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Lizano P, Kiely C, Mijalkov M, Meda SA, Keedy SK, Hoang D, Zeng V, Lutz O, Pereira JB, Ivleva EI, Volpe G, Xu Y, Lee AM, Rubin LH, Kristian Hill S, Clementz BA, Tamminga CA, Pearlson GD, Sweeney JA, Gershon ES, Keshavan MS, Bishop JR. Peripheral inflammatory subgroup differences in anterior Default Mode network and multiplex functional network topology are associated with cognition in psychosis. Brain Behav Immun 2023; 114:3-15. [PMID: 37506949 PMCID: PMC10592140 DOI: 10.1016/j.bbi.2023.07.014] [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: 01/30/2023] [Revised: 07/17/2023] [Accepted: 07/22/2023] [Indexed: 07/30/2023] Open
Abstract
INTRODUCTION High-inflammation subgroups of patients with psychosis demonstrate cognitive deficits and neuroanatomical alterations. Systemic inflammation assessed using IL-6 and C-reactive protein may alter functional connectivity within and between resting-state networks, but the cognitive and clinical implications of these alterations remain unknown. We aim to determine the relationships of elevated peripheral inflammation subgroups with resting-state functional networks and cognition in psychosis spectrum disorders. METHODS Serum and resting-state fMRI were collected from psychosis probands (schizophrenia, schizoaffective, psychotic bipolar disorder) and healthy controls (HC) from the B-SNIP1 (Chicago site) study who were stratified into inflammatory subgroups based on factor and cluster analyses of 13 cytokines (HC Low n = 32, Proband Low n = 65, Proband High n = 29). Nine resting-state networks derived from independent component analysis were used to assess functional and multilayer connectivity. Inter-network connectivity was measured using Fisher z-transformation of correlation coefficients. Network organization was assessed by investigating networks of positive and negative connections separately, as well as investigating multilayer networks using both positive and negative connections. Cognition was assessed using the Brief Assessment of Cognition in Schizophrenia. Linear regressions, Spearman correlations, permutations tests and multiple comparison corrections were used for analyses in R. RESULTS Anterior default mode network (DMNa) connectivity was significantly reduced in the Proband High compared to Proband Low (Cohen's d = -0.74, p = 0.002) and HC Low (d = -0.85, p = 0.0008) groups. Inter-network connectivity between the DMNa and the right-frontoparietal networks was lower in Proband High compared to Proband Low (d = -0.66, p = 0.004) group. Compared to Proband Low, the Proband High group had lower negative (d = 0.54, p = 0.021) and positive network (d = 0.49, p = 0.042) clustering coefficient, and lower multiplex network participation coefficient (d = -0.57, p = 0.014). Network findings in high inflammation subgroups correlate with worse verbal fluency, verbal memory, symbol coding, and overall cognition. CONCLUSION These results expand on our understanding of the potential effects of peripheral inflammatory signatures and/or subgroups on network dysfunction in psychosis and how they relate to worse cognitive performance. Additionally, the novel multiplex approach taken in this study demonstrated how inflammation may disrupt the brain's ability to maintain healthy co-activation patterns between the resting-state networks while inhibiting certain connections between them.
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Affiliation(s)
- Paulo Lizano
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA; Division of Translational Neuroscience, Beth Israel Deaconess Medical Center, Boston, MA, USA.
| | - Chelsea Kiely
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Mite Mijalkov
- Neuro Division, Department of Clinical Neurosciences, Karolinska Institutet, Stockholm, Sweden
| | - Shashwath A Meda
- Department of Psychiatry, Yale University, New Haven, Connecticut, USA
| | - Sarah K Keedy
- Department of Psychiatry and Behavioral Neurosciences, University of Chicago, Chicago, IL, USA
| | - Dung Hoang
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Victor Zeng
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Olivia Lutz
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Joana B Pereira
- Neuro Division, Department of Clinical Neurosciences, Karolinska Institutet, Stockholm, Sweden; Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Sweden
| | - Elena I Ivleva
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX
| | - Giovanni Volpe
- Physics Department, University of Gothenburg, Gothenburg, Sweden
| | - Yanxun Xu
- Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA
| | - Adam M Lee
- Department of Experimental and Clinical Pharmacology and Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Leah H Rubin
- Department of Neurology, Psychiatry and Behavioral Sciences, Molecular and Comparative Pathobiology, and Epidemiology, Johns Hopkins University, Baltimore, MD, USA
| | - S Kristian Hill
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL, USA
| | - Brett A Clementz
- Department of Psychology, University of Georgia, Athens, Georgia
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX
| | | | - John A Sweeney
- Department of Psychiatry, University of Cincinnati Medical Center, Cincinnati, OH, USA
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neurosciences, University of Chicago, Chicago, IL, USA
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Jeffrey R Bishop
- Department of Experimental and Clinical Pharmacology and Psychiatry, University of Minnesota, Minneapolis, MN, USA
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Book GA, Meda SA, Janssen R, Dager AD, Poppe A, Stevens MC, Assaf M, Glahn D, Pearlson GD. Effects of weather and season on human brain volume. PLoS One 2021; 16:e0236303. [PMID: 33760826 PMCID: PMC7990212 DOI: 10.1371/journal.pone.0236303] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 02/26/2021] [Indexed: 11/18/2022] Open
Abstract
We present an exploratory cross-sectional analysis of the effect of season and weather on Freesurfer-derived brain volumes from a sample of 3,279 healthy individuals collected on two MRI scanners in Hartford, CT, USA over a 15 year period. Weather and seasonal effects were analyzed using a single linear regression model with age, sex, motion, scan sequence, time-of-day, month of the year, and the deviation from average barometric pressure, air temperature, and humidity, as covariates. FDR correction for multiple comparisons was applied to groups of non-overlapping ROIs. Significant negative relationships were found between the left- and right- cerebellum cortex and pressure (t = -2.25, p = 0.049; t = -2.771, p = 0.017). Significant positive relationships were found between left- and right- cerebellum cortex and white matter between the comparisons of January/June and January/September. Significant negative relationships were found between several subcortical ROIs for the summer months compared to January. An opposing effect was observed between the supra- and infra-tentorium, with opposite effect directions in winter and summer. Cohen’s d effect sizes from monthly comparisons were similar to those reported in recent psychiatric big-data publications, raising the possibility that seasonal changes and weather may be confounds in large cohort studies. Additionally, changes in brain volume due to natural environmental variation have not been reported before and may have implications for weather-related and seasonal ailments.
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Affiliation(s)
- Gregory A. Book
- Olin Neuropsychiatry Research Center, Hartford Hospital, Hartford, CT, United States of America
- * E-mail:
| | - Shashwath A. Meda
- Olin Neuropsychiatry Research Center, Hartford Hospital, Hartford, CT, United States of America
| | - Ronald Janssen
- Olin Neuropsychiatry Research Center, Hartford Hospital, Hartford, CT, United States of America
| | - Alecia D. Dager
- Olin Neuropsychiatry Research Center, Hartford Hospital, Hartford, CT, United States of America
- Yale University, Department of Psychiatry, New Haven, CT, United States of America
| | - Andrew Poppe
- Olin Neuropsychiatry Research Center, Hartford Hospital, Hartford, CT, United States of America
| | - Michael C. Stevens
- Olin Neuropsychiatry Research Center, Hartford Hospital, Hartford, CT, United States of America
- Yale University, Department of Psychiatry, New Haven, CT, United States of America
| | - Michal Assaf
- Olin Neuropsychiatry Research Center, Hartford Hospital, Hartford, CT, United States of America
- Yale University, Department of Psychiatry, New Haven, CT, United States of America
| | - David Glahn
- Yale University, Department of Psychiatry, New Haven, CT, United States of America
- Boston Children’s Hospital, Department of Psychiatry, Boston, MA, United States of America
| | - Godfrey D. Pearlson
- Olin Neuropsychiatry Research Center, Hartford Hospital, Hartford, CT, United States of America
- Yale University, Department of Psychiatry, New Haven, CT, United States of America
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3
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Tamminga CA, Clementz BA, Pearlson G, Keshavan M, Gershon ES, Ivleva EI, McDowell J, Meda SA, Keedy S, Calhoun VD, Lizano P, Bishop JR, Hudgens-Haney M, Alliey-Rodriguez N, Asif H, Gibbons R. Biotyping in psychosis: using multiple computational approaches with one data set. Neuropsychopharmacology 2021; 46:143-155. [PMID: 32979849 PMCID: PMC7689458 DOI: 10.1038/s41386-020-00849-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [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: 05/28/2020] [Revised: 08/24/2020] [Accepted: 08/26/2020] [Indexed: 12/15/2022]
Abstract
Focusing on biomarker identification and using biomarkers individually or in clusters to define biological subgroups in psychiatry requires a re-orientation from behavioral phenomenology to quantifying brain features, requiring big data approaches for data integration. Much still needs to be accomplished, not only to refine but also to build support for the application and customization of such an analytical phenotypic approach. In this review, we present some of what Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) has learned so far to guide future applications of multivariate phenotyping and their analyses to understanding psychosis. This paper describes several B-SNIP projects that use phenotype data and big data computations to generate novel outcomes and glimpse what phenotypes contribute to disease understanding and, with aspiration, to treatment. The source of the phenotypes varies from genetic data, structural neuroanatomic localization, immune markers, brain physiology, and cognition. We aim to see guiding principles emerge and areas of commonality revealed. And, we will need to demonstrate not only data stability but also the usefulness of biomarker information for subgroup identification enhancing target identification and treatment development.
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Affiliation(s)
- Carol A. Tamminga
- grid.267313.20000 0000 9482 7121Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX 75390 USA
| | - Brett A. Clementz
- grid.213876.90000 0004 1936 738XDepartments of Psychology, Neuroscience, and BioImaging Research Center, University of Georgia, Athens, GA 30602 USA
| | - Godfrey Pearlson
- grid.277313.30000 0001 0626 2712Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT USA ,grid.47100.320000000419368710Departments of Psychiatry & Neuroscience, Yale University, New Haven, CT USA
| | - Macheri Keshavan
- grid.239395.70000 0000 9011 8547Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, United States
| | - Elliot S. Gershon
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL 60637 USA
| | - Elena I. Ivleva
- grid.267313.20000 0000 9482 7121Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX 75390 USA
| | - Jennifer McDowell
- grid.213876.90000 0004 1936 738XDepartments of Psychology, Neuroscience, and BioImaging Research Center, University of Georgia, Athens, GA 30602 USA
| | - Shashwath A. Meda
- grid.277313.30000 0001 0626 2712Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT USA ,grid.47100.320000000419368710Departments of Psychiatry & Neuroscience, Yale University, New Haven, CT USA
| | - Sarah Keedy
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL 60637 USA
| | - Vince D. Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia USA
| | - Paulo Lizano
- grid.239395.70000 0000 9011 8547Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, United States
| | - Jeffrey R. Bishop
- grid.17635.360000000419368657Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, United States ,grid.17635.360000000419368657Department of Psychiatry, University of Minnesota Medical School, Minneapolis, MN 55455 USA
| | - Matthew Hudgens-Haney
- grid.267313.20000 0000 9482 7121Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX 75390 USA
| | - Ney Alliey-Rodriguez
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL 60637 USA
| | - Huma Asif
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL 60637 USA
| | - Robert Gibbons
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL 60637 USA ,grid.170205.10000 0004 1936 7822Departments of Medicine and Public Health Sciences, University of Chicago, Chicago, Ill USA
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Chye Y, Mackey S, Gutman BA, Ching CR, Batalla A, Blaine S, Brooks S, Caparelli EC, Cousijn J, Dagher A, Foxe JJ, Goudriaan AE, Hester R, Hutchison K, Jahanshad N, Kaag AM, Korucuoglu O, Li CR, London ED, Lorenzetti V, Luijten M, Martin‐Santos R, Meda SA, Momenan R, Morales A, Orr C, Paulus MP, Pearlson G, Reneman L, Schmaal L, Sinha R, Solowij N, Stein DJ, Stein EA, Tang D, Uhlmann A, Holst R, Veltman DJ, Verdejo‐Garcia A, Wiers RW, Yücel M, Thompson PM, Conrod P, Garavan H. Subcortical surface morphometry in substance dependence: An ENIGMA addiction working group study. Addict Biol 2020; 25:e12830. [PMID: 31746534 DOI: 10.1111/adb.12830] [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] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Revised: 07/25/2019] [Accepted: 08/26/2019] [Indexed: 11/27/2022]
Abstract
While imaging studies have demonstrated volumetric differences in subcortical structures associated with dependence on various abused substances, findings to date have not been wholly consistent. Moreover, most studies have not compared brain morphology across those dependent on different substances of abuse to identify substance-specific and substance-general dependence effects. By pooling large multinational datasets from 33 imaging sites, this study examined subcortical surface morphology in 1628 nondependent controls and 2277 individuals with dependence on alcohol, nicotine, cocaine, methamphetamine, and/or cannabis. Subcortical structures were defined by FreeSurfer segmentation and converted to a mesh surface to extract two vertex-level metrics-the radial distance (RD) of the structure surface from a medial curve and the log of the Jacobian determinant (JD)-that, respectively, describe local thickness and surface area dilation/contraction. Mega-analyses were performed on measures of RD and JD to test for the main effect of substance dependence, controlling for age, sex, intracranial volume, and imaging site. Widespread differences between dependent users and nondependent controls were found across subcortical structures, driven primarily by users dependent on alcohol. Alcohol dependence was associated with localized lower RD and JD across most structures, with the strongest effects in the hippocampus, thalamus, putamen, and amygdala. Meanwhile, nicotine use was associated with greater RD and JD relative to nonsmokers in multiple regions, with the strongest effects in the bilateral hippocampus and right nucleus accumbens. By demonstrating subcortical morphological differences unique to alcohol and nicotine use, rather than dependence across all substances, results suggest substance-specific relationships with subcortical brain structures.
