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Lu F, Zhang J, Zhong Y, Hong L, Wang J, Du H, Fang J, Fan Y, Wang X, Yang Y, He Z, Jia C, Wang W, Lv X. Neural signatures of default mode network subsystems in first-episode, drug-naive patients with major depressive disorder after 6-week thought induction psychotherapy treatment. Brain Commun 2024; 6:fcae263. [PMID: 39171204 PMCID: PMC11337011 DOI: 10.1093/braincomms/fcae263] [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: 05/08/2024] [Revised: 06/20/2024] [Accepted: 08/08/2024] [Indexed: 08/23/2024] Open
Abstract
Evidence indicates that the default mode network (DMN) plays a crucial role in the neuropathology of major depressive disorder (MDD). However, the neural signatures of DMN subsystems in MDD after low resistance Thought Induction Psychotherapy (TIP) remain incompletely understood. We collected functional magnetic resonance imaging data from 20 first-episode, drug-naive MDD and 20 healthy controls (HCs). The DMN was segmented into three subsystems and seed-based functional connectivity (FC) was computed. After 6-week treatment, the significantly reduced FCs with the medial temporal lobe memory subsystem in MDD at baseline were enhanced and were comparable to that in HCs. Changed Hamilton Depression Rating Scale scores were significantly related with changed FC between the posterior cingulate cortex (PCC) and the right precuneus (PCUN). Further, changed serotonin 5-hydroxytryptamine levels were significantly correlated with changed FCs between the PCC and the left PCUN, between the posterior inferior parietal lobule and the left inferior temporal gyrus, and between the retrosplenial cortex and the right inferior frontal gyrus, opercular part. Finally, the support vector machine obtained an accuracy of 67.5% to distinguish between MDD at baseline and HCs. These findings may deepen our understanding of the neural basis of the effects of TIP on DMN subsystems in MDD.
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Affiliation(s)
- Fengmei Lu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Jinhua Zhang
- Psychology Department of Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Yihua Zhong
- Teaching Department, The Open University of Chengdu, Chengdu 610213, China
| | - Lan Hong
- Psychology Department of Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Jian Wang
- Psychology Department of Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Hui Du
- Psychology Department of Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Jiliang Fang
- Psychology Department of Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Yangyang Fan
- Psychology Department of Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Xiaoling Wang
- Psychology Department of Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Yang Yang
- Psychology Department of Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Zongling He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Chen Jia
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Weidong Wang
- Psychology Department of Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Xueyu Lv
- Psychology Department of Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
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Janet R, Derrington E, Dreher JC. Relationships between Serotonin Transporter Availability and the Global Efficiency of the Executive Control Brain Network. Int J Mol Sci 2024; 25:5713. [PMID: 38891901 PMCID: PMC11171774 DOI: 10.3390/ijms25115713] [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: 03/29/2024] [Revised: 05/14/2024] [Accepted: 05/18/2024] [Indexed: 06/21/2024] Open
Abstract
The diverse effects of serotonin on cognition may emerge from the modulation of large-scale brain networks that support distinct cognitive processes. Yet, the specific effect of serotoninergic modulation on the properties of these networks remains elusive. Here, we used a simultaneous PET-fMRI scanner combined with graph theory analyses to investigate the modulation of network properties by the Serotonin Transporter (SERT) availability measured in the dorsal raphe nucleus (DRN). We defined global efficiency as the average mean of efficiencies over all pairs of distinct nodes of specific brain networks, and determined whether SERT levels correlated with the global efficiency of each network. SERT availability in the DRN correlated negatively with the global efficiency of the executive control brain network, which is engaged in cognitive control and directed attention. No relationship was observed between SERT availability and the global efficiency of the default mode or the salience brain networks. These findings indicate a specific role of serotoninergic modulation in the executive control brain network via a change in its global efficiency.
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Affiliation(s)
| | | | - Jean-Claude Dreher
- UMR5229, Neuroeconomics Laboratory, CNRS-Institut de Sciences Cognitives Marc Jeannerod, 69500 Lyon, France; (R.J.); (E.D.)
