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Armio RL, Laurikainen H, Ilonen T, Walta M, Sormunen E, Tolvanen A, Salokangas RKR, Koutsouleris N, Tuominen L, Hietala J. Longitudinal study on hippocampal subfields and glucose metabolism in early psychosis. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2024; 10:66. [PMID: 39085221 PMCID: PMC11291638 DOI: 10.1038/s41537-024-00475-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 05/11/2024] [Indexed: 08/02/2024]
Abstract
Altered hippocampal morphology and metabolic pathology, but also hippocampal circuit dysfunction, are established phenomena seen in psychotic disorders. Thus, we tested whether hippocampal subfield volume deficits link with deviations in glucose metabolism commonly seen in early psychosis, and whether the glucose parameters or subfield volumes change during follow-up period using one-year longitudinal study design of 78 first-episode psychosis patients (FEP), 48 clinical high-risk patients (CHR) and 83 controls (CTR). We also tested whether hippocampal morphology and glucose metabolism relate to clinical outcome. Hippocampus subfields were segmented with Freesurfer from 3T MRI images and parameters of glucose metabolism were determined in fasting plasma samples. Hippocampal subfield volumes were consistently lower in FEPs, and findings were more robust in non-affective psychoses, with strongest decreases in CA1, molecular layer and hippocampal tail, and in hippocampal tail of CHRs, compared to CTRs. These morphometric differences remained stable at one-year follow-up. Both non-diabetic CHRs and FEPs had worse glucose parameters compared to CTRs at baseline. We found that, insulin levels and insulin resistance increased during the follow-up period only in CHR, effect being largest in the CHRs converting to psychosis, independent of exposure to antipsychotics. The worsening of insulin resistance was associated with deterioration of function and symptoms in CHR. The smaller volume of hippocampal tail was associated with higher plasma insulin and insulin resistance in FEPs, at the one-year follow-up. Our longitudinal study supports the view that temporospatial hippocampal subfield volume deficits are stable near the onset of first psychosis, being more robust in non-affective psychoses, but less prominent in the CHR group. Specific subfield defects were related to worsening glucose metabolism during the progression of psychosis, suggesting that hippocampus is part of the circuits regulating aberrant glucose metabolism in early psychosis. Worsening of glucose metabolism in CHR group was associated with worse clinical outcome measures indicating a need for heightened clinical attention to metabolic problems already in CHR.
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Grants
- Turun Yliopistollisen Keskussairaalan Koulutus- ja Tutkimussäätiö (TYKS-säätiö)
- Alfred Kordelinin Säätiö (Alfred Kordelin Foundation)
- Finnish Cultural Foundation | Varsinais-Suomen Rahasto (Varsinais-Suomi Regional Fund)
- Suomalainen Lääkäriseura Duodecim (Finnish Medical Society Duodecim)
- Turun Yliopisto (University of Turku)
- This work was supported by funding for the VAMI-project (Turku University Hospital, state research funding, no. P3848), partly supported by EU FP7 grants (PRONIA, grant a # 602152 and METSY grant #602478). Dr. Armio received personal funding from Doctoral Programme in Clinical Research at the University of Turku, grants from State Research Funding, Turunmaa Duodecim Society, Finnish Psychiatry Research Foundation, Finnish University Society of Turku (Valto Takala Foundation), Tyks-foundation, The Finnish Medical Foundation (Maija and Matti Vaskio fund), University of Turku, The Alfred Kordelin Foundation, Finnish Cultural Foundation (Terttu Enckell fund and Ritva Helminen fund) and The Alfred Kordelin foundation. Further, Dr. Tuominen received personal grant from Sigrid Juselius and Orion research foundation and NARSAD Young Investigator Grant from the Brain & Behavior Research Foundation.
- This work was supported by funding for the VAMI-project (Turku University Hospital, state research funding, no. P3848), partly supported by EU FP7 grants (PRONIA, grant a # 602152 and METSY grant #602478). Dr. Tuominen received personal grant from Sigrid Juselius and Orion research foundation and NARSAD Young Investigator Grant from the Brain & Behavior Research Foundation.
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Affiliation(s)
- Reetta-Liina Armio
- PET Centre, Turku University Hospital, 20520, Turku, Finland.
- Department of Psychiatry, University of Turku, 20700, Turku, Finland.
- Department of Psychiatry, Turku University Hospital, 20520, Turku, Finland.
| | - Heikki Laurikainen
- PET Centre, Turku University Hospital, 20520, Turku, Finland
- Department of Psychiatry, University of Turku, 20700, Turku, Finland
- Department of Psychiatry, Turku University Hospital, 20520, Turku, Finland
| | - Tuula Ilonen
- Department of Psychiatry, University of Turku, 20700, Turku, Finland
| | - Maija Walta
- PET Centre, Turku University Hospital, 20520, Turku, Finland
- Department of Psychiatry, University of Turku, 20700, Turku, Finland
- Department of Psychiatry, Turku University Hospital, 20520, Turku, Finland
| | - Elina Sormunen
- PET Centre, Turku University Hospital, 20520, Turku, Finland
- Department of Psychiatry, University of Turku, 20700, Turku, Finland
- Department of Psychiatry, Turku University Hospital, 20520, Turku, Finland
| | - Arvi Tolvanen
- Department of Psychiatry, University of Turku, 20700, Turku, Finland
| | | | - Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, D-80336, Munich, Germany
| | - Lauri Tuominen
- Department of Psychiatry, Turku University Hospital, 20520, Turku, Finland
- The Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
- Department of Psychiatry, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Jarmo Hietala
- PET Centre, Turku University Hospital, 20520, Turku, Finland
- Department of Psychiatry, University of Turku, 20700, Turku, Finland
- Department of Psychiatry, Turku University Hospital, 20520, Turku, Finland
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Patrick RE, Dickinson RA, Gentry MT, Kim JU, Oberlin LE, Park S, Principe JL, Teixeira AL, Weisenbach SL. Treatment resistant late-life depression: A narrative review of psychosocial risk factors, non-pharmacological interventions, and the role of clinical phenotyping. J Affect Disord 2024; 356:145-154. [PMID: 38593940 DOI: 10.1016/j.jad.2024.04.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 03/30/2024] [Accepted: 04/03/2024] [Indexed: 04/11/2024]
Abstract
BACKGROUND Treatment resistant depression (TRD) is a subset of major depressive disorder (MDD) in which symptoms do not respond to front line therapies. In older adults, the assessment and treatment of TRD is complicated by psychosocial risk factors unique to this population, as well as a relative paucity of research. METHODS Narrative review aimed at (1) defining TRLLD for clinical practice and research; (2) describing psychosocial risk factors; (3) reviewing psychological and non-pharmacological treatments; (4) discussing the role of clinical phenotyping for personalized treatment; and (5) outlining research priorities. RESULTS Our definition of TRLLD centers on response to medication and neuromodulation in primary depressive disorders. Psychosocial risk factors include trauma and early life adversity, chronic physical illness, social isolation, personality, and barriers to care. Promising non-pharmacological treatments include cognitive training, psychotherapy, and lifestyle interventions. The utility of clinical phenotyping is highlighted by studies examining the impact of comorbidities, symptom dimensions (e.g., apathy), and structural/functional brain changes. LIMITATIONS There is a relative paucity of TRLLD research. This limits the scope of empirical data from which to derive reliable patterns and complicates efforts to evaluate the literature quantitatively. CONCLUSIONS TRLLD is a complex disorder that demands further investigation given our aging population. While this review highlights the promising breadth of TRLLD research to date, more research is needed to help elucidate, for example, the optimal timing for implementing risk mitigation strategies, the value of collaborative care approaches, specific treatment components associated with more robust response, and phenotyping to help inform treatment decisions.
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Affiliation(s)
- Regan E Patrick
- Department of Neuropsychology, McLean Hospital, Belmont, MA, United States of America; Division of Geriatric Psychiatry, McLean Hospital, Belmont, MA, United States of America; Department of Psychiatry, Harvard Medical School, Boston, MA, United States of America.
| | - Rebecca A Dickinson
- Department of Neuropsychology, McLean Hospital, Belmont, MA, United States of America; Division of Geriatric Psychiatry, McLean Hospital, Belmont, MA, United States of America
| | - Melanie T Gentry
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States of America
| | - Joseph U Kim
- Department of Neurology, Brigham and Women's Hospital, Boston, MA, United States of America
| | - Lauren E Oberlin
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, United States of America; AdventHealth Research Institute, Neuroscience, Orlando, FL, United States of America
| | - Soohyun Park
- Department of Psychiatry, Tufts Medical Center, Boston, MA, United States of America
| | - Jessica L Principe
- Division of Geriatric Psychiatry, McLean Hospital, Belmont, MA, United States of America; Department of Psychiatry, Harvard Medical School, Boston, MA, United States of America; Department of Psychiatry, Massachusetts General Hospital, Boston, MA, United States of America; Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, United States of America
| | - Antonio L Teixeira
- Department of Psychiatry & Behavioral Sciences, UT Health Houston, Houston, TX, United States of America
| | - Sara L Weisenbach
- Department of Neuropsychology, McLean Hospital, Belmont, MA, United States of America; Division of Geriatric Psychiatry, McLean Hospital, Belmont, MA, United States of America; Department of Psychiatry, Harvard Medical School, Boston, MA, United States of America
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3
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Alonso M, Petit AC, Lledo PM. The impact of adult neurogenesis on affective functions: of mice and men. Mol Psychiatry 2024:10.1038/s41380-024-02504-w. [PMID: 38499657 DOI: 10.1038/s41380-024-02504-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 02/22/2024] [Accepted: 02/27/2024] [Indexed: 03/20/2024]
Abstract
In most mammals, new neurons are not only produced during embryogenesis but also after birth. Soon after adult neurogenesis was discovered, the influence of recruiting new neurons on cognitive functions, especially on memory, was documented. Likewise, the late process of neuronal production also contributes to affective functions, but this outcome was recognized with more difficulty. This review covers hypes and hopes of discovering the influence of newly-generated neurons on brain circuits devoted to affective functions. If the possibility of integrating new neurons into the adult brain is a commonly accepted faculty in the realm of mammals, the reluctance is strong when it comes to translating this concept to humans. Compiling data suggest now that new neurons are derived not only from stem cells, but also from a population of neuroblasts displaying a protracted maturation and ready to be engaged in adult brain circuits, under specific signals. Here, we discuss the significance of recruiting new neurons in the adult brain circuits, specifically in the context of affective outcomes. We also discuss the fact that adult neurogenesis could be the ultimate cellular process that integrates elements from both the internal and external environment to adjust brain functions. While we must be critical and beware of the unreal promises that Science could generate sometimes, it is important to continue exploring the potential of neural recruitment in adult primates. Reporting adult neurogenesis in humankind contributes to a new vision of humans as mammals whose brain continues to develop throughout life. This peculiar faculty could one day become the target of treatment for mental health, cognitive disorders, and elderly-associated diseases. The vision of an adult brain which never stops integrating new neurons is a real game changer for designing new therapeutic interventions to treat mental disorders associated with substantial morbidity, mortality, and social costs.
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Affiliation(s)
- Mariana Alonso
- Institut Pasteur, Université Paris Cité, CNRS UMR 3571, Perception and Action Unit, F-75015, Paris, France
| | - Anne-Cécile Petit
- Institut Pasteur, Université Paris Cité, CNRS UMR 3571, Perception and Action Unit, F-75015, Paris, France
- Pôle Hospitalo-Universitaire Psychiatrie Paris 15, GHU Paris Psychiatry and Neurosciences, Hôpital Sainte-Anne, Paris, France
| | - Pierre-Marie Lledo
- Institut Pasteur, Université Paris Cité, CNRS UMR 3571, Perception and Action Unit, F-75015, Paris, France.
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Chu Z, Yuan L, Lian K, He M, Lu Y, Cheng Y, Xu X, Shen Z. Reduced gray matter volume of the hippocampal tail in melancholic depression: evidence from an MRI study. BMC Psychiatry 2024; 24:183. [PMID: 38443878 PMCID: PMC10913289 DOI: 10.1186/s12888-024-05630-5] [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: 10/18/2023] [Accepted: 02/21/2024] [Indexed: 03/07/2024] Open
Abstract
BACKGROUND Melancholic depression (MD) is one of the most prevalent and severe subtypes of major depressive disorder (MDD). Previous studies have revealed inconsistent results regarding alterations in grey matter volume (GMV) of the hippocampus and amygdala of MD patients, possibly due to overlooking the complexity of their internal structure. The hippocampus and amygdala consist of multiple and functionally distinct subregions, and these subregions may play different roles in MD. This study aims to investigate the volumetric alterations of each subregion of the hippocampus and amygdala in patients with MD and non-melancholic depression (NMD). METHODS A total of 146 drug-naïve, first-episode MDD patients (72 with MD and 74 with NMD) and 81 gender-, age-, and education-matched healthy controls (HCs) were included in the study. All participants underwent magnetic resonance imaging (MRI) scans. The subregional segmentation of hippocampus and amygdala was performed using the FreeSurfer 6.0 software. The multivariate analysis of covariance (MANCOVA) was used to detect GMV differences of the hippocampal and amygdala subregions between three groups. Partial correlation analysis was conducted to explore the relationship between hippocampus or amygdala subfields and clinical characteristics in the MD group. Age, gender, years of education and intracranial volume (ICV) were included as covariates in both MANCOVA and partial correlation analyses. RESULTS Patients with MD exhibited a significantly lower GMV of the right hippocampal tail compared to HCs, which was uncorrelated with clinical characteristics of MD. No significant differences were observed among the three groups in overall and subregional GMV of amygdala. CONCLUSIONS Our findings suggest that specific hippocampal subregions in MD patients are more susceptible to volumetric alterations than the entire hippocampus. The reduced right hippocampal tail may underlie the unique neuropathology of MD. Future longitudinal studies are required to better investigate the associations between reduced right hippocampal tail and the onset and progression of MD.
