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Wei X, Iao WC, Zhang Y, Lin Z, Lin H. Retinal Microvasculature Causally Affects the Brain Cortical Structure: A Mendelian Randomization Study. OPHTHALMOLOGY SCIENCE 2024; 4:100465. [PMID: 39149712 PMCID: PMC11324828 DOI: 10.1016/j.xops.2024.100465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 01/05/2024] [Accepted: 01/08/2024] [Indexed: 08/17/2024]
Abstract
Purpose To reveal the causality between retinal vascular density (VD), fractal dimension (FD), and brain cortex structure using Mendelian randomization (MR). Design Cross-sectional study. Participants Genome-wide association studies of VD and FD involving 54 813 participants from the United Kingdom Biobank were used. The brain cortical features, including the cortical thickness (TH) and surface area (SA), were extracted from 51 665 patients across 60 cohorts. Surface area and TH were measured globally and in 34 functional regions using magnetic resonance imaging. Methods Bidirectional univariable MR (UVMR) was used to detect the causality between FD, VD, and brain cortex structure. Multivariable MR (MVMR) was used to adjust for confounding factors, including body mass index and blood pressure. Main Outcome Measures The global and regional measurements of brain cortical SA and TH. Results At the global level, higher VD is related to decreased TH (β = -0.0140 mm, 95% confidence interval: -0.0269 mm to -0.0011 mm, P = 0.0339). At the functional level, retinal FD is related to the TH of banks of the superior temporal sulcus and transverse temporal region without global weighted, as well as the SA of the posterior cingulate after adjustment. Vascular density is correlated with the SA of subregions of the frontal lobe and temporal lobe, in addition to the TH of the inferior temporal, entorhinal, and pars opercularis regions in both UVMR and MVMR. Bidirectional MR studies showed a causation between the SA of the parahippocampal and cauda middle frontal gyrus and retinal VD. No pleiotropy was detected. Conclusions Fractal dimension and VD causally influence the cortical structure and vice versa, indicating that the retinal microvasculature may serve as a biomarker for cortex structural changes. Our study provides insights into utilizing noninvasive fundus images to predict cortical structural deteriorations and neuropsychiatric disorders. Financial Disclosures The author(s) have no proprietary or commercial interest in any materials discussed in this article.
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Affiliation(s)
- Xiaoyue Wei
- State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Vision Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, Guangdong, China
- Center for Precision Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Wai Cheng Iao
- State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Vision Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, Guangdong, China
- Center for Precision Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Yi Zhang
- Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Zijie Lin
- Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Haotian Lin
- State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Vision Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, Guangdong, China
- Center for Precision Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China
- Hainan Eye Hospital and Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Haikou, Hainan, China
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Gao M, Zheng J, Li F, Yan Y, Wu Y, Li S, Li J, Li X, Wang H. Development and validation of dietary depression index in Chinese adults. Nutr Neurosci 2024:1-11. [PMID: 39046352 DOI: 10.1080/1028415x.2024.2376981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/25/2024]
Abstract
Objective: Previous studies have suggested diet was associated with depressive symptoms. We aimed to develop and validate Dietary Depression Index (DDI) based on dietary prediction of depression in a large Chinese cancer screening cohort.Methods: In the training set (n = 2729), we developed DDI by using intake of 20 food groups derived from a food frequency questionnaire to predict depression as assessed by Patient Health Questionnaire-9 based on the reduced rank regression method. Sensitivity, specificity, positive predictive value, and negative predictive value were used to assess the performance of DDI in evaluating depression in the validation dataset (n = 1176).Results: Receiver operating characteristic analysis was constructed to determine the best cut-off value of DDI in predicting depression. In the study population, the DDI ranged from -3.126 to 1.810. The discriminative ability of DDI in predicting depression was good with the AUC of 0.799 overall, 0.794 in males and 0.808 in females. The best cut-off values of DDI for depression prediction were 0.204 overall, 0.330 in males and 0.034 in females. DDI was a validated method to assess the effects of diet on depression.Conclusion: Among individual food components in DDI, fermented vegetables, fresh vegetables, whole grains and onions were inversely associated, whereas legumes, pickled vegetables and rice were positively associated with depressive symptoms.
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Affiliation(s)
- Min Gao
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
- Department of Nutrition and food hygiene, School of Public Health, Capital Medical University, Beijing, People's Republic of China
| | - Jiali Zheng
- Department of Epidemiology and Biostatistics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Fangyu Li
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Yumeng Yan
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Yin Wu
- Department of Psychiatry, McGill University Jewish General Hospital Centre for Clinical Epidemiology, Montreal, Canada
| | - Sha Li
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Jun Li
- Cancer Prevention and Treatment Office, Yanting Cancer Hospital, Mianyang, People's Republic of China
| | - Xiaoguang Li
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Hui Wang
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
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Zhang L, Zhang Y, Guo W, Ma Q, Zhang F, Li K, Yi Q. An Effect of Chronic Negative Stress on Hippocampal Structures and Functional Connectivity in Patients with Depressive Disorder. Neuropsychiatr Dis Treat 2024; 20:1011-1024. [PMID: 38764745 PMCID: PMC11102123 DOI: 10.2147/ndt.s460429] [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: 02/23/2024] [Accepted: 05/03/2024] [Indexed: 05/21/2024] Open
Abstract
Purpose Depressive disorder is a mental health disorder with complicated etiopathogenesis. Environmental stress and neurodevelopment combined with other factors contribute to the occurrence of depression. Especially for the depressive disorder with chronic negative stress, it has characteristics of recurrence and poor curative effect because of unclear mechanism. Here, we investigated the hippocampal structures and functional connectivity (FC) according to resting-state functional magnetic resonance imaging in patients with depression who underwent chronic negative stress. Patients and Methods A total of 65 patients with depression (34 underwent chronic negative stress and 31 non-underwent chronic negative stress) and 30 healthy controls who did not undergo chronic negative stress were included in the study. The volumes of hippocampal subfields, seed-based FCs between hippocampus and the whole brain voxels, and ROI-wise-based FC between hippocampal subfields were compared among the three groups. Results In the patients with depression who underwent chronic negative stress, the volumes of right_GC-ML-DG-head, right_CA4-head and right_CA3-head increased, FCs between Temporal_Mid_R, Precuneus_R, Frontal_Sup_R, Temporal_Sup_R, Angular_L, Frontal_Inf_Tri_R, Supp_Motor_Area_R, Precentral_L and hippocampus increased, and FCs between parasubiculum and CA3, and presubiculum and CA1 decreased. When compared to the patients who did not undergo chronic negative stress, the patients who underwent chronic negative stress had larger volumes of right_GC-ML-DG-head and right_CA3-head, higher FCs between Frontal_Sup_R, Frontal_Inf_Tri_R and hippocampus, and lower FCs between presubiculum and CA1. Conclusion The depression underwent chronic negative stress may experience disrupted hippocampal structures and functional connectivity. It may be one of potential depressive disorder subtypes.
