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Vike NL, Bari S, Kim BW, Katsaggelos AK, Blood AJ, Breiter HC. Characterizing major depressive disorder and substance use disorder using heatmaps and variable interactions: The utility of operant behavior and brain structure relationships. PLoS One 2024; 19:e0299528. [PMID: 38466739 PMCID: PMC10927130 DOI: 10.1371/journal.pone.0299528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 02/13/2024] [Indexed: 03/13/2024] Open
Abstract
BACKGROUND Rates of depression and addiction have risen drastically over the past decade, but the lack of integrative techniques remains a barrier to accurate diagnoses of these mental illnesses. Changes in reward/aversion behavior and corresponding brain structures have been identified in those with major depressive disorder (MDD) and cocaine-dependence polysubstance abuse disorder (CD). Assessment of statistical interactions between computational behavior and brain structure may quantitatively segregate MDD and CD. METHODS Here, 111 participants [40 controls (CTRL), 25 MDD, 46 CD] underwent structural brain MRI and completed an operant keypress task to produce computational judgment metrics. Three analyses were performed: (1) linear regression to evaluate groupwise (CTRL v. MDD v. CD) differences in structure-behavior associations, (2) qualitative and quantitative heatmap assessment of structure-behavior association patterns, and (3) the k-nearest neighbor machine learning approach using brain structure and keypress variable inputs to discriminate groups. RESULTS This study yielded three primary findings. First, CTRL, MDD, and CD participants had distinct structure-behavior linear relationships, with only 7.8% of associations overlapping between any two groups. Second, the three groups had statistically distinct slopes and qualitatively distinct association patterns. Third, a machine learning approach could discriminate between CTRL and CD, but not MDD participants. CONCLUSIONS These findings demonstrate that variable interactions between computational behavior and brain structure, and the patterns of these interactions, segregate MDD and CD. This work raises the hypothesis that analysis of interactions between operant tasks and structural neuroimaging might aide in the objective classification of MDD, CD and other mental health conditions.
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Affiliation(s)
- Nicole L. Vike
- Department of Computer Science, University of Cincinnati, Cincinnati, Ohio, United States of America
| | - Sumra Bari
- Department of Computer Science, University of Cincinnati, Cincinnati, Ohio, United States of America
| | - Byoung Woo Kim
- Department of Computer Science, University of Cincinnati, Cincinnati, Ohio, United States of America
| | - Aggelos K. Katsaggelos
- Department of Electrical and Computer Engineering, Northwestern University, Evanston, Illinois, United States of America
- Department of Computer Science, Northwestern University, Evanston, Illinois, United States of America
- Department of Radiology, Northwestern University, Chicago, Illinois, United States of America
| | - Anne J. Blood
- Department of Psychiatry, Mood and Motor Control Laboratory (MAML), Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Psychiatry, Laboratory of Neuroimaging and Genetics, Massachusetts General Hospital and Harvard School of Medicine, Boston, Massachusetts, United States of America
| | - Hans C. Breiter
- Department of Computer Science, University of Cincinnati, Cincinnati, Ohio, United States of America
- Department of Psychiatry, Mood and Motor Control Laboratory (MAML), Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Psychiatry, Laboratory of Neuroimaging and Genetics, Massachusetts General Hospital and Harvard School of Medicine, Boston, Massachusetts, United States of America
- Department of Biomedical Engineering, University of Cincinnati, Cincinnati, Ohio, United States of America
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Bae EB, Han KM. A structural equation modeling approach using behavioral and neuroimaging markers in major depressive disorder. J Psychiatr Res 2024; 171:246-255. [PMID: 38325105 DOI: 10.1016/j.jpsychires.2024.02.014] [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: 07/18/2023] [Revised: 12/16/2023] [Accepted: 02/01/2024] [Indexed: 02/09/2024]
Abstract
Major depressive disorder (MDD) has consistently proven to be a multifactorial and highly comorbid disease. Despite recent depression-related research demonstrating causalities between MDD-related factors and a small number of variables, including brain structural changes, a high-statistical power analysis of the various factors is yet to be conducted. We retrospectively analyzed data from 155 participants (84 healthy controls and 71 patients with MDD). We used magnetic resonance imaging and diffusion tensor imaging data, scales assessing childhood trauma, depression severity, cognitive dysfunction, impulsivity, and suicidal ideation. To simultaneously evaluate the causalities between multivariable, we implemented two types of MDD-specified structural equation models (SEM), the behavioral and neurobehavioral models. Behavioral SEM showed significant results in the MDD group: Comparative Fit Index [CFI] = 1.000, Root Mean Square Error of Approximation [RMSEA]) = 0.000), with a strong correlation in the scales for childhood trauma, depression severity, suicidal ideation, impulsivity, and cognitive dysfunction. Based on behavioral SEM, we established neurobehavioral models showing the best-fit in MDD, especially including the right cingulate cortex, central to the posterior corpus callosum, right putamen, pallidum, whole brainstem, and ventral diencephalon, including the thalamus (CFI >0.96, RMSEA <0.05). Our MDD-specific model revealed that the limbic-associated regions are strongly connected with childhood trauma rather than depression severity, and that they independently affect suicidal ideation and cognitive dysfunction. Furthermore, cognitive dysfunction could affect impulsivity.
