abnormal brain regions and functional networks, brain state, topological properties, relevant recognition, along with longitudinal studies. Though inconsistencies could be found, common findings are: (1) From different perspectives based on dFC, default-mode network (DMN) with its subregions exhibited a close relation to the pathological mechanism of MDD. (2) With a corrupted integrity within large-scale functional networks and imbalance between them, longer fraction time in a relatively weakly-connected state may be a possible property of MDD concerning its relation with DMN. Abnormal transition frequencies between states were correlated to the severity of MDD. (3) Including dynamic properties in topological network metrics enhanced recognition effect. In all, this review summarized its use for clinical diagnosis and treatment, elucidating the non-stationary of MDD patients' aberrant brain activity in the absence of stimuli and bringing new views into its underlying neuro mechanism.
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Affiliation(s)
- Shuting Sun
- Key Laboratory of Brain Health Intelligent Evaluation and Intervention, Beijing Institute of Technology, Ministry of Education, China; Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, China
| | - Chang Yan
- Key Laboratory of Brain Health Intelligent Evaluation and Intervention, Beijing Institute of Technology, Ministry of Education, China
| | - Shanshan Qu
- Key Laboratory of Brain Health Intelligent Evaluation and Intervention, Beijing Institute of Technology, Ministry of Education, China
| | - Gang Luo
- Key Laboratory of Brain Health Intelligent Evaluation and Intervention, Beijing Institute of Technology, Ministry of Education, China
| | - Xuesong Liu
- Key Laboratory of Brain Health Intelligent Evaluation and Intervention, Beijing Institute of Technology, Ministry of Education, China
| | - Fuze Tian
- Key Laboratory of Brain Health Intelligent Evaluation and Intervention, Beijing Institute of Technology, Ministry of Education, China; Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, China
| | - Qunxi Dong
- Key Laboratory of Brain Health Intelligent Evaluation and Intervention, Beijing Institute of Technology, Ministry of Education, China
| | - Xiaowei Li
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, China
| | - Bin Hu
- Key Laboratory of Brain Health Intelligent Evaluation and Intervention, Beijing Institute of Technology, Ministry of Education, China; Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, China.
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Dam S, Batail JM, Robert GH, Drapier D, Maurel P, Coloigner J. Structural Brain Connectivity and Treatment Improvement in Mood Disorder. Brain Connect 2024; 14:239-251. [PMID: 38534988 DOI: 10.1089/brain.2023.0063] [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] [Indexed: 04/25/2024] Open
Abstract
Background: The treatment of depressive episodes is well established, with clearly demonstrated effectiveness of antidepressants and psychotherapies. However, more than one-third of depressed patients do not respond to treatment. Identifying the brain structural basis of treatment-resistant depression could prevent useless pharmacological prescriptions, adverse events, and lost therapeutic opportunities. Methods: Using diffusion magnetic resonance imaging, we performed structural connectivity analyses on a cohort of 154 patients with mood disorder (MD) and 77 sex- and age-matched healthy control (HC) participants. To assess illness improvement, the patients with MD went through two clinical interviews at baseline and at 6-month follow-up and were classified based on the Clinical Global Impression-Improvement score into improved or not-improved (NI). First, the threshold-free network-based statistics (NBS) was conducted to measure the differences in regional network architecture. Second, nonparametric permutations tests were performed on topological metrics based on graph theory to examine differences in connectome organization. Results: The threshold-free NBS revealed impaired connections involving regions of the basal ganglia in patients with MD compared with HC. Significant increase of local efficiency and clustering coefficient was found in the lingual gyrus, insula, and amygdala in the MD group. Compared with the NI, the improved displayed significantly reduced network integration and segregation, predominately in the default-mode regions, including the precuneus, middle temporal lobe, and rostral anterior cingulate. Conclusions: This study highlights the involvement of regions belonging to the basal ganglia, the fronto-limbic network, and the default mode network, leading to a better understanding of MD disease and its unfavorable outcome.
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Affiliation(s)
- Sébastien Dam
- Univ Rennes, Inria, CNRS, IRISA, INSERM, Empenn U1228 ERL, Rennes, France
| | - Jean-Marie Batail
- Academic Psychiatry Department, Centre Hospitalier Guillaume Régnier, Rennes, France
- CIC 1414, CHU de Rennes, INSERM, Rennes, France
| | - Gabriel H Robert
- Univ Rennes, Inria, CNRS, IRISA, INSERM, Empenn U1228 ERL, Rennes, France
- Academic Psychiatry Department, Centre Hospitalier Guillaume Régnier, Rennes, France
- CIC 1414, CHU de Rennes, INSERM, Rennes, France
| | - Dominique Drapier
- Academic Psychiatry Department, Centre Hospitalier Guillaume Régnier, Rennes, France
- CIC 1414, CHU de Rennes, INSERM, Rennes, France
| | - Pierre Maurel
- Univ Rennes, Inria, CNRS, IRISA, INSERM, Empenn U1228 ERL, Rennes, France
| | - Julie Coloigner
- Univ Rennes, Inria, CNRS, IRISA, INSERM, Empenn U1228 ERL, Rennes, France
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Zhou Z, Gao Y, Bao W, Liang K, Cao L, Tang M, Li H, Hu X, Zhang L, Sun H, Roberts N, Gong Q, Huang X. Distinctive intrinsic functional connectivity alterations of anterior cingulate cortex subdivisions in major depressive disorder: A systematic review and meta-analysis. Neurosci Biobehav Rev 2024; 159:105583. [PMID: 38365137 DOI: 10.1016/j.neubiorev.2024.105583] [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: 09/30/2023] [Revised: 01/22/2024] [Accepted: 02/11/2024] [Indexed: 02/18/2024]
Abstract
Evidence of whether the intrinsic functional connectivity of anterior cingulate cortex (ACC) and its subregions is altered in major depressive disorder (MDD) remains inconclusive. A systematic review and meta-analysis were therefore performed on the whole-brain resting-state functional connectivity (rsFC) studies using the ACC and its subregions as seed regions in MDD, in order to draw more reliable conclusions. Forty-four ACC-based rsFC studies were included, comprising 25 subgenual ACC-based studies, 11 pregenual ACC-based studies, and 17 dorsal ACC-based studies. Specific alterations of rsFC were identified for each ACC subregion in patients with MDD, with altered rsFC of subgenual ACC in emotion-related brain regions, of pregenual ACC in sensorimotor-related regions, and of dorsal ACC in cognition-related regions. Furthermore, meta-regression analysis revealed a significant negative correlation between the pgACC-caudate hypoconnectivity and percentage of female patients in the study cohort. This meta-analysis provides robust evidence of altered intrinsic functional connectivity of the ACC subregions in MDD, which may hold relevance to understanding the origin of, and treating, the emotional, sensorimotor and cognitive dysfunctions that are often observed in these patients.
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Affiliation(s)
- Zilin Zhou
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Yingxue Gao
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Weijie Bao
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Kaili Liang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Lingxiao Cao
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Mengyue Tang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Hailong Li
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Xinyue Hu
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Lianqing Zhang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Huaiqiang Sun
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Science, Chengdu, China
| | - Neil Roberts
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Centre for Reproductive Health (CRH), School of Clinical Sciences, University of Edinburgh, Edinburgh, UK
| | - Qiyong Gong
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Science, Chengdu, China; The Xiaman Key Lab of psychoradiology and neuromodulation, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China
| | - Xiaoqi Huang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Science, Chengdu, China; The Xiaman Key Lab of psychoradiology and neuromodulation, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China.
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6
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Silva NA, Barrios-Martinez J, Yeh FC, Hodaie M, Roque D, Boerwinkle VL, Krishna V. Diffusion and functional MRI in surgical neuromodulation. Neurotherapeutics 2024; 21:e00364. [PMID: 38669936 PMCID: PMC11064589 DOI: 10.1016/j.neurot.2024.e00364] [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: 11/06/2023] [Revised: 04/13/2024] [Accepted: 04/15/2024] [Indexed: 04/28/2024] Open
Abstract
Surgical neuromodulation has witnessed significant progress in recent decades. Notably, deep brain stimulation (DBS), delivered precisely within therapeutic targets, has revolutionized the treatment of medication-refractory movement disorders and is now expanding for refractory psychiatric disorders, refractory epilepsy, and post-stroke motor recovery. In parallel, the advent of incisionless treatment with focused ultrasound ablation (FUSA) can offer patients life-changing symptomatic relief. Recent research has underscored the potential to further optimize DBS and FUSA outcomes by conceptualizing the therapeutic targets as critical nodes embedded within specific brain networks instead of strictly anatomical structures. This paradigm shift was facilitated by integrating two imaging modalities used regularly in brain connectomics research: diffusion MRI (dMRI) and functional MRI (fMRI). These advanced imaging techniques have helped optimize the targeting and programming techniques of surgical neuromodulation, all while holding immense promise for investigations into treating other neurological and psychiatric conditions. This review aims to provide a fundamental background of advanced imaging for clinicians and scientists, exploring the synergy between current and future approaches to neuromodulation as they relate to dMRI and fMRI capabilities. Focused research in this area is required to optimize existing, functional neurosurgical treatments while serving to build an investigative infrastructure to unlock novel targets to alleviate the burden of other neurological and psychiatric disorders.
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Affiliation(s)
- Nicole A Silva
- Department of Neurological Surgery, University of North Carolina - Chapel Hill, Chapel Hill, NC, USA
| | | | - Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mojgan Hodaie
- Division of Neurosurgery, University of Toronto, Toronto, Canada
| | - Daniel Roque
- Department of Neurology, University of North Carolina in Chapel Hill, NC, USA
| | - Varina L Boerwinkle
- Department of Neurology, University of North Carolina in Chapel Hill, NC, USA
| | - Vibhor Krishna
- Department of Neurological Surgery, University of North Carolina - Chapel Hill, Chapel Hill, NC, USA.
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Tsuchiyagaito A, Sánchez SM, Misaki M, Kuplicki R, Park H, Paulus MP, Guinjoan SM. Intensity of repetitive negative thinking in depression is associated with greater functional connectivity between semantic processing and emotion regulation areas. Psychol Med 2023; 53:5488-5499. [PMID: 36043367 PMCID: PMC9973538 DOI: 10.1017/s0033291722002677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Repetitive negative thinking (RNT), a cognitive process that encompasses past (rumination) and future (worry) directed thoughts focusing on negative experiences and the self, is a transdiagnostic construct that is especially relevant for major depressive disorder (MDD). Severe RNT often occurs in individuals with severe levels of MDD, which makes it challenging to disambiguate the neural circuitry underlying RNT from depression severity. METHODS We used a propensity score, i.e., a conditional probability of having high RNT given observed covariates to match high and low RNT individuals who are similar in the severity of depression, anxiety, and demographic characteristics. Of 148 MDD individuals, we matched high and low RNT groups (n = 50/group) and used a data-driven whole-brain voxel-to-voxel connectivity pattern analysis to investigate the resting-state functional connectivity differences between the groups. RESULTS There was an association between RNT and connectivity in the bilateral superior temporal sulcus (STS), an important region for speech processing including inner speech. High relative to low RNT individuals showed greater connectivity between right STS and bilateral anterior insular cortex (AI), and between bilateral STS and left dorsolateral prefrontal cortex (DLPFC). Greater connectivity in those regions was specifically related to RNT but not to depression severity. CONCLUSIONS RNT intensity is directly related to connectivity between STS and AI/DLPFC. This might be a mechanism underlying the role of RNT in perceptive, cognitive, speech, and emotional processing. Future investigations will need to determine whether modifying these connectivities could be a treatment target to reduce RNT.