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Affiliation(s)
- Lili Zhang
- The First Affiliated Hospital of Xinjiang Medical University, Urumqi, People’s Republic of China
- Hebei Provincial Mental Health Center, Baoding, Hebei Province, People’s Republic of China
- Hebei Key Laboratory of Major Mental and Behavioural Disorders, Baoding, Hebei Province, People’s Republic of China
| | - Yunshu Zhang
- Hebei Provincial Mental Health Center, Baoding, Hebei Province, People’s Republic of China
- Hebei Key Laboratory of Major Mental and Behavioural Disorders, Baoding, Hebei Province, People’s Republic of China
| | - Wentao Guo
- Hebei Provincial Mental Health Center, Baoding, Hebei Province, People’s Republic of China
- Hebei Key Laboratory of Major Mental and Behavioural Disorders, Baoding, Hebei Province, People’s Republic of China
| | - Qi Ma
- The First Affiliated Hospital of Xinjiang Medical University, Urumqi, People’s Republic of China
- Xinjiang Clinical Research Center for Mental (Psychological) Disorder, Urumqi, People’s Republic of China
| | - Feng Zhang
- Hebei Provincial Mental Health Center, Baoding, Hebei Province, People’s Republic of China
- Hebei Key Laboratory of Major Mental and Behavioural Disorders, Baoding, Hebei Province, People’s Republic of China
| | - Keqing Li
- Hebei Provincial Mental Health Center, Baoding, Hebei Province, People’s Republic of China
- Hebei Key Laboratory of Major Mental and Behavioural Disorders, Baoding, Hebei Province, People’s Republic of China
| | - Qizhong Yi
- The First Affiliated Hospital of Xinjiang Medical University, Urumqi, People’s Republic of China
- Xinjiang Clinical Research Center for Mental (Psychological) Disorder, Urumqi, People’s Republic of China
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Zhang L, Wang L, Yu M, Wu R, Steffens DC, Potter GG, Liu M. Hybrid representation learning for cognitive diagnosis in late-life depression over 5 years with structural MRI. Med Image Anal 2024; 94:103135. [PMID: 38461654 PMCID: PMC11016377 DOI: 10.1016/j.media.2024.103135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 07/14/2023] [Accepted: 03/05/2024] [Indexed: 03/12/2024]
Abstract
Late-life depression (LLD) is a highly prevalent mood disorder occurring in older adults and is frequently accompanied by cognitive impairment (CI). Studies have shown that LLD may increase the risk of Alzheimer's disease (AD). However, the heterogeneity of presentation of geriatric depression suggests that multiple biological mechanisms may underlie it. Current biological research on LLD progression incorporates machine learning that combines neuroimaging data with clinical observations. There are few studies on incident cognitive diagnostic outcomes in LLD based on structural MRI (sMRI). In this paper, we describe the development of a hybrid representation learning (HRL) framework for predicting cognitive diagnosis over 5 years based on T1-weighted sMRI data. Specifically, we first extract prediction-oriented MRI features via a deep neural network, and then integrate them with handcrafted MRI features via a Transformer encoder for cognitive diagnosis prediction. Two tasks are investigated in this work, including (1) identifying cognitively normal subjects with LLD and never-depressed older healthy subjects, and (2) identifying LLD subjects who developed CI (or even AD) and those who stayed cognitively normal over five years. We validate the proposed HRL on 294 subjects with T1-weighted MRIs from two clinically harmonized studies. Experimental results suggest that the HRL outperforms several classical machine learning and state-of-the-art deep learning methods in LLD identification and prediction tasks.
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Affiliation(s)
- Lintao Zhang
- School of Information Science and Engineering, Linyi University, Linyi, Shandong 27600, China; Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Lihong Wang
- Department of Psychiatry, University of Connecticut School of Medicine, University of Connecticut, Farmington, CT 06030, United States
| | - Minhui Yu
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Rong Wu
- Connecticut Convergence Institute for Translation in Regenerative Engineering, University of Connecticut Health, Farmington, CT 06030, United States
| | - David C Steffens
- Department of Psychiatry, University of Connecticut School of Medicine, University of Connecticut, Farmington, CT 06030, United States
| | - Guy G Potter
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, United States.
| | - Mingxia Liu
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States.
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Duan A, Zhao H, Zhou C. The Effects of a Healthy Lifestyle on Depressive Symptoms in Older Chinese Adults: The Mediating Role of Psychological Resilience. Cureus 2024; 16:e57258. [PMID: 38686246 PMCID: PMC11057559 DOI: 10.7759/cureus.57258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/30/2024] [Indexed: 05/02/2024] Open
Abstract
Objectives This study aimed to validate the interrelationships and potential pathways of influence between healthy lifestyles, psychological resilience, and depressive symptoms in the Chinese elderly population. Methods We utilized data from the Chinese Elderly Health Influential Factors Tracking Survey 2018 and included 9448 samples for the study after screening according to the qualifying conditions. The interrelationships among healthy lifestyles, psychological resilience and depressive symptoms were analyzed using stepwise regression, and the robustness of mediation effects was assessed using Sobel and Bootstrap test. Results Among Chinese older adults, healthy lifestyles were negatively associated with depressive symptoms (β = -0.310, 95% CI: -0.405, -0.215), positively associated with psychological resilience (β = 0.137, 95% CI:0.071, 0.023), and psychological resilience was negatively associated with depressive symptoms (β = -1.014, 95% CI: -1.037, -0.990). Conclusions Psychological resilience partially mediated the association between healthy lifestyles and depressive symptoms, with the mediating effect accounting for 44.8% of the total effect. Our study contributes to the understanding of the relationship between healthy lifestyles and depressive symptoms in the elderly population and emphasizes the important role of psychological resilience. It is recommended that the government and policymakers improve depressive symptoms among older adults through comprehensive measures such as promoting healthy lifestyles and education, providing psychological support services, and creating a favorable environment.
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Affiliation(s)
- Ailing Duan
- Public Health, Chongqing Medical University, Chongqing, CHN
| | - Hang Zhao
- Public Health, Chongqing Medical University, Chongqing, CHN
| | - Chunmin Zhou
- Public Health, Chongqing Medical University, Chonqing, CHN
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6
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Unterholzner J, Kautzky A, Reed MB, Wechsler TF, Popper V, Spurny-Dworak B, Stöhrmann P, Klöbl M, Varghese N, Mühlberger A, Eckert A, Frey R, Rujescu D, Lanzenberger R, Vanicek T. Effects of lockdowns on neurobiological and psychometric parameters in unipolar depression during the COVID-19 pandemic. Transl Psychiatry 2024; 14:42. [PMID: 38242882 PMCID: PMC10798945 DOI: 10.1038/s41398-024-02733-1] [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: 06/02/2023] [Revised: 12/19/2023] [Accepted: 01/02/2024] [Indexed: 01/21/2024] Open
Abstract
Defying the COVID-19 pandemic required restriction measures of unprecedented scale, that may induce and exacerbate psychiatric symptoms across the population. We aimed to assess in vivo dynamic effects of mitigation strategies on human brain neurobiology, neuroplastic as well as psychometric parameters. Three structural magnetic resonance imaging measurements, serum brain-derived neurotrophic factor (sBDNF) analyses, and psychometric assessments (Beck Depression Inventory-II and Perceived Stress Questionnaire-20) were performed in healthy individuals and patients with a recurrent major depressive disorder in the period from September 2020 to July 2021. Group differences and changes over time in structural imaging, neuroplastic and psychometric parameters were assessed with linear mixed models. Analysis of data from 18 patients with a recurrent major depressive disorder and 28 healthy individuals showed clinically relevant scores for depression and stress in the patient group as well as significant cross-sectional differences in depression scores (F = 30.89, p < 0.001) and three subscales of the Perceived Stress Questionnaire (Worries: F = 19.19, p < 0.001, Tension: F = 34.44, p < 0.001, Joy: F = 12.05, p = 0.001). Linear mixed models revealed no significant changes over time in cortical thickness of the prefrontal cortex, anterior cingulate cortex, hippocampus, and amygdala (F = 0.29, p > 0.1) and no interaction with group (F = 0.28, p > 0.1). Further, analysis revealed no main effect of time and no interaction of time x group in depressive symptoms, perceived stress subscales, and sBDNF (all p > 0.1). Despite the limited sample size, the strength of this investigation lies in the multimodal assessment of peri-pandemic lockdown effects. Nine months of varying restrictions measures did not result in observable changes in brain morphology nor impact depressive symptoms in either psychiatric patients with a recurrent major depressive disorder or healthy individuals. While these neurobiological and psychometric data stand in contrast to initial expectations about the effects of restriction measures, they might inform future investigations of longitudinal effects of restriction measures on mental health.