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Affiliation(s)
- Yann Chye
- Turner Institute for Brain and Mental Health, School of Psychological Sciences Monash University Clayton Victoria Australia
| | - Scott Mackey
- Departments of Psychiatry University of Vermont Burlington VT USA
| | - Boris A. Gutman
- Biomedical Engineering Illinois Institute of Technology Chicago IL USA
| | - Christopher R.K. Ching
- Department of Neurology, Keck School of Medicine, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute University of Southern California Los Angeles CA USA
| | - Albert Batalla
- Department of Psychiatry University Medical Centre Utrecht Brain Center, Utrecht University Utrecht The Netherlands
- Department of Psychiatry and Psychology, Hospital Clinic, IDIBAPS, CIBERSAM, Institute of Neuroscience University of Barcelona Barcelona Spain
| | - Sara Blaine
- Departments of Psychiatry and Neuroscience Yale University School of Medicine CT USA
| | - Samantha Brooks
- Faculty of Health, School of Psychology Liverpool John Moores University L3 3AF Liverpool UK
- Department of Neuroscience, Section of Functional Pharmacology Uppsala University 75240 Sweden
| | - Elisabeth C. Caparelli
- Neuroimaging Research Branch, Intramural Research Program National Institute of Drug Abuse Baltimore MD USA
| | - Janna Cousijn
- Department of Developmental Psychology University of Amsterdam The Netherlands
| | - Alain Dagher
- McConnell Brain Imaging Center, Montreal Neurological Institute McGill University Montreal Quebec Canada
| | - John J. Foxe
- Department of Neuroscience & The Ernest J. Del Monte Institute for Neuroscience University of Rochester School of Medicine and Dentistry Rochester NY USA
| | - Anna E. Goudriaan
- Amsterdam UMC, Department of Psychiatry, Amsterdam Institute for Addiction Research University of Amsterdam Amsterdam The Netherlands
- Department of Research and Quality of Care Arkin Mental Health Care Amsterdam The Netherlands
| | - Robert Hester
- Melbourne School of Psychological Sciences University of Melbourne Melbourne Victoria Australia
| | - Kent Hutchison
- Department of Psychology and Neuroscience University of Colorado Boulder Boulder CO USA
| | - Neda Jahanshad
- Department of Neurology, Keck School of Medicine, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute University of Southern California Los Angeles CA USA
| | - Anne M. Kaag
- Department of Developmental Psychology University of Amsterdam The Netherlands
| | - Ozlem Korucuoglu
- Department of Psychiatry Washington University School of Medicine Saint Louis MO USA
| | - Chiang‐Shan R. Li
- Departments of Psychiatry and Neuroscience Yale University School of Medicine CT USA
| | - Edythe D. London
- Jane and Terry Semel Institute of Neuroscience and Human Behavior, David Geffen School of Medicine Universityof California at Los Angeles Los Angeles CA USA
| | - Valentina Lorenzetti
- Turner Institute for Brain and Mental Health, School of Psychological Sciences Monash University Clayton Victoria Australia
- School of Psychology, Faculty of Health Sciences Australian Catholic University Melbourne Victoria Australia
| | - Maartje Luijten
- Behavioural Science Institute Radboud University Nijmegen The Netherlands
| | - Rocio Martin‐Santos
- Department of Psychiatry and Psychology, Hospital Clinic, IDIBAPS, CIBERSAM, Institute of Neuroscience University of Barcelona Barcelona Spain
| | - Shashwath A. Meda
- Olin Neuropsychiatry Research Center Hartford Hospital/IOL Hartford CT USA
| | - Reza Momenan
- Clinical NeuroImaging Research Core, Division of Intramural Clinical and BiologicalResearch National Institute of Alcohol Abuse and Alcoholism Bethesda MD USA
| | - Angelica Morales
- Jane and Terry Semel Institute of Neuroscience and Human Behavior, David Geffen School of Medicine Universityof California at Los Angeles Los Angeles CA USA
| | - Catherine Orr
- Departments of Psychiatry University of Vermont Burlington VT USA
| | - Martin P. Paulus
- VA San Diego Healthcare System and Department of Psychiatry University of California San Diego CA USA
- Laureate Institute for Brain Research Tulsa OK USA
| | - Godfrey Pearlson
- Departments of Psychiatry and Neuroscience Yale University School of Medicine CT USA
| | - Liesbeth Reneman
- Department of Radiology and Nuclear Medicine Amsterdam UMC, location AMC Amsterdam The Netherlands
| | - Lianne Schmaal
- Orygen The National Centre of Excellence in Youth Mental Health Parkville Australia
- Centre for Youth Mental Health The University of Melbourne Parkville Australia
| | - Rajita Sinha
- Departments of Psychiatry and Neuroscience Yale University School of Medicine CT USA
| | - Nadia Solowij
- School of Psychology and Illawarra Health and Medical Research Institute University of Wollongong Wollongong New South Wales Australia
- The Australian Centre for Cannabinoid Clinical and Research Excellence (ACRE) New Lambton Heights New South Wales Australia
| | - Dan J. Stein
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute University of Cape Town Cape Town South Africa
| | - Elliot A. Stein
- Neuroimaging Research Branch, Intramural Research Program National Institute of Drug Abuse Baltimore MD USA
| | - Deborah Tang
- McConnell Brain Imaging Center, Montreal Neurological Institute McGill University Montreal Quebec Canada
| | - Anne Uhlmann
- Department of Psychiatry and Mental Health Faculty of Health Sciences University of Cape Town South Africa
| | - Ruth Holst
- Department of Psychiatry University of Amsterdam Amsterdam The Netherlands
| | - Dick J. Veltman
- Department of Psychiatry VU University Medical Center Amsterdam The Netherlands
| | - Antonio Verdejo‐Garcia
- Turner Institute for Brain and Mental Health, School of Psychological Sciences Monash University Clayton Victoria Australia
| | - Reinout W. Wiers
- Addiction Development and Psychopathology (ADAPT) Lab University of Amsterdam Amsterdam The Netherlands
| | - Murat Yücel
- Turner Institute for Brain and Mental Health, School of Psychological Sciences Monash University Clayton Victoria Australia
| | - Paul M. Thompson
- Department of Neurology, Keck School of Medicine, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute University of Southern California Los Angeles CA USA
| | - Patricia Conrod
- Department of Psychiatry Université de Montreal, CHU Ste Justine Hospital Canada
| | - Hugh Garavan
- Departments of Psychiatry University of Vermont Burlington VT USA
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Ji L, Meda SA, Tamminga CA, Clementz BA, Keshavan MS, Sweeney JA, Gershon ES, Pearlson GD. Characterizing functional regional homogeneity (ReHo) as a B-SNIP psychosis biomarker using traditional and machine learning approaches. Schizophr Res 2020; 215:430-438. [PMID: 31439419 DOI: 10.1016/j.schres.2019.07.015] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [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: 07/17/2018] [Revised: 06/06/2019] [Accepted: 07/11/2019] [Indexed: 11/25/2022]
Abstract
BACKGROUND Recently, a biologically-driven psychosis classification (B-SNIP Biotypes) was derived using brain-based cognitive and electrophysiological markers. Here, we characterized a local functional-connectivity measure, regional homogeneity (ReHo), as a biomarker across Biotypes and conventional DSM diagnoses. METHODS Whole-brain ReHo measures of resting-state functional MRI were examined in psychosis patients and healthy controls organized by Biotype and by DSM-IV-TR diagnosis (n = 737). Group-level ANOVA and individual-level prediction models using support vector machines (SVM) were employed to evaluate the discriminative characteristics in comparisons of 1) DSM diagnostic groups, 2) Biotypes, to controls, and 3) within-proband subgroups with each other. RESULTS Probands grouped by Biotype versus controls showed a unique abnormality pattern: Biotype-1 displayed bidirectional ReHo differences in more widespread areas, with higher ReHo in para-hippocampus, fusiform, inferior temporal, cerebellum, thalamus and caudate, plus lower ReHo in the postcentral gyrus, middle temporal, cuneus, and middle occipital cortex; Biotype-2 and Biotype-3 showed lesser and unidirectional ReHo changes. Among diagnostic groups, only schizophrenia showed higher ReHo versus control values in the inferior/middle temporal area and fusiform gyrus. For within-patient comparisons, Biotype-1 showed characteristic ReHo when compared to Biotype-2 and Biotype-3. SVM results more accurately identified Biotypes than DSM diagnoses. CONCLUSION We characterized patterns of ReHo abnormalities across both Biotypes and DSM sub-groups. Both group-level statistical and machine-learning methods were more sensitive in capturing ReHo deficits in Biotypes than DSM. Overall ReHo is a robust psychosis biomarker.
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Affiliation(s)
- Lanxin Ji
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT, USA; Department of Psychiatry, Yale University, New Haven, CT, USA; Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China
| | - Shashwath A Meda
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT, USA
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Brett A Clementz
- Department of Psychology, University of Georgia, Athens, GA, USA
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Hospital, Harvard Medical School, Boston, MA, USA
| | - John A Sweeney
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Elliot S Gershon
- Department of Psychiatry, University of Chicago, Chicago, IL, USA
| | - Godfrey D Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT, USA; Department of Psychiatry, Yale University, New Haven, CT, USA; Department of Neuroscience, Yale University, New Haven, CT, USA.
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Alliey-Rodriguez N, Grey TA, Shafee R, Asif H, Lutz O, Bolo NR, Padmanabhan J, Tandon N, Klinger M, Reis K, Spring J, Coppes L, Zeng V, Hegde RR, Hoang DT, Bannai D, Nawaz U, Henson P, Liu S, Gage D, McCarroll S, Bishop JR, Hill S, Reilly JL, Lencer R, Clementz BA, Buckley P, Glahn DC, Meda SA, Narayanan B, Pearlson G, Keshavan MS, Ivleva EI, Tamminga C, Sweeney JA, Curtis D, Badner JA, Keedy S, Rapoport J, Liu C, Gershon ES. NRXN1 is associated with enlargement of the temporal horns of the lateral ventricles in psychosis. Transl Psychiatry 2019; 9:230. [PMID: 31530798 PMCID: PMC6748921 DOI: 10.1038/s41398-019-0564-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [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: 03/21/2019] [Revised: 07/11/2019] [Accepted: 07/30/2019] [Indexed: 12/19/2022] Open
Abstract
Schizophrenia, Schizoaffective, and Bipolar disorders share behavioral and phenomenological traits, intermediate phenotypes, and some associated genetic loci with pleiotropic effects. Volumetric abnormalities in brain structures are among the intermediate phenotypes consistently reported associated with these disorders. In order to examine the genetic underpinnings of these structural brain modifications, we performed genome-wide association analyses (GWAS) on 60 quantitative structural brain MRI phenotypes in a sample of 777 subjects (483 cases and 294 controls pooled together). Genotyping was performed with the Illumina PsychChip microarray, followed by imputation to the 1000 genomes multiethnic reference panel. Enlargement of the Temporal Horns of Lateral Ventricles (THLV) is associated with an intronic SNP of the gene NRXN1 (rs12467877, P = 6.76E-10), which accounts for 4.5% of the variance in size. Enlarged THLV is associated with psychosis in this sample, and with reduction of the hippocampus and enlargement of the choroid plexus and caudate. Eight other suggestively significant associations (P < 5.5E-8) were identified with THLV and 5 other brain structures. Although rare deletions of NRXN1 have been previously associated with psychosis, this is the first report of a common SNP variant of NRXN1 associated with enlargement of the THLV in psychosis.
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Affiliation(s)
- Ney Alliey-Rodriguez
- University of Chicago, Department of Psychiatry and Behavioral Neurosciences, Chicago, USA.
| | - Tamar A. Grey
- 0000 0001 2341 2786grid.116068.8Massachusetts Institute of Technology, Cambridge, USA
| | - Rebecca Shafee
- 000000041936754Xgrid.38142.3cHarvard Medical School, Department of Genetics, Boston, USA ,grid.66859.34Stanley Center, Broad Institute of MIT and Harvard, Cambridge, USA
| | - Huma Asif
- University of Chicago, Department of Psychiatry and Behavioral Neurosciences, Chicago, USA
| | - Olivia Lutz
- 000000041936754Xgrid.38142.3cHarvard Medical School, Department of Psychiatry, Boston, USA
| | - Nicolas R. Bolo
- 000000041936754Xgrid.38142.3cHarvard Medical School, Department of Psychiatry, Boston, USA
| | - Jaya Padmanabhan
- 000000041936754Xgrid.38142.3cHarvard Medical School, Department of Psychiatry, Boston, USA
| | - Neeraj Tandon
- 000000041936754Xgrid.38142.3cHarvard Medical School, Department of Psychiatry, Boston, USA
| | - Madeline Klinger
- University of Chicago, Department of Psychiatry and Behavioral Neurosciences, Chicago, USA
| | - Katherine Reis
- University of Chicago, Department of Psychiatry and Behavioral Neurosciences, Chicago, USA
| | - Jonathan Spring
- University of Chicago Laboratory for Advanced Computing, Chicago, USA
| | - Lucas Coppes
- University of Chicago, Department of Psychiatry and Behavioral Neurosciences, Chicago, USA
| | - Victor Zeng
- 000000041936754Xgrid.38142.3cHarvard University, Cambridge, USA
| | - Rachal R. Hegde
- 0000 0004 1936 7558grid.189504.1Boston University, Boston, USA
| | - Dung T. Hoang
- 000000041936754Xgrid.38142.3cHarvard University, Cambridge, USA
| | - Deepthi Bannai
- 0000 0004 1936 7558grid.189504.1Boston University, Boston, USA
| | - Uzma Nawaz
- 0000 0004 1936 7558grid.189504.1Boston University, Boston, USA
| | - Philip Henson
- 000000041936754Xgrid.38142.3cHarvard University, Cambridge, USA
| | - Siyuan Liu
- 0000 0001 2297 5165grid.94365.3dChild Psychiatry Branch, National Institutes of Mental Health, National Institutes of Health, Bethesda, MD USA
| | - Diane Gage
- grid.66859.34Broad Institute of MIT and Harvard, Cambridge, USA
| | | | - Jeffrey R. Bishop
- 0000000419368657grid.17635.36University of Minnesota, Department of Experimental and Clinical Pharmacology and Department of Psychiatry, Minneapolis, USA
| | - Scot Hill
- 0000 0004 0388 7807grid.262641.5Rosalind Franklin University, North Chicago, USA
| | - James L. Reilly
- 0000 0001 2299 3507grid.16753.36Northwestern University, Evanston, USA
| | - Rebekka Lencer
- 0000 0001 2172 9288grid.5949.1University of Muenster, Munster, Germany
| | - Brett A. Clementz
- 0000 0000 9564 9822grid.264978.6Department of Psychology, University of Georgia, Athens, Georgia
| | - Peter Buckley
- 0000 0004 0458 8737grid.224260.0Virginia Commonwealth University, Richmond, USA
| | - David C. Glahn
- 0000000419368710grid.47100.32Yale University Departments of Psychiatry & Neuroscience, New Haven, USA
| | - Shashwath A. Meda
- 0000000419368710grid.47100.32Yale University Departments of Psychiatry & Neuroscience, New Haven, USA
| | - Balaji Narayanan
- 0000000419368710grid.47100.32Yale University Departments of Psychiatry & Neuroscience, New Haven, USA
| | - Godfrey Pearlson
- 0000000419368710grid.47100.32Yale University Departments of Psychiatry & Neuroscience, New Haven, USA
| | - Matcheri S. Keshavan
- 000000041936754Xgrid.38142.3cHarvard Medical School, Department of Psychiatry, Boston, USA
| | - Elena I. Ivleva
- 0000 0000 9482 7121grid.267313.2University of Texas Southwestern Medical Center, Department of Psychiatry, Dallas, USA
| | - Carol Tamminga
- 0000 0000 9482 7121grid.267313.2University of Texas Southwestern Medical Center, Department of Psychiatry, Dallas, USA
| | - John A. Sweeney
- 0000 0000 9482 7121grid.267313.2University of Texas Southwestern Medical Center, Department of Psychiatry, Dallas, USA
| | - David Curtis
- 0000 0001 2171 1133grid.4868.2University College London and Centre for Psychiatry, Barts and the London School of Medicine and Dentistry, London, UK
| | - Judith A. Badner
- 0000 0001 0705 3621grid.240684.cRush University Medical Center, Chicago, USA
| | - Sarah Keedy
- University of Chicago, Department of Psychiatry and Behavioral Neurosciences, Chicago, USA
| | - Judith Rapoport
- 0000 0001 2297 5165grid.94365.3dChild Psychiatry Branch, National Institutes of Mental Health, National Institutes of Health, Bethesda, MD USA
| | - Chunyu Liu
- 0000 0000 9159 4457grid.411023.5SUNY Upstate Medical University, Binghamton, USA
| | - Elliot S. Gershon
- University of Chicago, Department of Psychiatry and Behavioral Neurosciences, Chicago, USA ,University of Chicago, Department of Human Genetics, Chicago, USA
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7
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Meda SA, Narayanan B, Chorlian D, Meyers JL, Gelernter J, Hesselbrock V, Bauer L, Calhoun VD, Porjesz B, Pearlson GD. Multivariate Analyses Reveal Biological Components Related to Neuronal Signaling and Immunity Mediating Electroencephalograms Abnormalities in Alcohol-Dependent Individuals from the Collaborative Study on the Genetics of Alcoholism Cohort. Alcohol Clin Exp Res 2019; 43:1462-1477. [PMID: 31009096 DOI: 10.1111/acer.14063] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [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: 11/13/2018] [Revised: 04/08/2019] [Accepted: 04/11/2019] [Indexed: 12/22/2022]
Abstract
BACKGROUND The underlying molecular mechanisms associated with alcohol use disorder (AUD) risk have only been partially revealed using traditional approaches such as univariate genomewide association and linkage-based analyses. We therefore aimed to identify gene clusters related to Electroencephalograms (EEG) neurobiological phenotypes distinctive to individuals with AUD using a multivariate approach. METHODS The current project adopted a bimultivariate data-driven approach, parallel independent component analysis (para-ICA), to derive and explore significant genotype-phenotype associations in a case-control subset of the Collaborative Study on the Genetics of Alcoholism (COGA) dataset. Para-ICA subjects comprised N = 799 self-reported European Americans (367 controls and 432 AUD cases), recruited from COGA, who had undergone resting EEG and genotyping. Both EEG and genomewide single nucleotide polymorphism (SNP) data were preprocessed prior to being subjected to para-ICA in order to derive genotype-phenotype relationships. RESULTS From the data, 4 EEG frequency and 4 SNP components were estimated, with 2 significantly correlated EEG-genetic relationship pairs. The first such pair primarily represented theta activity, negatively correlated with a genetic cluster enriched for (but not limited to) ontologies/disease processes representing cell signaling, neurogenesis, transmembrane drug transportation, alcoholism, and lipid/cholesterol metabolism. The second component pair represented mainly alpha activity, positively correlated with a genetic cluster with ontologies similarly enriched as the first component. Disease-related enrichments for this component revealed heart and autoimmune disorders as top hits. Loading coefficients for both the alpha and theta components were significantly reduced in cases compared to controls. CONCLUSIONS Our data suggest plausible multifactorial genetic components, primarily enriched for neuronal/synaptic signaling/transmission, immunity, and neurogenesis, mediating low-frequency alpha and theta abnormalities in alcohol addiction.
