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Kumar M, Goyal P, Sagar R, Kumaran SS. Gray matter biomarkers for major depressive disorder and manic disorder using logistic regression. J Psychiatr Res 2024; 171:177-184. [PMID: 38295451 DOI: 10.1016/j.jpsychires.2024.01.043] [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: 06/28/2023] [Revised: 01/16/2024] [Accepted: 01/22/2024] [Indexed: 02/02/2024]
Abstract
The study investigates morphometric changes using surface-based measures and logistic regression in Major depressive-disorder (MDD) and Manic-disorder patients as compared to controls. MDD (n = 21) and manic (n = 20) subjects were recruited from psychiatric clinics, along with 19 healthy-controls from local population, after structured and semi-structured clinical interview (DSM-IV, brief Psychotic-Rating Scale (BPRS), Young Mania Rating Scale (YMRS), Hamilton depression rating scale (HDRS), cognitive function by postgraduate Institute Battery of Brain Dysfunction (PGIBBD)). Using 3D T1-weighted images, gray matter (GM) cortical thickness and GM-based morphometric signatures (using logistic regression) were compared among MDD, manic disorder and controls using analysis of covariance (ANCOVA). No significant difference was found between the MDD and manic disorder patients. When compared to controls, cortical thinning was observed in bilateral rostral middle frontal gyrus and parsopercularis, right lateral occipital cortex, right lingual gyrus in MDD; and bilateral rostral middle frontal and superior frontal gyrus, right middle temporal gyrus, left supramarginal and left precentral gyrus in Manic disorders. Logistic regression analysis exhibited GM cortical thinning in the bilateral parsopercularis, right lateral occipital cortex and lingual gyrus in MDD; and bilateral rostral middle, superior frontal gyri, right middle temporal gyrus in Manic with a sensitivity and specificity of 85.7 % and 94.7 % and 90.0 % and 94.7 %, respectively in comparison with controls. Both groups exhibited GM loss in bilateral rostral middle frontal gyrus brain regions compared to controls. Multivariate analysis revealed common changes in GM in MDD and manic disorders associated with mood temperament, but differences when compared to controls.
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Affiliation(s)
- Mukesh Kumar
- Department of NMR, All India Institute of Medical Sciences, New Delhi, India.
| | - Prashant Goyal
- Department of Psychiatry, All India Institute of Medical Sciences, New Delhi, India.
| | - Rajesh Sagar
- Department of Psychiatry, All India Institute of Medical Sciences, New Delhi, India.
| | - S Senthil Kumaran
- Department of NMR, All India Institute of Medical Sciences, New Delhi, India.
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2
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Jellinger KA. The heterogeneity of late-life depression and its pathobiology: a brain network dysfunction disorder. J Neural Transm (Vienna) 2023:10.1007/s00702-023-02648-z. [PMID: 37145167 PMCID: PMC10162005 DOI: 10.1007/s00702-023-02648-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 04/28/2023] [Indexed: 05/06/2023]
Abstract
Depression is frequent in older individuals and is often associated with cognitive impairment and increasing risk of subsequent dementia. Late-life depression (LLD) has a negative impact on quality of life, yet the underlying pathobiology is still poorly understood. It is characterized by considerable heterogeneity in clinical manifestation, genetics, brain morphology, and function. Although its diagnosis is based on standard criteria, due to overlap with other age-related pathologies, the relationship between depression and dementia and the relevant structural and functional cerebral lesions are still controversial. LLD has been related to a variety of pathogenic mechanisms associated with the underlying age-related neurodegenerative and cerebrovascular processes. In addition to biochemical abnormalities, involving serotonergic and GABAergic systems, widespread disturbances of cortico-limbic, cortico-subcortical, and other essential brain networks, with disruption in the topological organization of mood- and cognition-related or other global connections are involved. Most recent lesion mapping has identified an altered network architecture with "depressive circuits" and "resilience tracts", thus confirming that depression is a brain network dysfunction disorder. Further pathogenic mechanisms including neuroinflammation, neuroimmune dysregulation, oxidative stress, neurotrophic and other pathogenic factors, such as β-amyloid (and tau) deposition are in discussion. Antidepressant therapies induce various changes in brain structure and function. Better insights into the complex pathobiology of LLD and new biomarkers will allow earlier and better diagnosis of this frequent and disabling psychopathological disorder, and further elucidation of its complex pathobiological basis is warranted in order to provide better prevention and treatment of depression in older individuals.