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Affiliation(s)
- Jakob Unterholzner
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Alexander Kautzky
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Murray Bruce Reed
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Theresa Friederike Wechsler
- Department for Psychology, Clinical Psychology and Psychotherapy, University of Regensburg, Regensburg, Germany
| | - Valentin Popper
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Benjamin Spurny-Dworak
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Peter Stöhrmann
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Manfred Klöbl
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Nimmy Varghese
- Neurobiology Lab for Brain Aging and Mental Health, Transfaculty Research Platform Molecular & Cognitive Neuroscience (MCN), University of Basel, Basel, Switzerland
| | - Andreas Mühlberger
- Department for Psychology, Clinical Psychology and Psychotherapy, University of Regensburg, Regensburg, Germany
| | - Anne Eckert
- Neurobiology Lab for Brain Aging and Mental Health, Transfaculty Research Platform Molecular & Cognitive Neuroscience (MCN), University of Basel, Basel, Switzerland
| | - Richard Frey
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Dan Rujescu
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Thomas Vanicek
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria.
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van de Weijer MP, Vermeulen J, Schrantee A, Munafò MR, Verweij KJH, Treur JL. The potential role of gray matter volume differences in the association between smoking and depression: A narrative review. Neurosci Biobehav Rev 2024; 156:105497. [PMID: 38100958 DOI: 10.1016/j.neubiorev.2023.105497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 11/14/2023] [Accepted: 11/28/2023] [Indexed: 12/17/2023]
Abstract
Tobacco use and major depression are both leading contributors to the global burden of disease and are also highly comorbid. Previous research indicates bi-directional causality between tobacco use and depression, but the mechanisms that underlie this causality are unclear, especially for the causality from tobacco use to depression. Here we narratively review the available evidence for a potential causal role of gray matter volume in the association. We summarize the findings of large existing neuroimaging meta-analyses, studies in UK Biobank, and the Enhancing NeuroImaging Genetics through MetaAnalysis (ENIGMA) consortium and assess the overlap in implicated brain areas. In addition, we review two types of methods that allow us more insight into the causal nature of associations between brain volume and depression/smoking: longitudinal studies and Mendelian Randomization studies. While the available evidence suggests overlap in the alterations in brain volumes implicated in tobacco use and depression, there is a lack of research examining the underlying pathophysiology. We conclude with recommendations on (genetically-informed) causal inference methods useful for studying these associations.
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Affiliation(s)
- Margot P van de Weijer
- Department of Psychiatry, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands.
| | - Jentien Vermeulen
- Department of Psychiatry, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| | - Anouk Schrantee
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| | - Marcus R Munafò
- School of Psychological Science, University of Bristol, Bristol, the United Kingdom
| | - Karin J H Verweij
- Department of Psychiatry, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| | - Jorien L Treur
- Department of Psychiatry, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
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8
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van Kleef RS, Müller A, van Velzen LS, Marie Bas-Hoogendam J, van der Wee NJA, Schmaal L, Veltman DJ, Rive MM, Ruhé HG, Marsman JBC, van Tol MJ. Functional MRI correlates of emotion regulation in major depressive disorder related to depressive disease load measured over nine years. Neuroimage Clin 2023; 40:103535. [PMID: 37984226 PMCID: PMC10696117 DOI: 10.1016/j.nicl.2023.103535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 10/26/2023] [Accepted: 10/30/2023] [Indexed: 11/22/2023]
Abstract
Major Depressive Disorder (MDD) often is a recurrent and chronic disorder. We investigated the neurocognitive underpinnings of the incremental risk for poor disease course by exploring relations between enduring depression and brain functioning during regulation of negative and positive emotions using cognitive reappraisal. We used fMRI-data from the longitudinal Netherlands Study of Depression and Anxiety acquired during an emotion regulation task in 77 individuals with MDD. Task-related brain activity was related to disease load, calculated from presence and severity of depression in the preceding nine years. Additionally, we explored task related brain-connectivity. Brain functioning in individuals with MDD was further compared to 35 controls to explore overlap between load-effects and general effects related to MDD history/presence. Disease load was not associated with changes in affect or with brain activity, but with connectivity between areas essential for processing, integrating and regulating emotional information during downregulation of negative emotions. Results did not overlap with general MDD-effects. Instead, MDD was generally associated with lower parietal activity during downregulation of negative emotions. During upregulation of positive emotions, disease load was related to connectivity between limbic regions (although driven by symptomatic state), and connectivity between frontal, insular and thalamic regions was lower in MDD (vs controls). Results suggest that previous depressive load relates to brain connectivity in relevant networks during downregulation of negative emotions. These abnormalities do not overlap with disease-general abnormalities and could foster an incremental vulnerability to recurrence or chronicity of MDD. Therefore, optimizing emotion regulation is a promising therapeutic target for improving long-term MDD course.
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Affiliation(s)
- Rozemarijn S van Kleef
- Department of Biomedical Sciences of Cells and Systems, Cognitive Neuroscience Center, University Medical Center Groningen, Groningen, the Netherlands.
| | - Amke Müller
- Department of Psychology, Helmut Schmidt University / University of the Federal Armed Forces Hamburg, Hamburg, Germany
| | - Laura S van Velzen
- Orygen Parkville, VIC, Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia
| | - Janna Marie Bas-Hoogendam
- Developmental and Educational Psychology, Institute of Psychology, Leiden University, Leiden, the Netherlands; Department of Psychiatry, Leiden University Medical Center, Leiden, the Netherlands; Leiden Institute for Brain and Cognition, Leiden University Medical Center, the Netherlands
| | - Nic J A van der Wee
- Department of Psychiatry, Leiden University Medical Center, Leiden, the Netherlands; Leiden Institute for Brain and Cognition, Leiden University Medical Center, the Netherlands
| | - Lianne Schmaal
- Orygen Parkville, VIC, Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam UMC location VUMC & Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Maria M Rive
- Department of Psychiatry, Amsterdam UMC location AMC, Amsterdam, the Netherlands; Triversum, Department of Child and Adolescent Psychiatry, GGZ Noord-Holland Noord, Hoorn, the Netherlands
| | - Henricus G Ruhé
- Department of Psychiatry, Radboudumc, Nijmegen, the Netherlands; Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, the Netherlands
| | - Jan-Bernard C Marsman
- Department of Biomedical Sciences of Cells and Systems, Cognitive Neuroscience Center, University Medical Center Groningen, Groningen, the Netherlands
| | - Marie-José van Tol
- Department of Biomedical Sciences of Cells and Systems, Cognitive Neuroscience Center, University Medical Center Groningen, Groningen, the Netherlands
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9
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Wang K, Hu Y, Yan C, Li M, Wu Y, Qiu J, Zhu X. Brain structural abnormalities in adult major depressive disorder revealed by voxel- and source-based morphometry: evidence from the REST-meta-MDD Consortium. Psychol Med 2023; 53:3672-3682. [PMID: 35166200 DOI: 10.1017/s0033291722000320] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
BACKGROUND Neuroimaging studies on major depressive disorder (MDD) have identified an extensive range of brain structural abnormalities, but the exact neural mechanisms associated with MDD remain elusive. Most previous studies were performed with voxel- or surface-based morphometry which were univariate methods without considering spatial information across voxels/vertices. METHODS Brain morphology was investigated using voxel-based morphometry (VBM) and source-based morphometry (SBM) in 1082 MDD patients and 990 healthy controls (HCs) from the REST-meta-MDD Consortium. We first examined group differences in regional grey matter (GM) volumes and structural covariance networks between patients and HCs. We then compared first-episode, drug-naïve (FEDN) patients, and recurrent patients. Additionally, we assessed the effects of symptom severity and illness duration on brain alterations. RESULTS VBM showed decreased GM volume in various regions in MDD patients including the superior temporal cortex, anterior and middle cingulate cortex, inferior frontal cortex, and precuneus. SBM returned differences only in the prefrontal network. Comparisons between FEDN and recurrent MDD patients showed no significant differences by VBM, but SBM showed greater decreases in prefrontal, basal ganglia, visual, and cerebellar networks in the recurrent group. Moreover, depression severity was associated with volumes in the inferior frontal gyrus and precuneus, as well as the prefrontal network. CONCLUSIONS Simultaneous application of VBM and SBM methods revealed brain alterations in MDD patients and specified differences between recurrent and FEDN patients, which tentatively provide an effective multivariate method to identify potential neurobiological markers for depression.