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Affiliation(s)
- Shashwath A Meda
- Olin Neuropsychiatry Research Center, Hartford Hospital/IOL, Hartford, Connecticut
| | - Balaji Narayanan
- Olin Neuropsychiatry Research Center, Hartford Hospital/IOL, Hartford, Connecticut
| | - David Chorlian
- Department of Psychiatry, SUNY Downstate Medical Center, Brooklyn, New York
| | - Jacquelyn L Meyers
- Department of Psychiatry, SUNY Downstate Medical Center, Brooklyn, New York
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | | | - Lance Bauer
- Department of Psychiatry, UConn Health, Farmington, Connecticut
| | | | - Bernice Porjesz
- Department of Psychiatry, SUNY Downstate Medical Center, Brooklyn, New York
| | - Godfrey D Pearlson
- Olin Neuropsychiatry Research Center, Hartford Hospital/IOL, Hartford, Connecticut.,Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
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8
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Gershon ES, Pearlson G, Keshavan MS, Tamminga C, Clementz B, Buckley PF, Alliey-Rodriguez N, Liu C, Sweeney JA, Keedy S, Meda SA, Tandon N, Shafee R, Bishop JR, Ivleva EI. Genetic analysis of deep phenotyping projects in common disorders. Schizophr Res 2018; 195:51-57. [PMID: 29056493 PMCID: PMC5910299 DOI: 10.1016/j.schres.2017.09.031] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [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: 07/02/2017] [Revised: 09/19/2017] [Accepted: 09/22/2017] [Indexed: 11/19/2022]
Abstract
Several studies of complex psychotic disorders with large numbers of neurobiological phenotypes are currently under way, in living patients and controls, and on assemblies of brain specimens. Genetic analyses of such data typically present challenges, because of the choice of underlying hypotheses on genetic architecture of the studied disorders and phenotypes, large numbers of phenotypes, the appropriate multiple testing corrections, limited numbers of subjects, imputations required on missing phenotypes and genotypes, and the cross-disciplinary nature of the phenotype measures. Advances in genotype and phenotype imputation, and in genome-wide association (GWAS) methods, are useful in dealing with these challenges. As compared with the more traditional single-trait analyses, deep phenotyping with simultaneous genome-wide analyses serves as a discovery tool for previously unsuspected relationships of phenotypic traits with each other, and with specific molecular involvements.
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Affiliation(s)
- Elliot S Gershon
- Department of Psychiatry, Department of Human Genetics, University of Chicago, United States.
| | - Godfrey Pearlson
- Yale University Departments of Psychiatry & Neuroscience, Hartford, CT, United States; Olin Neuropsychiatry Research Center, Institute of Living, Hartford, Connecticut, USA
| | | | - Carol Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Brett Clementz
- Department of Psychology, University of Georgia, Athens, GA, United States
| | - Peter F Buckley
- School of Medicine Virginia Commonwealth University (VCU), Richmond, VA, United States
| | - Ney Alliey-Rodriguez
- University of Chicago, Department of Psychiatry and Behavioral Neurosciences, Chicago, IL, United States
| | - Chunyu Liu
- University of Illinois at Chicago, Chicago, IL, United States
| | - John A Sweeney
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, United States; University of Cincinnati, Department of Psychiatry and Behavioral Neuroscience, Cincinnati, OH, United States
| | - Sarah Keedy
- University of Chicago, Department of Psychiatry and Behavioral Neurosciences, Chicago, IL, United States
| | - Shashwath A Meda
- Yale University Departments of Psychiatry & Neuroscience, Hartford, CT, United States
| | - Neeraj Tandon
- Beth Israel Deaconess Medical Center, Dept of Psychiatry, Harvard Medical School, United States
| | - Rebecca Shafee
- Broad Institute of MIT and Harvard, Cambridge, MA, United States; Department of Genetics, Harvard Medical School, United States
| | - Jeffrey R Bishop
- Department of Clinical and Experimental Pharmacology, University of Minnesota, Minneapolis, MN, United States
| | - Elena I Ivleva
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, United States
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9
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Meda SA, Hawkins KA, Dager AD, Tennen H, Khadka S, Austad CS, Wood RM, Raskin S, Fallahi CR, Pearlson GD. Longitudinal Effects of Alcohol Consumption on the Hippocampus and Parahippocampus in College Students. Biol Psychiatry Cogn Neurosci Neuroimaging 2018; 3:610-617. [PMID: 29680476 DOI: 10.1016/j.bpsc.2018.02.006] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Accepted: 02/20/2018] [Indexed: 12/11/2022]
Abstract
BACKGROUND The hazardous effects of alcohol consumption on both the hippocampus and memory have been well established. However, the longitudinal effects of ethanol on the developing brain and related consequences on memory are not well explored. Given the above, we investigated the longitudinal effects of college drinking on hippocampal volume in emerging college adults. METHODS Data were derived from the longitudinal Brain and Alcohol Research with College Students study. A subset of 146 freshmen (mean age at baseline = 18.5 years) underwent brain magnetic resonance imaging scans at baseline and 24 months later. Four drinking-related measures derived from monthly surveys were reduced to a single alcohol use index using principal component analysis. Gray matter volumetric change (GMV-c) data were derived using a longitudinal pipeline. Voxelwise hippocampal/para-hippocampal GMV-c associations with the drinking index were derived using a multiple regression framework within SPM12. Supplementary associations were assessed between GMV-c and memory scores computed from the California Verbal Learning Test-II (assessed at the end of the study), and between GMV-c and total alcohol-induced memory blackouts. RESULTS Larger alcohol use index was associated with an accelerated GMV decline in the hippocampus/para-hippocampus. Also, larger hippocampal volume decline was associated with poorer memory performance and more memory blackouts. CONCLUSIONS Our study extends prior cross-sectional literature by showing that a heavier drinking burden while in college is associated with greater hippocampal GMV decline that is in turn associated with poorer memory scores, all of which could ultimately have a significant impact on student success.
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Affiliation(s)
- Shashwath A Meda
- Olin Neuropsychiatry Research Center, Hartford HealthCare Corporation, Hartford, Connecticut.
| | - Keith A Hawkins
- Department of Psychiatry, Yale University, New Haven, Connecticut
| | - Alecia D Dager
- Olin Neuropsychiatry Research Center, Hartford HealthCare Corporation, Hartford, Connecticut; Department of Psychiatry, Yale University, New Haven, Connecticut
| | - Howard Tennen
- Department of Community Medicine, University of Connecticut School of Medicine, Farmington, Connecticut
| | - Sabin Khadka
- Olin Neuropsychiatry Research Center, Hartford HealthCare Corporation, Hartford, Connecticut
| | - Carol S Austad
- Department of Psychology, Central Connecticut State University, New Britain, Connecticut
| | - Rebecca M Wood
- Department of Psychology, Central Connecticut State University, New Britain, Connecticut
| | - Sarah Raskin
- Department of Psychology and Neurosciences, Trinity College, Hartford, Connecticut
| | - Carolyn R Fallahi
- Department of Psychology, Central Connecticut State University, New Britain, Connecticut
| | - Godfrey D Pearlson
- Olin Neuropsychiatry Research Center, Hartford HealthCare Corporation, Hartford, Connecticut; Department of Psychiatry, Yale University, New Haven, Connecticut; Department of Neuroscience, Yale University, New Haven, Connecticut
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10
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Meda SA, Dager AD, Hawkins KA, Tennen H, Raskin S, Wood RM, Austad CS, Fallahi CR, Pearlson GD. Heavy Drinking in College Students Is Associated with Accelerated Gray Matter Volumetric Decline over a 2 Year Period. Front Behav Neurosci 2017; 11:176. [PMID: 29033801 PMCID: PMC5627037 DOI: 10.3389/fnbeh.2017.00176] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2017] [Accepted: 09/07/2017] [Indexed: 12/11/2022] Open
Abstract
Background: Heavy and/or harmful alcohol use while in college is a perennial and significant public health issue. Despite the plethora of cross-sectional research suggesting deleterious effects of alcohol on the brain, there is a lack of literature investigating the longitudinal effects of alcohol consumption on the adolescent brain. We aim to probe the longitudinal effects of college drinking on gray matter change in students during this crucial neurodevelopmental period. Methods: Data were derived from the longitudinal Brain and Alcohol Research in College Students (BARCS) study of whom a subset underwent brain MRI scans at two time points 24 months apart. Students were young adults with a mean age at baseline of about 18.5 years. Based on drinking metrics assessed at both baseline and followup, subjects were classified as sustained abstainers/light drinkers (N = 45) or sustained heavy drinkers (N = 84) based on criteria established in prior literature. Gray matter volumetric change (GMV-c) maps were derived using the longitudinal DARTEL pipeline as implemented in SPM12. GMV-c maps were then subjected to a 1-sample and 2-sample t-test in SPM12 to determine within- and between-group GMV-c differences in drinking groups. Supplementary between-group differences were also computed at baseline only. Results: Within-group analysis revealed significant decline in GMV in both groups across the 2 year followup period. However, tissue loss in the sustained heavy drinking group was more significant, larger per region, and more widespread across regions compared to abstainers/light drinkers. Between-group analysis confirmed the above and showed a greater rate of GMV-c in the heavy drinking group in several brain regions encompassing inferior/medial frontal gyrus, parahippocampus, and anterior cingulate. Supplementary analyses suggest that some of the frontal differences existed at baseline and progressively worsened. Conclusion: Sustained heavy drinking while in college was associated with accelerated GMV decline in brain regions involved with executive functioning, emotional regulation, and memory, which are critical to everyday life functioning. Areas of significant GMV decreases also overlapped largely with brain reward and stress systems implicated in addictive behavior.
