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Toffanin T, Cattarinussi G, Ghiotto N, Lussignoli M, Pavan C, Pieri L, Schiff S, Finatti F, Romagnolo F, Folesani F, Nanni MG, Caruso R, Zerbinati L, Belvederi Murri M, Ferrara M, Pigato G, Grassi L, Sambataro F. Effects of electroconvulsive therapy on cortical thickness in depression: a systematic review. Acta Neuropsychiatr 2024:1-15. [PMID: 38343196 DOI: 10.1017/neu.2024.6] [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] [Indexed: 03/14/2024]
Abstract
OBJECTIVE Electroconvulsive therapy (ECT) is one of the most studied and validated available treatments for severe or treatment-resistant depression. However, little is known about the neural mechanisms underlying ECT. This systematic review aims to critically review all structural magnetic resonance imaging studies investigating longitudinal cortical thickness (CT) changes after ECT in patients with unipolar or bipolar depression. METHODS We performed a search on PubMed, Medline, and Embase to identify all available studies published before April 20, 2023. A total of 10 studies were included. RESULTS The investigations showed widespread increases in CT after ECT in depressed patients, involving mainly the temporal, insular, and frontal regions. In five studies, CT increases in a non-overlapping set of brain areas correlated with the clinical efficacy of ECT. The small sample size, heterogeneity in terms of populations, comorbidities, and ECT protocols, and the lack of a control group in some investigations limit the generalisability of the results. CONCLUSIONS Our findings support the idea that ECT can increase CT in patients with unipolar and bipolar depression. It remains unclear whether these changes are related to the clinical response. Future larger studies with longer follow-up are warranted to thoroughly address the potential role of CT as a biomarker of clinical response after ECT.
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Affiliation(s)
- Tommaso Toffanin
- Department of Neuroscience and Rehabilitation, Institute of Psychiatry, University of Ferrara, Ferrara, Italy
| | - Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
- Padova Neuroscience Center, University of Padova, Padua, Italy
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK
| | - Niccolò Ghiotto
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
| | | | - Chiara Pavan
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
| | - Luca Pieri
- Department of Medicine, University of Padova, Padua, Italy
| | - Sami Schiff
- Department of Medicine, University of Padova, Padua, Italy
| | - Francesco Finatti
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
| | - Francesca Romagnolo
- Department of Neuroscience and Rehabilitation, Institute of Psychiatry, University of Ferrara, Ferrara, Italy
| | - Federica Folesani
- Department of Neuroscience and Rehabilitation, Institute of Psychiatry, University of Ferrara, Ferrara, Italy
| | - Maria Giulia Nanni
- Department of Neuroscience and Rehabilitation, Institute of Psychiatry, University of Ferrara, Ferrara, Italy
| | - Rosangela Caruso
- Department of Neuroscience and Rehabilitation, Institute of Psychiatry, University of Ferrara, Ferrara, Italy
| | - Luigi Zerbinati
- Department of Neuroscience and Rehabilitation, Institute of Psychiatry, University of Ferrara, Ferrara, Italy
| | - Martino Belvederi Murri
- Department of Neuroscience and Rehabilitation, Institute of Psychiatry, University of Ferrara, Ferrara, Italy
| | - Maria Ferrara
- Department of Neuroscience and Rehabilitation, Institute of Psychiatry, University of Ferrara, Ferrara, Italy
| | - Giorgio Pigato
- Department of Psychiatry, Padova University Hospital, Padua, Italy
| | - Luigi Grassi
- Department of Neuroscience and Rehabilitation, Institute of Psychiatry, University of Ferrara, Ferrara, Italy
| | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
- Padova Neuroscience Center, University of Padova, Padua, Italy
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Zhao Y, Feng S, Dong L, Wu Z, Ning Y. Dysfunction of large-scale brain networks underlying cognitive impairments in shift work disorder. J Sleep Res 2023:e14080. [PMID: 37888149 DOI: 10.1111/jsr.14080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 09/13/2023] [Accepted: 10/12/2023] [Indexed: 10/28/2023]
Abstract
It has been demonstrated that shift work can affect cognitive functions. Several neuroimaging studies have revealed altered brain function and structure for patients with shift work disorder (SWD). However, knowledge on the dysfunction of large-scale brain networks underlying cognitive impairments in shift work disorder is limited. This study aims to identify altered functional networks associated with cognitive declines in shift work disorder, and to assess their potential diagnostic value. Thirty-four patients with shift work disorder and 36 healthy controls (HCs) were recruited to perform the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and resting-state functional scans. After surface-based preprocessing, we calculated within- and between-network functional connectivity (FC) using the Dosenbach atlas. Moreover, correlation analysis was done between altered functional connectivity of large-scale brain networks and scores of cognitive assessments in patients with shift work disorder. Finally, we established a classification model to provide features for patients with shift work disorder concerning the disrupted large-scale networks. Compared with healthy controls, increased functional connectivity within-networks across the seven brain networks, and between-networks involving ventral attention network (VAN)-subcortical network (SCN), SCN-frontoparietal network (FPN), and somatosensory network (SMN)-SCN were observed in shift work disorder. Decreased functional connectivity between brain networks was found in shift work disorder compared with healthy controls, including visual network (VN)-FPN, VN-default mode network (DMN), SMN-DMN, dorsal attention network (DAN)-DMN, VAN-DMN, and FPN-DMN. Furthermore, the altered functional connectivity of large-scale brain networks was significantly correlated with scores of immediate memory, visuospatial, and delayed memory in patients with shift work disorder, respectively. Abnormal functional connectivity of large-scale brain networks may play critical roles in cognitive dysfunction in shift work disorder. Our findings provide new evidence to interpret the underlying neural mechanisms of cognitive impairments in shift work disorder.