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Affiliation(s)
- KangCheng Wang
- School of Psychology, Shandong Normal University, Jinan, Shandong, China
| | - YuFei Hu
- School of Psychology, Shandong Normal University, Jinan, Shandong, China
| | - ChaoGan Yan
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
- Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- International Big-Data Center for Depression Research, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - MeiLing Li
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA
| | - YanJing Wu
- Faculty of Foreign Languages, Ningbo University, Ningbo, Zhejiang, China
| | - Jiang Qiu
- Faculty of Psychology, Southwest University, Chongqing 400716, China
| | - XingXing Zhu
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
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10
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Hu J, Huang Y, Zhang X, Liao B, Hou G, Xu Z, Dong S, Li P. Identifying suicide attempts, ideation, and non-ideation in major depressive disorder from structural MRI data using deep learning. Asian J Psychiatr 2023; 82:103511. [PMID: 36791609 DOI: 10.1016/j.ajp.2023.103511] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 02/06/2023] [Accepted: 02/07/2023] [Indexed: 02/12/2023]
Abstract
The present study aims to identify suicide risks in major depressive disorders (MDD) patients from structural MRI (sMRI) data using deep learning. In this paper, we collected the sMRI data of 288 MDD patients, including 110 patients with suicide ideation (SI), 93 patients with suicide attempts (SA), and 85 patients without suicidal ideation or attempts (NS). And we developed interpretable deep neural network models to classify patients in three tasks including SA-versus-SI, SA-versus-NS, and SI-versus-NS, respectively. Furthermore, we interpreted the models by extracting the important features that contributed most to the classification, and further discussed these features or ROI/brain regions.
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Affiliation(s)
- Jinlong Hu
- Guangdong Key Lab of Communication and Computer Network, School of Computer Science and Engineering, South China University of Technology, Guangzhou, China
| | - Yangmin Huang
- Guangdong Key Lab of Communication and Computer Network, School of Computer Science and Engineering, South China University of Technology, Guangzhou, China
| | - Xiaojing Zhang
- Guangdong Provincial Key Laboratory of Genome Stability and Disease Prevention and Regional Immunity and Diseases, Department of Pathology, Shenzhen University Medical School, Shenzhen University, Shenzhen, China
| | - Bin Liao
- College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China.
| | - Gangqiang Hou
- Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen, China.
| | - Ziyun Xu
- Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen, China
| | - Shoubin Dong
- Guangdong Key Lab of Communication and Computer Network, School of Computer Science and Engineering, South China University of Technology, Guangzhou, China
| | - Ping Li
- Department of Chinese and Bilingual Studies, Faculty of Humanities, The Hong Kong Polytechnic University, Hong Kong, China
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11
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Christova P, Georgopoulos AP. Differential reduction of gray matter volume with age in 35 cortical areas in men (more) and women (less). J Neurophysiol 2023; 129:894-899. [PMID: 36922162 PMCID: PMC10085548 DOI: 10.1152/jn.00066.2023] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 03/06/2023] [Accepted: 03/15/2023] [Indexed: 03/17/2023] Open
Abstract
It is known that brain volume decreases with age. Here, we assessed the rate of this decrease in gray matter volume of 35 cortical regions in a large sample of healthy participants (n = 712, age range 36-90 yr) of the Human Connectome Project-Aging. We evaluated the difference in this rate between men (n = 316) and women (n = 396) and found that the volumes of cortical areas decreased by an average of 5.25%/decade, with the highest rate of decrease observed in the rostral anterior cingulate cortex (7.28%/decade). The rate of decrease was higher in men than in women in general and in 30/35 (85.7%) areas in particular, involving most prominently the cingulate lobe. These findings could serve as a normative reference for clinical conditions that manifest with abnormal brain atrophy.NEW & NOTEWORTHY This study showed an overall decrease of cortical gray matter with age but with different rates of volume reduction in different areas, with smaller decrease rates in women than in men. The highest volume reduction rate was observed for the rostral anterior cingulate cortex, an area linked to depression. These findings could serve as a normative reference for clinical conditions that manifest with abnormal brain atrophy.
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Affiliation(s)
- Peka Christova
- Department of Veterans Affairs Health Care System, The Neuroimaging Research Group, Brain Sciences Center, Minneapolis, Minnesota, United States
- Department of Neuroscience, University of Minnesota Medical School, Minneapolis, Minnesota, United States
| | - Apostolos P Georgopoulos
- Department of Veterans Affairs Health Care System, The Neuroimaging Research Group, Brain Sciences Center, Minneapolis, Minnesota, United States
- Department of Neuroscience, University of Minnesota Medical School, Minneapolis, Minnesota, United States
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12
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Schuurmans IK, Lamballais S, Zou R, Muetzel RL, Hillegers MHJ, Cecil CAM, Luik AI. 10-Year trajectories of depressive symptoms and subsequent brain health in middle-aged adults. J Psychiatr Res 2023; 158:126-133. [PMID: 36584490 DOI: 10.1016/j.jpsychires.2022.12.018] [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: 10/07/2022] [Revised: 12/09/2022] [Accepted: 12/19/2022] [Indexed: 12/24/2022]
Abstract
Depressive symptoms differ in severity and stability over time. Trajectories depicting these changes, particularly those with high late-life depressive symptoms, have been associated with poor brain health at old age. To better understand these associations across the lifespan, we examined depressive symptoms trajectories in relation to brain health in middle age. We included 1676 participants from the ORACLE Study, all were expecting a child at baseline (mean age 32.8, 66.6% women). Depressive symptoms were assessed at baseline, 3 years and 10 years after baseline. Brain health (global brain volume, subcortical structures volume, white matter lesions, cerebral microbleeds, cortical thickness, cortical surface area) was assessed 15 years after baseline. Using k-means clustering, four depressive symptoms trajectories were identified: low, low increasing, decreasing, and high increasing symptoms. The high increasing trajectory was associated with smaller brain volume compared to low symptoms, not surviving multiple testing correction. The low increasing trajectory was associated with more cortical thickness in a small region encompassing the right lateral occipital cortex compared to low symptoms. These findings show that longitudinal depressive symptoms trajectories are only minimally associated with brain health in middle age, suggesting that associations may only emerge later in life.
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Affiliation(s)
- Isabel K Schuurmans
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands; The Generation R Study Group, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Sander Lamballais
- Department of Clinical Genetics, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Runyu Zou
- Department of Child and Adolescent Psychiatry and Psychology, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Ryan L Muetzel
- Department of Child and Adolescent Psychiatry and Psychology, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Manon H J Hillegers
- Department of Child and Adolescent Psychiatry and Psychology, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Charlotte A M Cecil
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Child and Adolescent Psychiatry and Psychology, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands; Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Annemarie I Luik
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Child and Adolescent Psychiatry and Psychology, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands.
