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Mootz JJ, Chantre C, Sikkema K, Greene MC, Lovero KL, Gouveia L, Santos P, Suleman A, Comé AS, Feliciano P, Uribe-Restrepo JM, Sweetland AC, Shelton RC, Kane J, Mello M, Fumo W, Cadena-Camargo Y, Weissman M, Wainberg ML. Leveraging a Digitized Mental Wellness (DIGImw) Program to Provide Mental Health Care for Internally Displaced People. Psychiatr Serv 2024; 75:98-101. [PMID: 37461818 PMCID: PMC10794516 DOI: 10.1176/appi.ps.202100552] [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] [Indexed: 01/02/2024]
Abstract
A local insurgency has displaced many people in the northern Mozambican province of Cabo Delgado. The authors' global team (comprising members from Brazil, Mozambique, South Africa, and the United States) has been scaling up mental health services across the neighboring province of Nampula, Mozambique, now host to >200,000 displaced people. The authors describe how mental health services can be expanded by leveraging digital technology and task-shifting (i.e., having nonspecialists deliver mental health care) to address the mental health needs of displaced people. These methods can serve as a model for other researchers and clinicians aiming to address mental health needs arising from humanitarian disasters in low-resource settings.
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Affiliation(s)
- Jennifer J Mootz
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, and New York State Psychiatric Institute, New York City (Mootz, Sweetland, Mello, Weissman, Wainberg) Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven (Chantre, Sweetland); Departments of Sociomedical Sciences (Sikkema, Lovero, Shelton) and Epidemiology (Kane, Weissman), Mailman School of Public Health, Columbia University, New York City; Program on Forced Migration and Health, Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York City (Greene); Department of Mental Health, Ministry of Health, Maputo, Mozambique (Gouveia, Santos, Suleman, Comé, Feliciano, Fumo); Social and Preventive Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia (Uribe-Restrepo, Cadena-Camargo)
| | - Catherine Chantre
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, and New York State Psychiatric Institute, New York City (Mootz, Sweetland, Mello, Weissman, Wainberg) Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven (Chantre, Sweetland); Departments of Sociomedical Sciences (Sikkema, Lovero, Shelton) and Epidemiology (Kane, Weissman), Mailman School of Public Health, Columbia University, New York City; Program on Forced Migration and Health, Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York City (Greene); Department of Mental Health, Ministry of Health, Maputo, Mozambique (Gouveia, Santos, Suleman, Comé, Feliciano, Fumo); Social and Preventive Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia (Uribe-Restrepo, Cadena-Camargo)
| | - Kathleen Sikkema
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, and New York State Psychiatric Institute, New York City (Mootz, Sweetland, Mello, Weissman, Wainberg) Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven (Chantre, Sweetland); Departments of Sociomedical Sciences (Sikkema, Lovero, Shelton) and Epidemiology (Kane, Weissman), Mailman School of Public Health, Columbia University, New York City; Program on Forced Migration and Health, Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York City (Greene); Department of Mental Health, Ministry of Health, Maputo, Mozambique (Gouveia, Santos, Suleman, Comé, Feliciano, Fumo); Social and Preventive Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia (Uribe-Restrepo, Cadena-Camargo)
| | - M Claire Greene
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, and New York State Psychiatric Institute, New York City (Mootz, Sweetland, Mello, Weissman, Wainberg) Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven (Chantre, Sweetland); Departments of Sociomedical Sciences (Sikkema, Lovero, Shelton) and Epidemiology (Kane, Weissman), Mailman School of Public Health, Columbia University, New York City; Program on Forced Migration and Health, Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York City (Greene); Department of Mental Health, Ministry of Health, Maputo, Mozambique (Gouveia, Santos, Suleman, Comé, Feliciano, Fumo); Social and Preventive Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia (Uribe-Restrepo, Cadena-Camargo)
| | - Kathryn L Lovero
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, and New York State Psychiatric Institute, New York City (Mootz, Sweetland, Mello, Weissman, Wainberg) Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven (Chantre, Sweetland); Departments of Sociomedical Sciences (Sikkema, Lovero, Shelton) and Epidemiology (Kane, Weissman), Mailman School of Public Health, Columbia University, New York City; Program on Forced Migration and Health, Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York City (Greene); Department of Mental Health, Ministry of Health, Maputo, Mozambique (Gouveia, Santos, Suleman, Comé, Feliciano, Fumo); Social and Preventive Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia (Uribe-Restrepo, Cadena-Camargo)
| | - Lidia Gouveia
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, and New York State Psychiatric Institute, New York City (Mootz, Sweetland, Mello, Weissman, Wainberg) Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven (Chantre, Sweetland); Departments of Sociomedical Sciences (Sikkema, Lovero, Shelton) and Epidemiology (Kane, Weissman), Mailman School of Public Health, Columbia University, New York City; Program on Forced Migration and Health, Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York City (Greene); Department of Mental Health, Ministry of Health, Maputo, Mozambique (Gouveia, Santos, Suleman, Comé, Feliciano, Fumo); Social and Preventive Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia (Uribe-Restrepo, Cadena-Camargo)
| | - Palmira Santos
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, and New York State Psychiatric Institute, New York City (Mootz, Sweetland, Mello, Weissman, Wainberg) Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven (Chantre, Sweetland); Departments of Sociomedical Sciences (Sikkema, Lovero, Shelton) and Epidemiology (Kane, Weissman), Mailman School of Public Health, Columbia University, New York City; Program on Forced Migration and Health, Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York City (Greene); Department of Mental Health, Ministry of Health, Maputo, Mozambique (Gouveia, Santos, Suleman, Comé, Feliciano, Fumo); Social and Preventive Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia (Uribe-Restrepo, Cadena-Camargo)
| | - Antonio Suleman
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, and New York State Psychiatric Institute, New York City (Mootz, Sweetland, Mello, Weissman, Wainberg) Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven (Chantre, Sweetland); Departments of Sociomedical Sciences (Sikkema, Lovero, Shelton) and Epidemiology (Kane, Weissman), Mailman School of Public Health, Columbia University, New York City; Program on Forced Migration and Health, Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York City (Greene); Department of Mental Health, Ministry of Health, Maputo, Mozambique (Gouveia, Santos, Suleman, Comé, Feliciano, Fumo); Social and Preventive Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia (Uribe-Restrepo, Cadena-Camargo)
| | - Andrea Simone Comé
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, and New York State Psychiatric Institute, New York City (Mootz, Sweetland, Mello, Weissman, Wainberg) Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven (Chantre, Sweetland); Departments of Sociomedical Sciences (Sikkema, Lovero, Shelton) and Epidemiology (Kane, Weissman), Mailman School of Public Health, Columbia University, New York City; Program on Forced Migration and Health, Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York City (Greene); Department of Mental Health, Ministry of Health, Maputo, Mozambique (Gouveia, Santos, Suleman, Comé, Feliciano, Fumo); Social and Preventive Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia (Uribe-Restrepo, Cadena-Camargo)
| | - Paulino Feliciano
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, and New York State Psychiatric Institute, New York City (Mootz, Sweetland, Mello, Weissman, Wainberg) Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven (Chantre, Sweetland); Departments of Sociomedical Sciences (Sikkema, Lovero, Shelton) and Epidemiology (Kane, Weissman), Mailman School of Public Health, Columbia University, New York City; Program on Forced Migration and Health, Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York City (Greene); Department of Mental Health, Ministry of Health, Maputo, Mozambique (Gouveia, Santos, Suleman, Comé, Feliciano, Fumo); Social and Preventive Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia (Uribe-Restrepo, Cadena-Camargo)
| | - José Miguel Uribe-Restrepo
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, and New York State Psychiatric Institute, New York City (Mootz, Sweetland, Mello, Weissman, Wainberg) Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven (Chantre, Sweetland); Departments of Sociomedical Sciences (Sikkema, Lovero, Shelton) and Epidemiology (Kane, Weissman), Mailman School of Public Health, Columbia University, New York City; Program on Forced Migration and Health, Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York City (Greene); Department of Mental Health, Ministry of Health, Maputo, Mozambique (Gouveia, Santos, Suleman, Comé, Feliciano, Fumo); Social and Preventive Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia (Uribe-Restrepo, Cadena-Camargo)
| | - Annika C Sweetland
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, and New York State Psychiatric Institute, New York City (Mootz, Sweetland, Mello, Weissman, Wainberg) Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven (Chantre, Sweetland); Departments of Sociomedical Sciences (Sikkema, Lovero, Shelton) and Epidemiology (Kane, Weissman), Mailman School of Public Health, Columbia University, New York City; Program on Forced Migration and Health, Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York City (Greene); Department of Mental Health, Ministry of Health, Maputo, Mozambique (Gouveia, Santos, Suleman, Comé, Feliciano, Fumo); Social and Preventive Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia (Uribe-Restrepo, Cadena-Camargo)
| | - Rachel C Shelton
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, and New York State Psychiatric Institute, New York City (Mootz, Sweetland, Mello, Weissman, Wainberg) Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven (Chantre, Sweetland); Departments of Sociomedical Sciences (Sikkema, Lovero, Shelton) and Epidemiology (Kane, Weissman), Mailman School of Public Health, Columbia University, New York City; Program on Forced Migration and Health, Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York City (Greene); Department of Mental Health, Ministry of Health, Maputo, Mozambique (Gouveia, Santos, Suleman, Comé, Feliciano, Fumo); Social and Preventive Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia (Uribe-Restrepo, Cadena-Camargo)
| | - Jeremy Kane
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, and New York State Psychiatric Institute, New York City (Mootz, Sweetland, Mello, Weissman, Wainberg) Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven (Chantre, Sweetland); Departments of Sociomedical Sciences (Sikkema, Lovero, Shelton) and Epidemiology (Kane, Weissman), Mailman School of Public Health, Columbia University, New York City; Program on Forced Migration and Health, Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York City (Greene); Department of Mental Health, Ministry of Health, Maputo, Mozambique (Gouveia, Santos, Suleman, Comé, Feliciano, Fumo); Social and Preventive Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia (Uribe-Restrepo, Cadena-Camargo)
| | - Milena Mello
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, and New York State Psychiatric Institute, New York City (Mootz, Sweetland, Mello, Weissman, Wainberg) Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven (Chantre, Sweetland); Departments of Sociomedical Sciences (Sikkema, Lovero, Shelton) and Epidemiology (Kane, Weissman), Mailman School of Public Health, Columbia University, New York City; Program on Forced Migration and Health, Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York City (Greene); Department of Mental Health, Ministry of Health, Maputo, Mozambique (Gouveia, Santos, Suleman, Comé, Feliciano, Fumo); Social and Preventive Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia (Uribe-Restrepo, Cadena-Camargo)
| | - Wilza Fumo
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, and New York State Psychiatric Institute, New York City (Mootz, Sweetland, Mello, Weissman, Wainberg) Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven (Chantre, Sweetland); Departments of Sociomedical Sciences (Sikkema, Lovero, Shelton) and Epidemiology (Kane, Weissman), Mailman School of Public Health, Columbia University, New York City; Program on Forced Migration and Health, Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York City (Greene); Department of Mental Health, Ministry of Health, Maputo, Mozambique (Gouveia, Santos, Suleman, Comé, Feliciano, Fumo); Social and Preventive Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia (Uribe-Restrepo, Cadena-Camargo)
| | - Yazmin Cadena-Camargo
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, and New York State Psychiatric Institute, New York City (Mootz, Sweetland, Mello, Weissman, Wainberg) Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven (Chantre, Sweetland); Departments of Sociomedical Sciences (Sikkema, Lovero, Shelton) and Epidemiology (Kane, Weissman), Mailman School of Public Health, Columbia University, New York City; Program on Forced Migration and Health, Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York City (Greene); Department of Mental Health, Ministry of Health, Maputo, Mozambique (Gouveia, Santos, Suleman, Comé, Feliciano, Fumo); Social and Preventive Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia (Uribe-Restrepo, Cadena-Camargo)
| | - Myrna Weissman
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, and New York State Psychiatric Institute, New York City (Mootz, Sweetland, Mello, Weissman, Wainberg) Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven (Chantre, Sweetland); Departments of Sociomedical Sciences (Sikkema, Lovero, Shelton) and Epidemiology (Kane, Weissman), Mailman School of Public Health, Columbia University, New York City; Program on Forced Migration and Health, Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York City (Greene); Department of Mental Health, Ministry of Health, Maputo, Mozambique (Gouveia, Santos, Suleman, Comé, Feliciano, Fumo); Social and Preventive Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia (Uribe-Restrepo, Cadena-Camargo)
| | - Milton L Wainberg
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, and New York State Psychiatric Institute, New York City (Mootz, Sweetland, Mello, Weissman, Wainberg) Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven (Chantre, Sweetland); Departments of Sociomedical Sciences (Sikkema, Lovero, Shelton) and Epidemiology (Kane, Weissman), Mailman School of Public Health, Columbia University, New York City; Program on Forced Migration and Health, Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York City (Greene); Department of Mental Health, Ministry of Health, Maputo, Mozambique (Gouveia, Santos, Suleman, Comé, Feliciano, Fumo); Social and Preventive Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia (Uribe-Restrepo, Cadena-Camargo)
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Allen-Brady K, Fyer AJ, Weissman M. The multi-generational familial aggregation of interstitial cystitis, other chronic nociplastic pain disorders, depression, and panic disorder. Psychol Med 2023; 53:7847-7856. [PMID: 37458197 DOI: 10.1017/s0033291723001885] [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] [Indexed: 07/24/2023]
Abstract
BACKGROUND Interstitial cystitis/painful bladder syndrome (IC) is a chronic pelvic pain condition which has high comorbidity with other nociplastic, or unexplained, pain disorders [e.g. fibromyalgia (FM), irritable bowel syndrome (IBS), and myalgic encephalomyelitis/chronic fatigue (ME/CFS)] and some psychiatric conditions [major depressive disorder (MDD) and panic disorder (PD)]. Here we investigated the shared familiality of IC and these other nociplastic and psychiatric conditions. METHODS Subjects were identified in the Utah Population Database, which links genealogy data back to the 1800s to medical record diagnosis billing code data back to 1995. We computed the relative risk of each of these disorders among first (FDR), second (SDR), and third-degree relatives (TDR) of six proband groups: IC, FM, IBS, ME/CFS, PD, and MDD. Given the known familial aggregation of each of these disorders, we conducted our analyses to test for heritable interrelationships using proband subgroups whose members did not have the diagnosis assessed in their relatives. RESULTS We observed strong evidence for heritable interrelationships among all six disorders. Most analyses indicated significantly increased risk for each of the six disorders in FDR, SDR, and TDR of all or most proband groups. Out of 30 possible bidirectional disorder interrelationships, 26 were significant among FDR, 23 were significant among SDR, and 7 were significant among TDR. Clustering was observed in both close and distant relatives. CONCLUSIONS Our results support a common, heritable component to IC and other nociplastic and psychiatric conditions.
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Affiliation(s)
- Kristina Allen-Brady
- Division of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Abby J Fyer
- Department of Psychiatry, Columbia University Vagelos College of Physicians & Surgeons, New York State Psychiatric Institute, New York City, New York, USA
| | - Myrna Weissman
- Department of Psychiatry, Columbia University Vagelos College of Physicians & Surgeons, New York State Psychiatric Institute, New York City, New York, USA
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Lugo-Candelas C, Chang L, Dworkin JD, Aw N, Fields A, Reed H, Spann M, Gilchrist MA, Hinds W, Marsh R, Fifer WP, Weissman M, Foerster BU, Manin MG, Silva I, Peterson B, Coelho Milani AC, Gingrich J, Monk C, Duarte CS, Jackowski A, Posner J. Maternal childhood maltreatment: associations to offspring brain volume and white matter connectivity. J Dev Orig Health Dis 2023; 14:591-601. [PMID: 37732425 PMCID: PMC10840844 DOI: 10.1017/s2040174423000247] [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] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
The deleterious effects of adversity are likely intergenerational, such that one generation's adverse experiences can affect the next. Epidemiological studies link maternal adversity to offspring depression and anxiety, possibly via transmission mechanisms that influence offspring fronto-limbic connectivity. However, studies have not thoroughly disassociated postnatal exposure effects nor considered the role of offspring sex. We utilized infant neuroimaging to test the hypothesis that maternal childhood maltreatment (CM) would be associated with increased fronto-limbic connectivity in infancy and tested brain-behavior associations in childhood. Ninety-two dyads participated (32 mothers with CM, 60 without; 52 infant females, 40 infant males). Women reported on their experiences of CM and non-sedated sleeping infants underwent MRIs at 2.44 ± 2.74 weeks. Brain volumes were estimated via structural MRI and white matter structural connectivity (fiber counts) via diffusion MRI with probabilistic tractography. A subset of parents (n = 36) reported on children's behaviors at age 5.17 ± 1.73 years. Males in the maltreatment group demonstrated greater intra-hemispheric fronto-limbic connectivity (b = 0.96, p= 0.008, [95%CI 0.25, 1.66]), no differences emerged for females. Fronto-limbic connectivity was related to somatic complaints in childhood only for males (r = 0.673, p = 0.006). Our findings suggest that CM could have intergenerational associations to offspring brain development, yet mechanistic studies are needed.
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Affiliation(s)
- Claudia Lugo-Candelas
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, USA
| | - Le Chang
- Department of Statistics, University of South Carolina, Columbia, USA
| | | | - Natalie Aw
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, USA
| | - Andrea Fields
- Department of Psychology, Columbia University, New York, USA
| | - Hannah Reed
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, USA
| | - Marisa Spann
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, USA
| | | | - Walter Hinds
- Department of Neurology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Rachel Marsh
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, USA
| | - William P. Fifer
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, USA
| | - Myrna Weissman
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, USA
| | - Bernd Uwe Foerster
- Department of Psychiatry, Universidade Federal de São Paulo, Sao Paulo, Brazil
| | - Marina Giorgi Manin
- Department of Pediatrics, Universidade Federal de São Paulo, Sao Paulo, Brazil
| | - Ivaldo Silva
- Department of Gynecology, Universidade Federal de São Paulo, Sao Paulo, Brazil
| | - Bradley Peterson
- Department of Psychiatry, University of Southern California, Los Angeles, CA, USA
| | | | - Jay Gingrich
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, USA
| | - Catherine Monk
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, USA
| | - Cristiane S. Duarte
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, USA
| | - Andrea Jackowski
- Department of Psychiatry, Universidade Federal de São Paulo, Sao Paulo, Brazil
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Giles MA, Cooper CM, Jha MK, Chin Fatt CR, Pizzagalli DA, Mayes TL, Webb CA, Greer TL, Etkin A, Trombello JM, Chase HW, Phillips ML, McInnis MG, Carmody T, Adams P, Parsey RV, McGrath PJ, Weissman M, Kurian BT, Fava M, Trivedi MH. Reward Behavior Disengagement, a Neuroeconomic Model-Based Objective Measure of Reward Pathology in Depression: Findings from the EMBARC Trial. Behav Sci (Basel) 2023; 13:619. [PMID: 37622759 PMCID: PMC10451479 DOI: 10.3390/bs13080619] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 06/28/2023] [Accepted: 07/21/2023] [Indexed: 08/26/2023] Open
Abstract
The probabilistic reward task (PRT) has identified reward learning impairments in those with major depressive disorder (MDD), as well as anhedonia-specific reward learning impairments. However, attempts to validate the anhedonia-specific impairments have produced inconsistent findings. Thus, we seek to determine whether the Reward Behavior Disengagement (RBD), our proposed economic augmentation of PRT, differs between MDD participants and controls, and whether there is a level at which RBD is high enough for depressed participants to be considered objectively disengaged. Data were gathered as part of the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study, a double-blind, placebo-controlled clinical trial of antidepressant response. Participants included 195 individuals with moderate to severe MDD (Quick Inventory of Depressive Symptomatology (QIDS-SR) score ≥ 15), not in treatment for depression, and with complete PRT data. Healthy controls (n = 40) had no history of psychiatric illness, a QIDS-SR score < 8, and complete PRT data. Participants with MDD were treated with sertraline or placebo for 8 weeks (stage I of the EMBARC trial). RBD was applied to PRT data using discriminant analysis, and classified MDD participants as reward task engaged (n = 137) or reward task disengaged (n = 58), relative to controls. Reward task engaged/disengaged groups were compared on sociodemographic features, reward-behavior, and sertraline/placebo response (Hamilton Depression Rating Scale scores). Reward task disengaged MDD participants responded only to sertraline, whereas those who were reward task engaged responded to sertraline and placebo (F(1293) = 4.33, p = 0.038). Reward task engaged/disengaged groups did not differ otherwise. RBD was predictive of reward impairment in depressed patients and may have clinical utility in identifying patients who will benefit from antidepressants.
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Affiliation(s)
- Michael A. Giles
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Crystal M. Cooper
- Center for Depression Research and Clinical Care, Peter O’Donnell Jr. Brain Institute and Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA (T.L.G.)