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Sawant N, Kshirsagar S, Reddy PH, Reddy AP. Protective effects of SSRI, Citalopram in mutant APP and mutant Tau expressed dorsal raphe neurons in Alzheimer's disease. Biochim Biophys Acta Mol Basis Dis 2024; 1870:166942. [PMID: 37931714 DOI: 10.1016/j.bbadis.2023.166942] [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: 06/25/2023] [Revised: 10/05/2023] [Accepted: 10/30/2023] [Indexed: 11/08/2023]
Abstract
Depression is among the most common neuropsychiatric comorbidities in Alzheimer's disease (AD) and other Tauopathies. Apart from its anti-depressive and anxiolytic effects, selective serotonin reuptake inhibitor (SSRI) treatment also offers intracellular modifications that may help to improve neurogenesis, reduce amyloid burden & Tau pathologies, and neuroinflammation in AD. Despite its multifaceted impact in the brain, the exact physiological and molecular mechanism by which SSRIs such as Citalopram improve neurogenesis and synaptogenesis in dementia is poorly understood. In the current study, we investigated the protective role of SSRI, Citalopram, in serotonergic, medullary raphe neurons (RN46A-B14). RN46A-B14 cells were transfected with wild-type and mutant APP and Tau cDNAs for 24 h and then treated with 20 μM Cit for 24 h. We then assessed mRNA and protein levels of pTau, total Tau, serotonin related proteins such as TPH2, SERT, and 5HTR1a, synaptic proteins and the cytoskeletal structure. We also assessed cell survival, mitochondrial respiration and mitochondrial morphology. The mutant APP and Tau transfected cells showed increased levels of serotonin related proteins and mRNA, while the mRNA and protein levels of synaptic proteins were downregulated. Citalopram treatment significantly reduced pathologically pTau level along with the serotonin related protein levels. On the other hand, there was a significant increase in the mRNA and protein levels of synaptic genes and cytoskeletal structure in the treated groups. Further, Citalopram also improved cell survival, mitochondrial respiration and mitochondrial morphology in the treated cells that express mAPP and mTau. Taken together these findings suggest Citalopram could not only be a promising therapeutic drug for treating patients with depression, but also for AD patients.
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Affiliation(s)
- Neha Sawant
- Nutritional Sciences Department, Texas Tech University, Lubbock, TX, USA; Internal Medicine Department, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA
| | - Sudhir Kshirsagar
- Internal Medicine Department, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA
| | - P Hemachandra Reddy
- Nutritional Sciences Department, Texas Tech University, Lubbock, TX, USA; Internal Medicine Department, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA; Pharmacology & Neuroscience Department, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA; Neurology Department, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA; Speech, Language and Hearing Sciences Departments, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA; Public Health Department, School of Population and Public Health, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA
| | - Arubala P Reddy
- Nutritional Sciences Department, Texas Tech University, Lubbock, TX, USA.
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Boucherie DE, Reneman L, Booij J, Martins D, Dipasquale O, Schrantee A. Modulation of functional networks related to the serotonin neurotransmitter system by citalopram: Evidence from a multimodal neuroimaging study. J Psychopharmacol 2023; 37:1209-1217. [PMID: 37947344 PMCID: PMC10714691 DOI: 10.1177/02698811231211154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2023]
Abstract
BACKGROUND Selective serotonin reuptake inhibitors (SSRIs) potentiate serotonergic neurotransmission by blocking the serotonin transporter (5-HTT), but the functional brain response to SSRIs involves neural circuits beyond regions with high 5-HTT expression. Currently, it is unclear whether and how changes in 5-HTT availability after SSRI administration modulate brain function of key serotoninergic circuits, including those characterized by high availability of the serotonin 1A receptor (5-HT1AR). AIM We investigated the association between 5-HTT availability and 5-HTT- and 5-HT1AR-enriched functional connectivity (FC) after an acute citalopram challenge. METHODS We analyzed multimodal data from a dose-response, placebo-controlled, double-blind study, in which 45 healthy women were randomized into three groups receiving placebo, a low (4 mg), or high (16 mg) oral dose of citalopram. Receptor-Enhanced Analysis of functional Connectivity by Targets was used to estimate 5-HTT- and 5-HT1AR-enriched FC from resting-state and task-based fMRI. 5-HTT availability was determined using [123I]FP-CIT single-photon emission computerized tomography. RESULTS 5-HTT availability was negatively correlated with resting-state 5-HTT-enriched FC, and with task-dependent 5-HT1AR-enriched FC. Our exploratory analyses revealed lower 5-HT1AR-enriched FC in the low-dose group compared to the high-dose group at rest and the placebo group during the emotional face-matching task. CONCLUSIONS Taken together, our findings provide evidence for differential links between 5-HTT availability and brain function within 5-HTT and 5-HT1AR pathways and in context- and dose-dependent manner. As such, they support a potential pivotal role of the 5-HT1AR in the effects of citalopram on the brain and add to its potential as a therapeutic avenue for mood and anxiety disturbances.
