1
|
Murck H, Fava M, Cusin C, Fatt CC, Trivedi M. Brain ventricle and choroid plexus morphology as predictor of treatment response in major depression: Findings from the EMBARC study. Brain Behav Immun Health 2024; 35:100717. [PMID: 38186634 PMCID: PMC10767278 DOI: 10.1016/j.bbih.2023.100717] [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] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 12/18/2023] [Indexed: 01/09/2024] Open
Abstract
Recent observations suggest a role of the volume of the cerebral ventricle volume, corpus callosum (CC) segment volume, in particular that of the central-anterior part, and choroid plexus (CP) volume for treatment resistance of major depressive disorder (MDD). An increased CP volume has been associated with increased inflammatory activity and changes in the structure of the ventricles and corpus callosum. We attempt to replicate and confirm that these imaging markers are associated with clinical outcome in subjects from the EMBARC study, as implied by a recent pilot study. The EMBARC study is a placebo controlled randomized study comparing sertraline vs. placebo in patients with MDD to identify biological markers of therapy resistance. Association of baseline volumes of the lateral ventricles (LVV), choroid plexus volume (CPV) and volume of segments of the CC with treatment response after 4 weeks treatment was evaluated. 171 subjects (61 male, 110 female) completed the 4 week assessments; gender and age were taken into account for this analyses. As previously reported, no treatment effect of sertraline vs. placebo was observed, therefore the study characterized prognostic markers of response in the pooled population. Change in depression severity was identified by the ratio of the Hamilton-Depression rating scale 17 (HAMD-17) at week 4 divided by the HAMD-17 at baseline (HAMD-17 ratio). Volumes of the lateral ventricles and choroid plexi were positively correlated with the HAMD-17 ratio, indication worse outcome with larger ventricles and choroid plexus volumes, whereas the volume of the central-anterior corpus callosum was negatively correlated with the HAMD-17 ratio. Responders (n = 54) had significantly smaller volumes of the lateral ventricles and CP compared to non-responders (n = 117), whereas the volume of mid-anterior CC was significantly larger compared to non-responders (n = 117), confirming our previous findings. In an exploratory way associations between enlarged LVV and CPV and signs of lipid dysregulation were observed. In conclusion, we confirmed that volumes of lateral ventricles, choroid plexi and the mid-anterior corpus callosum are associated with clinical improvement of depression and may be indicators of metabolic/inflammatory activity.
Collapse
Affiliation(s)
- Harald Murck
- Dept. of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Maurizio Fava
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Cristina Cusin
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Cherise Chin Fatt
- The University of Texas Southwestern Medical Center, Department of Psychiatry, Center for Depression Research and Clinical Care, Dallas, USA
| | - Madhukar Trivedi
- The University of Texas Southwestern Medical Center, Department of Psychiatry, Center for Depression Research and Clinical Care, Dallas, USA
| |
Collapse
|
2
|
Jha MK, Chin Fatt C, Minhajuddin A, Mayes TL, Trivedi MH. Accelerated Brain Aging in Adults With Major Depressive Disorder Predicts Poorer Outcome With Sertraline: Findings From the EMBARC Study. Biol Psychiatry Cogn Neurosci Neuroimaging 2023; 8:462-470. [PMID: 36179972 PMCID: PMC10177666 DOI: 10.1016/j.bpsc.2022.09.006] [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] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 09/09/2022] [Accepted: 09/20/2022] [Indexed: 02/05/2023]
Abstract
BACKGROUND Major depressive disorder (MDD) may be associated with accelerated brain aging (higher brain age than chronological age). This report evaluated whether brain age is a clinically useful biomarker by checking its test-retest reliability using magnetic resonance imaging scans acquired 1 week apart and by evaluating the association of accelerated brain aging with symptom severity and antidepressant treatment outcomes. METHODS Brain age was estimated in participants of the EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care) study using T1-weighted structural magnetic resonance imaging (MDD n = 290; female n = 192; healthy control participants n = 39; female n = 24). Intraclass correlation coefficient was used for baseline-to-week-1 test-retest reliability. Association of baseline Δ brain age (brain age minus chronological age) with Hamilton Depression Rating Scale-17 and Concise Health Risk Tracking Self-Report domains (impulsivity, suicide propensity [measures: pessimism, helplessness, perceived lack of social support, and despair], and suicidal thoughts) were assessed at baseline (linear regression) and during 8-week-long treatment with either sertraline or placebo (repeated-measures mixed models). RESULTS Mean ± SD baseline chronological age, brain age, and Δ brain age were 37.1 ± 13.3, 40.6 ± 13.1, and 3.1 ± 6.1 years in MDD and 37.1 ± 14.7, 38.4 ± 12.9, and 0.6 ± 5.5 years in healthy control groups, respectively. Test-retest reliability was high (intraclass correlation coefficient = 0.98-1.00). Higher baseline Δ brain age in the MDD group was associated with higher baseline impulsivity and suicide propensity and predicted smaller baseline-to-week-8 reductions in Hamilton Depression Rating Scale-17, impulsivity, and suicide propensity with sertraline but not with placebo. CONCLUSIONS Brain age is a reliable and potentially clinically useful biomarker that can prognosticate antidepressant treatment outcomes.
Collapse
Affiliation(s)
- Manish K Jha
- Center for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas; Department of Psychiatry, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Cherise Chin Fatt
- Center for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas; Department of Psychiatry, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Abu Minhajuddin
- Center for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas; Department of Psychiatry, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Taryn L Mayes
- Center for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas; Department of Psychiatry, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Madhukar H Trivedi
- Center for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas; Department of Psychiatry, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, Texas.
| |
Collapse
|
3
|
Chin Fatt C, Ayvaci ER, Jha MK, Emslie G, Gibson S, Minhajuddin AT, Mayes TL, Farrar JD, Trivedi MH. Characterizing inflammatory profiles of suicidal behavior in adolescents: Rationale and design. J Affect Disord 2023; 325:55-61. [PMID: 36586601 PMCID: PMC10177665 DOI: 10.1016/j.jad.2022.12.114] [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: 05/11/2022] [Revised: 08/26/2022] [Accepted: 12/23/2022] [Indexed: 12/30/2022]
Abstract
BACKGROUND The suicide rate in youth and young adults continues to climb - we do not understand why this increase is occurring, nor do we have adequate tools to predict or prevent it. Increased efforts to treat underlying depression and other disorders that are highly associated with suicide have had limited impact, despite considerable financial investments in developing and disseminating available methods. Thus, there is a tremendous need to identify potential markers of suicide behavior for youth during this high-risk period. METHODS Funded by the American Foundation for Suicide Prevention (AFSP), this study aims to map immune dysfunction to suicidal behavior and establish a reliable immune signature of suicide risk that can 1) guide future research into fundamental pathophysiology and 2) identify targets for drug development. The study design is an observational study where blood samples and a comprehensive array of clinical measures are collected from three groups of adolescents (n = 75 each) (1) with suicidal behavior [recent (within 3 months) suicide attempt or suicidal ideation warranting urgent evaluation,] (2) at risk for mood disorders, and (3) who are healthy (no psychiatric history). Participants will complete self-report and clinical assessments, along with a blood draw, at baseline, 3 months, 6 months and 12 months, and online self-report assessments once a month. RESULTS The recruitment for this study is ongoing. LIMITATIONS Observational, variability in treatment regimens. CONCLUSIONS This study will help elucidate immune mechanisms that may play a causal role in suicide and serve as targets for future therapeutic development.
