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Li J, Kuang S, Liu Y, Wu Y, Li H. Structural and functional brain alterations in subthreshold depression: A multimodal coordinate-based meta-analysis. Hum Brain Mapp 2024; 45:e26702. [PMID: 38726998 PMCID: PMC11083971 DOI: 10.1002/hbm.26702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 04/09/2024] [Accepted: 04/17/2024] [Indexed: 05/13/2024] Open
Abstract
Imaging studies of subthreshold depression (StD) have reported structural and functional abnormalities in a variety of spatially diverse brain regions. However, there is no consensus among different studies. In the present study, we applied a multimodal meta-analytic approach, the Activation Likelihood Estimation (ALE), to test the hypothesis that StD exhibits spatially convergent structural and functional brain abnormalities compared to healthy controls. A total of 31 articles with 25 experiments were included, collectively representing 1001 subjects with StD. We found consistent differences between StD and healthy controls mainly in the left insula across studies with various neuroimaging methods. Further exploratory analyses found structural atrophy and decreased functional activities in the right pallidum and thalamus in StD, and abnormal spontaneous activity converged to the middle frontal gyrus. Coordinate-based meta-analysis found spatially convergent structural and functional impairments in StD. These findings provide novel insights for understanding the neural underpinnings of subthreshold depression and enlighten the potential targets for its early screening and therapeutic interventions in the future.
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Affiliation(s)
- Jingyu Li
- School of PsychologyShanghai Normal UniversityShanghaiChina
- Lab for Educational Big Data and Policymaking, Ministry of EducationShanghai Normal UniversityShanghaiChina
| | - Shunrong Kuang
- School of PsychologyShanghai Normal UniversityShanghaiChina
- Lab for Educational Big Data and Policymaking, Ministry of EducationShanghai Normal UniversityShanghaiChina
| | - Yang Liu
- School of PsychologyShanghai Normal UniversityShanghaiChina
- Department of PsychologyUniversity of WashingtonSeattleWashingtonUSA
| | - Yuedong Wu
- Lab for Educational Big Data and Policymaking, Ministry of EducationShanghai Normal UniversityShanghaiChina
| | - Haijiang Li
- School of PsychologyShanghai Normal UniversityShanghaiChina
- Lab for Educational Big Data and Policymaking, Ministry of EducationShanghai Normal UniversityShanghaiChina
- The Research Base of Online Education for Shanghai Middle and Primary SchoolsShanghaiChina
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2
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Liang J, Xu Y, Gao W, Sun Y, Zhang Y, Shan F, Xia Q. Cytokine profile in first-episode drug-naïve major depressive disorder patients with or without anxiety. BMC Psychiatry 2024; 24:93. [PMID: 38308225 PMCID: PMC10835958 DOI: 10.1186/s12888-024-05536-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Accepted: 01/18/2024] [Indexed: 02/04/2024] Open
Abstract
OBJECTIVE It is known that cytokines play a role in both depression and anxiety. This study aimed to compare the levels of multiple cytokines in patients with first-episode drug-naive major depressive disorder (MDD) with or without anxiety and analyze the correlation between the level of depression or anxiety and the serum cytokine levels. METHODS The study involved 55 patients with first-episode drug-naive MDD. To assess anxiety symptoms, the 14-item HAMA was used. MDD patients were divided into two groups: 23 MDD patients without anxiety and 32 MDD patients with anxiety. The measurement of 37 cytokines was conducted. Serum cytokine levels between patients with MDD without anxiety and anxiety were compared. In multiple linear regression models, the relationship between the group and abnormal cytokines was explored. The receiver operating characteristic (ROC) curve analysis was performed to estimate diagnostic performance of serum cytokines in discriminating MDD patients with anxiety from MDD patients without anxiety. A correlation was evaluated between the scores of HAMD or HAMA and the serum cytokine levels. RESULTS In MDD patients with anxiety, IL-17 C and CCL17 levels were significantly lower than in MDD patients without anxiety (all P < 0.05). Multiple measurements were corrected with Benjamini-Hochberger corrections, but none of these differences persisted (all P > 0.05). The results of multiple linear regression models revealed that after controlling for other independent variables, group was not a significant independent predictor of serum IL-17 C or CCL17 (all P > 0.05). The AUC values of IL-17 C and CCL17 were 0.643 and 0.637, respectively, in discriminating MDD patients with anxiety from MDD patients without anxiety. The results of partial correlation analyses showed the scores of HAMD were negatively correlated with the IL-17 C (r = -0.314, P = 0.021) levels with sex as a covariate. CONCLUSIONS The findings suggest that there is a potential absence of disparity in the levels of circulating cytokines among individuals diagnosed with first-episode drug-naïve MDD, regardless of the presence or absence of comorbid anxiety.
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Affiliation(s)
- Jun Liang
- Affiliated Psychological Hospital of Anhui Medical University, Hefei, China
- Department of Pharmacy, Hefei Fourth People's Hospital, Hefei, China
- Psychopharmacology Research Laboratory, Anhui Mental Health Center, Hefei, China
- Anhui Clinical Research Center for Mental Disorders, Hefei, China
| | - Yayun Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Anhui Institute of Innovative Drugs, Anhui Medical University, Hefei, China
- The Key Laboratory of Anti-inflammatory and Immune Medicines, Ministry of Education, Hefei, China
| | - Wenfan Gao
- Affiliated Psychological Hospital of Anhui Medical University, Hefei, China
- Department of Pharmacy, Hefei Fourth People's Hospital, Hefei, China
- Psychopharmacology Research Laboratory, Anhui Mental Health Center, Hefei, China
- Anhui Clinical Research Center for Mental Disorders, Hefei, China
| | - Yanhong Sun
- Affiliated Psychological Hospital of Anhui Medical University, Hefei, China
- Department of Pharmacy, Hefei Fourth People's Hospital, Hefei, China
- Psychopharmacology Research Laboratory, Anhui Mental Health Center, Hefei, China
- Anhui Clinical Research Center for Mental Disorders, Hefei, China
| | - Yuanyuan Zhang
- Affiliated Psychological Hospital of Anhui Medical University, Hefei, China
- Department of Pharmacy, Hefei Fourth People's Hospital, Hefei, China
- Psychopharmacology Research Laboratory, Anhui Mental Health Center, Hefei, China
- Anhui Clinical Research Center for Mental Disorders, Hefei, China
| | - Feng Shan
- Affiliated Psychological Hospital of Anhui Medical University, Hefei, China
- Department of Pharmacy, Hefei Fourth People's Hospital, Hefei, China
- Psychopharmacology Research Laboratory, Anhui Mental Health Center, Hefei, China
- Anhui Clinical Research Center for Mental Disorders, Hefei, China
| | - Qingrong Xia
- Affiliated Psychological Hospital of Anhui Medical University, Hefei, China.
- Department of Pharmacy, Hefei Fourth People's Hospital, Hefei, China.
- Psychopharmacology Research Laboratory, Anhui Mental Health Center, Hefei, China.
- Anhui Clinical Research Center for Mental Disorders, Hefei, China.