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Affiliation(s)
- Eun Bit Bae
- Research Institute for Medical Bigdata Science, Korea University, Seoul, Republic of Korea; Department of Psychiatry, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Kyu-Man Han
- Department of Psychiatry, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea.
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Chen Y, Jia L, Gao W, Wu C, Mu Q, Fang Z, Hu S, Huang M, Zhang P, Lu S. Alterations of brainstem volume in patients with first-episode and recurrent major depressive disorder. BMC Psychiatry 2023; 23:687. [PMID: 37735630 PMCID: PMC10512480 DOI: 10.1186/s12888-023-05146-4] [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: 06/15/2023] [Accepted: 08/28/2023] [Indexed: 09/23/2023] Open
Abstract
BACKGROUND Major depressive disorder (MDD) is a prevalent mental health condition characterized by recurrent episodes in a substantial proportion of patients. The number of previous episodes is one of the most crucial predictors of depression recurrence. However, the underlying neural mechanisms remain unclear. To date, there have been limited neuroimaging studies investigating morphological changes of the brainstem in patients with first-episode MDD (FMDD) and recurrent MDD (RMDD). This study aimed to examine volumetric changes of individual brainstem regions in relation to the number of previous episodes and disease duration. METHOD A total of 111 individuals including 36 FMDD, 25 RMDD, and 50 healthy controls (HCs) underwent T1-weighted structural magnetic resonance imaging scans. A Bayesian segmentation algorithm was used to analyze the volume of each brainstem region, including the medulla oblongata, pons, midbrain, and superior cerebellar peduncle (SCP), as well as the whole brainstem volume. Analyses of variance (ANOVA) were performed to obtain brain regions with significant differences among three groups and then post hoc tests were calculated for inter-group comparisons. Partial correlation analyses were further conducted to identify associations between regional volumes and clinical features. RESULTS The ANOVA revealed significant brainstem volumetric differences among three groups in the pons, midbrain, SCP, and the whole brainstem (F = 3.996 ~ 5.886, adjusted p = 0.015 ~ 0.028). As compared with HCs, both groups of MDD patients showed decreased volumes in the pons as well as the entire brainstem (p = 0.002 ~ 0.034), however, only the FMDD group demonstrated a significantly reduced volume in the midbrain (p = 0.003). Specifically, the RMDD group exhibited significantly decreased SCP volume when comparing to both FMDD (p = 0.021) group and HCs (p = 0.008). Correlation analyses revealed that the SCP volumes were negatively associated with the number of depressive episodes (r=-0.36, p < 0.01) and illness duration (r=-0.28, p = 0.035) in patients with MDD. CONCLUSION The present findings provided evidence of decreased brainstem volume involving in the pathophysiology of MDD, particularly, volumetric reduction in the SCP might represent a neurobiological marker for RMDD. Further research is needed to confirm our observations and deepen our understanding of the neural mechanisms underlying depression recurrence.