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Affiliation(s)
- Daphne E Boucherie
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location Amsterdam Medical Center, Amsterdam, The Netherlands
| | - Liesbeth Reneman
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location Amsterdam Medical Center, Amsterdam, The Netherlands
| | - Jan Booij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location Amsterdam Medical Center, Amsterdam, The Netherlands
| | - Daniel Martins
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- Division of Adult Psychiatry, Department of Psychiatry, Geneva University Hospitals, Geneva, Switzerland
| | - Ottavia Dipasquale
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Anouk Schrantee
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location Amsterdam Medical Center, Amsterdam, The Netherlands
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Ju Y, Wang M, Liu J, Liu B, Yan D, Lu X, Sun J, Dong Q, Zhang L, Guo H, Zhao F, Liao M, Zhang L, Zhang Y, Li L. Modulation of resting-state functional connectivity in default mode network is associated with the long-term treatment outcome in major depressive disorder. Psychol Med 2023; 53:5963-5975. [PMID: 36164996 DOI: 10.1017/s0033291722002628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Treatment non-response and recurrence are the main sources of disease burden in major depressive disorder (MDD). However, little is known about its neurobiological mechanism concerning the brain network changes accompanying pharmacotherapy. The present study investigated the changes in the intrinsic brain networks during 6-month antidepressant treatment phase associated with the treatment response and recurrence in MDD. METHODS Resting-state functional magnetic resonance imaging was acquired from untreated patients with MDD and healthy controls at baseline. The patients' depressive symptoms were monitored by using the Hamilton Rating Scale for Depression (HAMD). After 6 months of antidepressant treatment, patients were re-scanned and followed up every 6 months over 2 years. Traditional statistical analysis as well as machine learning approaches were conducted to investigate the longitudinal changes in macro-scale resting-state functional network connectivity (rsFNC) strength and micro-scale resting-state functional connectivity (rsFC) associated with long-term treatment outcome in MDD. RESULTS Repeated measures of the general linear model demonstrated a significant difference in the default mode network (DMN) rsFNC change before and after the 6-month antidepressant treatment between remitters and non-remitters. The difference in the rsFNC change over the 6-month antidepressant treatment between recurring and stable MDD was also specific to DMN. Machine learning analysis results revealed that only the DMN rsFC change successfully distinguished non-remitters from the remitters at 6 months and recurring from stable MDD during the 2-year follow-up. CONCLUSION Our findings demonstrated that the intrinsic DMN connectivity could be a unique and important target for treatment and recurrence prevention in MDD.
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Affiliation(s)
- Yumeng Ju
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
- Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Mi Wang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
- Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Jin Liu
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
- Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Bangshan Liu
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
- Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Danfeng Yan
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
- Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Xiaowen Lu
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
- Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Jinrong Sun
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
- Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Qiangli Dong
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
- Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Liang Zhang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
- Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Hua Guo
- Zhumadian Psychiatric Hospital, Zhumadian, Henan 463000, China
| | - Futao Zhao
- Zhumadian Psychiatric Hospital, Zhumadian, Henan 463000, China
| | - Mei Liao
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
- Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Li Zhang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
- Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Yan Zhang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
- Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
| | - Lingjiang Li
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
- Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan 410011, China
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Escitalopram modulates learning content-specific neuroplasticity of functional brain networks. Neuroimage 2021; 247:118829. [PMID: 34923134 DOI: 10.1016/j.neuroimage.2021.118829] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 12/09/2021] [Accepted: 12/15/2021] [Indexed: 01/09/2023] Open
Abstract
Learning-induced neuroplastic changes, further modulated by content and setting, are mirrored in brain functional connectivity (FC). In animal models, selective serotonin reuptake inhibitors (SSRIs) have been shown to facilitate neuroplasticity. This is especially prominent during emotional relearning, such as fear extinction, which may translate to clinical improvements in patients. To investigate a comparable modulation of neuroplasticity in humans, 99 healthy subjects underwent three weeks of emotional (matching faces) or non-emotional learning (matching Chinese characters to unrelated German nouns). Shuffled pairings of the original content were subsequently relearned for the same time. During relearning, subjects received either a daily dose of the SSRI escitalopram or placebo. Resting-state functional magnetic resonance imaging was performed before and after the (re-)learning phases. FC changes in a network comprising Broca's area, the medial prefrontal cortex, the right inferior temporal and left lingual gyrus were modulated by escitalopram intake. More specifically, it increased the bidirectional connectivity between medial prefrontal cortex and lingual gyrus for non-emotional and the connectivity from medial prefrontal cortex to Broca's area for emotional relearning. The context dependence of these effects together with behavioral correlations supports the assumption that SSRIs in clinical practice improve neuroplasticity rather than psychiatric symptoms per se. Beyond expanding the complexities of learning, these findings emphasize the influence of external factors on human neuroplasticity.