- Department of Science and Education, Hefei Fourth People's Hospital, Affiliated Psychological Hospital of Anhui Medical University, Anhui Mental Health Center, 316 Huangshan Road, 230000, Hefei, PR China.
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Kryza-Lacombe M, Kassel MT, Insel PS, Rhodes E, Bickford D, Burns E, Butters MA, Tosun D, Aisen P, Raman R, Landau S, Saykin AJ, Toga AW, Jack CR, Koeppe R, Weiner MW, Nelson C, Mackin RS. Anxiety in late-life depression: Associations with brain volume, amyloid beta, white matter lesions, cognition, and functional ability. Int Psychogeriatr 2024:1-12. [PMID: 38268483 DOI: 10.1017/s1041610224000012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2024]
Abstract
OBJECTIVES Late-life depression (LLD) is common and frequently co-occurs with neurodegenerative diseases of aging. Little is known about how heterogeneity within LLD relates to factors typically associated with neurodegeneration. Varying levels of anxiety are one source of heterogeneity in LLD. We examined associations between anxiety symptom severity and factors associated with neurodegeneration, including regional brain volumes, amyloid beta (Aβ) deposition, white matter disease, cognitive dysfunction, and functional ability in LLD. PARTICIPANTS AND MEASUREMENTS Older adults with major depression (N = 121, Ages 65-91) were evaluated for anxiety severity and the following: brain volume (orbitofrontal cortex [OFC], insula), cortical Aβ standardized uptake value ratio (SUVR), white matter hyperintensity (WMH) volume, global cognition, and functional ability. Separate linear regression analyses adjusting for age, sex, and concurrent depression severity were conducted to examine associations between anxiety and each of these factors. A global regression analysis was then conducted to examine the relative associations of these variables with anxiety severity. RESULTS Greater anxiety severity was associated with lower OFC volume (β = -68.25, t = -2.18, p = .031) and greater cognitive dysfunction (β = 0.23, t = 2.46, p = .016). Anxiety severity was not associated with insula volume, Aβ SUVR, WMH, or functional ability. When examining the relative associations of cognitive functioning and OFC volume with anxiety in a global model, cognitive dysfunction (β = 0.24, t = 2.62, p = .010), but not OFC volume, remained significantly associated with anxiety. CONCLUSIONS Among multiple factors typically associated with neurodegeneration, cognitive dysfunction stands out as a key factor associated with anxiety severity in LLD which has implications for cognitive and psychiatric interventions.
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Affiliation(s)
- Maria Kryza-Lacombe
- Mental Illness Research Education and Clinical Centers, Veterans Affairs Medical Center, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Michelle T Kassel
- Mental Illness Research Education and Clinical Centers, Veterans Affairs Medical Center, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Philip S Insel
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Emma Rhodes
- Mental Illness Research Education and Clinical Centers, Veterans Affairs Medical Center, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - David Bickford
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Emily Burns
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Meryl A Butters
- Department of Psychiatry Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Duygu Tosun
- Veterans Affairs Medical Center, San Francisco, CA, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Paul Aisen
- University of Southern California, Los Angeles, CA, USA
- Keck School of Medicine, Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA
| | - Rema Raman
- University of Southern California, Los Angeles, CA, USA
- Keck School of Medicine, Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA
| | - Susan Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences and the Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Arthur W Toga
- Laboratory of Neuro Imaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | - Robert Koeppe
- Department of Radiology, University of Michigan, Ann Arbor, USA
| | - Michael W Weiner
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
- Veterans Affairs Medical Center, San Francisco, CA, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Craig Nelson
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - R Scott Mackin
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
- Veterans Affairs Medical Center, San Francisco, CA, USA
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Zhou E, Wang W, Ma S, Xie X, Kang L, Xu S, Deng Z, Gong Q, Nie Z, Yao L, Bu L, Wang F, Liu Z. Prediction of anxious depression using multimodal neuroimaging and machine learning. Neuroimage 2024; 285:120499. [PMID: 38097055 DOI: 10.1016/j.neuroimage.2023.120499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Revised: 11/15/2023] [Accepted: 12/11/2023] [Indexed: 12/18/2023] Open
Abstract
Anxious depression is a common subtype of major depressive disorder (MDD) associated with adverse outcomes and severely impaired social function. It is important to clarify the underlying neurobiology of anxious depression to refine the diagnosis and stratify patients for therapy. Here we explored associations between anxiety and brain structure/function in MDD patients. A total of 260 MDD patients and 127 healthy controls underwent three-dimensional T1-weighted structural scanning and resting-state functional magnetic resonance imaging. Demographic data were collected from all participants. Differences in gray matter volume (GMV), (fractional) amplitude of low-frequency fluctuation ((f)ALFF), regional homogeneity (ReHo), and seed point-based functional connectivity were compared between anxious MDD patients, non-anxious MDD patients, and healthy controls. A random forest model was used to predict anxiety in MDD patients using neuroimaging features. Anxious MDD patients showed significant differences in GMV in the left middle temporal gyrus and ReHo in the right superior parietal gyrus and the left precuneus than HCs. Compared with non-anxious MDD patients, patients with anxious MDD showed significantly different GMV in the left inferior temporal gyrus, left superior temporal gyrus, left superior frontal gyrus (orbital part), and left dorsolateral superior frontal gyrus; fALFF in the left middle temporal gyrus; ReHo in the inferior temporal gyrus and the superior frontal gyrus (orbital part); and functional connectivity between the left superior temporal gyrus(temporal pole) and left medial superior frontal gyrus. A diagnostic predictive random forest model built using imaging features and validated by 10-fold cross-validation distinguished anxious from non-anxious MDD with an AUC of 0.802. Patients with anxious depression exhibit dysregulation of brain regions associated with emotion regulation, cognition, and decision-making, and our diagnostic model paves the way for more accurate, objective clinical diagnosis of anxious depression.
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Affiliation(s)
- Enqi Zhou
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Wei Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Simeng Ma
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Xinhui Xie
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Lijun Kang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Shuxian Xu
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Zipeng Deng
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Qian Gong
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Zhaowen Nie
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Lihua Yao
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Lihong Bu
- PET/CT/MRI and Molecular Imaging Center, Renmin Hospital of Wuhan University, Wuhan, China.
| | - Fei Wang
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China.
| | - Zhongchun Liu
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China; Taikang Center for Life and Medical Sciences, Wuhan University, Wuhan, China.