- Jane and John Justin Neurosciences Center, Cook Children’s Health Care System, Fort Worth, TX 76104, USA
| | - Manish K. Jha
- Center for Depression Research and Clinical Care, Peter O’Donnell Jr. Brain Institute and Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA (T.L.G.)
| | - Cherise R. Chin Fatt
- Center for Depression Research and Clinical Care, Peter O’Donnell Jr. Brain Institute and Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA (T.L.G.)
| | - Diego A. Pizzagalli
- Department of Psychiatry, Harvard Medical School, Boston, MA 02215, USA
- McLean Hospital, Belmont, MA 02478, USA
| | - Taryn L. Mayes
- Center for Depression Research and Clinical Care, Peter O’Donnell Jr. Brain Institute and Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA (T.L.G.)
| | - Christian A. Webb
- Department of Psychiatry, Harvard Medical School, Boston, MA 02215, USA
- McLean Hospital, Belmont, MA 02478, USA
| | - Tracy L. Greer
- Center for Depression Research and Clinical Care, Peter O’Donnell Jr. Brain Institute and Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA (T.L.G.)
- Department of Psychology, University of Texas at Arlington, Arlington, TX 76019, USA
| | - Amit Etkin
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Joseph M. Trombello
- Center for Depression Research and Clinical Care, Peter O’Donnell Jr. Brain Institute and Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA (T.L.G.)
| | - Henry W. Chase
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Mary L. Phillips
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Melvin G. McInnis
- Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor, MI 48109, USA
| | - Thomas Carmody
- Peter O’Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Phillip Adams
- Department of Psychiatry, Columbia University, New York, NY 10032, USA
| | - Ramin V. Parsey
- Department of Psychiatry and Behavioral Health, Stony Brook University Renaissance School of Medicine, Stony Brook, NY 11794, USA
| | | | - Myrna Weissman
- Department of Psychiatry, Columbia University, New York, NY 10032, USA
| | - Benji T. Kurian
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Maurizio Fava
- Department of Psychiatry, Harvard Medical School, Boston, MA 02215, USA
- Massachusetts General Hospital, Boston, MA 02114, USA
| | - Madhukar H. Trivedi
- Center for Depression Research and Clinical Care, Peter O’Donnell Jr. Brain Institute and Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA (T.L.G.)
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5
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Adekkanattu P, Olfson M, Susser LC, Patra B, Vekaria V, Coombes BJ, Lepow L, Fennessy B, Charney A, Ryu E, Miller KD, Pan L, Yangchen T, Talati A, Wickramaratne P, Weissman M, Mann J, Biernacka JM, Pathak J. Comorbidity and healthcare utilization in patients with treatment resistant depression: A large-scale retrospective cohort analysis using electronic health records. J Affect Disord 2023; 324:102-113. [PMID: 36529406 PMCID: PMC10327872 DOI: 10.1016/j.jad.2022.12.044] [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: 07/20/2022] [Revised: 09/09/2022] [Accepted: 12/11/2022] [Indexed: 12/23/2022]
Abstract
BACKGROUND Medical comorbidity and healthcare utilization in patients with treatment resistant depression (TRD) is usually reported in convenience samples, making estimates unreliable. There is only limited large-scale clinical research on comorbidities and healthcare utilization in TRD patients. METHODS Electronic Health Record data from over 3.3 million patients from the INSIGHT Clinical Research Network in New York City was used to define TRD as initiation of a third antidepressant regimen in a 12-month period among patients diagnosed with major depressive disorder (MDD). Age and sex matched TRD and non-TRD MDD patients were compared for anxiety disorder, 27 comorbid medical conditions, and healthcare utilization. RESULTS Out of 30,218 individuals diagnosed with MDD, 15.2 % of patients met the criteria for TRD (n = 4605). Compared to MDD patients without TRD, the TRD patients had higher rates of anxiety disorder and physical comorbidities. They also had higher odds of ischemic heart disease (OR = 1.38), stroke/transient ischemic attack (OR = 1.57), chronic kidney diseases (OR = 1.53), arthritis (OR = 1.52), hip/pelvic fractures (OR = 2.14), and cancers (OR = 1.41). As compared to non-TRD MDD, TRD patients had higher rates of emergency room visits, and inpatient stays. In relation to patients without MDD, both TRD and non-TRD MDD patients had significantly higher levels of anxiety disorder and physical comorbidities. LIMITATIONS The INSIGHT-CRN data lack information on depression severity and medication adherence. CONCLUSIONS TRD patients compared to non-TRD MDD patients have a substantially higher prevalence of various psychiatric and medical comorbidities and higher health care utilization. These findings highlight the challenges of developing interventions and care coordination strategies to meet the complex clinical needs of TRD patients.
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Affiliation(s)
| | - Mark Olfson
- Columbia University and New York State Psychiatric Institute, New York, NY, USA
| | | | | | | | | | - Lauren Lepow
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Brian Fennessy
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | | | | | - Lifang Pan
- Columbia University and New York State Psychiatric Institute, New York, NY, USA
| | - Tenzin Yangchen
- Columbia University and New York State Psychiatric Institute, New York, NY, USA
| | - Ardesheer Talati
- Columbia University and New York State Psychiatric Institute, New York, NY, USA
| | - Priya Wickramaratne
- Columbia University and New York State Psychiatric Institute, New York, NY, USA
| | - Myrna Weissman
- Columbia University and New York State Psychiatric Institute, New York, NY, USA
| | - John Mann
- Columbia University and New York State Psychiatric Institute, New York, NY, USA
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6
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Kaiser RH, Chase HW, Phillips ML, Deckersbach T, Parsey RV, Fava M, McGrath PJ, Weissman M, Oquendo MA, McInnis MG, Carmody T, Cooper CM, Trivedi MH, Pizzagalli DA. Dynamic Resting-State Network Biomarkers of Antidepressant Treatment Response. Biol Psychiatry 2022; 92:533-542. [PMID: 35680431 PMCID: PMC10640874 DOI: 10.1016/j.biopsych.2022.03.020] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [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: 11/15/2021] [Revised: 03/02/2022] [Accepted: 03/23/2022] [Indexed: 12/26/2022]
Abstract
BACKGROUND Delivery of effective antidepressant treatment has been hampered by a lack of objective tools for predicting or monitoring treatment response. This study aimed to address this gap by testing novel dynamic resting-state functional network markers of antidepressant response. METHODS The Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study randomized adults with major depressive disorder to 8 weeks of either sertraline or placebo, and depression severity was evaluated longitudinally. Participants completed resting-state neuroimaging pretreatment and again after 1 week of treatment (n = 259 eligible for analyses). Coactivation pattern analyses identified recurrent whole-brain states of spatial coactivation, and computed time spent in each state for each participant was the main dynamic measure. Multilevel modeling estimated the associations between pretreatment network dynamics and sertraline response and between early (pretreatment to 1 week) changes in network dynamics and sertraline response. RESULTS Dynamic network markers of early sertraline response included increased time in network states consistent with canonical default and salience networks, together with decreased time in network states characterized by coactivation of cingulate and ventral limbic or temporal regions. The effect of sertraline on depression recovery was mediated by these dynamic network changes. In contrast, early changes in dynamic functioning of corticolimbic and frontoinsular-default networks were related to patterns of symptom recovery common across treatment groups. CONCLUSIONS Dynamic resting-state markers of early antidepressant response or general recovery may assist development of clinical tools for monitoring and predicting effective intervention.
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Affiliation(s)
- Roselinde H Kaiser
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado; Institute of Cognitive Science, University of Colorado Boulder, Boulder, Colorado; Renée Crown Wellness Institute, University of Colorado Boulder, Boulder, Colorado.
| | - Henry W Chase
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Mary L Phillips
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Thilo Deckersbach
- Department of Psychiatry, Harvard Medical School and Massachusetts General Hospital, Boston, Massachusetts
| | - Ramin V Parsey
- Department of Psychiatry, Stony Brook University, Stony Brook, New York
| | - Maurizio Fava
- Department of Psychiatry, Harvard Medical School and Massachusetts General Hospital, Boston, Massachusetts
| | - Patrick J McGrath
- Department of Psychiatry, New York State Psychiatric Institute and Columbia University Vagelos College of Physicians and Surgeons, New York, New York
| | - Myrna Weissman
- Department of Psychiatry, New York State Psychiatric Institute and Columbia University Vagelos College of Physicians and Surgeons, New York, New York
| | - Maria A Oquendo
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Melvin G McInnis
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan
| | - Thomas Carmody
- Department of Psychiatry, University of Texas, Southwestern Medical Center, Dallas, Texas
| | - Crystal M Cooper
- Department of Psychiatry, University of Texas, Southwestern Medical Center, Dallas, Texas
| | - Madhukar H Trivedi
- Department of Psychiatry, University of Texas, Southwestern Medical Center, Dallas, Texas
| | - Diego A Pizzagalli
- Department of Psychiatry, Harvard Medical School and McLean Hospital, Boston, Massachusetts
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7
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Ang YS, Bruder GE, Keilp JG, Rutherford A, Alschuler DM, Pechtel P, Webb CA, Carmody T, Fava M, Cusin C, McGrath PJ, Weissman M, Parsey R, Oquendo MA, McInnis MG, Cooper CM, Deldin P, Trivedi MH, Pizzagalli DA. Exploration of baseline and early changes in neurocognitive characteristics as predictors of treatment response to bupropion, sertraline, and placebo in the EMBARC clinical trial. Psychol Med 2022; 52:2441-2449. [PMID: 33213541 PMCID: PMC7613805 DOI: 10.1017/s0033291720004286] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
BACKGROUND Treatment for major depressive disorder (MDD) is imprecise and often involves trial-and-error to determine the most effective approach. To facilitate optimal treatment selection and inform timely adjustment, the current study investigated whether neurocognitive variables could predict an antidepressant response in a treatment-specific manner. METHODS In the two-stage Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) trial, outpatients with non-psychotic recurrent MDD were first randomized to an 8-week course of sertraline selective serotonin reuptake inhibitor or placebo. Behavioral measures of reward responsiveness, cognitive control, verbal fluency, psychomotor, and cognitive processing speeds were collected at baseline and week 1. Treatment responders then continued on another 8-week course of the same medication, whereas non-responders to sertraline or placebo were crossed-over under double-blinded conditions to bupropion noradrenaline/dopamine reuptake inhibitor or sertraline, respectively. Hamilton Rating for Depression scores were also assessed at baseline, weeks 8, and 16. RESULTS Greater improvements in psychomotor and cognitive processing speeds within the first week, as well as better pretreatment performance in these domains, were specifically associated with higher likelihood of response to placebo. Moreover, better reward responsiveness, poorer cognitive control and greater verbal fluency were associated with greater likelihood of response to bupropion in patients who previously failed to respond to sertraline. CONCLUSION These exploratory results warrant further scrutiny, but demonstrate that quick and non-invasive behavioral tests may have substantial clinical value in predicting antidepressant treatment response.
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Affiliation(s)
- Yuen-Siang Ang
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts, USA
| | - Gerard E. Bruder
- Department of Psychiatry, New York State Psychiatric Institute and Columbia University Vagelos College of Physicians and Surgeons, New York, USA
| | - John G. Keilp
- Department of Psychiatry, New York State Psychiatric Institute and Columbia University Vagelos College of Physicians and Surgeons, New York, USA
| | - Ashleigh Rutherford
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts, USA
| | - Daniel M. Alschuler
- Department of Psychiatry, New York State Psychiatric Institute and Columbia University Vagelos College of Physicians and Surgeons, New York, USA
| | - Pia Pechtel
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts, USA
| | - Christian A. Webb
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts, USA
| | - Thomas Carmody
- Department of Psychiatry, University of Texas, Southwestern Medical Center, Dallas, Texas, USA
| | - Maurizio Fava
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Cristina Cusin
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Patrick J. McGrath
- Department of Psychiatry, New York State Psychiatric Institute and Columbia University Vagelos College of Physicians and Surgeons, New York, USA
| | - Myrna Weissman
- Department of Psychiatry, New York State Psychiatric Institute and Columbia University Vagelos College of Physicians and Surgeons, New York, USA
| | - Ramin Parsey
- Department of Psychiatry, Stony Brook University, Stony Brook, New York, USA
| | - Maria A. Oquendo
- Department of Psychiatry, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Melvin G. McInnis
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
| | - Crystal M. Cooper
- Department of Psychiatry, University of Texas, Southwestern Medical Center, Dallas, Texas, USA
| | - Patricia Deldin
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
| | - Madhukar H. Trivedi
- Department of Psychiatry, University of Texas, Southwestern Medical Center, Dallas, Texas, USA
| | - Diego A. Pizzagalli
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts, USA
- McLean Imaging Center, McLean Hospital, Belmont, Massachusetts, USA
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8
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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.
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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.
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9
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Patra BG, Sharma MM, Vekaria V, Adekkanattu P, Patterson OV, Glicksberg B, Lepow LA, Ryu E, Biernacka JM, Furmanchuk A, George TJ, Hogan W, Wu Y, Yang X, Bian J, Weissman M, Wickramaratne P, Mann JJ, Olfson M, Campion TR, Weiner M, Pathak J. Extracting social determinants of health from electronic health records using natural language processing: a systematic review. J Am Med Inform Assoc 2021; 28:2716-2727. [PMID: 34613399 PMCID: PMC8633615 DOI: 10.1093/jamia/ocab170] [Citation(s) in RCA: 56] [Impact Index Per Article: 18.7] [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: 04/29/2021] [Revised: 07/09/2021] [Accepted: 08/04/2021] [Indexed: 11/27/2022] Open
Abstract
OBJECTIVE Social determinants of health (SDoH) are nonclinical dispositions that impact patient health risks and clinical outcomes. Leveraging SDoH in clinical decision-making can potentially improve diagnosis, treatment planning, and patient outcomes. Despite increased interest in capturing SDoH in electronic health records (EHRs), such information is typically locked in unstructured clinical notes. Natural language processing (NLP) is the key technology to extract SDoH information from clinical text and expand its utility in patient care and research. This article presents a systematic review of the state-of-the-art NLP approaches and tools that focus on identifying and extracting SDoH data from unstructured clinical text in EHRs. MATERIALS AND METHODS A broad literature search was conducted in February 2021 using 3 scholarly databases (ACL Anthology, PubMed, and Scopus) following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 6402 publications were initially identified, and after applying the study inclusion criteria, 82 publications were selected for the final review. RESULTS Smoking status (n = 27), substance use (n = 21), homelessness (n = 20), and alcohol use (n = 15) are the most frequently studied SDoH categories. Homelessness (n = 7) and other less-studied SDoH (eg, education, financial problems, social isolation and support, family problems) are mostly identified using rule-based approaches. In contrast, machine learning approaches are popular for identifying smoking status (n = 13), substance use (n = 9), and alcohol use (n = 9). CONCLUSION NLP offers significant potential to extract SDoH data from narrative clinical notes, which in turn can aid in the development of screening tools, risk prediction models, and clinical decision support systems.
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Affiliation(s)
- Braja G Patra
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, USA
| | - Mohit M Sharma
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, USA
| | - Veer Vekaria
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, USA
| | - Prakash Adekkanattu
- Information Technologies and Services, Weill Cornell Medicine, New York, New York, USA
| | - Olga V Patterson
- Department of Internal Medicine, Division of Epidemiology, University of Utah, Salt Lake City, Utah, USA
- US Department of Veterans Affairs, Salt Lake City, Utah, USA
| | | | - Lauren A Lepow
- Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Euijung Ryu
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | - Joanna M Biernacka
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Thomas J George
- Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, Florida, USA
| | - William Hogan
- Division of Hematology & Oncology, Department of Medicine, College of Medicine, University of Florida, Gainesville, Florida, USA, and
| | - Yonghui Wu
- Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, Florida, USA
| | - Xi Yang
- Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, Florida, USA
| | - Jiang Bian
- Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, Florida, USA
| | - Myrna Weissman
- Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Priya Wickramaratne
- Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - J John Mann
- Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Mark Olfson
- Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Thomas R Campion
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, USA
- Information Technologies and Services, Weill Cornell Medicine, New York, New York, USA
| | - Mark Weiner
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, USA
| | - Jyotishman Pathak
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, USA
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10
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Saunders D, Svob C, Pan L, Abraham E, Posner J, Weissman M, Wickramaratne P. Differential Association of Spirituality and Religiosity With Rumination: Implications for the Treatment of Depression. J Nerv Ment Dis 2021; 209:370-377. [PMID: 33835955 PMCID: PMC8041060 DOI: 10.1097/nmd.0000000000001306] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
ABSTRACT Recent studies have shown that religiosity (R) is associated with lower rates of depression, whereas spirituality (S) is associated with higher rates. Rumination has also been associated with higher rates of depression. Some have hypothesized that rumination mediates the differential association of religiosity and spirituality with depression. We empirically test this hypothesis in a longitudinal, multigenerational sample through associations between rumination and depression, R/S and depression, and R/S and rumination. Cross-sectionally, total rumination scores were predicted by spirituality (standardized β = 0.13; 95% confidence interval [CI], 0.00-0.26), with subscale (reflection, depression, and brooding) standardized betas ranging from 0.11 to 0.15 (95% CI, -0.03 to -0.29). Cross-sectionally, rumination was not predicted by religiosity. Longitudinally, and consistent with previous findings, religiosity, but not spirituality, predicted reduced depressive symptoms (standardized β = -0.3; 95% CI, -0.58 to -0.01). The association between spirituality and rumination was driven by millennials. Psychotherapies that target rumination for depression might therefore be especially effective in the millennial demographic.
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Affiliation(s)
| | | | - Lifang Pan
- Division of Translational Epidemiology, New York State Psychiatric Institute
| | - Eyal Abraham
- Division of Translational Epidemiology, New York State Psychiatric Institute
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11
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Chin Fatt CR, Cooper CM, Jha MK, Minhajuddin A, Rush AJ, Trombello JM, Fava M, McInnis M, Weissman M, Trivedi MH. Differential response to SSRI versus Placebo and distinct neural signatures among data-driven subgroups of patients with major depressive disorder. J Affect Disord 2021; 282:602-610. [PMID: 33445082 DOI: 10.1016/j.jad.2020.12.102] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 11/19/2020] [Accepted: 12/24/2020] [Indexed: 11/19/2022]
Abstract
OBJECTIVE To identify data-driven subgroups in Major Depressive Disorder (MDD) in order to elucidate underlying neural correlates and determine if these subgroups have utility in predicting response to antidepressant versus placebo. METHODS Using 27 clinical measures at baseline of Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC) study, participants with MDD (n=244) were sub grouped using principal component (PC) analysis. Baseline-to-week-8 changes in depression severity with sertraline versus placebo were compared in these subgroups. Resting-state functional connectivity of these subgroups were compared to those of healthy controls (n=38). RESULTS Eight subgroups were identified from four PCs: (PC1) severity of depression-associated symptoms, (PC2) sub-threshold mania and anhedonia, (PC3) childhood trauma, medical comorbidities, and sexual dysfunction, and (PC4) personality traits of openness and agreeableness. Participants with high childhood trauma experienced greater improvement with sertraline (Cohen's d=0.87), whereas those with either higher levels of subthreshold hypomanic symptoms (Cohen's d=0.67) or with lower levels of agreeableness and openness experienced greater improvement with placebo (Cohen's d=0.71). Participants with high childhood trauma had greater connectivity between salience and dorsal attention networks, whereas those with higher levels of subthreshold hypomanic symptoms and lower levels of agreeableness and openness had greater connectivity within limbic network and that of visual network with hippocampus and dorsal attention network. CONCLUSION Assessing history of childhood trauma, presence of subthreshold hypomanic symptoms and personality traits may help to identify subgroups of patients with MDD who respond differentially to sertraline or placebo and have distinct neural signatures.
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Affiliation(s)
- Cherise R Chin Fatt
- The University of Texas Southwestern Medical Center, Department of Psychiatry, Center for Depression Research and Clinical Care, Department of Psychiatry, 5323 Harry Hines Blvd., Dallas, TX, USA
| | - Crystal M Cooper
- The University of Texas Southwestern Medical Center, Department of Psychiatry, Center for Depression Research and Clinical Care, Department of Psychiatry, 5323 Harry Hines Blvd., Dallas, TX, USA
| | - Manish K Jha
- The University of Texas Southwestern Medical Center, Department of Psychiatry, Center for Depression Research and Clinical Care, Department of Psychiatry, 5323 Harry Hines Blvd., Dallas, TX, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place. Box 1230. New York, NY, 10029, USA
| | - Abu Minhajuddin
- The University of Texas Southwestern Medical Center, Department of Psychiatry, Center for Depression Research and Clinical Care, Department of Psychiatry, 5323 Harry Hines Blvd., Dallas, TX, USA
| | - A John Rush
- Department of Psychiatry and Behavioral Sciences, Duke-National University of Singapore, Singapore, 169857; Department of Psychiatry, Duke University Medical School, Durham, NC, USA; Department of Psychiatry, Texas Tech University, Health Science Center, Permian Basin, Midland, TX, USA
| | - Joseph M Trombello
- The University of Texas Southwestern Medical Center, Department of Psychiatry, Center for Depression Research and Clinical Care, Department of Psychiatry, 5323 Harry Hines Blvd., Dallas, TX, USA
| | - Maurizio Fava
- Department of Psychiatry, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02144, USA
| | - Melvin McInnis
- Department of Psychiatry, University of Michigan School of Medicine, 4250 Plymouth Road, Ann Arbor, MI 48109-2700, USA
| | - Myrna Weissman
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, 1051 Riverside Drive, New York, NY 10032, USA
| | - Madhukar H Trivedi
- The University of Texas Southwestern Medical Center, Department of Psychiatry, Center for Depression Research and Clinical Care, Department of Psychiatry, 5323 Harry Hines Blvd., Dallas, TX, USA.