Collapse
Affiliation(s)
- Cherise Chin Fatt
- Center for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA; Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Emine Rabia Ayvaci
- Center for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA; Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA; Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Manish K Jha
- Center for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA; Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Graham Emslie
- Center for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA; Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Sarah Gibson
- Center for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA; Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Abu T Minhajuddin
- Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Taryn L Mayes
- Center for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA; Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - J David Farrar
- Department of Immunology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Madhukar H Trivedi
- Center for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA; Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA.
| |
Collapse
|
4
|
Murck H, Fava M, Cusin C, Chin Fatt C, Trivedi M. Brain Ventricle and Choroid Plexus Morphology as Predictor of Treatment Response: Findings from the EMBARC Study. Res Sq 2023:rs.3.rs-2618151. [PMID: 36909585 PMCID: PMC10002825 DOI: 10.21203/rs.3.rs-2618151/v1] [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] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/05/2023]
Abstract
Recent observations suggest a role of the choroid plexus (CP) and cerebral ventricle volume (CV), to identify treatment resistance of major depressive disorder (MDD). We tested the hypothesis that these markers are associated with clinical improvement in subjects from the EMBARC study, as implied by a recent pilot study. The EMBARC study characterized biological markers in a randomized placebo-controlled trial of sertraline vs. placebo in patients with MDD. Association of baseline volumes of CV, CP and of the corpus callosum (CC) with treatment response after 4 weeks treatment were evaluated. 171 subjects (61 male, 110 female) completed the 4 week assessments; gender, site and age were taken into account for this analyses. As previously reported, no treatment effect of sertraline was observed, but prognostic markers for clinical improvement were identified. Responders (n = 54) had significantly smaller volumes of the CP and lateral ventricles, whereas the volume of mid-anterior and mid-posterior CC was significantly larger compared to non-responders (n = 117). A positive correlation between CV volume and CP volume was observed, whereas a negative correlation between CV volume and both central-anterior and central-posterior parts of the CC emerged. In an exploratory way correlations between enlarged VV and CP volume on the one hand and signs of metabolic syndrome, in particular triglyceride plasma concentrations, were observed. A primary abnormality of CP function in MDD may be associated with increased ventricles, compression of white matter volume, which may affect treatment response speed or outcome. Metabolic markers may mediate this relationship.
Collapse
Affiliation(s)
- Harald Murck
- Dept. of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Maurizio Fava
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Cristina Cusin
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Cherise Chin Fatt
- The University of Texas Southwestern Medical Center, Department of Psychiatry, Center for Depression Research and Clinical Care, Department of Psychiatry, Dallas, USA
| | - Madhukar Trivedi
- The University of Texas Southwestern Medical Center, Department of Psychiatry, Center for Depression Research and Clinical Care, Department of Psychiatry, Dallas, USA
| |
Collapse
|
5
|
Fu CHY, Erus G, Fan Y, Antoniades M, Arnone D, Arnott SR, Chen T, Choi KS, Fatt CC, Frey BN, Frokjaer VG, Ganz M, Garcia J, Godlewska BR, Hassel S, Ho K, McIntosh AM, Qin K, Rotzinger S, Sacchet MD, Savitz J, Shou H, Singh A, Stolicyn A, Strigo I, Strother SC, Tosun D, Victor TA, Wei D, Wise T, Woodham RD, Zahn R, Anderson IM, Deakin JFW, Dunlop BW, Elliott R, Gong Q, Gotlib IH, Harmer CJ, Kennedy SH, Knudsen GM, Mayberg HS, Paulus MP, Qiu J, Trivedi MH, Whalley HC, Yan CG, Young AH, Davatzikos C. AI-based dimensional neuroimaging system for characterizing heterogeneity in brain structure and function in major depressive disorder: COORDINATE-MDD consortium design and rationale. BMC Psychiatry 2023; 23:59. [PMID: 36690972 PMCID: PMC9869598 DOI: 10.1186/s12888-022-04509-7] [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] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 12/29/2022] [Indexed: 01/24/2023] Open
Abstract
BACKGROUND Efforts to develop neuroimaging-based biomarkers in major depressive disorder (MDD), at the individual level, have been limited to date. As diagnostic criteria are currently symptom-based, MDD is conceptualized as a disorder rather than a disease with a known etiology; further, neural measures are often confounded by medication status and heterogeneous symptom states. METHODS We describe a consortium to quantify neuroanatomical and neurofunctional heterogeneity via the dimensions of novel multivariate coordinate system (COORDINATE-MDD). Utilizing imaging harmonization and machine learning methods in a large cohort of medication-free, deeply phenotyped MDD participants, patterns of brain alteration are defined in replicable and neurobiologically-based dimensions and offer the potential to predict treatment response at the individual level. International datasets are being shared from multi-ethnic community populations, first episode and recurrent MDD, which are medication-free, in a current depressive episode with prospective longitudinal treatment outcomes and in remission. Neuroimaging data consist of de-identified, individual, structural MRI and resting-state functional MRI with additional positron emission tomography (PET) data at specific sites. State-of-the-art analytic methods include automated image processing for extraction of anatomical and functional imaging variables, statistical harmonization of imaging variables to account for site and scanner variations, and semi-supervised machine learning methods that identify dominant patterns associated with MDD from neural structure and function in healthy participants. RESULTS We are applying an iterative process by defining the neural dimensions that characterise deeply phenotyped samples and then testing the dimensions in novel samples to assess specificity and reliability. Crucially, we aim to use machine learning methods to identify novel predictors of treatment response based on prospective longitudinal treatment outcome data, and we can externally validate the dimensions in fully independent sites. CONCLUSION We describe the consortium, imaging protocols and analytics using preliminary results. Our findings thus far demonstrate how datasets across many sites can be harmonized and constructively pooled to enable execution of this large-scale project.
Collapse
Affiliation(s)
- Cynthia H Y Fu
- Department of Psychological Sciences, University of East London, London, UK.