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Affiliation(s)
- Kurt A Jellinger
- Institute of Clinical Neurobiology, Alberichgasse 5/13, 1150, Vienna, Austria.
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3
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Bracht T, Walther S, Breit S, Mertse N, Federspiel A, Meyer A, Soravia LM, Wiest R, Denier N. Distinct and shared patterns of brain plasticity during electroconvulsive therapy and treatment as usual in depression: an observational multimodal MRI-study. Transl Psychiatry 2023; 13:6. [PMID: 36627288 PMCID: PMC9832014 DOI: 10.1038/s41398-022-02304-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 12/16/2022] [Accepted: 12/30/2022] [Indexed: 01/11/2023] Open
Abstract
Electroconvulsive therapy (ECT) is a highly effective treatment for depression. Previous studies point to ECT-induced volume increase in the hippocampi and amygdalae, and to increase in cortical thickness. However, it is unclear if these neuroplastic changes are associated with treatment response. This observational study aimed to address this research question by comparing neuroplasticity between patients with depression receiving ECT and patients with depression that respond to treatment as usual (TAU-responders). Twenty ECT-patients (16 major depressive disorder (MDD), 4 depressed bipolar disorder), 20 TAU-responders (20 MDD) and 20 healthy controls (HC) were scanned twice with multimodal magnetic resonance imaging (structure: MP2RAGE; perfusion: arterial spin labeling). ECT-patients were scanned before and after an ECT-index series (ECT-group). TAU-responders were scanned during a depressive episode and following remission or treatment response. Volumes and cerebral blood flow (CBF) of the hippocampi and amygdalae, and global mean cortical thickness were compared between groups. There was a significant group × time interaction for hippocampal and amygdalar volumes, CBF in the hippocampi and global mean cortical thickness. Hippocampal and amygdalar enlargements and CBF increase in the hippocampi were observed in the ECT-group but neither in TAU-responders nor in HC. Increase in global mean cortical thickness was observed in the ECT-group and in TAU-responders but not in HC. The co-occurrence of increase in global mean cortical thickness in both TAU-responders and in ECT-patients may point to a shared mechanism of antidepressant response. This was not the case for subcortical volume and CBF increase.
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Affiliation(s)
- Tobias Bracht
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland. .,Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland.