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12
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Ang YS, Kaiser R, Deckersbach T, Almeida J, Phillips ML, Chase HW, Webb CA, Parsey R, Fava M, McGrath P, Weissman M, Adams P, Deldin P, Oquendo MA, McInnis MG, Carmody T, Bruder G, Cooper CM, Fatt CRC, Trivedi MH, Pizzagalli DA. Pretreatment Reward Sensitivity and Frontostriatal Resting-State Functional Connectivity Are Associated With Response to Bupropion After Sertraline Nonresponse. Biol Psychiatry 2020; 88:657-667. [PMID: 32507389 PMCID: PMC7529779 DOI: 10.1016/j.biopsych.2020.04.009] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [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: 12/02/2019] [Revised: 03/24/2020] [Accepted: 04/13/2020] [Indexed: 12/21/2022]
Abstract
BACKGROUND Standard guidelines recommend selective serotonin reuptake inhibitors as first-line antidepressants for adults with major depressive disorder, but success is limited and patients who fail to benefit are often switched to non-selective serotonin reuptake inhibitor agents. This study investigated whether brain- and behavior-based markers of reward processing might be associated with response to bupropion after sertraline nonresponse. METHODS In a two-stage, double-blinded clinical trial, 296 participants were randomized to receive 8 weeks of sertraline or placebo in stage 1. Individuals who responded continued on another 8-week course of the same intervention in stage 2, while sertraline and placebo nonresponders crossed over to bupropion and sertraline, respectively. Data from 241 participants were analyzed. The stage 2 sample comprised 87 patients with major depressive disorder who switched medication and 38 healthy control subjects. A total of 116 participants with major depressive disorder treated with sertraline in stage 1 served as an independent replication sample. The probabilistic reward task and resting-state functional magnetic resonance imaging were administered at baseline. RESULTS Greater pretreatment reward sensitivity and higher resting-state functional connectivity between bilateral nucleus accumbens and rostral anterior cingulate cortex were associated with positive response to bupropion but not sertraline. Null findings for sertraline were replicated in the stage 1 sample. CONCLUSIONS Pretreatment reward sensitivity and frontostriatal connectivity may identify patients likely to benefit from bupropion following selective serotonin reuptake inhibitor failures. Results call for a prospective replication based on these biomarkers to advance clinical care.
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Affiliation(s)
- Yuen-Siang Ang
- Department of Psychiatry, Harvard Medical School, Boston, 25 Shattuck Street, Boston, MA 02115,Center for Depression, Anxiety and Stress Research, McLean Hospital, 115 Mill Street, Belmont, MA 02478
| | - Roselinde Kaiser
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO 80302
| | - Thilo Deckersbach
- Department of Psychiatry, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114
| | - Jorge Almeida
- Department of Psychiatry, University of Texas at Austin, Dell Medical School, 1601 Trinity St., Austin, TX 78712
| | - Mary L. Phillips
- Department of Psychiatry, University of Pittsburgh, 3811 O’Hara St, Pittsburgh, PA 15213
| | - Henry W. Chase
- Department of Psychiatry, University of Pittsburgh, 3811 O’Hara St, Pittsburgh, PA 15213
| | - Christian A. Webb
- Department of Psychiatry, Harvard Medical School, Boston, 25 Shattuck Street, Boston, MA 02115,Center for Depression, Anxiety and Stress Research, McLean Hospital, 115 Mill Street, Belmont, MA 02478
| | - Ramin Parsey
- Department of Psychiatry, Stony Brook University, Stony Brook, 100 Nicolls Road, Stony Brook, NY 11794
| | - Maurizio Fava
- Department of Psychiatry, Harvard Medical School, Boston, 25 Shattuck Street, Boston, MA 02115,Department of Psychiatry, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114
| | - Patrick McGrath
- New York State Psychiatric Institute & Department of Psychiatry, Columbia University Vagelos College of Physicians and Surgeons, 1051 Riverside Drive, New York, NY 10032
| | - Myrna Weissman
- New York State Psychiatric Institute & Department of Psychiatry, Columbia University Vagelos College of Physicians and Surgeons, 1051 Riverside Drive, New York, NY 10032
| | - Phil Adams
- New York State Psychiatric Institute & Department of Psychiatry, Columbia University Vagelos College of Physicians and Surgeons, 1051 Riverside Drive, New York, NY 10032
| | - Patricia Deldin
- Department of Psychiatry, University of Michigan, 500 S State Street, Ann Arbor, MI 48109
| | - Maria A. Oquendo
- Department of Psychiatry, University of Pennsylvania, Perelman School of Medicine, 3400 Civic Center Blvd, Philadelphia, PA 19104
| | - Melvin G. McInnis
- Department of Psychiatry, University of Michigan, 500 S State Street, Ann Arbor, MI 48109
| | - Thomas Carmody
- Department of Psychiatry, University of Texas, Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390
| | - Gerard Bruder
- New York State Psychiatric Institute & Department of Psychiatry, Columbia University Vagelos College of Physicians and Surgeons, 1051 Riverside Drive, New York, NY 10032
| | - Crystal M. Cooper
- Department of Psychiatry, University of Texas, Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390
| | - Cherise R. Chin Fatt
- Department of Psychiatry, University of Texas, Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390
| | - Madhukar H. Trivedi
- Department of Psychiatry, University of Texas, Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390
| | - Diego A. Pizzagalli
- Department of Psychiatry, Harvard Medical School, Boston, 25 Shattuck Street, Boston, MA 02115,Center for Depression, Anxiety and Stress Research, McLean Hospital, 115 Mill Street, Belmont, MA 02478
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13
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Greenberg T, Fournier J, Stiffler R, Chase HW, Almeida JR, Aslam H, Deckersbach T, Cooper C, Toups M, Carmody T, Kurian B, Peltier S, Adams P, McInnis MG, Oquendo MA, Fava M, Parsey R, McGrath PJ, Weissman M, Trivedi M, Phillips ML. Reward related ventral striatal activity and differential response to sertraline versus placebo in depressed individuals. Mol Psychiatry 2020; 25:1526-1536. [PMID: 31462766 PMCID: PMC7047617 DOI: 10.1038/s41380-019-0490-5] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Revised: 04/16/2019] [Accepted: 05/31/2019] [Indexed: 12/22/2022]
Abstract
Medications to treat major depressive disorder (MDD) are not equally effective across patients. Given that neural response to rewards is altered in MDD and given that reward-related circuitry is modulated by dopamine and serotonin, we examined, for the first time, whether reward-related neural activity moderated response to sertraline, an antidepressant medication that targets these neurotransmitters. A total of 222 unmedicated adults with MDD randomized to receive sertraline (n = 110) or placebo (n = 112) in the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study completed demographic and clinical assessments, and pretreatment functional magnetic resonance imaging while performing a reward task. We tested whether an index of reward system function in the ventral striatum (VS), a key reward circuitry region, moderated differential response to sertraline versus placebo, assessed with the Hamilton Rating Scale for Depression (HSRD) over 8 weeks. We observed a significant moderation effect of the reward index, reflecting the temporal dynamics of VS activity, on week-8 depression levels (Fs ≥ 9.67, ps ≤ 0.002). Specifically, VS responses that were abnormal with respect to predictions from reinforcement learning theory were associated with lower week-8 depression symptoms in the sertraline versus placebo arms. Thus, a more abnormal pattern of pretreatment VS dynamic response to reward expectancy (expected outcome value) and prediction error (difference between expected and actual outcome), likely reflecting serotonergic and dopaminergic deficits, was associated with better response to sertraline than placebo. Pretreatment measures of reward-related VS activity may serve as objective neural markers to advance efforts to personalize interventions by guiding individual-level choice of antidepressant treatment.
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Affiliation(s)
- Tsafrir Greenberg
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Jay Fournier
- Department of Psychiatry, University of Pittsburgh School of Medicine
| | - Richelle Stiffler
- Department of Psychiatry, University of Pittsburgh School of Medicine
| | - Henry W. Chase
- Department of Psychiatry, University of Pittsburgh School of Medicine
| | - Jorge R. Almeida
- Department of Psychiatry, University of Texas at Austin Dell Medical School
| | - Haris Aslam
- Department of Psychiatry, University of Pittsburgh School of Medicine
| | | | - Crystal Cooper
- Department of Psychiatry, University of Texas Southwestern Medical Center
| | - Marisa Toups
- Department of Psychiatry, University of Texas at Austin Dell Medical School
| | - Tom Carmody
- Department of Psychiatry, University of Texas Southwestern Medical Center
| | - Benji Kurian
- Department of Psychiatry, University of Texas Southwestern Medical Center
| | | | - Phillip Adams
- Department of Psychiatry, Columbia University College of Physicians and Surgeons and the New York State Psychiatric Institute
| | | | - Maria A. Oquendo
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania
| | - Maurizio Fava
- Department of Psychiatry, Massachusetts General Hospital
| | - Ramin Parsey
- Departments of Psychiatry and Behavioral Science & Radiology, Stony Brook University
| | - Patrick J. McGrath
- Department of Psychiatry, Columbia University College of Physicians and Surgeons and the New York State Psychiatric Institute
| | - Myrna Weissman
- Department of Psychiatry, Columbia University College of Physicians and Surgeons and the New York State Psychiatric Institute
| | - Madhukar Trivedi
- Department of Psychiatry, University of Texas Southwestern Medical Center
| | - Mary L. Phillips
- Department of Psychiatry, University of Pittsburgh School of Medicine
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14
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Cooper CM, Chin Fatt CR, Liu P, Grannemann BD, Carmody T, Almeida JRC, Deckersbach T, Fava M, Kurian BT, Malchow AL, McGrath PJ, McInnis M, Oquendo MA, Parsey RV, Bartlett E, Weissman M, Phillips ML, Lu H, Trivedi MH. Discovery and replication of cerebral blood flow differences in major depressive disorder. Mol Psychiatry 2020; 25:1500-1510. [PMID: 31388104 DOI: 10.1038/s41380-019-0464-7] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [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: 10/16/2017] [Revised: 03/06/2019] [Accepted: 03/26/2019] [Indexed: 01/08/2023]
Abstract
Major depressive disorder (MDD) is a serious, heterogeneous disorder accompanied by brain-related changes, many of which are still to be discovered or refined. Arterial spin labeling (ASL) is a neuroimaging technique used to measure cerebral blood flow (CBF; perfusion) to understand brain function and detect differences among groups. CBF differences have been detected in MDD, and may reveal biosignatures of disease-state. The current work aimed to discover and replicate differences in CBF between MDD participants and healthy controls (HC) as part of the EMBARC study. Participants underwent neuroimaging at baseline, prior to starting study medication, to investigate biosignatures in MDD. Relative CBF (rCBF) was calculated and compared between 106 MDD and 36 HC EMBARC participants (whole-brain Discovery); and 58 MDD EMBARC participants and 58 HC from the DLBS study (region-of-interest Replication). Both analyses revealed reduced rCBF in the right parahippocampus, thalamus, fusiform and middle temporal gyri, as well as the left and right insula, for those with MDD relative to HC. Both samples also revealed increased rCBF in MDD relative to HC in both the left and right inferior parietal lobule, including the supramarginal and angular gyri. Cingulate and prefrontal regions did not fully replicate. Lastly, significant associations were detected between rCBF in replicated regions and clinical measures of MDD chronicity. These results (1) provide reliable evidence for ASL in detecting differences in perfusion for multiple brain regions thought to be important in MDD, and (2) highlight the potential role of using perfusion as a biosignature of MDD.
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Affiliation(s)
- Crystal M Cooper
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Cherise R Chin Fatt
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Peiying Liu
- Department of Radiology, Johns Hopkins University, Baltimore, MD, USA
| | - Bruce D Grannemann
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Thomas Carmody
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Jorge R C Almeida
- Department of Psychiatry, Dell Medical School, University of Texas Austin, Austin, TX, USA
| | - Thilo Deckersbach
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Maurizio Fava
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Benji T Kurian
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Ashley L Malchow
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Patrick J McGrath
- Department of Psychiatry, Columbia University, New York State Psychiatric Institute, New York, NY, USA
| | - Melvin McInnis
- Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor, MI, USA
| | - Maria A Oquendo
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ramin V Parsey
- Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA
| | - Elizabeth Bartlett
- Department of Psychiatry, Columbia University, New York State Psychiatric Institute, New York, NY, USA
| | - Myrna Weissman
- Department of Psychiatry, Columbia University, New York State Psychiatric Institute, New York, NY, USA
| | - Mary L Phillips
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Hanzhang Lu
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA.,Department of Radiology, Johns Hopkins University, Baltimore, MD, USA
| | - Madhukar H Trivedi
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA.
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15
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Chin Fatt CR, Jha MK, Cooper CM, Fonzo G, South C, Grannemann B, Carmody T, Greer TL, Kurian B, Fava M, McGrath PJ, Adams P, McInnis M, Parsey RV, Weissman M, Phillips ML, Etkin A, Trivedi MH. Effect of Intrinsic Patterns of Functional Brain Connectivity in Moderating Antidepressant Treatment Response in Major Depression. Am J Psychiatry 2020; 177:143-154. [PMID: 31537090 DOI: 10.1176/appi.ajp.2019.18070870] [Citation(s) in RCA: 64] [Impact Index Per Article: 16.0] [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: 11/30/2022]
Abstract
OBJECTIVE Major depressive disorder is associated with aberrant resting-state functional connectivity across multiple brain networks supporting emotion processing, executive function, and reward processing. The purpose of this study was to determine whether patterns of resting-state connectivity between brain regions predict differential outcome to antidepressant medication (sertraline) compared with placebo. METHODS Participants in the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study underwent structural and resting-state functional MRI at baseline. Participants were then randomly assigned to receive either sertraline or placebo treatment for 8 weeks (N=279). A region of interest-based approach was utilized to compute functional connectivity between brain regions. Linear mixed-model intent-to-treat analyses were used to identify brain regions that moderated (i.e., differentially predicted) outcomes between the sertraline and placebo arms. RESULTS Prediction of response to sertraline involved several within- and between-network connectivity patterns. In general, higher connectivity within the default mode network predicted better outcomes specifically for sertraline, as did greater between-network connectivity of the default mode and executive control networks. In contrast, both placebo and sertraline outcomes were predicted (in opposite directions) by between-network hippocampal connectivity. CONCLUSIONS This study identified specific functional network-based moderators of treatment outcome involving brain networks known to be affected by major depression. Specifically, functional connectivity patterns of brain regions between and within networks appear to play an important role in identifying a favorable response for a drug treatment for major depressive disorder.
