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Lee DY, Byeon G, Kim N, Son SJ, Park RW, Park B. Neuroimaging and natural language processing-based classification of suicidal thoughts in major depressive disorder. Transl Psychiatry 2024; 14:276. [PMID: 38965206 PMCID: PMC11224278 DOI: 10.1038/s41398-024-02989-7] [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: 11/17/2023] [Revised: 06/20/2024] [Accepted: 06/26/2024] [Indexed: 07/06/2024] Open
Abstract
Suicide is a growing public health problem around the world. The most important risk factor for suicide is underlying psychiatric illness, especially depression. Detailed classification of suicide in patients with depression can greatly enhance personalized suicide control efforts. This study used unstructured psychiatric charts and brain magnetic resonance imaging (MRI) records from a psychiatric outpatient clinic to develop a machine learning-based suicidal thought classification model. The study included 152 patients with new depressive episodes for development and 58 patients from a geographically different hospital for validation. We developed an eXtreme Gradient Boosting (XGBoost)-based classification models according to the combined types of data: independent components-map weightings from brain T1-weighted MRI and topic probabilities from clinical notes. Specifically, we used 5 psychiatric symptom topics and 5 brain networks for models. Anxiety and somatic symptoms topics were significantly more common in the suicidal group, and there were group differences in the default mode and cortical midline networks. The clinical symptoms plus structural brain patterns model had the highest area under the receiver operating characteristic curve (0.794) versus the clinical notes only and brain MRI only models (0.748 and 0.738, respectively). The results were consistent across performance metrics and external validation. Our findings suggest that focusing on personalized neuroimaging and natural language processing variables improves evaluation of suicidal thoughts.
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Affiliation(s)
- Dong Yun Lee
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, South Korea
- Department of Medical Sciences, Graduate School of Ajou University, Suwon, Republic of Korea
| | - Gihwan Byeon
- Department of Psychiatry, Kangwon National University School of Medicine, Chuncheon, Republic of Korea
| | - Narae Kim
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, South Korea
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Republic of Korea
| | - Sang Joon Son
- Department of Psychiatry, Ajou University School of Medicine, Suwon, South Korea
| | - Rae Woong Park
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, South Korea.
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Republic of Korea.
| | - Bumhee Park
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, South Korea.
- Office of Biostatistics, Medical Research Collaborating Center, Ajou Research Institute for innovative medicine, Ajou University Medical Center, Suwon, Republic of Korea.
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Malhi GS, Das P, Outhred T, Bryant RA, Calhoun V, Mann JJ. Default mode dysfunction underpins suicidal activity in mood disorders. Psychol Med 2020; 50:1214-1223. [PMID: 31144614 DOI: 10.1017/s0033291719001132] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
BACKGROUND Suicide is a serious and not uncommon consequence of mood disorders that occurs primarily when individuals are depressed. Understanding the neurobiology of suicidal activity (thoughts or behaviors) is likely to facilitate prevention. METHOD Seventy-nine adult depressed mood disorder patients (MDP), of which 25 had attempted suicide at least once, and 66 healthy controls (HC) participated in this study. Resting-state functional MRI was used to identify neural activity differences between suicide attempters (SA) and non-attempters (NA). Specifically, differences were examined in functional connectivity both within and between four large cognitive networks [Executive Control (ECN), Default Mode (DMN), Salience (SN), and Basal Ganglia (BGN)] and their respective associations with suicidal activity. RESULTS Compared to HCs, patients had greater posterior DMN activity, but less activity in the BGN, and less low-frequency spectral power in the dorso-medial DMN. Furthermore, increased posterior DMN activity in SA was associated with recent suicidal activity, whereas NA had reduced BGN activity and less dorso-medial DMN spectral power, the latter being associated with lifelong suicidal thinking. SA also had greater activity in midline circuitry compared to both HC and NA, and the pattern of BGN and DMN co-activity differed between SA and NA. CONCLUSIONS DMN engagement raises the possibility that suicidal activity in mood disorder patients may be a consequence of impaired self-referential thought processing. Furthermore, differential BGN and DMN co-activation according to suicide attempt status suggests that attempting suicide perhaps alters cognitive flexibility. These insights are potentially useful for understanding the neural basis of suicide activity.