| | - Sebastian Walther
- grid.5734.50000 0001 0726 5157Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland ,Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
| | - Sigrid Breit
- grid.5734.50000 0001 0726 5157Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland ,Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
| | - Nicolas Mertse
- grid.5734.50000 0001 0726 5157Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland ,Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
| | - Andrea Federspiel
- grid.5734.50000 0001 0726 5157Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland ,Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
| | - Agnes Meyer
- grid.5734.50000 0001 0726 5157Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Leila M. Soravia
- grid.5734.50000 0001 0726 5157Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland ,Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
| | - Roland Wiest
- Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland ,grid.5734.50000 0001 0726 5157Institute of Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland
| | - Niklaus Denier
- grid.5734.50000 0001 0726 5157Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland ,Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
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4
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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: 17] [Impact Index Per Article: 8.5] [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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5
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James D, Lam VT, Jo B, Fung LK. Region-specific associations between gamma-aminobutyric acid A receptor binding and cortical thickness in high-functioning autistic adults. Autism Res 2022; 15:1068-1082. [PMID: 35261207 DOI: 10.1002/aur.2703] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 02/08/2022] [Accepted: 02/26/2022] [Indexed: 11/10/2022]
Abstract
The neurobiology of autism has been shown to involve alterations in cortical morphology and gamma-aminobutyric acid A (GABAA ) receptor density. We hypothesized that GABAA receptor binding potential (GABAA R BPND ) would correlate with cortical thickness, but their correlations would differ between autistic adults and typically developing (TD) controls. We studied 50 adults (23 autism, 27 TD, mean age of 27 years) using magnetic resonance imaging to measure cortical thickness, and [18 F]flumazenil positron emission tomography imaging to measure GABAA R BPND . We determined the correlations between cortical thickness and GABAA R BPND by cortical lobe, region-of-interest, and diagnosis of autism spectrum disorder (ASD). We also explored potential sex differences in the relationship between cortical thickness and autism characteristics, as measured by autism spectrum quotient (AQ) scores. Comparing autism and TD groups, no significant differences were found in cortical thickness or GABAA R BPND . In both autism and TD groups, a negative relationship between cortical thickness and GABAA R BPND was observed in the frontal and occipital cortices, but no relationship was found in the temporal or limbic cortices. A positive correlation was seen in the parietal cortex that was only significant for the autism group. Interestingly, in an exploratory analysis, we found sex differences in the relationships between cortical thickness and GABAA R BPND , and cortical thickness and AQ scores in the left postcentral gyrus. LAY SUMMARY: The thickness of the brain cortex and the density of the receptors associated with inhibitory neurotransmitter GABA have been hypothesized to underlie the neurobiology of autism. In this study, we found that these biomarkers correlate positively in the parietal cortex, but negatively in the frontal and occipital cortical regions of the brain. Furthermore, we collected preliminary evidence that the correlations between cortical thickness and GABA receptor density are sexdependent in a brain region where sensory inputs are registered.
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Affiliation(s)
- David James
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, California, USA
| | - Vicky T Lam
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, California, USA
| | - Booil Jo
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, California, USA
| | - Lawrence K Fung
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, California, USA
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6
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Kocsis K, Holczer A, Kazinczi C, Boross K, Horváth R, Németh LV, Klivényi P, Kincses ZT, Must A. Voxel-based asymmetry of the regional gray matter over the inferior temporal gyrus correlates with depressive symptoms in medicated patients with major depressive disorder. Psychiatry Res Neuroimaging 2021; 317:111378. [PMID: 34479177 DOI: 10.1016/j.pscychresns.2021.111378] [Citation(s) in RCA: 3] [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: 04/01/2021] [Revised: 08/13/2021] [Accepted: 08/24/2021] [Indexed: 10/20/2022]
Abstract
The number of patients suffering from major depressive disorder (MDD) is increasing worldwide. Imbalanced hemispherical brain activity may be an underlying factor of MDD; however, whether structural asymmetry also contributes to the symptoms experienced in MDD has been scarcely investigated. In this study, we aimed to examine cortical asymmetry in association with the severity of depressive and cognitive symptoms observed in MDD during stable medication. The association between the affective and cognitive symptoms and gray matter asymmetry was evaluated in 17 MDD patients using voxel-wise gray matter asymmetry analysis on high-resolution T1-weighted MR images. Asymmetry index values in the inferior temporal gyrus (ITG) correlated with the scores of the 17-item Hamilton Depression Rating Scale (HDRS), but no association was found with the Beck Hopelessness Scale, and performance on the 1-, 2- and 3-back task. Our results indicate that the asymmetry of gray matter content in the ITG might be associated with higher depression severity. Our findings might help to better understand how structural changes contribute to depression severity in patients with MDD.