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Affiliation(s)
- Yan Zhao
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospitaldiscu, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Sitong Feng
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospitaldiscu, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Linrui Dong
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospitaldiscu, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Ziyao Wu
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospitaldiscu, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Yanzhe Ning
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospitaldiscu, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
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Feng S, Dong L, Yan B, Zheng S, Feng Z, Li X, Li J, Sun N, Ning Y, Jia H. Altered Functional Connectivity of Large-Scale Brain Networks in Psychogenic Erectile Dysfunction Associated with Cognitive Impairments. Neuropsychiatr Dis Treat 2023; 19:1925-1933. [PMID: 37693091 PMCID: PMC10492568 DOI: 10.2147/ndt.s426213] [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: 06/16/2023] [Accepted: 08/29/2023] [Indexed: 09/12/2023] Open
Abstract
Purpose Several studies have demonstrated that psychogenic erectile dysfunction (pED) patients potentially suffer from cognitive dysfunction. Despite that previous neuroimaging studies have reported abnormal functional connections of brain areas associated with cognitive function in pED, the underlying mechanisms of cognitive dysfunction in pED remain elusive. This study aims to investigate the underlying mechanisms of cognitive dysfunction by analyzing large-scale brain networks. Patients and Methods A total of 30 patients with pED and 30 matched healthy controls (HCs) were recruited in this study and scanned by resting-state functional magnetic resonance imaging. The Dosenbach Atlas was used to define large-scale networks across the brain. The resting-state functional connectivity (FC) within and between large-scale brain networks was calculated to compare pED patients with HCs. The relationship among cognitive performances and altered FC of large-scale brain networks was further explored in pED patients. Results Our results showed that the decreased FC within visual network, and between visual network and default mode network, visual network and frontoparietal network, and ventral attention and default mode network were found in pED patients. Furthermore, there was a positive correlation between immediate memory score and FC within visual network. The visuospatial score was negatively correlated with decreased FC between ventral attention network and default mode network. Conclusion Taken together, our findings revealed the relationship between cognitive impairments and altered FC between large-scale brain networks in pED patients, providing the new evidence about the neural mechanisms of cognitive dysfunction in pED patients.