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK.
| | - Guray Erus
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Yong Fan
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Mathilde Antoniades
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Danilo Arnone
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
- Department of Psychiatry and Behavioral Science, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | | | - Taolin Chen
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Ki Sueng Choi
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Cherise Chin Fatt
- Department of Psychiatry, Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, USA
| | - Benicio N Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Canada
- Mood Disorders Treatment and Research Centre and Women's Health Concerns Clinic, St Joseph's Healthcare Hamilton, Hamilton, Canada
| | - Vibe G Frokjaer
- Neurobiology Research Unit, University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Psychiatry, Psychiatric Centre Copenhagen, Copenhagen, Denmark
| | - Melanie Ganz
- Neurobiology Research Unit, University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | - Jose Garcia
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Beata R Godlewska
- Department of Psychiatry, University of Oxford, Oxford, UK
- Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, UK
| | - Stefanie Hassel
- Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary, Canada
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, Canada
| | - Keith Ho
- Department of Psychiatry, University Health Network, Toronto, Canada
| | - Andrew M McIntosh
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Kun Qin
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Susan Rotzinger
- Department of Psychiatry, University Health Network, Toronto, Canada
- Centre for Depression and Suicide Studies, Unity Health Toronto, Toronto, Canada
| | - Matthew D Sacchet
- Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, USA
| | | | - Haochang Shou
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE) Center, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, USA
| | - Ashish Singh
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Aleks Stolicyn
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Irina Strigo
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Stephen C Strother
- Rotman Research Institute, Baycrest Centre, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Duygu Tosun
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | | | - Dongtao Wei
- School of Psychology, Southwest University, Chongqing, China
| | - Toby Wise
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Rachel D Woodham
- Department of Psychological Sciences, University of East London, London, UK
| | - Roland Zahn
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Ian M Anderson
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
| | - J F William Deakin
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
| | - Boadie W Dunlop
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, USA
| | - Rebecca Elliott
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Ian H Gotlib
- Department of Psychology, Stanford University, Stanford, USA
| | | | - Sidney H Kennedy
- Department of Psychiatry, University Health Network, Toronto, Canada
- Centre for Depression and Suicide Studies, Unity Health Toronto, Toronto, Canada
- Unity Health Toronto, Toronto, Canada
| | - Gitte M Knudsen
- Neurobiology Research Unit, University Hospital Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Helen S Mayberg
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, USA
| | | | - Jiang Qiu
- School of Psychology, Southwest University, Chongqing, China
| | - Madhukar H Trivedi
- Department of Psychiatry, Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, USA
| | - Heather C Whalley
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Chao-Gan Yan
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China
| | - Allan H Young
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
- South London and Maudsley NHS Foundation Trust, Bethlem Royal Hospital, London, UK
| | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| |
Collapse
|
6
|
Trombello JM, Cooper CM, Fatt CC, Grannemann BD, Carmody TJ, Jha MK, Mayes TL, Greer TL, Yezhuvath U, Aslan S, Pizzagalli DA, Weissman MM, Webb CA, Dillon DG, McGrath PJ, Fava M, Parsey RV, McInnis MG, Etkin A, Trivedi MH. Neural substrates of emotional conflict with anxiety in major depressive disorder: Findings from the Establishing Moderators and biosignatures of Antidepressant Response in Clinical Care (EMBARC) randomized controlled trial. J Psychiatr Res 2022; 149:243-251. [PMID: 35290819 PMCID: PMC9746288 DOI: 10.1016/j.jpsychires.2022.03.015] [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: 11/05/2021] [Revised: 02/16/2022] [Accepted: 03/07/2022] [Indexed: 12/16/2022]
Abstract
BACKGROUND The brain circuitry of depression and anxiety/fear is well-established, involving regions such as the limbic system and prefrontal cortex. We expand prior literature by examining the extent to which four discrete factors of anxiety (immediate state anxiety, physiological/panic, neuroticism/worry, and agitation/restlessness) among depressed outpatients are associated with differential responses during reactivity to and regulation of emotional conflict. METHODS A total of 172 subjects diagnosed with major depressive disorder underwent functional magnetic resonance imaging while performing an Emotional Stroop Task. Two main contrasts were examined using whole brain voxel wise analyses: emotional reactivity and emotion regulation. We also evaluated the association of these contrasts with the four aforementioned anxiety factors. RESULTS During emotional reactivity, participants with higher immediate state anxiety showed potentiated activation in the rolandic operculum and insula, while individuals with higher levels of physiological/panic demonstrated decreased activation in the posterior cingulate. No significant results emerged for any of the four factors on emotion regulation. When re-analyzing these statistically-significant brain regions through analyses of a subsample with (n = 92) and without (n = 80) a current anxiety disorder, no significant associations occurred among those without an anxiety disorder. Among those with an anxiety disorder, results were similar to the full sample, except the posterior cingulate was associated with the neuroticism/worry factor. CONCLUSIONS Divergent patterns of task-related brain activation across four discrete anxiety factors could be used to inform treatment decisions and target specific aspects of anxiety that involve intrinsic processing to attenuate overactive responses to emotional stimuli.