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Affiliation(s)
- Krisztián Kocsis
- Department of Neurology, Albert Szent-Györgyi Health Centre, University of Szeged, Hungary
| | - Adrienn Holczer
- Department of Neurology, Albert Szent-Györgyi Health Centre, University of Szeged, Hungary
| | - Csaba Kazinczi
- Department of Neurology, Albert Szent-Györgyi Health Centre, University of Szeged, Hungary
| | - Katalin Boross
- Department of Radiology, Albert Szent-Györgyi Health Centre, University of Szeged, Hungary
| | - Regina Horváth
- Department of Radiology, Albert Szent-Györgyi Health Centre, University of Szeged, Hungary
| | - Luca Viola Németh
- Department of Neurology, Albert Szent-Györgyi Health Centre, University of Szeged, Hungary
| | - Péter Klivényi
- Department of Neurology, Albert Szent-Györgyi Health Centre, University of Szeged, Hungary
| | - Zsigmond Tamás Kincses
- Department of Radiology, Albert Szent-Györgyi Health Centre, University of Szeged, Hungary
| | - Anita Must
- Institute of Psychology, Faculty of Arts, University of Szeged, Egyetem utca 2 H-6722, Szeged, Hungary.
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7
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Ballester PL, Suh JS, Nogovitsyn N, Hassel S, Strother SC, Arnott SR, Minuzzi L, Sassi RB, Lam RW, Milev R, Müller DJ, Taylor VH, Kennedy SH, Frey BN. Accelerated brain aging in major depressive disorder and antidepressant treatment response: A CAN-BIND report. NEUROIMAGE-CLINICAL 2021; 32:102864. [PMID: 34710675 PMCID: PMC8556529 DOI: 10.1016/j.nicl.2021.102864] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 10/08/2021] [Accepted: 10/18/2021] [Indexed: 10/24/2022]
Abstract
OBJECTIVES Previous studies suggest that major depressive disorder (MDD) may be associated with volumetric indications of accelerated brain aging. This study investigated neuroanatomical signs of accelerated aging in MDD and evaluated whether a brain age gap is associated with antidepressant response. METHODS Individuals in a major depressive episode received escitalopram treatment (10-20 mg/d) for 8 weeks. Depression severity was assessed at baseline and at weeks 8 and 16 using the Montgomery-Asberg Depression Rating Scale (MADRS). Response to treatment was characterized by a significant reduction in the MADRS (≥50%). Nonresponders received adjunctive aripiprazole treatment (2-10 mg/d) for a further 8 weeks. The brain-predicted age difference (brain-PAD) at baseline was determined using machine learning methods trained on 3377 healthy individuals from seven publicly available datasets. The model used features from all brain regions extracted from structural magnetic resonance imaging data. RESULTS Brain-PAD was significantly higher in older MDD participants compared to younger MDD participants [t(147.35) = -2.35, p < 0.03]. BMI was significantly associated with brain-PAD in the MDD group [r(155) = 0.19, p < 0.03]. Response to treatment was not significantly associated with brain-PAD. CONCLUSION We found an elevated brain age gap in older individuals with MDD. Brain-PAD was not associated with overall treatment response to escitalopram monotherapy or escitalopram plus adjunctive aripiprazole.
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Affiliation(s)
- Pedro L Ballester
- Neuroscience Graduate Program, McMaster University, Hamilton, ON, Canada
| | - Jee Su Suh
- Neuroscience Graduate Program, McMaster University, Hamilton, ON, Canada
| | - Nikita Nogovitsyn
- Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Stefanie Hassel
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Stephen C Strother
- Rotman Research Institute, Baycrest, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, ON, Canada
| | | | - Luciano Minuzzi
- Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada; Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
| | - Roberto B Sassi
- Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Roumen Milev
- Departments of Psychiatry and Psychology, Queen's University, and Providence Care, Kingston, ON, Canada
| | - Daniel J Müller
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Valerie H Taylor
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Sidney H Kennedy
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Centre for Mental Health, University Health Network, Toronto, ON, Canada; Krembil Research Institute, University Health Network, Toronto, ON, Canada; Centre for Depression and Suicide Studies, and Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
| | - Benicio N Frey
- Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada; Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada.