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Affiliation(s)
- Zhaosong Chu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, 650032, Kunming, China
- Yunnan Province Clinical Research Center for Mental Health, 650032, Kunming, China
| | - Lijin Yuan
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, 650032, Kunming, China
- Yunnan Province Clinical Research Center for Mental Health, 650032, Kunming, China
| | - Kun Lian
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, 650032, Kunming, China
- Yunnan Province Clinical Research Center for Mental Health, 650032, Kunming, China
| | - Mengxin He
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, 650032, Kunming, China
- Yunnan Province Clinical Research Center for Mental Health, 650032, Kunming, China
| | - Yi Lu
- Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, 650032, Kunming, China
| | - Yuqi Cheng
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, 650032, Kunming, China
- Yunnan Province Clinical Research Center for Mental Health, 650032, Kunming, China
| | - Xiufeng Xu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, 650032, Kunming, China.
- Yunnan Province Clinical Research Center for Mental Health, 650032, Kunming, China.
| | - Zonglin Shen
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, 650032, Kunming, China.
- Yunnan Province Clinical Research Center for Mental Health, 650032, Kunming, China.
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5
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Roalf DR, Figee M, Oathes DJ. Elevating the field for applying neuroimaging to individual patients in psychiatry. Transl Psychiatry 2024; 14:87. [PMID: 38341414 PMCID: PMC10858949 DOI: 10.1038/s41398-024-02781-7] [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: 01/10/2023] [Revised: 12/06/2023] [Accepted: 01/15/2024] [Indexed: 02/12/2024] Open
Abstract
Although neuroimaging has been widely applied in psychiatry, much of the exuberance in decades past has been tempered by failed replications and a lack of definitive evidence to support the utility of imaging to inform clinical decisions. There are multiple promising ways forward to demonstrate the relevance of neuroimaging for psychiatry at the individual patient level. Ultra-high field magnetic resonance imaging is developing as a sensitive measure of neurometabolic processes of particular relevance that holds promise as a new way to characterize patient abnormalities as well as variability in response to treatment. Neuroimaging may also be particularly suited to the science of brain stimulation interventions in psychiatry given that imaging can both inform brain targeting as well as measure changes in brain circuit communication as a function of how effectively interventions improve symptoms. We argue that a greater focus on individual patient imaging data will pave the way to stronger relevance to clinical care in psychiatry. We also stress the importance of using imaging in symptom-relevant experimental manipulations and how relevance will be best demonstrated by pairing imaging with differential treatment prediction and outcome measurement. The priorities for using brain imaging to inform psychiatry may be shifting, which compels the field to solidify clinical relevance for individual patients over exploratory associations and biomarkers that ultimately fail to replicate.
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Affiliation(s)
- David R Roalf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Neurodevelopment & Psychosis Section, University of Pennsylvania, Philadelphia, PA, USA
| | - Martijn Figee
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Desmond J Oathes
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Center for Brain Imaging and Stimulation, University of Pennsylvania, Philadelphia, PA, USA.
- Center for Neuromodulation in Depression and Stress, University of Pennsylvania, Philadelphia, PA, USA.
- Penn Brain Science Translation, Innovation, and Modulation Center, University of Pennsylvania, Philadelphia, PA, USA.
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6
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Fu CHY, Antoniades M, Erus G, Garcia JA, Fan Y, Arnone D, Arnott SR, Chen T, Choi KS, Fatt CC, Frey BN, Frokjaer VG, Ganz M, Godlewska BR, Hassel S, Ho K, McIntosh AM, Qin K, Rotzinger S, Sacchet MD, Savitz J, Shou H, Singh A, Stolicyn A, Strigo I, Strother SC, Tosun D, Victor TA, Wei D, Wise T, Zahn R, Anderson IM, Craighead WE, Deakin JFW, Dunlop BW, Elliott R, Gong Q, Gotlib IH, Harmer CJ, Kennedy SH, Knudsen GM, Mayberg HS, Paulus MP, Qiu J, Trivedi MH, Whalley HC, Yan CG, Young AH, Davatzikos C. Neuroanatomical dimensions in medication-free individuals with major depressive disorder and treatment response to SSRI antidepressant medications or placebo. NATURE. MENTAL HEALTH 2024; 2:164-176. [PMID: 38948238 PMCID: PMC11211072 DOI: 10.1038/s44220-023-00187-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 11/17/2023] [Indexed: 07/02/2024]
Abstract
Major depressive disorder (MDD) is a heterogeneous clinical syndrome with widespread subtle neuroanatomical correlates. Our objective was to identify the neuroanatomical dimensions that characterize MDD and predict treatment response to selective serotonin reuptake inhibitor (SSRI) antidepressants or placebo. In the COORDINATE-MDD consortium, raw MRI data were shared from international samples (N = 1,384) of medication-free individuals with first-episode and recurrent MDD (N = 685) in a current depressive episode of at least moderate severity, but not treatment-resistant depression, as well as healthy controls (N = 699). Prospective longitudinal data on treatment response were available for a subset of MDD individuals (N = 359). Treatments were either SSRI antidepressant medication (escitalopram, citalopram, sertraline) or placebo. Multi-center MRI data were harmonized, and HYDRA, a semi-supervised machine-learning clustering algorithm, was utilized to identify patterns in regional brain volumes that are associated with disease. MDD was optimally characterized by two neuroanatomical dimensions that exhibited distinct treatment responses to placebo and SSRI antidepressant medications. Dimension 1 was characterized by preserved gray and white matter (N = 290 MDD), whereas Dimension 2 was characterized by widespread subtle reductions in gray and white matter (N = 395 MDD) relative to healthy controls. Although there were no significant differences in age of onset, years of illness, number of episodes, or duration of current episode between dimensions, there was a significant interaction effect between dimensions and treatment response. Dimension 1 showed a significant improvement in depressive symptoms following treatment with SSRI medication (51.1%) but limited changes following placebo (28.6%). By contrast, Dimension 2 showed comparable improvements to either SSRI (46.9%) or placebo (42.2%) (β = -18.3, 95% CI (-34.3 to -2.3), P = 0.03). Findings from this case-control study indicate that neuroimaging-based markers can help identify the disease-based dimensions that constitute MDD and predict treatment response.
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Affiliation(s)
- Cynthia H. Y. Fu
- School of Psychology, University of East London, London, UK
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, UK
| | - Mathilde Antoniades
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Guray Erus
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Jose A. Garcia
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Yong Fan
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Danilo Arnone
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, UK
| | | | - Taolin Chen
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Ki Sueng Choi
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Cherise Chin Fatt
- Department of Psychiatry, Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, TX USA
| | - Benicio N. Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario Canada
- Mood Disorders Treatment and Research Centre and Women’s Health Concerns Clinic, St Joseph’s Healthcare Hamilton, Hamilton, Ontario Canada
| | - Vibe G. Frokjaer
- Neurobiology Research Unit, University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Psychiatry, Psychiatric Centre Copenhagen, Copenhagen, Denmark
| | - Melanie Ganz
- Neurobiology Research Unit, University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | - Beata R. Godlewska
- Department of Psychiatry, University of Oxford, Oxford, UK
- Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, UK
| | - Stefanie Hassel
- Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary, Alberta Canada
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, Alberta Canada
| | - Keith Ho
- Department of Psychiatry, University Health Network, Toronto, Ontario Canada
| | - Andrew M. McIntosh
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Kun Qin
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, China
| | - Susan Rotzinger
- Department of Psychiatry, University Health Network, Toronto, Ontario Canada
- Centre for Depression and Suicide Studies, Unity Health Toronto, Toronto, Ontario Canada
| | - Matthew D. Sacchet
- Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA USA
| | | | - Haochang Shou
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE) Center, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA USA
| | - Ashish Singh
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Aleks Stolicyn
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Irina Strigo
- Department of Psychiatry, University of California San Francisco, San Francisco, USA
| | - Stephen C. Strother
- Rotman Research Institute, Baycrest Centre, Toronto, Ontario Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario Canada
| | - Duygu Tosun
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA USA
| | | | - Dongtao Wei
- School of Psychology, Southwest University, Chongqing, China
| | - Toby Wise
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Roland Zahn
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, UK
| | - Ian M. Anderson
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
| | - W. Edward Craighead
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA USA
- Department of Psychology, Emory University, Atlanta, GA USA
| | - J. F. William Deakin
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
| | - Boadie W. Dunlop
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA USA
| | - Rebecca Elliott
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Ian H. Gotlib
- Department of Psychology, Stanford University, Stanford, CA USA
| | | | - Sidney H. Kennedy
- Department of Psychiatry, University Health Network, Toronto, Ontario Canada
- Centre for Depression and Suicide Studies, Unity Health Toronto, Toronto, Ontario Canada
| | - Gitte M. Knudsen
- Neurobiology Research Unit, University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Helen S. Mayberg
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | | | - Jiang Qiu
- School of Psychology, Southwest University, Chongqing, China
| | - Madhukar H. Trivedi
- Department of Psychiatry, Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, TX USA
| | - Heather C. Whalley
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Chao-Gan Yan
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Allan H. Young
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, UK
- South London and Maudsley NHS Foundation Trust, Bethlem Royal Hospital, London, UK
| | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
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7
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Mazurka R, Cunningham S, Hassel S, Foster JA, Nogovitsyn N, Fiori LM, Strother SC, Arnott SR, Frey BN, Lam RW, MacQueen GM, Milev RV, Rotzinger S, Turecki G, Kennedy SH, Harkness KL. Relation of hippocampal volume and SGK1 gene expression to treatment remission in major depression is moderated by childhood maltreatment: A CAN-BIND-1 report. Eur Neuropsychopharmacol 2024; 78:71-80. [PMID: 38128154 DOI: 10.1016/j.euroneuro.2023.12.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 12/01/2023] [Accepted: 12/14/2023] [Indexed: 12/23/2023]
Abstract
Preclinical research implicates stress-induced upregulation of the enzyme, serum- and glucocorticoid-regulated kinase 1 (SGK1), in reduced hippocampal volume. In the current study, we tested the hypothesis that greater SGK1 mRNA expression in humans would be associated with lower hippocampal volume, but only among those with a history of prolonged stress exposure, operationalized as childhood maltreatment (physical, sexual, and/or emotional abuse). Further, we examined whether baseline levels of SGK1 and hippocampal volume, or changes in these markers over the course of antidepressant treatment, would predict treatment outcomes in adults with major depression [MDD]. We assessed SGK1 mRNA expression from peripheral blood, and left and right hippocampal volume at baseline, as well as change in these markers over the first 8 weeks of a 16-week open-label trial of escitalopram as part of the Canadian Biomarker Integration Network in Depression program (MDD [n = 161] and healthy comparison participants [n = 91]). Childhood maltreatment was assessed via contextual interview with standardized ratings. In the full sample at baseline, greater SGK1 expression was associated with lower hippocampal volume, but only among those with more severe childhood maltreatment. In individuals with MDD, decreases in SGK1 expression predicted lower remission rates at week 16, again only among those with more severe maltreatment. Decreases in hippocampal volume predicted lower week 16 remission for those with low childhood maltreatment. These results suggest that both glucocorticoid-related neurobiological mechanisms of the stress response and history of childhood stress exposure may be critical to understanding differential treatment outcomes in MDD. ClinicalTrials.gov: NCT01655706 Canadian Biomarker Integration Network for Depression Study.