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Affiliation(s)
- Cherise R Chin Fatt
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas (Chin Fatt, Jha, Cooper, South, Grannemann, Carmody, Greer, Kurian, Trivedi); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Jha); Department of Psychiatry and Behavioral Sciences and Stanford Neurosciences Institute, Stanford University, Stanford, Calif. (Fonzo, Etkin); Mental Illness Research, Education, and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Fonzo, Etkin); Department of Psychiatry, Massachusetts General Hospital, Boston (Fava); New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York (McGrath, Adams, Weissman); Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor (McInnis); Department of Psychiatry and Behavioral Science and Department of Radiology, Stony Brook University, Stony Brook, N.Y. (Parsey); and Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh (Phillips)
| | - Manish K Jha
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas (Chin Fatt, Jha, Cooper, South, Grannemann, Carmody, Greer, Kurian, Trivedi); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Jha); Department of Psychiatry and Behavioral Sciences and Stanford Neurosciences Institute, Stanford University, Stanford, Calif. (Fonzo, Etkin); Mental Illness Research, Education, and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Fonzo, Etkin); Department of Psychiatry, Massachusetts General Hospital, Boston (Fava); New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York (McGrath, Adams, Weissman); Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor (McInnis); Department of Psychiatry and Behavioral Science and Department of Radiology, Stony Brook University, Stony Brook, N.Y. (Parsey); and Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh (Phillips)
| | - Crystal M Cooper
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas (Chin Fatt, Jha, Cooper, South, Grannemann, Carmody, Greer, Kurian, Trivedi); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Jha); Department of Psychiatry and Behavioral Sciences and Stanford Neurosciences Institute, Stanford University, Stanford, Calif. (Fonzo, Etkin); Mental Illness Research, Education, and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Fonzo, Etkin); Department of Psychiatry, Massachusetts General Hospital, Boston (Fava); New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York (McGrath, Adams, Weissman); Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor (McInnis); Department of Psychiatry and Behavioral Science and Department of Radiology, Stony Brook University, Stony Brook, N.Y. (Parsey); and Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh (Phillips)
| | - Gregory Fonzo
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas (Chin Fatt, Jha, Cooper, South, Grannemann, Carmody, Greer, Kurian, Trivedi); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Jha); Department of Psychiatry and Behavioral Sciences and Stanford Neurosciences Institute, Stanford University, Stanford, Calif. (Fonzo, Etkin); Mental Illness Research, Education, and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Fonzo, Etkin); Department of Psychiatry, Massachusetts General Hospital, Boston (Fava); New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York (McGrath, Adams, Weissman); Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor (McInnis); Department of Psychiatry and Behavioral Science and Department of Radiology, Stony Brook University, Stony Brook, N.Y. (Parsey); and Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh (Phillips)
| | - Charles South
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas (Chin Fatt, Jha, Cooper, South, Grannemann, Carmody, Greer, Kurian, Trivedi); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Jha); Department of Psychiatry and Behavioral Sciences and Stanford Neurosciences Institute, Stanford University, Stanford, Calif. (Fonzo, Etkin); Mental Illness Research, Education, and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Fonzo, Etkin); Department of Psychiatry, Massachusetts General Hospital, Boston (Fava); New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York (McGrath, Adams, Weissman); Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor (McInnis); Department of Psychiatry and Behavioral Science and Department of Radiology, Stony Brook University, Stony Brook, N.Y. (Parsey); and Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh (Phillips)
| | - Bruce Grannemann
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas (Chin Fatt, Jha, Cooper, South, Grannemann, Carmody, Greer, Kurian, Trivedi); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Jha); Department of Psychiatry and Behavioral Sciences and Stanford Neurosciences Institute, Stanford University, Stanford, Calif. (Fonzo, Etkin); Mental Illness Research, Education, and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Fonzo, Etkin); Department of Psychiatry, Massachusetts General Hospital, Boston (Fava); New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York (McGrath, Adams, Weissman); Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor (McInnis); Department of Psychiatry and Behavioral Science and Department of Radiology, Stony Brook University, Stony Brook, N.Y. (Parsey); and Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh (Phillips)
| | - Thomas Carmody
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas (Chin Fatt, Jha, Cooper, South, Grannemann, Carmody, Greer, Kurian, Trivedi); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Jha); Department of Psychiatry and Behavioral Sciences and Stanford Neurosciences Institute, Stanford University, Stanford, Calif. (Fonzo, Etkin); Mental Illness Research, Education, and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Fonzo, Etkin); Department of Psychiatry, Massachusetts General Hospital, Boston (Fava); New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York (McGrath, Adams, Weissman); Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor (McInnis); Department of Psychiatry and Behavioral Science and Department of Radiology, Stony Brook University, Stony Brook, N.Y. (Parsey); and Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh (Phillips)
| | - Tracy L Greer
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas (Chin Fatt, Jha, Cooper, South, Grannemann, Carmody, Greer, Kurian, Trivedi); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Jha); Department of Psychiatry and Behavioral Sciences and Stanford Neurosciences Institute, Stanford University, Stanford, Calif. (Fonzo, Etkin); Mental Illness Research, Education, and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Fonzo, Etkin); Department of Psychiatry, Massachusetts General Hospital, Boston (Fava); New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York (McGrath, Adams, Weissman); Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor (McInnis); Department of Psychiatry and Behavioral Science and Department of Radiology, Stony Brook University, Stony Brook, N.Y. (Parsey); and Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh (Phillips)
| | - Benji Kurian
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas (Chin Fatt, Jha, Cooper, South, Grannemann, Carmody, Greer, Kurian, Trivedi); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Jha); Department of Psychiatry and Behavioral Sciences and Stanford Neurosciences Institute, Stanford University, Stanford, Calif. (Fonzo, Etkin); Mental Illness Research, Education, and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Fonzo, Etkin); Department of Psychiatry, Massachusetts General Hospital, Boston (Fava); New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York (McGrath, Adams, Weissman); Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor (McInnis); Department of Psychiatry and Behavioral Science and Department of Radiology, Stony Brook University, Stony Brook, N.Y. (Parsey); and Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh (Phillips)
| | - Maurizio Fava
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas (Chin Fatt, Jha, Cooper, South, Grannemann, Carmody, Greer, Kurian, Trivedi); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Jha); Department of Psychiatry and Behavioral Sciences and Stanford Neurosciences Institute, Stanford University, Stanford, Calif. (Fonzo, Etkin); Mental Illness Research, Education, and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Fonzo, Etkin); Department of Psychiatry, Massachusetts General Hospital, Boston (Fava); New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York (McGrath, Adams, Weissman); Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor (McInnis); Department of Psychiatry and Behavioral Science and Department of Radiology, Stony Brook University, Stony Brook, N.Y. (Parsey); and Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh (Phillips)
| | - Patrick J McGrath
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas (Chin Fatt, Jha, Cooper, South, Grannemann, Carmody, Greer, Kurian, Trivedi); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Jha); Department of Psychiatry and Behavioral Sciences and Stanford Neurosciences Institute, Stanford University, Stanford, Calif. (Fonzo, Etkin); Mental Illness Research, Education, and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Fonzo, Etkin); Department of Psychiatry, Massachusetts General Hospital, Boston (Fava); New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York (McGrath, Adams, Weissman); Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor (McInnis); Department of Psychiatry and Behavioral Science and Department of Radiology, Stony Brook University, Stony Brook, N.Y. (Parsey); and Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh (Phillips)
| | - Phillip Adams
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas (Chin Fatt, Jha, Cooper, South, Grannemann, Carmody, Greer, Kurian, Trivedi); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Jha); Department of Psychiatry and Behavioral Sciences and Stanford Neurosciences Institute, Stanford University, Stanford, Calif. (Fonzo, Etkin); Mental Illness Research, Education, and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Fonzo, Etkin); Department of Psychiatry, Massachusetts General Hospital, Boston (Fava); New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York (McGrath, Adams, Weissman); Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor (McInnis); Department of Psychiatry and Behavioral Science and Department of Radiology, Stony Brook University, Stony Brook, N.Y. (Parsey); and Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh (Phillips)
| | - Melvin McInnis
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas (Chin Fatt, Jha, Cooper, South, Grannemann, Carmody, Greer, Kurian, Trivedi); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Jha); Department of Psychiatry and Behavioral Sciences and Stanford Neurosciences Institute, Stanford University, Stanford, Calif. (Fonzo, Etkin); Mental Illness Research, Education, and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Fonzo, Etkin); Department of Psychiatry, Massachusetts General Hospital, Boston (Fava); New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York (McGrath, Adams, Weissman); Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor (McInnis); Department of Psychiatry and Behavioral Science and Department of Radiology, Stony Brook University, Stony Brook, N.Y. (Parsey); and Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh (Phillips)
| | - Ramin V Parsey
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas (Chin Fatt, Jha, Cooper, South, Grannemann, Carmody, Greer, Kurian, Trivedi); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Jha); Department of Psychiatry and Behavioral Sciences and Stanford Neurosciences Institute, Stanford University, Stanford, Calif. (Fonzo, Etkin); Mental Illness Research, Education, and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Fonzo, Etkin); Department of Psychiatry, Massachusetts General Hospital, Boston (Fava); New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York (McGrath, Adams, Weissman); Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor (McInnis); Department of Psychiatry and Behavioral Science and Department of Radiology, Stony Brook University, Stony Brook, N.Y. (Parsey); and Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh (Phillips)
| | - Myrna Weissman
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas (Chin Fatt, Jha, Cooper, South, Grannemann, Carmody, Greer, Kurian, Trivedi); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Jha); Department of Psychiatry and Behavioral Sciences and Stanford Neurosciences Institute, Stanford University, Stanford, Calif. (Fonzo, Etkin); Mental Illness Research, Education, and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Fonzo, Etkin); Department of Psychiatry, Massachusetts General Hospital, Boston (Fava); New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York (McGrath, Adams, Weissman); Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor (McInnis); Department of Psychiatry and Behavioral Science and Department of Radiology, Stony Brook University, Stony Brook, N.Y. (Parsey); and Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh (Phillips)
| | - Mary L Phillips
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas (Chin Fatt, Jha, Cooper, South, Grannemann, Carmody, Greer, Kurian, Trivedi); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Jha); Department of Psychiatry and Behavioral Sciences and Stanford Neurosciences Institute, Stanford University, Stanford, Calif. (Fonzo, Etkin); Mental Illness Research, Education, and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Fonzo, Etkin); Department of Psychiatry, Massachusetts General Hospital, Boston (Fava); New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York (McGrath, Adams, Weissman); Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor (McInnis); Department of Psychiatry and Behavioral Science and Department of Radiology, Stony Brook University, Stony Brook, N.Y. (Parsey); and Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh (Phillips)
| | - Amit Etkin
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas (Chin Fatt, Jha, Cooper, South, Grannemann, Carmody, Greer, Kurian, Trivedi); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Jha); Department of Psychiatry and Behavioral Sciences and Stanford Neurosciences Institute, Stanford University, Stanford, Calif. (Fonzo, Etkin); Mental Illness Research, Education, and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Fonzo, Etkin); Department of Psychiatry, Massachusetts General Hospital, Boston (Fava); New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York (McGrath, Adams, Weissman); Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor (McInnis); Department of Psychiatry and Behavioral Science and Department of Radiology, Stony Brook University, Stony Brook, N.Y. (Parsey); and Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh (Phillips)
| | - Madhukar H Trivedi
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas (Chin Fatt, Jha, Cooper, South, Grannemann, Carmody, Greer, Kurian, Trivedi); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Jha); Department of Psychiatry and Behavioral Sciences and Stanford Neurosciences Institute, Stanford University, Stanford, Calif. (Fonzo, Etkin); Mental Illness Research, Education, and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Fonzo, Etkin); Department of Psychiatry, Massachusetts General Hospital, Boston (Fava); New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York (McGrath, Adams, Weissman); Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor (McInnis); Department of Psychiatry and Behavioral Science and Department of Radiology, Stony Brook University, Stony Brook, N.Y. (Parsey); and Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh (Phillips)
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Cha J, Guffanti G, Gingrich J, Talati A, Wickramaratne P, Weissman M, Posner J. Effects of Serotonin Transporter Gene Variation on Impulsivity Mediated by Default Mode Network: A Family Study of Depression. Cereb Cortex 2019; 28:1911-1921. [PMID: 28444137 DOI: 10.1093/cercor/bhx097] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2017] [Accepted: 04/04/2017] [Indexed: 12/21/2022] Open
Abstract
Serotonergic neurotransmission, potentially through effects on the brain's default mode network (DMN), may regulate aspects of attention including impulse control. Indeed, genetic variants of the serotonin transporter (5-HTT) have been implicated in impulsivity and related psychopathology. Yet it remains unclear the mechanism by which the 5-HTT genetic variants contribute to individual variability in impulse control. Here, we tested whether DMN connectivity mediates an association between the 5-HTT genetic variants and impulsivity. Participants (N = 92) were from a family cohort study of depression in which we have previously shown a broad distribution of 5-HTT variants. We genotyped for 5-HTTLPR and rs25531 (stratified by transcriptional efficiency: 8 low/low, 53 low/high, and 31 high/high), estimated DMN structural connectivity using diffusion probabilistic tractography, and assessed behavioral measures of impulsivity (from 12 low/low, 48 low/high, and 31 high/high) using the Continuous Performance Task. We found that low transcriptional efficiency genotypes were associated with decreased connection strength between the posterior DMN and the superior frontal gyrus (SFG). Path modeling demonstrated that decreased DMN-SFG connectivity mediated the association between low-efficiency genotypes and increased impulsivity. Taken together, this study suggests a gene-brain-behavior pathway that perhaps underlies the role of the serotonergic neuromodulation in impulse control.
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Affiliation(s)
- Jiook Cha
- Department of Psychiatry, Columbia University Medical Center, The New York State Psychiatric Institute, New York, NY 10032, USA
| | - Guia Guffanti
- Harvard Medical School, Department of Psychiatry, McLean Hospital, Belmont, MA, USA
| | - Jay Gingrich
- Department of Psychiatry, Columbia University Medical Center, The New York State Psychiatric Institute, New York, NY 10032, USA
| | - Ardesheer Talati
- Department of Psychiatry, Columbia University Medical Center, The New York State Psychiatric Institute, New York, NY 10032, USA
| | - Priya Wickramaratne
- Department of Psychiatry, Columbia University Medical Center, The New York State Psychiatric Institute, New York, NY 10032, USA
| | - Myrna Weissman
- Department of Psychiatry, Columbia University Medical Center, The New York State Psychiatric Institute, New York, NY 10032, USA
| | - Jonathan Posner
- Department of Psychiatry, Columbia University Medical Center, The New York State Psychiatric Institute, New York, NY 10032, USA
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17
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Pillai RL, Chuan H, LaBella A, Mengru Z, Jie Y, Trivedi M, Weissman M, McGrath P, Fava M, Kurian B, Cooper C, McInnis M, Oquendo MA, Pizzagalli DA, Parsey RV, DeLorenzo C. Examining raphe-amygdala structural connectivity as a biological predictor of SSRI response. J Affect Disord 2019; 256:8-16. [PMID: 31158720 PMCID: PMC6750958 DOI: 10.1016/j.jad.2019.05.055] [Citation(s) in RCA: 10] [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] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2018] [Revised: 04/18/2019] [Accepted: 05/27/2019] [Indexed: 12/28/2022]
Abstract
BACKGROUND Our lab has previously found that structural integrity in tracts from the raphe nucleus (RN) to the amygdala, measured by fractional anisotropy (FA), predicts remission to selective serotonin reuptake inhibitors (SSRIs) in major depressive disorder (MDD). This could potentially serve as a biomarker for remission that can guide clinical decision-making. To enhance repeatability and reproducibility, we replicated our study in a larger, more representative multi-site sample. METHODS 64 direction DTI was collected in 144 medication-free patients with MDD from the Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) study. We performed probabilistic tractography between the RN and bilateral amygdala and hippocampus and calculated weighted FA in these tracts. Patients were treated with either sertraline or placebo, and their change in Hamilton Depression Rating Scale (HDRS) score reported. Pretreatment weighted FA was compared between remitters and nonremitters, and correlation between FA and percent change in HDRS score was assessed. Exploratory moderator and voxel analyses were also performed. RESULTS Contrary to our hypotheses, FA was greater in nonremitters than in remitters in RN-left and right amygdala tracts (p = 0.02 and 0.01, respectively). Pretreatment FA between the raphe and left amygdala correlated with greater, not reduced, HDRS (r = 0.18, p = 0.04). This finding was found to be greater in the placebo group. Moderator and voxel analyses yielded no significant findings. CONCLUSIONS We found greater FA in nonremitters between the RN and amygdala than in remitters, and a correlation between FA and symptom worsening, particularly with placebo. These findings may help reveal more about the nature of MDD, as well as guide research methods involving placebo response.
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Affiliation(s)
| | - Huang Chuan
- Department of Psychiatry, Stony Brook University, Stony Brook, NY, United States,Department of Radiology, Stony Brook University, Stony Brook, NY, United States,Corresponding author at: Department of Psychiatry, Stony Brook Medicine, HSC-T10-020, Stony Brook, NY 11794, United States., (C. Huang)
| | - Andrew LaBella
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, United States
| | - Zhang Mengru
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, United States
| | - Yang Jie
- Department of Family, Population, & Preventive Medicine, Stony Brook University, Stony Brook, NY, United States
| | - Madhukar Trivedi
- Department of Psychiatry, University of Texas Southwestern Medical Center, United States
| | - Myrna Weissman
- Department of Psychiatry, College of Physicians and Surgeons, Columbia University and the New York Psychiatric Institute, United States
| | - Patrick McGrath
- Department of Psychiatry, College of Physicians and Surgeons, Columbia University and the New York Psychiatric Institute, United States
| | - Maurizio Fava
- Department of Psychiatry, Harvard Medical School, United States
| | - Benji Kurian
- Department of Psychiatry, University of Texas Southwestern Medical Center, United States
| | - Crystal Cooper
- Department of Psychiatry, University of Texas Southwestern Medical Center, United States
| | - Melvin McInnis
- Department of Psychiatry, University of Michigan, United States
| | - Maria A. Oquendo
- Department of Psychiatry, University of Pennsylvania, United States
| | | | - Ramin V. Parsey
- Department of Psychiatry, Stony Brook University, Stony Brook, NY, United States
| | - Christine DeLorenzo
- Department of Psychiatry, Stony Brook University, Stony Brook, NY, United States,Department of Psychiatry, Molecular Imaging and Neuropathology Division, Columbia University, New York, NY, United States
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18
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Whitton AE, Webb CA, Dillon DG, Kayser J, Rutherford A, Goer F, Fava M, McGrath P, Weissman M, Parsey R, Adams P, Trombello JM, Cooper C, Deldin P, Oquendo MA, McInnis MG, Carmody T, Bruder G, Trivedi MH, Pizzagalli DA. Pretreatment Rostral Anterior Cingulate Cortex Connectivity With Salience Network Predicts Depression Recovery: Findings From the EMBARC Randomized Clinical Trial. Biol Psychiatry 2019; 85:872-880. [PMID: 30718038 PMCID: PMC6499696 DOI: 10.1016/j.biopsych.2018.12.007] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [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: 08/07/2018] [Revised: 12/06/2018] [Accepted: 12/07/2018] [Indexed: 11/24/2022]
Abstract
BACKGROUND Baseline rostral anterior cingulate cortex (rACC) activity is a well-replicated nonspecific predictor of depression improvement. The rACC is a key hub of the default mode network, which prior studies indicate is hyperactive in major depressive disorder. Because default mode network downregulation is reliant on input from the salience network and frontoparietal network, an important question is whether rACC connectivity with these systems contributes to depression improvement. METHODS Our study evaluated this hypothesis in outpatients (N = 238; 151 female) enrolled in the Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) 8-week randomized clinical trial of sertraline versus placebo for major depressive disorder. Depression severity was measured using the Hamilton Rating Scale for Depression, and electroencephalography was recorded at baseline and week 1. Exact low-resolution electromagnetic tomography was used to compute activity from the rACC, and key regions within the default mode network (posterior cingulate cortex), frontoparietal network (left dorsolateral prefrontal cortex), and salience network (right anterior insula [rAI]). Connectivity in the theta band (4.5-7 Hz) and beta band (12.5-21 Hz) was computed using lagged phase synchronization. RESULTS Stronger baseline theta-band rACC-rAI (salience network hub) connectivity predicted greater depression improvement across 8 weeks of treatment for both treatment arms (B = -0.57, 95% confidence interval = -1.07, -0.08, p = .03). Early increases in theta-band rACC-rAI connectivity predicted greater likelihood of achieving remission at week 8 (odds ratio = 2.90, p = .03). CONCLUSIONS Among patients undergoing treatment, theta-band rACC-rAI connectivity is a prognostic, albeit treatment-nonspecific, indicator of depression improvement, and early connectivity changes may predict clinically meaningful outcomes.
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Affiliation(s)
- Alexis E. Whitton
- Department of Psychiatry, Harvard Medical School, 25 Shattuck Street, Boston, MA 02115,Center for Depression, Anxiety & Stress Research, McLean Hospital, 115 Mill Street, Belmont, MA 02478
| | - Christian A. Webb
- Department of Psychiatry, Harvard Medical School, 25 Shattuck Street, Boston, MA 02115,Center for Depression, Anxiety & Stress Research, McLean Hospital, 115 Mill Street, Belmont, MA 02478
| | - Daniel G. Dillon
- Department of Psychiatry, Harvard Medical School, 25 Shattuck Street, Boston, MA 02115,Center for Depression, Anxiety & Stress Research, McLean Hospital, 115 Mill Street, Belmont, MA 02478
| | - Jürgen Kayser
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, 1051 Riverside Drive, New York, NY 10032
| | - Ashleigh Rutherford
- Department of Psychiatry, Harvard Medical School, 25 Shattuck Street, Boston, MA 02115
| | - Franziska Goer
- Department of Psychiatry, Harvard Medical School, 25 Shattuck Street, Boston, MA 02115
| | - Maurizio Fava
- Department of Psychiatry, Harvard Medical School, 25 Shattuck Street, Boston, MA 02115,Department of Psychiatry, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114
| | - Patrick McGrath
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, 1051 Riverside Drive, New York, NY 10032
| | - Myrna Weissman
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, 1051 Riverside Drive, New York, NY 10032
| | - Ramin Parsey
- Department of Psychiatry, Stony Brook University, Stony Brook, 100 Nicolls Road, Stony Brook, NY 11794
| | - Phil Adams
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, 1051 Riverside Drive, New York, NY 10032
| | - Joseph M. Trombello
- Department of Psychiatry, University of Texas, Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390
| | - Crystal Cooper
- Department of Psychiatry, University of Texas, Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390
| | - Patricia Deldin
- Department of Psychiatry, University of Michigan, 500 S State Street, Ann Arbor, MI 48109
| | - Maria A. Oquendo
- Department of Psychiatry, University of Pennsylvania, Perelman School of Medicine, 3400 Civic Center Blvd, Philadelphia, PA 19104
| | - Melvin G. McInnis
- Department of Psychiatry, University of Michigan, 500 S State Street, Ann Arbor, MI 48109
| | - Thomas Carmody
- Department of Psychiatry, University of Texas, Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390
| | - Gerard Bruder
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, 1051 Riverside Drive, New York, NY 10032
| | - Madhukar H. Trivedi
- Department of Psychiatry, University of Texas, Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390
| | - Diego A. Pizzagalli
- Department of Psychiatry, Harvard Medical School, 25 Shattuck Street, Boston, MA 02115,Center for Depression, Anxiety & Stress Research, McLean Hospital, 115 Mill Street, Belmont, MA 02478
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19
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Webb CA, Trivedi MH, Cohen ZD, Dillon DG, Fournier JC, Goer F, Fava M, McGrath PJ, Weissman M, Parsey R, Adams P, Trombello JM, Cooper C, Deldin P, Oquendo MA, McInnis MG, Huys Q, Bruder G, Kurian BT, Jha M, DeRubeis RJ, Pizzagalli DA. Personalized prediction of antidepressant v. placebo response: evidence from the EMBARC study. Psychol Med 2019; 49:1118-1127. [PMID: 29962359 PMCID: PMC6314923 DOI: 10.1017/s0033291718001708] [Citation(s) in RCA: 66] [Impact Index Per Article: 13.2] [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] [Indexed: 12/23/2022]
Abstract
BACKGROUND Major depressive disorder (MDD) is a highly heterogeneous condition in terms of symptom presentation and, likely, underlying pathophysiology. Accordingly, it is possible that only certain individuals with MDD are well-suited to antidepressants. A potentially fruitful approach to parsing this heterogeneity is to focus on promising endophenotypes of depression, such as neuroticism, anhedonia, and cognitive control deficits. METHODS Within an 8-week multisite trial of sertraline v. placebo for depressed adults (n = 216), we examined whether the combination of machine learning with a Personalized Advantage Index (PAI) can generate individualized treatment recommendations on the basis of endophenotype profiles coupled with clinical and demographic characteristics. RESULTS Five pre-treatment variables moderated treatment response. Higher depression severity and neuroticism, older age, less impairment in cognitive control, and being employed were each associated with better outcomes to sertraline than placebo. Across 1000 iterations of a 10-fold cross-validation, the PAI model predicted that 31% of the sample would exhibit a clinically meaningful advantage [post-treatment Hamilton Rating Scale for Depression (HRSD) difference ⩾3] with sertraline relative to placebo. Although there were no overall outcome differences between treatment groups (d = 0.15), those identified as optimally suited to sertraline at pre-treatment had better week 8 HRSD scores if randomized to sertraline (10.7) than placebo (14.7) (d = 0.58). CONCLUSIONS A subset of MDD patients optimally suited to sertraline can be identified on the basis of pre-treatment characteristics. This model must be tested prospectively before it can be used to inform treatment selection. However, findings demonstrate the potential to improve individual outcomes through algorithm-guided treatment recommendations.