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Affiliation(s)
- Yue Chen
- Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory of Mental Disorder's Management of Zhejiang Province, Zhejiang Engineering Center for Mathematical Mental Health, No. 79 Qingchun Road, Hangzhou, Zhejiang, 310003, China
- Faculty of Clinical Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Lili Jia
- Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory of Mental Disorder's Management of Zhejiang Province, Zhejiang Engineering Center for Mathematical Mental Health, No. 79 Qingchun Road, Hangzhou, Zhejiang, 310003, China
- Faculty of Clinical Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Department of Clinical Psychology, The Fifth Peoples' Hospital of Lin'an District, Hangzhou, Zhejiang, China
| | - Weijia Gao
- Department of Child Psychology, The Children's Hospital, National Clinical Research Center for Child Health, Zhejiang University School of Medicine, National Children's Regional Medical Center, Hangzhou, Zhejiang, China
| | - Congchong Wu
- Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory of Mental Disorder's Management of Zhejiang Province, Zhejiang Engineering Center for Mathematical Mental Health, No. 79 Qingchun Road, Hangzhou, Zhejiang, 310003, China
- Faculty of Clinical Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Qingli Mu
- Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory of Mental Disorder's Management of Zhejiang Province, Zhejiang Engineering Center for Mathematical Mental Health, No. 79 Qingchun Road, Hangzhou, Zhejiang, 310003, China
- Faculty of Clinical Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Zhe Fang
- Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory of Mental Disorder's Management of Zhejiang Province, Zhejiang Engineering Center for Mathematical Mental Health, No. 79 Qingchun Road, Hangzhou, Zhejiang, 310003, China
- Faculty of Clinical Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Shaohua Hu
- Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory of Mental Disorder's Management of Zhejiang Province, Zhejiang Engineering Center for Mathematical Mental Health, No. 79 Qingchun Road, Hangzhou, Zhejiang, 310003, China
| | - Manli Huang
- Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory of Mental Disorder's Management of Zhejiang Province, Zhejiang Engineering Center for Mathematical Mental Health, No. 79 Qingchun Road, Hangzhou, Zhejiang, 310003, China
| | - Peng Zhang
- Department of Psychiatry, Affiliated Xiaoshan Hospital, Hangzhou Normal University, No. 728 North Yucai Road, Hangzhou, Zhejiang, 311200, China.
| | - Shaojia Lu
- Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory of Mental Disorder's Management of Zhejiang Province, Zhejiang Engineering Center for Mathematical Mental Health, No. 79 Qingchun Road, Hangzhou, Zhejiang, 310003, China.
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4
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Kerr WT, Tatekawa H, Lee JK, Karimi AH, Sreenivasan SS, O'Neill J, Smith JM, Hickman LB, Savic I, Nasrullah N, Espinoza R, Narr K, Salamon N, Beimer NJ, Hadjiiski LM, Eliashiv DS, Stacey WC, Engel J, Feusner JD, Stern JM. Clinical MRI morphological analysis of functional seizures compared to seizure-naïve and psychiatric controls. Epilepsy Behav 2022; 134:108858. [PMID: 35933959 DOI: 10.1016/j.yebeh.2022.108858] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 06/26/2022] [Accepted: 07/15/2022] [Indexed: 11/15/2022]
Abstract
PURPOSE Functional seizures (FS), also known as psychogenic nonepileptic seizures (PNES), are physical manifestations of acute or chronic psychological distress. Functional and structural neuroimaging have identified objective signs of this disorder. We evaluated whether magnetic resonance imaging (MRI) morphometry differed between patients with FS and clinically relevant comparison populations. METHODS Quality-screened clinical-grade MRIs were acquired from 666 patients from 2006 to 2020. Morphometric features were quantified with FreeSurfer v6. Mixed-effects linear regression compared the volume, thickness, and surface area within 201 regions-of-interest for 90 patients with FS, compared to seizure-naïve patients with depression (n = 243), anxiety (n = 68), and obsessive-compulsive disorder (OCD, n = 41), respectively, and to other seizure-naïve controls with similar quality MRIs, accounting for the influence of multiple confounds including depression and anxiety based on chart review. These comparison populations were obtained through review of clinical records plus research studies obtained on similar scanners. RESULTS After Bonferroni-Holm correction, patients with FS compared with seizure-naïve controls exhibited thinner bilateral superior temporal cortex (left 0.053 mm, p = 0.014; right 0.071 mm, p = 0.00006), thicker left lateral occipital cortex (0.052 mm, p = 0.0035), and greater left cerebellar white-matter volume (1085 mm3, p = 0.0065). These findings were not accounted for by lower MRI quality in patients with FS. CONCLUSIONS These results reinforce prior indications of structural neuroimaging correlates of FS and, in particular, distinguish brain morphology in FS from that in depression, anxiety, and OCD. Future work may entail comparisons with other psychiatric disorders including bipolar and schizophrenia, as well as exploration of brain structural heterogeneity within FS.