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Affiliation(s)
- Aki Tsuchiyagaito
- Laureate Institute for Brain Research, Tulsa, OK, USA
- The University of Tulsa, Tulsa, OK, USA
- Chiba University, Chiba, Japan
| | | | - Masaya Misaki
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | | | - Heekyong Park
- Laureate Institute for Brain Research, Tulsa, OK, USA
- University of North Texas at Dallas, Dallas, TX, USA
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Van Assche E, Hohoff C, Zang J, Knight MJ, Baune BT. Longitudinal early epigenomic signatures inform molecular paths of therapy response and remission in depressed patients. Front Mol Neurosci 2023; 16:1223216. [PMID: 37664245 PMCID: PMC10472456 DOI: 10.3389/fnmol.2023.1223216] [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: 05/15/2023] [Accepted: 07/24/2023] [Indexed: 09/05/2023] Open
Abstract
Introduction The etiology of major depressive disorder (MDD) involves the interaction between genes and environment, including treatment. Early molecular signatures for treatment response and remission are relevant in a context of personalized medicine and stratification and reduce the time-to-decision. Therefore, we focused the analyses on patients that responded or remitted following a cognitive intervention of 8 weeks. Methods We used data from a randomized controlled trial (RCT) with MDD patients (N = 112) receiving a cognitive intervention. At baseline and 8 weeks, blood for DNA methylation (Illumina Infinium MethylationEPIC 850k BeadChip) was collected, as well as MADRS. First, responders (N = 24; MADRS-reduction of at least 50%) were compared with non-responders (N = 60). Then, we performed longitudinal within-individual analyses, for response (N = 21) and for remission (N = 18; MADRS smaller or equal to 9 and higher than 9 at baseline), respectively, as well as patients with no change in MADRS over time. At 8 weeks the sample comprised 84 individuals; 73 patients had DNA methylation for both time-points. The RnBeads package (R) was used for data cleaning, quality control, and differential DNA-methylation (limma). The within-individual paired longitudinal analysis was performed using Welch's t-test. Subsequently gene-ontology (GO) pathway analyses were performed. Results No CpG was genome-wide significant CpG (p < 5 × 10-8). The most significant CpG in the differential methylation analysis comparing response versus non-response was in the IQSEC1 gene (cg01601845; p = 1.53 × 10-6), linked to neurotransmission. The most significant GO-terms were linked to telomeres. The longitudinal response analysis returned 67 GO pathways with a p < 0.05. Two of the three most significant pathways were linked to sodium transport. The analysis for remission returned 46 GO terms with a p-value smaller than 0.05 with pathways linked to phosphatase regulation and synaptic functioning. The analysis with stable patients returned mainly GO-terms linked to basic cellular processes. Discussion Our result suggest that DNA methylation can be suitable to capture early signs of treatment response and remission following a cognitive intervention in depression. Despite not being genome-wide significant, the CpG locations and GO-terms returned by our analysis comparing patients with and without cognitive impairment, are in line with prior knowledge on pathways and genes relevant for depression treatment and cognition. Our analysis provides new hypotheses for the understanding of how treatment for depression can act through DNA methylation and induce response and remission.
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Affiliation(s)
| | - Christa Hohoff
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Johannes Zang
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Matthew J. Knight
- Discipline of Psychiatry, Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia
| | - Bernhard T. Baune
- Department of Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, Australia
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
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Zhang S, She S, Qiu Y, Li Z, Wu X, Hu H, Zheng W, Huang R, Wu H. Multi-modal MRI measures reveal sensory abnormalities in major depressive disorder patients: A surface-based study. Neuroimage Clin 2023; 39:103468. [PMID: 37473494 PMCID: PMC10372163 DOI: 10.1016/j.nicl.2023.103468] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 06/17/2023] [Accepted: 07/05/2023] [Indexed: 07/22/2023]
Abstract
BACKGROUND Multi-modal magnetic resonance imaging (MRI) measures are supposed to be able to capture different brain neurobiological aspects of major depressive disorder (MDD). A fusion analysis of structural and functional modalities may better reveal the disease biomarker specific to the MDD disease. METHODS We recruited 30 MDD patients and 30 matched healthy controls (HC). For each subject, we acquired high-resolution brain structural images and resting-state fMRI (rs-fMRI) data using a 3 T MRI scanner. We first extracted the brain morphometric measures, including the cortical volume (CV), cortical thickness (CT), and surface area (SA), for each subject from the structural images, and then detected the structural clusters showing significant between-group differences in each measure using the surface-based morphology (SBM) analysis. By taking the identified structural clusters as seeds, we performed seed-based functional connectivity (FC) analyses to determine the regions with abnormal FC in the patients. Based on a logistic regression model, we performed a classification analysis by selecting these structural and functional cluster-wise measures as features to distinguish the MDD patients from the HC. RESULTS The MDD patients showed significantly lower CV in a cluster involving the right superior temporal gyrus (STG) and middle temporal gyrus (MTG), and lower SA in three clusters involving the bilateral STG, temporal pole gyrus, and entorhinal cortex, and the left inferior temporal gyrus, and fusiform gyrus, than the controls. No significant difference in CT was detected between the two groups. By taking the above-detected clusters as seeds to perform the seed-based FC analysis, we found that the MDD patients showed significantly lower FC between STG/MTG (CV's cluster) and two clusters located in the bilateral visual cortices than the controls. The logistic regression model based on the structural and functional features reached a classification accuracy of 86.7% (p < 0.001) between MDD and controls. CONCLUSION The present study showed sensory abnormalities in MDD patients using the multi-modal MRI analysis. This finding may act as a disease biomarker distinguishing MDD patients from healthy individuals.
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Affiliation(s)
- Shufei Zhang
- School of Psychology, Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou 510631, China
| | - Shenglin She
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou 510370, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou 510370, China
| | - Yidan Qiu
- School of Psychology, Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou 510631, China
| | - Zezhi Li
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou 510370, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou 510370, China
| | - Xiaoyan Wu
- School of Psychology, Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou 510631, China
| | - Huiqing Hu
- School of Psychology, Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou 510631, China
| | - Wei Zheng
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou 510370, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou 510370, China
| | - Ruiwang Huang
- School of Psychology, Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou 510631, China.
| | - Huawang Wu
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou 510370, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou 510370, China.
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Katayama N, Nakagawa A, Umeda S, Terasawa Y, Shinagawa K, Kikuchi T, Tabuchi H, Abe T, Mimura M. Functional connectivity changes between frontopolar cortex and nucleus accumbens following cognitive behavioral therapy in major depression: A randomized clinical trial. Psychiatry Res Neuroimaging 2023; 332:111643. [PMID: 37060839 DOI: 10.1016/j.pscychresns.2023.111643] [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: 11/17/2022] [Revised: 03/19/2023] [Accepted: 04/05/2023] [Indexed: 04/17/2023]
Abstract
Cognitive behavioral therapy (CBT) is a psychotherapy that challenges distorted cognitions; however, the neural mechanisms that underpin CBT remain unclear. Hence, we aimed to assess the treatment-related resting-state functional connectivity (rsFC) changes in the brain regions associated with future thinking and the associations between rsFC changes and clinical improvements. Thirty-eight adult patients with MDD were randomly assigned with equal likelihood to receive 16-week individual CBT or talking control with a 12-month follow-up period. We evaluated the rsFC changes in the frontal regions, nucleus accumbens, amygdala, and limbic structures key to the depression pathophysiology and future thinking with 2 × 2 mixed ANOVA interaction analysis. Pearson's correlation analysis with Bonferroni's correction was also performed to examine the associations with clinical symptoms, such as depression severity and automatic thoughts in follow-up evaluations. Treatment-specific changes include enhancement in frontopolar connectivity with the nucleus accumbens. An increased rsFC was associated with lower negative automatic thoughts postoperatively, together with lower depressive symptoms and higher positive automatic thoughts at follow-up. Conclusively, rsFC changes in the fronto-limbic neural control circuit after CBT, particularly between the frontal pole and nucleus accumbens, may be clinically meaningful functional changes related to the depression recovery process.
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Affiliation(s)
- Nariko Katayama
- Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | - Atsuo Nakagawa
- Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan; Department of Neuropsychiatry, School of Medicine, St. Marianna University, Kawasaki, Japan.
| | - Satoshi Umeda
- Department of Psychology, Faculty of Letters, Keio University, Tokyo, Japan
| | - Yuri Terasawa
- Department of Psychology, Faculty of Letters, Keio University, Tokyo, Japan
| | - Kazushi Shinagawa
- Department of Psychology, Faculty of Letters, Keio University, Tokyo, Japan
| | - Toshiaki Kikuchi
- Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | - Hajime Tabuchi
- Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | - Takayuki Abe
- Department of Neuropsychiatry, School of Medicine, St. Marianna University, Kawasaki, Japan; School of Data Science, Yokohama City University, Yokohama, Japan
| | - Masaru Mimura
- Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
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11
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Li X, Guo J, Chen X, Yu R, Chen W, Zheng A, Yu Y, Zhou D, Dai L, Kuang L. Predicting Responses to Electroconvulsive Therapy in Adolescents with Treatment-Refractory Depression Based on Resting-State fMRI. J Clin Med 2023; 12:jcm12103556. [PMID: 37240663 DOI: 10.3390/jcm12103556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 03/09/2023] [Accepted: 03/22/2023] [Indexed: 05/28/2023] Open
Abstract
OBJECTS The efficacy of electroconvulsive therapy (ECT) in the treatment of adolescents with treatment-refractory depression is still unsatisfactory, and the individual differences are large. It is not clear which factors are related to the treatment effect. Resting-state fMRI may be a good tool to predict the clinical efficacy of this treatment, and it is helpful to identify the most suitable population for this treatment. METHODS Forty treatment-refractory depression adolescents were treated by ECT and evaluated using HAMD and BSSI scores before and after treatment, and were then divided into a treatment response group and a non-treatment group according to the reduction rate of the HAMD scale. We extracted the ALFF, fALFF, ReHo, and functional connectivity of patients as predicted features after a two-sample t-test and LASSO to establish and evaluate a prediction model of ECT in adolescents with treatment-refractory depression. RESULTS Twenty-seven patients achieved a clinical response; symptoms of depression and suicidal ideation were significantly improved after treatment with ECT, which was reflected in a significant decrease in the scores of HAMD and BSSI (p < 0.001). The efficacy was predicted by ALFF, fALFF, ReHo, and whole-brain-based functional connectivity. We found that models built on a subset of features of ALFF in the left insula, fALFF in the left superior parietal gyrus, right superior parietal gyrus, and right angular, and functional connectivity between the left superior frontal gyrus, dorsolateral-right paracentral lobule, right middle frontal gyrus, orbital part-left cuneus, right olfactory cortex-left hippocampus, left insula-left thalamus, and left anterior cingulate gyrus-right hippocampus to have the best predictive performance (AUC > 0.8). CONCLUSIONS The local brain function in the insula, superior parietal gyrus, and angular gyrus as well as characteristic changes in the functional connectivity of cortical-limbic circuits may serve as potential markers for efficacy judgment of ECT and help to provide optimized individual treatment strategies for adolescents with depression and suicidal ideation in the early stages of treatment.