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Siarkos K, Karavasilis E, Velonakis G, Papageorgiou C, Smyrnis N, Kelekis N, Politis A. Brain multi-contrast, multi-atlas segmentation of diffusion tensor imaging and ensemble learning automatically diagnose late-life depression. Sci Rep 2023; 13:22743. [PMID: 38123613 PMCID: PMC10733280 DOI: 10.1038/s41598-023-49935-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 12/13/2023] [Indexed: 12/23/2023] Open
Abstract
We investigated the potential of machine learning for diagnostic classification in late-life major depression based on an advanced whole brain white matter segmentation framework. Twenty-six late-life depression and 12 never depressed individuals aged > 55 years, matched for age, MMSE, and education underwent brain diffusion tensor imaging and a multi-contrast, multi-atlas segmentation in MRIcloud. Fractional anisotropy volume, mean fractional anisotropy, trace, axial and radial diffusivity (RD) extracted from 146 white matter parcels for each subject were used to train and test the AdaBoost classifier using stratified 12-fold cross validation. Performance was evaluated using various measures. The statistical power of the classifier was assessed using label permutation test. Statistical analysis did not yield significant differences in DTI measures between the groups. The classifier achieved a balanced accuracy of 71% and an Area Under the Receiver Operator Characteristic Curve (ROC-AUC) of 0.81 by trace, and a balanced accuracy of 70% and a ROC-AUC of 0.80 by RD, in limbic, cortico-basal ganglia-thalamo-cortical loop, brainstem, external and internal capsules, callosal and cerebellar structures. Both indices shared important structures for classification, while fornix was the most important structure for classification by both indices. The classifier proved statistically significant, as trace and RD ROC-AUC scores after permutation were lower than those obtained with the actual data (P = 0.022 and P = 0.024, respectively). Similar results were obtained with the Gradient Boosting classifier, whereas the RBF-kernel Support Vector Machine with k-best feature selection did not exceed the chance level. Finally, AdaBoost significantly predicted the class using all features together. Limitations are discussed. The results encourage further investigation of the implemented methods for computer aided diagnostics and anatomically informed therapeutics.
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Affiliation(s)
- Kostas Siarkos
- Division of Geriatric Psychiatry, First Department of Psychiatry, National and Kapodistrian University of Athens, Athens, Greece.
| | - Efstratios Karavasilis
- Medical School, Democritus University of Thrace, Alexandroupolis, Greece
- Second Department of Radiology, Attikon General University Hospital, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Georgios Velonakis
- Second Department of Radiology, Attikon General University Hospital, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Charalabos Papageorgiou
- University Mental Health, Neurosciences and Precision Medicine Research Institute "Costas Stefanis", Athens, Greece
| | - Nikolaos Smyrnis
- Second Department of Psychiatry, Attikon General University Hospital, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Nikolaos Kelekis
- Second Department of Radiology, Attikon General University Hospital, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Antonios Politis
- Division of Geriatric Psychiatry, First Department of Psychiatry, National and Kapodistrian University of Athens, Athens, Greece
- Department of Psychiatry, Division of Geriatric Psychiatry and Neuropsychiatry, Johns Hopkins Medical School, Baltimore, USA
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Krause-Sorio B, Siddarth P, Milillo MM, Kilpatrick L, Ercoli L, Narr KL, Lavretsky H. Grey matter volume predicts improvement in geriatric depression in response to Tai Chi compared to Health Education. Int Psychogeriatr 2023:1-9. [PMID: 38053398 DOI: 10.1017/s1041610223004386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/07/2023]
Abstract
OBJECTIVES Geriatric depression (GD) is associated with cognitive impairment and brain atrophy. Tai-Chi-Chih (TCC) is a promising adjunct treatment to antidepressants. We previously found beneficial effects of TCC on resting state connectivity in GD. We now tested the effect of TCC on gray matter volume (GMV) change and the association between baseline GMV and clinical outcome. PARTICIPANTS Forty-nine participants with GD (>=60 y) underwent antidepressant treatment (38 women). INTERVENTION Participants completed 3 months of TCC (N = 26) or health and wellness education control (HEW; N = 23). MEASUREMENTS Depression and anxiety symptoms and MRI scans were acquired at baseline and 3-month follow-up. General linear models (GLMs) tested group-by-time interactions on clinical scores. Freesurfer 6.0 was used to process T1-weighted images and to perform voxel-wise whole-brain GLMs of group on symmetrized percent GMV change, and on the baseline GMV and symptom change association, controlling for baseline symptom severity. Age and sex served as covariates in all models. RESULTS There were no group differences in baseline demographics or clinical scores, symptom change from baseline to follow-up, or treatment-related GMV change. However, whole-brain analysis revealed that lower baseline GMV in several clusters in the TCC, but not the HEW group, was associated with larger improvements in anxiety. This was similar for right precuneus GMV and depressive symptoms. CONCLUSIONS While we observed no effect on GMV due to the interventions, baseline regional GMV predicted symptom improvements with TCC but not HEW. Longer trials are needed to investigate the long-term effects of TCC on clinical symptoms and neuroplasticity.
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Affiliation(s)
- Beatrix Krause-Sorio
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Prabha Siddarth
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Michaela M Milillo
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Lisa Kilpatrick
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Linda Ercoli
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Katherine L Narr
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
| | - Helen Lavretsky
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
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Krause-Sorio B, Siddarth P, Milillo MM, Kilpatrick LA, Narr KL, Lavretsky H. Regional gray matter volume correlates with anxiety, apathy, and resilience in geriatric depression. Int Psychogeriatr 2023; 35:698-706. [PMID: 37381880 DOI: 10.1017/s1041610223000510] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/30/2023]
Abstract
OBJECTIVES Geriatric depression (GD) is associated with significant medical comorbidity, cognitive impairment, brain atrophy, premature mortality, and suboptimal treatment response. While apathy and anxiety are common comorbidities, resilience is a protective factor. Understanding the relationships between brain morphometry, depression, and resilience in GD could inform clinical treatment. Only few studies have addressed gray matter volume (GMV) associations with mood and resilience. PARTICIPANTS Forty-nine adults aged >60 years (38 women) with major depressive disorder undergoing concurrent antidepressant treatment participated in the study. MEASUREMENTS Anatomical T1-weighted scans, apathy, anxiety, and resilience data were collected. Freesurfer 6.0 was used to preprocess T1-weighted images and qdec to perform voxel-wise whole-brain analyses. Partial Spearman correlations controlling for age and sex tested the associations between clinical scores, and general linear models identified clusters of associations between GMV and clinical scores, with age and sex as covariates. Cluster correction and Monte-Carlo simulations were applied (corrected alpha = 0.05). RESULTS Greater depression severity was associated with greater anxiety (r = 0.53, p = 0.0001), lower resilience (r = -0.33, p = 0.03), and greater apathy (r = 0.39, p = 0.01). Greater GMV in widespread, partially overlapping clusters across the brain was associated with reduced anxiety and apathy, as well as increased resilience. CONCLUSION Our results suggest that greater GMV in extended brain regions is a potential marker for resilience in GD, while GMV in more focal and overlapping regions may be markers for depression and anxiety. Interventions focused on improving symptoms in GD may seek to examine their effects on these brain regions.