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Affiliation(s)
- Shashwath A Meda
- Olin Neuropsychiatry Research Center, Hartford HealthCare Corporation, Hartford, CT, United States
| | - Alecia D Dager
- Olin Neuropsychiatry Research Center, Hartford HealthCare Corporation, Hartford, CT, United States.,Department of Psychiatry, Yale University, New Haven, CT, United States
| | - Keith A Hawkins
- Department of Psychiatry, Yale University, New Haven, CT, United States
| | - Howard Tennen
- Department of Community Medicine, University of Connecticut School of Medicine, Farmington, CT, United States
| | - Sarah Raskin
- Department of Psychology and Neurosciences, Trinity College, Hartford, CT, United States
| | - Rebecca M Wood
- Department of Psychology, Central Connecticut State University, New Britain, CT, United States
| | - Carol S Austad
- Department of Psychology, Central Connecticut State University, New Britain, CT, United States
| | - Carolyn R Fallahi
- Department of Psychology, Central Connecticut State University, New Britain, CT, United States
| | - Godfrey D Pearlson
- Olin Neuropsychiatry Research Center, Hartford HealthCare Corporation, Hartford, CT, United States.,Department of Psychiatry, Yale University, New Haven, CT, United States.,Department of Neuroscience, Yale University, New Haven, CT, United States
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11
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Ivleva EI, Clementz BA, Dutcher AM, Arnold SJ, Jeon-Slaughter H, Aslan S, Witte B, Poudyal G, Lu H, Meda SA, Pearlson GD, Sweeney JA, Keshavan MS, Tamminga CA. Brain Structure Biomarkers in the Psychosis Biotypes: Findings From the Bipolar-Schizophrenia Network for Intermediate Phenotypes. Biol Psychiatry 2017; 82:26-39. [PMID: 27817844 PMCID: PMC6501573 DOI: 10.1016/j.biopsych.2016.08.030] [Citation(s) in RCA: 100] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2016] [Revised: 08/17/2016] [Accepted: 08/17/2016] [Indexed: 11/27/2022]
Abstract
BACKGROUND The current definitions of psychotic illness lack biological validity, motivating alternative biomarker-driven disease entities. Building on experimental constructs-Biotypes-that were previously developed from cognitive and neurophysiologic measures, we contrast brain anatomy characteristics across Biotypes alongside conventional diagnoses, examining gray matter density (GMD) as an independent validator for the Biotypes. METHODS Whole brain GMD measures were examined in probands, their relatives, and healthy subjects organized by Biotype and then by DSM-IV-TR diagnosis (n = 1409) using voxel-based morphometry with subsequent subject-level regional characterization and distribution analyses. RESULTS Probands grouped by Biotype versus healthy controls showed a stepwise pattern of GMD reductions as follows: Biotype1, extensive and diffusely distributed GMD loss, with the largest effects in frontal, anterior/middle cingulate cortex, and temporal regions; Biotype2, intermediate and more localized reductions, with the largest effects in insula and frontotemporal regions; and Biotype3, small reductions localized to anterior limbic regions. Relatives showed regionally distinct GMD reductions versus healthy controls, with primarily anterior (frontotemporal) effects in Biotype1; posterior (temporo-parieto-cerebellar) in Biotype2; and normal GMD in Biotype3. Schizophrenia and schizoaffective probands versus healthy controls showed overlapping GMD reductions, with the largest effects in frontotemporal and parietal regions; psychotic bipolar probands had small reductions, primarily in frontal regions. GMD changes in relatives followed regional patterns observed in probands, albeit less extensive. Biotypes showed stronger between-group separation based on GMD than the conventional diagnoses and were the strongest predictor of GMD change. CONCLUSIONS GMD biomarkers depicted unique brain structure characteristics within Biotypes, consistent with their cognitive and sensorimotor profiles, and provided stronger discrimination for biologically driven biotypes than symptom-based diagnoses.
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Affiliation(s)
| | | | | | | | | | - Sina Aslan
- Advance MRI, LLC, Frisco,University of Texas at Dallas, Richardson, Texas
| | - Bradley Witte
- University of Texas Southwestern Medical Center, Dallas
| | | | - Hanzhang Lu
- University of Texas Southwestern Medical Center, Dallas,Johns Hopkins University, Baltimore, Maryland
| | | | - Godfrey D. Pearlson
- Institute of Living/Hartford Hospital, Hartford,Yale School of Medicine, New Haven, Connecticut
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12
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Polimanti R, Meda SA, Pearlson GD, Zhao H, Sherva R, Farrer LA, Kranzler HR, Gelernter J. S100A10 identified in a genome-wide gene × cannabis dependence interaction analysis of risky sexual behaviours. J Psychiatry Neurosci 2017; 42:252-261. [PMID: 28418321 PMCID: PMC5487272 DOI: 10.1503/jpn.160189] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [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] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND We conducted a genome-wide gene × environment interaction analysis to identify genetic variants that interact with cannabis dependence (CaD) in influencing risky sexual behaviours (RSB). METHODS Our sample included cannabis-exposed and sexually experienced African-American and European-American participants. A DSM-IV CaD diagnosis and RSB were evaluated using the Semi-Structured Assessment for Drug Dependence and Alcoholism. We analyzed RSBs as a score that takes into account experiences of unprotected sex and multiple sexual partners. RESULTS A total of 3350 people participated in our study; 43% had a CaD diagnosis, 56% were African-American and 33% were women. We identified a genome-wide significant locus in African-American participants (S100A10 rs72993629, p = 2.73 × 10-8) and a potential transpopulation signal in women (CLTC rs12944716, p = 5.27 × 10-8). A resting-state fMRI follow-up analysis of S100A10 rs72993629 conducted in an independent cohort showed 2 significant associations: reduced power of the left paracentral lobule in amplitude of low frequency fluctuations (ALFF) analysis (p = 7.8 × 10-3) and reduced power of the right pallidum in fractional ALFF analysis (p = 4.6 × 10-3). The activity of these brain regions is known to be involved in sexual functions and behaviours. The S100A10 result functionally recapitulated our S100B finding observed in our previous genome-wide association study of CaD. The probability of identifying 2 S100 genes in 2 independent genome-wide investigations by chance is approximately 1 in 1.1 million. LIMITATIONS We were not able to identify any African-American cohort with appropriate sample size, and phenotypic assessment is available to replicate our findings. CONCLUSION The S100A10 and S100B genes, which are located on different chromosomes, encode specialized calcium-binding proteins. These data support a role for calcium homeostasis in individuals with CaD and its induced behaviours.
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Affiliation(s)
| | | | | | | | | | | | | | - Joel Gelernter
- Correspondence to: J. Gelernter, Yale University School of Medicine, Department of Psychiatry, 950 Campbell Ave., West Haven, CT 06516;
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13
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Tandon N, Nanda P, Padmanabhan JL, Mathew IT, Eack SM, Narayanan B, Meda SA, Bergen SE, Ruaño G, Windemuth A, Kocherla M, Petryshen TL, Clementz B, Sweeney J, Tamminga C, Pearlson G, Keshavan MS. Novel gene-brain structure relationships in psychotic disorder revealed using parallel independent component analyses. Schizophr Res 2017; 182:74-83. [PMID: 27789186 DOI: 10.1016/j.schres.2016.10.026] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2016] [Revised: 10/14/2016] [Accepted: 10/16/2016] [Indexed: 01/13/2023]
Abstract
BACKGROUND Schizophrenia, schizoaffective disorder, and psychotic bipolar disorder overlap with regard to symptoms, structural and functional brain abnormalities, and genetic risk factors. Neurobiological pathways connecting genes to clinical phenotypes across the spectrum from schizophrenia to psychotic bipolar disorder remain largely unknown. METHODS We examined the relationship between structural brain changes and risk alleles across the psychosis spectrum in the multi-site Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) cohort. Regional MRI brain volumes were examined in 389 subjects with a psychotic disorder (139 schizophrenia, 90 schizoaffective disorder, and 160 psychotic bipolar disorder) and 123 healthy controls. 451,701 single-nucleotide polymorphisms were screened and processed using parallel independent component analysis (para-ICA) to assess associations between genes and structural brain abnormalities in probands. RESULTS 482 subjects were included after quality control (364 individuals with psychotic disorder and 118 healthy controls). Para-ICA identified four genetic components including several risk genes already known to contribute to schizophrenia and bipolar disorder and revealed three structural components that showed overlapping relationships with the disease risk genes across the three psychotic disorders. Functional ontologies representing these gene clusters included physiological pathways involved in brain development, synaptic transmission, and ion channel activity. CONCLUSIONS Heritable brain structural findings such as reduced cortical thickness and surface area in probands across the psychosis spectrum were associated with somewhat distinct genes related to putative disease pathways implicated in psychotic disorders. This suggests that brain structural alterations might represent discrete psychosis intermediate phenotypes along common neurobiological pathways underlying disease expression across the psychosis spectrum.
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Affiliation(s)
- Neeraj Tandon
- Psychiatry, Harvard Medical School, Beth Israel Deaconess Medical Ctr, Boston, MA, USA; Baylor College of Medicine, Texas Medical Center, Houston, TX, USA.
| | - Pranav Nanda
- Psychiatry, Harvard Medical School, Beth Israel Deaconess Medical Ctr, Boston, MA, USA; College of Physicians & Surgeons, Columbia University Medical Center, New York, NY, USA
| | - Jaya L Padmanabhan
- Psychiatry, Harvard Medical School, Beth Israel Deaconess Medical Ctr, Boston, MA, USA
| | - Ian T Mathew
- Psychiatry, Harvard Medical School, Beth Israel Deaconess Medical Ctr, Boston, MA, USA
| | - Shaun M Eack
- School of Social Work, University of Pittsburgh, Pittsburgh, PA, USA
| | - Balaji Narayanan
- Olin Neuropsychiatry Research Center, Hartford, CT, USA; Department of Psychiatry and Neurobiology, Yale University, New Haven, CT, USA
| | - Shashwath A Meda
- Olin Neuropsychiatry Research Center, Hartford, CT, USA; Department of Psychiatry and Neurobiology, Yale University, New Haven, CT, USA
| | - Sarah E Bergen
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research and Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | | | | | | | - Tracey L Petryshen
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research and Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Brett Clementz
- Department of Psychology, Department of Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA, USA
| | | | | | - Godfrey Pearlson
- Olin Neuropsychiatry Research Center, Hartford, CT, USA; Department of Psychiatry and Neurobiology, Yale University, New Haven, CT, USA
| | - Matcheri S Keshavan
- Psychiatry, Harvard Medical School, Beth Israel Deaconess Medical Ctr, Boston, MA, USA
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14
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Meda SA, Gueorguieva RV, Pittman B, Rosen RR, Aslanzadeh F, Tennen H, Leen S, Hawkins K, Raskin S, Wood RM, Austad CS, Dager A, Fallahi C, Pearlson GD. Longitudinal influence of alcohol and marijuana use on academic performance in college students. PLoS One 2017; 12:e0172213. [PMID: 28273162 PMCID: PMC5342177 DOI: 10.1371/journal.pone.0172213] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [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: 10/07/2016] [Accepted: 02/01/2017] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Alcohol and marijuana are the two most abused substances in US colleges. However, research on the combined influence (cross sectional or longitudinal) of these substances on academic performance is currently scant. METHODS Data were derived from the longitudinal 2-year Brain and Alcohol Research in College Students (BARCS) study including 1142 freshman students who completed monthly marijuana use and alcohol consumption surveys. Subjects were classified into data-driven groups based on their alcohol and marijuana consumption. A linear mixed-model (LMM) was employed using this grouping factor to predict grade point average (GPA), adjusted for a variety of socio-demographic and clinical factors. RESULTS Three data-driven clusters emerged: 1) No/low users of both, 2) medium-high alcohol/no-low marijuana, and 3) medium-high users of both substances. Individual cluster derivations between consecutive semesters remained stable. No significant interaction between clusters and semester (time) was noted. Post-hoc analysis suggest that at the outset, compared to sober peers, students using moderate to high levels of alcohol and low marijuana demonstrate lower GPAs, but this difference becomes non-significant over time. In contrast, students consuming both substances at moderate-to-high levels score significantly lower at both the outset and across the 2-year investigation period. Our follow-up analysis also indicate that when students curtailed their substance use over time they had significantly higher academic GPA compared to those who remained stable in their substance use patterns over the two year period. CONCLUSIONS Overall, our study validates and extends the current literature by providing important implications of concurrent alcohol and marijuana use on academic achievement in college.
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Affiliation(s)
- Shashwath A. Meda
- Olin Neuropsychiatry Research Center, Hartford HealthCare Corporation, Hartford, Connecticut, United States of America
| | - Ralitza V. Gueorguieva
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America
- Department of Psychiatry, Yale University, New Haven, Connecticut, United States of America
| | - Brian Pittman
- Department of Psychiatry, Yale University, New Haven, Connecticut, United States of America
| | - Rivkah R. Rosen
- Olin Neuropsychiatry Research Center, Hartford HealthCare Corporation, Hartford, Connecticut, United States of America
| | - Farah Aslanzadeh
- Olin Neuropsychiatry Research Center, Hartford HealthCare Corporation, Hartford, Connecticut, United States of America
| | - Howard Tennen
- Department of Psychology and Neurosciences, Trinity College, Hartford, Connecticut, United States of America
| | - Samantha Leen
- Olin Neuropsychiatry Research Center, Hartford HealthCare Corporation, Hartford, Connecticut, United States of America
| | - Keith Hawkins
- Department of Psychiatry, Yale University, New Haven, Connecticut, United States of America
| | - Sarah Raskin
- Department of Community Medicine, University of Connecticut School of Medicine, Farmington, Connecticut, United States of America
| | - Rebecca M. Wood
- Department of Psychology, Central Connecticut State University, New Britain, Connecticut, United States of America
| | - Carol S. Austad
- Department of Psychology, Central Connecticut State University, New Britain, Connecticut, United States of America
| | - Alecia Dager
- Olin Neuropsychiatry Research Center, Hartford HealthCare Corporation, Hartford, Connecticut, United States of America
- Department of Psychiatry, Yale University, New Haven, Connecticut, United States of America
| | - Carolyn Fallahi
- Department of Psychology, Central Connecticut State University, New Britain, Connecticut, United States of America
| | - Godfrey D. Pearlson
- Olin Neuropsychiatry Research Center, Hartford HealthCare Corporation, Hartford, Connecticut, United States of America
- Department of Psychiatry, Yale University, New Haven, Connecticut, United States of America
- Department of Neurobiology, Yale University, New Haven, Connecticut, United States of America
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Meda SA, Clementz BA, Sweeney JA, Keshavan MS, Tamminga CA, Ivleva EI, Pearlson GD. Examining Functional Resting-State Connectivity in Psychosis and Its Subgroups in the Bipolar-Schizophrenia Network on Intermediate Phenotypes Cohort. Biol Psychiatry Cogn Neurosci Neuroimaging 2016; 1:488-497. [PMID: 29653095 DOI: 10.1016/j.bpsc.2016.07.001] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2016] [Revised: 07/06/2016] [Accepted: 07/07/2016] [Indexed: 01/27/2023]
Abstract
BACKGROUND We sought to examine resting-state functional magnetic resonance imaging connectivity measures in psychotic patients to both identify cumulative differences across psychosis and subsequently probe deficits across conventional DSM-IV diagnoses and a newly identified classification using cognitive/neurophysiological data (Biotypes). METHODS We assessed 1125 subjects, including healthy control subjects, probands (schizophrenia, schizoaffective disorder, psychotic bipolar disorder), and relatives of probands. Probands and relatives were also segregated into Biotype groups (B1-B3, B1R-B3R using a method reported previously). Empirical resting-state functional magnetic resonance imaging networks were derived using independent component analysis. Global psychosis-related abnormalities were first identified. Subsequent post hoc t tests were performed across various diagnostic categories. Follow-up linear mixed model compared significance of within-proband differences across categories. Secondary analyses assessed correlations with biological profile scores. RESULTS Voxelwise tests between proband and control subjects revealed nine abnormal networks. Post hoc analysis revealed lower connectivity in most networks for all proband subgroups (DSM and Biotypes). Within-proband effect sizes of discrimination were marginally better for Biotypes over DSM. Reduced connectivity was noted in relatives of patients with schizophrenia in two networks and relatives of patients with psychotic bipolar disorder in one network. Biotype relatives showed similar deficits in one network. Connectivity deficits across four networks were significantly associated with cognitive control profile scores. CONCLUSIONS Overall, we found psychosis-related connectivity deficits in nine large-scale networks. Deficits in these networks tracked more closely with cognitive control factors, suggesting potential implications for disease profiling and therapeutic intervention. Biotypes performed marginally better in terms of separating out psychosis subgroups compared with conventional DSM or psychiatric diagnoses.