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Affiliation(s)
- Xiao Li
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Jiamei Guo
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Xiaolu Chen
- The First Branch, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400015, China
| | - Renqiang Yu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Wanjun Chen
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Anhai Zheng
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Yanjie Yu
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Dongdong Zhou
- Mental Health Center, University-Town Hospital of Chongqing Medical University, Chongqing 401331, China
| | - Linqi Dai
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Li Kuang
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
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12
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Jellinger KA. The heterogeneity of late-life depression and its pathobiology: a brain network dysfunction disorder. J Neural Transm (Vienna) 2023:10.1007/s00702-023-02648-z. [PMID: 37145167 PMCID: PMC10162005 DOI: 10.1007/s00702-023-02648-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 04/28/2023] [Indexed: 05/06/2023]
Abstract
Depression is frequent in older individuals and is often associated with cognitive impairment and increasing risk of subsequent dementia. Late-life depression (LLD) has a negative impact on quality of life, yet the underlying pathobiology is still poorly understood. It is characterized by considerable heterogeneity in clinical manifestation, genetics, brain morphology, and function. Although its diagnosis is based on standard criteria, due to overlap with other age-related pathologies, the relationship between depression and dementia and the relevant structural and functional cerebral lesions are still controversial. LLD has been related to a variety of pathogenic mechanisms associated with the underlying age-related neurodegenerative and cerebrovascular processes. In addition to biochemical abnormalities, involving serotonergic and GABAergic systems, widespread disturbances of cortico-limbic, cortico-subcortical, and other essential brain networks, with disruption in the topological organization of mood- and cognition-related or other global connections are involved. Most recent lesion mapping has identified an altered network architecture with "depressive circuits" and "resilience tracts", thus confirming that depression is a brain network dysfunction disorder. Further pathogenic mechanisms including neuroinflammation, neuroimmune dysregulation, oxidative stress, neurotrophic and other pathogenic factors, such as β-amyloid (and tau) deposition are in discussion. Antidepressant therapies induce various changes in brain structure and function. Better insights into the complex pathobiology of LLD and new biomarkers will allow earlier and better diagnosis of this frequent and disabling psychopathological disorder, and further elucidation of its complex pathobiological basis is warranted in order to provide better prevention and treatment of depression in older individuals.
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Affiliation(s)
- Kurt A Jellinger
- Institute of Clinical Neurobiology, Alberichgasse 5/13, 1150, Vienna, Austria.
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13
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Sheu YH, Magdamo C, Miller M, Das S, Blacker D, Smoller JW. AI-assisted prediction of differential response to antidepressant classes using electronic health records. NPJ Digit Med 2023; 6:73. [PMID: 37100858 PMCID: PMC10133261 DOI: 10.1038/s41746-023-00817-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 04/04/2023] [Indexed: 04/28/2023] Open
Abstract
Antidepressant selection is largely a trial-and-error process. We used electronic health record (EHR) data and artificial intelligence (AI) to predict response to four antidepressants classes (SSRI, SNRI, bupropion, and mirtazapine) 4 to 12 weeks after antidepressant initiation. The final data set comprised 17,556 patients. Predictors were derived from both structured and unstructured EHR data and models accounted for features predictive of treatment selection to minimize confounding by indication. Outcome labels were derived through expert chart review and AI-automated imputation. Regularized generalized linear model (GLM), random forest, gradient boosting machine (GBM), and deep neural network (DNN) models were trained and their performance compared. Predictor importance scores were derived using SHapley Additive exPlanations (SHAP). All models demonstrated similarly good prediction performance (AUROCs ≥ 0.70, AUPRCs ≥ 0.68). The models can estimate differential treatment response probabilities both between patients and between antidepressant classes for the same patient. In addition, patient-specific factors driving response probabilities for each antidepressant class can be generated. We show that antidepressant response can be accurately predicted from real-world EHR data with AI modeling, and our approach could inform further development of clinical decision support systems for more effective treatment selection.
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Affiliation(s)
- Yi-Han Sheu
- Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA, USA.
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Department of Psychiatry, Massachusetts General Hospital / Harvard Medical School, Boston, MA, USA.
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Colin Magdamo
- Department of Neurology, Massachusetts General Hospital / Harvard Medical School, Boston, MA, USA
| | - Matthew Miller
- Harvard Injury Control Research Center, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Bouvé College of Health Sciences, Northeastern University, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Sudeshna Das
- Department of Neurology, Massachusetts General Hospital / Harvard Medical School, Boston, MA, USA
| | - Deborah Blacker
- Department of Psychiatry, Massachusetts General Hospital / Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jordan W Smoller
- Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital / Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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14
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Zhang S, Zhou J, Cui J, Zhang Z, Liu R, Feng Y, Feng L, Wang Y, Chen X, Wu H, Jin Y, Zhou Y, Wang G. Effects of 12-week escitalopram treatment on resting-state functional connectivity of large-scale brain networks in major depressive disorder. Hum Brain Mapp 2023; 44:2572-2584. [PMID: 36773284 PMCID: PMC10028676 DOI: 10.1002/hbm.26231] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 01/06/2023] [Accepted: 01/30/2023] [Indexed: 02/12/2023] Open
Abstract
In this study, the effects of antidepressants on large-scale brain networks and the neural basis of individual differences in response were explored. A total of 41 patients with major depressive disorder (MDD) and 42 matched healthy controls (HCs) were scanned by resting-state functional magnetic resonance imaging separately at baseline and after a 12-week follow-up. The patients with MDD received escitalopram for 12 weeks. After treatment, patients were classified into those with MDD in remission [MDDr, endpoint 17-item Hamilton Depression Rating Scale (HAMD) total score ≤7] and those in nonremission (MDDnr). The human Brainnetome Atlas was used to define large-scale networks and compute within- and between-network resting-state functional connectivity (rsFC). Results showed the decreased subcortical network (SCN)-ventral attention network (VAN) connectivity at baseline increased in patients with MDD after 12-week treatment, and it was comparable with that of HCs. This change was only observed in patients with MDDr. However, the decreased within-network rsFC in SCN and default mode network (DMN) persisted in all patients with MDD, including those with MDDr and MDDnr, after treatment. The strength of SCN-VAN connectivity at baseline was significantly negatively correlated with the reduction rate of HAMD score in all patients with MDD. Thus, SCN-VAN connectivity may be an antidepressant target associated with depressive state changes and a predictor of treatment response to serotonin reuptake inhibitors. The within-network rsFC in SCN and DMN may reflect a trait-like abnormality in MDD. These findings provide further insights into the mechanism of antidepressants and their individual differences in response. The trial name is "Appropriate technology study of MDD diagnosis and treatment based on objective indicators and measurement" (URL: http://www.chictr.org.cn/showproj.aspx?proj=21377; registration number: ChiCTR-OOC-17012566).
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Affiliation(s)
- Shudong Zhang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Jingjing Zhou
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Jian Cui
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
- Department of Psychiatry, Shandong Daizhuang Hospital, Jining, China
| | - Zhifang Zhang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Rui Liu
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Yuan Feng
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Lei Feng
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Yun Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Xiongying Chen
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Hang Wu
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Yuening Jin
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Yuan Zhou
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Gang Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
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15
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Fu Z, Abbott CC, Sui J, Calhoun VD. Predictive signature of static and dynamic functional connectivity for ECT clinical outcomes. Front Pharmacol 2023; 14:1102413. [PMID: 36755955 PMCID: PMC9899999 DOI: 10.3389/fphar.2023.1102413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 01/11/2023] [Indexed: 01/24/2023] Open
Abstract
Introduction: Electroconvulsive therapy (ECT) remains one of the most effective approaches for treatment-resistant depressive episodes, despite the potential cognitive impairment associated with this treatment. As a potent stimulator of neuroplasticity, ECT might normalize aberrant depression-related brain function via the brain's reconstruction by forming new neural connections. Multiple lines of evidence have demonstrated that functional connectivity (FC) changes are reliable indicators of antidepressant efficacy and cognitive changes from static and dynamic perspectives. However, no previous studies have directly ascertained whether and how different aspects of FC provide complementary information in terms of neuroimaging-based prediction of clinical outcomes. Methods: In this study, we implemented a fully automated independent component analysis framework to an ECT dataset with subjects (n = 50, age = 65.54 ± 8.92) randomized to three treatment amplitudes (600, 700, or 800 milliamperes [mA]). We extracted the static functional network connectivity (sFNC) and dynamic FNC (dFNC) features and employed a partial least square regression to build predictive models for antidepressant outcomes and cognitive changes. Results: We found that both antidepressant outcomes and memory changes can be robustly predicted by the changes in sFNC (permutation test p < 5.0 × 10-3). More interestingly, by adding dFNC information, the model achieved higher accuracy for predicting changes in the Hamilton Depression Rating Scale 24-item (HDRS24, t = 9.6434, p = 1.5 × 10-21). The predictive maps of clinical outcomes show a weakly negative correlation, indicating that the ECT-induced antidepressant outcomes and cognitive changes might be associated with different functional brain neuroplasticity. Discussion: The overall results reveal that dynamic FC is not redundant but reflects mechanisms of ECT that cannot be captured by its static counterpart, especially for the prediction of antidepressant efficacy. Tracking the predictive signatures of static and dynamic FC will help maximize antidepressant outcomes and cognitive safety with individualized ECT dosing.
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Affiliation(s)
- Zening Fu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States,*Correspondence: Christopher C. Abbott, ; Zening Fu,
| | - Christopher C. Abbott
- Department of Psychiatry, University of New Mexico, Albuquerque, NM, United States,*Correspondence: Christopher C. Abbott, ; Zening Fu,
| | - Jing Sui
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States,State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Vince D. Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States,Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States
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16
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Toffanin T, Folesani F, Ferrara M, Belvederi Murri M, Zerbinati L, Caruso R, Nanni MG, Koch G, Fadiga L, Palagini L, Perini G, Benatti B, Dell'Osso B, Grassi L. Cognitive functioning as predictor and marker of response to repetitive transcranial magnetic stimulation in depressive disorders: A systematic review. Gen Hosp Psychiatry 2022; 79:19-32. [PMID: 36240649 DOI: 10.1016/j.genhosppsych.2022.10.001] [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: 05/09/2022] [Revised: 10/04/2022] [Accepted: 10/05/2022] [Indexed: 11/17/2022]
Abstract
OBJECTIVE Cognitive performance in Major Depressive Disorder (MDD) is frequently impaired and related to functional outcomes. Repetitive Transcranial Magnetic Stimulation (rTMS) may exert its effects on MDD acting both on depressive symptoms and neurocognition. Furthermore, cognitive status could predict the therapeutic response of depressive symptoms to rTMS. However, cognitive performances as a predictor of rTMS response in MDD has not been thoroughly investigated. This review aims to evaluate the role of pre-treatment cognitive performance as a predictor of clinical response to rTMS, and the effects of rTMS on neurocognition in MDD. METHOD A systematic review of studies evaluating neurocognition in MDD as an outcome and/or predictor of response to rTMS was conducted using PubMed/Medline and Embase. RESULTS Fifty-eight articles were identified: 25 studies included neurocognition as a predictor of response to rTMS; 56 used cognitive evaluation as an outcome of rTMS. Baseline cognitive performance and cognitive improvements after rTMS predicted clinical response to rTMS. Moreover, rTMS improved cognition in MDD. CONCLUSIONS Cognitive assessment could predict improvement of depression in MDD patients undergoing rTMS and help selecting patients that could have beneficial effects from rTMS. A routine cognitive assessment might stratify MDD patients and track rTMS related cognitive improvement.