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Affiliation(s)
- Beatrix Krause-Sorio
- Department of Psychiatry, Semel Institute for Neuroscience and Behavior, University of California Los Angeles, Los Angeles, CA, USA
| | - Prabha Siddarth
- Department of Psychiatry, Semel Institute for Neuroscience and Behavior, University of California Los Angeles, Los Angeles, CA, USA
| | - Michaela M Milillo
- Department of Psychiatry, Semel Institute for Neuroscience and Behavior, University of California Los Angeles, Los Angeles, CA, USA
| | - Lisa A Kilpatrick
- Department of Psychiatry, Semel Institute for Neuroscience and Behavior, University of California Los Angeles, Los Angeles, CA, USA
- G. Oppenheimer Family Center for Neurobiology of Stress and Resilience, Department of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Katherine L Narr
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
| | - Helen Lavretsky
- Department of Psychiatry, Semel Institute for Neuroscience and Behavior, University of California Los Angeles, Los Angeles, CA, USA
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8
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Estévez-López F, Kim HH, López-Vicente M, Legerstee JS, Hillegers MHJ, Tiemeier H, Muetzel RL. Physical symptoms and brain morphology: a population neuroimaging study in 12,286 pre-adolescents. Transl Psychiatry 2023; 13:254. [PMID: 37438345 DOI: 10.1038/s41398-023-02528-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 06/13/2023] [Accepted: 06/15/2023] [Indexed: 07/14/2023] Open
Abstract
Physical symptoms, also known as somatic symptoms, are those for which medical examinations do not reveal a sufficient underlying root cause (e.g., pain and fatigue). The extant literature of the neurobiological underpinnings of physical symptoms is largely inconsistent and primarily comprises of (clinical) case-control studies with small sample sizes. In this cross-sectional study, we studied the association between dimensionally measured physical symptoms and brain morphology in pre-adolescents from two population-based cohorts; the Generation R Study (n = 2649, 10.1 ± 0.6 years old) and ABCD Study (n = 9637, 9.9 ± 0.6 years old). Physical symptoms were evaluated using continuous scores from the somatic complaints syndrome scale from the parent-reported Child Behavior Checklist (CBCL). High-resolution structural magnetic resonance imaging (MRI) was collected using 3-Tesla MRI systems. Linear regression models were fitted for global brain metrics (cortical and subcortical grey matter and total white matter volume) and surface-based vertex-wise measures (surface area and cortical thickness). Results were meta-analysed. Symptoms of anxiety/depression were studied as a contrasting comorbidity. In the meta-analyses across cohorts, we found negative associations between physical symptoms and surface area in the (i) left hemisphere; in the lateral orbitofrontal cortex and pars triangularis and (ii) right hemisphere; in the pars triangularis, the pars orbitalis, insula, middle temporal gyrus and caudal anterior cingulate cortex. However, only a subset of regions (left lateral orbitofrontal cortex and right pars triangularis) were specifically associated with physical symptoms, while others were also related to symptoms of anxiety/depression. No significant associations were observed for cortical thickness. This study in preadolescents, the most representative and well-powered to date, showed that more physical symptoms are modestly related to less surface area of the prefrontal cortex mostly. While these effects are subtle, future prospective research is warranted to understand the longitudinal relationship of physical symptoms and brain changes over time. Particularly, to elucidate whether physical symptoms are a potential cause or consequence of distinct neurodevelopmental trajectories.
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Affiliation(s)
- Fernando Estévez-López
- Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
- Department of Education, Faculty of Education Sciences, SPORT Research Group (CTS-1024) and CERNEP Research Center, University of Almería, Almería, Spain.
| | - Hannah H Kim
- Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Mónica López-Vicente
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Jeroen S Legerstee
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Manon H J Hillegers
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Henning Tiemeier
- Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Ryan L Muetzel
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, the Netherlands
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9
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Yang M, Chen B, Zhou H, Mai N, Zhang M, Wu Z, Peng Q, Wang Q, Liu M, Zhang S, Lin G, Lao J, Zeng Y, Zhong X, Ning Y. Relationships Among Short Self-Reported Sleep Duration, Cognitive Impairment, and Insular Functional Connectivity in Late-Life Depression. J Alzheimers Dis 2023:JAD220968. [PMID: 37182865 DOI: 10.3233/jad-220968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
BACKGROUND Both late-life depression (LLD) and short sleep duration increase the risk of cognitive impairment. Increased insular resting-state functional connectivity (FC) has been reported in individuals with short sleep duration and dementia. OBJECTIVE This study aimed to investigate whether short sleep duration is associated with impaired cognition and higher insular FC in patients with LLD. METHODS This case- control study recruited 186 patients with LLD and 83 normal controls (NC), and comprehensive psychometric assessments, sleep duration reports and resting-state functional MRI scans (81 LLD patients and 54 NC) were conducted. RESULTS Patients with LLD and short sleep duration (LLD-SS patients) exhibited more severe depressive symptoms and worse cognitive function than those with normal sleep duration (LLD-NS patients) and NC. LLD-SS patients exhibited higher FC between the bilateral insula and inferior frontal gyrus (IFG) pars triangularis than LLD-NS patients and NC, while LLD-NS patients exhibited lower FC than NC. Increased insular FC was correlated with short sleep duration, severe depressive symptoms, and slower information processing speeds. Furthermore, an additive effect was found between sleep duration and LLD on global cognition and insular FC. CONCLUSION LLD-SS patients exhibited impaired cognition and increased insular FC. Abnormal FC in LLD-SS patients may be a therapeutic target for neuromodulation to improve sleep and cognitive performance and thus decrease the risk of dementia.
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Affiliation(s)
- Mingfeng Yang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
- The first School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Ben Chen
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Huarong Zhou
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Naikeng Mai
- Department of Neurology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Min Zhang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Zhangying Wu
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Qi Peng
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Qiang Wang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Meiling Liu
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Si Zhang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Gaohong Lin
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Jingyi Lao
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Yijie Zeng
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Xiaomei Zhong
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Yuping Ning
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
- The first School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong Province, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
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10
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Kong Z, Zhu X, Chang S, Bao Y, Ma Y, Yu W, Zhu R, Sun Q, Sun W, Deng J, Sun H. Somatic symptoms mediate the association between subclinical anxiety and depressive symptoms and its neuroimaging mechanisms. BMC Psychiatry 2022; 22:835. [PMID: 36581819 PMCID: PMC9798660 DOI: 10.1186/s12888-022-04488-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 12/20/2022] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Subclinical anxiety, depressive and somatic symptoms appear closely related. However, it remains unclear whether somatic symptoms mediate the association between subclinical anxiety and depressive symptoms and what the underlying neuroimaging mechanisms are for the mediating effect. METHODS Data of healthy participants (n = 466) and participants in remission of major depressive disorder (n = 53) were obtained from the Human Connectome Project. The Achenbach Adult Self-Report was adopted to assess anxiety, depressive and somatic symptoms. All participants completed four runs of resting-state functional magnetic resonance imaging. Mediation analyses were utilized to explore the interactions among these symptoms and their neuroimaging mechanisms. RESULTS Somatic symptoms partially mediated the association between subclinical anxiety and depressive symptoms in healthy participants (anxiety→somatic→depression: effect: 0.2785, Boot 95% CI: 0.0958-0.3729; depression→somatic→anxiety: effect: 0.0753, Boot 95% CI: 0.0232-0.1314) and participants in remission of MDD (anxiety→somatic→depression: effect: 0.2948, Boot 95% CI: 0.0357-0.7382; depression→somatic→anxiety: effect: 0.0984, Boot 95% CI: 0.0007-0.2438). Resting-state functional connectivity (FC) between the right medial superior frontal gyrus and the left thalamus and somatic symptoms as chain mediators partially mediated the effect of subclinical depressive symptoms on subclinical anxiety symptoms in healthy participants (effect: 0.0020, Boot 95% CI: 0.0003-0.0043). The mean strength of common FCs of subclinical depressive and somatic symptoms, somatic symptoms, and the mean strength of common FCs of subclinical anxiety and somatic symptoms as chain mediators partially mediated the effect of subclinical depressive symptoms on subclinical anxiety symptoms in remission of MDD (effect: 0.0437, Boot 95% CI: 0.0024-0.1190). These common FCs mainly involved the insula, precentral gyri, postcentral gyri and cingulate gyri. Furthermore, FC between the triangular part of the left inferior frontal gyrus and the left postcentral gyrus was positively associated with subclinical anxiety, depressive and somatic symptoms in remission of MDD (FDR-corrected p < 0.01). CONCLUSIONS Somatic symptoms partially mediate the interaction between subclinical anxiety and depressive symptoms. FCs involving the right medial superior frontal gyrus, left thalamus, triangular part of left inferior frontal gyrus, bilateral insula, precentral gyri, postcentral gyri and cingulate gyri maybe underlie the mediating effect of somatic symptoms.