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Affiliation(s)
| | | | | | | | | | | | - Maurizio Fava
- Harvard Medical School – Massachusetts General Hospital, Boston, MA
| | - Patrick J. McGrath
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY
| | - Myrna Weissman
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY
| | | | - Phil Adams
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY
| | | | - Crystal Cooper
- University of Texas, Southwestern Medical Center, Dallas, TX
| | | | | | | | | | - Gerard Bruder
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY
| | - Benji T. Kurian
- University of Texas, Southwestern Medical Center, Dallas, TX
| | - Manish Jha
- University of Texas, Southwestern Medical Center, Dallas, TX
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20
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Cooper CM, Chin Fatt CR, Jha M, Fonzo GA, Grannemann BD, Carmody T, Ali A, Aslan S, Almeida JR, Deckersbach T, Fava M, Kurian BT, McGrath PJ, McInnis M, Parsey RV, Weissman M, Phillips ML, Lu H, Etkin A, Trivedi MH. Cerebral Blood Perfusion Predicts Response to Sertraline versus Placebo for Major Depressive Disorder in the EMBARC Trial. EClinicalMedicine 2019; 10:32-41. [PMID: 31193824 PMCID: PMC6543260 DOI: 10.1016/j.eclinm.2019.04.007] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Revised: 04/10/2019] [Accepted: 04/11/2019] [Indexed: 01/14/2023] Open
Abstract
BACKGROUND Major Depressive Disorder (MDD) has been associated with brain-related changes. However, biomarkers have yet to be defined that could "accurately" identify antidepressant-responsive patterns and reduce the trial-and-error process in treatment selection. Cerebral blood perfusion, as measured by Arterial Spin Labelling (ASL), has been used to understand resting-state brain function, detect abnormalities in MDD, and could serve as a marker for treatment selection. As part of a larger trial to identify predictors of treatment outcome, the current investigation aimed to identify perfusion predictors of treatment response in MDD. METHODS For this secondary analysis, participants include 231 individuals with MDD from the EMBARC study, a randomised, placebo-controlled trial investigating clinical, behavioural, and biological predictors of antidepressant response. Participants received sertraline (n = 114) or placebo (n = 117) and response was monitored for 8 weeks. Pre-treatment neuroimaging was completed, including ASL. A whole-brain, voxel-wise linear mixed-effects model was conducted to identify brain regions in which perfusion levels differentially predict (moderate) treatment response. Clinical effectiveness of perfusion moderators was investigated by composite moderator analysis and remission rates. Composite moderator analysis combined the effect of individual perfusion moderators and identified which contribute to sertraline or placebo as the "preferred" treatment. Remission rates were calculated for participants "accurately" treated based on the composite moderator (lucky) versus "inaccurately" treated (unlucky). FINDINGS Perfusion levels in multiple brain regions differentially predicted improvement with sertraline over placebo. Of these regions, perfusion in the putamen and anterior insula, inferior temporal gyrus, fusiform, parahippocampus, inferior parietal lobule, and orbital frontal gyrus contributed to sertraline response. Remission rates increased from 37% for all those who received sertraline to 53% for those who were lucky to have received it and sertraline was their perfusion-preferred treatment. INTERPRETATION This large study showed that perfusion patterns in brain regions involved with reward, salience, affective, and default mode processing moderate treatment response favouring sertraline over placebo. Accurately matching patients with defined perfusion patterns could significantly increase remission rates. FUNDING National Institute of Mental Health, the Hersh Foundation, and the Center for Depression Research and Clinical Care, Peter O'Donnell Brain Institute at UT Southwestern Medical Center.Trial Registration.Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMARC) Registration Number: NCT01407094 (https://clinicaltrials.gov/ct2/show/NCT01407094).
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Affiliation(s)
- Crystal M. Cooper
- Department of Psychiatry, University of Texas Southwestern Medical Center, United States of America
| | - Cherise R. Chin Fatt
- Department of Psychiatry, University of Texas Southwestern Medical Center, United States of America
| | - Manish Jha
- Department of Psychiatry, University of Texas Southwestern Medical Center, United States of America
| | - Gregory A. Fonzo
- Department of Psychiatry and behavioural Sciences, Stanford University School of Medicine, United States of America
- Stanford Neurosciences Institute, Stanford University, United States of America
- Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Veterans Affairs Palo Alto Healthcare System, United States of America
| | - Bruce D. Grannemann
- Department of Psychiatry, University of Texas Southwestern Medical Center, United States of America
| | - Thomas Carmody
- Department of Psychiatry, University of Texas Southwestern Medical Center, United States of America
| | - Aasia Ali
- Department of Psychiatry, University of Texas Southwestern Medical Center, United States of America
| | - Sina Aslan
- Department of Psychiatry, University of Texas Southwestern Medical Center, United States of America
- Advance MRI, LLC, United States of America
| | - Jorge R.C. Almeida
- Department of Psychiatry, University of Texas Austin, United States of America
| | - Thilo Deckersbach
- Department of Psychiatry, Massachusetts General Hospital, United States of America
| | - Maurizio Fava
- Department of Psychiatry, Massachusetts General Hospital, United States of America
| | - Benji T. Kurian
- Department of Psychiatry, University of Texas Southwestern Medical Center, United States of America
| | - Patrick J. McGrath
- Department of Psychiatry, Columbia University, New York State Psychiatric Institute, United States of America
| | - Melvin McInnis
- Department of Psychiatry, University of Michigan School of Medicine, United States of America
| | - Ramin V. Parsey
- Departments of Psychiatry, Stony Brook University, United States of America
| | - Myrna Weissman
- Department of Psychiatry, Columbia University, New York State Psychiatric Institute, United States of America
| | - Mary L. Phillips
- Department of Psychiatry, University of Pittsburgh School of Medicine, United States of America
| | - Hanzhang Lu
- Department of Psychiatry, University of Texas Southwestern Medical Center, United States of America
- Department of Radiology, Johns Hopkins University, United States of America
| | - Amit Etkin
- Department of Psychiatry and behavioural Sciences, Stanford University School of Medicine, United States of America
- Stanford Neurosciences Institute, Stanford University, United States of America
- Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Veterans Affairs Palo Alto Healthcare System, United States of America
| | - Madhukar H. Trivedi
- Department of Psychiatry, University of Texas Southwestern Medical Center, United States of America
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21
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Li X, Weissman M, Talati A, Svob C, Wickramaratne P, Posner J, Xu D. A diffusion tensor imaging study of brain microstructural changes related to religion and spirituality in families at high risk for depression. Brain Behav 2019; 9:e01209. [PMID: 30648349 PMCID: PMC6379589 DOI: 10.1002/brb3.1209] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [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: 08/06/2018] [Revised: 12/11/2018] [Accepted: 12/13/2018] [Indexed: 01/22/2023] Open
Abstract
INTRODUCTION Previously in a three-generation study of families at high risk for depression, we found that belief in the importance of religion/spirituality (R/S) was associated with thicker cortex in bilateral parietal and occipital regions. In the same sample using functional magnetic resonance imaging and electroencephalograph (EEG), we found that offspring at high familial risk had thinner cortices, increased default mode network connectivity, and reduced EEG power. These group differences were significantly diminished in offspring at high risk who reported high importance of R/S beliefs, suggesting a protective effect. METHODS This study extends previous work examining brain microstructural differences associated with risk for major depressive disorder (MDD) and tests whether these are normalized in at-risk offspring who report high importance of R/S beliefs. Diffusion tensor imaging (DTI) data were selected from 99 2nd and 3rd generation offspring of 1st generation depressed (high-risk, HR) or nondepressed (low-risk, LR) parents. Whole-brain and region-of-interest analyses were performed, using ellipsoidal area ratio (EAR, an alternative diffusion anisotropy index comparable to fractional anisotropy). We examined microstructural differences associated with familial risk for depression within the groups of high and low importance of R/S beliefs (HI, LI). RESULTS In the LI group, HR individuals showed significantly decreased EAR in white matter regions neighboring the precuneus, superior parietal lobe, superior and middle frontal gyrus, and bilateral insula, supplementary motor area, and postcentral gyrus. In the HI group, HR individuals showed reduced EAR in white matter surrounding the left superior, and middle frontal gyrus, left superior parietal lobule, and right supplementary motor area. Microstructural differences associated with familial risk for depression in precuneus, frontal lobe, and temporal lobe were nonsignificant or less significant in the HI group. CONCLUSION R/S beliefs may affect microstructure in brain regions associated with R/S, potentially conferring resilience to depression among HR individuals.
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Affiliation(s)
- Xuzhou Li
- East China Normal University, Shanghai, China.,Department of Psychiatry, Columbia University, New York, New York.,New York State Psychiatry Institute, New York, New York
| | - Myrna Weissman
- Department of Psychiatry, Columbia University, New York, New York.,New York State Psychiatry Institute, New York, New York
| | - Ardesheer Talati
- Department of Psychiatry, Columbia University, New York, New York.,New York State Psychiatry Institute, New York, New York
| | - Connie Svob
- Department of Psychiatry, Columbia University, New York, New York.,New York State Psychiatry Institute, New York, New York
| | - Priya Wickramaratne
- Department of Psychiatry, Columbia University, New York, New York.,New York State Psychiatry Institute, New York, New York
| | - Jonathan Posner
- Department of Psychiatry, Columbia University, New York, New York.,New York State Psychiatry Institute, New York, New York
| | - Dongrong Xu
- Department of Psychiatry, Columbia University, New York, New York.,New York State Psychiatry Institute, New York, New York
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22
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Bartlett EA, DeLorenzo C, Sharma P, Yang J, Zhang M, Petkova E, Weissman M, McGrath PJ, Fava M, Ogden RT, Kurian BT, Malchow A, Cooper CM, Trombello JM, McInnis M, Adams P, Oquendo MA, Pizzagalli DA, Trivedi M, Parsey RV. Pretreatment and early-treatment cortical thickness is associated with SSRI treatment response in major depressive disorder. Neuropsychopharmacology 2018; 43:2221-2230. [PMID: 29955151 PMCID: PMC6135779 DOI: 10.1038/s41386-018-0122-9] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [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: 01/16/2018] [Revised: 05/30/2018] [Accepted: 06/11/2018] [Indexed: 12/19/2022]
Abstract
To date, there are no biomarkers for major depressive disorder (MDD) treatment response in clinical use. Such biomarkers could allow for individualized treatment selection, reducing time spent on ineffective treatments and the burden of MDD. In search of such a biomarker, multisite pretreatment and early-treatment (1 week into treatment) structural magnetic resonance (MR) images were acquired from 184 patients with MDD randomized to an 8-week trial of the selective serotonin reuptake inhibitor (SSRI) sertraline or placebo. This study represents a large, multisite, placebo-controlled effort to examine the association between pretreatment differences or early-treatment changes in cortical thickness and treatment-specific outcomes. For standardization, a novel, robust site harmonization procedure was applied to structural measures in a priori regions (rostral and caudal anterior cingulate, lateral orbitofrontal, rostral middle frontal, and hippocampus), chosen based on previously published reports. Pretreatment cortical thickness or volume did not significantly associate with SSRI response. Thickening of the rostral anterior cingulate cortex in the first week of treatment was associated with better 8-week responses to SSRI (p = 0.010). These findings indicate that frontal lobe structural alterations in the first week of treatment may be associated with long-term treatment efficacy. While these associational findings may help to elucidate the specific neural targets of SSRIs, the predictive accuracy of pretreatment or early-treatment structural alterations in classifying treatment remitters from nonremitters was limited to 63.9%. Therefore, in this large sample of adults with MDD, structural MR imaging measures were not found to be clinically translatable biomarkers of treatment response to SSRI or placebo.
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Affiliation(s)
- Elizabeth A. Bartlett
- 0000 0001 2216 9681grid.36425.36Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY USA
| | - Christine DeLorenzo
- 0000 0001 2216 9681grid.36425.36Department of Psychiatry, Stony Brook University, Stony Brook, NY USA
| | - Priya Sharma
- 0000 0001 2216 9681grid.36425.36Department of Psychiatry, Stony Brook University, Stony Brook, NY USA
| | - Jie Yang
- 0000 0001 2216 9681grid.36425.36Department of Family, Population, and Preventive Medicine, Stony Brook University, Stony Brook, NY USA
| | - Mengru Zhang
- 0000 0001 2216 9681grid.36425.36Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY USA
| | - Eva Petkova
- 0000 0001 2109 4251grid.240324.3Department of Child & Adolescent Psychiatry, Department of Population Health, New York University Langone Medical Center, NY, NY USA
| | - Myrna Weissman
- 0000000419368729grid.21729.3fDepartment of Psychiatry, Columbia University College of Physicians & Surgeons and New York State Psychiatric Institute, NY, NY USA
| | - Patrick J. McGrath
- 0000000419368729grid.21729.3fDepartment of Psychiatry, Columbia University College of Physicians & Surgeons and New York State Psychiatric Institute, NY, NY USA
| | - Maurizio Fava
- 0000 0004 0386 9924grid.32224.35Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
| | - R. Todd Ogden
- 0000000419368729grid.21729.3fDepartment of Biostatistics, Columbia University, NY, NY USA
| | - Benji T. Kurian
- 0000 0000 9482 7121grid.267313.2Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX USA
| | - Ashley Malchow
- 0000 0000 9482 7121grid.267313.2Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX USA
| | - Crystal M. Cooper
- 0000 0000 9482 7121grid.267313.2Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX USA
| | - Joseph M. Trombello
- 0000 0000 9482 7121grid.267313.2Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX USA
| | - Melvin McInnis
- 0000000086837370grid.214458.eDepartment of Psychiatry, University of Michigan, Ann Arbor, MI USA
| | - Phillip Adams
- 0000000419368729grid.21729.3fDepartment of Psychiatry, Columbia University College of Physicians & Surgeons and New York State Psychiatric Institute, NY, NY USA
| | - Maria A. Oquendo
- 0000 0004 1936 8972grid.25879.31Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Diego A. Pizzagalli
- 000000041936754Xgrid.38142.3cDepartment of Psychiatry, Harvard Medical School, Boston, MA USA
| | - Madhukar Trivedi
- 0000 0000 9482 7121grid.267313.2Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX USA
| | - Ramin V. Parsey
- 0000 0001 2216 9681grid.36425.36Department of Psychiatry, Stony Brook University, Stony Brook, NY USA
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23
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Yang J, Zhang M, Ahn H, Zhang Q, Jin TB, Li I, Nemesure M, Joshi N, Jiang H, Miller JM, Ogden RT, Petkova E, Milak MS, Sublette ME, Sullivan GM, Trivedi MH, Weissman M, McGrath PJ, Fava M, Kurian BT, Pizzagalli DA, Cooper CM, McInnis M, Oquendo MA, Mann JJ, Parsey RV, DeLorenzo C. Development and evaluation of a multimodal marker of major depressive disorder. Hum Brain Mapp 2018; 39:4420-4439. [PMID: 30113112 DOI: 10.1002/hbm.24282] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 05/16/2018] [Accepted: 06/04/2018] [Indexed: 12/30/2022] Open
Abstract
This study aimed to identify biomarkers of major depressive disorder (MDD), by relating neuroimage-derived measures to binary (MDD/control), ordinal (severe MDD/mild MDD/control), or continuous (depression severity) outcomes. To address MDD heterogeneity, factors (severity of psychic depression, motivation, anxiety, psychosis, and sleep disturbance) were also used as outcomes. A multisite, multimodal imaging (diffusion MRI [dMRI] and structural MRI [sMRI]) cohort (52 controls and 147 MDD patients) and several modeling techniques-penalized logistic regression, random forest, and support vector machine (SVM)-were used. An additional cohort (25 controls and 83 MDD patients) was used for validation. The optimally performing classifier (SVM) had a 26.0% misclassification rate (binary), 52.2 ± 1.69% accuracy (ordinal) and r = .36 correlation coefficient (p < .001, continuous). Using SVM, R2 values for prediction of any MDD factors were <10%. Binary classification in the external data set resulted in 87.95% sensitivity and 32.00% specificity. Though observed classification rates are too low for clinical utility, four image-based features contributed to accuracy across all models and analyses-two dMRI-based measures (average fractional anisotropy in the right cuneus and left insula) and two sMRI-based measures (asymmetry in the volume of the pars triangularis and the cerebellum) and may serve as a priori regions for future analyses. The poor accuracy of classification and predictive results found here reflects current equivocal findings and sheds light on challenges of using these modalities for MDD biomarker identification. Further, this study suggests a paradigm (e.g., multiple classifier evaluation with external validation) for future studies to avoid nongeneralizable results.
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Affiliation(s)
- Jie Yang
- Department of Family, Population and Preventive Medicine, Stony Brook University, New York, New York
| | - Mengru Zhang
- Department of Applied Mathematics and Statistics, Stony Brook University, New York, New York
| | - Hongshik Ahn
- Department of Applied Mathematics and Statistics, Stony Brook University, New York, New York
| | - Qing Zhang
- Department of Applied Mathematics and Statistics, Stony Brook University, New York, New York
| | - Tony B Jin
- Department of Psychiatry, Stony Brook University, New York, New York
| | - Ien Li
- Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey
| | - Matthew Nemesure
- Integrative Neuroscience Program, Binghamton University, Binghamton, New York
| | - Nandita Joshi
- Department of Electrical and Computer Engineering, Stony Brook University, New York, New York
| | - Haoran Jiang
- Department of Applied Mathematics and Statistics, Stony Brook University, New York, New York
| | - Jeffrey M Miller
- Department of Psychiatry, Columbia University, New York, New York
| | | | - Eva Petkova
- Department of Child & Adolescent Psychiatry, Department of Population Health, New York University, New York, New York
| | - Matthew S Milak
- Department of Psychiatry, Columbia University, New York, New York
| | | | - Gregory M Sullivan
- Chief Medical Officer, Clinical Research and Development program, Tonix Pharmaceuticals, Inc., New York, New York
| | - Madhukar H Trivedi
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Myrna Weissman
- Department of Psychiatry, Columbia University, New York, New York
| | | | - Maurizio Fava
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
| | - Benji T Kurian
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | | | - Crystal M Cooper
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Melvin McInnis
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan
| | - Maria A Oquendo
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Joseph John Mann
- Department of Psychiatry, Columbia University, New York, New York
| | - Ramin V Parsey
- Department of Psychiatry, Stony Brook University, New York, New York
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24
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Pizzagalli DA, Webb CA, Dillon DG, Tenke CE, Kayser J, Goer F, Fava M, McGrath P, Weissman M, Parsey R, Adams P, Trombello J, Cooper C, Deldin P, Oquendo MA, McInnis MG, Carmody T, Bruder G, Trivedi MH. Pretreatment Rostral Anterior Cingulate Cortex Theta Activity in Relation to Symptom Improvement in Depression: A Randomized Clinical Trial. JAMA Psychiatry 2018; 75:547-554. [PMID: 29641834 PMCID: PMC6083825 DOI: 10.1001/jamapsychiatry.2018.0252] [Citation(s) in RCA: 101] [Impact Index Per Article: 16.8] [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: 01/18/2023]
Abstract
IMPORTANCE Major depressive disorder (MDD) remains challenging to treat. Although several clinical and demographic variables have been found to predict poor antidepressant response, these markers have not been robustly replicated to warrant implementation in clinical care. Increased pretreatment rostral anterior cingulate cortex (rACC) theta activity has been linked to better antidepressant outcomes. However, no prior study has evaluated whether this marker has incremental predictive validity over clinical and demographic measures. OBJECTIVE To determine whether increased pretreatment rACC theta activity would predict symptom improvement regardless of randomization arm. DESIGN, SETTING, AND PARTICIPANTS A multicenter randomized clinical trial enrolled outpatients without psychosis and with chronic or recurrent MDD between July 29, 2011, and December 15, 2015 (Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care [EMBARC]). Patients were consecutively recruited from 4 university hospitals: 634 patients were screened, 296 were randomized to receive sertraline hydrochloride or placebo, 266 had electroencephalographic (EEG) recordings, and 248 had usable EEG data. Resting EEG data were recorded at baseline and 1 week after trial onset, and rACC theta activity was extracted using source localization. Intent-to-treat analysis was conducted. Data analysis was performed from October 7, 2016, to January 19, 2018. INTERVENTIONS An 8-week course of sertraline or placebo. MAIN OUTCOMES AND MEASURES The 17-item Hamilton Rating Scale for Depression score (assessed at baseline and weeks 1, 2, 3, 4, 6, and 8). RESULTS The 248 participants (160 [64.5%] women, 88 [35.5%] men) with usable EEG data had a mean (SD) age of 36.75 (13.15) years. Higher rACC theta activity at both baseline (b = -1.05; 95% CI, -1.77 to -0.34; P = .004) and week 1 (b = -0.83; 95% CI, -1.60 to -0.06; P < .04) predicted greater depressive symptom improvement, even when controlling for clinical and demographic variables previously linked with treatment outcome. These effects were not moderated by treatment arm. The rACC theta marker, in combination with clinical and demographic variables, accounted for an estimated 39.6% of the variance in symptom change (with 8.5% of the variance uniquely attributable to the rACC theta marker). CONCLUSIONS AND RELEVANCE Increased pretreatment rACC theta activity represents a nonspecific prognostic marker of treatment outcome. This is the first study to date to demonstrate that rACC theta activity has incremental predictive validity. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT01407094.