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Affiliation(s)
- Raegan Mazurka
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada.
| | | | - Stefanie Hassel
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Jane A Foster
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Nikita Nogovitsyn
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada; Centre for Depression and Suicide Studies, St. Michael's Hospital, Toronto ON, Canada
| | - Laura M Fiori
- Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, Canada
| | - Stephen C Strother
- Rotman Research Institute, Baycrest, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Canada
| | | | - Benicio N Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada; Mood Disorders Program, St. Joseph's Healthcare Hamilton, ON, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Glenda M MacQueen
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - Roumen V Milev
- Departments of Psychiatry and Psychology, And Providence Care Hospital, Queen's University, Kingston, ON, Canada
| | - Susan Rotzinger
- Department of Psychiatry, University of Toronto, Canada; Centre for Depression and Suicide Studies, St. Michael's Hospital, Toronto ON, Canada
| | - Gustavo Turecki
- Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, Canada
| | - Sidney H Kennedy
- Department of Psychiatry, University of Toronto, Canada; Centre for Depression and Suicide Studies, St. Michael's Hospital, Toronto ON, Canada
| | - Kate L Harkness
- Department of Psychology, Queen's University, Kingston, ON, Canada
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8
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Paolini M, Harrington Y, Colombo F, Bettonagli V, Poletti S, Carminati M, Colombo C, Benedetti F, Zanardi R. Hippocampal and parahippocampal volume and function predict antidepressant response in patients with major depression: A multimodal neuroimaging study. J Psychopharmacol 2023; 37:1070-1081. [PMID: 37589290 PMCID: PMC10647896 DOI: 10.1177/02698811231190859] [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: 08/18/2023]
Abstract
BACKGROUND For many patients with major depressive disorder (MDD) adequate treatment remains elusive. Neuroimaging techniques received attention for their potential use in guiding and predicting response, but were rarely investigated in real-world psychiatric settings. AIMS To identify structural and functional Magnetic Resonance Imaging (MRI) biomarkers associated with antidepressant response in a real-world clinical sample. METHODS We studied 100 MDD inpatients admitted to our psychiatric ward, treated with various antidepressants upon clinical need. Hamilton Depression Rating Scale percentage decrease from admission to discharge was used as a measure of response. All patients underwent 3.0 T MRI scanning. Grey matter (GM) volumes were investigated both in a voxel-based morphometry (VBM), and in a regions of interest (ROI) analysis. In a subsample of patients, functional resting-state connectivity patterns were also explored. RESULTS In the VBM analysis, worse response was associated to lower GM volumes in two clusters, encompassing the left hippocampus and parahippocampal gyrus, and the right superior and middle temporal gyrus. Investigating ROIs, lower bilateral hippocampi and amygdalae volumes predicted worse treatment outcomes. Functional connectivity in the right temporal and parahippocampal gyrus was also associated to response. CONCLUSION Our results expand existing literature on the relationship between the structure and function of several brain regions and treatment response in MDD. While we are still far from routine use of MRI biomarkers in clinical practice, we confirm a possible role of these techniques in guiding treatment choices and predicting their efficacy.
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Affiliation(s)
- Marco Paolini
- Vita-Salute San Raffaele University, Milano, Italy
- Psychiatry and Clinical Psychobiology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Yasmin Harrington
- Vita-Salute San Raffaele University, Milano, Italy
- Psychiatry and Clinical Psychobiology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Federica Colombo
- Vita-Salute San Raffaele University, Milano, Italy
- Psychiatry and Clinical Psychobiology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | | | - Sara Poletti
- Vita-Salute San Raffaele University, Milano, Italy
- Psychiatry and Clinical Psychobiology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Matteo Carminati
- Vita-Salute San Raffaele University, Milano, Italy
- Mood Disorders Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Cristina Colombo
- Vita-Salute San Raffaele University, Milano, Italy
- Mood Disorders Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Francesco Benedetti
- Vita-Salute San Raffaele University, Milano, Italy
- Psychiatry and Clinical Psychobiology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Raffaella Zanardi
- Mood Disorders Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
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9
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Zavaliangos-Petropulu A, McClintock SM, Joshi SH, Taraku B, Al-Sharif NB, Espinoza RT, Narr KL. Hippocampal subfield volumes in treatment resistant depression and serial ketamine treatment. Front Psychiatry 2023; 14:1227879. [PMID: 37876623 PMCID: PMC10590913 DOI: 10.3389/fpsyt.2023.1227879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 09/11/2023] [Indexed: 10/26/2023] Open
Abstract
Introduction Subanesthetic ketamine is a rapidly acting antidepressant that has also been found to improve neurocognitive performance in adult patients with treatment resistant depression (TRD). Provisional evidence suggests that ketamine may induce change in hippocampal volume and that larger pre-treatment volumes might be related to positive clinical outcomes. Here, we examine the effects of serial ketamine treatment on hippocampal subfield volumes and relationships between pre-treatment subfield volumes and changes in depressive symptoms and neurocognitive performance. Methods Patients with TRD (N = 66; 31M/35F; age = 39.5 ± 11.1 years) received four ketamine infusions (0.5 mg/kg) over 2 weeks. Structural MRI scans, the National Institutes of Health Toolbox (NIHT) Cognition Battery, and Hamilton Depression Rating Scale (HDRS) were collected at baseline, 24 h after the first and fourth ketamine infusion, and 5 weeks post-treatment. The same data was collected for 32 age and sex matched healthy controls (HC; 17M/15F; age = 35.03 ± 12.2 years) at one timepoint. Subfield (CA1/CA3/CA4/subiculum/molecular layer/GC-ML-DG) volumes corrected for whole hippocampal volume were compared across time, between treatment remitters/non-remitters, and patients and HCs using linear regression models. Relationships between pre-treatment subfield volumes and clinical and cognitive outcomes were also tested. All analyses included Bonferroni correction. Results Patients had smaller pre-treatment left CA4 (p = 0.004) and GC.ML.DG (p = 0.004) volumes compared to HC, but subfield volumes remained stable following ketamine treatment (all p > 0.05). Pre-treatment or change in hippocampal subfield volumes over time showed no variation by remission status nor correlated with depressive symptoms (p > 0.05). Pre-treatment left CA4 was negatively correlated with improved processing speed after single (p = 0.0003) and serial ketamine infusion (p = 0.005). Left GC.ML.DG also negatively correlated with improved processing speed after single infusion (p = 0.001). Right pre-treatment CA3 positively correlated with changes in list sorting working memory at follow-up (p = 0.0007). Discussion These results provide new evidence to suggest that hippocampal subfield volumes at baseline may present a biomarker for neurocognitive improvement following ketamine treatment in TRD. In contrast, pre-treatment subfield volumes and changes in subfield volumes showed negligible relationships with ketamine-related improvements in depressive symptoms.
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Affiliation(s)
- Artemis Zavaliangos-Petropulu
- Ahmanson-Lovelace Brain Mapping Center, Department of Neurology, Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA, United States
| | - Shawn M. McClintock
- Division of Psychology, Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, United States
| | - Shantanu H. Joshi
- Ahmanson-Lovelace Brain Mapping Center, Department of Neurology, Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA, United States
| | - Brandon Taraku
- Ahmanson-Lovelace Brain Mapping Center, Department of Neurology, Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA, United States
| | - Noor B. Al-Sharif
- Ahmanson-Lovelace Brain Mapping Center, Department of Neurology, Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA, United States
| | - Randall T. Espinoza
- Jane and Terry Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA, United States
| | - Katherine L. Narr
- Ahmanson-Lovelace Brain Mapping Center, Department of Neurology, Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA, United States
- Jane and Terry Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA, United States
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10
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Wilkes FA, Jakabek D, Walterfang M, Velakoulis D, Poudel GR, Stout JC, Chua P, Egan GF, Looi JCL, Georgiou-Karistianis N. Hippocampal morphology in Huntington's disease, implications for plasticity and pathogenesis: The IMAGE-HD study. Psychiatry Res Neuroimaging 2023; 335:111694. [PMID: 37598529 DOI: 10.1016/j.pscychresns.2023.111694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 06/10/2023] [Accepted: 07/26/2023] [Indexed: 08/22/2023]
Abstract
While striatal changes in Huntington's Disease (HD) are well established, few studies have investigated changes in the hippocampus, a key neuronal hub. Using MRI scans obtained from the IMAGE-HD study, hippocampi were manually traced and then analysed with the Spherical Harmonic Point Distribution Method (SPHARM-PDM) in 36 individuals with presymptomatic-HD, 37 with early symptomatic-HD, and 36 healthy matched controls. There were no significant differences in overall hippocampal volume between groups. Interestingly we found decreased bilateral hippocampal volume in people with symptomatic-HD who took selective serotonin reuptake inhibitors compared to those who did not, despite no significant differences in anxiety, depressive symptoms, or motor incapacity between the two groups. In symptomatic-HD, there was also significant shape deflation in the right hippocampal head, showing the utility of using manual tracing and SPHARM-PDM to characterise subtle shape changes which may be missed by other methods. This study confirms previous findings of the lack of hippocampal volumetric differentiation in presymptomatic-HD and symptomatic-HD compared to controls. We also find novel shape and volume findings in those with symptomatic-HD, especially in relation to decreased hippocampal volume in those treated with SSRIs.
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Affiliation(s)
- Fiona A Wilkes
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, Australian National University Medical School, Canberra Hospital, Canberra, Australia.
| | | | - Mark Walterfang
- Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne Neuropsychiatry Centre, University of Melbourne and Northwestern Mental Health, Melbourne, Australia; Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia
| | - Dennis Velakoulis
- Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne Neuropsychiatry Centre, University of Melbourne and Northwestern Mental Health, Melbourne, Australia; Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia
| | - Govinda R Poudel
- Mary Mackillop Institute for Health Research, Australian Catholic University, Melbourne, Australia
| | - Julie C Stout
- School of Psychological Sciences and the Turner Institute of Brain and Mental Health, Monash University, Melbourne, Australia
| | - Phyllis Chua
- Department of Psychiatry, School of Clinical Sciences, Monash University, Monash Medical Centre, Melbourne, Australia
| | - Gary F Egan
- School of Psychological Sciences and the Turner Institute of Brain and Mental Health, Monash University, Melbourne, Australia
| | - Jeffrey C L Looi
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, Australian National University Medical School, Canberra Hospital, Canberra, Australia; Neuroscience Research Australia, Sydney, Australia
| | - Nellie Georgiou-Karistianis
- School of Psychological Sciences and the Turner Institute of Brain and Mental Health, Monash University, Melbourne, Australia
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11
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Ping L, Sun S, Zhou C, Que J, You Z, Xu X, Cheng Y. Altered topology of individual brain structural covariance networks in major depressive disorder. Psychol Med 2023:1-12. [PMID: 37427670 DOI: 10.1017/s003329172300168x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
BACKGROUND The neurobiological pathogenesis of major depression disorder (MDD) remains largely controversial. Previous literatures with limited sample size utilizing group-level structural covariance networks (SCN) commonly generated mixed findings regarding the topology of brain networks. METHODS We analyzed T1 images from a high-powered multisite sample including 1173 patients with MDD and 1019 healthy controls (HCs). We used regional gray matter volume to construct individual SCN by utilizing a novel approach based on the interregional effect size difference. We further investigated MDD-related structural connectivity alterations using topological metrics. RESULTS Compared to HCs, the MDD patients showed a shift toward randomization characterized by increased integration. Further subgroup analysis of patients in different stages revealed this randomization pattern was also observed in patients with recurrent MDD, while the first-episode drug naïve patients exhibited decreased segregation. Altered nodal properties in several brain regions which have a key role in both emotion regulation and executive control were also found in MDD patients compared with HCs. The abnormalities in inferior temporal gyrus were not influenced by any specific site. Moreover, antidepressants increased nodal efficiency in the anterior ventromedial prefrontal cortex. CONCLUSIONS The MDD patients at different stages exhibit distinct patterns of randomization in their brain networks, with increased integration during illness progression. These findings provide valuable insights into the disruption in structural brain networks that occurs in patients with MDD and might be useful to guide future therapeutic interventions.
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Affiliation(s)
- Liangliang Ping
- Department of Psychiatry, Xiamen Xianyue Hospital, Xiamen, China
| | - Shan Sun
- Department of Psychiatry, Xiamen Xianyue Hospital, Xiamen, China
| | - Cong Zhou
- School of Mental Health, Jining Medical University, Jining, China
| | - Jianyu Que
- Department of Psychiatry, Xiamen Xianyue Hospital, Xiamen, China
| | - Zhiyi You
- Department of Psychiatry, Xiamen Xianyue Hospital, Xiamen, China
| | - Xiufeng Xu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yuqi Cheng
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China
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12
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Tsai HJ, Yang WC, Tsai SJ, Lin CH, Yang AC. Right-side frontal-central cortical hyperactivation before the treatment predicts outcomes of antidepressant and electroconvulsive therapy responsivity in major depressive disorder. J Psychiatr Res 2023; 161:377-385. [PMID: 37012197 DOI: 10.1016/j.jpsychires.2023.03.023] [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: 01/04/2023] [Revised: 03/08/2023] [Accepted: 03/13/2023] [Indexed: 04/05/2023]
Abstract
Major depressive disorder places a great burden on healthcare resources worldwide. Antidepressants are the first-line treatment for major depressive disorder, but if patients don't respond adequately, brain stimulation therapy may be needed as second-line treatment. Digital phenotyping in patients with major depressive disorder will aid in the timely prediction of treatment effectiveness. This study explored electroencephalographic (EEG) signatures that diversify depression treatment responsivity, including antidepressant administration or brain stimulation therapy. Resting-state, pre-treatment EEG sequences from depressive patients who received fluoxetine treatment (n = 55; 26 remitters and 29 poor responders) or electroconvulsive therapy (ECT, n = 58; 36 remitters and 22 nonremitters) were recorded on 19 channels. Twenty-nine EEG segments were obtained from each patient per recording electrode. Power spectral analysis was conducted for feature extraction and showed the highest predictive accuracy for fluoxetine or ECT outcomes. Both occurred with beta-band oscillations within right-side frontal-central (F1-score = 0.9437) or prefrontal areas of the brain (F1-score = 0.9416), respectively. Significantly higher beta-band power was observed among patients who lacked adequate treatment response than the remitters, specifically at 19.2 Hz or 24.5 Hz for fluoxetine administration or ECT outcome, respectively. Our findings indicated that pre-treatment, right-side cortical hyperactivation is associated with poor outcomes of antidepressant-based or ECT-based treatment in major depression. Whether depression treatment response rates can be improved by reducing the high-frequency EEG power in corresponding areas of the brain to provide a protective effect against depression recurrence warrants further study.