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13
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Li XL, Wei J, Zhang X, Meng Z, Zhu W. Relationship between night-sleep duration and risk for depression among middle-aged and older people: A dose-response meta-analysis. Front Physiol 2023; 14:1085091. [PMID: 36935736 PMCID: PMC10017495 DOI: 10.3389/fphys.2023.1085091] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 02/13/2023] [Indexed: 03/06/2023] Open
Abstract
Objective: The study aimed to examine the dose-response associations between night-sleep duration and depression risk in middle-aged and older adults. Methods: We searched PubMed, Embase, Web of Science, CNKI, VIP, and the Wanfang data knowledge service platforms from inception to 31 July 2022. Cohort and case-control studies assessing the relationship between night-sleep duration and depression were selected. We used the Newcastle-Ottawa scale to assess the quality of the published research. Two researchers carried out data extraction and quality assessment. The restricted cubic spline function and generalized least squares method were used to establish dose-response relationships between sleep duration and depression. We aimed to analyze the estimated effect size presented as the risk ratio (RR) and its 95% confidence interval (CI) using Stata 12.0. Result: Six cohort studies with 33,595 participants were included in this meta-analysis. A U-shaped association between sleep duration and depression risk was revealed. On one hand, compared with 7-h of night sleep, both shorter and longer sleep duration were associated with an increased risk of depression (5 h: risk ratio = 1.09, 95% confidence interval = 1.07-1.12; 6 h: RR = 1.03, 95% CI = 1.02-1.04; 8 h: RR = 1.10, 95% CI = 1.05-1.15; 9 h: RR = 1.31, 95% CI = 1.17-1.47; 10 h: RR = 1.59, 95% CI = 1.31-1.92; non-linear test p < 0.05). On the other hand, an increased risk of depression with shorter sleep duration was observed in middle-aged and older people among the non-Asian population (5 h: RR = 1.09; 95% CI = 1.02-1.17), while both shorter and longer sleep duration can increase the risk of depression among an Asian population (5 h: RR = 1.10, 95% CI = 1.07-1.13; 6 h: RR = 1.04, 95% CI = 1.02-1.05; 8 h: RR = 1.09, 95% CI = 1.05-1.14; 9 h: RR = 1.35, 95% CI = 1.18-1.53; 10 h: RR = 1.70, 95% CI = 1.36-2.12). Conclusion: The lowest-risk onset of depression occurred among middle-aged and older people with 7 h of night sleep, which suggested that shorter and longer night-sleep duration might lead to an increased incidence of depression. Clinical Trial Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=344052, identifier 344052.
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Affiliation(s)
- Xin-lin Li
- School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Jiayin Wei
- School of Management, Beijing University of Chinese Medicine, Beijing, China
| | - Xinying Zhang
- School of Management, Beijing University of Chinese Medicine, Beijing, China
| | - Zhuo Meng
- School of Management, Beijing University of Chinese Medicine, Beijing, China
| | - Wentao Zhu
- School of Management, Beijing University of Chinese Medicine, Beijing, China
- *Correspondence: Wentao Zhu, ,
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14
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Twait EL, Blom K, Koek HL, Zwartbol MHT, Ghaznawi R, Hendrikse J, Gerritsen L, Geerlings MI. Psychosocial factors and hippocampal subfields: The Medea-7T study. Hum Brain Mapp 2022; 44:1964-1984. [PMID: 36583397 PMCID: PMC9980899 DOI: 10.1002/hbm.26185] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 11/21/2022] [Accepted: 12/05/2022] [Indexed: 12/31/2022] Open
Abstract
Specific subfields within the hippocampus have shown vulnerability to chronic stress, highlighting the importance of looking regionally within the hippocampus to understand the role of psychosocial factors in the development of neurodegenerative diseases. A systematic review on psychosocial factors and hippocampal subfield volumes was performed and showed inconsistent results, highlighting the need for future studies to explore this relationship. The current study aimed to explore the association of psychosocial factors with hippocampal (subfield) volumes, using high-field 7T MRI. Data were from the Memory Depression and Aging (Medea)-7T study, which included 333 participants without dementia. Hippocampal subfields were automatically segmented from T2-weighted images using ASHS software. Generalized linear models accounting for correlated outcomes were used to assess the association between subfields (i.e., entorhinal cortex, subiculum, Cornu Ammonis [CA]1, CA2, CA3, dentate gyrus, and tail) and each psychosocial factor (i.e., depressive symptoms, anxiety symptoms, childhood maltreatment, recent stressful life events, and social support), adjusted for age, sex, and intracranial volume. Neither depression nor anxiety was associated with specific hippocampal (subfield) volumes. A trend for lower total hippocampal volume was found in those reporting childhood maltreatment, and a trend for higher total hippocampal volume was found in those who experienced a recent stressful life event. Among subfields, low social support was associated with lower volume in the CA3 (B = -0.43, 95% CI: -0.72; -0.15). This study suggests possible differential effects among hippocampal (subfield) volumes and psychosocial factors.
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Affiliation(s)
- Emma L. Twait
- Department of Epidemiology, Julius Center for Health Sciences and Primary CareUniversity Medical Center Utrecht and Utrecht UniversityUtrechtThe Netherlands
| | - Kim Blom
- Department of Epidemiology, Julius Center for Health Sciences and Primary CareUniversity Medical Center Utrecht and Utrecht UniversityUtrechtThe Netherlands
| | - Huiberdina L. Koek
- Department of GeriatricsUniversity Medical Center Utrecht and Utrecht UniversityUtrechtThe Netherlands
| | - Maarten H. T. Zwartbol
- Department of RadiologyUniversity Medical Center Utrecht and Utrecht UniversityUtrechtThe Netherlands
| | - Rashid Ghaznawi
- Department of RadiologyUniversity Medical Center Utrecht and Utrecht UniversityUtrechtThe Netherlands
| | - Jeroen Hendrikse
- Department of RadiologyUniversity Medical Center Utrecht and Utrecht UniversityUtrechtThe Netherlands
| | - Lotte Gerritsen
- Department of PsychologyUtrecht UniversityUtrechtThe Netherlands
| | - Mirjam I. Geerlings
- Department of Epidemiology, Julius Center for Health Sciences and Primary CareUniversity Medical Center Utrecht and Utrecht UniversityUtrechtThe Netherlands,Department of General PracticeAmsterdam UMC, Location University of AmsterdamAmsterdamThe Netherlands,Amsterdam Public Health, Aging & Later life, and Personalized MedicineAmsterdamThe Netherlands,Amsterdam Neuroscience, Neurodegeneration, and Mood, Anxiety, Psychosis, Stress, and SleepAmsterdamThe Netherlands
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15
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Li W, Wang W, Lai W, Li X, Zhu L, Shi J, Teopiz KM, McIntyre RS, Guo L, Lu C. The association of FKBP5 gene methylation, adolescents' sex, and depressive symptoms among Chinese adolescents: a nested case-control study. BMC Psychiatry 2022; 22:749. [PMID: 36451133 PMCID: PMC9710023 DOI: 10.1186/s12888-022-04392-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 11/15/2022] [Indexed: 12/05/2022] Open
Abstract
BACKGROUND Depressive symptoms among adolescents are a serious health concern around the world. Altered DNA methylation in the FK506 binding protein 5 (FKBP5) gene has been reported to regulate stress response, which has been reported to be closely associated with depressive symptoms. However, most of the contributing studies have been conducted among adults and relatively few studies have considered the effect of disparate social influences and sex differences on the DNA methylation of FKBP5 in persons with depressive symptoms. The present study aimed to test the associations of FKBP5 DNA methylation and depressive symptoms among adolescents and explore possible sex differences in the foregoing associations. METHODS This study was conducted using a nested case-control design within a longitudinal cohort study from January 2019 to December 2019. Adolescents aged 12 to 17 years from 69 classes in 10 public high schools located in Guangdong province of China participated in this research. Students with persistent depressive symptoms that reported having depressive symptoms at both baseline and follow-up were treated as the case group, and those without depressive symptoms were randomly selected as the control group. Our study finally included 87 cases and 151 controls. Quantitative methylation analyses of the selected gene were carried out by MassARRAY platform System. RESULTS The overall DNA methylation trend of FKBP5 CpG sites in the case group was lower in comparison to the control group. Compared to healthy controls, lower methylation percentage of FKBP5-12 CpG 1 was observed in adolescents with persistent depressive symptoms after adjusting for covariates (case: 0.94 ± 2.00, control: 0.47 ± 0.92; F = 5.41, P = 0.021), although the statistical significance of the difference was lost after false discovery rate correction (q > 0.05). In addition, the hypomethylation of FKBP5-12 CpG 1 was approaching significance after adjustment for social-environmental factors (aOR = 0.77; P = 0.055), which indicated that no independent association was detected between hypomethylation of FKBP5 CpG sites and persistent depressive symptoms. Furthermore, in the present study, we were unable to identify sex differences in the association of FKBP5 gene methylation with depressive symptoms. CONCLUSION The decreased methylation level of FKBP5 was observed in adolescents with persistent depressive symptoms, albeit non-significant after correction for multiple testing. Our results presented here are preliminary and underscore the complex gene-environment interactions relevant to the risk for depressive symptoms.