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Cui J, Wang Y, Liu R, Chen X, Zhang Z, Feng Y, Zhou J, Zhou Y, Wang G. Effects of escitalopram therapy on resting-state functional connectivity of subsystems of the default mode network in unmedicated patients with major depressive disorder. Transl Psychiatry 2021; 11:634. [PMID: 34903712 PMCID: PMC8668990 DOI: 10.1038/s41398-021-01754-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 11/21/2021] [Accepted: 11/30/2021] [Indexed: 11/09/2022] Open
Abstract
Antidepressants are often the first-line medications prescribed for patients with major depressive disorder (MDD). Given the critical role of the default mode network (DMN) in the physiopathology of MDD, the current study aimed to investigate the effects of antidepressants on the resting-state functional connectivity (rsFC) within and between the DMN subsystems. We collected resting-state functional magnetic resonance imaging (rs-fMRI) data from 36 unmedicated MDD patients at baseline and after escitalopram treatment for 12 weeks. The rs-fMRI data were also collected from 61 matched healthy controls at the time point with the same interval. Then, we decomposed the DMN into three subsystems based on a template from previous studies and computed the rsFC within and between the three subsystems. Finally, repeated measures analysis of covariance was conducted to identify the main effect of group and time and their interaction effect. We found that the significantly reduced within-subsystem rsFC in the DMN core subsystem in patients with MDD at baseline was increased after escitalopram treatment and became comparable with that in the healthy controls, whereas the reduced within-subsystem rsFC persisted in the DMN dorsal medial prefrontal cortex (dMPFC) and medial temporal subsystems in patients with MDD following escitalopram treatment. In addition, the reduced between-subsystem rsFC between the core and dMPFC subsystem showed a similar trend of change after treatment in patients with MDD. Moreover, our main results were confirmed using the DMN regions from another brain atlas. In the current study, we found different effects of escitalopram on the rsFC of the DMN subsystems. These findings deepened our understanding of the neuronal basis of antidepressants' effect on brain function in patients with MDD. The trial name: appropriate technology study of MDD diagnosis and treatment based on objective indicators and measurement. URL: http://www.chictr.org.cn/showproj.aspx?proj=21377 . Registration number: ChiCTR-OOC-17012566.
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Affiliation(s)
- Jian Cui
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, 100088, China
| | - Yun Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, 100088, China
| | - Rui Liu
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, 100088, China
| | - Xiongying Chen
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, 100088, China
| | - Zhifang Zhang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, 100088, China
| | - Yuan Feng
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, 100088, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, 100069, China
| | - Jingjing Zhou
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, 100088, China
| | - Yuan Zhou
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, 100088, China.
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, 100101, China.
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Gang Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, 100088, China.
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, 100069, China.
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8
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Molloy EN, Zsido RG, Piecha FA, Beinhölzl N, Scharrer U, Zheleva G, Regenthal R, Sehm B, Nikulin VV, Möller HE, Villringer A, Sacher J, Mueller K. Decreased thalamo-cortico connectivity during an implicit sequence motor learning task and 7 days escitalopram intake. Sci Rep 2021; 11:15060. [PMID: 34301974 PMCID: PMC8302647 DOI: 10.1038/s41598-021-94009-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Accepted: 07/05/2021] [Indexed: 11/12/2022] Open
Abstract
Evidence suggests that selective serotonin reuptake inhibitors (SSRIs) reorganize neural networks via a transient window of neuroplasticity. While previous findings support an effect of SSRIs on intrinsic functional connectivity, little is known regarding the influence of SSRI-administration on connectivity during sequence motor learning. To investigate this, we administered 20 mg escitalopram or placebo for 1-week to 60 healthy female participants undergoing concurrent functional magnetic resonance imaging and sequence motor training in a double-blind randomized controlled design. We assessed task-modulated functional connectivity with a psycho-physiological interaction (PPI) analysis in the thalamus, putamen, cerebellum, dorsal premotor, primary motor, supplementary motor, and dorsolateral prefrontal cortices. Comparing an implicit sequence learning condition to a control learning condition, we observed decreased connectivity between the thalamus and bilateral motor regions after 7 days of escitalopram intake. Additionally, we observed a negative correlation between plasma escitalopram levels and PPI connectivity changes, with higher escitalopram levels being associated with greater thalamo-cortico decreases. Our results suggest that escitalopram enhances network-level processing efficiency during sequence motor learning, despite no changes in behaviour. Future studies in more diverse samples, however, with quantitative imaging of neurochemical markers of excitation and inhibition, are necessary to further assess neural responses to escitalopram.