Collapse
Affiliation(s)
- Joseph M. Trombello
- Department of Psychiatry, Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, TX, USA,Janssen Research & Development, LLC, Titusville, NJ, USA
| | - Crystal M. Cooper
- Department of Psychiatry, Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, TX, USA,Neuroscience Research, Cook Children’s Medical Center, Fort Worth, TX, USA
| | - Cherise Chin Fatt
- Department of Psychiatry, Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Bruce D. Grannemann
- Department of Psychiatry, Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Thomas J. Carmody
- Department of Psychiatry, Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, TX, USA,Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Manish K. Jha
- Department of Psychiatry, Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Taryn L. Mayes
- Department of Psychiatry, Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Tracy L. Greer
- Department of Psychiatry, Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, TX, USA,Department of Psychology, The University of Texas at Arlington, Arlington, TX, USA
| | | | - Sina Aslan
- Department of Psychiatry, Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, TX, USA,Advance MRI LLC, Frisco, TX, USA
| | - Diego A. Pizzagalli
- Harvard Medical School, McLean Hospital, Department of Psychiatry, Boston, MA, USA
| | - Myrna M. Weissman
- Columbia University, Department of Psychiatry, New York, NY, USA,New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY, USA
| | - Christian A. Webb
- Harvard Medical School, McLean Hospital, Department of Psychiatry, Boston, MA, USA
| | - Daniel G. Dillon
- Harvard Medical School, McLean Hospital, Department of Psychiatry, Boston, MA, USA
| | - Patrick J. McGrath
- Columbia University, Department of Psychiatry, New York, NY, USA,New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY, USA
| | - Maurizio Fava
- Massachusetts General Hospital, Department of Psychiatry, Boston, MA, USA
| | - Ramin V. Parsey
- Stony Brook University, Department of Psychiatry, Stony Brook, NY, USA
| | - Melvin G. McInnis
- University of Michigan, Department of Psychiatry, Ann Arbor, MI, USA
| | - Amit Etkin
- Stanford University School of Medicine, Department of Psychiatry, Palo Alto, CA, USA
| | - Madhukar H. Trivedi
- Department of Psychiatry, Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, TX, USA,Corresponding author. Center for Depression Research and Clinical Care, Peter O’Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, USA. (M.H. Trivedi)
| |
Collapse
|
7
|
Nguyen KP, Chin Fatt C, Treacher A, Mellema C, Cooper C, Jha MK, Kurian B, Fava M, McGrath PJ, Weissman M, Phillips ML, Trivedi MH, Montillo AA. Patterns of Pretreatment Reward Task Brain Activation Predict Individual Antidepressant Response: Key Results From the EMBARC Randomized Clinical Trial. Biol Psychiatry 2022; 91:550-560. [PMID: 34916068 PMCID: PMC8857018 DOI: 10.1016/j.biopsych.2021.09.011] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [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: 12/02/2020] [Revised: 08/31/2021] [Accepted: 09/14/2021] [Indexed: 12/28/2022]
Abstract
BACKGROUND The lack of biomarkers to inform antidepressant selection is a key challenge in personalized depression treatment. This work identifies candidate biomarkers by building deep learning predictors of individual treatment outcomes using reward processing measures from functional magnetic resonance imaging, clinical assessments, and demographics. METHODS Participants in the EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care) study (n = 222) underwent reward processing task-based functional magnetic resonance imaging at baseline and were randomized to 8 weeks of sertraline (n = 106) or placebo (n = 116). Subsequently, sertraline nonresponders (n = 37) switched to 8 weeks of bupropion. The change in Hamilton Depression Rating Scale was measured after treatment. Reward processing, clinical measurements, and demographics were used to train treatment-specific deep learning models. RESULTS The predictive model for sertraline achieved R2 of 48% (95% CI, 33%-61%; p < 10-3) in predicting the change in Hamilton Depression Rating Scale and number-needed-to-treat (NNT) of 4.86 participants in predicting response. The placebo model achieved R2 of 28% (95% CI, 15%-42%; p < 10-3) and NNT of 2.95 in predicting response. The bupropion model achieved R2 of 34% (95% CI, 10%-59%, p < 10-3) and NNT of 1.68 in predicting response. Brain regions where reward processing activity was predictive included the prefrontal cortex and cerebellar crus 1 for sertraline and the cingulate cortex, caudate, orbitofrontal cortex, and crus 1 for bupropion. CONCLUSIONS These findings demonstrate the utility of reward processing measurements and deep learning to predict antidepressant outcomes and to form multimodal treatment biomarkers.
Collapse
Affiliation(s)
- Kevin P Nguyen
- Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Cherise Chin Fatt
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Alex Treacher
- Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Cooper Mellema
- Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Crystal Cooper
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas; Jane and John Justin Neuroscience Center, Cook Children's Health Care System, Fort Worth, Texas
| | - Manish K Jha
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Benji Kurian
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Maurizio Fava
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
| | - Patrick J McGrath
- New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, New York
| | - Myrna Weissman
- New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, New York
| | - Mary L Phillips
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Madhukar H Trivedi
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas.
| | - Albert A Montillo
- Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, Texas; Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas; Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas.
| |
Collapse
|
8
|
Jha MK, Kim JW, Kenny PJ, Chin Fatt C, Minhajuddin A, Salas R, Ely BA, Klein M, Abdallah CG, Xu J, Trivedi MH. Smoking status links habenular volume to glycated hemoglobin: Findings from the Human Connectome Project-Young Adult. Psychoneuroendocrinology 2021; 131:105321. [PMID: 34157587 DOI: 10.1016/j.psyneuen.2021.105321] [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] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Revised: 06/07/2021] [Accepted: 06/08/2021] [Indexed: 11/24/2022]
Abstract
BACKGROUND The habenula-pancreas axis regulates the stimulatory effects of nicotine on blood glucose levels and may participate in the emergence of type 2 diabetes in human tobacco smokers. This secondary analysis of young adults from the Human Connectome Project (HCP-YA) evaluated whether smoking status links the relationship between habenular volume and glycated hemoglobin (HbA1c), a marker of long-term glycemic control. METHODS Habenula segmentation was performed using a fully-automated myelin content-based approach in HCP-YA participants and the results were inspected visually (n = 693; aged 22-37 years). A linear regression analysis was used with habenular volume as the dependent variable, the smoking-by-HbA1c interaction as the independent variable of interest, and age, gender, race, ethnicity, education, income, employment status, body mass index, and total gray matter volume as covariates. RESULTS Habenula volume and HbA1c were similar in smokers and nonsmokers. There was a significant interaction effect (F(1, 673)= 5.03, p = 0.025) indicating that habenular volume was related to HbA1c in a manner that depended on smoking status. Among participants who were smokers (n = 120), higher HbA1c was associated with apparently larger habenular volume (β = 6.74, standard error=2.36, p = 0.005). No such association between habenular volume and HbA1c was noted among participants who were nonsmokers (n = 573). DISCUSSION Blood glucose levels over an extended time period, reflected by HbA1c, were correlated with habenular volume in smokers, consistent with a relationship between the habenula and blood glucose homeostasis in smokers. Future studies are needed to evaluate how habenular function relates to glycemic control in smokers and nonsmokers.
Collapse
Affiliation(s)
- Manish K Jha
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, TX, United States
| | - Joo-Won Kim
- Department of Radiology, Baylor College of Medicine, Houston, TX, United States; Department of Psychiatry, Baylor College of Medicine, Houston, TX, United States
| | - Paul J Kenny
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Cherise Chin Fatt
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, TX, United States
| | - Abu Minhajuddin
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, TX, United States
| | - Ramiro Salas
- Department of Psychiatry, Baylor College of Medicine, Houston, TX, United States; Michael E DeBakey VA Medical Center, Houston, TX, United States; The Menninger Clinic, Houston, TX, United States
| | - Benjamin A Ely
- Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, The Bronx, NY, United States
| | - Matthew Klein
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Chadi G Abdallah
- Department of Psychiatry, Baylor College of Medicine, Houston, TX, United States; Michael E DeBakey VA Medical Center, Houston, TX, United States
| | - Junqian Xu
- Department of Radiology, Baylor College of Medicine, Houston, TX, United States; Department of Psychiatry, Baylor College of Medicine, Houston, TX, United States
| | - Madhukar H Trivedi
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, TX, United States.