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Affiliation(s)
- Shashwath A Meda
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, Connecticut.
| | - Brett A Clementz
- Department of Psychology, University of Georgia, Athens, Georgia
| | - John A Sweeney
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Hospital, Harvard Medical School, Boston, Massachusetts
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Elena I Ivleva
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Godfrey D Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, Connecticut; Department of Psychiatry, Yale University, New Haven, Connecticut; Department of Neuroscience, Yale University, New Haven, Connecticut
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16
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Meda SA, Wang Z, Ivleva EI, Poudyal G, Keshavan MS, Tamminga CA, Sweeney JA, Clementz BA, Schretlen DJ, Calhoun VD, Lui S, Damaraju E, Pearlson GD. Frequency-Specific Neural Signatures of Spontaneous Low-Frequency Resting State Fluctuations in Psychosis: Evidence From Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) Consortium. Schizophr Bull 2015; 41:1336-48. [PMID: 26012519 PMCID: PMC4601713 DOI: 10.1093/schbul/sbv064] [Citation(s) in RCA: 80] [Impact Index Per Article: 8.9] [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: 02/05/2023]
Abstract
BACKGROUND We quantified frequency-specific, absolute, and fractional amplitude of low-frequency fluctuations (ALFF/fALFF) across the schizophrenia (SZ)-psychotic bipolar disorder (PBP) psychosis spectrum using resting functional magnetic resonance imaging data from the large BSNIP family study. METHODS We assessed 242 healthy controls (HC), 547 probands (180 PBP, 220 SZ, and 147 schizoaffective disorder-SAD), and 410 of their first-degree relatives (134 PBPR, 150SZR, and 126 SADR). Following standard preprocessing in statistical parametric mapping (SPM8), we computed absolute and fractional power (ALFF/fALFF) in 2 low-frequency bands: slow-5 (0.01-0.027 Hz) and slow-4 (0.027-0.073 Hz). We evaluated voxelwise post hoc differences across traditional Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition diagnostic categories. RESULTS Across ALFF/fALFF, in contrast to HC, BP/SAD showed hypoactivation in frontal/anterior brain regions in the slow-5 band and hypoactivation in posterior brain regions in the slow-4 band. SZ showed consistent hypoactivation in precuneus/cuneus and posterior cingulate across both bands and indices. Increased ALFF/fALFF was noted predominantly in deep subcortical and temporal structures across probands in both bands and indices. Across probands, spatial ALFF/fALFF differences in SAD resembled PBP more than SZ. None of these ALFF/fALFF differences were detected in relatives. CONCLUSIONS Results suggest ALFF/fALFF is a putative biomarker rather than a familial endophenotype. Overall sensitivity to discriminate proband brain alteration was stronger for fALFF than ALFF. Patterns of differences noted in SAD were more similar to those observed in PBP. Differential effects were noted across the 2 frequency bands, more prominently for BP/SAD compared with SZ, suggesting frequency-sensitive physiologic mechanisms for the former.
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Affiliation(s)
- Shashwath A. Meda
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT;,*To whom correspondence should be addressed; 200 Retreat Avenue, Olin Neuropsychiatry Research Center, Hartford Hospital/IOL, Hartford, CT 06102, US; tel: 860-545-7483, fax: 860-545-7797, e-mail:
| | - Zheng Wang
- Mental Health Institute of the Second Xiangya Hospital, Key Laboratory of Psychiatry and Mental Health of Hunan Province, Central South University, Changsha, Hunan, China
| | - Elena I. Ivleva
- Department of Psychiatry, University of Texas Southwestern Medical School, Dallas, TX
| | - Gaurav Poudyal
- Department of Psychiatry, University of Texas Southwestern Medical School, Dallas, TX
| | | | - Carol A. Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical School, Dallas, TX
| | - John A. Sweeney
- Department of Psychiatry, University of Texas Southwestern Medical School, Dallas, TX
| | | | | | | | - Su Lui
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | | | - Godfrey D. Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT;,Department of Psychiatry, Yale University, New Haven, CT;,Department of Neurobiology, Yale University, New Haven, CT
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Yarosh HL, Meda SA, de Wit H, Hart AB, Pearlson GD. Multivariate analysis of subjective responses to d-amphetamine in healthy volunteers finds novel genetic pathway associations. Psychopharmacology (Berl) 2015; 232:2781-94. [PMID: 25843748 PMCID: PMC4504822 DOI: 10.1007/s00213-015-3914-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [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: 12/25/2014] [Accepted: 03/06/2015] [Indexed: 11/24/2022]
Abstract
RATIONALE Researchers studying behavioral and physiologic effects of d-amphetamine have explored individual response differences to the drug. Concurrently, genome-wide analyses have identified several single-nucleotide polymorphisms (SNPs) associated with these traits. Univariate methods can identify SNPs associated with behavioral and physiological traits, but multivariate analyses allow identification of clusters of related biologically relevant SNPs and behavioral components. OBJECTIVES The aim of the study was to identify clusters of related biologically relevant SNPs and behavioral components in the responses of healthy individuals to d-amphetamine using multivariate analysis. METHODS Individuals (N = 375) without substance abuse histories completed surveys and detailed cardiovascular monitoring during randomized, blinded sessions: d-amphetamine (10 and 20 mg) and placebo. We applied parallel independent component analysis (Para-ICA) to data previously analyzed with univariate approaches, revealing new associations between genes and behavioral responses to d-amphetamine. RESULTS Three significantly associated (p < .001) phenotype-genotype pairs emerged. The first component included physiologic measures of systolic and diastolic blood pressure (BP) and mean arterial pressure (MAP) along with SNPs in calcium and glutamatergic signaling pathways. The second associated components included the "Anger" items from the Profile of Mood States (POMS) questionnaire and the marijuana effects from the Addiction Research Center Inventory (Cuyas, Verdejo-Garcia et al.), with enriched genetic pathways involved in cardiomyopathy and MAPK signaling. The final pair included "Anxious," "Fatigue," and "Confusion" items from the POMS questionnaire, plus functional pathways related to cardiac muscle contraction and cardiomyopathy. CONCLUSIONS Multifactorial genetic networks related to calcium signaling, glutamatergic and dopaminergic synapse function, and amphetamine addiction appear to mediate common behavioral and cardiovascular responses to d-amphetamine.
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Affiliation(s)
- Haley L. Yarosh
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, Connecticut,Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Shashwath A. Meda
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, Connecticut
| | - Harriet de Wit
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois
| | - Amy B. Hart
- Department of Human Genetics, University of Chicago, Chicago, Illinois
| | - Godfrey D. Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, Connecticut,Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut,Department of Neurobiology, Yale University School of Medicine, New Haven, Connecticut
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18
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Wang Z, Meda SA, Keshavan MS, Tamminga CA, Sweeney JA, Clementz BA, Schretlen DJ, Calhoun VD, Lui S, Pearlson GD. Large-Scale Fusion of Gray Matter and Resting-State Functional MRI Reveals Common and Distinct Biological Markers across the Psychosis Spectrum in the B-SNIP Cohort. Front Psychiatry 2015; 6:174. [PMID: 26732139 PMCID: PMC4685049 DOI: 10.3389/fpsyt.2015.00174] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [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: 08/19/2015] [Accepted: 11/27/2015] [Indexed: 02/05/2023] Open
Abstract
To investigate whether aberrant interactions between brain structure and function present similarly or differently across probands with psychotic illnesses [schizophrenia (SZ), schizoaffective disorder (SAD), and bipolar I disorder with psychosis (BP)] and whether these deficits are shared with their first-degree non-psychotic relatives. A total of 1199 subjects were assessed, including 220 SZ, 147 SAD, 180 psychotic BP, 150 first-degree relatives of SZ, 126 SAD relatives, 134 BP relatives, and 242 healthy controls (1). All subjects underwent structural MRI (sMRI) and resting-state functional MRI (rs-fMRI) scanning. Joint-independent component analysis (jICA) was used to fuse sMRI gray matter and rs-fMRI amplitude of low-frequency fluctuations data to identify the relationship between the two modalities. jICA revealed two significantly fused components. The association between functional brain alteration in a prefrontal-striatal-thalamic-cerebellar network and structural abnormalities in the default mode network was found to be common across psychotic diagnoses and correlated with cognitive function, social function, and schizo-bipolar scale scores. The fused alteration in the temporal lobe was unique to SZ and SAD. The above effects were not seen in any relative group (including those with cluster-A personality). Using a multivariate-fused approach involving two widely used imaging markers, we demonstrate both shared and distinct biological traits across the psychosis spectrum. Furthermore, our results suggest that the above traits are psychosis biomarkers rather than endophenotypes.
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Affiliation(s)
- Zheng Wang
- Mental Health Institute of the Second Xiangya Hospital, Central South University , Changsha , China
| | - Shashwath A Meda
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital , Hartford, CT , USA
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Hospital, Harvard Medical School , Boston, MA , USA
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center , Dallas, TX , USA
| | - John A Sweeney
- Department of Psychiatry, University of Texas Southwestern Medical Center , Dallas, TX , USA
| | - Brett A Clementz
- Department of Psychology, University of Georgia , Athens, GA , USA
| | - David J Schretlen
- Department of Psychiatry, Johns Hopkins University , Baltimore, MD , USA
| | - Vince D Calhoun
- Department of Psychiatry, Johns Hopkins University, Baltimore, MD, USA; The Mind Research Network, Albuquerque, NM, USA; Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Su Lui
- Department of Radiology, Huaxi MR Research Center, West China Hospital of Sichuan University , Chengdu , China
| | - Godfrey D Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT, USA; Department of Psychiatry, Yale University, New Haven, CT, USA
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19
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Abstract
Deficits in response inhibition and error processing can result in maladaptive behavior, including failure to use past mistakes to inform present decisions. A specific deficit in inhibiting a prepotent response represents one aspect of impulsivity and is a prominent feature of addictive behaviors in general, including cocaine abuse/dependence. Brain regions implicated in cognitive control exhibit reduced activation in cocaine abusers. The purposes of the present investigation were (1) to identify neural differences associated with error processing in current and former cocaine-dependent individuals compared to healthy controls and (2) to determine whether former, long-term abstinent cocaine users showed similar differences compared with current users. The present study used an fMRI Go/No-Go task to investigate differences in BOLD response to correct rejections and false alarms between current cocaine users (n = 30), former cocaine users (n = 29), and healthy controls (n = 35). Impulsivity trait measures were also assessed and compared with BOLD activity. Nineteen regions of interest previously implicated in errors of disinhibition were queried. There were no group differences in the correct rejections condition, but both current and former users exhibited increased BOLD response relative to controls for false alarms. In current users, the pregenual cingulate gyrus and left angular/supramarginal gyri overactivated. In former users, the right middle frontal/precentral gyri, right inferior parietal lobule, and left angular/supramarginal gyri overactivated. Overall, our results support a hypothesis that neural activity in former users differs more from healthy controls than that of current users due to cognitive compensation that facilitates abstinence.
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Affiliation(s)
- Brian C Castelluccio
- Olin Neuropsychiatric Research Center, Institute of Living, Hartford Hospital, 200 Retreat Avenue, Whitehall Building, Hartford, CT, 06106, USA,
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Koran MEI, Hohman TJ, Meda SA, Thornton-Wells TA. Genetic interactions within inositol-related pathways are associated with longitudinal changes in ventricle size. J Alzheimers Dis 2014; 38:145-54. [PMID: 24077433 DOI: 10.3233/jad-130989] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
The genetic etiology of late-onset Alzheimer's disease (LOAD) has proven complex, involving clinical and genetic heterogeneity and gene-gene interactions. Recent genome wide association studies in LOAD have led to the discovery of novel genetic risk factors; however, the investigation of gene-gene interactions has been limited. Conventional genetic studies often use binary disease status as the primary phenotype, but for complex brain-based diseases, neuroimaging data can serve as quantitative endophenotypes that correlate with disease status and closely reflect pathological changes. In the Alzheimer's Disease Neuroimaging Initiative cohort, we tested for association of genetic interactions with longitudinal MRI measurements of the inferior lateral ventricles (ILVs), which have repeatedly shown a relationship to LOAD status and progression. We performed linear regression to evaluate the ability of pathway-derived SNP-SNP pairs to predict the slope of change in volume of the ILVs. After Bonferroni correction, we identified four significant interactions in the right ILV (RILV) corresponding to gene-gene pairs SYNJ2-PI4KA, PARD3-MYH2, PDE3A-ABHD12B, and OR2L13-PRKG1 and one significant interaction in the left ILV (LILV) corresponding to SYNJ2-PI4KA. The SNP-SNP interaction corresponding to SYNJ2-PI4KA was identical in the RILV and LILV and was the most significant interaction in each (RILV: p = 9.13 × 10(-12); LILV: p = 8.17 × 10(-13)). Both genes belong to the inositol phosphate signaling pathway which has been previously associated with neurodegeneration in AD and we discuss the possibility that perturbation of this pathway results in a down-regulation of the Akt cell survival pathway and, thereby, decreased neuronal survival, as reflected by increased volume of the ventricles.
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Affiliation(s)
- Mary Ellen I Koran
- Center for Human Genetics and Research, Department of Molecular Physiology & Biophysics, Vanderbilt University School of Medicine, Nashville, TN, USA Medical Scientist Training Program, Vanderbilt University School of Medicine, Nashville, TN, USA
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21
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Koran MEI, Hohman TJ, Edwards CM, Vega JN, Pryweller JR, Slosky LE, Crockett G, Villa de Rey L, Meda SA, Dankner N, Avery SN, Blackford JU, Dykens EM, Thornton-Wells TA. Differences in age-related effects on brain volume in Down syndrome as compared to Williams syndrome and typical development. J Neurodev Disord 2014; 6:8. [PMID: 24713364 PMCID: PMC4022321 DOI: 10.1186/1866-1955-6-8] [Citation(s) in RCA: 26] [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] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2013] [Accepted: 03/20/2014] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Individuals with Down Syndrome (DS) are reported to experience early onset of brain aging. However, it is not well understood how pre-existing neurodevelopmental effects versus neurodegenerative processes might be contributing to the observed pattern of brain atrophy in younger adults with DS. The aims of the current study were to: (1) to confirm previous findings of age-related changes in DS compared to adults with typical development (TD), (2) to test for an effect of these age-related changes in a second neurodevelopmental disorder, Williams syndrome (WS), and (3) to identify a pattern of regional age-related effects that are unique to DS. METHODS High-resolution T1-weighted MRI of the brains of subjects with DS, WS, and TD controls were segmented, and estimates of regional brain volume were derived using FreeSurfer. A general linear model was employed to test for age-related effects on volume between groups. Secondary analyses in the DS group explored the relationship between brain volume and neuropsychological tests and APOE. RESULTS Consistent with previous findings, the DS group showed significantly greater age-related effects relative to TD controls in total gray matter and in regions of the orbitofrontal cortex and the parietal cortex. Individuals with DS also showed significantly greater age-related effects on volume of the left and right inferior lateral ventricles (LILV and RILV, respectively). There were no significant differences in age-related effects on volume when comparing the WS and TD groups. In the DS group, cognitive tests scores measuring signs of dementia and APOE ϵ4 carrier status were associated with LILV and RILV volume. CONCLUSIONS Individuals with DS demonstrated a unique pattern of age-related effects on gray matter and ventricular volume, the latter of which was associated with dementia rating scores in the DS group. Results may indicate that early onset of brain aging in DS is primarily due to DS-specific neurodegenerative processes, as opposed to general atypical neurodevelopment.