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Affiliation(s)
- Wesley T Kerr
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Neurology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA.
| | - Hiroyuki Tatekawa
- Department of Radiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - John K Lee
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Amir H Karimi
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - Siddhika S Sreenivasan
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - Joseph O'Neill
- Division of Child & Adolescent Psychiatry, Jane & Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA; Brain Research Institute, University of California Los Angeles, Los Angeles, CA, USA
| | - Jena M Smith
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - L Brian Hickman
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Ivanka Savic
- Department of Women's and Children's Health, Karolinska Institute and Neurology Clinic, Karolinksa University Hospital, Karolinska Universitetssjukhuset, Stockholm, Sweden
| | - Nilab Nasrullah
- Department of Women's and Children's Health, Karolinska Institute and Neurology Clinic, Karolinksa University Hospital, Karolinska Universitetssjukhuset, Stockholm, Sweden
| | - Randall Espinoza
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - Katherine Narr
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - Noriko Salamon
- Department of Radiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Nicholas J Beimer
- Department of Neurology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA; Department of Psychiatry, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Lubomir M Hadjiiski
- Department of Radiology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Dawn S Eliashiv
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - William C Stacey
- Department of Neurology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA; Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Jerome Engel
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA; Brain Research Institute, University of California Los Angeles, Los Angeles, CA, USA; Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Jamie D Feusner
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA; Centre for Addiction and Mental Health, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada; Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - John M Stern
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
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Jung JY, Cho SE, Kim N, Kang CK, Kang SG. Decreased resting-state functional connectivity of the habenula-cerebellar in a major depressive disorder. Front Psychiatry 2022; 13:925823. [PMID: 36147982 PMCID: PMC9485485 DOI: 10.3389/fpsyt.2022.925823] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 08/11/2022] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND In animal experiments, the habenula and septal nuclei are known as the key brain areas of depression. However, there are few magnetic resonance imaging (MRI) studies on the functional connectivity between these areas and the subcortical areas in humans with major depression. We aimed to investigate the difference in resting-state functional connectivity (RSFC) among the major regions of interest (ROI) in the subcortical areas, including both the habenula and septal nuclei. METHODS We performed the seed-to-voxel analysis to investigate the RSFC between both the habenula and septal nucleus, as well as other subcortical regions. Furthermore, ROI-to-ROI analysis was performed among the combinations of ROI pairs in the subcortical areas. RESULTS The seed-to-voxel analysis showed a lower RSFC between the left habenula and the cerebellum in major depressive disorder (MDD) than in healthy controls (HCs). As a result of ROI-to-ROI analysis in subcortical areas, a total of 31 pairs of FCs in the MDD group showed a lower RSFC than in the HCs group. CONCLUSION This study revealed a lower RSFC between the left habenula and cerebellum in patients with MDD and reduced RSFC among numerous subcortical areas. These new findings on the neural circuitry of MDD might contribute to an in-depth understanding of depression.