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Affiliation(s)
- Hsin-Jung Tsai
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan; Digital Medicine and Smart Healthcare Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Wei-Cheng Yang
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Psychiatry, Tainan Hospital, Ministry of Health and Welfare, Tainan, Taiwan
| | - Shih-Jen Tsai
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Psychiatry, Taipei Veteran General Hospital, Taipei, Taiwan
| | - Ching-Hua Lin
- Kaohsiung Municipal Kai-Syuan Psychiatric Hospital, Kaohsiung, Taiwan.
| | - Albert C Yang
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan; Digital Medicine and Smart Healthcare Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan.
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13
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Zhang L, Hu X, Hu Y, Tang M, Qiu H, Zhu Z, Gao Y, Li H, Kuang W, Ji W. Structural covariance network of the hippocampus-amygdala complex in medication-naïve patients with first-episode major depressive disorder. PSYCHORADIOLOGY 2022; 2:190-198. [PMID: 38665275 PMCID: PMC10917195 DOI: 10.1093/psyrad/kkac023] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 12/05/2022] [Accepted: 12/14/2022] [Indexed: 04/28/2024]
Abstract
Background The hippocampus and amygdala are densely interconnected structures that work together in multiple affective and cognitive processes that are important to the etiology of major depressive disorder (MDD). Each of these structures consists of several heterogeneous subfields. We aim to explore the topologic properties of the volume-based intrinsic network within the hippocampus-amygdala complex in medication-naïve patients with first-episode MDD. Methods High-resolution T1-weighted magnetic resonance imaging scans were acquired from 123 first-episode, medication-naïve, and noncomorbid MDD patients and 81 age-, sex-, and education level-matched healthy control participants (HCs). The structural covariance network (SCN) was constructed for each group using the volumes of the hippocampal subfields and amygdala subregions; the weights of the edges were defined by the partial correlation coefficients between each pair of subfields/subregions, controlled for age, sex, education level, and intracranial volume. The global and nodal graph metrics were calculated and compared between groups. Results Compared with HCs, the SCN within the hippocampus-amygdala complex in patients with MDD showed a shortened mean characteristic path length, reduced modularity, and reduced small-worldness index. At the nodal level, the left hippocampal tail showed increased measures of centrality, segregation, and integration, while nodes in the left amygdala showed decreased measures of centrality, segregation, and integration in patients with MDD compared with HCs. Conclusion Our results provide the first evidence of atypical topologic characteristics within the hippocampus-amygdala complex in patients with MDD using structure network analysis. It provides more delineate mechanism of those two structures that underlying neuropathologic process in MDD.
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Affiliation(s)
- Lianqing Zhang
- Functional and molecular imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, PR China
| | - Xinyue Hu
- Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Yongbo Hu
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Mengyue Tang
- Functional and molecular imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, PR China
| | - Hui Qiu
- Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Ziyu Zhu
- Functional and molecular imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, PR China
| | - Yingxue Gao
- Functional and molecular imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, PR China
| | - Hailong Li
- Functional and molecular imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, PR China
| | - Weihong Kuang
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Weidong Ji
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science and Affiliated Mental Health Center, East China Normal University, Shanghai 200335, China
- Child Psychiatry, Shanghai Changning Mental Health Center, Shanghai 200335, China
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14
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Zavaliangos-Petropulu A, Al-Sharif NB, Taraku B, Leaver AM, Sahib AK, Espinoza RT, Narr KL. Neuroimaging-Derived Biomarkers of the Antidepressant Effects of Ketamine. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 8:361-386. [PMID: 36775711 DOI: 10.1016/j.bpsc.2022.11.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 11/03/2022] [Accepted: 11/07/2022] [Indexed: 11/27/2022]
Abstract
Major depressive disorder is a highly prevalent psychiatric disorder. Despite an extensive range of treatment options, about a third of patients still struggle to respond to available therapies. In the last 20 years, ketamine has gained considerable attention in the psychiatric field as a promising treatment of depression, particularly in patients who are treatment resistant or at high risk for suicide. At a subanesthetic dose, ketamine produces a rapid and pronounced reduction in depressive symptoms and suicidal ideation, and serial treatment appears to produce a greater and more sustained therapeutic response. However, the mechanism driving ketamine's antidepressant effects is not yet well understood. Biomarker discovery may advance knowledge of ketamine's antidepressant action, which could in turn translate to more personalized and effective treatment strategies. At the brain systems level, neuroimaging can be used to identify functional pathways and networks contributing to ketamine's therapeutic effects by studying how it alters brain structure, function, connectivity, and metabolism. In this review, we summarize and appraise recent work in this area, including 51 articles that use resting-state and task-based functional magnetic resonance imaging, arterial spin labeling, positron emission tomography, structural magnetic resonance imaging, diffusion magnetic resonance imaging, or magnetic resonance spectroscopy to study brain and clinical changes 24 hours or longer after ketamine treatment in populations with unipolar or bipolar depression. Though individual studies have included relatively small samples, used different methodological approaches, and reported disparate regional findings, converging evidence supports that ketamine leads to neuroplasticity in structural and functional brain networks that contribute to or are relevant to its antidepressant effects.
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Affiliation(s)
- Artemis Zavaliangos-Petropulu
- Ahmanson-Lovelace Brain Mapping Center, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California.
| | - Noor B Al-Sharif
- Ahmanson-Lovelace Brain Mapping Center, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Brandon Taraku
- Ahmanson-Lovelace Brain Mapping Center, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Amber M Leaver
- Department of Radiology, Northwestern University, Chicago, Illinois
| | - Ashish K Sahib
- Ahmanson-Lovelace Brain Mapping Center, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Randall T Espinoza
- Jane and Terry Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Katherine L Narr
- Ahmanson-Lovelace Brain Mapping Center, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California; Jane and Terry Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
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15
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Saat P, Nogovitsyn N, Hassan MY, Ganaie MA, Souza R, Hemmati H. A domain adaptation benchmark for T1-weighted brain magnetic resonance image segmentation. Front Neuroinform 2022; 16:919779. [PMID: 36213544 PMCID: PMC9538795 DOI: 10.3389/fninf.2022.919779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 08/29/2022] [Indexed: 01/18/2023] Open
Abstract
Accurate brain segmentation is critical for magnetic resonance imaging (MRI) analysis pipelines. Machine-learning-based brain MR image segmentation methods are among the state-of-the-art techniques for this task. Nevertheless, the segmentations produced by machine learning models often degrade in the presence of expected domain shifts between the test and train sets data distributions. These domain shifts are expected due to several factors, such as scanner hardware and software differences, technology updates, and differences in MRI acquisition parameters. Domain adaptation (DA) methods can make machine learning models more resilient to these domain shifts. This paper proposes a benchmark for investigating DA techniques for brain MR image segmentation using data collected across sites with scanners from different vendors (Philips, Siemens, and General Electric). Our work provides labeled data, publicly available source code for a set of baseline and DA models, and a benchmark for assessing different brain MR image segmentation techniques. We applied the proposed benchmark to evaluate two segmentation tasks: skull-stripping; and white-matter, gray-matter, and cerebrospinal fluid segmentation, but the benchmark can be extended to other brain structures. Our main findings during the development of this benchmark are that there is not a single DA technique that consistently outperforms others, and hyperparameter tuning and computational times for these methods still pose a challenge before broader adoption of these methods in the clinical practice.
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Affiliation(s)
- Parisa Saat
- Electrical and Software Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada
- *Correspondence: Parisa Saat
| | - Nikita Nogovitsyn
- Centre for Depression and Suicide Studies, St. Michael's Hospital, Toronto, ON, Canada
- Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Muhammad Yusuf Hassan
- Electrical and Software Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada
- Electrical Engineering, Indian Institute of Technology, Gandhinagar, Gujarat, India
| | - Muhammad Athar Ganaie
- Electrical and Software Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada
- Chemical Engineering, Indian Institute of Technology, Kharagpur, West Bengal, India
| | - Roberto Souza
- Electrical and Software Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Hadi Hemmati
- Electrical and Software Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada
- Electrical Engineering and Computer Science, Lassonde School of Engineering, York University, Toronto, ON, Canada
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16
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Ahmed R, Ryan C, Christman S, Elson D, Bermudez C, Landman BA, Szymkowicz SM, Boyd BD, Kang H, Taylor WD. Structural MRI-Based Measures of Accelerated Brain Aging do not Moderate the Acute Antidepressant Response in Late-Life Depression. Am J Geriatr Psychiatry 2022; 30:1015-1025. [PMID: 34949526 PMCID: PMC9142760 DOI: 10.1016/j.jagp.2021.11.011] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 11/14/2021] [Accepted: 11/21/2021] [Indexed: 01/22/2023]
Abstract
OBJECTIVE Late-life depression (LLD) is characterized by accelerated biological aging. Accelerated brain aging, estimated from structural magnetic resonance imaging (sMRI) data by a machine learning algorithm, is associated with LLD diagnosis, poorer cognitive performance, and disability. We hypothesized that accelerated brain aging moderates the antidepressant response. DESIGN AND INTERVENTIONS Following MRI, participants entered an 8-week randomized, controlled trial of escitalopram. Nonremitting participants then entered an open-label 8-week trial of bupropion. PARTICIPANTS Ninety-five individuals with LLD. MEASUREMENTS A machine learning algorithm estimated each participant's brain age from sMRI data. This was used to calculate the brain-age gap (BAG), or how estimated age differed from chronological age. Secondary sMRI measures of aging pathology included white matter hyperintensity (WMH) volumes and hippocampal volumes. Mixed models examined the relationship between sMRI measures and change in depression severity. Initial analyses tested for a moderating effect of MRI measures on change in depression severity with escitalopram. Subsequent analyses tested for the effect of MRI measures on change in depression severity over time across trials. RESULTS In the blinded initial phase, BAG was not significantly associated with a differential response to escitalopram over time. BAG was also not associated with a change in depression severity over time across both arms in the blinded phase or in the subsequent open-label bupropion phase. We similarly did not observe effects of WMH volume or hippocampal volume on change in depression severity over time. CONCLUSION sMRI markers of accelerated brain aging were not associated with treatment response in this sequential antidepressant trial.