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Affiliation(s)
- Mary Ellen I Koran
- Center for Human Genetics and Research, Department of Molecular Physiology & Biophysics, Vanderbilt University School of Medicine, 37232-0700, 519 Light Hall, Nashville, TN, USA ; Medical Scientist Training Program, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Timothy J Hohman
- Center for Human Genetics and Research, Department of Molecular Physiology & Biophysics, Vanderbilt University School of Medicine, 37232-0700, 519 Light Hall, Nashville, TN, USA
| | - Courtney M Edwards
- Center for Human Genetics and Research, Department of Molecular Physiology & Biophysics, Vanderbilt University School of Medicine, 37232-0700, 519 Light Hall, Nashville, TN, USA ; Short-Term Training Program Undergraduate Research Fellow, Vanderbilt University, Nashville, TN, USA
| | - Jennifer N Vega
- Center for Human Genetics and Research, Department of Molecular Physiology & Biophysics, Vanderbilt University School of Medicine, 37232-0700, 519 Light Hall, Nashville, TN, USA ; Neuroscience Graduate Program, Vanderbilt University, Nashville, TN, USA
| | - Jennifer R Pryweller
- Center for Human Genetics and Research, Department of Molecular Physiology & Biophysics, Vanderbilt University School of Medicine, 37232-0700, 519 Light Hall, Nashville, TN, USA ; Interdisciplinary Studies in Neuroimaging of Neurodevelopmental Disorders, The Graduate School, Vanderbilt University, Nashville, USA
| | - Laura E Slosky
- Center for Human Genetics and Research, Department of Molecular Physiology & Biophysics, Vanderbilt University School of Medicine, 37232-0700, 519 Light Hall, Nashville, TN, USA
| | - Genea Crockett
- Center for Human Genetics and Research, Department of Molecular Physiology & Biophysics, Vanderbilt University School of Medicine, 37232-0700, 519 Light Hall, Nashville, TN, USA
| | - Lynette Villa de Rey
- Center for Human Genetics and Research, Department of Molecular Physiology & Biophysics, Vanderbilt University School of Medicine, 37232-0700, 519 Light Hall, Nashville, TN, USA
| | - Shashwath A Meda
- Center for Human Genetics and Research, Department of Molecular Physiology & Biophysics, Vanderbilt University School of Medicine, 37232-0700, 519 Light Hall, Nashville, TN, USA
| | - Nathan Dankner
- Graduate Program in Clinical Psychological Sciences, Department of Psychology, Vanderbilt University, Nashville, TN, USA ; Vanderbilt Kennedy Center for Research on Human Development, Vanderbilt University, Nashville, TN, USA
| | - Suzanne N Avery
- Neuroscience Graduate Program, Vanderbilt University, Nashville, TN, USA ; Department of Psychiatry, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Jennifer U Blackford
- Department of Psychiatry, Vanderbilt University School of Medicine, Nashville, TN, USA ; Vanderbilt Kennedy Center for Research on Human Development, Vanderbilt University, Nashville, TN, USA
| | - Elisabeth M Dykens
- Department of Psychiatry, Vanderbilt University School of Medicine, Nashville, TN, USA ; Vanderbilt Kennedy Center for Research on Human Development, Vanderbilt University, Nashville, TN, USA ; Department of Psychology and Human Development, Vanderbilt University, Nashville, TN, USA
| | - Tricia A Thornton-Wells
- Center for Human Genetics and Research, Department of Molecular Physiology & Biophysics, Vanderbilt University School of Medicine, 37232-0700, 519 Light Hall, Nashville, TN, USA ; Vanderbilt Kennedy Center for Research on Human Development, Vanderbilt University, Nashville, TN, USA ; Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
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Yarosh HL, Hyatt CJ, Meda SA, Jiantonio-Kelly R, Potenza MN, Assaf M, D.Pearlson G. Relationships between reward sensitivity, risk-taking and family history of alcoholism during an interactive competitive fMRI task. PLoS One 2014; 9:e88188. [PMID: 24505424 PMCID: PMC3913753 DOI: 10.1371/journal.pone.0088188] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [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: 11/13/2013] [Accepted: 01/04/2014] [Indexed: 01/03/2023] Open
Abstract
Background Individuals with a positive family history for alcoholism (FHP) have shown differences from family-history-negative (FHN) individuals in the neural correlates of reward processing. FHP, compared to FHN individuals, demonstrate relatively diminished ventral striatal activation during anticipation of monetary rewards, and the degree of ventral striatal activation shows an inverse correlation with specific impulsivity measures in alcohol-dependent individuals. Rewards in socially interactive contexts relate importantly to addictive propensities, yet have not been examined with respect to how their neural underpinnings relate to impulsivity-related measures. Here we describe impulsivity measures in FHN and FHP individuals as they relate to a socially interactive functional magnetic resonance imaging (fMRI) task. Methods Forty FHP and 29 FHN subjects without histories of Axis-I disorders completed a socially interactive Domino task during functional magnetic resonance imaging and completed self-report and behavioral impulsivity-related assessments. Results FHP compared to FHN individuals showed higher scores (p = .004) on one impulsivity-related factor relating to both compulsivity (Padua Inventory) and reward/punishment sensitivity (Sensitivity to Punishment/Sensitivity to Reward Questionnaire). Multiple regression analysis within a reward-related network revealed a correlation between risk-taking (involving another impulsivity-related factor, the Balloon Analog Risk Task (BART)) and right ventral striatum activation under reward >punishment contrast (p<0.05 FWE corrected) in the social task. Conclusions Behavioral risk-taking scores may be more closely associated with neural correlates of reward responsiveness in socially interactive contexts than are FH status or impulsivity-related self-report measures. These findings suggest that risk-taking assessments be examined further in socially interactive settings relevant to addictive behaviors.
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Affiliation(s)
- Haley L. Yarosh
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, Connecticut, United States of America
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, United States of America
- * E-mail:
| | - Christopher J. Hyatt
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, Connecticut, United States of America
| | - Shashwath A. Meda
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, Connecticut, United States of America
| | - Rachel Jiantonio-Kelly
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, Connecticut, United States of America
| | - Marc N. Potenza
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, United States of America
- Department of Neurobiology, Yale University School of Medicine, New Haven, Connecticut, United States of America
- Child Study Center, Yale University School of Medicine, New Haven, Connecticut, United States of America
| | - Michal Assaf
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, Connecticut, United States of America
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, United States of America
| | - Godfrey D.Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, Connecticut, United States of America
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, United States of America
- Department of Neurobiology, Yale University School of Medicine, New Haven, Connecticut, United States of America
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Ivleva EI, Bidesi AS, Keshavan MS, Pearlson GD, Meda SA, Dodig D, Moates AF, Lu H, Francis AN, Tandon N, Schretlen DJ, Sweeney JA, Clementz BA, Tamminga CA. Gray matter volume as an intermediate phenotype for psychosis: Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP). Am J Psychiatry 2013; 170:1285-96. [PMID: 24185241 PMCID: PMC6487663 DOI: 10.1176/appi.ajp.2013.13010126] [Citation(s) in RCA: 119] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
OBJECTIVE The study examined gray matter volume across psychosis diagnoses organized by dimensional and DSM-IV categories from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) sample. METHOD In total, 351 probands with psychosis (146 with schizophrenia, 90 with schizoaffective disorder, and 115 with psychotic bipolar I disorder), 369 of their first-degree relatives (134 were relatives of individuals with schizophrenia, 106 of individuals with schizoaffective disorder, and 129 of individuals with psychotic bipolar I disorder), and 200 healthy comparison subjects were assessed. Gray matter volumes from 3-T T1-weighted images were analyzed using the VBM8 toolbox for SPM8, and outcomes were determined at a false discovery rate-corrected threshold of p<0.005. RESULTS Across the psychosis dimension, probands (N=351) and relatives with psychosis spectrum disorders (N=34) showed substantial overlapping gray matter reductions throughout the neocortex, whereas relatives without psychosis spectrum (N=332) had normal gray matter volumes relative to comparison subjects. Across DSM-IV diagnoses, schizophrenia and schizoaffective probands showed overlapping gray matter reductions in numerous cortical and subcortical regions, whereas psychotic bipolar probands showed limited gray matter reductions localized to the frontotemporal cortex relative to comparison subjects. All relative groups had gray matter volumes that did not differ from comparison subjects. CONCLUSIONS Across the dimensional psychosis categories, these findings indicate extensive neocortical gray matter reductions in psychosis probands and relatives with psychosis spectrum disorders, possibly reflecting lifetime psychosis burden, but normal gray matter in nonpsychotic relatives. Traditional DSM-IV psychosis grouping revealed partially divergent gray matter phenotypes for probands with schizophrenia or schizoaffective disorder (extensive neocortical or subcortical gray matter reductions) relative to those with psychotic bipolar disorder (smaller reductions were limited to frontotemporal regions). The dimensional conceptualization of psychosis appears useful in defining more homogenous disease categories that may help identify underlying psychosis biomarkers and develop a biologically driven diagnostic system and targeted treatments.
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Patel KT, Stevens MC, Meda SA, Muska C, Thomas AD, Potenza MN, Pearlson GD. Robust changes in reward circuitry during reward loss in current and former cocaine users during performance of a monetary incentive delay task. Biol Psychiatry 2013; 74:529-37. [PMID: 23778289 PMCID: PMC3775945 DOI: 10.1016/j.biopsych.2013.04.029] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2012] [Revised: 04/17/2013] [Accepted: 04/20/2013] [Indexed: 11/17/2022]
Abstract
BACKGROUND Abnormal function in reward circuitry in cocaine addiction could predate drug use as a risk factor, follow drug use as a consequence of substance-induced alterations, or both. METHODS We used a functional magnetic resonance imaging monetary incentive delay task (MIDT) to investigate reward-loss neural response differences among 42 current cocaine users, 35 former cocaine users, and 47 healthy subjects who also completed psychological measures and tasks related to impulsivity and reward. RESULTS We found various reward processing-related group differences in several MIDT phases. Across task phases we found a control > current user > former user activation pattern, except for loss outcome, where former compared with current cocaine users activated ventral tegmental area more robustly. We also found regional prefrontal activation differences during loss anticipation between cocaine-using groups. Both groups of cocaine users scored higher than control subjects on impulsivity, compulsivity and reward-punishment sensitivity factors. In addition, impulsivity-related factors correlated positively with activation in amygdala and negatively with anterior cingulate activation during loss anticipation. CONCLUSIONS Compared with healthy subjects, both former and current users displayed abnormal brain activation patterns during MIDT performance. Both cocaine groups differed similarly from healthy subjects, but differences between former and current users were localized to the ventral tegmental area during loss outcome and to prefrontal regions during loss anticipation, suggesting that long-term cocaine abstinence does not normalize most reward circuit abnormalities. Elevated impulsivity-related factors that relate to loss processing in current and former users suggest that these tendencies and relationships may pre-exist cocaine addiction.
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Affiliation(s)
- Krishna T Patel
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, Connecticut.
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DeVito EE, Meda SA, Jiantonio R, Potenza MN, Krystal JH, Pearlson GD. Neural correlates of impulsivity in healthy males and females with family histories of alcoholism. Neuropsychopharmacology 2013; 38:1854-63. [PMID: 23584260 PMCID: PMC3746701 DOI: 10.1038/npp.2013.92] [Citation(s) in RCA: 56] [Impact Index Per Article: 5.1] [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: 08/13/2012] [Revised: 02/08/2013] [Accepted: 03/11/2013] [Indexed: 01/25/2023]
Abstract
Individuals family-history positive (FHP) for alcoholism have increased risk for the disorder, which may be mediated by intermediate behavioral traits such as impulsivity. Given the sex differences in the risk for and clinical presentation of addictive disorders, risk for addiction may be differentially mediated by impulsivity within FHP males and females. FHP (N=28) and family-history negative (FHN, N=31) healthy, non-substance-abusing adults completed an fMRI Go/No-Go task and were assessed on impulsivity and alcohol use. Effects of family history and sex were investigated as were associations between neural correlates of impulse control and out-of-scanner measures of impulsivity and alcohol use. FHP individuals showed greater activation in the left anterior insula and inferior frontal gyrus during successful inhibitions, an effect that was driven primarily by FHP males. Higher self-reported impulsivity and behavioral discounting impulsivity, but not alcohol use measures, were associated with greater BOLD signal in the region that differentiated the FHP and FHN groups. Impulsivity factors were associated with alcohol use measures across the FHP and FHN groups. These findings are consistent with increased risk for addiction among FHP individuals being conferred through disrupted function within neural systems important for impulse control.
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Affiliation(s)
- Elise E DeVito
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510, USA.
| | - Shashwath A Meda
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT, USA
| | - Rachel Jiantonio
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT, USA
| | - Marc N Potenza
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA,Department of Neurobiology, Yale University School of Medicine, New Haven, CT, USA,Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - John H Krystal
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA,Clinical Neuroscience Division, VA National Center for PTSD, VA Connecticut Healthcare System, West Haven, CT, USA
| | - Godfrey D Pearlson
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA,Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT, USA,Department of Neurobiology, Yale University School of Medicine, New Haven, CT, USA
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Jamadar S, Powers NR, Meda SA, Calhoun VD, Gelernter J, Gruen JR, Pearlson GD. Genetic influences of resting state fMRI activity in language-related brain regions in healthy controls and schizophrenia patients: a pilot study. Brain Imaging Behav 2013; 7:15-27. [PMID: 22669497 DOI: 10.1007/s11682-012-9168-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Individuals with schizophrenia show a broad range of language impairments, similar to those observed in reading disability (RD). Genetic linkage and association studies of RD have identified a number of candidate RD-genes that are associated with neuronal migration. Some individuals with schizophrenia also show evidence of impaired cortical neuronal migration. We have previously linked RD-related genes with gray matter distributions in healthy controls and schizophrenia. The aim of the current study was to extend these structural findings and to examine links between putative RD-genes and functional connectivity of language-related regions in healthy controls (n = 27) and schizophrenia (n = 28). Parallel independent component analysis (parallel-ICA) was used to examine the relationship between language-related regions extracted from resting-state fMRI and 16 single nucleotide polymorphisms (SNPs) spanning 5 RD-related genes. Parallel-ICA identified four significant fMRI-SNP relationships. A Left Broca-Superior/Inferior Parietal network was related to two KIAA0319 SNPs in controls but not in schizophrenia. For both diagnostic groups, a Broca-Medial Parietal network was related to two DCDC2 SNPs, while a Left Wernicke-Fronto-Occipital network was related to two KIAA0319 SNPs. A Bilateral Wernicke-Fronto-Parietal network was related to one KIAA0319 SNP only in controls. Thus, RD-genes influence functional connectivity in language-related regions, but no RD-gene uniquely affected network function in schizophrenia as compared to controls. This is in contrast with our previous study where RD-genes affected gray matter distribution in some structural networks in schizophrenia but not in controls. Thus these RD-genes may exert a more important influence on structure rather than function of language-related networks in schizophrenia.