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Affiliation(s)
- Zhifei Kong
- grid.459847.30000 0004 1798 0615Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191 China
| | - Ximei Zhu
- grid.459847.30000 0004 1798 0615Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191 China
| | - Suhua Chang
- grid.459847.30000 0004 1798 0615Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191 China
| | - Yanping Bao
- grid.11135.370000 0001 2256 9319National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, 100191 China ,grid.11135.370000 0001 2256 9319School of Public Health, Peking University, Beijing, 100191 China
| | - Yundong Ma
- grid.459847.30000 0004 1798 0615Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191 China
| | - Wenwen Yu
- grid.459847.30000 0004 1798 0615Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191 China
| | - Ran Zhu
- grid.459847.30000 0004 1798 0615Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191 China
| | - Qiqing Sun
- grid.459847.30000 0004 1798 0615Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191 China
| | - Wei Sun
- grid.459847.30000 0004 1798 0615Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191 China
| | - Jiahui Deng
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China.
| | - Hongqiang Sun
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China.
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11
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Chen X, Li W, Qin J, Gao X, Liu Y, Song S, Huang Y, Chen H. Gray matter volume and functional connectivity underlying binge eating in healthy children. Eat Weight Disord 2022; 27:3469-3478. [PMID: 36223059 DOI: 10.1007/s40519-022-01483-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 09/14/2022] [Indexed: 01/04/2023] Open
Abstract
PURPOSE As a maladaptive disordered eating behavior, binge eating (BE) onset has been reported in children as young as eight years old and is linked with a range of negative psychological consequences. However, previous neuroimaging research of BE has mainly focused on adults in clinical conditions, and little is known about the potential neurostructural and neurofunctional bases of BE in healthy children. METHODS In this study, we examined these issues in 76 primary school students (mean age = 9.86 years) using voxel-based morphometry and resting-state functional connectivity (rsFC) approaches. RESULTS After controlling for age, sex, and total intracranial volume/head motion, we observed that higher levels of BE were correlated with greater gray matter volumes (GMV) in the left fusiform and right insula and weaker rsFC between the right insula and following three regions: right orbital frontal cortex, left cingulate gyrus, and left superior frontal gyrus. No significant associations were observed between BE and regional white matter volume. Significant sex differences were found only in the relationship between BE and GMV in the left fusiform. Furthermore, the GMV- and rsFC-based predictive models (a machine-learning method) achieved significant correlations between the actual and predicted BE values, demonstrating the robustness of our findings. CONCLUSION The present study provides novel evidence for the brain structural and functional substrates of children's BE, and further reveals that the weakened communication between core regions associated with negative affectivity, reward responsivity, and executive function is strongly related to dysregulated eating. LEVEL OF EVIDENCE Level V, descriptive study.
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Affiliation(s)
- Ximei Chen
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, No. 2, Tiansheng Road, Beibei District, Chongqing, 400715, China
| | - Wei Li
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, No. 2, Tiansheng Road, Beibei District, Chongqing, 400715, China
| | - Jingmin Qin
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, No. 2, Tiansheng Road, Beibei District, Chongqing, 400715, China
| | - Xiao Gao
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, No. 2, Tiansheng Road, Beibei District, Chongqing, 400715, China
| | - Yong Liu
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, No. 2, Tiansheng Road, Beibei District, Chongqing, 400715, China
| | - Shiqing Song
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, No. 2, Tiansheng Road, Beibei District, Chongqing, 400715, China
| | - Yufei Huang
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, No. 2, Tiansheng Road, Beibei District, Chongqing, 400715, China
| | - Hong Chen
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, No. 2, Tiansheng Road, Beibei District, Chongqing, 400715, China.
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12
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Guàrdia-Olmos J, Soriano-Mas C, Tormo-Rodríguez L, Cañete-Massé C, Cerro ID, Urretavizcaya M, Menchón JM, Soria V, Peró-Cebollero M. Abnormalities in the default mode network in late-life depression: A study of resting-state fMRI. Int J Clin Health Psychol 2022; 22:100317. [PMID: 35662792 DOI: 10.1016/j.ijchp.2022.100317] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Accepted: 05/10/2022] [Indexed: 11/23/2022] Open
Abstract
Background/Objective Neuroimaging studies have reported abnormalities in the examination of functional connectivity in late-life depression (LLD) in the default mode network (DMN). The present study aims to study resting-state functional connectivity within the DMN in people diagnosed with late-life major depressive disorder (MDD) compared to healthy controls (HCs). Moreover, we would like to differentiate these same connectivity patterns between participants with high vs. low anxiety levels. Method The sample comprised 56 participants between the ages of 60 and 75; 27 of them were patients with a diagnosis of MDD. Patients were further divided into two samples according to anxiety level: the four people with the highest anxiety level and the five with the lowest anxiety level. Clinical aspects were measured using psychological questionnaires. Each participant underwent functional magnetic resonance imaging (fMRI) acquisition in different regions of interest (ROIs) of the DMN. Results There was a greater correlation between pairs of ROIs in the control group than in patients with LLD, being this effect preferentially observed in patients with higher anxiety levels. Conclusions There are differences in functional connectivity within the DMN depending on the level of psychopathology. This can be reflected in these correlations and in the number of clusters and how the brain lateralizes (clustering).