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Affiliation(s)
- Ju-Yeon Jung
- Department of Health Science, Gachon University Graduate School, Incheon, South Korea
| | - Seo-Eun Cho
- Department of Psychiatry, Gil Medical Center, Gachon University College of Medicine, Incheon, South Korea
| | - Nambeom Kim
- Department of Biomedical Engineering Research Center, Gachon University, Incheon, South Korea
| | - Chang-Ki Kang
- Department of Radiological Science, College of Health Science, Gachon University, Incheon, South Korea
| | - Seung-Gul Kang
- Department of Psychiatry, Gil Medical Center, Gachon University College of Medicine, Incheon, South Korea
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Hou Z, Kong Y, Yin Y, Zhang Y, Yuan Y. Identification of first-episode unmedicated major depressive disorder using pretreatment features of dominant coactivation patterns. Prog Neuropsychopharmacol Biol Psychiatry 2021; 104:110038. [PMID: 32682877 DOI: 10.1016/j.pnpbp.2020.110038] [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: 03/14/2020] [Revised: 07/05/2020] [Accepted: 07/12/2020] [Indexed: 01/17/2023]
Abstract
Identifying neuroimaging features to diagnose major depressive disorder (MDD) and predict treatment response remains challenging. Using the pretreatment dominant coactivation pattern (dCAP) analysis approach, we aimed to identify patients with MDD and predict antidepressant efficacy. Seventy-seven first-episode unmedicated MDD patients and forty-two age- and sex-matched healthy controls (HCs) were recruited in the study. The dCAP analysis was performed for the reward and default mode network (DMN) to identify the MDD patients from the HCs. The dCAP1 of the left posterior DMN and bilateral anterior DMN were significantly higher in the MDD group than in the HC group (P < .001), and the dCAP1 in the left posterior DMN was positively correlated with the baseline severity of depression (rho = 0.248, P = .030). Besides, the MDD group exhibited significantly higher dCAP1 in the right reward network than the HC group. Further correlation analyses revealed that the transfer probability in the right reward network was positively correlated with the treatment responsivity (r = 0.247, P = .030). Importantly, integrating the dCAPs of the above four subnetworks can effectively identify the patients with MDD (AUC = 0.920, P < .001). The distinct pretreatment features of the dCAP in the subnetwork of the DMN and reward network may serve as potential indicators for individual diagnosis and prediction of antidepressant response in the early stage.
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Affiliation(s)
- Zhenghua Hou
- Department of Psychosomatics & Psychiatry, Institute of Psychosomatic Medicine, Affiliated Zhongda Hospital, Southeast University, Nanjing 210009, China; Department of Psychiatry, Columbia University College of Physicians and Surgeons, The New York State Psychiatric Institute, New York, NY 10032, United States
| | - Youyong Kong
- Lab of Image Science and Technology, School of Computer Science and Engineering, Key Laboratory of Computer Network and Information Integration, Ministry of Education, Southeast University, Nanjing 210009, China
| | - Yingying Yin
- Department of Psychosomatics & Psychiatry, Institute of Psychosomatic Medicine, Affiliated Zhongda Hospital, Southeast University, Nanjing 210009, China
| | - Yuqun Zhang
- Department of Psychosomatics & Psychiatry, Institute of Psychosomatic Medicine, Affiliated Zhongda Hospital, Southeast University, Nanjing 210009, China
| | - Yonggui Yuan
- Department of Psychosomatics & Psychiatry, Institute of Psychosomatic Medicine, Affiliated Zhongda Hospital, Southeast University, Nanjing 210009, China.
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Espinoza Oyarce DA, Shaw ME, Alateeq K, Cherbuin N. Volumetric brain differences in clinical depression in association with anxiety: a systematic review with meta-analysis. J Psychiatry Neurosci 2020; 45:406-429. [PMID: 32726102 PMCID: PMC7595741 DOI: 10.1503/jpn.190156] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Structural differences associated with depression have not been confirmed in brain regions apart from the hippocampus. Comorbid anxiety has been inconsistently assessed, and may explain discrepancies in previous findings. We investigated the link between depression, comorbid anxiety and brain structure. METHODS We followed Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines (PROSPERO CRD42018089286). We searched the Cochrane Library, MEDLINE, PsycInfo, PubMed and Scopus, from database inception to Sept. 13, 2018, for MRI case-control studies that reported brain volumes in healthy adults and adults with clinical depression. We summarized mean volumetric differences using meta-analyses, and we assessed demographics, depression factors and segmentation procedure as moderators using meta-regressions. RESULTS We included 112 studies in the meta-analyses, assessing 4911 healthy participants and 5934 participants with depression (mean age 49.8 yr, 68.2% female). Volume effects were greater in late-onset depression and in multiple episodes of depression. Adults with depression and no comorbidity showed significantly lower volumes in the putamen, pallidum and thalamus, as well as significantly lower grey matter volume and intracranial volume; the largest effects were in the hippocampus (6.8%, p < 0.001). Adults with depression and comorbid anxiety showed significantly higher volumes in the amygdala (3.6%, p < 0.001). Comorbid anxiety lowered depression effects by 3% on average. Sex moderated reductions in intracranial volume. LIMITATIONS High heterogeneity in hippocampus effects could not be accounted for by any moderator. Data on symptom severity and medication were sparse, but other factors likely made significant contributions. CONCLUSION Depression-related differences in brain structure were modulated by comorbid anxiety, chronicity of symptoms and onset of illness. Early diagnosis of anxiety symptomatology will prove crucial to ensuring effective, tailored treatments for improving long-term mental health and mitigating cognitive problems, given the effects in the hippocampus.