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Affiliation(s)
- Sharna Jamadar
- Olin Neuropsychiatry Research Center, Institute of Living, 200 Retreat Ave, Hartford, CT 06106, USA.
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Meda SA, Koran MEI, Pryweller JR, Vega JN, Thornton-Wells TA. Genetic interactions associated with 12-month atrophy in hippocampus and entorhinal cortex in Alzheimer's Disease Neuroimaging Initiative. Neurobiol Aging 2012; 34:1518.e9-18. [PMID: 23107432 DOI: 10.1016/j.neurobiolaging.2012.09.020] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2012] [Revised: 09/14/2012] [Accepted: 09/27/2012] [Indexed: 12/22/2022]
Abstract
Missing heritability in late onset Alzheimer disease can be attributed, at least in part, to heterogeneity in disease status and to the lack of statistical analyses exploring genetic interactions. In the current study, we use quantitative intermediate phenotypes derived from magnetic resonance imaging data available from the Alzheimer's Disease Neuroimaging Initiative, and we test for association with gene-gene interactions within biological pathways. Regional brain volumes from the hippocampus (HIP) and entorhinal cortex (EC) were estimated from baseline and 12-month magnetic resonance imaging scans. Approximately 560,000 single nucleotide polymorphisms (SNPs) were available genome-wide. We tested all pairwise SNP-SNP interactions (approximately 151 million) within 212 Kyoto Encyclopedia of Genes and Genomes pathways for association with 12-month regional atrophy rates using linear regression, with sex, APOE ε4 carrier status, age, education, and clinical status as covariates. A total of 109 SNP-SNP interactions were associated with right HIP atrophy, and 125 were associated with right EC atrophy. Enrichment analysis indicated significant SNP-SNP interactions were overrepresented in the calcium signaling and axon guidance pathways for both HIP and EC atrophy and in the ErbB signaling pathway for HIP atrophy.
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Affiliation(s)
- Shashwath A Meda
- Center for Human Genetics and Research, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, USA
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Meda SA, Narayanan B, Liu J, Perrone-Bizzozero NI, Stevens MC, Calhoun VD, Glahn DC, Shen L, Risacher SL, Saykin AJ, Pearlson GD. Erratum to “A large scale multivariate parallel ICA method reveals novel imaging-genetic relationships for Alzheimer's Disease in the ADNI cohort” [Neuroimage 60/3(2012) 1608–1621]. Neuroimage 2012. [DOI: 10.1016/j.neuroimage.2012.03.058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
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Meda SA, Narayanan B, Liu J, Perrone-Bizzozero NI, Stevens MC, Calhoun VD, Glahn DC, Shen L, Risacher SL, Saykin AJ, Pearlson GD. A large scale multivariate parallel ICA method reveals novel imaging-genetic relationships for Alzheimer's disease in the ADNI cohort. Neuroimage 2012; 60:1608-21. [PMID: 22245343 DOI: 10.1016/j.neuroimage.2011.12.076] [Citation(s) in RCA: 90] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2011] [Revised: 12/16/2011] [Accepted: 12/19/2011] [Indexed: 11/16/2022] Open
Abstract
The underlying genetic etiology of late onset Alzheimer's disease (LOAD) remains largely unknown, likely due to its polygenic architecture and a lack of sophisticated analytic methods to evaluate complex genotype-phenotype models. The aim of the current study was to overcome these limitations in a bi-multivariate fashion by linking intermediate magnetic resonance imaging (MRI) phenotypes with a genome-wide sample of common single nucleotide polymorphism (SNP) variants. We compared associations between 94 different brain regions of interest derived from structural MRI scans and 533,872 genome-wide SNPs using a novel multivariate statistical procedure, parallel-independent component analysis, in a large, national multi-center subject cohort. The study included 209 elderly healthy controls, 367 subjects with amnestic mild cognitive impairment and 181 with mild, early-stage LOAD, all of them Caucasian adults, from the Alzheimer's Disease Neuroimaging Initiative cohort. Imaging was performed on comparable 1.5 T scanners at over 50 sites in the USA/Canada. Four primary "genetic components" were associated significantly with a single structural network including all regions involved neuropathologically in LOAD. Pathway analysis suggested that each component included several genes already known to contribute to LOAD risk (e.g. APOE4) or involved in pathologic processes contributing to the disorder, including inflammation, diabetes, obesity and cardiovascular disease. In addition significant novel genes identified included ZNF673, VPS13, SLC9A7, ATP5G2 and SHROOM2. Unlike conventional analyses, this multivariate approach identified distinct groups of genes that are plausibly linked in physiologic pathways, perhaps epistatically. Further, the study exemplifies the value of this novel approach to explore large-scale data sets involving high-dimensional gene and endophenotype data.
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Affiliation(s)
- Shashwath A Meda
- Olin Neuropsychiatric Research Center, Hartford Hospital/IOL, Hartford, CT 06106, USA.
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Andrews MM, Meda SA, Thomas AD, Potenza MN, Krystal JH, Worhunsky P, Stevens MC, O’Malley S, Book GA, Reynolds B, Pearlson GD. Individuals family history positive for alcoholism show functional magnetic resonance imaging differences in reward sensitivity that are related to impulsivity factors. Biol Psychiatry 2011; 69:675-83. [PMID: 21126735 PMCID: PMC3677031 DOI: 10.1016/j.biopsych.2010.09.049] [Citation(s) in RCA: 141] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2010] [Revised: 08/09/2010] [Accepted: 09/08/2010] [Indexed: 11/18/2022]
Abstract
BACKGROUND Substance-abusing individuals tend to display abnormal reward processing and a vulnerability to being impulsive. Detoxified alcoholics show differences in regional brain activation during a monetary incentive delay task. However, there is limited information on whether this uncharacteristic behavior represents a biological predisposition toward alcohol abuse, a consequence of chronic alcohol use, or both. METHODS We investigated proposed neural correlates of substance disorder risk by examining reward system activity during a monetary incentive delay task with separate reward prospect, reward anticipation, and reward outcome phases in 30 individuals with and 19 without family histories of alcoholism. All subjects were healthy, lacked DSM-IV past or current alcohol or substance abuse histories, and were free of illegal substances as verified by a urine toxicology screening at the time of scanning. Additionally, we explored specific correlations between task-related nucleus accumbens (NAcc) activation and distinct factor analysis-derived domains of behavioral impulsivity. RESULTS During reward anticipation, functional magnetic resonance imaging data confirmed blunted NAcc activation in family history positive subjects. In addition, we found atypical activation in additional reward-associated brain regions during additional task phases. We further found a significant negative correlation between NAcc activation during reward anticipation and an impulsivity construct. CONCLUSIONS Overall, results demonstrate that sensitivity of the reward circuit, including NAcc, is functionally different in alcoholism family history positive individuals in multiple regards.
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Affiliation(s)
- Melissa M. Andrews
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT 06106
| | - Shashwath A. Meda
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT 06106
| | - Andre D. Thomas
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT 06106
| | - Marc N. Potenza
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510
- Child Study Center, Yale University School of Medicine, New Haven, CT 06510
| | - John H Krystal
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510
| | - Patrick Worhunsky
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510
| | - Michael C. Stevens
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT 06106
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510
| | - Stephanie O’Malley
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510
| | - Gregory A. Book
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT 06106
| | | | - Godfrey D. Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT 06106
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510
- Corresponding Author Godfrey Pearlson, MD, 200 Retreat Avenue (Whitehall Bldg), Hartford Hospital/IOL, Hartford, CT 06106, , Tel: (860)-545-7757, Fax: (860)-545-7797
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Anderson BM, Stevens MC, Meda SA, Jordan K, Calhoun VD, Pearlson GD. Functional imaging of cognitive control during acute alcohol intoxication. Alcohol Clin Exp Res 2010; 35:156-65. [PMID: 20958334 DOI: 10.1111/j.1530-0277.2010.01332.x] [Citation(s) in RCA: 59] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
BACKGROUND The anterior cingulate and several other prefrontal and parietal brain regions are implicated in error processing and cognitive control. The effects of different doses of alcohol on activity within these brain regions during a functional magnetic resonance imaging (fMRI) task where errors are frequently committed have not been fully explored. METHODS This study examined the impact of a placebo [breath alcohol concentration (BrAC) = 0.00%], moderate (BrAC = 0.05%), and high (BrAC = 0.10%) doses of alcohol on brain hemodynamic activity during a functional MRI (fMRI) Go/No-Go task in 38 healthy volunteers. RESULTS Alcohol increased reaction time and false alarm errors in a dose-dependent manner. fMRI analyses showed alcohol decreased activity in anterior cingulate, lateral prefrontal cortex, insula, and parietal lobe regions during false alarm responses to No-Go stimuli. CONCLUSIONS These findings indicate that brain regions implicated in error processing are affected by alcohol and might provide a neural basis for alcohol's effects on behavioral performance.
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Affiliation(s)
- Beth M Anderson
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Connecticut, USA.
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Lui S, Li T, Deng W, Jiang L, Wu Q, Tang H, Yue Q, Huang X, Chan RC, Collier DA, Meda SA, Pearlson G, Mechelli A, Sweeney JA, Gong Q. Short-term effects of antipsychotic treatment on cerebral function in drug-naive first-episode schizophrenia revealed by "resting state" functional magnetic resonance imaging. ACTA ACUST UNITED AC 2010; 67:783-92. [PMID: 20679586 DOI: 10.1001/archgenpsychiatry.2010.84] [Citation(s) in RCA: 300] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
CONTEXT Most of what we know about antipsychotic drug effects is at the receptor level, distal from the neural system effects that mediate their clinical efficacy. Studying cerebral function in antipsychotic-naive patients with schizophrenia before and after pharmacotherapy can enhance understanding of the therapeutic mechanisms of these clinically effective treatments. OBJECTIVE To examine alterations of regional and neural network function in antipsychotic-naive patients with first-episode schizophrenia before and after treatment with second-generation antipsychotic medication. DESIGN Case-control study. SETTING Huaxi MR Research Center and Mental Health Centre of the West China Hospital. PARTICIPANTS Thirty-four antipsychotic-naive patients with first-episode schizophrenia were scanned using gradient-echo echo-planar imaging while in a resting state. After 6 weeks of antipsychotic treatment, patients were rescanned. Thirty-four matched healthy control subjects were studied at baseline for comparison purposes. MAIN OUTCOME MEASURES The amplitude of low-frequency fluctuations (ALFF) of blood oxygen level-dependent signals, believed to reflect spontaneous neural activity, was used to characterize regional cerebral function. Functional connectivity across brain regions was evaluated using a seed voxel correlation approach and an independent component analysis. Changes in these measures after treatment were examined to characterize effects of antipsychotic drugs on regional function and functional integration. RESULTS After short-term treatment with second-generation antipsychotic medications, patients showed increased ALFF, particularly in the bilateral prefrontal and parietal cortex, left superior temporal cortex, and right caudate nucleus. Increased regional ALFF was associated with a reduction of clinical symptoms, and a widespread attenuation in functional connectivity was observed that was correlated with increased regional ALFF. CONCLUSIONS We demonstrate for the first time, to our knowledge, that widespread increased regional synchronous neural activity occurs after antipsychotic therapy, accompanied by decreased integration of function across widely distributed neural networks. These findings contribute to the understanding of the complex systems-level effects of antipsychotic drugs.
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Affiliation(s)
- Su Lui
- Huaxi MR Research Center, Department of Radiology, State Key Lab of Biotherapy,West China Hospital of Sichuan University, Chengdu, China
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Parker BA, Polk DM, Rabdiya V, Meda SA, Anderson K, Hawkins KA, Pearlson GD, Thompson PD. Changes in Memory Function and Neuronal Activation Associated with Atorvastatin Therapy. Pharmacotherapy 2010. [DOI: 10.1592/phco.30.6.625] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Rzepecki-Smith CI, Meda SA, Calhoun VD, Stevens MC, Jafri MJ, Astur RS, Pearlson GD. Disruptions in functional network connectivity during alcohol intoxicated driving. Alcohol Clin Exp Res 2009; 34:479-87. [PMID: 20028354 DOI: 10.1111/j.1530-0277.2009.01112.x] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
BACKGROUND Driving while under the influence of alcohol is a major public health problem whose neural basis is not well understood. In a recently published functional magnetic resonance imaging (fMRI) study (Meda et al., 2009), our group identified 5, independent critical driving-associated brain circuits whose inter-regional connectivity was disrupted by alcohol intoxication. However, the functional connectivity between these circuits has not yet been explored in order to determine how these networks communicate with each other during sober and alcohol-intoxicated states. METHODS In the current study, we explored such differences in connections between the above brain circuits and driving behavior, under the influence of alcohol versus placebo. Forty social drinkers who drove regularly underwent fMRI scans during virtual reality driving simulations following 2 alcohol doses, placebo and an individualized dose producing blood alcohol concentrations (BACs) of 0.10%. RESULTS At the active dose, we found specific disruptions of functional network connectivity between the frontal-temporal-basal ganglia and the cerebellar circuits. The temporal connectivity between these 2 circuits was found to be less correlated (p < 0.05) when driving under the influence of alcohol. This disconnection was also associated with an abnormal driving behavior (unstable motor vehicle steering). CONCLUSIONS Connections between frontal-temporal-basal ganglia and cerebellum have recently been explored; these may be responsible in part for maintaining normal motor behavior by integrating their overlapping motor control functions. These connections appear to be disrupted by alcohol intoxication, in turn associated with an explicit type of impaired driving behavior.
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Affiliation(s)
- Catherine I Rzepecki-Smith
- Olin Neuropsychiatry Research Center, Institute of Living/Hartford Hospital, Hartford, Connecticut, USA.