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Affiliation(s)
- Tommaso Toffanin
- Department of Neuroscience and Rehabilitation, Institute of Psychiatry, University of Ferrara, Ferrara, Italy
| | - Federica Folesani
- Department of Neuroscience and Rehabilitation, Institute of Psychiatry, University of Ferrara, Ferrara, Italy
| | - Maria Ferrara
- Department of Neuroscience and Rehabilitation, Institute of Psychiatry, University of Ferrara, Ferrara, Italy; Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.
| | - Martino Belvederi Murri
- Department of Neuroscience and Rehabilitation, Institute of Psychiatry, University of Ferrara, Ferrara, Italy
| | - Luigi Zerbinati
- Department of Neuroscience and Rehabilitation, Institute of Psychiatry, University of Ferrara, Ferrara, Italy
| | - Rosangela Caruso
- Department of Neuroscience and Rehabilitation, Institute of Psychiatry, University of Ferrara, Ferrara, Italy
| | - Maria Giulia Nanni
- Department of Neuroscience and Rehabilitation, Institute of Psychiatry, University of Ferrara, Ferrara, Italy
| | - Giacomo Koch
- Department of Neuroscience and Rehabilitation, Institute of Physiology, University of Ferrara, Ferrara, Italy; Center for Translational Neurophysiology of Speech and Communication (CTNSC), Italian Institute of Technology (IIT), Ferrara, Italy
| | - Luciano Fadiga
- Department of Neuroscience and Rehabilitation, Institute of Physiology, University of Ferrara, Ferrara, Italy; Center for Translational Neurophysiology of Speech and Communication (CTNSC), Italian Institute of Technology (IIT), Ferrara, Italy
| | - Laura Palagini
- Department of Neuroscience and Rehabilitation, Institute of Psychiatry, University of Ferrara, Ferrara, Italy
| | - Giulia Perini
- Padova Neuroscience Center, University of Padova, Padova, Italy; Casa di Cura Parco dei Tigli, Padova, Italy
| | - Beatrice Benatti
- Department of Biomedical and Clinical Sciences Luigi Sacco, University of Milan, Milan, Italy
| | - Bernardo Dell'Osso
- Department of Biomedical and Clinical Sciences Luigi Sacco, University of Milan, Milan, Italy
| | - Luigi Grassi
- Department of Neuroscience and Rehabilitation, Institute of Psychiatry, University of Ferrara, Ferrara, Italy
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17
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Kaiser RH, Chase HW, Phillips ML, Deckersbach T, Parsey RV, Fava M, McGrath PJ, Weissman M, Oquendo MA, McInnis MG, Carmody T, Cooper CM, Trivedi MH, Pizzagalli DA. Dynamic Resting-State Network Biomarkers of Antidepressant Treatment Response. Biol Psychiatry 2022; 92:533-542. [PMID: 35680431 PMCID: PMC10640874 DOI: 10.1016/j.biopsych.2022.03.020] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 03/02/2022] [Accepted: 03/23/2022] [Indexed: 12/26/2022]
Abstract
BACKGROUND Delivery of effective antidepressant treatment has been hampered by a lack of objective tools for predicting or monitoring treatment response. This study aimed to address this gap by testing novel dynamic resting-state functional network markers of antidepressant response. METHODS The Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study randomized adults with major depressive disorder to 8 weeks of either sertraline or placebo, and depression severity was evaluated longitudinally. Participants completed resting-state neuroimaging pretreatment and again after 1 week of treatment (n = 259 eligible for analyses). Coactivation pattern analyses identified recurrent whole-brain states of spatial coactivation, and computed time spent in each state for each participant was the main dynamic measure. Multilevel modeling estimated the associations between pretreatment network dynamics and sertraline response and between early (pretreatment to 1 week) changes in network dynamics and sertraline response. RESULTS Dynamic network markers of early sertraline response included increased time in network states consistent with canonical default and salience networks, together with decreased time in network states characterized by coactivation of cingulate and ventral limbic or temporal regions. The effect of sertraline on depression recovery was mediated by these dynamic network changes. In contrast, early changes in dynamic functioning of corticolimbic and frontoinsular-default networks were related to patterns of symptom recovery common across treatment groups. CONCLUSIONS Dynamic resting-state markers of early antidepressant response or general recovery may assist development of clinical tools for monitoring and predicting effective intervention.
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Affiliation(s)
- Roselinde H Kaiser
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado; Institute of Cognitive Science, University of Colorado Boulder, Boulder, Colorado; Renée Crown Wellness Institute, University of Colorado Boulder, Boulder, Colorado.
| | - Henry W Chase
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Mary L Phillips
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Thilo Deckersbach
- Department of Psychiatry, Harvard Medical School and Massachusetts General Hospital, Boston, Massachusetts
| | - Ramin V Parsey
- Department of Psychiatry, Stony Brook University, Stony Brook, New York
| | - Maurizio Fava
- Department of Psychiatry, Harvard Medical School and Massachusetts General Hospital, Boston, Massachusetts
| | - Patrick J McGrath
- Department of Psychiatry, New York State Psychiatric Institute and Columbia University Vagelos College of Physicians and Surgeons, New York, New York
| | - Myrna Weissman
- Department of Psychiatry, New York State Psychiatric Institute and Columbia University Vagelos College of Physicians and Surgeons, New York, New York
| | - Maria A Oquendo
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Melvin G McInnis
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan
| | - Thomas Carmody
- Department of Psychiatry, University of Texas, Southwestern Medical Center, Dallas, Texas
| | - Crystal M Cooper
- Department of Psychiatry, University of Texas, Southwestern Medical Center, Dallas, Texas
| | - Madhukar H Trivedi
- Department of Psychiatry, University of Texas, Southwestern Medical Center, Dallas, Texas
| | - Diego A Pizzagalli
- Department of Psychiatry, Harvard Medical School and McLean Hospital, Boston, Massachusetts
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18
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The Location Reliability of the Resting-State fMRI FC of Emotional Regions Towards rTMS Therapy. Neuroinformatics 2022; 20:1055-1064. [PMID: 35608748 DOI: 10.1007/s12021-022-09585-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/02/2022] [Indexed: 12/31/2022]
Abstract
Resting-state magnetic resonance imaging (RS-fMRI) studies indicated that the repetitive transcranial magnetic stimulation (rTMS) exerts antidepression effect through the functional connectivity (FC) of the DLPFC with the subgenual anterior cingulate cortex (sgACC), pregneual ACC (pgACC), or nucleus accumbens (NAc). It is proposed that the FC-guided individualized precise stimulation on the DLPFC would be more effective. The current study systematically investigated the reliability of the RS-fMRI FC location as well as the FC strength with multiple potential factors. We aimed to provide a stable stimulation target for future FC-guided TMS therapy for affective related disorders. Twenty-one subjects under RS-fMRI conditions with the first two times (V1, V2) scanned on a GE 3 T scanner and the third visit (V3) on a Siemens 3 T scanner. Then the FC strength and location reliability were assessed by using intra-class correlation (ICC) and intra-individual distance, respectively. The factors included deep seed ROIs (midline (mid-) sgACC, left pgACC, mid-pgACC, and left NAc), eyes closed (EC) vs eyes open (EO), frequency bands, FC algorithm (Pearson vs Spearman), scanning length (half a session vs whole session), and location method (FC peak vs center of gravity (COG)). The reliability of the voxel-wise FC strength was low to moderate. The intra-individual distances of the COG were 3.8-7.3 mm across all factors, much smaller than that of FC peak (approximately 30 mm). The COG of seed-based FC might be a potential rTMS stimulation target. Anyway, all potential stimulation targets should be tested in future rTMS treatment studies.
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Caparelli EDC, Abulseoud OA, Gu H, Zhai T, Schleyer B, Yang Y. Low frequency repetitive transcranial magnetic stimulation to the right dorsolateral prefrontal cortex engages thalamus, striatum, and the default mode network. Front Neurosci 2022; 16:997259. [PMID: 36248660 PMCID: PMC9565480 DOI: 10.3389/fnins.2022.997259] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 09/16/2022] [Indexed: 11/25/2022] Open
Abstract
The positive treatment outcomes of low frequency (LF) repetitive transcranial magnetic stimulation (rTMS) when applied over the right dorsolateral prefrontal cortex (DLPFC) in treatment-refractory depression has been verified. However, the mechanism of action behind these results have not been well-explored. In this work we used simultaneous functional magnetic resonance imaging (fMRI) during TMS to explore the effect of LF rTMS on brain activity when applied to the right [RDLPFC1 (MNI: 50, 30, 36)] and left DLPFC sites [LDLPFC1 (MNI: -50, 30, 36), LDLPFC2 (MNI: -41, 16, 54)]. Seventeen healthy adult volunteers participated in this study. To identify brain areas affected by rTMS, an independent component analysis and a general linear model were used. Our results showed an important laterality effect when contrasting rTMS over the left and right sites. Specifically, LF rTMS increased brain activity at the striatum, thalamus, and areas of the default mode network when applied to the right, but not to the contralateral left DLPFC. In contrast, no site differences were observed when evaluating the effect of LF rTMS over the two left sites. These findings demonstrate that LF rTMS to the right DLPFC was able to stimulate the cortico-striato-thalamo-cortical pathway, which is dysregulated in patients with major depressive disorder; therefore, possibly providing some neurobiological justification for the successful outcomes found thus far for LF rTMS in the treatment of depression.
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Affiliation(s)
- Elisabeth de Castro Caparelli
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, United States
- *Correspondence: Elisabeth de Castro Caparelli,
| | - Osama A. Abulseoud
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, United States
- Department of Psychiatry and Psychology, Mayo Clinic, Phoenix, AZ, United States
| | - Hong Gu
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, United States
| | - Tianye Zhai
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, United States
| | - Brooke Schleyer
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, United States
- Department of Psychology, College of Liberal Arts, Temple University, Philadelphia, PA, United States
| | - Yihong Yang
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, United States
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Prediction of remission among patients with a major depressive disorder based on the resting-state functional connectivity of emotion regulation networks. Transl Psychiatry 2022; 12:391. [PMID: 36115833 PMCID: PMC9482642 DOI: 10.1038/s41398-022-02152-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 08/29/2022] [Accepted: 09/02/2022] [Indexed: 11/08/2022] Open
Abstract
The prediction of antidepressant response is critical for psychiatrists to select the initial antidepressant drug for patients with major depressive disorders (MDD). The implicated brain networks supporting emotion regulation (ER) are critical in the pathophysiology of MDD and the prediction of antidepressant response. Therefore, the primary aim of the current study was to identify the neuroimaging biomarkers for the prediction of remission in patients with MDD based on the resting-state functional connectivity (rsFC) of the ER networks. A total of 81 unmedicated adult MDD patients were investigated and they underwent resting-state functional magnetic resonance imagining (fMRI) scans. The patients were treated with escitalopram for 12 weeks. The 17-item Hamilton depression rating scale was used for assessing remission. The 36 seed regions from predefined ER networks were selected and the rsFC matrix was caculated for each participant. The support vector machine algorithm was employed to construct prediction model, which separated the patients with remission from those with non-remission. And leave-one-out cross-validation and the area under the curve (AUC) of the receiver operating characteristic were used for evaluating the performance of the model. The accuracy of the prediction model was 82.08% (sensitivity = 71.43%, specificity = 89.74%, AUC = 0.86). The rsFC between the left medial superior frontal gyrus and the right inferior frontal gyrus as well as the precuneus were the features with the highest discrimination ability in predicting remission from escitalopram among the MDD patients. Results from our study demonstrated that rsFC of the ER brain networks are potential predictors for the response of antidepressant drugs. The trial name: appropriate technology study of MDD diagnosis and treatment based on objective indicators and measurement. URL: http://www.chictr.org.cn/showproj.aspx?proj=21377 . Registration number: ChiCTR-OOC-17012566.