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Affiliation(s)
- Daniela A Espinoza Oyarce
- From the Centre for Research on Ageing, Health and Wellbeing, The Australian National University, Canberra, ACT, Australia (Espinoza Oyarce, Alateeq, Cherbuin); and the College of Engineering and Computer Science, The Australian National University, Canberra, ACT, Australia (Shaw)
| | - Marnie E Shaw
- From the Centre for Research on Ageing, Health and Wellbeing, The Australian National University, Canberra, ACT, Australia (Espinoza Oyarce, Alateeq, Cherbuin); and the College of Engineering and Computer Science, The Australian National University, Canberra, ACT, Australia (Shaw)
| | - Khawlah Alateeq
- From the Centre for Research on Ageing, Health and Wellbeing, The Australian National University, Canberra, ACT, Australia (Espinoza Oyarce, Alateeq, Cherbuin); and the College of Engineering and Computer Science, The Australian National University, Canberra, ACT, Australia (Shaw)
| | - Nicolas Cherbuin
- From the Centre for Research on Ageing, Health and Wellbeing, The Australian National University, Canberra, ACT, Australia (Espinoza Oyarce, Alateeq, Cherbuin); and the College of Engineering and Computer Science, The Australian National University, Canberra, ACT, Australia (Shaw)
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Kim J, Cho H, Kim J, Kim A, Kang Y, Kang W, Choi KW, Ham BJ, Han KM, Tae WS. Changes in cortical thickness and volume of cerebellar subregions in patients with bipolar disorders. J Affect Disord 2020; 271:74-80. [PMID: 32479334 DOI: 10.1016/j.jad.2020.03.087] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2019] [Revised: 01/26/2020] [Accepted: 03/25/2020] [Indexed: 02/06/2023]
Abstract
BACKGROUND Numerous studies have suggested that structural changes in the cerebellum are implicated in the pathophysiology of bipolar disorder (BD). We aimed to investigate differences in the volume and cortical thickness of the cerebellar subregions between patients with BD and healthy controls (HCs). METHODS Ninety patients with BD and one hundred sixty-six HCs participated in this study and underwent T1-weighted structural magnetic resonance imaging. We analyzed the volume and cortical thickness of each cerebellar hemisphere divided into 12 subregions using T1-weighted images of participants. One-way analysis of covariance was used to evaluate differences between the groups, with age, sex, medication, and total intracranial cavity volume used as covariates. RESULTS The BD group had significantly increased cortical thickness of the cerebellum in all cerebellar subregions compared to the HC group. The cortical thicknesses of the whole cerebellum and each hemisphere were also significantly thicker in the BD group than in the HC group. The volume of the left lobule IX was significantly lower in patients with BD than in HCs, whereas no significant differences in the volumes were observed in the other subregions. LIMITATIONS Our cross-sectional design cannot provide a causal relationship between the increased cortical thickness of the cerebellum and the risk of BD. CONCLUSIONS We observed widespread and significant cortical thickening in all the cerebellar subregions. Our results provide evidence for the involvement of the cerebellum in BD. Further studies are required to integrate neurobiological evidence and structural brain imaging to elucidate the pathophysiology of BD.
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Affiliation(s)
- Jooyeon Kim
- Department of Medicine, Korea University College of Medicine, Seoul, Republic of Korea
| | - Heejoon Cho
- Department of Medicine, Korea University College of Medicine, Seoul, Republic of Korea
| | - Jinha Kim
- Department of Medicine, Korea University College of Medicine, Seoul, Republic of Korea
| | - Aram Kim
- Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Republic of Korea
| | - Youbin Kang
- Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Republic of Korea
| | - Wooyoung Kang
- Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Republic of Korea
| | - Kwan Woo Choi
- Department of Psychiatry, Korea University College of Medicine, Seoul, Republic of Korea
| | - Byung-Joo Ham
- Department of Psychiatry, Korea University College of Medicine, Seoul, Republic of Korea; Brain Convergence Research Center, Korea University Anam Hospital, Seoul, Republic of Korea
| | - Kyu-Man Han
- Department of Psychiatry, Korea University College of Medicine, Seoul, Republic of Korea.
| | - Woo-Suk Tae
- Brain Convergence Research Center, Korea University Anam Hospital, Seoul, Republic of Korea.