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8
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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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9
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Wu P, Zhang A, Sun N, Lei L, Liu P, Wang Y, Li H, Yang C, Zhang K. Cortical Thickness Predicts Response Following 2 Weeks of SSRI Regimen in First-Episode, Drug-Naive Major Depressive Disorder: An MRI Study. Front Psychiatry 2021; 12:751756. [PMID: 35273524 PMCID: PMC8902047 DOI: 10.3389/fpsyt.2021.751756] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 12/23/2021] [Indexed: 12/14/2022] Open
Abstract
OBJECTIVE Major depression disorder (MDD) is a harmful disorder, and the pathological mechanism remains unclear. The primary pharmacotherapy regimen for MDD is selective serotonin reuptake inhibitors (SSRIs), but fewer than 40% of patients with MDD are in remission following initial treatment. Neuroimaging biomarkers of treatment efficacy can be used to guide personalized treatment in MDD. This study aims to determine if cortical thickness can be used as a predictor for SSRIs. METHODS A total of 126 first-episode, drug-naive MDD patients (MDDs) and 71 healthy controls (HCs) were enrolled in our study. Demographic data were collected according to the self-made case report form (CRF) at the baseline of all subjects. Magnetic resonance imaging (MRI) scanning was performed for all the participants at baseline, and all imaging was processed using the DPABISurf software. All MDDs were treated with SSRIs, and symptoms were assessed at both the baseline and 2 weeks using the 17-item Hamilton Rating Scale (HAMD-17). According to HAMD-17 total score improvement from baseline to the end of 2 weeks, the MDDs were divided into the non-responder group (defined as ≤ 20% HAMD-17 reduction) and responder group (defined as ≥50% HAMD-17 reduction). The receiver operating characteristic (ROC) curve was used to analyze the diagnostic value of MDDs' and HCs' cortical thickness for MDD. Correlation analysis was performed for the responder group and the non-responder group separately to identify the relationship between cortical thickness and SSRI treatment efficacy. To analyze whether cortical thickness was sufficient to differentiate responders and non-responders at baseline, we used ROC curve analysis. RESULTS Significant decreases were found in the cortical thickness of the right supplementary motor area (SMA) in MDDs at the baseline (corrected by the Monte Carlo permutation correction, cluster-wise significant threshold at p < 0.025 and vertex-wise threshold at p = 0.001), area under the curve (AUC) = 0.732 [95% confidence interval (CI) = 0.233-0.399]. In the responder group, the cortical thickness of the right SMA was significantly thinner than in the non-responder group at baseline. There was a negative correlation (r = -0.373, p = 0.044) between the cortical thickness of SMA (0 weeks) and HAMD-17 reductive rate (2 weeks) in the responder group. The results of ROC curve analyses of the responder and non-responder groups were AUC = 0.885 (95% CI = 0.803-0.968), sensitivity = 73.5%, and specificity = 96.6%, and the cutoff value was 0.701. CONCLUSION Lower cortical thickness of the right SMA in MDD patients at the baseline may be a neuroimaging biomarker for MDD diagnosis, and a greater extent of thinner cortical thickness in the right SMA at baseline may predict improved SSRI treatment response. Our study shows the potential of cortical thickness as a possible biomarker that predicts a patient's clinical treatment response to SSRIs in MDD.
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Affiliation(s)
- Peiyi Wu
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China.,Department of Psychiatry, Shanxi Medical University, Taiyuan, China
| | - Aixia Zhang
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Ning Sun
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China.,Department of Mental Health, Shanxi Medical University, Taiyuan, China
| | - Lei Lei
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China.,Department of Psychiatry, Shanxi Medical University, Taiyuan, China
| | - Penghong Liu
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Yikun Wang
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Hejun Li
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Chunxia Yang
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Kerang Zhang
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China
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