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Affiliation(s)
- Ryan Ahmed
- School of Medicine (RA), Vanderbilt University, Nashville, TN; Department of Psychiatry and Behavioral Sciences (SC, DE, BAL, SMS, BDB, WDT), Vanderbilt University Medical Center, Nashville, TN; Department of Biomedical Engineering (CB, BAL), Vanderbilt University, Nashville TN; Department of Electrical Engineering and Computer Science (BAL), Vanderbilt University, Nashville, TN; Department of Biostatistics (HK), Vanderbilt University Medical Center, Nashville, TN; Geriatric Research, Education, and Clinical Center (WDT), Veterans Affairs Tennessee Valley Health System, Nashville, TN
| | - Claire Ryan
- School of Medicine (RA), Vanderbilt University, Nashville, TN; Department of Psychiatry and Behavioral Sciences (SC, DE, BAL, SMS, BDB, WDT), Vanderbilt University Medical Center, Nashville, TN; Department of Biomedical Engineering (CB, BAL), Vanderbilt University, Nashville TN; Department of Electrical Engineering and Computer Science (BAL), Vanderbilt University, Nashville, TN; Department of Biostatistics (HK), Vanderbilt University Medical Center, Nashville, TN; Geriatric Research, Education, and Clinical Center (WDT), Veterans Affairs Tennessee Valley Health System, Nashville, TN
| | - Seth Christman
- School of Medicine (RA), Vanderbilt University, Nashville, TN; Department of Psychiatry and Behavioral Sciences (SC, DE, BAL, SMS, BDB, WDT), Vanderbilt University Medical Center, Nashville, TN; Department of Biomedical Engineering (CB, BAL), Vanderbilt University, Nashville TN; Department of Electrical Engineering and Computer Science (BAL), Vanderbilt University, Nashville, TN; Department of Biostatistics (HK), Vanderbilt University Medical Center, Nashville, TN; Geriatric Research, Education, and Clinical Center (WDT), Veterans Affairs Tennessee Valley Health System, Nashville, TN
| | - Damian Elson
- School of Medicine (RA), Vanderbilt University, Nashville, TN; Department of Psychiatry and Behavioral Sciences (SC, DE, BAL, SMS, BDB, WDT), Vanderbilt University Medical Center, Nashville, TN; Department of Biomedical Engineering (CB, BAL), Vanderbilt University, Nashville TN; Department of Electrical Engineering and Computer Science (BAL), Vanderbilt University, Nashville, TN; Department of Biostatistics (HK), Vanderbilt University Medical Center, Nashville, TN; Geriatric Research, Education, and Clinical Center (WDT), Veterans Affairs Tennessee Valley Health System, Nashville, TN
| | - Camilo Bermudez
- School of Medicine (RA), Vanderbilt University, Nashville, TN; Department of Psychiatry and Behavioral Sciences (SC, DE, BAL, SMS, BDB, WDT), Vanderbilt University Medical Center, Nashville, TN; Department of Biomedical Engineering (CB, BAL), Vanderbilt University, Nashville TN; Department of Electrical Engineering and Computer Science (BAL), Vanderbilt University, Nashville, TN; Department of Biostatistics (HK), Vanderbilt University Medical Center, Nashville, TN; Geriatric Research, Education, and Clinical Center (WDT), Veterans Affairs Tennessee Valley Health System, Nashville, TN
| | - Bennett A Landman
- School of Medicine (RA), Vanderbilt University, Nashville, TN; Department of Psychiatry and Behavioral Sciences (SC, DE, BAL, SMS, BDB, WDT), Vanderbilt University Medical Center, Nashville, TN; Department of Biomedical Engineering (CB, BAL), Vanderbilt University, Nashville TN; Department of Electrical Engineering and Computer Science (BAL), Vanderbilt University, Nashville, TN; Department of Biostatistics (HK), Vanderbilt University Medical Center, Nashville, TN; Geriatric Research, Education, and Clinical Center (WDT), Veterans Affairs Tennessee Valley Health System, Nashville, TN
| | - Sarah M Szymkowicz
- School of Medicine (RA), Vanderbilt University, Nashville, TN; Department of Psychiatry and Behavioral Sciences (SC, DE, BAL, SMS, BDB, WDT), Vanderbilt University Medical Center, Nashville, TN; Department of Biomedical Engineering (CB, BAL), Vanderbilt University, Nashville TN; Department of Electrical Engineering and Computer Science (BAL), Vanderbilt University, Nashville, TN; Department of Biostatistics (HK), Vanderbilt University Medical Center, Nashville, TN; Geriatric Research, Education, and Clinical Center (WDT), Veterans Affairs Tennessee Valley Health System, Nashville, TN
| | - Brian D Boyd
- School of Medicine (RA), Vanderbilt University, Nashville, TN; Department of Psychiatry and Behavioral Sciences (SC, DE, BAL, SMS, BDB, WDT), Vanderbilt University Medical Center, Nashville, TN; Department of Biomedical Engineering (CB, BAL), Vanderbilt University, Nashville TN; Department of Electrical Engineering and Computer Science (BAL), Vanderbilt University, Nashville, TN; Department of Biostatistics (HK), Vanderbilt University Medical Center, Nashville, TN; Geriatric Research, Education, and Clinical Center (WDT), Veterans Affairs Tennessee Valley Health System, Nashville, TN
| | - Hakmook Kang
- School of Medicine (RA), Vanderbilt University, Nashville, TN; Department of Psychiatry and Behavioral Sciences (SC, DE, BAL, SMS, BDB, WDT), Vanderbilt University Medical Center, Nashville, TN; Department of Biomedical Engineering (CB, BAL), Vanderbilt University, Nashville TN; Department of Electrical Engineering and Computer Science (BAL), Vanderbilt University, Nashville, TN; Department of Biostatistics (HK), Vanderbilt University Medical Center, Nashville, TN; Geriatric Research, Education, and Clinical Center (WDT), Veterans Affairs Tennessee Valley Health System, Nashville, TN
| | - Warren D Taylor
- School of Medicine (RA), Vanderbilt University, Nashville, TN; Department of Psychiatry and Behavioral Sciences (SC, DE, BAL, SMS, BDB, WDT), Vanderbilt University Medical Center, Nashville, TN; Department of Biomedical Engineering (CB, BAL), Vanderbilt University, Nashville TN; Department of Electrical Engineering and Computer Science (BAL), Vanderbilt University, Nashville, TN; Department of Biostatistics (HK), Vanderbilt University Medical Center, Nashville, TN; Geriatric Research, Education, and Clinical Center (WDT), Veterans Affairs Tennessee Valley Health System, Nashville, TN.
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17
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Gerlach AR, Karim HT, Peciña M, Ajilore O, Taylor WD, Butters MA, Andreescu C. MRI predictors of pharmacotherapy response in major depressive disorder. Neuroimage Clin 2022; 36:103157. [PMID: 36027717 PMCID: PMC9420953 DOI: 10.1016/j.nicl.2022.103157] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 07/11/2022] [Accepted: 08/15/2022] [Indexed: 02/08/2023]
Abstract
Major depressive disorder is among the most prevalent psychiatric disorders, exacting a substantial personal, social, and economic toll. Antidepressant treatment typically involves an individualized trial and error approach with an inconsistent success rate. Despite a pressing need, no reliable biomarkers for predicting treatment outcome have yet been discovered. Brain MRI measures hold promise in this regard, though clinical translation remains elusive. In this review, we summarize structural MRI and functional MRI (fMRI) measures that have been investigated as predictors of treatment outcome. We broadly divide these into five categories including three structural measures: volumetric, white matter burden, and white matter integrity; and two functional measures: resting state fMRI and task fMRI. Currently, larger hippocampal volume is the most widely replicated predictor of successful treatment. Lower white matter hyperintensity burden has shown robustness in late life depression. However, both have modest discriminative power. Higher fractional anisotropy of the cingulum bundle and frontal white matter, amygdala hypoactivation and anterior cingulate cortex hyperactivation in response to negative emotional stimuli, and hyperconnectivity within the default mode network (DMN) and between the DMN and executive control network also show promise as predictors of successful treatment. Such network-focused measures may ultimately provide a higher-dimensional measure of treatment response with closer ties to the underlying neurobiology.
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Affiliation(s)
- Andrew R Gerlach
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Helmet T Karim
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Marta Peciña
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Olusola Ajilore
- Department of Psychiatry, University of Illinois-Chicago, Chicago, IL, USA
| | - Warren D Taylor
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Geriatric Research, Education, and Clinical Center, Veterans Affairs Tennessee Valley Health System, Nashville, TN, USA
| | - Meryl A Butters
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Carmen Andreescu
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
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18
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Zhu P, Tang J, Liang X, Luo Y, Wang J, Li Y, Xiao K, Li J, Deng Y, Jiang L, Xiao Q, Qi Y, Xie Y, Yang H, Zhu L, Tang Y, Huang C. Activation of liver X receptors protects oligodendrocytes in CA3 of stress-induced mice. Front Pharmacol 2022; 13:936045. [PMID: 35959443 PMCID: PMC9358133 DOI: 10.3389/fphar.2022.936045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 06/30/2022] [Indexed: 11/17/2022] Open
Abstract
Depression is a complex disorder that is associated with various structural abnormalities. Oligodendrocyte (OL) dysfunction is associated with the pathogenesis of depression and the promotion of hippocampal oligodendrocyte maturation and myelination could be a novel therapeutic strategy for ameliorating depressive behaviors. Recent studies have shown that activation of liver X receptors (LXRs) by GW3965 improves depressive phenotypes, but the effects of GW3965 on OL function and myelination in the hippocampus of depression remain relatively unclear. To address this issue, we investigated the effects of GW3965 on mature OL in the hippocampus and on the myelin sheaths of mice subjected to chronic unpredictable stress (CUS). Behavioral tests were performed to assess depressive behaviors. Then, the number of mature OLs (CC1+) in each hippocampal subregion was precisely quantified with immunohistochemical and stereological methods, and the density of newborn mature OLs (BrdU+/Olig2+/CC1+ cells) in each hippocampal subregion was quantified with immunofluorescence. In addition, myelin basic protein (MBP) staining intensity in the cornu ammonis 3 (CA3) region was assessed by using immunofluorescence. We found that both the number of CC1+ OLs and the density of BrdU+/Olig2+/CC1+ cells were obviously decreased in each hippocampal subregion of mice subjected to CUS, and 4 weeks of GW3965 treatment reversed these effects only in the CA3 region. Furthermore, the decreased MBP expression in the CA3 region of mice subjected to CUS was ameliorated by GW3965 treatment. Collectively, these results suggested that improvement of OL maturation and enhancement of myelination may be structural mechanisms underlying the antidepressant effects of LXR agonists.
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Affiliation(s)
- Peilin Zhu
- Department of Histology and Embryology, Chongqing Medical University, Chongqing, China
- Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
| | - Jing Tang
- Department of Histology and Embryology, Chongqing Medical University, Chongqing, China
- Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
| | - Xin Liang
- Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
- Department of Pathophysiology, Chongqing Medical University, Chongqing, China
| | - Yanmin Luo
- Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
- Department of Physiology, Chongqing Medical University, Chongqing, China
| | - Jin Wang
- Department of Histology and Embryology, Chongqing Medical University, Chongqing, China
- Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
| | - Yue Li
- Department of Histology and Embryology, Chongqing Medical University, Chongqing, China
- Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
| | - Kai Xiao
- Department of Histology and Embryology, Chongqing Medical University, Chongqing, China
- Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
| | - Jing Li
- Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
- Department of Physiology, Chongqing Medical University, Chongqing, China
| | - Yuhui Deng
- Department of Histology and Embryology, Chongqing Medical University, Chongqing, China
- Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
| | - Lin Jiang
- Lab Teaching and Management Center, Chongqing Medical University, Chongqing, China
| | - Qian Xiao
- Department of Radioactive Medicine, Chongqing Medical University, Chongqing, China
| | - Yingqiang Qi
- Department of Electron Microscope, Institute of Life Science, Chongqing Medical University, Chongqing, China
| | - Yuhan Xie
- Department of Histology and Embryology, Chongqing Medical University, Chongqing, China
- Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
| | - Hao Yang
- Department of Histology and Embryology, Chongqing Medical University, Chongqing, China
- Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
| | - Lin Zhu
- Department of Histology and Embryology, Chongqing Medical University, Chongqing, China
- Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
| | - Yong Tang
- Department of Histology and Embryology, Chongqing Medical University, Chongqing, China
- Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
| | - Chunxia Huang
- Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University, Chongqing, China
- Department of Physiology, Chongqing Medical University, Chongqing, China
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19
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Wang Y, Wang Y, Zhou J, Ge C, Shi Y, Hu Z. Volumetric changes in specific neurofunctional subfields of the hippocampus in major depressive disorder. Neuroreport 2022; 33:380-385. [PMID: 35594428 DOI: 10.1097/wnr.0000000000001794] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE There is evidence that hippocampal volume is abnormal in patients with major depressive disorder (MDD), but there have been no studies on volumetric changes in different subfields based on functional topography. This was investigated in the present study by comparing hippocampal neurofunctional subfield volumes between MDD patients and healthy control (HC) subjects. METHODS Patients with MDD (n = 44) and HCs (n = 27) recruited at Shanghai Traditional Chinese Medicine Integrated Hospital underwent a T1-weighted anatomical MRI scan in the sagittal orientation, and the data were used to calculate hippocampal subfield volumes. Logistic regression was used to evaluate the association between the volumes and risk of MDD. A nomogram for predicting MDD risk based on volume changes in different subfields was developed, and its predictive power was evaluated by calculating the concordance (C)-index. RESULTS Compared with HCs, MDD patients showed reduced volume in hippocampal neurofunctional subfields, specifically in left (L)1, right (R)1, and R2 (related to emotion) and L2, L3, and R4 (related to cognition and perception). The logistic regression analysis revealed that the risk of MDD was 4.59-, 5.8-, 8.33-, and 6.92-fold higher with atrophies of L1, L2, L3, and R4, respectively. A nomogram for predicting MDD risk was developed based on age; sex; and hippocampal L1, L2, L3, and R4 subfield volumes and showed good accuracy, with a C-index of 0.784. CONCLUSION Volumetric changes in the neurofunctional subfield of the hippocampus are potential imaging markers that can predict the occurrence of MDD.