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Choi KW, Kwon S, Pyun SB, Tae WS. Shape Deformation in the Brainstem of Medication-Naïve Female Patients with Major Depressive Disorder. Psychiatry Investig 2020; 17:465-474. [PMID: 32403210 PMCID: PMC7265019 DOI: 10.30773/pi.2020.0025] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 03/09/2020] [Indexed: 11/27/2022] Open
Abstract
OBJECTIVE Although neuroimaging studies have shown volumetric reductions, such as the anterior cingulate, prefrontal cortices, and hippocampus in patients with major depressive disorder (MDD), few studies have investigated the volume of or shape alterations in the subcortical regions and the brainstem. We hypothesized that medication-naïve female adult patients with MDD might present with shape and volume alterations in the subcortical regions, including the brainstem, compared to healthy controls (HCs). METHODS A total of 20 medication-naïve female patients with MDD and 21 age-matched female HCs, underwent 3D T1-weighted structural magnetic resonance scanning. We analyzed the volumes of each subcortical region and each brainstem region, including the midbrain, pons, and medulla oblongata. We also performed surface-based vertex analyses on the subcortical areas and brainstem. RESULTS Female patients with MDD showed non-significant volumetric differences in the subcortical regions, whole brainstem, and each brainstem region compared to the HCs. However, in the surface-based vertex analyses, significant shape contractions were observed in both cerebellar peduncles located on the lateral wall of the posterior brainstem [threshold-free cluster enhancement, corrected for family-wise error (FWE) at p<0.05] in patients with MDD. CONCLUSION We revealed shape alterations in the posterior brainstem in female patients with MDD.
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Affiliation(s)
- Kwan Woo Choi
- Department of Psychiatry, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Soonwook Kwon
- Department of Anatomy, School of Medicine, Catholic University of Daegu, Daegu, Republic of Korea
| | - Sung-Bom Pyun
- Department of Physical Medicine and Rehabilitation, Korea University College of Medicine, Seoul, Republic of Korea.,Brain Convergence Research Center, Korea University, Seoul, Republic of Korea
| | - Woo-Suk Tae
- Brain Convergence Research Center, Korea University, Seoul, Republic of Korea
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10
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Majrashi NA, Ahearn TS, Waiter GD. Brainstem volume mediates seasonal variation in depressive symptoms: A cross sectional study in the UK Biobank cohort. Sci Rep 2020; 10:3592. [PMID: 32108162 PMCID: PMC7046735 DOI: 10.1038/s41598-020-60620-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Accepted: 02/10/2020] [Indexed: 11/18/2022] Open
Abstract
Seasonal differences in mood and depressive symptoms affect a large percentage of the general population, with seasonal affective disorder (SAD) representing the most common presentation. SAD affects up to 3% of the world’s population, and it tends to be more predominant in females than males. The brainstem has been shown to be affected by photoperiodic changes, and that longer photoperiods are associated with higher neuronal density and decreased depressive-like behaviours. We predict that longer photoperiod days are associated with larger brainstem volumes and lower depressive scores, and that brainstem volume mediates the seasonality of depressive symptoms. Participants (N = 9289, 51.8% females and 48.1% males) ranging in age from 44 to 79 years were scanned by MRI at a single location. Photoperiod was found to be negatively correlated with low mood and anhedonia in females while photoperiod was found to be positively correlated with brainstem volumes. In females, whole brainstem, pons and medulla volumes individually mediated the relationship between photoperiod and both anhedonia and low mood, while midbrain volume mediated the relationship between photoperiod and anhedonia. No mediation effects were seen in males. Our study extends the understanding of the neurobiological factors that contribute to the pathophysiology of seasonal mood variations.
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Affiliation(s)
- Naif A Majrashi
- Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, UK.,Diagnostic Radiology Department, College of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia
| | - Trevor S Ahearn
- Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, UK.,Medical Physics, NHS Grampian, Aberdeen, UK
| | - Gordon D Waiter
- Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, UK.