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21
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Transcriptome Profiling of the Dorsomedial Prefrontal Cortex in Suicide Victims. Int J Mol Sci 2022; 23:ijms23137067. [PMID: 35806070 PMCID: PMC9266666 DOI: 10.3390/ijms23137067] [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] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 06/20/2022] [Accepted: 06/23/2022] [Indexed: 01/27/2023] Open
Abstract
The default mode network (DMN) plays an outstanding role in psychiatric disorders. Still, gene expressional changes in its major component, the dorsomedial prefrontal cortex (DMPFC), have not been characterized. We used RNA sequencing in postmortem DMPFC samples to investigate suicide victims compared to control subjects. 1400 genes differed using log2FC > ±1 and adjusted p-value < 0.05 criteria between groups. Genes associated with depressive disorder, schizophrenia and impaired cognition were strongly overexpressed in top differentially expressed genes. Protein−protein interaction and co-expressional networks coupled with gene set enrichment analysis revealed that pathways related to cytokine receptor signaling were enriched in downregulated, while glutamatergic synaptic signaling upregulated genes in suicidal individuals. A validated differentially expressed gene, which is known to be associated with mGluR5, was the N-terminal EF-hand calcium-binding protein 2 (NECAB2). In situ hybridization histochemistry and immunohistochemistry proved that NECAB2 is expressed in two different types of inhibitory neurons located in layers II-IV and VI, respectively. Our results imply extensive gene expressional alterations in the DMPFC related to suicidal behavior. Some of these genes may contribute to the altered mental state and behavior of suicide victims.
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22
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Li C, Hu Q, Zhang D, Hoffstaedter F, Bauer A, Elmenhorst D. Neural correlates of affective control regions induced by common therapeutic strategies in major depressive disorders: An activation likelihood estimation meta-analysis study. Neurosci Biobehav Rev 2022; 137:104643. [PMID: 35367222 DOI: 10.1016/j.neubiorev.2022.104643] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 03/26/2022] [Accepted: 03/27/2022] [Indexed: 01/30/2023]
Abstract
In major depressive disorder (MDD), not only the pathophysiology of this disease is unknown but also the mechanisms of clinical efficacy across its therapeutic strategies are unclear. Although neuroimaging studies adopted activation likelihood estimation (ALE) approach to identify the convergent abnormalities of human brain in the MDD patients, the common alterations after antidepressant therapies were not summarized. Thus, we extracted the coordinates of brain regions in the MDD patients that showed differences in resting-state function, gray matter morphometry, and task-evoked neuronal responses after therapies. The ALE algorithm (GingerALE2.0.3) was employed in all 53 studies (64 experiments with 1406 MDD patients). Consistent results across treatment therapies were reported in the affective control network, including the bilateral thalamus, bilateral amygdala/parahippocampal gyrus, right anterior cingulate cortex/middle frontal gyrus, and right insular cortex/claustrum. Only electroconvulsive therapy partially replicated above findings. Our results indicate the antidepressant therapies efficiently influence core structures of the affective control network, which might be the underlying mechanism of remission in depression and provides potential targets for further treatment strategies.
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Affiliation(s)
- Changhong Li
- College of Teacher Education, Guangdong University of Education, Guangzhou 510303, China; Institute of Neuroscience and Medicine (INM-2), Forschungszentrum Jülich, 52425 Jülich, Germany
| | - Quanling Hu
- School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, China; Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, China
| | - Delong Zhang
- School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, China; Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, China,.
| | - Felix Hoffstaedter
- Institute of Neuroscience and Medicine-7, Juelich Research Center, Juelich, Germany; Institute of Systems Neuroscience, Heinrich Heine University, Duesseldorf, Germany
| | - Andreas Bauer
- Institute of Neuroscience and Medicine (INM-2), Forschungszentrum Jülich, 52425 Jülich, Germany; Department of Neurology, Medical Faculty, Heinrich-Heine-University Düsseldorf, 40225 Düsseldorf, Germany
| | - David Elmenhorst
- Institute of Neuroscience and Medicine (INM-2), Forschungszentrum Jülich, 52425 Jülich, Germany; Rheinische Friedrich-Wilhelms-Universität Bonn, Division of Medical Psychology, Venusberg-Campus 1, 53127 Bonn, North Rhine-Westphalia, Germany; University Hospital Cologne, Multimodal Neuroimaging Group, Department of Nuclear Medicine, Kerpener Strasse 62, 50937 Cologne, North Rhine-Westphalia, Germany.
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23
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Struckmann W, Bodén R, Gingnell M, Fällmar D, Persson J. Modulation of dorsolateral prefrontal cortex functional connectivity after intermittent theta-burst stimulation in depression: Combining findings from fNIRS and fMRI. Neuroimage Clin 2022; 34:103028. [PMID: 35537216 PMCID: PMC9118162 DOI: 10.1016/j.nicl.2022.103028] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 04/04/2022] [Accepted: 04/28/2022] [Indexed: 12/21/2022]
Abstract
BACKGROUND Resting-state functional magnetic resonance imaging (fMRI) can assess modulation of functional connectivity networks following repetitive transcranial magnetic stimulation (rTMS) in the treatment of depression. Functional near-infrared spectroscopy (fNIRS) is well suited for the concurrent application during rTMS treatment sessions to capture immediate blood oxygenation (oxy-Hb) effects, however limited in spatial resolution. OBJECTIVE To understand the network effects behind such a prefrontal fNIRS response during rTMS, and to test whether the fNIRS signal may be predictive of treatment response, we linked data from fNIRS and fMRI within a clinical intervention study. METHODS 42 patients with ongoing depression were recruited and randomized to receive active or sham intermittent theta-burst stimulation (iTBS) over the dorsomedial prefrontal cortex (dmPFC) twice daily for ten days at target intensity. Oxy-Hb was recorded with fNIRS during the first, fifth, and final day of iTBS, with the probe holders located laterally to the TMS coil over regions corresponding to the left and right dorsolateral prefrontal cortex (dlPFC). Resting-state fMRI scanning was performed before and after the whole iTBS treatment course. Functional connectivity analyses were then performed using dlPFC seeds from parcels of a brain atlas showing most overlap with the fNIRS probe locations during treatment. RESULTS After active iTBS, left dlPFC-connectivity to the right insula/operculum was reduced compared to sham. The left insula showed a connectivity reduction to the left dlPFC that correlated with an improvement in symptoms. In addition, the posterior parietal cortex showed a connectivity reduction to the left dlPFC that correlated with the fNIRS signal following active iTBS. Finally, the fNIRS oxy-Hb signal from the left dlPFC-seed during the first treatment day was predictive of dlPFC-connectivity change to precentral and temporal cortex regions. CONCLUSION By linking findings from these two different methods, this study suggests that changes within both the salience network and the central executive network affect the fNIRS response to iTBS.
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Affiliation(s)
- Wiebke Struckmann
- Department of Medical Sciences, Psychiatry, Uppsala University, Sweden.
| | - Robert Bodén
- Department of Medical Sciences, Psychiatry, Uppsala University, Sweden
| | - Malin Gingnell
- Department of Medical Sciences, Psychiatry, Uppsala University, Sweden; Department of Psychology, Uppsala University, Sweden
| | - David Fällmar
- Department of Surgical Sciences, Radiology, Uppsala University, Sweden
| | - Jonas Persson
- Department of Medical Sciences, Psychiatry, Uppsala University, Sweden
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24
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Liu C, Pan W, Zhu D, Meng F, Tian T, Li L, Li X. Factors of suicidal behavior among inpatients with major depressive disorder: A retrospective case series. Front Psychiatry 2022; 13:996402. [PMID: 36213915 PMCID: PMC9537680 DOI: 10.3389/fpsyt.2022.996402] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Accepted: 09/07/2022] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVE Previous studies indicate that more than half of those who died by suicide had a depressive disorder. When discussing the factors associated to suicidal behavior (SB) among patients with major depressive disorder (MDD), sociocultural contexts should also be carefully considered. This case series study explored the factors correlated to SB among MDD patients in Beijing, China. METHODS The patient information sheets were retrieved from an electronic database that comprised patient medical information. Three forms of binary logistic regression equations were conducted to explore the factors associated to SB among patients with MDD. For the inconsistent variables produced by the three regression models, the propensity score matching (PSM) analysis was done for further verification. RESULTS In this retrospective study, 1,091 depressed cases were enrolled. The difference between the SB group and non-SB group in gender, impulsivity, the severity of depression, history of major mental trauma, and family history of suicide were statistically significant in univariate comparisons (P < 0.05); the binary logistic regression analysis and the PSM analysis showed that female gender, history of major mental trauma, impulsivity, family history of suicide and severity of depression were factors correlated to SB among patients with MDD (odds ratios >1). CONCLUSIONS Female gender, the history of major mental trauma, impulsivity, the severity of depression, and family history of suicide were independently associated with the appearance of SB among MDD patients in Beijing, China. Inevitably, these findings should be viewed with particular caution due to the inherent drawbacks of a retrospective nature. More prospective longitudinal research should be conducted to examine those dynamic alterations in the corresponding confounders.
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Affiliation(s)
- Chaomeng Liu
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Weigang Pan
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Dandi Zhu
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Fanqiang Meng
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Tengfei Tian
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Li Li
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Xiaohong Li
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
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25
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Tateishi H, Mizoguchi Y, Monji A. Is the Therapeutic Mechanism of Repetitive Transcranial Magnetic Stimulation in Cognitive Dysfunctions of Depression Related to the Neuroinflammatory Processes in Depression? Front Psychiatry 2022; 13:834425. [PMID: 35280153 PMCID: PMC8907472 DOI: 10.3389/fpsyt.2022.834425] [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: 12/13/2021] [Accepted: 01/28/2022] [Indexed: 12/27/2022] Open
Abstract
The lifetime prevalence of depression is reported to be >10%, and it is an important illness that causes various disabilities over a long period of life. Neuroinflammation process is often reported to be closely linked to the pathophysiology of depression. Approximately one-third of depression is known to be treatment-resistant depression (TRD), in which the symptoms are refractory to adequate treatment. Cognitive dysfunction is one of the most important symptoms of depression that impedes the rehabilitation of patients with depression. Repetitive transcranial magnetic stimulation (rTMS) is a minimally invasive and effective treatment for TRD and is also known to be effective in cognitive dysfunction in depression. Since the details of the therapeutic mechanism of rTMS are still unknown, we have been conducting studies to clarify the therapeutic mechanism of rTMS, especially focusing on cognitive dysfunction in depression. In the present review, we present our latest results and discuss them from the standpoint of the neuroinflammation hypothesis of depression, while citing relevant literature.