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Affiliation(s)
- Yuning Wang
- Yueyang Clinical Medicine School, Shanghai University of Traditional Chinese Medicine
| | - Yi Wang
- Shanghai TCM-Integrated Hospital, Shanghai University of Traditional Chinese Medicine
| | - Jing Zhou
- Shanghai TCM-Integrated Hospital, Shanghai University of Traditional Chinese Medicine
| | - Chenjin Ge
- Shanghai TCM-Integrated Hospital, Shanghai University of Traditional Chinese Medicine
| | - Yin Shi
- Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Zhihai Hu
- Shanghai TCM-Integrated Hospital, Shanghai University of Traditional Chinese Medicine
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20
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An assessment of the existence of adult neurogenesis in humans and value of its rodent models for neuropsychiatric diseases. Mol Psychiatry 2022; 27:377-382. [PMID: 34667259 PMCID: PMC8967762 DOI: 10.1038/s41380-021-01314-8] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 09/08/2021] [Accepted: 09/22/2021] [Indexed: 12/14/2022]
Abstract
In sub-mammalian vertebrates like fishes, amphibians, and reptiles, new neurons are produced during the entire lifespan. This capacity diminishes considerably in birds and even more in mammals where it persists only in the olfactory system and hippocampal dentate gyrus. Adult neurogenesis declines even more drastically in nonhuman primates and recent evidence shows that this is basically extinct in humans. Why should such seemingly useful capacity diminish during primate evolution? It has been proposed that this occurs because of the need to retain acquired complex knowledge in stable populations of neurons and their synaptic connections during many decades of human life. In this review, we will assess critically the claim of significant adult neurogenesis in humans and show how current evidence strongly indicates that humans lack this trait. In addition, we will discuss the allegation of many rodent studies that adult neurogenesis is involved in psychiatric diseases and that it is a potential mechanism for human neuron replacement and regeneration. We argue that these reports, which usually neglect significant structural and functional species-specific differences, mislead the general population into believing that there might be a cure for a variety of neuropsychiatric diseases as well as stroke and brain trauma by genesis of new neurons and their incorporation into existing synaptic circuitry.
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21
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Du Preez A, Lefèvre-Arbogast S, González-Domínguez R, Houghton V, de Lucia C, Low DY, Helmer C, Féart C, Delcourt C, Proust-Lima C, Pallàs M, Sánchez-Pla A, Urpi-Sardà M, Ruigrok SR, Altendorfer B, Aigner L, Lucassen PJ, Korosi A, Manach C, Andres-Lacueva C, Samieri C, Thuret S. Impaired hippocampal neurogenesis in vitro is modulated by dietary-related endogenous factors and associated with depression in a longitudinal ageing cohort study. Mol Psychiatry 2022; 27:3425-3440. [PMID: 35794184 PMCID: PMC7613865 DOI: 10.1038/s41380-022-01644-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2021] [Revised: 05/09/2022] [Accepted: 05/23/2022] [Indexed: 12/20/2022]
Abstract
Environmental factors like diet have been linked to depression and/or relapse risk in later life. This could be partially driven by the food metabolome, which communicates with the brain via the circulatory system and interacts with hippocampal neurogenesis (HN), a form of brain plasticity implicated in depression aetiology. Despite the associations between HN, diet and depression, human data further substantiating this hypothesis are largely missing. Here, we used an in vitro model of HN to test the effects of serum samples from a longitudinal ageing cohort of 373 participants, with or without depressive symptomology. 1% participant serum was applied to human fetal hippocampal progenitor cells, and changes in HN markers were related to the occurrence of depressive symptoms across a 12-year period. Key nutritional, metabolomic and lipidomic biomarkers (extracted from participant plasma and serum) were subsequently tested for their ability to modulate HN. In our assay, we found that reduced cell death and increased neuronal differentiation were associated with later life depressive symptomatology. Additionally, we found impairments in neuronal cell morphology in cells treated with serum from participants experiencing recurrent depressive symptoms across the 12-year period. Interestingly, we found that increased neuronal differentiation was modulated by increased serum levels of metabolite butyrylcarnitine and decreased glycerophospholipid, PC35:1(16:0/19:1), levels - both of which are closely linked to diet - all in the context of depressive symptomology. These findings potentially suggest that diet and altered HN could subsequently shape the trajectory of late-life depressive symptomology.
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Affiliation(s)
- Andrea Du Preez
- grid.13097.3c0000 0001 2322 6764Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, SE5 9NU UK
| | - Sophie Lefèvre-Arbogast
- grid.508062.90000 0004 8511 8605University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, F-33000 Bordeaux, France
| | - Raúl González-Domínguez
- grid.5841.80000 0004 1937 0247Nutrition, Food Science and Gastronomy Department, Faculty of Pharmacy and Food Science, University of Barcelona, 08028 Barcelona, Spain ,grid.413448.e0000 0000 9314 1427CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, 0828 Barcelona, Spain
| | - Vikki Houghton
- grid.13097.3c0000 0001 2322 6764Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, SE5 9NU UK
| | - Chiara de Lucia
- grid.13097.3c0000 0001 2322 6764Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, SE5 9NU UK
| | - Dorrain Y. Low
- Université Clermont Auvergne, INRA, UMR1019, Human Nutrition Unit, F-63000 Clermont Ferrand, France
| | - Catherine Helmer
- grid.508062.90000 0004 8511 8605University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, F-33000 Bordeaux, France
| | - Catherine Féart
- grid.508062.90000 0004 8511 8605University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, F-33000 Bordeaux, France
| | - Cécile Delcourt
- grid.508062.90000 0004 8511 8605University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, F-33000 Bordeaux, France
| | - Cécile Proust-Lima
- grid.508062.90000 0004 8511 8605University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, F-33000 Bordeaux, France
| | - Mercè Pallàs
- grid.5841.80000 0004 1937 0247Pharmacology Section, Department of Pharmacology, Toxicology and Medicinal Chemistry, Faculty of Pharmacy and Food Sciences, and Institute of Neurosciences, University of Barcelona, Av. Joan XXIII, 27-31, E-08028 Barcelona, Spain
| | - Alex Sánchez-Pla
- grid.5841.80000 0004 1937 0247Nutrition, Food Science and Gastronomy Department, Faculty of Pharmacy and Food Science, University of Barcelona, 08028 Barcelona, Spain ,grid.413448.e0000 0000 9314 1427CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, 0828 Barcelona, Spain
| | - Mireia Urpi-Sardà
- grid.5841.80000 0004 1937 0247Nutrition, Food Science and Gastronomy Department, Faculty of Pharmacy and Food Science, University of Barcelona, 08028 Barcelona, Spain ,grid.413448.e0000 0000 9314 1427CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, 0828 Barcelona, Spain
| | - Silvie R. Ruigrok
- grid.7177.60000000084992262Brain Plasticity Group, Swammerdam Institute for Life Sciences, Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Barbara Altendorfer
- grid.21604.310000 0004 0523 5263Institute of Molecular Regenerative Medicine, Spinal Cord Injury and Tissue Regeneration Center Salzburg, Paracelsus Medical University, Salzburg, 5020 Austria
| | - Ludwig Aigner
- grid.21604.310000 0004 0523 5263Institute of Molecular Regenerative Medicine, Spinal Cord Injury and Tissue Regeneration Center Salzburg, Paracelsus Medical University, Salzburg, 5020 Austria
| | - Paul J. Lucassen
- grid.7177.60000000084992262Brain Plasticity Group, Swammerdam Institute for Life Sciences, Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Aniko Korosi
- grid.7177.60000000084992262Brain Plasticity Group, Swammerdam Institute for Life Sciences, Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Claudine Manach
- Université Clermont Auvergne, INRA, UMR1019, Human Nutrition Unit, F-63000 Clermont Ferrand, France
| | - Cristina Andres-Lacueva
- grid.5841.80000 0004 1937 0247Nutrition, Food Science and Gastronomy Department, Faculty of Pharmacy and Food Science, University of Barcelona, 08028 Barcelona, Spain ,grid.413448.e0000 0000 9314 1427CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, 0828 Barcelona, Spain
| | - Cécilia Samieri
- grid.508062.90000 0004 8511 8605University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, F-33000 Bordeaux, France
| | - Sandrine Thuret
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 9NU, UK. .,Department of Neurology, University Hospital Carl Gustav Carus, Technische Universität Dresden, 01307, Dresden, Germany.
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22
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Ekong MB, Iniodu CF. Nutritional therapy can reduce the burden of depression management in low income countries: A review. IBRO Neurosci Rep 2021; 11:15-28. [PMID: 34939062 PMCID: PMC8664701 DOI: 10.1016/j.ibneur.2021.06.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 02/06/2021] [Accepted: 06/22/2021] [Indexed: 12/15/2022] Open
Abstract
Depression is a serious mental and mood disorder with global health and economic burden. This burden may be overwhelming in low income countries, although there are insufficient data. Most antidepressant formulations are predicated on the monoamine, neuroendocrine and neuro-inflammation hypotheses, with little or no cognizance to other neurochemicals altered in depression. A nutritional strategy with or without conventional antidepressants is recommended, as nutrition plays vital roles in the onset, severity and duration of depression, with poor nutrition contributing to its pathogenesis. This review discusses nutritional potentials of utilizing omega-3 fatty acids, proteins, vitamins, minerals and herbs or their phytochemicals in the management of depression with the aim of reducing depression burden. Literature search of empirical data in books and journals in data bases including but not limited to PubMed, Scopus, Science Direct, Web of Science and Google Scholar that might contain discussions of sampling were sought, their full text obtained, and searched for relevant content to determine eligibility. Omega-3 fatty and amino acids had significant positive anti-depression outcomes, while vitamins and minerals although essential, enhanced omega-3 fatty and amino acids activities. Some herbs either as whole extracts or their phytochemicals/metabolites had significant positive anti-depression efficacy. Nutrition through the application of necessary food classes or herbs as well as their phytochemicals, may go a long way to effectively manage depression. This therefore will provide inexpensive, natural, and non-invasive therapeutic means with reduced adverse effects that can also be applied alongside clinical management. This nutritional strategy should be given more attention in research, assessment and treatment for those with depression and other mental illness in low income countries, especially in Africa.
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Affiliation(s)
- Moses B Ekong
- Department of Anatomy, Faculty of Basic Medical Sciences, University of Uyo, Nigeria
| | - Clementina F Iniodu
- Department of Anatomy, Faculty of Basic Medical Sciences, University of Uyo, Nigeria
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Fink A, Koschutnig K, Zussner T, Perchtold-Stefan CM, Rominger C, Benedek M, Papousek I. A two-week running intervention reduces symptoms related to depression and increases hippocampal volume in young adults. Cortex 2021; 144:70-81. [PMID: 34653905 DOI: 10.1016/j.cortex.2021.08.010] [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: 02/15/2021] [Revised: 06/09/2021] [Accepted: 08/10/2021] [Indexed: 10/20/2022]
Abstract
This study examined the effects of a two-week running intervention on depressive symptoms and structural changes of different subfields of the hippocampus in young adults from the general population. The intervention was realized in small groups of participants in a mostly forested area and was organized into seven units of about 60 min each. The study design included two intervention groups which were tested at three time points and which received the intervention time-delayed: The first group between the first and the second time point, and the second group between the second and the third time point (waiting control group). At each test session, magnetic resonance imaging (MRI) was performed and symptoms related to depression were measured by means of the Center for Epidemiological Studies Depression (CES-D) Scale. Results revealed a significant reduction of CES-D scores after the running intervention. The intervention also resulted in significant increases in the volume of the hippocampus, and reductions of CES-D scores right after the intervention were associated with increases in hippocampal volume. These findings add important new evidence on the beneficial role of aerobic exercise on depressive symptoms and related structural alterations of the hippocampus.
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Affiliation(s)
- Andreas Fink
- Institute of Psychology, University of Graz, Austria.
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24
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Suh JS, Fiori LM, Ali M, Harkness KL, Ramonas M, Minuzzi L, Hassel S, Strother SC, Zamyadi M, Arnott SR, Farzan F, Foster JA, Lam RW, MacQueen GM, Milev R, Müller DJ, Parikh SV, Rotzinger S, Sassi RB, Soares CN, Uher R, Kennedy SH, Turecki G, Frey BN. Hypothalamus volume and DNA methylation of stress axis genes in major depressive disorder: A CAN-BIND study report. Psychoneuroendocrinology 2021; 132:105348. [PMID: 34229186 DOI: 10.1016/j.psyneuen.2021.105348] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 06/14/2021] [Accepted: 06/25/2021] [Indexed: 11/28/2022]
Abstract
Dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis is considered one of the mechanisms underlying the development of major depressive disorder (MDD), but the exact nature of this dysfunction is unknown. We investigated the relationship between hypothalamus volume (HV) and blood-derived DNA methylation in MDD. We obtained brain MRI, clinical and molecular data from 181 unmedicated MDD and 90 healthy control (HC) participants. MDD participants received a 16-week standardized antidepressant treatment protocol, as part of the first Canadian Biomarker Integration Network in Depression (CAN-BIND) study. We collected bilateral HV measures via manual segmentation by two independent raters. DNA methylation and RNA sequencing were performed for three key HPA axis-regulating genes coding for the corticotropin-binding protein (CRHBP), glucocorticoid receptor (NR3C1) and FK506 binding protein 5 (FKBP5). We used elastic net regression to perform variable selection and assess predictive ability of methylation variables on HV. Left HV was negatively associated with duration of current episode (ρ = -0.17, p = 0.035). We did not observe significant differences in HV between MDD and HC or any associations between HV and treatment response at weeks 8 or 16, overall depression severity, illness duration or childhood maltreatment. We also did not observe any differentially methylated CpG sites between MDD and HC groups. After assessing functionality by correlating methylation levels with RNA expression of the respective genes, we observed that the number of functionally relevant CpG sites differed between MDD and HC groups in FKBP5 (χ2 = 77.25, p < 0.0001) and NR3C1 (χ2 = 7.29, p = 0.007). Cross-referencing functionally relevant CpG sites to those that were highly ranked in predicting HV in elastic net modeling identified one site from FKBP5 (cg03591753) and one from NR3C1 (cg20728768) within the MDD group. Stronger associations between DNA methylation, gene expression and HV in MDD suggest a novel putative molecular pathway of stress-related sensitivity in depression. Future studies should consider utilizing the epigenome and ultra-high field MR data which would allow the investigation of HV sub-fields.