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Affiliation(s)
- Wenyan Li
- grid.12981.330000 0001 2360 039XDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Rd 2, 510080 Guangzhou, China
| | - Wanxin Wang
- grid.12981.330000 0001 2360 039XDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Rd 2, 510080 Guangzhou, China
| | - Wenjian Lai
- grid.12981.330000 0001 2360 039XDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Rd 2, 510080 Guangzhou, China
| | - Xiuwen Li
- grid.12981.330000 0001 2360 039XDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Rd 2, 510080 Guangzhou, China
| | - Liwan Zhu
- grid.12981.330000 0001 2360 039XDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Rd 2, 510080 Guangzhou, China
| | - Jingman Shi
- grid.12981.330000 0001 2360 039XDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Rd 2, 510080 Guangzhou, China
| | - Kayla M. Teopiz
- grid.231844.80000 0004 0474 0428Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON Canada
| | - Roger S. McIntyre
- grid.231844.80000 0004 0474 0428Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Pharmacology, University of Toronto, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Psychiatry, University of Toronto, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Institute of Medical Science, University of Toronto, Toronto, ON Canada
| | - Lan Guo
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Rd 2, 510080, Guangzhou, China.
| | - Ciyong Lu
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Rd 2, 510080, Guangzhou, China.
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16
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Lou ZQ, Zhou YY, Zhang X, Jiang HY. Exposure to selective noradrenalin reuptake inhibitors during the first trimester of pregnancy and risk of congenital malformations: A meta-analysis of cohort studies. Psychiatry Res 2022; 316:114756. [PMID: 35932572 DOI: 10.1016/j.psychres.2022.114756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 07/25/2022] [Accepted: 07/28/2022] [Indexed: 10/16/2022]
Abstract
Selective serotonin-noradrenalin reuptake inhibitors (SNRIs) are used to treat depression and anxiety during pregnancy; however, information regarding their foetal safety is limited. Cohort studies concerning congenital malformations in infants born to mothers exposed to SNRIs during the first trimester of pregnancy were identified. Eight studies were included in the analysis. In general, the use of SNRIs was not associated with an increased risk of overall congenital malformations when compared with no exposure (rate ratio [RR] = 1.07, 95% confidence interval [CI] = 0.94-1.22; P = 0.31), exposure to SSRIs (RR = 1.12, 95% CI = 0.97-1.31; P = 0.12) and no exposure with clinical indication (RR = 1.04, 95% CI = 0.9-1.2; P = 0.564). A significantly increased risk of cardiac malformations was observed (RR = 1.33, 95% CI = 1.15-1.53; P < 0.001); however, this association was not statistically significant when the reference group comprised mothers exposed to SSRIs (RR = 1.1, 95% CI = 0.85-1.43; P = 0.47) or no exposure with clinical indication (RR = 1.17, 95% CI = 0.95-1.42; P = 0.13). The evidence shows no increased risk of congenital malformations and argues against a substantial cardiac teratogenic effect of SNRIs.
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Affiliation(s)
- Zhuo-Qi Lou
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yuan-Yue Zhou
- Department of Medical Psychology, The First Affiliated Hospital, Hainan Medical University, Haikou, Hainan, China
| | - Xue Zhang
- Department of Infectious Diseases, the Affiliated Hangzhou First People's Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Hai-Yin Jiang
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
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17
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Binnewies J, Nawijn L, Brandmaier AM, Baaré WFC, Bartrés-Faz D, Drevon CA, Düzel S, Fjell AM, Han LKM, Knights E, Lindenberger U, Milaneschi Y, Mowinckel AM, Nyberg L, Plachti A, Madsen KS, Solé-Padullés C, Suri S, Walhovd KB, Zsoldos E, Ebmeier KP, Penninx BWJH. Associations of depression and regional brain structure across the adult lifespan: Pooled analyses of six population-based and two clinical cohort studies in the European Lifebrain consortium. Neuroimage Clin 2022; 36:103180. [PMID: 36088843 PMCID: PMC9467888 DOI: 10.1016/j.nicl.2022.103180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 08/08/2022] [Accepted: 08/30/2022] [Indexed: 12/14/2022]
Abstract
OBJECTIVE Major depressive disorder has been associated with lower prefrontal thickness and hippocampal volume, but it is unknown whether this association also holds for depressive symptoms in the general population. We investigated associations of depressive symptoms and depression status with brain structures across population-based and patient-control cohorts, and explored whether these associations are similar over the lifespan and across sexes. METHODS We included 3,447 participants aged 18-89 years from six population-based and two clinical patient-control cohorts of the European Lifebrain consortium. Cross-sectional meta-analyses using individual person data were performed for associations of depressive symptoms and depression status with FreeSurfer-derived thickness of bilateral rostral anterior cingulate cortex (rACC) and medial orbitofrontal cortex (mOFC), and hippocampal and total grey matter volume (GMV), separately for population-based and clinical cohorts. RESULTS Across patient-control cohorts, depressive symptoms and presence of mild-to-severe depression were associated with lower mOFC thickness (rsymptoms = -0.15/ rstatus = -0.22), rACC thickness (rsymptoms = -0.20/ rstatus = -0.25), hippocampal volume (rsymptoms = -0.13/ rstatus = 0.13) and total GMV (rsymptoms = -0.21/ rstatus = -0.25). Effect sizes were slightly larger for presence of moderate-to-severe depression. Associations were similar across age groups and sex. Across population-based cohorts, no associations between depression and brain structures were observed. CONCLUSIONS Fitting with previous meta-analyses, depressive symptoms and depression status were associated with lower mOFC, rACC thickness, and hippocampal and total grey matter volume in clinical patient-control cohorts, although effect sizes were small. The absence of consistent associations in population-based cohorts with mostly mild depressive symptoms, suggests that significantly lower thickness and volume of the studied brain structures are only detectable in clinical populations with more severe depressive symptoms.
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Affiliation(s)
- Julia Binnewies
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress Program, Amsterdam, The Netherlands.
| | - Laura Nawijn
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress Program, Amsterdam, The Netherlands
| | - Andreas M Brandmaier
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Max Planck, UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany; Department of Psychology, MSB Medical School Berlin, Berlin, Germany
| | - William F C Baaré
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
| | - David Bartrés-Faz
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona and Institut de Neurociències, Universitat de Barcelona, Spain
| | - Christian A Drevon
- Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo & Vitas Ltd, Oslo Science Park, Oslo, Norway
| | - Sandra Düzel
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Max Planck, UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
| | - Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Norway; Department of Radiology and Nuclear Medicine, Oslo University Hospital, Norway
| | - Laura K M Han
- Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Ethan Knights
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Max Planck, UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
| | - Yuri Milaneschi
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress Program, Amsterdam, The Netherlands
| | | | - Lars Nyberg
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Anna Plachti
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
| | - Kathrine Skak Madsen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark; Radiography, Department of Technology, University College Copenhagen, Copenhagen, Denmark
| | - Cristina Solé-Padullés
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona and Institut de Neurociències, Universitat de Barcelona, Spain
| | - Sana Suri
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, United Kingdom; Department of Psychiatry, University of Oxford, United Kingdom
| | - Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Norway; Department of Radiology and Nuclear Medicine, Oslo University Hospital, Norway
| | - Enikő Zsoldos
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, United Kingdom; Department of Psychiatry, University of Oxford, United Kingdom
| | - Klaus P Ebmeier
- Department of Psychiatry, University of Oxford, United Kingdom
| | - Brenda W J H Penninx
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress Program, Amsterdam, The Netherlands
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18
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The association between clinical and biological characteristics of depression and structural brain alterations. J Affect Disord 2022; 312:268-274. [PMID: 35760189 DOI: 10.1016/j.jad.2022.06.056] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 05/31/2022] [Accepted: 06/20/2022] [Indexed: 11/23/2022]
Abstract
BACKGROUND Structural brain alterations are observed in major depressive disorder (MDD). However, MDD is a highly heterogeneous disorder and specific clinical or biological characteristics of depression might relate to specific structural brain alterations. Clinical symptom subtypes of depression, as well as immuno-metabolic dysregulation associated with subtypes of depression, have been associated with brain alterations. Therefore, we examined if specific clinical and biological characteristics of depression show different brain alterations compared to overall depression. METHOD Individuals with and without depressive and/or anxiety disorders from the Netherlands Study of Depression and Anxiety (NESDA) (328 participants from three timepoints leading to 541 observations) and the Mood Treatment with Antidepressants or Running (MOTAR) study (123 baseline participants) were included. Symptom profiles (atypical energy-related profile, melancholic profile and depression severity) and biological indices (inflammatory, metabolic syndrome, and immuno-metabolic indices) were created. The associations of the clinical and biological profiles with depression-related structural brain measures (anterior cingulate cortex [ACC], orbitofrontal cortex, insula, and nucleus accumbens) were examined dimensionally in both studies and meta-analysed. RESULTS Depression severity was negatively associated with rostral ACC thickness (B = -0.55, pFDR = 0.03), and melancholic symptoms were negatively associated with caudal ACC thickness (B = -0.42, pFDR = 0.03). The atypical energy-related symptom profile and immuno-metabolic indices did not show a consistent association with structural brain measures across studies. CONCLUSION Overall depression- and melancholic symptom severity showed a dose-response relationship with reduced ACC thickness. No associations between immuno-metabolic dysregulation and structural brain alterations were found, suggesting that although both are associated with depression, distinct mechanisms may be involved.