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Affiliation(s)
- Hiroshi Tateishi
- Department of Psychiatry, Faculty of Medicine, Saga University, Saga, Japan
| | - Yoshito Mizoguchi
- Department of Psychiatry, Faculty of Medicine, Saga University, Saga, Japan
| | - Akira Monji
- Department of Psychiatry, Faculty of Medicine, Saga University, Saga, Japan
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26
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Pizzagalli DA, Roberts AC. Prefrontal cortex and depression. Neuropsychopharmacology 2022; 47:225-246. [PMID: 34341498 PMCID: PMC8617037 DOI: 10.1038/s41386-021-01101-7] [Citation(s) in RCA: 191] [Impact Index Per Article: 95.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 06/26/2021] [Accepted: 06/28/2021] [Indexed: 01/03/2023]
Abstract
The prefrontal cortex (PFC) has emerged as one of the regions most consistently impaired in major depressive disorder (MDD). Although functional and structural PFC abnormalities have been reported in both individuals with current MDD as well as those at increased vulnerability to MDD, this information has not translated into better treatment and prevention strategies. Here, we argue that dissecting depressive phenotypes into biologically more tractable dimensions - negative processing biases, anhedonia, despair-like behavior (learned helplessness) - affords unique opportunities for integrating clinical findings with mechanistic evidence emerging from preclinical models relevant to depression, and thereby promises to improve our understanding of MDD. To this end, we review and integrate clinical and preclinical literature pertinent to these core phenotypes, while emphasizing a systems-level approach, treatment effects, and whether specific PFC abnormalities are causes or consequences of MDD. In addition, we discuss several key issues linked to cross-species translation, including functional brain homology across species, the importance of dissecting neural pathways underlying specific functional domains that can be fruitfully probed across species, and the experimental approaches that best ensure translatability. Future directions and clinical implications of this burgeoning literature are discussed.
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Affiliation(s)
- Diego A Pizzagalli
- Department of Psychiatry, Harvard Medical School & McLean Hospital, Belmont, MA, USA.
| | - Angela C Roberts
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.
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27
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Demchenko I, Tassone VK, Kennedy SH, Dunlop K, Bhat V. Intrinsic Connectivity Networks of Glutamate-Mediated Antidepressant Response: A Neuroimaging Review. Front Psychiatry 2022; 13:864902. [PMID: 35722550 PMCID: PMC9199367 DOI: 10.3389/fpsyt.2022.864902] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Accepted: 04/12/2022] [Indexed: 11/23/2022] Open
Abstract
Conventional monoamine-based pharmacotherapy, considered the first-line treatment for major depressive disorder (MDD), has several challenges, including high rates of non-response. To address these challenges, preclinical and clinical studies have sought to characterize antidepressant response through monoamine-independent mechanisms. One striking example is glutamate, the brain's foremost excitatory neurotransmitter: since the 1990s, studies have consistently reported altered levels of glutamate in MDD, as well as antidepressant effects following molecular targeting of glutamatergic receptors. Therapeutically, this has led to advances in the discovery, testing, and clinical application of a wide array of glutamatergic agents, particularly ketamine. Notably, ketamine has been demonstrated to rapidly improve mood symptoms, unlike monoamine-based interventions, and the neurobiological basis behind this rapid antidepressant response is under active investigation. Advances in brain imaging techniques, including functional magnetic resonance imaging, magnetic resonance spectroscopy, and positron emission tomography, enable the identification of the brain network-based characteristics distinguishing rapid glutamatergic modulation from the effect of slow-acting conventional monoamine-based pharmacology. Here, we review brain imaging studies that examine brain connectivity features associated with rapid antidepressant response in MDD patients treated with glutamatergic pharmacotherapies in contrast with patients treated with slow-acting monoamine-based treatments. Trends in recent brain imaging literature suggest that the activity of brain regions is organized into coherent functionally distinct networks, termed intrinsic connectivity networks (ICNs). We provide an overview of major ICNs implicated in depression and explore how treatment response following glutamatergic modulation alters functional connectivity of limbic, cognitive, and executive nodes within ICNs, with well-characterized anti-anhedonic effects and the enhancement of "top-down" executive control. Alterations within and between the core ICNs could potentially exert downstream effects on the nodes within other brain networks of relevance to MDD that are structurally and functionally interconnected through glutamatergic synapses. Understanding similarities and differences in brain ICNs features underlying treatment response will positively impact the trajectory and outcomes for adults suffering from MDD and will facilitate the development of biomarkers to enable glutamate-based precision therapeutics.
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Affiliation(s)
- Ilya Demchenko
- Interventional Psychiatry Program, Mental Health and Addictions Service, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Center for Depression and Suicide Studies, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - Vanessa K Tassone
- Interventional Psychiatry Program, Mental Health and Addictions Service, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - Sidney H Kennedy
- Interventional Psychiatry Program, Mental Health and Addictions Service, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Center for Depression and Suicide Studies, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Keenan Research Center for Biomedical Science, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Katharine Dunlop
- Interventional Psychiatry Program, Mental Health and Addictions Service, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Center for Depression and Suicide Studies, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Keenan Research Center for Biomedical Science, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Venkat Bhat
- Interventional Psychiatry Program, Mental Health and Addictions Service, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Center for Depression and Suicide Studies, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Keenan Research Center for Biomedical Science, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
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28
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Kuburi S, Di Passa AM, Tassone VK, Mahmood R, Lalovic A, Ladha KS, Dunlop K, Rizvi S, Demchenko I, Bhat V. Neuroimaging Correlates of Treatment Response with Psychedelics in Major Depressive Disorder: A Systematic Review. CHRONIC STRESS 2022; 6:24705470221115342. [PMID: 35936944 PMCID: PMC9350516 DOI: 10.1177/24705470221115342] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 07/07/2022] [Indexed: 12/03/2022]
Abstract
Preliminary evidence supports the use of psychedelics for major depressive
disorder (MDD). However, less attention has been given to the neural mechanisms
behind their effects. We conducted a systematic review examining the
neuroimaging correlates of antidepressant response following psychedelic
interventions for MDD. Through MEDLINE, Embase, and APA PsycINFO, 187 records
were identified and 42 articles were screened. Six published studies and one
conference abstract were included. Five ongoing trials were included from
subjective outcomesTrials.gov. Our search covered several psychedelics, though
included studies were specific to psilocybin, ayahuasca, and lysergic acid
diethylamide. Three psilocybin studies noted amygdala activity and functional
connectivity (FC) alterations that correlated with treatment response. Two
psilocybin studies reported that FC changes in the medial and ventromedial
prefrontal cortices correlated with treatment response. Two trials from a single
study reported global decreases in brain network modularity which correlated
with antidepressant response. One ayahuasca study reported increased activity in
the limbic regions following treatment. Preliminary evidence suggests that the
default mode and limbic networks may be a target for future research on the
neural mechanisms of psychedelics. More data is required to corroborate these
initial findings as the evidence summarized in this review is based on four
datasets.
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Affiliation(s)
- Sarah Kuburi
- Interventional Psychiatry Program, Mental Health and Addictions Service, St. Michael’s Hospital, 193 Yonge Street 6-013, M5B 1M8, Toronto, Ontario, Canada
| | - Anne-Marie Di Passa
- Interventional Psychiatry Program, Mental Health and Addictions Service, St. Michael’s Hospital, 193 Yonge Street 6-013, M5B 1M8, Toronto, Ontario, Canada
| | - Vanessa K. Tassone
- Interventional Psychiatry Program, Mental Health and Addictions Service, St. Michael’s Hospital, 193 Yonge Street 6-013, M5B 1M8, Toronto, Ontario, Canada
| | - Raesham Mahmood
- Institute of Medical Science, Faculty of Medicine, University of Toronto, 1 King's College Circle, Medical Sciences Building, M5S 1A8, Toronto, Ontario, Canada
| | - Aleksandra Lalovic
- Department of Psychiatry, Faculty of Medicine, University of Toronto, 250 College Street, M5T 1R8, Toronto, Ontario, Canada
- Li Ka Shing Knowledge Institute, St. Michael’s Hospital, 209 Victoria Street, M5B 1T8, Toronto, Ontario, Canada
| | - Karim S. Ladha
- Li Ka Shing Knowledge Institute, St. Michael’s Hospital, 209 Victoria Street, M5B 1T8, Toronto, Ontario, Canada
- Department of Anesthesiology and Pain Medicine, University of Toronto, 250 College Street, M5T 1R8, Toronto, Ontario, Canada
- Department of Anesthesia, St. Michael's Hospital, 193 Yonge Street 6-013, M5B 1M8, Toronto, Ontario, Canada
| | - Katharine Dunlop
- Interventional Psychiatry Program, Mental Health and Addictions Service, St. Michael’s Hospital, 193 Yonge Street 6-013, M5B 1M8, Toronto, Ontario, Canada
- Department of Psychiatry, Faculty of Medicine, University of Toronto, 250 College Street, M5T 1R8, Toronto, Ontario, Canada
- Center for Depression and Suicide Studies, St. Michael’s Hospital, Unity Health Toronto, 30 Bond Street, M5B 1W8, Toronto, ON, Canada
- Keenan Research Center for Biomedical Science, St. Michael’s Hospital, Unity Health Toronto, 30 Bond Street, M5B 1W8, Toronto, Ontario, Canada
| | - Sakina Rizvi
- Department of Psychiatry, Faculty of Medicine, University of Toronto, 250 College Street, M5T 1R8, Toronto, Ontario, Canada
- Li Ka Shing Knowledge Institute, St. Michael’s Hospital, 209 Victoria Street, M5B 1T8, Toronto, Ontario, Canada
| | - Ilya Demchenko
- Interventional Psychiatry Program, Mental Health and Addictions Service, St. Michael’s Hospital, 193 Yonge Street 6-013, M5B 1M8, Toronto, Ontario, Canada
| | - Venkat Bhat
- Interventional Psychiatry Program, Mental Health and Addictions Service, St. Michael’s Hospital, 193 Yonge Street 6-013, M5B 1M8, Toronto, Ontario, Canada
- Institute of Medical Science, Faculty of Medicine, University of Toronto, 1 King's College Circle, Medical Sciences Building, M5S 1A8, Toronto, Ontario, Canada
- Department of Psychiatry, Faculty of Medicine, University of Toronto, 250 College Street, M5T 1R8, Toronto, Ontario, Canada
- Li Ka Shing Knowledge Institute, St. Michael’s Hospital, 209 Victoria Street, M5B 1T8, Toronto, Ontario, Canada
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29
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Zhang M, Wang R, Luo X, Zhang S, Zhong X, Ning Y, Zhang B. Repetitive Transcranial Magnetic Stimulation Target Location Methods for Depression. Front Neurosci 2021; 15:695423. [PMID: 34566561 PMCID: PMC8458642 DOI: 10.3389/fnins.2021.695423] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 08/03/2021] [Indexed: 01/18/2023] Open
Abstract
Major depressive disorder (MDD) is a substantial global public health problem in need of novel and effective treatment strategies. Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive and promising treatment for depression that has been approved by the U.S. Food and Drug Administration (FDA). However, the methodological weaknesses of existing work impairs the universal clinical use of rTMS. The variation of stimulated targets across the dorsolateral prefrontal cortex may account for most of the heterogeneity in the efficacy of rTMS. Many rTMS target location methods for MDD have been developed in recent decades. This review was conducted to assess this emerging field and to improve treatment outcomes in clinical practice.