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Affiliation(s)
- Gin S Malhi
- Academic Department of Psychiatry, Northern Sydney Local Health District, St Leonards, NSW2065, Australia
- ARCHI, Sydney Medical School Northern, The University of Sydney, NSW2006, Australia
- Sydney Medical School Northern, The University of Sydney, NSW2006, Australia
- CADE Clinic, Royal North Shore Hospital, Northern Sydney Local Health District, St Leonards, NSW2065, Australia
| | - Pritha Das
- Academic Department of Psychiatry, Northern Sydney Local Health District, St Leonards, NSW2065, Australia
- ARCHI, Sydney Medical School Northern, The University of Sydney, NSW2006, Australia
- Sydney Medical School Northern, The University of Sydney, NSW2006, Australia
- CADE Clinic, Royal North Shore Hospital, Northern Sydney Local Health District, St Leonards, NSW2065, Australia
| | - Tim Outhred
- Academic Department of Psychiatry, Northern Sydney Local Health District, St Leonards, NSW2065, Australia
- ARCHI, Sydney Medical School Northern, The University of Sydney, NSW2006, Australia
- Sydney Medical School Northern, The University of Sydney, NSW2006, Australia
- CADE Clinic, Royal North Shore Hospital, Northern Sydney Local Health District, St Leonards, NSW2065, Australia
| | - Richard A Bryant
- School of Psychology, University of New South Wales, Sydney, New South Wales, NSW2052, Australia
| | - Vince Calhoun
- The Mind Research Network, Albuquerque, NM, USA
- Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA
| | - J John Mann
- Department of Psychiatry, Columbia University, New York, USA
- Molecular Imaging and the Neuropathology Division, New York State Psychiatric Institute, New York, USA
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Wang Y, Gao Y, Tang S, Lu L, Zhang L, Bu X, Li H, Hu X, Hu X, Jiang P, Jia Z, Gong Q, Sweeney JA, Huang X. Large-scale network dysfunction in the acute state compared to the remitted state of bipolar disorder: A meta-analysis of resting-state functional connectivity. EBioMedicine 2020; 54:102742. [PMID: 32259712 PMCID: PMC7136605 DOI: 10.1016/j.ebiom.2020.102742] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Revised: 02/28/2020] [Accepted: 03/16/2020] [Indexed: 02/08/2023] Open
Abstract
Background Bipolar disorder (BD) is a mental disorder characterized by mood fluctuations between an acute episodic state of either mania or depression and a clinically remitted state. Dysfunction of large-scale intrinsic brain networks has been demonstrated in this disorder, but it remains unknown whether those network alterations are related to different states. Methods In the present study, we performed a meta-analysis of whole-brain seed-based resting-state functional connectivity (rsFC) studies in BD patients to compare the intrinsic function of brain networks between episodic and remitted states. Thirty-nine seed-based voxel-wise rsFC datasets from thirty publications (1047 BD patients vs 1081 controls) were included in the meta-analysis. Seeds were categorized into networks by their locations within a priori functional networks. Seed-based d mapping analysis of between-state effects identified brain systems in which different states were associated with increased connectivity or decreased connectivity within and between each seed network. Findings We found that BD patients presented decreased connectivity within the affective network (AN) in acute episodes but not in the remitted state of the illness. Similar decreased connectivity within the default-mode network (DMN) was also found in the acute state, but it was replaced by increased connectivity in the remitted state. In addition, different patterns of between-network dysconnectivity were observed between the acute and remitted states. Interpretation This study is the first to identify different patterns of intrinsic function in large-scale brain networks between the acute and remitted states of BD through meta-analysis. The findings suggest that a shift in network function between the acute and remitted states may be related to distinct emotional and cognitive dysfunctions in BD, which may have important implications for identifying clinically relevant biomarkers to guide alternative treatment strategies for BD patients during active episodes or remission. Funding This study was supported by grants from the National Natural Science Foundation of China (81171488, 81671669 and 81820108018) and by a Sichuan Provincial Youth Grant (2017JQ0001).
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Affiliation(s)
- Yanlin Wang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Yingxue Gao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Shi Tang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Lu Lu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Lianqing Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Xuan Bu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Hailong Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Xiaoxiao Hu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Xinyu Hu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Ping Jiang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Zhiyun Jia
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, United States
| | - Xiaoqi Huang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China.