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13
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Li GZ, Liu PH, Zhang AX, Andari E, Zhang KR. A resting state fMRI study of major depressive disorder with and without anxiety. Psychiatry Res 2022; 315:114697. [PMID: 35839636 DOI: 10.1016/j.psychres.2022.114697] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Revised: 06/17/2022] [Accepted: 06/25/2022] [Indexed: 11/28/2022]
Abstract
BACKGROUND The neurobiology of the Major depressive disorder (MDD) with anxiety is still unclear. The present study aimed to explore the brain correlates of MDD with and without anxiety in men and women during resting-state fMRI. METHODS Two hundred and fifty-four patients with MDD (MDD with anxiety, N = 152) and MDD without anxiety, N = 102) and 228 healthy controls (HCs) participated in this study. We compared the fALFF(fractional amplitude of low-frequency fluctuations) and ReHo(regional homogeneity) of ACC(anterior cingulate cortex) and insula among these three groups. We also compared gender difference between MDD with anxiety and MDD without anxiety. RESULTS We found that the fALFF values within the ACC and insula were significantly lower in MDD with anxiety compared to without anxiety and HCs. However, we did not find differences in ReHo values among the three groups. In women, we found significant differences in fALFF values between MDD with and without anxiety. These differences were not observed in men. CONCLUSIONS It is possible that MDD with anxiety show less spontaneous BOLD-fMRI signal intensity within the ACC and insula compared to MDD without anxiety, especially in women. The fALFF within the ACC and insula can be a potential biomarker for severe MDD phenotype.
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Affiliation(s)
- Gai-Zhi Li
- Department of psychiatry, First Hospital of Shanxi Medical University, Taiyuan, Shanxi 030001, China; Shanxi Medical University, Taiyuan, Shanxi, China
| | - Peng-Hong Liu
- Department of psychiatry, First Hospital of Shanxi Medical University, Taiyuan, Shanxi 030001, China; Shanxi Medical University, Taiyuan, Shanxi, China
| | - Ai-Xia Zhang
- Department of psychiatry, First Hospital of Shanxi Medical University, Taiyuan, Shanxi 030001, China; Shanxi Medical University, Taiyuan, Shanxi, China
| | - Elissar Andari
- Department of Psychiatry, College of Medicine and Life Sciences, University of Toledo, Toledo, OH, United States.
| | - Ke-Rang Zhang
- Department of psychiatry, First Hospital of Shanxi Medical University, Taiyuan, Shanxi 030001, China; Shanxi Medical University, Taiyuan, Shanxi, China.
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14
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Cong E, Li Q, Chen H, Cai Y, Ling Z, Wang Y, Wen H, Zhang H, Li Y, Hu Y, Liu X, Wang X, Yang Z, Xu Y, Peng D, Wu Y. Association between the volume of subregions of the amygdala and major depression with suicidal thoughts and anxiety in a Chinese cohort. J Affect Disord 2022; 312:39-45. [PMID: 35691414 DOI: 10.1016/j.jad.2022.05.122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 05/24/2022] [Accepted: 05/27/2022] [Indexed: 11/17/2022]
Abstract
BACKGROUND Major depression is the largest single contributor to suicide, and anxiety symptoms are associated with the severity of depression and suicidality. It is important to explore biomarkers of anxiety and suicidal ideation in major depression. In this study we hypothesized that the volume of subregions of the amygdala might be indicators of anxiety and suicidal ideation in patients with major depression. METHODS We recruited 59 drug-naïve patients with first-episode depression who scored >17 on the Hamilton Rating Scale for depression, and 30 healthy controls to participate in a magnetic resonance imaging study. We examined the volume of sub-regions of the amygdala thought to be involved in processing anxious emotion in the depression and healthy control groups. We performed pair-wise comparisons of amygdala subfield volumes in patients with depression and healthy controls with an analysis of variance. We used logistic regression to test the relationship between suicidal ideation and anxious character with the volume of subregions of the amygdala. RESULTS 1) We found a significant difference in the volumes of the left amygdala (P = 0.003) and right amygdala (P = 0.001) between the two groups. There are significant differences in the volumes of the sub-region of the left amygdala. 2) The volume of the left lateral nucleus (P<0.001), basal nucleus (P<0.001), accessory basal nucleus (P<0.05), left Paralaminar-nucleus (P<0.001), right lateral-nucleus (P<0.05), right basal-nucleus (P<0.05), right anterior-amygdaloid area AAA (P<0.05), right paralaminar-nucleus (P<0.001) in the depression group are larger than healthy controls, however the volumes of the central-nucleus (P<0.05), medial-nucleus (P<0.001) in both sides are decreased in the major depression group. 3) There is a significantly larger volume of right medial nucleus in the suicidal ideation group comparing the hopelessness (P = 0.026), and the depressive patients without hopeless thoughts (P = 0.004). 4) We found a negative relation between the left basal nucleus and anxiety (OR: 0.940, 95%CI: 0.891-0.991), and a positive relation between the accessory basal nucleus on the left side and anxiety (OR: 1.007, 95%CI: 1.002-1.158). LIMITATIONS We were not able to examine the effects of gender or age. The changes of amygdala volume in patients with depression were not followed up. Our sample size was such that independent replication is needed to confirm the robustness of our results. CONCLUSIONS The volumes of the basal nucleus in both sides are increased in depressed patients while the volumes of the central-nucleus, medial-nucleus bilaterally are reduced in the major depression group. Among the subregions, the volume of right medial nucleus might be the biomarkers for suicidal ideation in depressive patients.
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Affiliation(s)
- Enzhao Cong
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Qingfeng Li
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Haiying Chen
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yiyun Cai
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Zheng Ling
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yun Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Hui Wen
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Huifeng Zhang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yan Li
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yao Hu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Xiaohua Liu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Xuexue Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Zhi Yang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yifeng Xu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Daihui Peng
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China.
| | - Yan Wu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China.
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15
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Takahashi T, Ota M, Numata Y, Kitabatake A, Nemoto K, Tamura M, Ide M, Matsuzaki A, Kaneda Y, Arai T. Relationships between the Fear of COVID-19 Scale and regional brain atrophy in mild cognitive impairment. Acta Neuropsychiatr 2022; 34:153-62. [PMID: 35156604 DOI: 10.1017/neu.2022.7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Several studies have reported that the pandemic of coronavirus disease 2019 (COVID-19) influenced cognitive function in the elderly. However, the effect of COVID-19-related fear on brain atrophy has not been evaluated. In this study, we evaluated the relation between brain atrophy and the effect of COVID-19-related fear by analysing changes in brain volume over time using magnetic resonance imaging (MRI). METHODS Participants were 25 Japanese patients with mild cognitive impairment (MCI) or subjective cognitive decline (SCD), who underwent 1.5-tesla MRI scan twice, once before and once after the pandemic outbreak of COVID-19, and the Fear of Coronavirus Disease 2019 Scale (FCV-19S) assessment during that period. We computed regional brain atrophy per day between the 1st and 2nd scan, and evaluated the relation between the FCV-19S scores and regional shrinkage. RESULTS There was significant positive correlation between the total FCV-19S score and volume reduction per day in the right posterior cingulate cortex. Regarding the subscales of FCV-19S, we found significant positive correlation between factor 2 of the FCV-19S and shrinkage of the right posterior cingulate cortex. CONCLUSIONS There was positive correlation between the FCV-19S score and regional brain atrophy per day. Although it is already known that the psychological effects surrounding the COVID-19 pandemic cause cognitive function decline, our results further suggest that anxiety and fear related to COVID-19 cause regional brain atrophy.