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Affiliation(s)
- Min Zhang
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Runhua Wang
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xin Luo
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Si Zhang
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xiaomei Zhong
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yuping Ning
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China.,The First School of Clinical Medicine, Southern Medical University, Guangzhou, China.,Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Bin Zhang
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
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30
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Alteration of regional heterogeneity and functional connectivity for obese undergraduates: evidence from resting-state fMRI. Brain Imaging Behav 2021; 16:627-636. [PMID: 34487278 DOI: 10.1007/s11682-021-00542-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/09/2021] [Indexed: 10/20/2022]
Abstract
Obesity was found to be related with the changes of brain functions in human beings. There were several brain areas that were verified to be correlated with the obesity, including the parietal cortex, frontal cortex and so on. However, the cortical regions found from different studies were discrepant due to the different ages, gender distribution and satiation degree of participants. We found that the regional homogeneity of right angular gyrus were smaller in obese undergraduates than that in normal-weight undergraduates. Moreover, functional connectivity of the left middle temporal cortex and the right angular gyrus were found to be smaller in obese group than that in normal-weight group by setting the right angular gyrus as seed region. In addition, multiple regression analysis suggested that the right superior frontal gyrus and left middle temporal gyrus were significantly correlated with their body mass index for normal-weight undergraduates, but no significant correlation was found for obese group. In summary, these findings indicated the functional changes of the cortex in obese undergraduates, which might be significant for providing imaging-based biomarkers for intervention and therapy of obesity.
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31
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Zhu Z, Hubbard E, Guo X, Barbosa DAN, Popal AM, Cai C, Jiang H, Zheng Z, Lin J, Gao W, Zhang J, Bartas K, Macchia D, Derdeyn P, Halpern CH, Mayberg HS, Beier KT, Zhu J, Wu H. A connectomic analysis of deep brain stimulation for treatment-resistant depression. Brain Stimul 2021; 14:1226-1233. [PMID: 34400379 DOI: 10.1016/j.brs.2021.08.010] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 08/11/2021] [Accepted: 08/11/2021] [Indexed: 11/17/2022] Open
Abstract
OBJECTIVE Deep brain stimulation (DBS) has been used as a treatment of last resort for treatment-resistant depression (TRD) for more than a decade. Many DBS targets have been proposed and tested clinically, but the underlying circuit mechanisms remain unclear. Uncovering white matter tracts (WMT) activated by DBS targets may provide crucial information about the circuit substrates mediating DBS efficacy in ameliorating TRD. METHODS We performed probabilistic tractography using diffusion magnetic resonance imaging datas from 100 healthy volunteers in Human Connectome Project datasets to analyze the structural connectivity patterns of stimulation targeting currently-used DBS target for TRD. We generated mean and binary fiber distribution maps and calculated the numbers of WMT streamlines in the dataset. RESULTS Probabilistic tracking results revealed that activation of distinct DBS targets demonstrated modulation of overlapping but considerably distinct pathways. DBS targets were categorized into 4 groups: Cortical, Striatal, Thalamic, and Medial Forebrain Bundle according to their main modulated WMT and brain areas. Our data also revealed that Brodmann area 10 and amygdala are hub structures that are associated with all DBS targets. CONCLUSIONS Our results together suggest that the distinct mechanism of DBS targets implies individualized target selection and formulation in the future of DBS treatment for TRD. The modulation of Brodmann area 10 and amygdala may be critical for the efficacy of DBS-mediated treatment of TRD.
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Affiliation(s)
- Zhoule Zhu
- Department of Neurosurgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, 310009, China
| | - Elizabeth Hubbard
- Department of Physiology and Biophysics, University of California, Irvine, CA, 92697-4560, USA
| | - Xinxia Guo
- Department of Neurosurgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, 310009, China
| | - Daniel A N Barbosa
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Abdul Malik Popal
- Department of Neurosurgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, 310009, China
| | - Chengwei Cai
- Department of Neurosurgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, 310009, China
| | - Hongjie Jiang
- Department of Neurosurgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, 310009, China
| | - Zhe Zheng
- Department of Neurosurgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, 310009, China
| | - Jingquan Lin
- Department of Neurosurgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, 310009, China
| | - Wei Gao
- Department of Neurosurgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, 310009, China
| | - Jianmin Zhang
- Department of Neurosurgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, 310009, China
| | - Katrina Bartas
- Program in Mathematical, Computational, and Systems Biology, University of California, Irvine, CA, 92697-4560, USA
| | - Desiree Macchia
- Department of Physiology and Biophysics, University of California, Irvine, CA, 92697-4560, USA
| | - Pieter Derdeyn
- Program in Mathematical, Computational, and Systems Biology, University of California, Irvine, CA, 92697-4560, USA
| | - Casey H Halpern
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Helen S Mayberg
- Departments of Neurology and Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Kevin T Beier
- Department of Physiology and Biophysics, University of California, Irvine, CA, 92697-4560, USA; Department of Neurobiology and Behavior, University of California, Irvine, CA, 92697-4560, USA; Department of Biomedical Engineering, University of California, Irvine, CA, 92697-4560, USA; Department of Pharmaceutical Sciences, University of California, Irvine, CA, 92697-4560, USA; Center for the Neurobiology of Learning and Memory, University of California, Irvine, CA, 92697, USA.
| | - Junming Zhu
- Department of Neurosurgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, 310009, China.
| | - Hemmings Wu
- Department of Neurosurgery, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, 310009, China.
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32
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van der Wijk G, Harris JK, Hassel S, Davis AD, Zamyadi M, Arnott SR, Milev R, Lam RW, Frey BN, Hall GB, Müller DJ, Rotzinger S, Kennedy SH, Strother SC, MacQueen GM, Protzner AB. Baseline Functional Connectivity in Resting State Networks Associated with Depression and Remission Status after 16 Weeks of Pharmacotherapy: A CAN-BIND Report. Cereb Cortex 2021; 32:1223-1243. [PMID: 34416758 DOI: 10.1093/cercor/bhab286] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 07/19/2021] [Accepted: 07/20/2021] [Indexed: 02/07/2023] Open
Abstract
Understanding the neural underpinnings of major depressive disorder (MDD) and its treatment could improve treatment outcomes. So far, findings are variable and large sample replications scarce. We aimed to replicate and extend altered functional connectivity associated with MDD and pharmacotherapy outcomes in a large, multisite sample. Resting-state fMRI data were collected from 129 patients and 99 controls through the Canadian Biomarker Integration Network in Depression. Symptoms were assessed with the Montgomery-Åsberg Depression Rating Scale (MADRS). Connectivity was measured as correlations between four seeds (anterior and posterior cingulate cortex, insula and dorsolateral prefrontal cortex) and all other brain voxels. Partial least squares was used to compare connectivity prior to treatment between patients and controls, and between patients reaching remission (MADRS ≤ 10) early (within 8 weeks), late (within 16 weeks), or not at all. We replicated previous findings of altered connectivity in patients. In addition, baseline connectivity of the anterior/posterior cingulate and insula seeds differentiated patients with different treatment outcomes. The stability of these differences was established in the largest single-site subsample. Our replication and extension of altered connectivity highlighted previously reported and new differences between patients and controls, and revealed features that might predict remission prior to pharmacotherapy. Trial registration: ClinicalTrials.gov: NCT01655706.
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Affiliation(s)
- Gwen van der Wijk
- Department of Psychology, University of Calgary, Calgary AB T2N 1N4, Canada
| | - Jacqueline K Harris
- Department of Computing Science, University of Alberta, Edmonton AB T6G 2S4, Canada.,Alberta Machine Intelligence Institute, Edmonton AB T5J 3B1, Canada
| | - Stefanie Hassel
- Cumming School of Medicine, Department of Psychiatry, University of Calgary, Calgary AB T2N 4N1, Canada.,Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary AB T2N 4Z6, Canada
| | - Andrew D Davis
- Rotman Research Institute, Baycrest Health Sciences, Toronto ON M6A 2E1, Canada.,Department of Psychology, Neuroscience & Behaviour, McMaster University, Hamilton ON L8S 4L6, Canada
| | - Mojdeh Zamyadi
- Rotman Research Institute, Baycrest Health Sciences, Toronto ON M6A 2E1, Canada
| | - Stephen R Arnott
- Rotman Research Institute, Baycrest Health Sciences, Toronto ON M6A 2E1, Canada
| | - Roumen Milev
- Queen's University, Departments of Psychiatry and Psychology, and Providence Care Hospital, Kingston ON K7L 3N6, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver BC V6T 2A1, Canada
| | - Benicio N Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton ON L8S 4L8, Canada.,Mood Disorders Program and Women's Health Concerns Clinic, St. Joseph's Healthcare, Hamilton ON L8N 4N6, Canada
| | - Geoffrey B Hall
- Department of Psychology, Neuroscience & Behaviour, McMaster University, Hamilton ON L8S 4L6, Canada.,Imaging Research Centre, St. Joseph's Healthcare Hamilton, Hamilton ON L8N 4N6, Canada
| | - Daniel J Müller
- Department of Psychiatry, University of Toronto, Toronto ON M5T 1R8, Canada.,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto ON M5T 1R8, Canada.,Department of Pharmacology and Toxicology, University of Toronto, Toronto ON M5S 1A8, Canada.,Institute of Medical Sciences, University of Toronto, Toronto ON M5S 1A8, Canada
| | - Susan Rotzinger
- Centre for Mental Health, University Health Network, Toronto ON M5G 1L7, Canada.,Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto ON M5B 1T8, Canada
| | - Sidney H Kennedy
- Department of Psychiatry, University of Toronto, Toronto ON M5T 1R8, Canada.,Institute of Medical Sciences, University of Toronto, Toronto ON M5S 1A8, Canada.,Centre for Mental Health, University Health Network, Toronto ON M5G 1L7, Canada.,Centre for Depression and Suicide Studies, Unity Health Toronto, Toronto ON M5B 1W8, Canada.,Krembil Research Institute, Toronto Western Hospital, Toronto ON M5T 0S8, Canada
| | - Stephen C Strother
- Rotman Research Institute, Baycrest Health Sciences, Toronto ON M6A 2E1, Canada.,Department of Medical Biophysics, University of Toronto, Toronto ON M5G 1L7, Canada
| | - Glenda M MacQueen
- Cumming School of Medicine, Department of Psychiatry, University of Calgary, Calgary AB T2N 4N1, Canada.,Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary AB T2N 4Z6, Canada
| | - Andrea B Protzner
- Department of Psychology, University of Calgary, Calgary AB T2N 1N4, Canada.,Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary AB T2N 4Z6, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary AB T2N 4N1, Canada
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Padberg F, Bulubas L, Mizutani-Tiebel Y, Burkhardt G, Kranz GS, Koutsouleris N, Kambeitz J, Hasan A, Takahashi S, Keeser D, Goerigk S, Brunoni AR. The intervention, the patient and the illness - Personalizing non-invasive brain stimulation in psychiatry. Exp Neurol 2021; 341:113713. [PMID: 33798562 DOI: 10.1016/j.expneurol.2021.113713] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 03/09/2021] [Accepted: 03/28/2021] [Indexed: 02/08/2023]
Abstract
Current hypotheses on the therapeutic action of non-invasive brain stimulation (NIBS) in psychiatric disorders build on the abundant data from neuroimaging studies. This makes NIBS a very promising tool for developing personalized interventions within a precision medicine framework. NIBS methods fundamentally vary in their neurophysiological properties. They comprise repetitive transcranial magnetic stimulation (rTMS) and its variants (e.g. theta burst stimulation - TBS) as well as different types of transcranial electrical stimulation (tES), with the largest body of evidence for transcranial direct current stimulation (tDCS). In the last two decades, significant conceptual progress has been made in terms of NIBS targets, i.e. from single brain regions to neural circuits and to functional connectivity as well as their states, recently leading to brain state modulating closed-loop approaches. Regarding structural and functional brain anatomy, NIBS meets an individually unique constellation, which varies across normal and pathophysiological states. Thus, individual constitutions and signatures of disorders may be indistinguishable at a given time point, but can theoretically be parsed along course- and treatment-related trajectories. We address precision interventions on three levels: 1) the NIBS intervention, 2) the constitutional factors of a single patient, and 3) the phenotypes and pathophysiology of illness. With examples from research on depressive disorders, we propose solutions and discuss future perspectives, e.g. individual MRI-based electrical field strength as a proxy for NIBS dosage, and also symptoms, their clusters, or biotypes instead of disorder focused NIBS. In conclusion, we propose interleaved research on these three levels along a general track of reverse and forward translation including both clinically directed research in preclinical model systems, and biomarker guided controlled clinical trials. Besides driving the development of safe and efficacious interventions, this framework could also deepen our understanding of psychiatric disorders at their neurophysiological underpinnings.