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Affiliation(s)
- Diego A. Pizzagalli
- Department of Psychiatry, Harvard Medical School, McLean Hospital, Belmont, Massachusetts
| | - Christian A. Webb
- Department of Psychiatry, Harvard Medical School, McLean Hospital, Belmont, Massachusetts
| | - Daniel G. Dillon
- Department of Psychiatry, Harvard Medical School, McLean Hospital, Belmont, Massachusetts
| | - Craig E. Tenke
- Department of Psychiatry, New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York
| | - Jürgen Kayser
- Department of Psychiatry, New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York
| | - Franziska Goer
- Department of Psychiatry, Harvard Medical School, McLean Hospital, Belmont, Massachusetts
| | - Maurizio Fava
- Department of Psychiatry, Harvard Medical School, Massachusetts General Hospital, Boston
| | - Patrick McGrath
- Department of Psychiatry, New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York
| | - Myrna Weissman
- Department of Psychiatry, New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York
| | - Ramin Parsey
- Department of Psychiatry, Stony Brook University, Stony Brook, New York
| | - Phil Adams
- Department of Psychiatry, New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York
| | - Joseph Trombello
- Department of Psychiatry, University of Texas, Southwestern Medical Center, Dallas
| | - Crystal Cooper
- Department of Psychiatry, University of Texas, Southwestern Medical Center, Dallas
| | | | - Maria A. Oquendo
- Department of Psychiatry, University of Pennsylvania, Perelman School of Medicine, Philadelphia
| | | | - Thomas Carmody
- Department of Psychiatry, University of Texas, Southwestern Medical Center, Dallas
| | - Gerard Bruder
- Department of Psychiatry, New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York
| | - Madhukar H. Trivedi
- Department of Psychiatry, University of Texas, Southwestern Medical Center, Dallas
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25
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Lugo-Candelas C, Cha J, Hong S, Bastidas V, Weissman M, Fifer WP, Myers M, Talati A, Bansal R, Peterson BS, Monk C, Gingrich JA, Posner J. Associations Between Brain Structure and Connectivity in Infants and Exposure to Selective Serotonin Reuptake Inhibitors During Pregnancy. JAMA Pediatr 2018; 172:525-533. [PMID: 29630692 PMCID: PMC6137537 DOI: 10.1001/jamapediatrics.2017.5227] [Citation(s) in RCA: 78] [Impact Index Per Article: 13.0] [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: 11/14/2022]
Abstract
IMPORTANCE Selective serotonin reuptake inhibitor (SSRI) use among pregnant women is increasing, yet the association between prenatal SSRI exposure and fetal neurodevelopment is poorly understood. Animal studies show that perinatal SSRI exposure alters limbic circuitry and produces anxiety and depressive-like behaviors after adolescence, but literature on prenatal SSRI exposure in humans is limited and mixed. OBJECTIVE To examine associations between prenatal SSRI exposure and brain development using structural and diffusion magnetic resonance imaging (MRI). DESIGN, SETTING, AND PARTICIPANTS A cohort study conducted at Columbia University Medical Center and New York State Psychiatric Institute included 98 infants: 16 with in utero SSRI exposure, 21 with in utero untreated maternal depression exposure, and 61 healthy controls. Data were collected between January 6, 2011, and October 25, 2016. EXPOSURES Selective serotonin reuptake inhibitors and untreated maternal depression. MAIN OUTCOMES AND MEASURES Gray matter volume estimates using structural MRI with voxel-based morphometry and white matter structural connectivity (connectome) using diffusion MRI with probabilistic tractography. RESULTS The sample included 98 mother (31 [32%] white, 26 [27%] Hispanic/Latina, 26 [27%] black/African American, 15 [15%] other) and infant (46 [47%] boys, 52 [53%] girls) dyads. Mean (SD) age of the infants at the time of the scan was 3.43 (1.50) weeks. Voxel-based morphometry showed significant gray matter volume expansion in the right amygdala (Cohen d = 0.65; 95% CI, 0.06-1.23) and right insula (Cohen d = 0.86; 95% CI, 0.26-1.14) in SSRI-exposed infants compared with both healthy controls and infants exposed to untreated maternal depression (P < .05; whole-brain correction). In connectome-level analysis of white matter structural connectivity, the SSRI group showed a significant increase in connectivity between the right amygdala and the right insula with a large effect size (Cohen d = 0.99; 95% CI, 0.40-1.57) compared with healthy controls and untreated depression (P < .05; whole connectome correction). CONCLUSIONS AND RELEVANCE Our findings suggest that prenatal SSRI exposure has an association with fetal brain development, particularly in brain regions critical to emotional processing. The study highlights the need for further research on the potential long-term behavioral and psychological outcomes of these neurodevelopmental changes.
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Affiliation(s)
- Claudia Lugo-Candelas
- Department of Psychiatry, Columbia University Medical Center, New York, New York,New York State Psychiatric Institute, New York
| | - Jiook Cha
- Department of Psychiatry, Columbia University Medical Center, New York, New York,New York State Psychiatric Institute, New York
| | - Susie Hong
- Department of Psychiatry, Columbia University Medical Center, New York, New York,New York State Psychiatric Institute, New York
| | - Vanessa Bastidas
- Department of Psychiatry, Columbia University Medical Center, New York, New York,New York State Psychiatric Institute, New York
| | - Myrna Weissman
- Department of Psychiatry, Columbia University Medical Center, New York, New York,New York State Psychiatric Institute, New York,Sackler Institute for Developmental Psychobiology, Columbia University Medical Center, New York, New York
| | - William P. Fifer
- Department of Psychiatry, Columbia University Medical Center, New York, New York,New York State Psychiatric Institute, New York,Sackler Institute for Developmental Psychobiology, Columbia University Medical Center, New York, New York
| | - Michael Myers
- Department of Psychiatry, Columbia University Medical Center, New York, New York,New York State Psychiatric Institute, New York,Sackler Institute for Developmental Psychobiology, Columbia University Medical Center, New York, New York
| | - Ardesheer Talati
- Department of Psychiatry, Columbia University Medical Center, New York, New York,New York State Psychiatric Institute, New York,Sackler Institute for Developmental Psychobiology, Columbia University Medical Center, New York, New York
| | - Ravi Bansal
- Department of Pediatrics, Keck School of Medicine, Los Angeles, California,Department of Psychiatry, Institute for the Developing Mind, Los Angeles, California
| | - Bradley S. Peterson
- Department of Pediatrics, Keck School of Medicine, Los Angeles, California,Department of Psychiatry, Institute for the Developing Mind, Los Angeles, California
| | - Catherine Monk
- Department of Psychiatry, Columbia University Medical Center, New York, New York,New York State Psychiatric Institute, New York,Sackler Institute for Developmental Psychobiology, Columbia University Medical Center, New York, New York
| | - Jay A. Gingrich
- Department of Psychiatry, Columbia University Medical Center, New York, New York,New York State Psychiatric Institute, New York,Sackler Institute for Developmental Psychobiology, Columbia University Medical Center, New York, New York
| | - Jonathan Posner
- Department of Psychiatry, Columbia University Medical Center, New York, New York,New York State Psychiatric Institute, New York,Sackler Institute for Developmental Psychobiology, Columbia University Medical Center, New York, New York
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26
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Trivedi MH, South C, Jha MK, Rush AJ, Cao J, Kurian B, Phillips M, Pizzagalli DA, Trombello JM, Oquendo MA, Cooper C, Dillon DG, Webb C, Grannemann BD, Bruder G, McGrath PJ, Parsey R, Weissman M, Fava M. A Novel Strategy to Identify Placebo Responders: Prediction Index of Clinical and Biological Markers in the EMBARC Trial. Psychother Psychosom 2018; 87:285-295. [PMID: 30110685 PMCID: PMC9764260 DOI: 10.1159/000491093] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Accepted: 06/15/2018] [Indexed: 11/19/2022]
Abstract
BACKGROUND One in three clinical trial patients with major depressive disorder report symptomatic improvement with placebo. Strategies to mitigate the effect of placebo responses have focused on modifying study design with variable success. Identifying and excluding or controlling for individuals with a high likelihood of responding to placebo may improve clinical trial efficiency and avoid unnecessary medication trials. METHODS Participants included those assigned to the placebo arm (n = 141) of the Establishing Moderators and Biosignatures for Antidepressant Response in Clinical Care (EMBARC) trial. The elastic net was used to evaluate 283 baseline clinical, behavioral, imaging, and electrophysiological variables to identify the most robust yet parsimonious features that predicted depression severity at the end of the double-blind 8-week trial. Variables retained in at least 50% of the 100 imputed data sets were used in a Bayesian multiple linear regression model to simultaneously predict the probabilities of response and remission. RESULTS Lower baseline depression severity, younger age, absence of melancholic features or history of physical abuse, less anxious arousal, less anhedonia, less neuroticism, and higher average theta current density in the rostral anterior cingulate predicted a higher likelihood of improvement with placebo. The Bayesian model predicted remission and response with an actionable degree of accuracy (both AUC > 0.73). An interactive calculator was developed predicting the likelihood of placebo response at the individual level. CONCLUSION Easy-to-measure clinical, behavioral, and electrophysiological assessments can be used to identify placebo responders with a high degree of accuracy. Development of this calculator based on these findings can be used to identify potential placebo responders.
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Affiliation(s)
- Madhukar H. Trivedi
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Charles South
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Manish K. Jha
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - A. John Rush
- Duke-National University of Singapore, Singapore, Singapore;,Duke Medical School, Durham, NC, USA;,Texas Tech University Health Sciences Center, Permian Basin, TX, USA
| | - Jing Cao
- Department of Statistical Science, Southern Methodist University, Dallas, TX, USA
| | - Benji Kurian
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Mary Phillips
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA;,Columbia University, New York, NY, USA
| | - Diego A. Pizzagalli
- Center for Depression, Anxiety and Stress Research, Mclean Hospital, Belmont, MA, USA
| | - Joseph M. Trombello
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Maria A. Oquendo
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Crystal Cooper
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Daniel G. Dillon
- Center for Depression, Anxiety and Stress Research, Mclean Hospital, Belmont, MA, USA
| | - Christian Webb
- Center for Depression, Anxiety and Stress Research, Mclean Hospital, Belmont, MA, USA
| | - Bruce D. Grannemann
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Gerard Bruder
- New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons, New York, NY, USA
| | - Patrick J. McGrath
- New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons, New York, NY, USA
| | - Ramin Parsey
- Stony Brook University School of Medicine, Stony Brook, NY, USA
| | - Myrna Weissman
- New York State Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons, New York, NY, USA
| | - Maurizio Fava
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
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Almeida JRC, Greenberg T, Lu H, Chase HW, Fournier JC, Cooper CM, Deckersbach T, Adams P, Carmody T, Fava M, Kurian B, McGrath PJ, McInnis MG, Oquendo MA, Parsey R, Weissman M, Trivedi M, Phillips ML. Test-retest reliability of cerebral blood flow in healthy individuals using arterial spin labeling: Findings from the EMBARC study. Magn Reson Imaging 2017; 45:26-33. [PMID: 28888770 DOI: 10.1016/j.mri.2017.09.004] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2016] [Revised: 03/17/2017] [Accepted: 09/01/2017] [Indexed: 12/20/2022]
Abstract
INTRODUCTION Previous investigations of test-retest reliability of cerebral blood flow (CBF) at rest measured with pseudo-continuous Arterial Spin Labeling (pCASL) demonstrated good reliability, but are limited by the use of similar scanner platforms. In the present study we examined test-retest reliability of CBF in regions implicated in emotion and the default mode network. MATERIAL AND METHODS We measured absolute and relative CBF at rest in thirty-one healthy subjects in two scan sessions, one week apart, at four different sites and three different scan platforms. We derived CBF from pCASL images with an automated algorithm and calculated intra-class correlation coefficients (ICCs) across sessions for regions of interest. In addition, we investigated site effects. RESULTS For both absolute and relative CBF measures, ICCs were good to excellent (i.e. >0.6) in most brain regions, with highest values observed for the subgenual anterior cingulate cortex and ventral striatum. A leave-one-site-out cross validation analysis did not show a significant effect for site on whole brain CBF and there was no proportional bias across sites. However, a significant site effect was present in the repeated measures ANOVA. CONCLUSIONS The high test-retest reliability of CBF measured with pCASL in a range of brain regions implicated in emotion and salience processing, emotion regulation, and the default mode network, which have been previously linked to depression symptomatology supports its use in studies that aim to identify neuroimaging biomarkers of treatment response.
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Affiliation(s)
- Jorge R C Almeida
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA; Department of Psychiatry, Brown University School of Medicine, Providence, RI 02906, USA; Departments of Psychiatry, Dell Medical School, University of Texas at Austin, Austin, TX 78712, USA.
| | - Tsafrir Greenberg
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Hanzhang Lu
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX 75235, USA
| | - Henry W Chase
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Jay C Fournier
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Crystal M Cooper
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX 75235, USA
| | - Thilo Deckersbach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Phil Adams
- Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX 75235, USA
| | - Thomas Carmody
- Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX 75235, USA
| | - Maurizio Fava
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Benji Kurian
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX 75235, USA
| | - Patrick J McGrath
- Department of Psychiatry, Columbia University College of Physicians and Surgeons and the New York State Psychiatric Institute, New York, NY 10032, USA
| | - Melvin G McInnis
- Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor, MI 48109, USA
| | - Maria A Oquendo
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104-3309, USA
| | - Ramin Parsey
- Departments of Psychiatry & Radiology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Myrna Weissman
- Department of Psychiatry, Columbia University College of Physicians and Surgeons and the New York State Psychiatric Institute, New York, NY 10032, USA
| | - Madhukar Trivedi
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX 75235, USA
| | - Mary L Phillips
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
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Perlman G, Bartlett E, DeLorenzo C, Weissman M, McGrath P, Ogden T, Jin T, Adams P, Trivedi M, Kurian B, Oquendo M, McInnis M, Weyandt S, Fava M, Cooper C, Malchow A, Parsey R. Cortical thickness is not associated with current depression in a clinical treatment study. Hum Brain Mapp 2017; 38:4370-4385. [PMID: 28594150 DOI: 10.1002/hbm.23664] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2016] [Revised: 05/13/2017] [Accepted: 05/16/2017] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Reduced cortical thickness is a candidate biological marker of depression, although findings are inconsistent. This could reflect analytic heterogeneity, such as use of region-wise cortical thickness based on the Freesurfer Desikan-Killiany (DK) atlas or surface-based morphometry (SBM). The Freesurfer Destrieux (DS) atlas (more, smaller regions) has not been utilized in depression studies. This could also reflect differential gender and age effects. METHODS Cortical thickness was collected from 170 currently depressed adults and 52 never-depressed adults. Visually inspected and approved Freesurfer-generated surfaces were used to extract cortical thickness estimates according to the DK atlas (68 regions) and DS atlas (148 regions) for region-wise analysis (216 total regions) and for SBM. RESULTS Overall, except for small effects in a few regions, the two region-wise approaches generally failed to discriminate depressed adults from nondepressed adults or current episode severity. Differential effects by age and gender were also rare and small in magnitude. Using SBM, depressed adults showed a significantly thicker cluster in the left supramarginal gyrus than nondepressed adults (P = 0.047) but there were no associations with current episode severity. CONCLUSIONS Three analytic approaches (i.e., DK atlas, DS atlas, and SBM) converge on the notion that cortical thickness is a relatively weak discriminator of current depression status. Differential age and gender effects do not appear to represent key moderators. Robust associations with demographic factors will likely hinder translation of cortical thickness into a clinically useful biomarker. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc. Hum Brain Mapp 38:4370-4385, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Greg Perlman
- Department of Psychiatry, Stony Brook University, Stony Brook, New York
| | - Elizabeth Bartlett
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York
| | | | - Myrna Weissman
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY, USA
| | - Patrick McGrath
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY, USA
| | - Todd Ogden
- Department of Biostatistics, Mailman School of Public Health, Columbia University
| | - Tony Jin
- Department of Psychiatry, Stony Brook University, Stony Brook, New York
| | - Phillip Adams
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY, USA
| | - Madhukar Trivedi
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Benji Kurian
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Maria Oquendo
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY, USA
| | - Melvin McInnis
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan
| | - Sarah Weyandt
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Maurizio Fava
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
| | - Crystal Cooper
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Ashley Malchow
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Ramin Parsey
- Department of Psychiatry, Stony Brook University, Stony Brook, New York
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Petkova E, Ogden RT, Tarpey T, Ciarleglio A, Jiang B, Su Z, Carmody T, Adams P, Kraemer HC, Grannemann BD, Oquendo MA, Parsey R, Weissman M, McGrath PJ, Fava M, Trivedi MH. Statistical Analysis Plan for Stage 1 EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care) Study. Contemp Clin Trials Commun 2017; 6:22-30. [PMID: 28670629 PMCID: PMC5485858 DOI: 10.1016/j.conctc.2017.02.007] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2016] [Revised: 02/08/2017] [Accepted: 02/13/2017] [Indexed: 12/28/2022] Open
Abstract
Antidepressant medications are commonly used to treat depression, but only about 30% of patients reach remission with any single first-step antidepressant. If the first-step treatment fails, response and remission rates at subsequent steps are even more limited. The literature on biomarkers for treatment response is largely based on secondary analyses of studies designed to answer primary questions of efficacy, rather than on a planned systematic evaluation of biomarkers for treatment decision. The lack of evidence-based knowledge to guide treatment decisions for patients with depression has lead to the recognition that specially designed studies with the primary objective being to discover biosignatures for optimizing treatment decisions are necessary. Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) is one such discovery study. Stage 1 of EMBARC is a randomized placebo controlled clinical trial of 8 week duration. A wide array of patient characteristics is collected at baseline, including assessments of brain structure, function and connectivity along with electrophysiological, biological, behavioral and clinical features. This paper reports on the data analytic strategy for discovering biosignatures for treatment response based on Stage 1 of EMBARC.
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Affiliation(s)
- Eva Petkova
- New York University, New York, NY, USA
- Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | | | - Thaddeus Tarpey
- New York University, New York, NY, USA
- Wright State University, Dayton, OH, USA
| | - Adam Ciarleglio
- New York University, New York, NY, USA
- Columbia University, New York, NY, USA
| | - Bei Jiang
- University of Alberta, Edmonton, Alberta, Canada
| | - Zhe Su
- New York University, New York, NY, USA
| | - Thomas Carmody
- University of Texas, Southwestern Medical Center, Dallas, TX, USA
| | - Philip Adams
- New York State Psychiatric Institute, New York, NY, USA
- Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY, USA
| | | | | | - Maria A. Oquendo
- New York State Psychiatric Institute, New York, NY, USA
- Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY, USA
| | | | - Myrna Weissman
- New York State Psychiatric Institute, New York, NY, USA
- Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY, USA
| | - Patrick J. McGrath
- New York State Psychiatric Institute, New York, NY, USA
- Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY, USA
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30
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Malm H, Brown AS, Gissler M, Gyllenberg D, Hinkka-Yli-Salomäki S, McKeague IW, Weissman M, Wickramaratne P, Artama M, Gingrich JA, Sourander A. Gestational Exposure to Selective Serotonin Reuptake Inhibitors and Offspring Psychiatric Disorders: A National Register-Based Study. J Am Acad Child Adolesc Psychiatry 2016; 55:359-66. [PMID: 27126849 PMCID: PMC4851729 DOI: 10.1016/j.jaac.2016.02.013] [Citation(s) in RCA: 147] [Impact Index Per Article: 18.4] [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: 11/19/2015] [Revised: 02/01/2016] [Accepted: 02/26/2016] [Indexed: 01/17/2023]
Abstract
OBJECTIVE To investigate the impact of gestational exposure to selective serotonin reuptake inhibitors (SSRIs) on offspring neurodevelopment. METHOD This is a cohort study using national register data in Finland between the years 1996 and 2010. Pregnant women and their offspring were categorized into 4 groups: SSRI exposed (n = 15,729); exposed to psychiatric disorder, no antidepressants (n = 9,651); exposed to SSRIs only before pregnancy (n = 7,980); and unexposed to antidepressants and psychiatric disorders (n = 31,394). We investigated the cumulative incidence of offspring diagnoses of depression, anxiety, autism spectrum disorder (ASD), and attention-deficit/hyperactivity disorder (ADHD) for the 4 groups from birth to 14 years, adjusting for confounders. RESULTS The cumulative incidence of depression among offspring exposed prenatally to SSRIs was 8.2% (95% CI = 3.1-13.3%) by age 14.9 years, compared with 1.9% (95% CI = 0.9-2.9%) in the psychiatric disorder, no medication group (adjusted hazard ratio [HR] = 1.78; 95% CI = 1.12-2.82; p = .02) and to 2.8% (95% CI = 1.4-4.3%) in the SSRI discontinued group (HR = 1.84; 95% CI = 1.14-2.97; p = .01). Rates of anxiety, ASD, and ADHD diagnoses were comparable to rates in offspring of mothers with a psychiatric disorder but no medication during pregnancy. Comparing SSRI exposed to unexposed individuals, the HRs were significantly elevated for each outcome. CONCLUSION Prenatal SSRI exposure was associated with increased rates of depression diagnoses in early adolescence but not with ASD or ADHD. Until confirmed, these findings must be balanced against the substantial adverse consequences of untreated maternal depression.
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Affiliation(s)
- Heli Malm
- Teratology Information and Clinical Pharmacology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Department of Child Psychiatry, University of Turku, Turku, Finland.