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16
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Wang LQ, Zhang TH, Dang W, Liu S, Fan ZL, Tu LH, Zhang M, Wang HN, Zhang N, Ma QY, Zhang Y, Li HZ, Wang LC, Zheng YN, Wang H, Yu X. Heterogenous Subtypes of Late-Life Depression and Their Cognitive Patterns: A Latent Class Analysis. Front Psychiatry 2022; 13:917111. [PMID: 35873245 PMCID: PMC9298648 DOI: 10.3389/fpsyt.2022.917111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Accepted: 06/03/2022] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Late-life depression (LLD), characterized by cognitive deficits, is considered heterogeneous across individuals. Previous studies have identified subtypes with diverse symptom profiles, but their cognitive patterns are unknown. This study aimed to investigate the subtypes of LLD and the cognitive profile of each group. METHODS In total, 109 depressed older adults were enrolled. We performed latent class analysis using Geriatric Depression Scale items as indicators to generate latent classes. We compared the sociodemographic and clinical characteristics with cognitive functions between groups and conducted regression analysis to investigate the association between class membership and variables with significant differences. RESULTS Two classes were identified: the "pessimistic" group was characterized by pessimistic thoughts and the "worried" group with a relatively high prevalence of worry symptoms. The two groups did not differ in sociodemographic characteristics. The "pessimistic" group showed a higher rate of past history of depression and lower age of onset. The "worried" group had more physical comorbidities and a higher rate of past history of anxiety. The "pessimistic" group was more impaired in general cognitive function, executive function, information processing speed, and attention. Lower general and executive functions were associated with the membership in the "pessimistic" group. CONCLUSIONS Subjects with pessimistic symptoms and subjects with a propensity to worry may form two distinct subtypes of late-life depression with different cognitive profiles. Further, the cognitive evaluation of subjects with pessimistic symptoms is of utmost importance.
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Affiliation(s)
- Li-Qi Wang
- Clinical Research Division, Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China.,Beijing Dementia Key Lab, National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory of Mental Health, Beijing, China
| | - Tian-Hong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wei Dang
- Department of Psychiatry, Xi'an Mental Health Center, Xi'an, China
| | - Sha Liu
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Zi-Li Fan
- Clinical Research Division, Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China.,Beijing Dementia Key Lab, National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory of Mental Health, Beijing, China.,Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Li-Hui Tu
- Clinical Research Division, Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China.,Beijing Dementia Key Lab, National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory of Mental Health, Beijing, China.,Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Ming Zhang
- Clinical Research Division, Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China.,Beijing Dementia Key Lab, National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory of Mental Health, Beijing, China.,Department of Psychiatry, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Hua-Ning Wang
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Nan Zhang
- Department of Neurology, General Hospital of Tianjin Medical University, Tianjin, China
| | - Qin-Ying Ma
- Department of Neurology, The First Hospital of Hebei Medical University, Shijiazhuang, China
| | - Ying Zhang
- Clinical Research Division, Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China.,Beijing Dementia Key Lab, National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory of Mental Health, Beijing, China
| | - Hui-Zi Li
- Clinical Research Division, Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China.,Beijing Dementia Key Lab, National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory of Mental Health, Beijing, China
| | - Lu-Chun Wang
- Clinical Research Division, Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China.,Beijing Dementia Key Lab, National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory of Mental Health, Beijing, China
| | - Yao-Nan Zheng
- Clinical Research Division, Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China.,Beijing Dementia Key Lab, National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory of Mental Health, Beijing, China
| | - Huali Wang
- Clinical Research Division, Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China.,Beijing Dementia Key Lab, National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory of Mental Health, Beijing, China
| | - Xin Yu
- Clinical Research Division, Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China.,Beijing Dementia Key Lab, National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory of Mental Health, Beijing, China
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17
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Antypa D, Simos NJ, Kavroulakis E, Bertsias G, Fanouriakis A, Sidiropoulos P, Boumpas D, Papadaki E. Anxiety and depression severity in neuropsychiatric SLE are associated with perfusion and functional connectivity changes of the frontolimbic neural circuit: a resting-state f(unctional) MRI study. Lupus Sci Med 2021; 8:8/1/e000473. [PMID: 33927003 PMCID: PMC8094334 DOI: 10.1136/lupus-2020-000473] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 03/18/2021] [Accepted: 03/27/2021] [Indexed: 11/04/2022]
Abstract
OBJECTIVE To examine the hypothesis that perfusion and functional connectivity disturbances in brain areas implicated in emotional processing are linked to emotion-related symptoms in neuropsychiatric SLE (NPSLE). METHODS Resting-state fMRI (rs-fMRI) was performed and anxiety and/or depression symptoms were assessed in 32 patients with NPSLE and 18 healthy controls (HC). Whole-brain time-shift analysis (TSA) maps, voxel-wise global connectivity (assessed through intrinsic connectivity contrast (ICC)) and within-network connectivity were estimated and submitted to one-sample t-tests. Subgroup differences (high vs low anxiety and high vs low depression symptoms) were assessed using independent-samples t-tests. In the total group, associations between anxiety (controlling for depression) or depression symptoms (controlling for anxiety) and regional TSA or ICC metrics were also assessed. RESULTS Elevated anxiety symptoms in patients with NPSLE were distinctly associated with relatively faster haemodynamic response (haemodynamic lead) in the right amygdala, relatively lower intrinsic connectivity of orbital dlPFC, and relatively lower bidirectional connectivity between dlPFC and vmPFC combined with relatively higher bidirectional connectivity between ACC and amygdala. Elevated depression symptoms in patients with NPSLE were distinctly associated with haemodynamic lead in vmPFC regions in both hemispheres (lateral and medial orbitofrontal cortex) combined with relatively lower intrinsic connectivity in the right medial orbitofrontal cortex. These measures failed to account for self-rated, milder depression symptoms in the HC group. CONCLUSION By using rs-fMRI, altered perfusion dynamics and functional connectivity was found in limbic and prefrontal brain regions in patients with NPSLE with severe anxiety and depression symptoms. Although these changes could not be directly attributed to NPSLE pathology, results offer new insights on the pathophysiological substrate of psychoemotional symptomatology in patients with lupus, which may assist its clinical diagnosis and treatment.