| |
Collapse
|
9
|
Jha MK, Minhajuddin A, Chin Fatt C, Shoptaw S, Kircanski K, Stringaris A, Leibenluft E, Trivedi M. Irritability as an independent predictor of concurrent and future suicidal ideation in adults with stimulant use disorder: Findings from the STRIDE study. J Affect Disord 2021; 292:108-113. [PMID: 34111690 DOI: 10.1016/j.jad.2021.04.019] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [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: 12/18/2020] [Revised: 04/09/2021] [Accepted: 04/15/2021] [Indexed: 10/21/2022]
Abstract
BACKGROUND This report evaluated whether irritability in adults with stimulant use disorder is associated with suicidal ideation (SI) at the same visit (i.e., concurrently) and whether early changes in irritability predict subsequent levels of SI. METHODS Adults with stimulant use disorder (n=302) from nine residential addiction treatment programs were included. Participants were randomized to augmentation of usual care with dosed exercise or health education intervention. Irritability, SI, and depression were measured every week with 5-item irritability domain of Concise Associated Symptom Tracking scale, 3-item suicidal thoughts factor of Concise Health Risk Tracking scale, and 16-item Quick Inventory of Depressive Symptomatology Clinician-Rated version (excluding the suicide-related item) respectively during acute-(baseline-to-week-12) and continuation-(week-12-to-week-36) phase. Covariates included age, sex, race, ethnicity, treatment arm, type of substance(s) used, and comorbid psychiatric and medical disorders. RESULTS Higher irritability was associated with higher SI concurrently both in the acute-phase: r=0.28 (p<0.0001) and in the continuation-phase: r=0.33 (p<0.0001). Irritability was associated with concurrent SI after controlling for depression [acute-phase: β=0.17 (p<0.0001); continuation-phase: β=0.18 (p<0.0001)]. Greater baseline-to-week-2 reductions in irritability predicted lower levels of SI from week-2-to-week-12 (β=-0.11, p=0.003) and from week-12-to-week-36 (β=-0.22, p<0.0001) after controlling for baseline levels of depression and SI and baseline-to-week-2 changes in depression and SI. LIMITATIONS Secondary analyses, self-report measures of irritability and SI, limited generalizability. CONCLUSIONS Irritability is associated with SI concurrently, and greater reductions in irritability earlier in treatment are associated with lower levels of subsequent SI. Therefore, targeting irritability may reduce suicidality in adults with stimulant use disorder.
Collapse
Affiliation(s)
- Manish K Jha
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place, Box 1230, New York 10029, NY, United States; Center for Depression Research and Clinical Care, UT Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX, United States
| | - Abu Minhajuddin
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX, United States; Department of Population and Data Science, UT Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX, United States
| | - Cherise Chin Fatt
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX, United States
| | - Steve Shoptaw
- Departments of Family Medicine and Psychiatry and Biobehavioral Sciences, University of California Los Angeles, 10880 Wilshire Blvd, Los Angeles 90024, CA, United States
| | - Katharina Kircanski
- Intramural Research Program, National Institute of Mental Health, Building 15K, Room 210, MSC 2670, Bethesda 20892-2670, MD, United States
| | - Argyris Stringaris
- Intramural Research Program, National Institute of Mental Health, Building 15K, Room 210, MSC 2670, Bethesda 20892-2670, MD, United States
| | - Ellen Leibenluft
- Intramural Research Program, National Institute of Mental Health, Building 15K, Room 210, MSC 2670, Bethesda 20892-2670, MD, United States
| | - Madhukar Trivedi
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX, United States.
| |
Collapse
|
10
|
Jha MK, Fava M, Minhajuddin A, Chin Fatt C, Mischoulon D, Wakhlu N, Trombello JM, Cusin C, Trivedi MH. Anger attacks are associated with persistently elevated irritability in MDD: findings from the EMBARC study. Psychol Med 2021; 51:1355-1363. [PMID: 32138798 DOI: 10.1017/s0033291720000112] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [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] [Indexed: 12/20/2022]
Abstract
BACKGROUND This report tests the association of self-reported symptoms of irritability with overt behavior of anger attacks (uncharacteristic sudden bouts of anger that are disproportionate to situation and associated with autonomic activation). METHODS Participants of the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care study who completed Massachusetts General Hospital Anger Attacks questionnaire were included (n = 293). At each visit, the 17-item Hamilton Depression Rating Scale and the 16-item Concise Associated Symptom Tracking scale were used to measure depression, anxiety, and irritability. In those with anger attacks present v. those without anger attacks, separate t tests and mixed model analyses compared afore-mentioned symptoms at baseline and changes with treatment respectively. As anger attacks may occur without aggressive behaviors, analyses were repeated based only on the presence of aggressive behaviors. RESULTS At baseline, those with anger attacks (n = 109) v. those without anger attacks (n = 184) had similar levels of depression but higher levels of irritability [effect size (d) = 0.80] and anxiety (d = 0.32). With acute-phase treatment, participants with anger attacks experienced a greater reduction in irritability (p < 0.001) but not in depression (p = 0.813) or anxiety (p = 0.771) as compared to those without anger attacks. Yet, irritability levels at week-8 were higher in those with anger attacks (d = 0.32) than those without anger attacks. Similar results were found in participants with aggressive behaviors. CONCLUSIONS The presence of anger attacks in outpatients with major depressive disorder may identify a sub-group of patients with persistently elevated irritability.