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Meda SA, Jagannathan K, Gelernter J, Calhoun VD, Liu J, Stevens MC, Pearlson GD. A pilot multivariate parallel ICA study to investigate differential linkage between neural networks and genetic profiles in schizophrenia. Neuroimage 2009; 53:1007-15. [PMID: 19944766 DOI: 10.1016/j.neuroimage.2009.11.052] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2009] [Revised: 10/29/2009] [Accepted: 11/19/2009] [Indexed: 11/28/2022] Open
Abstract
Understanding genetic influences on both healthy and disordered brain function is a major focus in psychiatric neuroimaging. We utilized task-related imaging findings from an fMRI auditory oddball task known to be robustly associated with abnormal activation in schizophrenia, to investigate genomic factors derived from multiple single nucleotide polymorphisms (SNPs) from genes previously shown to be associated with schizophrenia. Our major aim was to investigate the relationship of these genomic factors to normal/abnormal brain functionality between controls and schizophrenia patients. We studied a Caucasian-only sample of 35 healthy controls and 31 schizophrenia patients. All subjects performed an auditory oddball task, which consists of detecting an infrequent sound within a series of frequent sounds. Each subject was characterized on 24 different SNP markers spanning multiple risk genes previously associated with schizophrenia. We used a recently developed technique named parallel independent component analysis (para-ICA) to analyze this multimodal data set (Liu et al., 2008). The method aims to identify simultaneously independent components of each modality (functional imaging, genetics) and the relationships between them. We detected three fMRI components significantly correlated with two distinct gene components. The fMRI components, along with their significant genetic profile (dominant SNP) correlations were as follows: (1) Inferior frontal-anterior/posterior cingulate-thalamus-caudate with SNPs from Brain derived neurotropic factor (BDNF) and dopamine transporter (DAT) [r=-0.51; p<0.0001], (2) superior/middle temporal gyrus-cingulate-premotor with SLC6A4_PR and SLC6A4_PR_AG (serotonin transporter promoter; 5HTTLPR) [r=0.27; p=0.03], and (3) default mode-fronto-temporal gyrus with Brain derived neurotropic factor and dopamine transporter (BDNF, DAT) [r=-0.25; p=0.04]. Functional components comprised task-relevant regions (including PFC, ACC, STG and MTG) frequently identified as abnormal in schizophrenia. Further, gene-fMRI combinations 1 (Z=1.75; p=0.03), 2 (Z=1.84; p=0.03) and 3 (Z=1.67; p=0.04) listed above showed significant differences between controls and patients, based on their correlated loading coefficients. We demonstrate a framework to identify interactions between "clusters" of brain function and of genetic information. Our results reveal the effect/influence of specific interactions, (perhaps epistastatic in nature), between schizophrenia risk genes on imaging endophenotypes representing attention/working memory and goal directed related brain function, thus establishing a useful methodology to probe multivariate genotype-phenotype relationships.
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Affiliation(s)
- Shashwath A Meda
- Olin Neuropsychiatry Research Center, Institute of Living, 200 Retreat Avenue, Hartford, CT 06106, USA.
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Meda SA, Stevens MC, Folley BS, Calhoun VD, Pearlson GD. Evidence for anomalous network connectivity during working memory encoding in schizophrenia: an ICA based analysis. PLoS One 2009; 4:e7911. [PMID: 19936244 PMCID: PMC2775682 DOI: 10.1371/journal.pone.0007911] [Citation(s) in RCA: 103] [Impact Index Per Article: 6.9] [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: 10/16/2009] [Accepted: 10/27/2009] [Indexed: 12/04/2022] Open
Abstract
Background Numerous neuroimaging studies report abnormal regional brain activity during working memory performance in schizophrenia, but few have examined brain network integration as determined by “functional connectivity” analyses. Methodology/Principal Findings We used independent component analysis (ICA) to identify and characterize dysfunctional spatiotemporal networks in schizophrenia engaged during the different stages (encoding and recognition) of a Sternberg working memory fMRI paradigm. 37 chronic schizophrenia and 54 healthy age/gender-matched participants performed a modified Sternberg Item Recognition fMRI task. Time series images preprocessed with SPM2 were analyzed using ICA. Schizophrenia patients showed relatively less engagement of several distinct “normal” encoding-related working memory networks compared to controls. These encoding networks comprised 1) left posterior parietal-left dorsal/ventrolateral prefrontal cortex, cingulate, basal ganglia, 2) right posterior parietal, right dorsolateral prefrontal cortex and 3) default mode network. In addition, the left fronto-parietal network demonstrated a load-dependent functional response during encoding. Network engagement that differed between groups during recognition comprised the posterior cingulate, cuneus and hippocampus/parahippocampus. As expected, working memory task accuracy differed between groups (p<0.0001) and was associated with degree of network engagement. Functional connectivity within all three encoding-associated functional networks correlated significantly with task accuracy, which further underscores the relevance of abnormal network integration to well-described schizophrenia working memory impairment. No network was significantly associated with task accuracy during the recognition phase. Conclusions/Significance This study extends the results of numerous previous schizophrenia studies that identified isolated dysfunctional brain regions by providing evidence of disrupted schizophrenia functional connectivity using ICA within widely-distributed neural networks engaged for working memory cognition.
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Affiliation(s)
- Shashwath A Meda
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, Connecticut, United States of America.
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Turner BM, Meda SA, Ruopp K, Stevens MC, Pearlson GD. Pharmacological Manipulations of “Resting State” Brain Function using Alcohol and Marijuana. Neuroimage 2009. [DOI: 10.1016/s1053-8119(09)72069-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
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Meda SA, Calhoun VD, Astur RS, Turner BM, Ruopp K, Pearlson GD. Alcohol dose effects on brain circuits during simulated driving: an fMRI study. Hum Brain Mapp 2009; 30:1257-70. [PMID: 18571794 DOI: 10.1002/hbm.20591] [Citation(s) in RCA: 55] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Driving while intoxicated remains a major public health hazard. Driving is a complex task involving simultaneous recruitment of multiple cognitive functions. The investigators studied the neural substrates of driving and their response to different blood alcohol concentrations (BACs), using functional magnetic resonance imaging (fMRI) and a virtual reality driving simulator. We used independent component analysis (ICA) to isolate spatially independent and temporally correlated driving-related brain circuits in 40 healthy, adult moderate social drinkers. Each subject received three individualized, separate single-blind doses of beverage alcohol to produce BACs of 0.05% (moderate), 0.10% (high), or 0% (placebo). 3 T fMRI scanning and continuous behavioral measurement occurred during simulated driving. Brain function was assessed and compared using both ICA and a conventional general linear model (GLM) analysis. ICA results replicated and significantly extended our previous 1.5T study (Calhoun et al. [2004a]: Neuropsychopharmacology 29:2097-2017). GLM analysis revealed significant dose-related functional differences, complementing ICA data. Driving behaviors including opposite white line crossings and mean speed independently demonstrated significant dose-dependent changes. Behavior-based factors also predicted a frontal-basal-temporal circuit to be functionally impaired with alcohol dosage across baseline scaled, good versus poorly performing drivers. We report neural correlates of driving behavior and found dose-related spatio-temporal disruptions in critical driving-associated regions including the superior, middle and orbito frontal gyri, anterior cingulate, primary/supplementary motor areas, basal ganglia, and cerebellum. Overall, results suggest that alcohol (especially at high doses) causes significant impairment of both driving behavior and brain functionality related to motor planning and control, goal directedness, error monitoring, and memory.
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Affiliation(s)
- Shashwath A Meda
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Connecticut, USA.
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Parker BA, Thompson PD, Ruopp KC, Meda SA, Grimaldi AS, Pearlson GD. Direct Effects Of Exercise Training On The Hippocampus In Humans. Med Sci Sports Exerc 2009. [DOI: 10.1249/01.mss.0000353280.47679.41] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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Allen AJ, Meda SA, Skudlarski P, Calhoun VD, Astur R, Ruopp KC, Pearlson GD. Effects of alcohol on performance on a distraction task during simulated driving. Alcohol Clin Exp Res 2009; 33:617-25. [PMID: 19183133 DOI: 10.1111/j.1530-0277.2008.00876.x] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
BACKGROUND Prior studies report that accidents involving intoxicated drivers are more likely to occur during performance of secondary tasks. We studied this phenomenon, using a dual-task paradigm, involving performance of a visual oddball (VO) task while driving in an alcohol challenge paradigm. Previous functional MRI (fMRI) studies of the VO task have shown activation in the anterior cingulate, hippocampus, and prefrontal cortex. Thus, we predicted dose-dependent decreases in activation of these areas during VO performance. METHODS Forty healthy social drinkers were administered 3 different doses of alcohol, individually tailored to their gender and weight. Participants performed a VO task while operating a virtual reality driving simulator in a 3T fMRI scanner. RESULTS Analysis showed a dose-dependent linear decrease in Blood Oxygen Level Dependent activation during task performance, primarily in hippocampus, anterior cingulate, and dorsolateral prefrontal areas, with the least activation occurring during the high dose. Behavioral analysis showed a dose-dependent linear increase in reaction time, with no effects associated with either correct hits or false alarms. In all dose conditions, driving speed decreased significantly after a VO stimulus. However, at the high dose this decrease was significantly less. Passenger-side line crossings significantly increased at the high dose. CONCLUSIONS These results suggest that driving impairment during secondary task performance may be associated with alcohol-related effects on the above brain regions, which are involved with attentional processing/decision-making. Drivers with high blood alcohol concentrations may be less able to orient or detect novel or sudden stimuli during driving.
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Affiliation(s)
- Allyssa J Allen
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, 200 Retreat Avenue, Hartford, Connecticut 06106, USA.
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Meda SA, Bhattarai M, Morris NA, Astur RS, Calhoun VD, Mathalon DH, Kiehl KA, Pearlson GD. An fMRI study of working memory in first-degree unaffected relatives of schizophrenia patients. Schizophr Res 2008; 104:85-95. [PMID: 18678469 PMCID: PMC2577216 DOI: 10.1016/j.schres.2008.06.013] [Citation(s) in RCA: 43] [Impact Index Per Article: 2.7] [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: 01/30/2008] [Revised: 06/16/2008] [Accepted: 06/18/2008] [Indexed: 11/19/2022]
Abstract
Identifying intermediate phenotypes of genetically complex psychiatric illnesses such as schizophrenia is important. First-degree relatives of persons with schizophrenia have increased genetic risk for the disorder and tend to show deficits on working memory (WM) tasks. An open question is the relationship between such behavioral endophenotypes and the corresponding brain activation patterns revealed during functional imaging. We measured task performance during a Sternberg WM task and used functional magnetic resonance imaging (fMRI) to assess whether 23 non-affected first-degree relatives showed altered performance and functional activation compared to 43 matched healthy controls. We predicted that a significant proportion of unaffected first-degree relatives would show either aberrant task performance and/or abnormal related fMRI blood oxygen level dependent (BOLD) patterns. While task performance in the relatives was not different than that of controls they were significantly slower in responding to probes., Schizophrenia relatives displayed reduced activation, most markedly in bilateral dorsolateral/ventrolateral (DLPFC/VLPFC) prefrontal and posterior parietal cortex when encoding stimuli and in bilateral DLPFC and parietal areas during response selection. Additionally, fMRI differences in both conditions were modulated by load, with a parametric increase in between-group differences with load in several key regions during encoding and an opposite effect during response selection.
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Affiliation(s)
- Shashwath A Meda
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, 200 Retreat Avenue, Hartford, CT 06106, USA.
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Skelly LR, Calhoun V, Meda SA, Kim J, Mathalon DH, Pearlson GD. Diffusion tensor imaging in schizophrenia: relationship to symptoms. Schizophr Res 2008; 98:157-62. [PMID: 18031994 PMCID: PMC2668961 DOI: 10.1016/j.schres.2007.10.009] [Citation(s) in RCA: 101] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2007] [Revised: 10/10/2007] [Accepted: 10/12/2007] [Indexed: 10/22/2022]
Abstract
In this diffusion tensor imaging (DTI) study, the authors investigated white matter integrity in schizophrenia and the relationships between white matter alterations and specific symptoms of the disorder. We compared DTI images of 25 schizophrenia patients and 25 matched healthy controls and performed voxel-wise correlational analyses using the patient's DTI data and their severity scores of positive and negative symptoms. We found diffuse deficits in multiple types of white matter tracts in schizophrenia, and an inverse relationship of DTI fractional anisotropy (FA) values with positive symptom scores in association fibers, supporting a "disconnection" hypothesis of positive symptoms in schizophrenia.
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Affiliation(s)
- Laurie R Skelly
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT 06106, USA.
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Benson RR, Meda SA, Vasudevan S, Kou Z, Govindarajan KA, Hanks RA, Millis SR, Makki M, Latif Z, Coplin W, Meythaler J, Haacke EM. Global White Matter Analysis of Diffusion Tensor Images Is Predictive of Injury Severity in Traumatic Brain Injury. J Neurotrauma 2007; 24:446-59. [PMID: 17402851 DOI: 10.1089/neu.2006.0153] [Citation(s) in RCA: 172] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Conventional clinical neuroimaging is insensitive to axonal injury in traumatic brain injury (TBI). Immunocytochemical staining reveals changes to axonal morphology within hours, suggesting potential for diffusion-weighted magnetic resonance (MR) in early diagnosis and management of TBI. Diffusion tensor imaging (DTI) characterizes the three-dimensional (3D) distribution of water diffusion, which is highly anisotropic in white matter fibers owing to axonal length. Recently, DTI has been used to investigate traumatic axonal injury (TAI), emphasizing regional analysis in more severe TBI. In the current study, we hypothesized that a global white matter (WM) analysis of DTI data would be sensitive to TAI across a spectrum of TBI severity and injury to scan interval. To investigate this, we compared WM-only histograms of a scalar, fractional anisotropy (FA), between 20 heterogeneous TBI patients recruited from Detroit Medical Center, including six mild TBI (GCS 13-15), and 14 healthy age-matched controls. FA histogram parameters were correlated with admission GCS and posttraumatic amnesia (PTA). In all cases, including mild TBI, patients' FA histograms were globally decreased compared with control histograms. The shape of the TBI histograms also differed from controls, being more peaked and skewed. The mean FA, kurtosis and skewness were highly correlated suggesting a common mechanism. FA histogram properties also correlated with injury severity indexed by GCS and PTA, with mean FA being the best predictor and duration of PTA (r = 0.64) being superior to GCS (r = 0.47). Therefore, in this heterogeneous sample, the FA mean accounted for 40% of the variance in PTA. Increased diffusion in the short axis dimension, likely reflecting dysmyelination and swelling of axons, accounted for most of the FA decrease. FA is globally deceased in WM, including mild TBI, possibly reflecting widespread involvement. FA changes appear to be correlated with injury severity suggesting a role in early diagnosis and prognosis of TBI.
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Affiliation(s)
- Randall R Benson
- Department of Neurology, Wayne State University School of Medicine, Detroit, Michigan 48201, USA.
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