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Affiliation(s)
- Eóin N Molloy
- Emotion and Neuroimaging Lab, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1A, 04103, Leipzig, Germany.
- International Max Planck Research School NeuroCom, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Rachel G Zsido
- Emotion and Neuroimaging Lab, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1A, 04103, Leipzig, Germany
- International Max Planck Research School NeuroCom, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Max Planck School of Cognition, Leipzig, Germany
| | - Fabian A Piecha
- Emotion and Neuroimaging Lab, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1A, 04103, Leipzig, Germany
| | - Nathalie Beinhölzl
- Emotion and Neuroimaging Lab, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1A, 04103, Leipzig, Germany
| | - Ulrike Scharrer
- Emotion and Neuroimaging Lab, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1A, 04103, Leipzig, Germany
| | - Gergana Zheleva
- Emotion and Neuroimaging Lab, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1A, 04103, Leipzig, Germany
| | - Ralf Regenthal
- Division of Clinical Pharmacology, Rudolf-Boehm-Institute of Pharmacology and Toxicology, Leipzig University, Leipzig, Germany
| | - Bernhard Sehm
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1A, 04103, Leipzig, Germany
- Department of Neurology, University Hospital Halle (Saale), Halle, Germany
| | - Vadim V Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1A, 04103, Leipzig, Germany
- Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia
| | - Harald E Möller
- Nuclear Magnetic Resonance Methods and Development Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1A, 04103, Leipzig, Germany
- International Max Planck Research School NeuroCom, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- MindBrainBody Institute, Berlin School of Mind and Brain, Charité-Berlin University of Medicine and Humboldt University Berlin, Berlin, Germany
- Clinic of Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Julia Sacher
- Emotion and Neuroimaging Lab, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1A, 04103, Leipzig, Germany.
- International Max Planck Research School NeuroCom, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
- Max Planck School of Cognition, Leipzig, Germany.
- Clinic of Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany.
| | - Karsten Mueller
- Nuclear Magnetic Resonance Methods and Development Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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9
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Lupattelli A, Mahic M, Handal M, Ystrom E, Reichborn-Kjennerud T, Nordeng H. Attention-deficit/hyperactivity disorder in children following prenatal exposure to antidepressants: results from the Norwegian mother, father and child cohort study. BJOG 2021; 128:1917-1927. [PMID: 33982858 DOI: 10.1111/1471-0528.16743] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/31/2021] [Indexed: 01/05/2023]
Abstract
OBJECTIVE To determine the association between child attention-deficit/hyperactivity disorder (ADHD) and prenatal exposure to selective serotonin (SSRI) and serotonin-norepinephrine (SNRI) reuptake inhibitor antidepressants, by timing and duration, with quantification of bias due to exposure misclassification. DESIGN Norwegian Mother, Father and Child Cohort Study and national health registries. SETTING Nationwide, Norway. POPULATION A total of 6395 children born to women who reported depression/anxiety in pregnancy and were either medicated with SSRI/SNRI in pregnancy (n = 818) or non-medicated (n = 5228), or did not report depression/anxiety but used antidepressants 6 months before pregnancy (discontinuers, n = 349). MAIN OUTCOME MEASURE Diagnosis of ADHD or filled prescription for ADHD medication in children, and mother-reported symptoms of ADHD by child age 5 years. RESULTS When the hazard was averaged over the duration of the study follow up, there was no difference in ADHD risk between ever in utero SSRI/SNRI-exposed children and comparators (weighted hazard ratio [wHR] 1.07, 95% CI 0.76-1.51 versus non-medicated; wHR 1.53, 95% CI 0.77-3.07 versus discontinuers). Underestimation of effects due to exposure misclassification was modest. In early childhood, the risk for ADHD was lower with prenatal SSRI/SNRI exposure compared with no exposure, and so were ADHD symptoms (weighted β -0.23, 95% CI -0.39 to -0.08); this risk became elevated at child age 7-9 years (wHR 1.93, 95% CI 1.22-3.05). Maternal depression/anxiety before pregnancy was independently associated with child ADHD. CONCLUSION Prenatal SSRI/SNRI exposure is unlikely to considerably increase the risk of child ADHD beyond that posed by maternal depression/anxiety. The elevated risk at child age 7-9 years needs to be elucidated. TWEETABLE ABSTRACT Women with depression who use antidepressants in pregnancy do not have greater risk of having children with ADHD. Findings in school-age children needs follow up.