Collapse
Affiliation(s)
- Manish K Jha
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Depression Research and Clinical Care, Peter O'Donnell Jr. Brain Institute, UT Southwestern Medical Center, Dallas, TX, USA
| | - Maurizio Fava
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Abu Minhajuddin
- Center for Depression Research and Clinical Care, Peter O'Donnell Jr. Brain Institute, UT Southwestern Medical Center, Dallas, TX, USA
| | - Cherise Chin Fatt
- Center for Depression Research and Clinical Care, Peter O'Donnell Jr. Brain Institute, UT Southwestern Medical Center, Dallas, TX, USA
| | - David Mischoulon
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Nausheen Wakhlu
- Center for Depression Research and Clinical Care, Peter O'Donnell Jr. Brain Institute, UT Southwestern Medical Center, Dallas, TX, USA
| | - Joseph M Trombello
- Center for Depression Research and Clinical Care, Peter O'Donnell Jr. Brain Institute, UT Southwestern Medical Center, Dallas, TX, USA
| | - Cristina Cusin
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Madhukar H Trivedi
- Center for Depression Research and Clinical Care, Peter O'Donnell Jr. Brain Institute, UT Southwestern Medical Center, Dallas, TX, USA
| |
Collapse
|
11
|
Jha MK, Schatzberg A, Minhajuddin A, Fatt CC, Mayes TL, Trivedi MH. Cross-Sectional Associations Among Symptoms of Pain, Irritability, and Depression and How These Symptoms Relate to Social Functioning and Quality of Life: Findings From the EMBARC and STRIDE Studies and the VitalSign6 Project. J Clin Psychiatry 2021; 82:20m13740. [PMID: 34000130 PMCID: PMC9578176 DOI: 10.4088/jcp.20m13740] [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] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
OBJECTIVE The aim of this report was to evaluate the psychometric properties of the Pain Frequency, Intensity, and Burden Scale (P-FIBS), a brief measure of pain, as well as the association of pain with irritability and depression and how these symptoms relate to functional impairments. METHODS Participants of 2 randomized controlled trials (Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care [EMBARC; n = 251 with DSM-IV diagnosis of major depressive disorder; study duration: August 2011-December 2015] and STimulant Reduction Intervention Using Dosed Exercise [STRIDE; n = 302 with DSM-IV diagnosis of stimulant abuse or dependence; study-duration: July 2010-February 2013]) and treatment-seeking patients in primary care clinics from an ongoing quality-improvement project (VitalSign6; n = 4,370; project duration: August 2014-July 2019) were included. Psychometric properties of the P-FIBS were evaluated with confirmatory factor and item response theory analyses in EMBARC and VitalSign6. The approach of Baron and Kenny was used to assess whether irritability accounted for the effect of pain on depression. RESULTS Cronbach α (0.84-0.89) and model fits for single-factor structure of P-FIBS were acceptable. Pain was positively correlated with irritability (r = 0.22-0.29) and depression (r = 0.10-0.33). Irritability accounted for 40.7%-65.5% of the effect of pain on depression. Higher irritability and depression were associated with poorer social functioning, quality of life, and productivity in work- and non-work-related activities. Pain was associated with non-work-related activity impairments even after controlling for irritability and depression. CONCLUSIONS The P-FIBS is a brief and reliable measure of pain. Irritability is associated with pain and accounts for a large proportion of the effect of pain on depression. Symptoms of pain, irritability, and depression are associated with functional impairments. TRIAL REGISTRATION ClinicalTrials.gov identifiers: NCT01407094 (EMBARC), NCT01141608 (STRIDE).
Collapse
Affiliation(s)
- Manish K. Jha
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York,Department of Psychiatry and Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Alan Schatzberg
- Department of Psychiatry and Behavioral Science, Stanford University, Stanford, California
| | - Abu Minhajuddin
- Department of Psychiatry and Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, Texas,Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Cherise Chin Fatt
- Department of Psychiatry and Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Taryn L. Mayes
- Department of Psychiatry and Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Madhukar H. Trivedi
- Department of Psychiatry and Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, Texas
| |
Collapse
|
12
|
Jha MK, Fava M, Minhajuddin A, Chin Fatt C, Mischoulon D, Cusin C, Trivedi MH. Association of anger attacks with suicidal ideation in adults with major depressive disorder: Findings from the EMBARC study. Depress Anxiety 2021; 38:57-66. [PMID: 33038902 DOI: 10.1002/da.23095] [Citation(s) in RCA: 3] [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] [Received: 04/30/2020] [Revised: 08/06/2020] [Accepted: 09/09/2020] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND This report evaluates whether anger attacks (sudden uncharacteristic bouts of anger that are associated with autonomic arousal and/or aggression) in patients with major depressive disorder (MDD) are associated with elevated suicidal ideation (SI; active suicidal thoughts and plans). METHODS Participants of Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study who completed Massachusetts General Hospital Anger Attack Questionnaire (AAQ) at baseline were included (n = 293). Levels of SI (suicidal thoughts factor of Concise Health Risk Tracking) were compared at baseline with generalized linear models, and during Stage 1 (baseline-to-week-8) and Stage 2 (week-8-to-week-16) with repeated-measures mixed model analyses. Covariates included age, sex, race, ethnicity, site, and treatment arm. RESULTS At baseline, participants with (n = 109) versus without anger attacks (n = 184) had higher levels of SI (Cohen's d effect size [d] = 1.20). Those with ≥9 anger attacks in the past month had significantly higher SI than those with 1-2 (d = 1.21), 3-4 (d = 1.48), and 5-8 (d = 0.94) anger attacks in the past month. Furthermore, participants with anger attacks at baseline reported higher SI at each post-baseline visit (both Stages 1 and 2) of EMBARC study (d = 0.39-0.77; all p < .05). Associations between anger attacks and SI were significant even after controlling for irritability, hostility, anxious arousal, depression, suicide propensity, and self-reported pain at baseline and lifetime suicidal tendencies. Similar results were found in participants with aggressive behaviors. CONCLUSION Anger attacks in outpatients with MDD may be associated with chronically elevated SI. Clinical Trials Registration: Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC); NCT01407094; https://clinicaltrials.gov/ct2/show/NCT01407094.
Collapse
Affiliation(s)
- Manish Kumar Jha
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Psychiatry, Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Maurizio Fava
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Abu Minhajuddin
- Department of Psychiatry, Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Cherise Chin Fatt
- Department of Psychiatry, Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, Texas, USA
| | - David Mischoulon
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Christina Cusin
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Madhukar H Trivedi
- Department of Psychiatry, Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, Texas, USA
| |
Collapse
|
13
|
Sharp KJ, South CC, Chin Fatt C, Trivedi MH, Rethorst CD. Pilot Studies to Evaluate Feasibility of a Physical Activity Intervention for Persons With Depression. J Sport Exerc Psychol 2020; 42:443-451. [PMID: 33212425 DOI: 10.1123/jsep.2019-0248] [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] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 05/29/2020] [Accepted: 06/10/2020] [Indexed: 06/11/2023]
Abstract
Exercise reduces depressive symptoms and improves physical health in persons with depression. However, the interventions implemented in research studies require significant resources, limiting adoption into clinical practice and suggesting the need for more efficient interventions. In two nonrandomized pilot studies, the authors evaluated the feasibility of a multicomponent intervention (group educational sessions, Fitbit, and access to exercise facility) in adult persons with depression and breast cancer survivors with depression. The participants in both pilot studies completed 12 weeks of group educational sessions to increase physical activity levels, were provided with self-monitoring devices, and were provided access to on-site exercise facilities. Depressive symptoms significantly decreased postintervention, and over 90% of the participants reported that they had benefited from the intervention. These results indicate that implementing a multicomponent intervention is feasible and may reduce depressive symptoms and improve other psychosocial outcomes.