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Affiliation(s)
- Frank Padberg
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Germany; Center for Non-invasive Brain Stimulation Munich-Augsburg (CNBS(MA)), Germany
| | - Lucia Bulubas
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Germany; Center for Non-invasive Brain Stimulation Munich-Augsburg (CNBS(MA)), Germany; International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, Germany
| | - Yuki Mizutani-Tiebel
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Germany; Center for Non-invasive Brain Stimulation Munich-Augsburg (CNBS(MA)), Germany
| | - Gerrit Burkhardt
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Germany; Center for Non-invasive Brain Stimulation Munich-Augsburg (CNBS(MA)), Germany
| | - Georg S Kranz
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, SAR, China; Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Germany; Max-Planck Institute of Psychiatry, Munich, Germany
| | - Joseph Kambeitz
- Department of Psychiatry, University of Cologne, Faculty of Medicine and University Hospital Cologne, 50937, Germany
| | - Alkomiet Hasan
- Center for Non-invasive Brain Stimulation Munich-Augsburg (CNBS(MA)), Germany; Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, University of Augsburg, BKH Augsburg, Dr.-Mack-Str. 1, 86156 Augsburg, Germany; Department of Clinical Radiology, LMU Hospital, Munich, Germany
| | - Shun Takahashi
- Department of Neuropsychiatry, Wakayama Medical University, 811-1 Kimiidera, 6410012 Wakayama, Japan
| | - Daniel Keeser
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Germany; Center for Non-invasive Brain Stimulation Munich-Augsburg (CNBS(MA)), Germany
| | - Stephan Goerigk
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Germany; Center for Non-invasive Brain Stimulation Munich-Augsburg (CNBS(MA)), Germany; Department of Psychological Methodology and Assessment, Ludwig-Maximilians-University, Leopoldstraße 13, 80802 Munich, Germany; Hochschule Fresenius, University of Applied Sciences, Infanteriestraße 11A, 80797 Munich, Germany
| | - Andre R Brunoni
- Laboratory of Neurosciences (LIM-27), Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBioN), Department and Institute of Psychiatry, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil; Department of Internal Medicine, Faculdade de Medicina da Universidade de São Paulo & Hospital Universitário, Universidade de São Paulo, Av. Prof Lineu Prestes 2565, 05508-000 São Paulo, Brazil
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34
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Nakamura T, Tomita M, Horikawa N, Ishibashi M, Uematsu K, Hiraki T, Abe T, Uchimura N. Functional connectivity between the amygdala and subgenual cingulate gyrus predicts the antidepressant effects of ketamine in patients with treatment-resistant depression. Neuropsychopharmacol Rep 2021; 41:168-178. [PMID: 33615749 PMCID: PMC8340826 DOI: 10.1002/npr2.12165] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 01/21/2021] [Accepted: 01/23/2021] [Indexed: 12/28/2022] Open
Abstract
Aim Approximately one‐third of patients with major depressive disorder develop treatment‐resistant depression. One‐third of patients with treatment‐resistant depression demonstrate resistance to ketamine, which is a novel antidepressant effective for this disorder. The objective of this study was to examine the utility of resting‐state functional magnetic resonance imaging for the prediction of treatment response to ketamine in treatment‐resistant depression. Methods An exploratory seed‐based resting‐state functional magnetic resonance imaging analysis was performed to examine baseline resting‐state functional connectivity differences between ketamine responders and nonresponders before treatment with multiple intravenous ketamine infusions. Results Fifteen patients with treatment‐resistant depression received multiple intravenous subanesthetic (0.5 mg/kg/40 minutes) ketamine infusions, and nine were identified as responders. The exploratory resting‐state functional magnetic resonance imaging analysis identified a cluster of significant baseline resting‐state functional connectivity differences associating ketamine response between the amygdala and subgenual anterior cingulate gyrus in the right hemisphere. Using anatomical region of interest analysis of the resting‐state functional connectivity, ketamine response was predicted with 88.9% sensitivity and 100% specificity. The resting‐state functional connectivity of significant group differences between responders and nonresponders retained throughout the treatment were considered a trait‐like feature of heterogeneity in treatment‐resistant depression. Conclusion This study suggests the possible clinical utility of resting‐state functional magnetic resonance imaging for predicting the antidepressant effects of ketamine in treatment‐resistant depression patients and implicated resting‐state functional connectivity alterations to determine the trait‐like pathophysiology underlying treatment response heterogeneity in treatment‐resistant depression. This study illustrates that the alteration in the RSFC within the right AN in TRD patients reflects the antidepressant response to ketamine at baseline. The alteration remained throughout the 2‐week treatment with multiple ketamine infusions and seemed to reflect the trait‐like features underlying treatment heterogeneity in TRD. By employing an anatomical ROI of the sc/sgACC, the present study also suggests the possible clinical utility of the rsfMRI to predict the treatment response to ketamine in TRD patients.
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Affiliation(s)
- Tomoyuki Nakamura
- Department of Neuropsychiatry, Kurume University School of Medicine, Kurume City, Japan
| | - Masaru Tomita
- Department of Neuropsychiatry, Kurume University School of Medicine, Kurume City, Japan.,Elm-tree Mental Clinic, Ogori City, Japan
| | - Naoki Horikawa
- Department of Neuropsychiatry, Kurume University School of Medicine, Kurume City, Japan.,Nozoe Hills Hospital, Kurume City, Japan
| | - Masatoshi Ishibashi
- Department of Neuropsychiatry, Kurume University School of Medicine, Kurume City, Japan
| | - Ken Uematsu
- Uematsu Mental Clinic, Chikugo City, Japan.,Department of Pharmacology, Kurume University School of Medicine, Kurume City, Japan
| | - Teruyuki Hiraki
- Department of Anaesthesiology, Kurume University School of Medicine, Kurume City, Japan
| | - Toshi Abe
- Department of Radiology, Kurume University School of Medicine, Kurume City, Japan
| | - Naohisa Uchimura
- Department of Neuropsychiatry, Kurume University School of Medicine, Kurume City, Japan
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35
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Li Z, Ruan M, Chen J, Fang Y. Major Depressive Disorder: Advances in Neuroscience Research and Translational Applications. Neurosci Bull 2021; 37:863-880. [PMID: 33582959 PMCID: PMC8192601 DOI: 10.1007/s12264-021-00638-3] [Citation(s) in RCA: 105] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2020] [Accepted: 09/30/2020] [Indexed: 02/07/2023] Open
Abstract
Major depressive disorder (MDD), also referred to as depression, is one of the most common psychiatric disorders with a high economic burden. The etiology of depression is still not clear, but it is generally believed that MDD is a multifactorial disease caused by the interaction of social, psychological, and biological aspects. Therefore, there is no exact pathological theory that can independently explain its pathogenesis, involving genetics, neurobiology, and neuroimaging. At present, there are many treatment measures for patients with depression, including drug therapy, psychotherapy, and neuromodulation technology. In recent years, great progress has been made in the development of new antidepressants, some of which have been applied in the clinic. This article mainly reviews the research progress, pathogenesis, and treatment of MDD.
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Affiliation(s)
- Zezhi Li
- Clinical Research Center and Division of Mood Disorders of Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.,Department of Neurology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China
| | - Meihua Ruan
- Shanghai Institute of Nutrition and Health, Shanghai Information Center for Life Sciences, Chinese Academy of Science, Shanghai, 200031, China
| | - Jun Chen
- Clinical Research Center and Division of Mood Disorders of Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.,Shanghai Key Laboratory of Psychotic Disorders, Shanghai, 201108, China
| | - Yiru Fang
- Clinical Research Center and Division of Mood Disorders of Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China. .,Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Science, Shanghai, 200031, China. .,Shanghai Key Laboratory of Psychotic Disorders, Shanghai, 201108, China.
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36
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Sinha P, Joshi H, Ithal D. Resting State Functional Connectivity of Brain With Electroconvulsive Therapy in Depression: Meta-Analysis to Understand Its Mechanisms. Front Hum Neurosci 2021; 14:616054. [PMID: 33551779 PMCID: PMC7859100 DOI: 10.3389/fnhum.2020.616054] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Accepted: 12/15/2020] [Indexed: 12/25/2022] Open
Abstract
Introduction: Electroconvulsive therapy (ECT) is a commonly used brain stimulation treatment for treatment-resistant or severe depression. This study was planned to find the effects of ECT on brain connectivity by conducting a systematic review and coordinate-based meta-analysis of the studies performing resting state fMRI (rsfMRI) in patients with depression receiving ECT. Methods: We systematically searched the databases published up to July 31, 2020, for studies in patients having depression that compared resting-state functional connectivity (rsFC) before and after a course of pulse wave ECT. Meta-analysis was performed using the activation likelihood estimation method after extracting details about coordinates, voxel size, and method for correction of multiple comparisons corresponding to the significant clusters and the respective rsFC analysis measure with its method of extraction. Results: Among 41 articles selected for full-text review, 31 articles were included in the systematic review. Among them, 13 articles were included in the meta-analysis, and a total of 73 foci of 21 experiments were examined using activation likelihood estimation in 10 sets. Using the cluster-level interference method, one voxel-wise analysis with the measure of amplitude of low frequency fluctuations and one seed-voxel analysis with the right hippocampus showed a significant reduction (p < 0.0001) in the left cingulate gyrus (dorsal anterior cingulate cortex) and a significant increase (p < 0.0001) in the right hippocampus with the right parahippocampal gyrus, respectively. Another analysis with the studies implementing network-wise (posterior default mode network: dorsomedial prefrontal cortex) resting state functional connectivity showed a significant increase (p < 0.001) in bilateral posterior cingulate cortex. There was considerable variability as well as a few key deficits in the preprocessing and analysis of the neuroimages and the reporting of results in the included studies. Due to lesser studies, we could not do further analysis to address the neuroimaging variability and subject-related differences. Conclusion: The brain regions noted in this meta-analysis are reasonably specific and distinguished, and they had significant changes in resting state functional connectivity after a course of ECT for depression. More studies with better neuroimaging standards should be conducted in the future to confirm these results in different subgroups of depression and with varied aspects of ECT.
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Affiliation(s)
- Preeti Sinha
- ECT Services, Noninvasive Brain Stimulation (NIBS) Team, Department of Psychiatry, Bengaluru, India.,Geriatric Clinic and Services, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Himanshu Joshi
- Geriatric Clinic and Services, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India.,Multimodal Brain Image Analysis Laboratory, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Dhruva Ithal
- ECT Services, Noninvasive Brain Stimulation (NIBS) Team, Department of Psychiatry, Bengaluru, India.,Accelerated Program for Discovery in Brain Disorders, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
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