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Affiliation(s)
- A Lupattelli
- PharmacoEpidemiology and Drug Safety Research Group, Department of Pharmacy, and PharmaTox Strategic Research Initiative, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, 0316, Norway
| | - M Mahic
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, 0213, Norway
| | - M Handal
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, 0213, Norway
| | - E Ystrom
- PharmacoEpidemiology and Drug Safety Research Group, Department of Pharmacy, and PharmaTox Strategic Research Initiative, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, 0316, Norway.,Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, 0213, Norway.,Department of Psychology, PROMENTA Research Centre, University of Oslo, Oslo, Norway
| | - T Reichborn-Kjennerud
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, 0213, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - H Nordeng
- PharmacoEpidemiology and Drug Safety Research Group, Department of Pharmacy, and PharmaTox Strategic Research Initiative, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, 0316, Norway.,Department of Child Health and Development, Norwegian Institute of Public Health, Oslo, 0213, Norway
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10
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Tian T, Li J, Zhang G, Wang J, Liu D, Wan C, Fang J, Wu D, Zhou Y, Qin Y, Zhu W. Default Mode Network Alterations Induced by Childhood Trauma Correlate With Emotional Function and SLC6A4 Expression. Front Psychiatry 2021; 12:760411. [PMID: 35153849 PMCID: PMC8828908 DOI: 10.3389/fpsyt.2021.760411] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 12/08/2021] [Indexed: 11/13/2022] Open
Abstract
As one of the most studied resting-state functional networks, default mode network (DMN) is related to pathogenesis in neuropsychiatry. However, it is unclear whether changed DMN connectivity is transformed into vulnerability to psychopathology in adults who experienced childhood trauma, and what is the underlying genetic basis. Exploring the effect of DMN on environment-behavior pathway and the related genetic modulation mechanisms could further a better understanding of psychiatric pathogenesis and early prevention strategy. Two hundred and sixteen young adults with varying levels of early trauma indexed by the Childhood Trauma Questionnaire (CTQ) were recruited from the community. Static and dynamic functional connectivity based on DMN seeds and independent component analysis based on whole-brain voxels were combined to explore DMN alterations related to the CTQ score. Relationships between CTQ score, DMN connectivity, and behavioral scores were confirmed by mediation effect analysis. Imaging-genomic correlations were further used to identify risk genes whose expression was associated with the DMN changes. Dysregulated DMN connectivity was found both in seed-level and voxel-level analyses. Moreover, the functional disruption in the left temporal pole, right parahippocampal gyrus, and frontoparietal connectivity mediated the effects of childhood trauma on emotional behavior. The serotonin transporter gene was identified and might suggest the biological underpinning of the relationship between childhood trauma, DMN, and emotion regulation. Changed DMN may be useful as biomarkers to provide a powerful supplement to psychological evaluation related to childhood trauma. Combined with gene expression profiles, our findings advance a more integrative understanding of DMN alterations induced by childhood trauma, and clarify its implications for psychiatric pathogenesis and early prevention strategies.