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Pasion R, Martins EC, Barbosa F. Empirically supported interventions in psychology: contributions of Research Domain Criteria. ACTA ACUST UNITED AC 2019; 32:15. [PMID: 32027006 PMCID: PMC6966736 DOI: 10.1186/s41155-019-0128-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Accepted: 07/05/2019] [Indexed: 11/10/2022]
Abstract
Empirically supported interventions in psychological disorders should provide (1) evidence supporting the underlying psychological mechanisms of psychopathology to target in the intervention and (2) evidence supporting the efficacy of the intervention. However, research has been dedicated in a greater extent to efficacy than to the acquisition of empirical support for the theoretical basis of therapies. Research Domain Criteria (RDoC) emerges as a new framework to provide empirically based theories about psychological mechanisms that may be targeted in intervention and tested for its efficacy. The current review aims to demonstrate the possible applications of RDoC to design empirically supported interventions for psychological disorders. Two RDoC-inspired interventions are reviewed, and the RDoC framework is broadly explored in terms of its contributions and limitations. From preliminary evidence, RDoC offers many avenues for improving evidence-based interventions in psychology, but some limitations must be anticipated to increase the RDoC applicability to naturalistic settings.
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Affiliation(s)
- Rita Pasion
- Laboratory of Neuropsychophysiology, Faculty of Psychology and Educational Sciences, University of Porto, Rua Alfredo Allen, 535, 4200-135, Porto, Portugal.
| | - Eva C Martins
- Department of Social and Behavioural Sciences (CPUP), University of Porto, Porto, Portugal.,Maia University Institute (ISMAI), Maia, Portugal
| | - Fernando Barbosa
- Laboratory of Neuropsychophysiology, Faculty of Psychology and Educational Sciences, University of Porto, Rua Alfredo Allen, 535, 4200-135, Porto, Portugal
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Yang J, Pu W, Ouyang X, Tao H, Chen X, Huang X, Liu Z. Abnormal Connectivity Within Anterior Cortical Midline Structures in Bipolar Disorder: Evidence From Integrated MRI and Functional MRI. Front Psychiatry 2019; 10:788. [PMID: 31736805 PMCID: PMC6829675 DOI: 10.3389/fpsyt.2019.00788] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2019] [Accepted: 10/03/2019] [Indexed: 11/13/2022] Open
Abstract
Background: Aberrant functional and structural connectivity across multiple brain networks have been reported in bipolar disorder (BD). However, most previous studies consider the functional and structural alterations in isolation regardless of their possible integrative relationship. The present study aimed to identify the brain connectivity alterations in BD by capturing the latent nexus in multimodal neuroimaging data. Methods: Structural and resting-state images were acquired from 83 patients with BD and 94 healthy controls (HCs). Combined with univariate methods conducted to detect the dysconnectivity in BD, we also employed a semi-multimodal fusion framework fully utilizing the interrelationship between the two modalities to distinguish patients from HCs. Moreover, one-way analysis of variance was adopted to explore whether the detected dysconnectivity has differences across stages of patients with BD. Results: The semi-multimodal fusion framework distinguished patients from HCs with 81.47% accuracy, 85.42% specificity, and 74.75% sensitivity. The connection between the anterior cingulate cortex (ACC) and superior medial prefrontal cortex (sMPFC) contributed the most to BD diagnosis. Consistently, the univariate method also identified that this ACC-sMPFC functional connection significantly decreased in BD patients compared to HCs, and the significant order of the dysconnectivity is: depressive episode < HCs and remission episode < HCs. Conclusions: Our findings, by adopting univariate and multivariate analysis methods, shed light on the decoupling within the anterior midline brain in the pathophysiology of BD, and this decoupling may serve as a trait marker for this disease.