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Affiliation(s)
- Despina Antypa
- Department of Psychiatry, University of Crete School of Medicine, Heraklion, Greece
| | - Nicholas J Simos
- School of Electronics and Computer Engineering, Technical University of Crete, Chania, Crete, Greece.,Computational Bio-Medicine Laboratory, Institute of Computer Science, Foundation for Research and Technology - Hellas, Heraklion, Crete, Greece
| | | | - George Bertsias
- Rheumatology, Clinical Immunology and Allergy, University Hospital of Heraklion, Heraklion, Greece.,Institute of Molecular Biology and Biotechnology, Foundation of Research and Technology-Hellas, Heraklion, Crete, Greece
| | - Antonis Fanouriakis
- Rheumatology, Clinical Immunology and Allergy, University Hospital of Heraklion, Heraklion, Greece.,"Attikon" University Hospital, Athens, Greece
| | - Prodromos Sidiropoulos
- Rheumatology, Clinical Immunology and Allergy, University Hospital of Heraklion, Heraklion, Greece
| | - Dimitrios Boumpas
- Rheumatology, Clinical Immunology and Allergy, University Hospital of Heraklion, Heraklion, Greece.,"Attikon" University Hospital, Athens, Greece.,Laboratory of Autoimmunity and Inflammation, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.,Joint Academic Rheumatology Program, and 4th Department of Medicine, Medical School, National and Kapodestrian University of Athens, Athens, Greece
| | - Efrosini Papadaki
- Computational Bio-Medicine Laboratory, Institute of Computer Science, Foundation for Research and Technology - Hellas, Heraklion, Crete, Greece .,Department of Radiology, University of Crete, School of Medicine, Heraklion, Greece
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18
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Grzenda A, Speier W, Siddarth P, Pant A, Krause-Sorio B, Narr K, Lavretsky H. Machine Learning Prediction of Treatment Outcome in Late-Life Depression. Front Psychiatry 2021; 12:738494. [PMID: 34744829 PMCID: PMC8563624 DOI: 10.3389/fpsyt.2021.738494] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 09/20/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Recent evidence suggests that integration of multi-modal data improves performance in machine learning prediction of depression treatment outcomes. Here, we compared the predictive performance of three machine learning classifiers using differing combinations of sociodemographic characteristics, baseline clinical self-reports, cognitive tests, and structural magnetic resonance imaging (MRI) features to predict treatment outcomes in late-life depression (LLD). Methods: Data were combined from two clinical trials conducted with depressed adults aged 60 and older, including response to escitalopram (N = 32, NCT01902004) and Tai Chi (N = 35, NCT02460666). Remission was defined as a score of 6 or less on the 24-item Hamilton Rating Scale for Depression (HAMD) at the end of 24 weeks of treatment. Features subsets were constructed from baseline sociodemographic and clinical features, gray matter volumes (GMVs), or both. Three classification algorithms were compared: (1) Support Vector Machine-Radial Bias Function (SVMRBF), (2) Random Forest (RF), and (3) Logistic Regression (LR). A repeated 5-fold cross-validation approach with a wrapper-based feature selection method was used for model fitting. Model performance metrics included Area under the ROC Curve (AUC) and Matthews correlation coefficient (MCC). Cross-validated performance significance was tested by permutation analysis. Classifiers were compared by Cochran's Q and post-hoc pairwise comparisons using McNemar's Chi-Square test with Bonferroni correction. Results: For the RF and SVMRBF algorithms, the combined feature set outperformed the clinical and GMV feature sets with a final cross-validated AUC of 0.83 ± 0.11 and 0.80 ± 0.11, respectively. Both classifiers passed permutation analysis. The LR algorithm performed best using GMV features alone (AUC 0.79 ± 0.14) but failed to pass permutation analysis using any feature set. Performance of the three classifiers differed significantly for all three features sets. Important predictive features of treatment response included anterior and posterior cingulate volumes, depression characteristics, and self-reported health-related quality scores. Conclusion: This preliminary exploration into the use of ML and multi-modal data to identify predictors of general treatment response in LLD indicates that integration of clinical and structural MRI features significantly increases predictive capability. Identified features are among those previously implicated in geriatric depression, encouraging future work in this arena.
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Affiliation(s)
- Adrienne Grzenda
- Department of Psychiatry and Biobehavioral Science, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - William Speier
- Medical Imaging and Informatics Group, Department of Radiological Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Prabha Siddarth
- Department of Psychiatry and Biobehavioral Science, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.,Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States
| | - Anurag Pant
- Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States
| | - Beatrix Krause-Sorio
- Department of Psychiatry and Biobehavioral Science, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.,Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States
| | - Katherine Narr
- Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Helen Lavretsky
- Department of Psychiatry and Biobehavioral Science, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.,Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States
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19
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Pini L, Wennberg AM. Structural imaging outcomes in subjective cognitive decline: Community vs. clinical-based samples. Exp Gerontol 2021; 145:111216. [PMID: 33340685 DOI: 10.1016/j.exger.2020.111216] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Revised: 11/13/2020] [Accepted: 12/05/2020] [Indexed: 11/21/2022]
Abstract
Subjective cognitive decline (SCD) has been proposed as a preclinical stage of Alzheimer's disease (AD). Neuroimaging studies have suggested early AD-like structural brain alterations in SCD subjects compared to healthy controls. However, there is substantial heterogeneity in the results, which might depend on whether SCD samples were drawn from the community or from memory clinics. Here we reviewed brain atrophy, assessed through structural magnetic resonance imaging, separately for SCD-community and clinic-based samples. SCD-community samples show a more consistent pattern of atrophy, involving the hippocampus and temporal and parietal cortices. Similarly, in SCD-clinic samples the temporo-parietal cortex showed early vulnerability, however these studies reported a more heterogeneous atrophy pattern. Overall, these studies suggest both commonalities and differences in brain atrophy patterns between SCD clinical and community samples. In SCD-community, the temporal cortex is involved, while SCD-clinical exhibited a more complex pattern of atrophy, which may be related to a more heterogeneous sample reporting neuropsychiatric symptoms along with preclinical AD.
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20
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Li H, Lin X, Liu L, Su S, Zhu X, Zheng Y, Huang W, Que J, Shi L, Bao Y, Lu L, Deng J, Sun X. Disruption of the structural and functional connectivity of the frontoparietal network underlies symptomatic anxiety in late-life depression. Neuroimage Clin 2020; 28:102398. [PMID: 32919365 DOI: 10.1016/j.nicl.2020.102398] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Revised: 08/18/2020] [Accepted: 08/19/2020] [Indexed: 12/31/2022]
Abstract
LLD patients present lower functional connectivity in the right FPN. LLD patients present impaired white matter integrity in tracts to the right FPN. FPN alterations were negatively correlated with anxiety severity in LLD patients. The right IFG might be a crucial hub underlying the neuropathology of LLD.
The present study investigated functional connectivity and white matter integrity of the fronto-parietal network (FPN) to reveal the neural mechanisms that underlie late-life depression (LLD). Fifty patients with LLD and 40 non-depressed controls were included in the study. A multi-parametric approach was used by applying independent component analysis (ICA) to estimate functional connectivity of the FPN and by applying tractbased spatial statistics to examine white-matter integrity in tracts to the FPN. Patients with LLD exhibited functional abnormalities in the right inferior frontal gyrus, middle frontal gyrus, and inferior parietal gyrus and lower white matter fractional anisotropy in the right inferior fronto-occipital fasciculus, anterior thalamic radiation, and uncinate fasciculus. Alterations of functional connectivity and white matter fractional anisotropy in these regions were negatively correlated with the severity of symptomatic anxiety in LLD patients. The right inferior frontal gyrus might be a crucial hub in transferring information between these abnormal regions. Significant correlations were found between anxiety symptoms and brain alterations, suggesting that impairments in the FPN network might be involved in symptomatic anxiety in elderly individuals with depression.
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