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Affiliation(s)
- Tian Tian
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jia Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Guiling Zhang
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jian Wang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Dong Liu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Changhua Wan
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jicheng Fang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Di Wu
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yiran Zhou
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuanyuan Qin
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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11
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Klöbl M, Gryglewski G, Rischka L, Godbersen GM, Unterholzner J, Reed MB, Michenthaler P, Vanicek T, Winkler-Pjrek E, Hahn A, Kasper S, Lanzenberger R. Predicting Antidepressant Citalopram Treatment Response via Changes in Brain Functional Connectivity After Acute Intravenous Challenge. Front Comput Neurosci 2020; 14:554186. [PMID: 33123000 PMCID: PMC7573155 DOI: 10.3389/fncom.2020.554186] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 08/31/2020] [Indexed: 01/30/2023] Open
Abstract
Introduction: The early and therapy-specific prediction of treatment success in major depressive disorder is of paramount importance due to high lifetime prevalence, and heterogeneity of response to standard medication and symptom expression. Hence, this study assessed the predictability of long-term antidepressant effects of escitalopram based on the short-term influence of citalopram on functional connectivity. Methods: Twenty nine subjects suffering from major depression were scanned twice with resting-state functional magnetic resonance imaging under the influence of intravenous citalopram and placebo in a randomized, double-blinded cross-over fashion. Symptom factors were identified for the Hamilton depression rating scale (HAM-D) and Beck's depression inventory (BDI) taken before and after a median of seven weeks of escitalopram therapy. Predictors were calculated from whole-brain functional connectivity, fed into robust regression models, and cross-validated. Results: Significant predictive power could be demonstrated for one HAM-D factor describing insomnia and the total score (r = 0.45-0.55). Remission and response could furthermore be predicted with an area under the receiver operating characteristic curve of 0.73 and 0.68, respectively. Functional regions with high influence on the predictor were located especially in the ventral attention, fronto-parietal, and default mode networks. Conclusion: It was shown that medication-specific antidepressant symptom improvements can be predicted using functional connectivity measured during acute pharmacological challenge as an easily assessable imaging marker. The regions with high influence have previously been related to major depression as well as the response to selective serotonin reuptake inhibitors, corroborating the advantages of the current approach of focusing on treatment-specific symptom improvements.
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Affiliation(s)
- Manfred Klöbl
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Gregor Gryglewski
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Lucas Rischka
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | | | - Jakob Unterholzner
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Murray Bruce Reed
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Paul Michenthaler
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Thomas Vanicek
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Edda Winkler-Pjrek
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Andreas Hahn
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Siegfried Kasper
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
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12
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Zhou J, Ma X, Li C, Liao A, Yang Z, Ren H, Tang J, Li J, Li Z, He Y, Chen X. Frequency-Specific Changes in the Fractional Amplitude of the Low-Frequency Fluctuations in the Default Mode Network in Medication-Free Patients With Bipolar II Depression: A Longitudinal Functional MRI Study. Front Psychiatry 2020; 11:574819. [PMID: 33488415 PMCID: PMC7819893 DOI: 10.3389/fpsyt.2020.574819] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2020] [Accepted: 11/24/2020] [Indexed: 12/27/2022] Open
Abstract
Objective: This study aimed to examine the treatment-related changes of the fractional amplitude of low-frequency fluctuations (fALFF) in the default mode network (DMN) across different bands after the medication-free patients with bipolar II depression received a 16-week treatment of escitalopram and lithium. Methods: A total of 23 medication-free patients with bipolar II depression and 29 healthy controls (HCs) were recruited. We evaluated the fALFF values of slow 4 (0.027-0.073 Hz) band and slow 5 (0.01-0.027 Hz) band of the patients and compared the results with those of the 29 HCs at baseline. After 16-week treatment of escitalopram with lithium, the slow 4 and slow 5 fALFF values of the patients were assessed and compared with the baselines of patients and HCs. The depressive symptoms of bipolar II depression in patients were assessed with a 17-item Hamilton Depression Rating Scale (HDRS) before and after treatment. Results: Treatment-related effects showed increased slow 5 fALFF in cluster D (bilateral medial superior frontal gyrus, bilateral superior frontal gyrus, right middle frontal gyrus, and bilateral anterior cingulate), cluster E (bilateral precuneus/posterior cingulate, left cuneus), and cluster F (left angular, left middle temporal gyrus, left superior temporal gyrus, and left supramarginal gyrus) in comparison with the baseline of the patients. Moreover, a positive association was found between the increase in slow 5 fALFF values (follow-up value minus the baseline values) in cluster D and the decrease in HDRS scores (baseline HDRS scores minus follow-up HDRS scores) at follow-up, and the same association between the increase in slow 5 fALFF values and the decrease in HDRS scores was found in cluster E. Conclusions: The study reveals that the hypoactivity of slow 5 fALFF in the DMN is related to depression symptoms and might be corrected by the administration of escitalopram with lithium, implying that slow 5 fALFF of the DMN plays a key role in bipolar depression.