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31
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Webb CA, Dillon DG, Pechtel P, Goer FK, Murray L, Huys QJM, Fava M, McGrath PJ, Weissman M, Parsey R, Kurian BT, Adams P, Weyandt S, Trombello JM, Grannemann B, Cooper CM, Deldin P, Tenke C, Trivedi M, Bruder G, Pizzagalli DA. Neural Correlates of Three Promising Endophenotypes of Depression: Evidence from the EMBARC Study. Neuropsychopharmacology 2016; 41:454-63. [PMID: 26068725 PMCID: PMC5130121 DOI: 10.1038/npp.2015.165] [Citation(s) in RCA: 72] [Impact Index Per Article: 9.0] [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: 02/16/2015] [Revised: 04/24/2015] [Accepted: 05/27/2015] [Indexed: 11/09/2022]
Abstract
Major depressive disorder (MDD) is clinically, and likely pathophysiologically, heterogeneous. A potentially fruitful approach to parsing this heterogeneity is to focus on promising endophenotypes. Guided by the NIMH Research Domain Criteria initiative, we used source localization of scalp-recorded EEG resting data to examine the neural correlates of three emerging endophenotypes of depression: neuroticism, blunted reward learning, and cognitive control deficits. Data were drawn from the ongoing multi-site EMBARC study. We estimated intracranial current density for standard EEG frequency bands in 82 unmedicated adults with MDD, using Low-Resolution Brain Electromagnetic Tomography. Region-of-interest and whole-brain analyses tested associations between resting state EEG current density and endophenotypes of interest. Neuroticism was associated with increased resting gamma (36.5-44 Hz) current density in the ventral (subgenual) anterior cingulate cortex (ACC) and orbitofrontal cortex (OFC). In contrast, reduced cognitive control correlated with decreased gamma activity in the left dorsolateral prefrontal cortex (dlPFC), decreased theta (6.5-8 Hz) and alpha2 (10.5-12 Hz) activity in the dorsal ACC, and increased alpha2 activity in the right dlPFC. Finally, blunted reward learning correlated with lower OFC and left dlPFC gamma activity. Computational modeling of trial-by-trial reinforcement learning further indicated that lower OFC gamma activity was linked to reduced reward sensitivity. Three putative endophenotypes of depression were found to have partially dissociable resting intracranial EEG correlates, reflecting different underlying neural dysfunctions. Overall, these findings highlight the need to parse the heterogeneity of MDD by focusing on promising endophenotypes linked to specific pathophysiological abnormalities.
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Affiliation(s)
- Christian A Webb
- Department of Psychiatry, Harvard Medical School and McLean Hospital, Belmont, MA, USA
| | - Daniel G Dillon
- Department of Psychiatry, Harvard Medical School and McLean Hospital, Belmont, MA, USA
| | - Pia Pechtel
- Department of Psychiatry, Harvard Medical School and McLean Hospital, Belmont, MA, USA
| | - Franziska K Goer
- Department of Psychiatry, Harvard Medical School and McLean Hospital, Belmont, MA, USA
| | - Laura Murray
- Department of Psychiatry, Harvard Medical School and McLean Hospital, Belmont, MA, USA
| | - Quentin JM Huys
- Centre for Addiction Disorders, Department of Psychiatry, Psychotherapy and Psychosomatics, Hospital of Psychiatry, University of Zurich, Switzerland,Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich and Swiss Federal Institute of Technology (ETH) Zurich, Switzerland
| | - Maurizio Fava
- Clinical Research Program, Massachusetts General Hospital, Boston, MA, USA
| | - Patrick J McGrath
- Department of Psychiatry, New York State Psychiatric Institute, College of Physicians and Surgeons of Columbia University, New York, NY, USA
| | - Myrna Weissman
- Department of Psychiatry, New York State Psychiatric Institute, College of Physicians and Surgeons of Columbia University, New York, NY, USA
| | - Ramin Parsey
- Department of Psychiatry and Behavioral Science, Stony Brook University, Stony Brook, NY, USA
| | - Benji T Kurian
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Phillip Adams
- Department of Psychiatry, New York State Psychiatric Institute, College of Physicians and Surgeons of Columbia University, New York, NY, USA
| | - Sarah Weyandt
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Joseph M Trombello
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Bruce Grannemann
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Crystal M Cooper
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Patricia Deldin
- Department of Psychiatry, University of Michigan Health System, Ann Arbor, MI, USA
| | - Craig Tenke
- Department of Psychiatry, New York State Psychiatric Institute, College of Physicians and Surgeons of Columbia University, New York, NY, USA
| | - Madhukar Trivedi
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Gerard Bruder
- Department of Psychiatry, New York State Psychiatric Institute, College of Physicians and Surgeons of Columbia University, New York, NY, USA
| | - Diego A Pizzagalli
- Department of Psychiatry, Harvard Medical School and McLean Hospital, Belmont, MA, USA,Center for Depression, Anxiety, and Stress Research, McLean Hospital, Harvard Medical School, 115 Mill Street, Belmont, MA 02478, USA, Tel: +1 617 855 4230, Fax: +1 617 855 4230, E-mail:
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Greenberg T, Chase HW, Almeida JR, Stiffler R, Zevallos CR, Aslam HA, Deckersbach T, Weyandt S, Cooper C, Toups M, Carmody T, Kurian B, Peltier S, Adams P, McInnis MG, Oquendo MA, McGrath PJ, Fava M, Weissman M, Parsey R, Trivedi MH, Phillips ML. Moderation of the Relationship Between Reward Expectancy and Prediction Error-Related Ventral Striatal Reactivity by Anhedonia in Unmedicated Major Depressive Disorder: Findings From the EMBARC Study. Am J Psychiatry 2015; 172:881-91. [PMID: 26183698 PMCID: PMC4858169 DOI: 10.1176/appi.ajp.2015.14050594] [Citation(s) in RCA: 75] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
OBJECTIVE Anhedonia, disrupted reward processing, is a core symptom of major depressive disorder. Recent findings demonstrate altered reward-related ventral striatal reactivity in depressed individuals, but the extent to which this is specific to anhedonia remains poorly understood. The authors examined the effect of anhedonia on reward expectancy (expected outcome value) and prediction error- (discrepancy between expected and actual outcome) related ventral striatal reactivity, as well as the relationship between these measures. METHOD A total of 148 unmedicated individuals with major depressive disorder and 31 healthy comparison individuals recruited for the multisite EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care) study underwent functional MRI during a well-validated reward task. Region of interest and whole-brain data were examined in the first- (N=78) and second- (N=70) recruited cohorts, as well as the total sample, of depressed individuals, and in healthy individuals. RESULTS Healthy, but not depressed, individuals showed a significant inverse relationship between reward expectancy and prediction error-related right ventral striatal reactivity. Across all participants, and in depressed individuals only, greater anhedonia severity was associated with a reduced reward expectancy-prediction error inverse relationship, even after controlling for other symptoms. CONCLUSIONS The normal reward expectancy and prediction error-related ventral striatal reactivity inverse relationship concords with conditioning models, predicting a shift in ventral striatal responding from reward outcomes to reward cues. This study shows, for the first time, an absence of this relationship in two cohorts of unmedicated depressed individuals and a moderation of this relationship by anhedonia, suggesting reduced reward-contingency learning with greater anhedonia. These findings help elucidate neural mechanisms of anhedonia, as a step toward identifying potential biosignatures of treatment response.
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Dillon DG, Wiecki T, Pechtel P, Webb C, Goer F, Murray L, Trivedi M, Fava M, McGrath PJ, Weissman M, Parsey R, Kurian B, Adams P, Carmody T, Weyandt S, Shores-Wilson K, Toups M, McInnis M, Oquendo MA, Cusin C, Deldin P, Bruder G, Pizzagalli DA. A computational analysis of flanker interference in depression. Psychol Med 2015; 45:2333-2344. [PMID: 25727375 PMCID: PMC4499007 DOI: 10.1017/s0033291715000276] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [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] [Indexed: 11/06/2022]
Abstract
BACKGROUND Depression is characterized by poor executive function, but - counterintuitively - in some studies, it has been associated with highly accurate performance on certain cognitively demanding tasks. The psychological mechanisms responsible for this paradoxical finding are unclear. To address this issue, we applied a drift diffusion model (DDM) to flanker task data from depressed and healthy adults participating in the multi-site Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC) study. METHOD One hundred unmedicated, depressed adults and 40 healthy controls completed a flanker task. We investigated the effect of flanker interference on accuracy and response time, and used the DDM to examine group differences in three cognitive processes: prepotent response bias (tendency to respond to the distracting flankers), response inhibition (necessary to resist prepotency), and executive control (required for execution of correct response on incongruent trials). RESULTS Consistent with prior reports, depressed participants responded more slowly and accurately than controls on incongruent trials. The DDM indicated that although executive control was sluggish in depressed participants, this was more than offset by decreased prepotent response bias. Among the depressed participants, anhedonia was negatively correlated with a parameter indexing the speed of executive control (r = -0.28, p = 0.007). CONCLUSIONS Executive control was delayed in depression but this was counterbalanced by reduced prepotent response bias, demonstrating how participants with executive function deficits can nevertheless perform accurately in a cognitive control task. Drawing on data from neural network simulations, we speculate that these results may reflect tonically reduced striatal dopamine in depression.
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Affiliation(s)
- Daniel G. Dillon
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Harvard Medical School, Belmont, MA USA
| | - Thomas Wiecki
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI USA
| | - Pia Pechtel
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Harvard Medical School, Belmont, MA USA
| | - Christian Webb
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Harvard Medical School, Belmont, MA USA
| | - Franziska Goer
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Harvard Medical School, Belmont, MA USA
| | - Laura Murray
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Harvard Medical School, Belmont, MA USA
| | - Madhukar Trivedi
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX USA
| | - Maurizio Fava
- Clinical Research Program, Massachusetts General Hospital, Boston, MA USA
| | - Patrick J. McGrath
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY USA
| | - Myrna Weissman
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY USA
| | - Ramin Parsey
- Department of Psychiatry and Behavioral Science, Stony Brook University, Stony Brook, NY USA
| | - Benji Kurian
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX USA
| | - Phillip Adams
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY USA
| | - Thomas Carmody
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX USA
| | - Sarah Weyandt
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX USA
| | - Kathy Shores-Wilson
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX USA
| | - Marisa Toups
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX USA
| | - Melvin McInnis
- Department of Psychiatry, University of Michigan Health System, Ann Arbor, MI USA
| | - Maria A. Oquendo
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY USA
| | - Cristina Cusin
- Clinical Research Program, Massachusetts General Hospital, Boston, MA USA
| | - Patricia Deldin
- Department of Psychiatry, University of Michigan Health System, Ann Arbor, MI USA
| | - Gerard Bruder
- New York State Psychiatric Institute & Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY USA
| | - Diego A. Pizzagalli
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Harvard Medical School, Belmont, MA USA
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34
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Iscan Z, Jin TB, Kendrick A, Szeglin B, Lu H, Trivedi M, Fava M, McGrath PJ, Weissman M, Kurian BT, Adams P, Weyandt S, Toups M, Carmody T, McInnis M, Cusin C, Cooper C, Oquendo MA, Parsey RV, DeLorenzo C. Test-retest reliability of freesurfer measurements within and between sites: Effects of visual approval process. Hum Brain Mapp 2015; 36:3472-85. [PMID: 26033168 DOI: 10.1002/hbm.22856] [Citation(s) in RCA: 112] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2014] [Revised: 05/11/2015] [Accepted: 05/15/2015] [Indexed: 12/30/2022] Open
Abstract
In the last decade, many studies have used automated processes to analyze magnetic resonance imaging (MRI) data such as cortical thickness, which is one indicator of neuronal health. Due to the convenience of image processing software (e.g., FreeSurfer), standard practice is to rely on automated results without performing visual inspection of intermediate processing. In this work, structural MRIs of 40 healthy controls who were scanned twice were used to determine the test-retest reliability of FreeSurfer-derived cortical measures in four groups of subjects-those 25 that passed visual inspection (approved), those 15 that failed visual inspection (disapproved), a combined group, and a subset of 10 subjects (Travel) whose test and retest scans occurred at different sites. Test-retest correlation (TRC), intraclass correlation coefficient (ICC), and percent difference (PD) were used to measure the reliability in the Destrieux and Desikan-Killiany (DK) atlases. In the approved subjects, reliability of cortical thickness/surface area/volume (DK atlas only) were: TRC (0.82/0.88/0.88), ICC (0.81/0.87/0.88), PD (0.86/1.19/1.39), which represent a significant improvement over these measures when disapproved subjects are included. Travel subjects' results show that cortical thickness reliability is more sensitive to site differences than the cortical surface area and volume. To determine the effect of visual inspection on sample size required for studies of MRI-derived cortical thickness, the number of subjects required to show group differences was calculated. Significant differences observed across imaging sites, between visually approved/disapproved subjects, and across regions with different sizes suggest that these measures should be used with caution.
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Affiliation(s)
- Zafer Iscan
- Centre for Cognition and Decision Making, National Research University Higher School of Economics, Russian Federation
| | - Tony B Jin
- Department of Psychiatry, Stony Brook University, Stony Brook, New York
| | | | - Bryan Szeglin
- Department of Psychiatry, Stony Brook University, Stony Brook, New York
| | - Hanzhang Lu
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, Texas
| | - Madhukar Trivedi
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, Texas
| | - Maurizio Fava
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
| | - Patrick J McGrath
- New York State Psychiatric Institute, New York, New York.,Department of Psychiatry, Columbia University/New York State Psychiatric Institute, New York, New York
| | - Myrna Weissman
- Department of Psychiatry, Columbia University/New York State Psychiatric Institute, New York, New York
| | - Benji T Kurian
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, Texas
| | - Phillip Adams
- New York State Psychiatric Institute, New York, New York
| | - Sarah Weyandt
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, Texas
| | - Marisa Toups
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, Texas
| | - Thomas Carmody
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, Texas
| | - Melvin McInnis
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan
| | - Cristina Cusin
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
| | - Crystal Cooper
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, Texas
| | | | - Ramin V Parsey
- Department of Psychiatry, Stony Brook University, Stony Brook, New York
| | - Christine DeLorenzo
- Department of Psychiatry, Stony Brook University, Stony Brook, New York.,Department of Psychiatry, Columbia University/New York State Psychiatric Institute, New York, New York
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Chase HW, Fournier JC, Greenberg T, Almeida JR, Stiffler R, Zevallos CR, Aslam H, Cooper C, Deckersbach T, Weyandt S, Adams P, Toups M, Carmody T, Oquendo MA, Peltier S, Fava M, McGrath PJ, Weissman M, Parsey R, McInnis MG, Kurian B, Trivedi MH, Phillips ML. Accounting for Dynamic Fluctuations across Time when Examining fMRI Test-Retest Reliability: Analysis of a Reward Paradigm in the EMBARC Study. PLoS One 2015; 10:e0126326. [PMID: 25961712 PMCID: PMC4427400 DOI: 10.1371/journal.pone.0126326] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2014] [Accepted: 03/31/2015] [Indexed: 02/06/2023] Open
Abstract
Longitudinal investigation of the neural correlates of reward processing in depression may represent an important step in defining effective biomarkers for antidepressant treatment outcome prediction, but the reliability of reward-related activation is not well understood. Thirty-seven healthy control participants were scanned using fMRI while performing a reward-related guessing task on two occasions, approximately one week apart. Two main contrasts were examined: right ventral striatum (VS) activation fMRI BOLD signal related to signed prediction errors (PE) and reward expectancy (RE). We also examined bilateral visual cortex activation coupled to outcome anticipation. Significant VS PE-related activity was observed at the first testing session, but at the second testing session, VS PE-related activation was significantly reduced. Conversely, significant VS RE-related activity was observed at time 2 but not time 1. Increases in VS RE-related activity from time 1 to time 2 were significantly associated with decreases in VS PE-related activity from time 1 to time 2 across participants. Intraclass correlations (ICCs) in VS were very low. By contrast, visual cortex activation had much larger ICCs, particularly in individuals with high quality data. Dynamic changes in brain activation are widely predicted, and failure to account for these changes could lead to inaccurate evaluations of the reliability of functional MRI signals. Conventional measures of reliability cannot distinguish between changes specified by algorithmic models of neural function and noisy signal. Here, we provide evidence for the former possibility: reward-related VS activations follow the pattern predicted by temporal difference models of reward learning but have low ICCs.
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Affiliation(s)
- Henry W. Chase
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
- * E-mail:
| | - Jay C. Fournier
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
| | - Tsafrir Greenberg
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
| | - Jorge R. Almeida
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
| | - Richelle Stiffler
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
| | - Carlos R. Zevallos
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
| | - Haris Aslam
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
| | - Crystal Cooper
- UT Southwestern Medical Center, Department of Psychiatry, Dallas, Texas, United States of America
| | - Thilo Deckersbach
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Sarah Weyandt
- UT Southwestern Medical Center, Department of Psychiatry, Dallas, Texas, United States of America
| | - Phillip Adams
- Department of Psychiatry and Behavioral Science, Stony Brook University, Stony Brook, New York, United States of America
| | - Marisa Toups
- UT Southwestern Medical Center, Department of Psychiatry, Dallas, Texas, United States of America
| | - Tom Carmody
- UT Southwestern Medical Center, Department of Psychiatry, Dallas, Texas, United States of America
| | - Maria A. Oquendo
- NY State Psychiatric Institute, Therapeutics Depression Evaluation Service, New York, New York, United States of America
- Department of Psychiatry, Columbia University College of Physicians and Surgeons, New York, New York, United States of America
| | - Scott Peltier
- Functional MRI Laboratory, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Maurizio Fava
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Patrick J. McGrath
- NY State Psychiatric Institute, Therapeutics Depression Evaluation Service, New York, New York, United States of America
- Department of Psychiatry, Columbia University College of Physicians and Surgeons, New York, New York, United States of America
| | - Myrna Weissman
- NY State Psychiatric Institute, Therapeutics Depression Evaluation Service, New York, New York, United States of America
- Department of Psychiatry, Columbia University College of Physicians and Surgeons, New York, New York, United States of America
| | - Ramin Parsey
- Department of Psychiatry and Behavioral Science, Stony Brook University, Stony Brook, New York, United States of America
- Department of Radiology, Stony Brook University, Stony Brook, New York, United States of America
| | - Melvin G. McInnis
- Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor, Michigan, United States of America
| | - Benji Kurian
- UT Southwestern Medical Center, Department of Psychiatry, Dallas, Texas, United States of America
| | - Madhukar H. Trivedi
- UT Southwestern Medical Center, Department of Psychiatry, Dallas, Texas, United States of America
| | - Mary L. Phillips
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
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Affiliation(s)
- Annika Sweetland
- Department of Psychiatry, Columbia College of Physicians and SurgeonsNew York, NY, USA,New York State Psychiatric InstituteNew York, NY, USA
| | - Maria Oquendo
- Department of Psychiatry, Columbia College of Physicians and SurgeonsNew York, NY, USA,New York State Psychiatric InstituteNew York, NY, USA
| | - Priya Wickramaratne
- Department of Psychiatry, Columbia College of Physicians and SurgeonsNew York, NY, USA,New York State Psychiatric InstituteNew York, NY, USA
| | - Myrna Weissman
- Department of Psychiatry, Columbia College of Physicians and SurgeonsNew York, NY, USA,New York State Psychiatric InstituteNew York, NY, USA
| | - Milton Wainberg
- Department of Psychiatry, Columbia College of Physicians and SurgeonsNew York, NY, USA,New York State Psychiatric InstituteNew York, NY, USA
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Lewandowski RE, Verdeli H, Wickramaratne P, Warner V, Mancini A, Weissman M. Predictors of Positive Outcomes in Offspring of Depressed Parents and Non-depressed Parents Across 20 Years. J Child Fam Stud 2014; 23:800-811. [PMID: 25374449 PMCID: PMC4217704 DOI: 10.1007/s10826-013-9732-3] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Understanding differences in factors leading to positive outcomes in high-risk and low-risk offspring has important implications for preventive interventions. We identified variables predicting positive outcomes in a cohort of 235 offspring from 76 families in which one, both, or neither parent had major depressive disorder. Positive outcomes were termed resilient in offspring of depressed parents, and competent in offspring of non-depressed parents, and defined by two separate criteria: absence of psychiatric diagnosis and consistently high functioning at 2, 10, and 20 years follow-up. In offspring of depressed parents, easier temperament and higher self-esteem were associated with greater odds of resilient outcome defined by absence of diagnosis. Lower maternal overprotection, greater offspring self-esteem, and higher IQ were associated with greater odds of resilient outcome defined by consistently high functioning. Multivariate analysis indicated that resilient outcome defined by absence of diagnosis was best predicted by offspring self-esteem; resilient outcome defined by functioning was best predicted by maternal overprotection and self-esteem. Among offspring of non-depressed parents, greater family cohesion, easier temperament and higher self-esteem were associated with greater odds of offspring competent outcome defined by absence of diagnosis. Higher maternal affection and greater offspring self-esteem were associated with greater odds of competent outcome, defined by consistently high functioning. Multivariate analysis for each criterion indicated that competent outcome was best predicted by offspring self-esteem. As the most robust predictor of positive outcomes in offspring of depressed and non-depressed parents, self-esteem is an important target for youth preventive interventions.