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Affiliation(s)
- Jee Su Suh
- Neuroscience Graduate Program, McMaster University, Hamilton, ON, Canada; Mood Disorders Program and Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, ON, Canada
| | - Laura M Fiori
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Mohammad Ali
- Neuroscience Graduate Program, McMaster University, Hamilton, ON, Canada; Mood Disorders Program and Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, ON, Canada
| | - Kate L Harkness
- Department of Psychology, Queen's University, Kingston, ON, Canada
| | - Milita Ramonas
- Juravinski Hospital and Cancer Centre, Hamilton Health Sciences, Hamilton, ON, Canada
| | - Luciano Minuzzi
- Neuroscience Graduate Program, McMaster University, Hamilton, ON, Canada; Mood Disorders Program and Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, ON, Canada; Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Stefanie Hassel
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | | | - Mojdeh Zamyadi
- Rotman Research Institute, Baycrest, Toronto, ON, Canada
| | | | - Faranak Farzan
- eBrain Lab, School of Mechatronic Systems Engineering, Simon Fraser University, Surrey, BC, Canada
| | - Jane A Foster
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Glenda M MacQueen
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - Roumen Milev
- Departments of Psychiatry and Psychology, Queen's University, and Providence Care Hospital, Kingston, ON, Canada
| | - Daniel J Müller
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Centre for Addiction and Mental Health, Pharmacogenetics Research Clinic, Toronto, ON, Canada
| | - Sagar V Parikh
- University of Michigan Depression Center, Ann Arbor, MI, United States
| | - Susan Rotzinger
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Roberto B Sassi
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Claudio N Soares
- Departments of Psychiatry and Psychology, Queen's University, and Providence Care Hospital, Kingston, ON, Canada
| | - Rudolf Uher
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Sidney H Kennedy
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Centre for Depression and Suicide Studies, St. Michael's Hospital, Toronto, ON, Canada
| | - Gustavo Turecki
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Benicio N Frey
- Neuroscience Graduate Program, McMaster University, Hamilton, ON, Canada; Mood Disorders Program and Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, ON, Canada; Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada.
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25
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Association between the expression of lncRNA BASP-AS1 and volume of right hippocampal tail moderated by episode duration in major depressive disorder: a CAN-BIND 1 report. Transl Psychiatry 2021; 11:469. [PMID: 34508068 PMCID: PMC8433329 DOI: 10.1038/s41398-021-01592-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 08/16/2021] [Accepted: 08/26/2021] [Indexed: 02/08/2023] Open
Abstract
The pathophysiology of major depressive disorder (MDD) encompasses an array of changes at molecular and neurobiological levels. As chronic stress promotes neurotoxicity there are alterations in the expression of genes and gene-regulatory molecules. The hippocampus is particularly sensitive to the effects of stress and its posterior volumes can deliver clinically valuable information about the outcomes of antidepressant treatment. In the present work, we analyzed individuals with MDD (N = 201) and healthy controls (HC = 104), as part of the CAN-BIND-1 study. We used magnetic resonance imaging (MRI) to measure hippocampal volumes, evaluated gene expression with RNA sequencing, and assessed DNA methylation with the (Infinium MethylationEpic Beadchip), in order to investigate the association between hippocampal volume and both RNA expression and DNA methylation. We identified 60 RNAs which were differentially expressed between groups. Of these, 21 displayed differential methylation, and seven displayed a correlation between methylation and expression. We found a negative association between expression of Brain Abundant Membrane Attached Signal Protein 1 antisense 1 RNA (BASP1-AS1) and right hippocampal tail volume in the MDD group (β = -0.218, p = 0.021). There was a moderating effect of the duration of the current episode on the association between the expression of BASP1-AS1 and right hippocampal tail volume in the MDD group (β = -0.48, 95% C.I. [-0.80, -0.16]. t = -2.95 p = 0.004). In conclusion, we found that overexpression of BASP1-AS1 was correlated with DNA methylation, and was negatively associated with right tail hippocampal volume in MDD.
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26
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Businaro R, Vauzour D, Sarris J, Münch G, Gyengesi E, Brogelli L, Zuzarte P. Therapeutic Opportunities for Food Supplements in Neurodegenerative Disease and Depression. Front Nutr 2021; 8:669846. [PMID: 34055858 PMCID: PMC8160227 DOI: 10.3389/fnut.2021.669846] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 04/19/2021] [Indexed: 12/16/2022] Open
Abstract
Emerging evidence is showing nutrition as a crucial factor in the high prevalence and incidence of neurodegenerative mental disorders. Preventive interventions on neuroinflammation seem to be able to interfere with neurodegeneration. Supplementation of essential nutrients, such as long-chain-polyunsaturated fatty acids, vitamin E and mineral elements, may minimize inflammation, enhancing antioxidative defense, and lowering the risk and incidence of age-related diseases, such as cardiovascular diseases and neurodegenerative diseases. This manuscript reviews the current evidence on the role of neuroinflammation in the pathophysiology of neurodegenerative and mental disorders, and preventive strategies for food supplementation in these neuropsychiatric diseases. Dietary supplementation-based strategies have been demonstrated to be effective in subjects with mild cognitive impairment, while weaker results have been obtained in patients with advance neurodegenerative disease. Adjunctive supplementation has also been demonstrated to improve depression, this being of marked benefit considering the comorbidity between cognitive impairment/dementia and depression. Further research is needed to improve the prescriptive precision of supplementation in patients, and to better understand potential interactions with clinical and pharmacokinetic factors.
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Affiliation(s)
- Rita Businaro
- Department of Medico-Surgical Sciences and Biotechnologies, Sapienza University of Rome, Rome, Italy
| | - David Vauzour
- Faculty of Medicine and Health Sciences, Norwich Medical School, University of East Anglia, Norwich, United Kingdom
| | - Jerome Sarris
- NICM Health Research Institute, Western Sydney University, Westmead, NSW, Australia.,Professorial Unit, The Melbourne Clinic, Department of Psychiatry, Melbourne University, Melbourne, VIC, Australia
| | - Gerald Münch
- Pharmacology Unit, School of Medicine, Western Sydney University, Campbelltown, NSW, Australia
| | - Erika Gyengesi
- Pharmacology Unit, School of Medicine, Western Sydney University, Campbelltown, NSW, Australia
| | | | - Pedro Zuzarte
- Psychiatric Clinic, Faculty of Medicine, University of Lisbon, Lisbon, Portugal.,Neuropsychiatry Research Department, GNR Clinical Center, Lisbon, Portugal
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27
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Santini T, Koo M, Farhat N, Campos VP, Alkhateeb S, Vieira MAC, Butters MA, Rosano C, Aizenstein HJ, Mettenburg J, Novelli EM, Ibrahim TS. Analysis of hippocampal subfields in sickle cell disease using ultrahigh field MRI. Neuroimage Clin 2021; 30:102655. [PMID: 34215139 PMCID: PMC8102634 DOI: 10.1016/j.nicl.2021.102655] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 03/28/2021] [Accepted: 03/29/2021] [Indexed: 12/05/2022]
Abstract
Sickle cell disease (SCD) is an inherited hemoglobinopathy that causes organ dysfunction, including cerebral vasculopathy and neurological complications. Hippocampal segmentation with newer and advanced 7 Tesla (7T) MRI protocols has revealed atrophy in specific subregions in other neurodegenerative and neuroinflammatory diseases, however, there is limited evidence of hippocampal involvement in SCD. Thus, we explored whether SCD may be also associated with abnormalities in hippocampal subregions. We conducted 7T MRI imaging in individuals with SCD, including the HbSS, HbSC and HbS/beta thalassemia genotypes (n = 53), and healthy race and age-matched controls (n = 47), using a customized head coil. Both T1- and T2-weighted images were used for automatic segmentation of the hippocampal subfields. Individuals with SCD had, on average, significantly smaller volume of the region including the Dentate Gyrus and Cornu Ammonis (CA) 2 and 3 as compared to the control group. Other hippocampal subregions also showed a trend towards smaller volumes in the SCD group. These findings support and extend previous reports of reduced volume in the temporal lobe in SCD patients. Further studies are necessary to investigate the mechanisms that lead to structural changes in the hippocampus subfields and their relationship with cognitive performance in SCD patients.
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Affiliation(s)
- Tales Santini
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Minseok Koo
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Nadim Farhat
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Vinicius P Campos
- Department of Electrical and Computer Engineering, University of São Paulo, São Carlos, SP, Brazil
| | - Salem Alkhateeb
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Marcelo A C Vieira
- Department of Electrical and Computer Engineering, University of São Paulo, São Carlos, SP, Brazil
| | - Meryl A Butters
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Caterina Rosano
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Howard J Aizenstein
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States; Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Joseph Mettenburg
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Enrico M Novelli
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States; Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, PA, United States.
| | - Tamer S Ibrahim
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States; Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States; Department of Radiology, University of Pittsburgh, Pittsburgh, PA, United States.
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28
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Hubachek S, Botdorf M, Riggins T, Leong HC, Klein DN, Dougherty LR. Hippocampal subregion volume in high-risk offspring is associated with increases in depressive symptoms across the transition to adolescence. J Affect Disord 2021; 281:358-366. [PMID: 33348179 PMCID: PMC7856102 DOI: 10.1016/j.jad.2020.12.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 11/18/2020] [Accepted: 12/05/2020] [Indexed: 11/16/2022]
Abstract
BACKGROUND The hippocampus has been implicated in the pathophysiology of depression. This study examined whether youth hippocampal subregion volumes were differentially associated with maternal depression history and youth's depressive symptoms across the transition to adolescence. METHODS 74 preadolescent offspring (Mage=10.74+/-0.84 years) of mothers with (n = 33) and without a lifetime depression history (n = 41) completed a structural brain scan. Youth depressive symptoms were assessed with clinical interviews and mother- and youth-reports prior to the neuroimaging assessment at age 9 (Mage=9.08+/-0.29 years), at the neuroimaging assessment, and in early adolescence (Mage=12.56+/-0.40 years). RESULTS Maternal depression was associated with preadolescent offspring's reduced bilateral hippocampal head volumes and increased left hippocampal body volume. Reduced bilateral head volumes were associated with offspring's increased concurrent depressive symptoms. Furthermore, reduced right hippocampal head volume mediated associations between maternal depression and increases in offspring depressive symptoms from age 9 to age 12. LIMITATIONS This study included a modest-sized sample that was oversampled for early temperamental characteristics, one neuroimaging assessment, and no correction for multiple comparisons. CONCLUSIONS Findings implicate reductions in hippocampal head volume in the intergenerational transmission of risk from parents to offspring.
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Dai D, Lacadie CM, Holmes SE, Cool R, Anticevic A, Averill C, Abdallah C, Esterlis I. Ketamine Normalizes the Structural Alterations of Inferior Frontal Gyrus in Depression. CHRONIC STRESS 2021; 4:2470547020980681. [PMID: 33426409 PMCID: PMC7758564 DOI: 10.1177/2470547020980681] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 11/20/2020] [Indexed: 12/20/2022]
Abstract
Background Ketamine is a novel fast-acting antidepressant. Acute ketamine treatment can reverse microstructure deficits and normalize functional alterations in the brain, but little is known about the impacts of ketamine on brain volumes in individuals with depression. Methods We used 3 T magnetic resonance imaging (MRI) and tensorbased morphological methods to investigate the regional volume differences for 29 healthy control (HC) subjects and 21 subjects with major depressive disorder (MDD), including 10 subjects with comorbid post-traumatic stress disorder (PTSD). All the subjects participated in MRI scanning before and 24 h post intravenous ketamine infusion. The effects of acute ketamine administration on HC, MDD, and MDD/PTSD groups were examined separately by whole-brain voxel-wise t-tests. Results Our data showed smaller volume of inferior frontal gyrus (IFG, opercular part) in MDD and MDD/PTSD subjects compared to HC, and a significant correlation between opercular IFG volume and depressive severity in MDD subjects only. Ketamine administration normalized the structural alterations of opercular IFG in both MDD and MDD/PTSD groups, and significantly improved depressive and PTSD symptoms. Twenty-four hours after a single ketamine infusion, there were two clusters of voxels with volume changes in MDD subjects, including significantly increased volumes of opercular IFG. No significant structural alterations were found in the MDD/PTSD or HC groups. Conclusion These findings provide direct evidence that acute ketamine administration can normalize structural alterations associated with depression and highlight the importance of IFG in the guidance of future therapeutic targets.