Collapse
|
14
|
Jha MK, Minhajuddin A, Chin Fatt C, Kircanski K, Stringaris A, Leibenluft E, Trivedi MH. Association between irritability and suicidal ideation in three clinical trials of adults with major depressive disorder. Neuropsychopharmacology 2020; 45:2147-2154. [PMID: 32663842 PMCID: PMC7784964 DOI: 10.1038/s41386-020-0769-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [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: 05/13/2020] [Revised: 06/19/2020] [Accepted: 07/08/2020] [Indexed: 12/19/2022]
Abstract
Irritability in pediatric samples is associated with higher rates of subsequent suicide-related outcomes. No study, to date, has evaluated the longitudinal association between irritability and suicidal ideation (SI) in adults with major depressive disorder (MDD). This report evaluated whether irritability is associated with SI at the same visit (i.e., concurrently) and whether early changes in irritability with antidepressant treatment predict subsequent levels of SI. Participants of Combining Medications to Enhance Depression Outcomes (CO-MED, n = 665), Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC, n = 296), and Suicide Assessment Methodology Study (SAMS, n = 266) were included. Repeated-measures mixed model analyses evaluated concurrent association throughout the trial between irritability (five-item irritability domain of Concise Associated Symptom Tracking scale) and SI (three-item suicidal thoughts factor of Concise Health Risk Tracking scale) after controlling for overall depression (excluding suicidality-related item), and predicted subsequent levels of SI (repeated observations from week-2-to-week-8) based on early (baseline-to-week-2) changes in irritability after controlling for early changes in overall depression. Higher irritability was associated with higher SI concurrently; estimates (standard error) were 0.18 (0.02, p < 0.0001), 0.64 (0.02, p < 0.0001), and 0.26 (0.04, p < 0.0001) in CO-MED, EMBARC, and SAMS respectively. Greater baseline-to-week-2 reductions in irritability predicted lower levels of subsequent SI; estimates (standard errors) were -0.08 (0.03, p = 0.023), -0.50 (0.05, p < 0.0001), and -0.12 (0.05, p = 0.024) in CO-MED, EMBARC, and SAMS, respectively. Controlling for anxiety or insomnia produced similar results. In conclusion, irritability and SI were consistently linked in adults with MDD. These findings support careful assessment of irritability in suicide risk assessment.
Collapse
Affiliation(s)
- Manish K Jha
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY, 10029, USA
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX, 75390-9119, USA
| | - Abu Minhajuddin
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX, 75390-9119, USA
| | - Cherise Chin Fatt
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX, 75390-9119, USA
| | | | - Argyris Stringaris
- National Institute of Mental Health, 10 Center Dr, Bethesda, MD, 20814, USA
| | - Ellen Leibenluft
- National Institute of Mental Health, 10 Center Dr, Bethesda, MD, 20814, USA
| | - Madhukar H Trivedi
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX, 75390-9119, USA.
| |
Collapse
|
15
|
Minhajuddin A, Jha MK, Fatt CC, Trivedi MH. Psychometric Properties of the Concise Associated Symptom Tracking Scale and Validation of Clinical Utility in the EMBARC Study. Psychiatr res clin pract 2020; 2:10-18. [PMID: 36101888 PMCID: PMC9175787 DOI: 10.1176/appi.prcp.20190041] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Revised: 11/21/2019] [Accepted: 12/05/2019] [Indexed: 11/30/2022] Open
Affiliation(s)
- Abu Minhajuddin
- Center for Depression Research and Clinical CareUniversity of Texas Southwestern Medical CenterDallas
| | - Manish K. Jha
- Center for Depression Research and Clinical CareUniversity of Texas Southwestern Medical CenterDallas
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew York
| | - Cherise Chin Fatt
- Center for Depression Research and Clinical CareUniversity of Texas Southwestern Medical CenterDallas
| | - Madhukar H. Trivedi
- Center for Depression Research and Clinical CareUniversity of Texas Southwestern Medical CenterDallas
| |
Collapse
|
16
|
Nguyen KP, Fatt CC, Treacher A, Mellema C, Trivedi MH, Montillo A. Anatomically-Informed Data Augmentation for Functional MRI with Applications to Deep Learning. Proc SPIE Int Soc Opt Eng 2020; 11313. [PMID: 33767520 DOI: 10.1117/12.2548630] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
The application of deep learning to build accurate predictive models from functional neuroimaging data is often hindered by limited dataset sizes. Though data augmentation can help mitigate such training obstacles, most data augmentation methods have been developed for natural images as in computer vision tasks such as CIFAR, not for medical images. This work helps to fills in this gap by proposing a method for generating new functional Magnetic Resonance Images (fMRI) with realistic brain morphology. This method is tested on a challenging task of predicting antidepressant treatment response from pre-treatment task-based fMRI and demonstrates a 26% improvement in performance in predicting response using augmented images. This improvement compares favorably to state-of-the-art augmentation methods for natural images. Through an ablative test, augmentation is also shown to substantively improve performance when applied before hyperparameter optimization. These results suggest the optimal order of operations and support the role of data augmentation method for improving predictive performance in tasks using fMRI.
Collapse
Affiliation(s)
- Kevin P Nguyen
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | | | - Alex Treacher
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Cooper Mellema
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | | | - Albert Montillo
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| |
Collapse
|
17
|
Jha MK, Cai L, Minhajuddin A, Fatt CC, Furman JL, Gadad BS, Mason BL, Greer TL, Hughes JL, Xiao G, Emslie G, Kennard B, Mayes T, Trivedi MH. Dysfunctional adaptive immune response in adolescents and young adults with suicide behavior. Psychoneuroendocrinology 2020; 111:104487. [PMID: 31756521 DOI: 10.1016/j.psyneuen.2019.104487] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [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: 06/24/2019] [Revised: 10/17/2019] [Accepted: 10/18/2019] [Indexed: 01/03/2023]
Abstract
BACKGROUND Immune system dysfunction has been implicated in the pathophysiology of suicide behavior. Here, we conducted an exploratory analysis of immune profile differences of three groups of adolescents and young adults (ages 10-25 years): healthy controls (n = 39), at risk of major depressive disorder (MDD; at-risk, n = 33), and MDD with recent suicide behavior/ ideation (suicide behavior, n = 37). METHODS Plasma samples were assayed for chemokines and cytokines using Bio-Plex Pro Human Chemokine 40-plex assay. Log-transformed cytokine and chemokine levels were compared after controlling for age, gender, body mass index, race, ethnicity, and C-reactive protein (CRP) levels. In post-hoc analyses to understand the effect of dysregulated immune markers identified in this exploratory analysis, their association with autoantibodies was tested in an unrelated sample (n = 166). RESULTS Only levels of interleukin 4 (IL-4) differed significantly among the three groups [false discovery rate (FDR) adjusted p = 0.0007]. Participants with suicide behavior had lower IL-4 [median = 16.8 pg/ml, interquartile range (IQR) = 7.9] levels than healthy controls (median = 29.1 pg/ml, IQR = 16.1, effect size [ES] = 1.30) and those at-risk (median = 24.4 pg/ml, IQR = 16.3, ES = 1.03). IL-4 levels were negatively correlated with depression severity (r= -0.38, p = 0.024). In an unrelated sample of outpatients with MDD, levels of IL-4 were negatively correlated (all FDR p < 0.05) with several autoantibodies [54/117 in total and 12/18 against innate immune markers]. CONCLUSIONS Adolescent and young adult patients with recent suicide behavior exhibit lower IL-4 levels. One biological consequence of reduced IL-4 levels may be increased risk of autoimmunity.