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Affiliation(s)
- R. Eric Lewandowski
- Child Study Center, Department of Child and Adolescent Psychiatry, New York University School of Medicine, New York, NY 10016, USA
| | - Helen Verdeli
- Department of Counseling and Clinical Psychology, Teachers College, Columbia University, New York, NY 10027, USA
| | - Priya Wickramaratne
- Division of Epidemiology, New York State Psychiatric Institute, New York, NY 10032, USA
| | - Virginia Warner
- Division of Epidemiology, New York State Psychiatric Institute, New York, NY 10032, USA
| | - Anthony Mancini
- Psychology Department, Pace University, Pleasantville, NY 10570, USA
| | - Myrna Weissman
- Department of Psychiatry, Columbia University College of Physicians and Surgeons, New York, NY 10032, USA
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John T, Morton M, Weissman M, O'Brien E, Hamburger E, Hancock Y, Moon RY. Feasibility of a virtual learning collaborative to implement an obesity QI project in 29 pediatric practices. Int J Qual Health Care 2014; 26:205-13. [DOI: 10.1093/intqhc/mzu012] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Westphal M, Olfson M, Bravova M, Gameroff MJ, Gross R, Wickramaratne P, Pilowsky DJ, Neugebauer R, Shea S, Lantigua R, Weissman M, Neria Y. Borderline personality disorder, exposure to interpersonal trauma, and psychiatric comorbidity in urban primary care patients. Psychiatry 2013; 76:365-80. [PMID: 24299094 DOI: 10.1521/psyc.2013.76.4.365] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
OBJECTIVE Few data are available on interpersonal trauma as a risk factor for borderline personality disorder (BPD) and its psychiatric comorbidity in ethnic minority primary care populations. This study aimed to examine the relation between trauma exposure and BPD in low-income, predominantly Hispanic primary care patients. METHOD Logistic regression was used to analyze data from structured clinical interviews and self-report measures (n = 474). BPD was assessed with the McLean screening scale. Trauma exposure was assessed with the Life Events Checklist (LEC); posttraumatic stress disorder (PTSD) was assessed with the Lifetime Composite International Diagnostic Interview, other psychiatric disorders with the SCID-I, and functional impairment with items from the Sheehan Disability Scale and Social Adjustment Scale Self-Report (SAS-SR). RESULTS Of the 57 (14%) patients screening positive for BPD, 83% reported a history of interpersonally traumatic events such as sexual and physical assault or abuse. While interpersonal trauma experienced during adulthood was as strongly associated with BPD as interpersonal trauma experienced during childhood, noninterpersonal trauma was associated with BPD only if it had occurred during childhood. The majority (91%) of patients screening positive for BPD met criteria for at least one current DSM-IV Axis I diagnosis and exhibited significant levels of functional impairment. CONCLUSION Increased awareness of BPD in minority patients attending primary care clinics, high rates of exposure to interpersonal trauma, and elevated risk for psychiatric comorbidity in this population may enhance physicians' understanding, treatment, and referral of BPD patients.
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Bansal R, Staib LH, Laine AF, Hao X, Xu D, Liu J, Weissman M, Peterson BS. Anatomical brain images alone can accurately diagnose chronic neuropsychiatric illnesses. PLoS One 2012; 7:e50698. [PMID: 23236384 PMCID: PMC3517530 DOI: 10.1371/journal.pone.0050698] [Citation(s) in RCA: 62] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2012] [Accepted: 10/25/2012] [Indexed: 11/28/2022] Open
Abstract
Objective Diagnoses using imaging-based measures alone offer the hope of improving the accuracy of clinical diagnosis, thereby reducing the costs associated with incorrect treatments. Previous attempts to use brain imaging for diagnosis, however, have had only limited success in diagnosing patients who are independent of the samples used to derive the diagnostic algorithms. We aimed to develop a classification algorithm that can accurately diagnose chronic, well-characterized neuropsychiatric illness in single individuals, given the availability of sufficiently precise delineations of brain regions across several neural systems in anatomical MR images of the brain. Methods We have developed an automated method to diagnose individuals as having one of various neuropsychiatric illnesses using only anatomical MRI scans. The method employs a semi-supervised learning algorithm that discovers natural groupings of brains based on the spatial patterns of variation in the morphology of the cerebral cortex and other brain regions. We used split-half and leave-one-out cross-validation analyses in large MRI datasets to assess the reproducibility and diagnostic accuracy of those groupings. Results In MRI datasets from persons with Attention-Deficit/Hyperactivity Disorder, Schizophrenia, Tourette Syndrome, Bipolar Disorder, or persons at high or low familial risk for Major Depressive Disorder, our method discriminated with high specificity and nearly perfect sensitivity the brains of persons who had one specific neuropsychiatric disorder from the brains of healthy participants and the brains of persons who had a different neuropsychiatric disorder. Conclusions Although the classification algorithm presupposes the availability of precisely delineated brain regions, our findings suggest that patterns of morphological variation across brain surfaces, extracted from MRI scans alone, can successfully diagnose the presence of chronic neuropsychiatric disorders. Extensions of these methods are likely to provide biomarkers that will aid in identifying biological subtypes of those disorders, predicting disease course, and individualizing treatments for a wide range of neuropsychiatric illnesses.
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Affiliation(s)
- Ravi Bansal
- Department of Psychiatry, Columbia College of Physicians & Surgeons and the New York State Psychiatric Institute, New York, New York, USA.
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Cole DA, Cho SJ, Martin NC, Youngstrom EA, March JS, Findling RL, Compas BE, Goodyer IM, Rohde P, Weissman M, Essex MJ, Hyde JS, Curry JF, Forehand R, Slattery MJ, Felton JW, Maxwell MA. Are increased weight and appetite useful indicators of depression in children and adolescents? J Abnorm Psychol 2012; 121:838-51. [PMID: 22686866 PMCID: PMC3547528 DOI: 10.1037/a0028175] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
During childhood and adolescence, physiological, psychological, and behavioral processes strongly promote weight gain and increased appetite while also inhibiting weight loss and decreased appetite. The Diagnostic and Statistical Manual-IV (DSM-IV) treats both weight-gain/increased-appetite and weight-loss/decreased-appetite as symptoms of major depression during these developmental periods, despite the fact that one complements typical development and the other opposes it. To disentangle the developmental versus pathological correlates of weight and appetite disturbance in younger age groups, the current study examined symptoms of depression in an aggregated sample of 2307 children and adolescents, 47.25% of whom met criteria for major depressive disorder. A multigroup, multidimensional item response theory model generated three key results. First, weight loss and decreased appetite loaded strongly onto a general depression dimension; in contrast, weight gain and increased appetite did not. Instead, weight gain and increased appetite loaded onto a separate dimension that did not correlate strongly with general depression. Second, inclusion or exclusion of weight gain and increased appetite affected neither the nature of the general depression dimension nor the fidelity of major depressive disorder diagnosis. Third, the general depression dimension and the weight-gain/increased-appetite dimension showed different patterns across age and gender. In child and adolescent populations, these results call into question the utility of weight gain and increased appetite as indicators of depression. This has serious implications for the diagnostic criteria of depression in children and adolescents. These findings inform a revision of the DSM, with implications for the diagnosis of depression in this age group and for research on depression.
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Affiliation(s)
- David A Cole
- Department of Psychology and Human Development, Vanderbilt University, 230 Appleton Place, Nashville, TN 37203, USA.
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Abstract
Depression is highly prevalent and debilitating among medically ill patients. As high as one third of the primary practise patients screen positive for depression symptoms and over half of the patients diagnosed with major depressive disorder are treated in primary care. However, current primary care service arrangements do not efficiently triage patients who screen positive for depression into appropriate treatments that reflect their individual needs and preferences. In this paper, we describe a tool that aims to fill the gap between screening the patients for depression and triaging them to appropriate care. This is a three-session adaptation of interpersonal psychotherapy: ipt; evaluation, support, triage (IPT-EST). We first outline IPT-EST procedures that aim to provide structure and content to primary care practitioners who identify patients with positive depression symptoms, thus assisting the practitioners to explore the patients' psychosocial triggers of depression, give basic strategies to manage these interpersonal stressors and provide decisions tools about triaging patients with severe/persistent depression into appropriate treatment.
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Affiliation(s)
- Myrna Weissman
- College of Physicians and Surgeons, Columbia University, New York, USA.
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Murphy E, Wickramaratne P, Weissman M. The stability of parental bonding reports: a 20-year follow-up. J Affect Disord 2010; 125:307-15. [PMID: 20138671 PMCID: PMC2889015 DOI: 10.1016/j.jad.2010.01.003] [Citation(s) in RCA: 61] [Impact Index Per Article: 4.4] [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: 07/03/2009] [Revised: 01/01/2010] [Accepted: 01/06/2010] [Indexed: 11/25/2022]
Abstract
BACKGROUND Addressing the long-term reliability of retrospectively assessed parenting is underscored by the well-documented association between parenting behaviors, and mood disorders in offspring. The rarity of longitudinal research with follow-up periods exceeding 10 years creates a need for additional studies. METHODS 134 offspring of depressed and non-depressed parents were assessed on Parental Bonding Instrument (PBI) scores, lifetime major depression (MDD), and current depressive symptoms at four waves across 20 years. PBI rank order and mean level stability, individual trajectories, and the impact of baseline age, gender, and lifetime MDD on stability, were obtained using multiple regression and linear mixed model analyses. RESULTS Besides paternal overprotection which showed a 1.6-point average decrease, the PBI domains remained non-significant for mean level change over 20 years. However, there was a significant individual variation for all PBI domains. Lifetime MDD and age did not significantly impact retest correlations; older age at baseline was associated with higher average paternal overprotection. Sons had lower retest correlations than daughters, but did not differ from daughters on mean level stability. Current depressive symptoms were associated with PBI scores, but did not impact the effect of lifetime MDD, gender or age on mean level stability and individual trajectories. LIMITATIONS Small sample sizes and measuring lifetime MDD as present or absent may have restricted our ability to detect effects of MDD history on PBI stability. CONCLUSION The PBI is a robust measure of an important environmental risk for depressive disorders, and can be variably sensitive to sample characteristics, the passage of time and mood fluctuations. However, this sensitivity does not appear to significantly bias the long-term stability of this instrument.
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Affiliation(s)
- Eleanor Murphy
- Department of Psychiatry, College of Physicians and Surgeons, Columbia University & Division of Epidemiology, New York State Psychiatric Institute, United States.
| | - Priya Wickramaratne
- Department of Psychiatry, College of Physicians and Surgeons, Columbia University & Division of Epidemiology, New York State Psychiatric Institute
| | - Myrna Weissman
- Department of Psychiatry, College of Physicians and Surgeons, Columbia University & Division of Epidemiology, New York State Psychiatric Institute
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Feher G, Weissman M. Fluctuation spectroscopy: determination of chemical reaction kinetics from the frequency spectrum of fluctuations. Proc Natl Acad Sci U S A 2010; 70:870-5. [PMID: 16592071 PMCID: PMC433378 DOI: 10.1073/pnas.70.3.870] [Citation(s) in RCA: 111] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The kinetic parameters of a chemical reaction were obtained from analysis of the frequency spectrum of the fluctuations (i.e., "noise") in the concentrations of the reactants. In "fluctuation spectroscopy," no external perturbation is applied and the system remains in macroscopic chemical equilibrium during the experiment. Results obtained by this method for the dissociation reaction of beryllium sulfate agree well with those obtained by relaxation methods in which the approach to equilibrium is analyzed. Other noise sources not originating from a chemical reaction were observed and analyzed. The most prominent of these arose from the flow of an electrolyte through a capillary. The method of fluctuation spectroscopy should be applicable to problems of physical, chemical, and biological interest.
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Affiliation(s)
- G Feher
- University of California, San Diego, Department of Physics, La Jolla, Calif. 92037
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Abstract
This is an invited article on how my career as an epidemiologist studying depression unfolded. The role of the Civil Rights movement in opening the PhD doors to women at Yale began my career. The unfolding of depression studies are described. These studies included a clinical trial of medication and what later was known as interpersonal psychotherapy (IPT), the first community survey of psychiatric disorder, family genetic and brain imaging studies or depression and anxiety disorders. I hope the new generation will have the wonderful opportunities I have had.
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Affiliation(s)
- Myrna Weissman
- Department of Psychiatry, College of Physicians and Surgeons and Mailman School of Public Health, Columbia University, 1051 Riverside Drive, New York, NY 10032, USA.
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Abstract
OBJECTIVE To test the feasibility, acceptability and helpfulness of group Interpersonal Psychotherapy (IPT-PA) for depression in pregnant adolescents. METHOD Two open clinical trials were conducted of IPT-PA delivered in group format in a New York City public school for pregnant girls. Study 1 tests IPT-PA for management of depressive symptoms by delivery during health class to pregnant girls with varying levels of depressive symptoms (N = 14; 10 Hispanic, 3 African-American and 1 bi-racial). Study 2 tests IPT-PA for treatment of depression by delivery after school for self-nominating pregnant girls with DSM-IVR diagnoses of depressive disorder or an adjustment disorder (N = 11; 8 African-American, 1 girl Hispanic and 2 bi-racial). Depressive symptoms were assessed using the Beck Depression Inventory and the Edinburgh Depression Scale (for its sensitivity to severe symptoms, the Hamilton Depression Scale was added in Study 2). Clinical diagnosis was assessed using the Schedule for Affective Disorders and Schizophrenia for Children (K-SADS). STUDY 1 RESULTS At 12-week termination, level of depressive symptoms had decreased by 50%; 13/14 girls showed a decrease in level of symptoms. STUDY 2 RESULTS At 12-week termination, level of depressive symptoms had decreased by 40%; 10/11 girls showed decrease in level of symptoms and in DSM-IVR clinical diagnosis; treatment gains were maintained at 20-week post-partum follow-up. CONCLUSION IPT-PA appears feasible and helpful in managing and treating depression in pregnant girls.
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Affiliation(s)
- Lisa Miller
- Teachers College, Columbia University, New York, USA.
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Bruder B, Warner V, Talati A, Nomura Y, Bruder G, Weissman M. Temperament among offspring at high and low risk for depression. Psychiatry Res 2007; 153:145-51. [PMID: 17651814 PMCID: PMC2128059 DOI: 10.1016/j.psychres.2007.02.013] [Citation(s) in RCA: 44] [Impact Index Per Article: 2.6] [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: 02/28/2006] [Revised: 11/15/2006] [Accepted: 02/14/2007] [Indexed: 11/18/2022]
Abstract
The purpose of this study was to examine relationships between parental depression, offspring temperament, and offspring major depressive disorder (MDD), and to determine whether difficult temperament, as measured by the Dimensions of Temperament Survey (DOTS), mediates the relation between parental MDD and offspring MDD. Offspring (n=169) of depressed or never depressed parents were followed over approximately 20 years and were blindly assessed up to 4 times (Waves 1 to 4) using semi-structured interviews. Offspring completed the DOTS at the time of first or second assessment. The results showed: (1) high-risk offspring with one or more depressed parent were significantly more likely than offspring with neither parent depressed to have a difficult temperament; (2) offspring with a difficult temperament were more than twice as likely as those with an easy temperament to develop a MDD; and (3) difficult temperament explained more than 10% of the association between parental depression and new onsets of MDD in offspring. The findings suggest that offspring temperament is associated with development of MDD and that difficult temperament at least partially mediates the relationship between parental depression and offspring depression. When identifying those at greatest risk for MDD, measures of temperament could serve as a useful supplement to family psychiatric history of MDD.
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Affiliation(s)
- Beth Bruder
- Department of Psychiatry, College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
- Division of Clinical and Genetic Epidemiology New York State Psychiatric Institute, New York, NY 10032, USA
| | - Virginia Warner
- Department of Psychiatry, College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
- Division of Clinical and Genetic Epidemiology New York State Psychiatric Institute, New York, NY 10032, USA
| | - Ardesheer Talati
- Department of Psychiatry, College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
- Division of Clinical and Genetic Epidemiology New York State Psychiatric Institute, New York, NY 10032, USA
| | - Yoko Nomura
- Department of Psychiatry, College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| | - Gerard Bruder
- Department of Psychiatry, College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
- Division of Biopsychology, New York State Psychiatric Institute, New York, NY 10032, USA
| | - Myrna Weissman
- Department of Psychiatry, College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
- Division of Clinical and Genetic Epidemiology New York State Psychiatric Institute, New York, NY 10032, USA
- *Address for Correspondence: Dr. Myrna M. Weissman, College of Physicians and Surgeons, Columbia University, New York State Psychiatric Institute, Unit 24, 1051 Riverside Drive, New York, NY 10032, USA. Tel.: +1 (212) 543-5880. E-mail:
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Bass J, Neugebauer R, Clougherty KF, Verdeli H, Wickramaratne P, Ndogoni L, Speelman L, Weissman M, Bolton P. Group interpersonal psychotherapy for depression in rural Uganda: 6-month outcomes: randomised controlled trial. Br J Psychiatry 2006; 188:567-73. [PMID: 16738348 DOI: 10.1192/bjp.188.6.567] [Citation(s) in RCA: 122] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
BACKGROUND A randomised controlled trial comparing group interpersonal psychotherapy with treatment as usual among rural Ugandans meeting symptom and functional impairment criteria for DSM-IV major depressive disorder or sub-threshold disorder showed evidence of effectiveness immediately following the intervention. AIMS To assess the long-term effectiveness of this therapy over a subsequent 6-month period. METHOD A follow-up study of trial participants was conducted in which the primary outcomes were depression diagnosis, depressive symptoms and functional impairment. RESULTS At 6 months, participants receiving the group interpersonal psychotherapy had mean depression symptom and functional impairment scores respectively 14.0 points (95% CI 12.2-15.8; P<0.0001) and 5.0 points (95% CI 3.6-6.4; P<0.0001) lower than the control group. Similarly, the rate of major depression among those in the treatment arm (11.7%) was significantly lower than that in the control arm (54.9%) (P<0.0001). CONCLUSIONS Participation in a 16-week group interpersonal psychotherapy intervention continued to confer a substantial mental health benefit 6 months after conclusion of the formal intervention.
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Affiliation(s)
- Judith Bass
- Center for International Health and Development, Boston University School of Public Health, 85 East Concord Street, 5th Floor, Boston, MA 02118, USA.
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Abstract
This study tests the hypothesis that maternal depression (major depressive disorder; MDD) decreases rates of the intergenerational transmission of religiosity from mother to offspring and attenuates the beneficial qualities of religiosity in offspring. Depression was assessed using semistructured clinical interviews; religiosity was assessed based upon the personal importance of religion, frequency of attendance at religious services, and religious denomination. Results suggest that (1) maternal depression attenuates the intergenerational transmission of religion; (2) in the presence of maternal depression, offspring were more likely to have MDD at 10-year follow-up when mother-offspring were concordant on religious importance; and (3) in the absence of maternal depression, offspring were less likely to have MDD at 10-year follow-up when mother-offspring were concordant on attendance. Thus, in the presence of maternal depression, transmission of religious attendance is no longer associated with decreased likelihood of offspring MDD, whereas transmission of religious importance is associated with increased likelihood of offspring depression.
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Affiliation(s)
- Merav Gur
- Department of Psychiatry, Columbia University, New York State Psychiatric Institute, New York, New York 10032, USA
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Judd F, Weissman M, Davis J, Hodgins G, Piterman L. Interpersonal counselling in general practice. Aust Fam Physician 2004; 33:332-7. [PMID: 15227863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 04/30/2023]
Abstract
BACKGROUND Interpersonal counselling (IPC) derives from interpersonal psycho-therapy (IPT) but is briefer in the number and duration of sessions and is particularly suited to the primary care setting. While depression and other psychological symptoms are not necessarily 'caused' by interpersonal problems, they do occur in a social and interpersonal context. Problem areas commonly associated with the onset of depression are unresolved grief, interpersonal disputes, role transition and interpersonal deficits such as social isolation. OBJECTIVE This article discusses IPC and how it can be used in the general practice setting. DISCUSSION The structure of IPC is of a brief treatment of six sessions, each with an explicit focus: assessment, education about the interaction between interpersonal relationships and psychological symptoms, identifying current stress areas and helping the patient deal with these more positively and termination of the IPC relationship. Interpersonal counselling can be utilised general practice to reduce psychological symptoms, restore morale, improve self esteem and the quality of the patient's social adjustment and interpersonal relationships.
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Affiliation(s)
- Fiona Judd
- Centre for Rural Mental Health, Bendigo Health Care Group, Monash University School of Psychology, Psychiatry and Psychological Medicine, Victoria.
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