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Affiliation(s)
- Dan Dai
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Cheryl M Lacadie
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut
| | - Sophie E Holmes
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Ryan Cool
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Alan Anticevic
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut.,Department of Psychology, Yale University School of Medicine, New Haven, Connecticut
| | - Chris Averill
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut.,Clinical Neurosciences Division, National Center for PTSD, US Department of Veterans Affairs, West Haven, Connecticut
| | - Chadi Abdallah
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut.,Clinical Neurosciences Division, National Center for PTSD, US Department of Veterans Affairs, West Haven, Connecticut.,Michael E. DeBakey, VA Medical Center, Houston, Texas.,Menninger Department of Psychiatry, Baylor College of Medicine, Houston, Texas
| | - Irina Esterlis
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut.,Department of Psychology, Yale University School of Medicine, New Haven, Connecticut.,Clinical Neurosciences Division, National Center for PTSD, US Department of Veterans Affairs, West Haven, Connecticut
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Tai HH, Cha J, Vedaei F, Dunlop BW, Craighead WE, Mayberg HS, Choi KS. Treatment-Specific Hippocampal Subfield Volume Changes With Antidepressant Medication or Cognitive-Behavior Therapy in Treatment-Naive Depression. Front Psychiatry 2021; 12:718539. [PMID: 35002790 PMCID: PMC8739262 DOI: 10.3389/fpsyt.2021.718539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 11/08/2021] [Indexed: 12/02/2022] Open
Abstract
Background: Hippocampal atrophy has been consistently reported in major depressive disorder with more recent focus on subfields. However, literature on hippocampal volume changes after antidepressant treatment has been limited. The first-line treatments for depression include antidepressant medication (ADM) or cognitive-behavior therapy (CBT). To understand the differential effects of CBT and ADM on the hippocampus, we investigated the volume alterations of hippocampal subfields with treatment, outcome, and chronicity in treatment-naïve depression patients. Methods: Treatment-naïve depressed patients from the PReDICT study were included in this analysis. A total of 172 patients who completed 12 weeks of randomized treatment with CBT (n = 45) or ADM (n = 127) were included for hippocampal subfield volume analysis. Forty healthy controls were also included for the baseline comparison. Freesurfer 6.0 was used to segment 26 hippocampal substructures and bilateral whole hippocampus from baseline and week 12 structural MRI scans. A generalized linear model with covariates of age and gender was used for group statistical tests. A linear mixed model for the repeated measures with covariates of age and gender was used to examine volumetric changes over time and the contributing effects of treatment type, outcome, and illness chronicity. Results: Of the 172 patients, 85 achieved remission (63/127 ADM, 22/45 CBT). MDD patients showed smaller baseline volumes than healthy controls in CA1, CA3, CA4, parasubiculum, GC-ML-DG, Hippocampal Amygdala Transition Area (HATA), and fimbria. Over 12 weeks of treatment, further declines in the volumes of CA1, fimbria, subiculum, and HATA were observed regardless of treatment type or outcome. CBT remitters, but not ADM remitters, showed volume reduction in the right hippocampal tail. Unlike ADM remitters, ADM non-responders had a decline in volume in the bilateral hippocampal tails. Baseline volume of left presubiculum (regardless of treatment type) and right fimbria and HATA in CBT patients were correlated with a continuous measure of clinical improvement. Chronicity of depression had no effect on any measures of hippocampal subfield volumes. Conclusion: Two first-line antidepressant treatments, CBT and ADM, have different effects on hippocampal tail after 12 weeks. This finding suggests that remission achieved via ADM may protect against progressive hippocampal atrophy by altering neuronal plasticity or supporting neurogenesis. Studies with multimodal neuroimaging, including functional and structural analysis, are needed to assess further the impact of two different antidepressant treatments on hippocampal subfields.
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Affiliation(s)
- Hua-Hsin Tai
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Jungho Cha
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Faezeh Vedaei
- Thomas Jefferson University, Philadelphia, PA, United States
| | - Boadie W Dunlop
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States
| | - W Edward Craighead
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States
| | - Helen S Mayberg
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Ki Sueng Choi
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, United States
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Hippocampal subfield abnormalities and memory functioning in children with fetal alcohol Spectrum disorders. Neurotoxicol Teratol 2020; 83:106944. [PMID: 33232797 DOI: 10.1016/j.ntt.2020.106944] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 11/06/2020] [Accepted: 11/15/2020] [Indexed: 01/26/2023]
Abstract
BACKGROUND Prenatal alcohol exposure (PAE) affects early brain development and has been associated with hippocampal damage. Animal models of PAE have suggested that some subfields of the hippocampus may be more susceptible to damage than others. Recent advances in structural MRI processing now allow us to examine the morphology of hippocampal subfields in humans with PAE. METHOD Structural MRI scans were collected from 40 children with PAE and 39 typically developing children (ages 8-16). The images were processed using the Human Connectome Project Minimal Preprocessing Pipeline (v4.0.1) and the Hippocampal Subfields package (v21) from FreeSurfer. Using a large dataset of typically developing children enrolled in the Human Connectome Project in Development (HCP-D) for normative standards, we computed age-specific volumetric z-scores for our two samples. Using these norm-adjusted hippocampal subfield volumes, comparisons were performed between children with PAE and typically developing children, controlling for total intracranial volume. Lastly, we investigated whether subfield volumes correlated with episodic memory (i.e., Picture Sequence Memory test of the NIH toolbox). RESULTS Five subfields had significantly smaller adjusted volumes in children with PAE than in typically developing controls: CA1, CA4, subiculum, presubiculum, and the hippocampal tail. Subfield volumes were not significantly correlated with episodic memory. CONCLUSIONS The results suggest that several regions of the hippocampus may be particularly affected by PAE. The finding of smaller CA1 volumes parallels previous reports in rodent models. The novel findings of decreased volume in the subicular cortex, CA4 and the hippocampal tail suggest avenues for future research.
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32
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Spuhler K, Serrano-Sosa M, Cattell R, DeLorenzo C, Huang C. Full-count PET recovery from low-count image using a dilated convolutional neural network. Med Phys 2020; 47:4928-4938. [PMID: 32687608 DOI: 10.1002/mp.14402] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Revised: 06/11/2020] [Accepted: 07/10/2020] [Indexed: 01/18/2023] Open
Abstract
PURPOSE Positron emission tomography (PET) is an essential technique in many clinical applications that allows for quantitative imaging at the molecular level. This study aims to develop a denoising method using a novel dilated convolutional neural network (CNN) to recover full-count images from low-count images. METHODS We adopted similar hierarchical structures as the conventional U-Net and incorporated dilated kernels in each convolution to allow the network to observe larger, more robust features within the image without the requirement of downsampling and upsampling internal representations. Our dNet was trained alongside a U-Net for comparison. Both models were evaluated using a leave-one-out cross-validation procedure on a dataset of 35 subjects (~3500 slabs), which were obtained from an ongoing 18 F-Fluorodeoxyglucose (FDG) study. Low-count PET data (10% count) were generated by randomly selecting one-tenth of all events in the associated listmode file. Analysis was done on the static image from the last 10 minutes of emission data. Both low-count PET and full-count PET were reconstructed using ordered subset expectation maximization (OSEM). Objective image quality metrics, including mean absolute percent error (MAPE), peak signal-to-noise ratio (PSNR), and structural similarity index metric (SSIM), were used to analyze the deep learning methods. Both deep learning methods were further compared to a traditional Gaussian filtering method. Further, region of interest (ROI) quantitative analysis was also used to compare U-Net and dNet architectures. RESULTS Both the U-Net and our proposed network were successfully trained to synthesize full-count PET images from the generated low-count PET images. Compared to low-count PET and Gaussian filtering, both deep learning methods improved MAPE, PSNR, and SSIM. Our dNet also systematically outperformed U-Net on all three metrics (MAPE: 4.99 ± 0.68 vs 5.31 ± 0.76, P < 0.01; PSNR: 31.55 ± 1.31 dB vs 31.05 ± 1.39, P < 0.01; SSIM: 0.9513 ± 0.0154 vs 0.9447 ± 0.0178, P < 0.01). ROI quantification showed greater quantitative improvements using dNet over U-Net. CONCLUSION This study proposed a novel approach of using dilated convolutions for recovering full-count PET images from low-count PET images.
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Affiliation(s)
- Karl Spuhler
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA
| | - Mario Serrano-Sosa
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA
| | - Renee Cattell
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA
| | - Christine DeLorenzo
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA
- Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA
| | - Chuan Huang
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA
- Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA
- Department of Radiology, Stony Brook University, Stony Brook, NY, USA
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Lee J, Song Y, Won E, Bang M, Lee SH. Higher Rightward Laterality of the Hippocampal Tail and Its Association with Early Trauma in Panic Disorder. CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE : THE OFFICIAL SCIENTIFIC JOURNAL OF THE KOREAN COLLEGE OF NEUROPSYCHOPHARMACOLOGY 2020; 18:311-321. [PMID: 32329311 PMCID: PMC7242112 DOI: 10.9758/cpn.2020.18.2.311] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Revised: 12/23/2019] [Accepted: 02/17/2020] [Indexed: 01/13/2023]
Abstract
OBJECTIVE Early trauma (ET) is widely recognized as a contributing factor to the development of panic disorder (PD) in patients. However, there is a dearth of research on the specific volumes of hippocampal subregions and their laterality with respect to ET and PD. METHODS A total of 30 subjects with PD and 30 age- and sex-matched healthy controls (HCs) were included in this study. All the subjects were evaluated by 3T-magnetic resonance imaging. FreeSurfer version 6.0 was used for volumetric analysis of the hippocampal subregions and their laterality. A shortened version of the Early Trauma Inventory Self Report (ETISR) as well as Anxiety Sensitivity Inventory-Revised (ASI-R), and Panic Disorder Severity Scale were utilized for analysis. RESULTS Multivariate analysis of variance showed that the volume of the right hippocampal tail and laterality indices (LIs) of the hippocampal body and tail were significantly larger in subjects with PD relative to HCs. The significance of the observations remained unchanged after multivariate analysis of covariance, controlling for age, sex, years of education, medication, depressive symptoms, and intracranial volume as covariates. The LIs of the hippocampal tails that showed a significant correlation to ETISR emotional and physical subscales were also associated with ASI-R for cardiovascular symptoms in PD. CONCLUSION Our study displayed an increased rightward lateralization of the hippocampal tails in subjects with PD compared with HCs. This alteration in the brain, which was associated with early emotional and physical trauma, would negatively affect anxiety sensitivity to cardiovascular symptoms in subjects with PD.
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Affiliation(s)
- Joonho Lee
- Departments of Psychiatry, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Korea
| | - Yoonsu Song
- Departments of Psychiatry, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Korea
| | - Eunsoo Won
- Departments of Psychiatry, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Korea
| | - Minji Bang
- Departments of Psychiatry, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Korea
| | - Sang-Hyuk Lee
- Departments of Psychiatry, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Korea
- Clinical Pharmacology and Therapeutics, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Korea
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Severe J, Greden JF, Reddy P. Consequences of Recurrence of Major Depressive Disorder: Is Stopping Effective Antidepressant Medications Ever Safe? FOCUS (AMERICAN PSYCHIATRIC PUBLISHING) 2020; 18:120-128. [PMID: 33162849 PMCID: PMC7587881 DOI: 10.1176/appi.focus.20200008] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
According to the World Health Organization, major depressive disorder is the world's leading cause of disability. If clinical remission is not attained and sustained, episodes tend to recur with greater severity and with lessening responsivity to conventional treatments. Reasonably well-established clues and guidelines are presented about the high risk and profound consequences of recurrence of major depressive disorder if successful antidepressant treatments are discontinued. The authors describe actions required to achieve a "lifetime wellness" focus for treatment. Current approaches would need to be transformed from attainment of clinical remission to attainment and maintenance of lifetime wellness, with the knowledge that some individuals may need continuous treatment. Risk factors would need to be assessed and used to formulate clinical treatment guidelines for risk of recurrence. Clinical trials would need to be greatly lengthened. Measurement-based care and precision medicine would be the foundation for informing clinical decisions. The authors provide guidance in determining how to discontinue antidepressants if that decision is made despite risks.
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Affiliation(s)
| | - John F Greden
- Department of Psychiatry, University of Michigan, Ann Arbor
| | - Priyanka Reddy
- Department of Psychiatry, University of Michigan, Ann Arbor
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