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11
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Luo L, Wu K, Lu Y, Gao S, Kong X, Lu F, Wu F, Wu H, Wang J. Increased Functional Connectivity Between Medulla and Inferior Parietal Cortex in Medication-Free Major Depressive Disorder. Front Neurosci 2019; 12:926. [PMID: 30618555 PMCID: PMC6295569 DOI: 10.3389/fnins.2018.00926] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2018] [Accepted: 11/26/2018] [Indexed: 11/13/2022] Open
Abstract
Emerging evidence has documented the abnormalities of primary brain functions in major depressive disorder (MDD). The brainstem has shown to play an important role in regulating basic functions of the human brain, but little is known about its role in MDD, especially the roles of its subregions. To uncover this, the present study adopted resting-state functional magnetic resonance imaging with fine-grained brainstem atlas in 23 medication-free MDD patients and 34 matched healthy controls (HC). The analysis revealed significantly increased functional connectivity of the medulla, one of the brainstem subregions, with the inferior parietal cortex (IPC) in MDD patients. A positive correlation was further identified between the increased medulla-IPC functional connectivity and Hamilton anxiety scores. Functional characterization of the medulla and IPC using a meta-analysis revealed that both regions primarily participated in action execution and inhibition. Our findings suggest that increased medulla-IPC functional connectivity may be related to over-activity or abnormal control of negative emotions in MDD, which provides a new insight for the neurobiology of MDD.
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Affiliation(s)
- Lizhu Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Kunhua Wu
- Department of MRI, The First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, China
| | - Yi Lu
- The Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Shan Gao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Foreign Languages, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiangchao Kong
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Fengmei Lu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Fengchun Wu
- The Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangzhou, China.,Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Huawang Wu
- The Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangzhou, China.,Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Jiaojian Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
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12
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Brown GM, McIntyre RS, Rosenblat J, Hardeland R. Depressive disorders: Processes leading to neurogeneration and potential novel treatments. Prog Neuropsychopharmacol Biol Psychiatry 2018; 80:189-204. [PMID: 28433459 DOI: 10.1016/j.pnpbp.2017.04.023] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2017] [Accepted: 04/01/2017] [Indexed: 12/18/2022]
Abstract
Mood disorders are wide spread with estimates that one in seven of the population are affected at some time in their life (Kessler et al., 2012). Many of those affected with severe depressive disorders have cognitive deficits which may progress to frank neurodegeneration. There are several peripheral markers shown by patients who have cognitive deficits that could represent causative factors and could potentially serve as guides to the prevention or even treatment of neurodegeneration. Circadian rhythm misalignment, immune dysfunction and oxidative stress are key pathologic processes implicated in neurodegeneration and cognitive dysfunction in depressive disorders. Novel treatments targeting these pathways may therefore potentially improve patient outcomes whereby the primary mechanism of action is outside of the monoaminergic system. Moreover, targeting immune dysfunction, oxidative stress and circadian rhythm misalignment (rather than primarily the monoaminergic system) may hold promise for truly disease modifying treatments that may prevent neurodegeneration rather than simply alleviating symptoms with no curative intent. Further research is required to more comprehensively understand the contributions of these pathways to the pathophysiology of depressive disorders to allow for disease modifying treatments to be discovered.
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Affiliation(s)
- Gregory M Brown
- Department of Psychiatry, University of Toronto, Centre for Addiction and Mental Health, 250 College St. Toronto, ON M5T 1R8, Canada.
| | - Roger S McIntyre
- Psychiatry and Pharmacology, University of Toronto, Mood Disorders Psychopharmacology Unit, University Health Network, 399 Bathurst Street, MP 9-325, Toronto, ON M5T 2S8, Canada.
| | - Joshua Rosenblat
- Resident of Psychiatry, Clinician Scientist Stream, University of Toronto, Mood Disorders Psychopharmacology Unit, University Health Network, 399 Bathurst Street, MP 9-325, Toronto, ON M5T 2S8, Canada
| | - Rüdiger Hardeland
- Johann Friedrich Blumenbach Institut für Zoologie und Anthropologie, Universität Göttingen, Buergerstrasse 50, D-37073 Göttingen, Germany.
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