Collapse
Affiliation(s)
- Manish K Jha
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, TX, United States; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Ling Cai
- Quantitative Biomedical Research Center, Department of Population and Data Sciences, UT Southwestern Medical Center, Dallas, TX, United States
| | - Abu Minhajuddin
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, TX, United States
| | - Cherise Chin Fatt
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, TX, United States
| | - Jennifer L Furman
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, TX, United States
| | - Bharathi S Gadad
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, TX, United States; Department of Psychiatry, Texas Tech University Health Science Center, El Paso, Texas, United States
| | - Brittany L Mason
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, TX, United States
| | - Tracy L Greer
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, TX, United States
| | - Jennifer L Hughes
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, TX, United States
| | - Guanghua Xiao
- Quantitative Biomedical Research Center, Department of Population and Data Sciences, UT Southwestern Medical Center, Dallas, TX, United States
| | - Graham Emslie
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, United States
| | - Betsy Kennard
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, United States
| | - Taryn Mayes
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, TX, United States
| | - Madhukar H Trivedi
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, TX, United States.
| |
Collapse
|
18
|
Jha MK, Minhajuddin A, Gadad BS, Chin Fatt C, Trivedi MH. Higher S100B Levels Predict Persistently Elevated Anhedonia with Escitalopram Monotherapy Versus Antidepressant Combinations: Findings from CO-MED Trial. Pharmaceuticals (Basel) 2019; 12:ph12040184. [PMID: 31861074 PMCID: PMC6958482 DOI: 10.3390/ph12040184] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Revised: 12/11/2019] [Accepted: 12/13/2019] [Indexed: 02/06/2023] Open
Abstract
Background: Elevated S100 calcium binding protein B (S100B) levels in systemic circulation may induce neuroinflammation and reflect greater blood–brain barrier (BBB) dysfunction. Neuroinflammation in patients with major depressive disorder (MDD), in turn, may reduce likelihood of improvement with serotonergic antidepressants. Methods: Levels of S100B were measured in plasma samples obtained prior to initiation of treatment with bupropion-plus-escitalopram, escitalopram-plus-placebo, or venlafaxine-plus-mirtazapine in participants of Combining Medications to Enhance Depression Outcomes trial (n = 153). Depression severity was measured with 16-item Quick Inventory of Depressive Symptomatology Self-Report and anhedonia was measured with 3 items of 30-item Inventory of Depressive Symptomatology. Differential changes in depression severity and anhedonia over acute-phase (baseline, weeks 1, 2, 4, 6, 8, 10, and 12) in the three treatment arms were tested with logS100B-by-treatment-arm interaction in mixed model analyses after controlling for age, gender, and body mass index. Results: There was a significant logS100B-by-treatment-arm interaction for anhedonia (F = 3.21; df = 2, 142; p = 0.04) but not for overall depression severity (F = 1.99; df = 2, 142; p = 0.14). Higher logS100B levels were associated with smaller reductions in anhedonia (effect size = 0.67, p = 0.047) in escitalopram monotherapy but not in the other two arms. Correlation coefficients of anhedonia severity averaged over acute-phase (including baseline) with baseline S100B levels were 0.57, −0.19, and 0.22 for escitalopram monotherapy, bupropion-plus-escitalopram and venlafaxine-plus-mirtazapine arms respectively. Conclusion: Higher baseline S100B levels in depressed patients resulted in poorer response to escitalopram monotherapy. Addition of bupropion, a dopaminergic antidepressant, partially mitigated this effect.
Collapse
Affiliation(s)
- Manish K. Jha
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA;
| | - Abu Minhajuddin
- Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, TX 75235, USA; (A.M.); (B.S.G.); (C.C.F.)
| | - Bharathi S. Gadad
- Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, TX 75235, USA; (A.M.); (B.S.G.); (C.C.F.)
- Department of Psychiatry, Texas Tech University Health Science Center, El Paso, TX 79905, USA
| | - Cherise Chin Fatt
- Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, TX 75235, USA; (A.M.); (B.S.G.); (C.C.F.)
| | - Madhukar H. Trivedi
- Center for Depression Research and Clinical Care, University of Texas Southwestern Medical Center, Dallas, TX 75235, USA; (A.M.); (B.S.G.); (C.C.F.)
- Correspondence:
| |
Collapse
|
19
|
Nguyen KP, Fatt CC, Mellema C, Trivedi MH, Montillo A. Sensitivity of derived clinical biomarkers to rs-fMRI preprocessing software versions. Proc IEEE Int Symp Biomed Imaging 2019; 2019:1581-1584. [PMID: 31741703 DOI: 10.1109/isbi.2019.8759526] [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] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
When common software packages (CONN and SPM) are used to process fMRI, results such as functional connectivity measures can substantially differ depending on the versions of the packages used and the tools used to convert image formats such as DICOM to NIFTI. The significance of these differences are illustrated within the context of a realistic research application: finding moderators of antidepressant response from a large psychiatric study of 288 major depressive disorder (MDD) patients. Significant differences in functional connectivity measurements and discrepancies in derived moderators were found between nearly all software configurations. These results should encourage researchers to be vigilant of software versions during fMRI preprocessing, to maintain consistency throughout each project, and to carefully report versions to facilitate reproducibility.
Collapse
Affiliation(s)
- Kevin P Nguyen
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Cherise Chin Fatt
- Center for Depression Research and Clinical Care, Department of Psychiatry, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Cooper Mellema
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Madhukar H Trivedi
- Center for Depression Research and Clinical Care, Department of Psychiatry, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Albert Montillo
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, Texas, USA
| |
Collapse
|
20
|
Devous M, Fatt CC, Abdi H, Harris T, Hynanc L, O'Bryant S. O4–03–04: Delineating the relationship between cognitive measures and functional connectivity in Alzheimer's disease. Alzheimers Dement 2013. [DOI: 10.1016/j.jalz.2013.04.349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Affiliation(s)
- Michael Devous
- University of Texas Southwestern Medical Center Dallas Texas United States
| | | | - Hervé Abdi
- University of Texas at Dallas Richardson Texas United States
| | - Thomas Harris
- University of Texas Southwestern Medical Center Dallas Texas United States
| | - Linda Hynanc
- Alzheimer's Disease Center, University of Texas Southwestern Medical Center Dallas Texas United States
| | - Sid O'Bryant
- University of North Texas Health Science Center Fort Worth Texas United States
| |
Collapse
|