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19
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McWhinney SR, Abé C, Alda M, Benedetti F, Bøen E, del Mar Bonnin C, Borgers T, Brosch K, Canales-Rodríguez EJ, Cannon DM, Dannlowski U, Diaz-Zuluaga AM, Lorielle Dietze, Elvsåshagen T, Eyler LT, Fullerton JM, Goikolea JM, Goltermann J, Grotegerd D, Haarman BCM, Hahn T, Howells FM, Ingvar M, Kircher TTJ, Krug A, Kuplicki RT, Landén M, Lemke H, Liberg B, Lopez-Jaramillo C, Malt UF, Martyn FM, Mazza E, McDonald C, McPhilemy G, Meier S, Meinert S, Meller T, Melloni EMT, Mitchell PB, Nabulsi L, Nenadic I, Opel N, Ophoff RA, Overs BJ, Pfarr JK, Pineda-Zapata JA, Pomarol-Clotet E, Raduà J, Repple J, Richter M, Ringwald KG, Roberts G, Ross A, Salvador R, Savitz J, Schmitt S, Schofield PR, Sim K, Stein DJ, Stein F, Temmingh HS, Thiel K, Thomopoulos SI, van Haren NEM, Van Gestel H, Vargas C, Vieta E, Vreeker A, Waltemate L, Yatham LN, Ching CRK, Andreassen O, Thompson PM, Hajek T. Diagnosis of bipolar disorders and body mass index predict clustering based on similarities in cortical thickness-ENIGMA study in 2436 individuals. Bipolar Disord 2022; 24:509-520. [PMID: 34894200 PMCID: PMC9187778 DOI: 10.1111/bdi.13172] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
AIMS Rates of obesity have reached epidemic proportions, especially among people with psychiatric disorders. While the effects of obesity on the brain are of major interest in medicine, they remain markedly under-researched in psychiatry. METHODS We obtained body mass index (BMI) and magnetic resonance imaging-derived regional cortical thickness, surface area from 836 bipolar disorders (BD) and 1600 control individuals from 14 sites within the ENIGMA-BD Working Group. We identified regionally specific profiles of cortical thickness using K-means clustering and studied clinical characteristics associated with individual cortical profiles. RESULTS We detected two clusters based on similarities among participants in cortical thickness. The lower thickness cluster (46.8% of the sample) showed thinner cortex, especially in the frontal and temporal lobes and was associated with diagnosis of BD, higher BMI, and older age. BD individuals in the low thickness cluster were more likely to have the diagnosis of bipolar disorder I and less likely to be treated with lithium. In contrast, clustering based on similarities in the cortical surface area was unrelated to BD or BMI and only tracked age and sex. CONCLUSIONS We provide evidence that both BD and obesity are associated with similar alterations in cortical thickness, but not surface area. The fact that obesity increased the chance of having low cortical thickness could explain differences in cortical measures among people with BD. The thinner cortex in individuals with higher BMI, which was additive and similar to the BD-associated alterations, may suggest that treating obesity could lower the extent of cortical thinning in BD.
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Affiliation(s)
| | - Christoph Abé
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Martin Alda
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Francesco Benedetti
- Vita-Salute San Raffaele University, Milan, Italy.,Division of Neuroscience, Psychiatry and Psychobiology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Erlend Bøen
- Unit for Psychosomatics / CL Outpatient Clinic for Adults, Division of Mental Health and Addiction, Oslo University Hospital, Oslo Norway
| | - Caterina del Mar Bonnin
- Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain
| | - Tiana Borgers
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | | | - Dara M. Cannon
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Udo Dannlowski
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Ana M. Diaz-Zuluaga
- Research Group in Psychiatry GIPSI, Department of Psychiatry, Faculty of Medicine, Universidad de Antioquia, Medellín, Colombia
| | - Lorielle Dietze
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Torbjørn Elvsåshagen
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Neurology, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Lisa T. Eyler
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA.,Desert-Pacific MIRECC, VA San Diego Healthcare, San Diego, CA, USA
| | - Janice M. Fullerton
- Neuroscience Research Australia, Randwick, NSW, Australia.,School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Jose M. Goikolea
- Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain
| | - Janik Goltermann
- Department of Psychiatry, University of Münster, Münster, Germany
| | | | - Bartholomeus C. M. Haarman
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Tim Hahn
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Fleur M. Howells
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa.,Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Martin Ingvar
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Tilo T. J. Kircher
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Axel Krug
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany.,Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
| | | | - Mikael Landén
- Department of Neuroscience and Physiology, Sahlgrenska Academy at Gothenburg University, Gothenburg, Sweden.,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Hannah Lemke
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Benny Liberg
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Carlos Lopez-Jaramillo
- Research Group in Psychiatry GIPSI, Department of Psychiatry, Faculty of Medicine, Universidad de Antioquia, Medellín, Colombia
| | - Ulrik F. Malt
- Unit for Psychosomatics / CL Outpatient Clinic for Adults, Division of Mental Health and Addiction, Oslo University Hospital, Oslo Norway.,Institute of Clinical Medicine, Department of Neurology, University of Oslo, Oslo, Norway
| | - Fiona M. Martyn
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Elena Mazza
- Vita-Salute San Raffaele University, Milan, Italy.,Division of Neuroscience, Psychiatry and Psychobiology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Colm McDonald
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Genevieve McPhilemy
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Sandra Meier
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Susanne Meinert
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Tina Meller
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany.,Center for Mind, Brain and Behavior (CMBB), University of Marburg and Justus Liebig University Giessen, Marburg, Germany
| | - Elisa M. T. Melloni
- Vita-Salute San Raffaele University, Milan, Italy.,Division of Neuroscience, Psychiatry and Psychobiology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Philip B. Mitchell
- School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - Leila Nabulsi
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Igor Nenadic
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Nils Opel
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Roel A. Ophoff
- UCLA Center for Neurobehavioral Genetics, Los Angeles, CA, USA.,Department of Psychiatry, Erasmus University Medical Center, Rotterdam, The Netherlands
| | | | - Julia-Katharina Pfarr
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Julian A. Pineda-Zapata
- Research Group, Instituto de Alta Tecnología Médica, Ayudas diagnósticas SURA, Medellin, Colombia
| | | | - Joaquim Raduà
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain.,Institute of Psychiartry, King’s College Londen, London, UK
| | - Jonathan Repple
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Maike Richter
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Kai G. Ringwald
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Gloria Roberts
- School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - Alex Ross
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
| | - Jonathan Savitz
- Laureate Institute for Brain Research, Tulsa, OK, USA.,Oxley College of Health Sciences, The University of Tulsa, Tulsa, OK, USA
| | - Simon Schmitt
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Peter R. Schofield
- Neuroscience Research Australia, Randwick, NSW, Australia.,School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore, Singapore.,Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Dan J. Stein
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa.,Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa.,South African MRC Unit on Risk & Resilience in Mental Disorders, University of Cape Town
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Henk S. Temmingh
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Katharina Thiel
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Neeltje E. M. van Haren
- Department of Child and Adolescent Psychiatry and Psychology, Erasmus University, Rotterdam, The Netherlands.,Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Holly Van Gestel
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Cristian Vargas