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Affiliation(s)
- Jie Yang
- Institute of Mental Health, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Weidan Pu
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China.,Medical Psychological Institute, Central South University, Changsha, China
| | - Xuan Ouyang
- Institute of Mental Health, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Haojuan Tao
- Institute of Mental Health, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Xudong Chen
- Institute of Mental Health, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Xiaojun Huang
- Institute of Mental Health, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Zhening Liu
- Institute of Mental Health, The Second Xiangya Hospital, Central South University, Changsha, China
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Neural Correlates of Emotion Regulation and Adolescent Suicidal Ideation. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2017. [PMID: 29529407 DOI: 10.1016/j.bpsc.2017.08.008] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
BACKGROUND Research on the neural correlates associated with risk for suicidal ideation (SI) has been limited, particularly in one increasingly at-risk group-adolescents. Previous research with adolescents indicates that poor emotion regulation skills are linked with SI, but these studies have not previously examined neural activation in service of emotion regulation between those with and without SI histories. METHODS Here we examine whether SI is associated with neural responses during an emotion regulation functional magnetic resonance imaging task in a group of adolescents (N = 49) 13 to 20 years of age (mean = 16.95). RESULTS While there were no differences between youths with and without SI in self-reported emotional responses to negative pictures, youths with SI activated the dorsolateral prefrontal cortex more than youths without SI on trials in which they attempted to regulate their emotional responses compared with trials in which they passively viewed negative pictures. In contrast, during passive viewing of negative stimuli, youths with SI activated the dorsolateral prefrontal cortex, temporoparietal junction, and cerebellum less than same-age control subjects. CONCLUSIONS These findings were robust to control subjects for depression and adversity exposure and are consistent with the idea that youths with SI have disrupted emotion regulation, potentially related to differences in recruitment of top-down control regions. In contrast, youths without SI activated regions implicated in emotion regulation even when not directed to effortfully control their emotional response. This is the first study to examine neural function during emotion regulation as a potential neural correlate of risk for SI in adolescents.
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Johnston JAY, Wang F, Liu J, Blond BN, Wallace A, Liu J, Spencer L, Cox Lippard ET, Purves KL, Landeros-Weisenberger A, Hermes E, Pittman B, Zhang S, King R, Martin A, Oquendo MA, Blumberg HP. Multimodal Neuroimaging of Frontolimbic Structure and Function Associated With Suicide Attempts in Adolescents and Young Adults With Bipolar Disorder. Am J Psychiatry 2017; 174:667-675. [PMID: 28135845 PMCID: PMC5939580 DOI: 10.1176/appi.ajp.2016.15050652] [Citation(s) in RCA: 150] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE Bipolar disorder is associated with high risk for suicidal behavior that often develops in adolescence and young adulthood. Elucidation of involved neural systems is critical for prevention. This study of adolescents and young adults with bipolar disorder with and without a history of suicide attempts combines structural, diffusion tensor, and functional MR imaging methods to investigate implicated abnormalities in the morphology and structural and functional connectivity within frontolimbic systems. METHOD The study had 26 participants with bipolar disorder who had a prior suicide attempt (the attempter group) and 42 participants with bipolar disorder without a suicide attempt (the nonattempter group). Regional gray matter volume, white matter integrity, and functional connectivity during processing of emotional stimuli were compared between groups, and differences were explored for relationships between imaging modalities and associations with suicide-related symptoms and behaviors. RESULTS Compared with the nonattempter group, the attempter group showed significant reductions in gray matter volume in the orbitofrontal cortex, hippocampus, and cerebellum; white matter integrity in the uncinate fasciculus, ventral frontal, and right cerebellum regions; and amygdala functional connectivity to the left ventral and right rostral prefrontal cortex. In exploratory analyses, among attempters, there was a significant negative correlation between right rostral prefrontal connectivity and suicidal ideation and between left ventral prefrontal connectivity and attempt lethality. CONCLUSIONS Adolescent and young adult suicide attempters with bipolar disorder demonstrate less gray matter volume and decreased structural and functional connectivity in a ventral frontolimbic neural system subserving emotion regulation. Among attempters, reductions in amygdala-prefrontal functional connectivity may be associated with severity of suicidal ideation and attempt lethality.
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Affiliation(s)
| | - Fei Wang
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, US
| | - Jie Liu
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, US
| | - Benjamin N. Blond
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, US
| | - Amanda Wallace
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, US
| | - Jiacheng Liu
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, US
| | - Linda Spencer
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, US
| | | | - Kirstin L. Purves
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, US,Division of Psychology and Language Sciences, University College London, London, UK
| | - Angeli Landeros-Weisenberger
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, US,Child Study Center, Yale School of Medicine, New Haven, CT, USA
| | - Eric Hermes
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, US
| | - Brian Pittman
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, US
| | - Sheng Zhang
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, US
| | - Robert King
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, US,Child Study Center, Yale School of Medicine, New Haven, CT, USA
| | - Andrés Martin
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, US,Child Study Center, Yale School of Medicine, New Haven, CT, USA
| | - Maria A. Oquendo
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Hilary P. Blumberg
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, US,Child Study Center, Yale School of Medicine, New Haven, CT, USA
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