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Affiliation(s)
- Sitong Feng
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
| | - Linrui Dong
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
| | - Bin Yan
- Department of Andrology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, People’s Republic of China
| | - Sisi Zheng
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
| | - Zhengtian Feng
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
| | - Xue Li
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
| | - Jiajia Li
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
| | - Ning Sun
- Department of Andrology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, People’s Republic of China
| | - Yanzhe Ning
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
| | - Hongxiao Jia
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
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Jellinger KA. The heterogeneity of late-life depression and its pathobiology: a brain network dysfunction disorder. J Neural Transm (Vienna) 2023:10.1007/s00702-023-02648-z. [PMID: 37145167 PMCID: PMC10162005 DOI: 10.1007/s00702-023-02648-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 04/28/2023] [Indexed: 05/06/2023]
Abstract
Depression is frequent in older individuals and is often associated with cognitive impairment and increasing risk of subsequent dementia. Late-life depression (LLD) has a negative impact on quality of life, yet the underlying pathobiology is still poorly understood. It is characterized by considerable heterogeneity in clinical manifestation, genetics, brain morphology, and function. Although its diagnosis is based on standard criteria, due to overlap with other age-related pathologies, the relationship between depression and dementia and the relevant structural and functional cerebral lesions are still controversial. LLD has been related to a variety of pathogenic mechanisms associated with the underlying age-related neurodegenerative and cerebrovascular processes. In addition to biochemical abnormalities, involving serotonergic and GABAergic systems, widespread disturbances of cortico-limbic, cortico-subcortical, and other essential brain networks, with disruption in the topological organization of mood- and cognition-related or other global connections are involved. Most recent lesion mapping has identified an altered network architecture with "depressive circuits" and "resilience tracts", thus confirming that depression is a brain network dysfunction disorder. Further pathogenic mechanisms including neuroinflammation, neuroimmune dysregulation, oxidative stress, neurotrophic and other pathogenic factors, such as β-amyloid (and tau) deposition are in discussion. Antidepressant therapies induce various changes in brain structure and function. Better insights into the complex pathobiology of LLD and new biomarkers will allow earlier and better diagnosis of this frequent and disabling psychopathological disorder, and further elucidation of its complex pathobiological basis is warranted in order to provide better prevention and treatment of depression in older individuals.
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Affiliation(s)
- Kurt A Jellinger
- Institute of Clinical Neurobiology, Alberichgasse 5/13, 1150, Vienna, Austria.
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Yang T, Yan MZ, Li X, Lau EHY. Sequelae of COVID-19 among previously hospitalized patients up to 1Â year after discharge: a systematic review and meta-analysis. Infection 2022; 50:1067-1109. [PMID: 35750943 PMCID: PMC9244338 DOI: 10.1007/s15010-022-01862-3] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 05/21/2022] [Indexed: 02/06/2023]
Abstract
OBJECTIVE Although complications and clinical symptoms of COVID-19 have been elucidated, the prevalence of long-term sequelae of COVID-19 is less clear in previously hospitalized COVID-19 patients. This review and meta-analysis present the occurrence of different symptoms up to 1 year of follow-up for previously hospitalized patients. METHODS We performed a systematic review from PubMed and Web of Science using keywords such as "COVID-19", "SARS-CoV-2", "sequelae", "long-term effect" and included studies with at least 3-month of follow-up. Meta-analyses using random-effects models were performed to estimate the pooled prevalence for different sequelae. Subgroup analyses were conducted by different follow-up time, regions, age and ICU admission. RESULTS 72 articles were included in the meta-analyses after screening 11,620 articles, identifying a total of 167 sequelae related to COVID-19 from 88,769 patients. Commonly reported sequelae included fatigue (27.5%, 95% CI 22.4-33.3%, range 1.5-84.9%), somnipathy (20.1%, 95% CI 14.7-26.9%, range 1.2-64.8%), anxiety (18.0%, 95% CI 13.8-23.1%, range 0.6-47.8%), dyspnea (15.5%, 95% CI 11.3-20.9%, range 0.8-58.4%), PTSD (14.6%, 95% CI 11.3-18.7%, range 1.2-32.0%), hypomnesia (13.4%, 95% CI 8.4-20.7%, range 0.6-53.8%), arthralgia (12.9%, 95% CI 8.4-19.2%, range 0.0-47.8%), depression (12.7%, 95% CI 9.3-17.2%, range 0.6-37.5%), alopecia (11.2%, 95% CI 6.9-17.6%, range 0.0-47.0%) over 3-13.2 months of follow-up. The prevalence of most symptoms reduced after > 9 months of follow-up, but fatigue and somnipathy persisted in 26.2% and 15.1%, respectively, of the patients over a year. COVID-19 patients from Asia reported a lower prevalence than those from other regions. CONCLUSIONS This review identified a wide spectrum of COVID-19 sequelae in previously hospitalized COVID-19 patients, with some symptoms persisting up to 1 year. Management and rehabilitation strategies targeting these symptoms may improve quality of life of recovered patients.
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Affiliation(s)
- Tianqi Yang
- School of Public Health, The University of Hong Kong, Hong Kong, China
| | - Michael Zhipeng Yan
- Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Xingyi Li
- School of Public Health, The University of Hong Kong, Hong Kong, China
| | - Eric H Y Lau
- School of Public Health, The University of Hong Kong, Hong Kong, China.
- Laboratory of Data Discovery for Health Limited, Hong Kong Science Park, Hong Kong, China.
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