- Research Group in Psychiatry GIPSI, Department of Psychiatry, Faculty of Medicine, Universidad de Antioquia, Medellín, Colombia
| | - Eduard Vieta
- Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain
| | - Annabel Vreeker
- Department of Child and Adolescent Psychiatry and Psychology, Erasmus University, Rotterdam, The Netherlands
| | - Lena Waltemate
- Department of Psychiatry, University of Münster, Münster, Germany
| | | | - Christopher R. K. Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Ole Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Tomas Hajek
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada.,National Institute of Mental Health, Klecany, Czech Republic
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20
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Liu Y, Zhang Y, Thyreau B, Tatewaki Y, Matsudaira I, Takano Y, Hirabayashi N, Furuta Y, Jun H, Ninomiya T, Taki Y. Altruistic Social Activity, Depressive Symptoms, and Brain Regional Gray Matter Volume: Voxel-Based Morphometry Analysis from 8695 Old Adults. J Gerontol A Biol Sci Med Sci 2022; 77:1789-1797. [PMID: 35443061 DOI: 10.1093/gerona/glac093] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Indexed: 11/14/2022] Open
Abstract
Altruistic social activity, such as giving support to others, has shown protective benefits on dementia risk and cognitive decline. However, the pathological mechanism is unclear. In the present study, we investigated the association between altruistic social activity and brain regional gray matter. Furthermore, to explore the psychological interplay in altruistic social activity, we tested mediating effect of depressive symptoms on brain regional gray matter. We performed a cross-sectional Voxel-Based Morphology (VBM) analysis including 8695 old adults (72.9±6.1 years) from Japan Prospective Studies Collaboration for Aging and Dementia (JPSC-AD) Cohort. We measured altruistic social activities by self-report questionnaire, depressive symptoms by Geriatric Depression Scale (GDS)-short version. We employed the whole-brain VBM method to detect relevant structural properties related to altruistic social activity. We then performed multiple regression models to detect the mediating effect of depressive symptoms on particular brain regional gray matter volume while adjusting possible physical and social lifestyle covariables. We found that altruistic social activity is associated with larger gray matter volume in posterior insula, middle cingulate gyrus, hippocampus, thalamus, superior temporal gyrus, anterior orbital gyrus, and middle occipital gyrus. Depressive symptoms mediated over 10% on altruistic social activity and hippocampus volume, over 20% on altruistic social activity and cingulate gyrus volume. Our results indicated that altruistic social activity might preserve brain regional gray matter where are sensitive to aging and cognitive decline. Meanwhile, this association may be explained by indirect effect on depressive symptoms, suggesting that altruistic social activity may mitigate the neuropathology of dementia.
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Affiliation(s)
- Yingxu Liu
- Department of Aging Research and Geriatric Medicine, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Ye Zhang
- Department of Aging Research and Geriatric Medicine, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Benjamin Thyreau
- Smart-Aging Research Center, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Yasuko Tatewaki
- Department of Aging Research and Geriatric Medicine, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.,Department of Geriatric Medicine and Neuroimaging, Tohoku University Hospital, Sendai, Japan
| | - Izumi Matsudaira
- Smart-Aging Research Center, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Yuji Takano
- Department of Aging Research and Geriatric Medicine, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Naoki Hirabayashi
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - YoshihikTo Furuta
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Hata Jun
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Toshiharu Ninomiya
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Yasuyuki Taki
- Department of Aging Research and Geriatric Medicine, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.,Smart-Aging Research Center, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.,Department of Geriatric Medicine and Neuroimaging, Tohoku University Hospital, Sendai, Japan
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21
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Abstract
PURPOSE OF REVIEW Converging evidence suggest axonal damage is implicated in depression and cognitive function. Neurofilament light protein, measured within serum and cerebrospinal fluid, may be a biomarker of axonal damage. This article examines the emerging evidence implicating neurofilament light protein in depression and cognitive function. RECENT FINDINGS Preliminary cross-sectional and case-control studies in cohorts with depression have yielded inconsistent results regarding the association between neurofilament light protein and symptomatology. However, these studies had methodological limitations, requiring further investigation. Importantly, neurofilament light protein concentrations may be a marker of progression of cognitive decline and may be associated with cognitive performance within cognitively intact cohorts. SUMMARY Axonal damage is implicated in the neuropathology of depression and cognitive dysfunction. Consequently, neurofilament light protein is an emerging biomarker with potential in depression and cognitive function. Results are more consistent for cognition, requiring more research to assess neurofilament light protein in depression as well as other psychiatric disorders. Future longitudinal studies are necessary to determine whether neurofilament light protein can predict the onset and progression of depression and measure the effectiveness of potential psychiatric interventions and medications.
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22
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van Tol MJ, van der Wee NJA, Veltman DJ. Fifteen years of NESDA Neuroimaging: An overview of results related to clinical profile and bio-social risk factors of major depressive disorder and common anxiety disorders. J Affect Disord 2021; 289:31-45. [PMID: 33933910 DOI: 10.1016/j.jad.2021.04.009] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Revised: 04/05/2021] [Accepted: 04/07/2021] [Indexed: 10/21/2022]
Abstract
The longitudinal Netherlands Study of Depression and Anxiety (NESDA) Neuroimaging study was set up in 2003 to investigate whether neuroanatomical and functional abnormalities during tasks of primary emotional processing, executive planning and memory formation, and intrinsic brain connectivity are i) shared by individuals with major depressive disorder (MDD) and common anxiety disorders; and ii) characterized by symptomatology-specific abnormalities. Furthermore, questions related to individual variations in vulnerability for onset, comorbidity, and longitudinal course could be investigated. Between 2005 and 2007, 233 individuals fulfilling a diagnosis of MDD, panic disorder, social anxiety disorder and/or generalized anxiety disorder and 68 healthy controls aging between 18 and 57 were invited from the NESDA main sample (n = 2981). An emotional faces processing task, an emotional word-encoding task, and an executive planning task were administered during 3T BOLD-fMRI acquisitions. In addition, resting state BOLD-fMRI was acquired and T1-weighted structural imaging was performed. All participants were invited to participate in the two-year and nine-year follow-up MRI measurement. Fifteen years of NESDA Neuroimaging demonstrated common morphological and neurocognitive abnormalities across individuals with depression and anxiety disorders. It however provided limited support for the idea of more extensive abnormalities in patients suffering from both depression and anxiety, despite their worse prognosis. Risk factors including childhood maltreatment and specific risk genes had an emotion processing modulating effect, apparently stronger than effects of diagnostic labels. Furthermore, brain imaging data, especially during emotion processing seemed valuable for predicting the long-term course of affective disorders, outperforming prediction based on clinical information alone.
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Affiliation(s)
- M J van Tol
- University of Groningen, University Medical Center Groningen, Department of Biomedical Sciences of Cells and Systems, Cognitive Neuroscience Center, Groningen, the Netherlands.
| | - N J A van der Wee
- Department of Psychiatry and Leiden Institute for Brain and Cognition, Leiden University Medical Center, Department of Psychiatry, Leiden, the Netherlands
| | - D J Veltman
- Department of Psychiatry, Amsterdam University Medical Center, Location VUMC and Amsterdam Neuroscience, Amsterdam, the Netherlands
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