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Affiliation(s)
- Jun Zhou
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China.,National Technology Institute on Mental Disorders, Changsha, China.,Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China.,Mental Health Institute of Central South University, Changsha, China
| | - Xiaoqian Ma
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China.,National Technology Institute on Mental Disorders, Changsha, China.,Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China.,Mental Health Institute of Central South University, Changsha, China
| | - Chunwang Li
- Department of Radiology, Hunan Children's Hospital, Changsha, China
| | - Aijun Liao
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China.,National Technology Institute on Mental Disorders, Changsha, China.,Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China.,Mental Health Institute of Central South University, Changsha, China
| | - Zihao Yang
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China.,National Technology Institute on Mental Disorders, Changsha, China.,Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China.,Mental Health Institute of Central South University, Changsha, China
| | - Honghong Ren
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China.,National Technology Institute on Mental Disorders, Changsha, China.,Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China.,Mental Health Institute of Central South University, Changsha, China
| | - Jinsong Tang
- Department of Psychiatry, Sir Run Run Shaw Hospital, Zhejiang University, Hangzhou, China
| | - Jinguang Li
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China.,National Technology Institute on Mental Disorders, Changsha, China.,Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China.,Mental Health Institute of Central South University, Changsha, China
| | - Zongchang Li
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China.,National Technology Institute on Mental Disorders, Changsha, China.,Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China.,Mental Health Institute of Central South University, Changsha, China
| | - Ying He
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China.,National Technology Institute on Mental Disorders, Changsha, China.,Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China.,Mental Health Institute of Central South University, Changsha, China
| | - Xiaogang Chen
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China.,National Technology Institute on Mental Disorders, Changsha, China.,Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China.,Mental Health Institute of Central South University, Changsha, China
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13
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Gryglewski G, Klöbl M, Berroterán-Infante N, Rischka L, Balber T, Vanicek T, Pichler V, Kautzky A, Klebermass EM, Reed MB, Vraka C, Hienert M, James GM, Silberbauer L, Godbersen GM, Unterholzner J, Michenthaler P, Hartenbach M, Winkler-Pjrek E, Wadsak W, Mitterhauser M, Hahn A, Hacker M, Kasper S, Lanzenberger R. Modeling the acute pharmacological response to selective serotonin reuptake inhibitors in human brain using simultaneous PET/MR imaging. Eur Neuropsychopharmacol 2019; 29:711-719. [PMID: 31076187 DOI: 10.1016/j.euroneuro.2019.04.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2018] [Revised: 04/02/2019] [Accepted: 04/08/2019] [Indexed: 01/05/2023]
Abstract
Pharmacological imaging of the effects of selective serotonin reuptake inhibitors (SSRI) may aid the clarification of their mechanism of action and influence treatment of highly prevalent neuropsychiatric conditions if the detected effects could be related to patient outcomes. In a randomized double-blind design, 38 healthy participants received a constant infusion of 8 mg citalopram or saline during either their first or second of two PET/MR scans. Resting-state functional MRI (fMRI) was acquired simultaneously with PET data on the binding of serotonin transporters (5-HTT) using [11C]DASB. Three different approaches for modeling of pharmacological fMRI response were tested separately. These relied on the use of regressors corresponding to (1) the drug infusion paradigm, (2) time courses of citalopram plasma concentrations and (3) changes in 5-HTT binding measured in each individual, respectively. Furthermore, the replication of results of a widely used model-free analysis method was attempted which assesses the deviation of signal in discrete time bins of fMRI data acquired after start of drug infusion. Following drug challenge, average 5-HTT occupancy was 69±7% and peak citalopram plasma levels were 111.8 ± 21.1 ng/ml. None of the applied methods could detect significant differences in the pharmacological response between SSRI and placebo scans. The failed replication of SSRI effects reported in the literature despite a threefold larger sample size highlights the importance of appropriate correction for family-wise error in order to avoid spurious results in pharmacological imaging. This calls for the development of analysis methods which take regional specialization and the dynamics of brain activity into account.
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Affiliation(s)
- Gregor Gryglewski
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Manfred Klöbl
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Neydher Berroterán-Infante
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Austria
| | - Lucas Rischka
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Theresa Balber
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Austria
| | - Thomas Vanicek
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Verena Pichler
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Austria
| | - Alexander Kautzky
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Eva-Maria Klebermass
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Austria
| | - Murray Bruce Reed
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Chrysoula Vraka
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Austria
| | - Marius Hienert
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Gregory Miles James
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Leo Silberbauer
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Godber Mathis Godbersen
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Jakob Unterholzner
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Paul Michenthaler
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Markus Hartenbach
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Austria
| | - Edda Winkler-Pjrek
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Wolfgang Wadsak
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Austria; Center for Biomarker Research in Medicine (CBmed), Graz, Austria
| | - Markus Mitterhauser
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Austria; Ludwig Boltzmann Institute Applied Diagnostics, Vienna, Austria
| | - Andreas Hahn
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Marcus Hacker
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Austria
| | - Siegfried Kasper
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria.
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