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Ghazikhanian SE, Surti TS. Sleep apnea in schizophrenia: Estimating prevalence and impact on cognition. J Psychiatr Res 2024; 177:330-337. [PMID: 39068777 DOI: 10.1016/j.jpsychires.2024.07.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2024] [Revised: 07/14/2024] [Accepted: 07/16/2024] [Indexed: 07/30/2024]
Abstract
Undertreated medical illnesses can compound the disabling cognitive deficits of schizophrenia. Obstructive sleep apnea (OSA) impairs cognitive domains also affected by schizophrenia, is common, and is treatable. The effects of sleep apnea on cognition in schizophrenia, however, are not well understood. We estimated the prevalence of OSA in a previously characterized sample of 3942 Veterans with schizophrenia by self-report and with a predictive model to identify individuals at high risk for OSA. We then compared neuropsychological and functional capacity assessment results between those who reported OSA versus those who did not, and between those predicted to have OSA versus predicted to not have OSA. We expected that many Veterans not reporting sleep apnea would be predicted to have it, and that both reported and predicted sleep apnea would be associated with lower cognitive and functional performance. The reported prevalence of OSA in the sample was 14%, whereas 72% were predicted to be at high risk of OSA. Interestingly, participants who reported having OSA had better cognitive and functional capacity performance (p's < 0.001) compared to those who did not report OSA, particularly on speed of processing assessments (p < 0.001). Predicted OSA, by contrast, was associated with lower speed of processing, verbal learning and working memory test scores (p's < 0.001). One possible interpretation of these results is that people with higher cognitive capacity may be more likely to seek medical care, while those with cognitive impairments are at greater risk for having untreated co-occurring medical conditions that further compromise cognition.
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Affiliation(s)
| | - Toral S Surti
- Department of Psychiatry, Yale University School of Medicine, 300 George Street, New Haven, CT, 06515, USA; Mental Health Service Line, Veterans Affairs Connecticut Healthcare System, 950 Campbell Avenue, West Haven, CT, 06516, USA.
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2
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Bigdeli TB, Chatzinakos C, Bendl J, Barr PB, Venkatesh S, Gorman BR, Clarence T, Genovese G, Iyegbe CO, Peterson RE, Kolokotronis SO, Burstein D, Meyers JL, Li Y, Rajeevan N, Sayward F, Cheung KH, DeLisi LE, Kosten TR, Zhao H, Achtyes E, Buckley P, Malaspina D, Lehrer D, Rapaport MH, Braff DL, Pato MT, Fanous AH, Pato CN, Huang GD, Muralidhar S, Michael Gaziano J, Pyarajan S, Girdhar K, Lee D, Hoffman GE, Aslan M, Fullard JF, Voloudakis G, Harvey PD, Roussos P. Biological Insights from Schizophrenia-associated Loci in Ancestral Populations. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.27.24312631. [PMID: 39252912 PMCID: PMC11383513 DOI: 10.1101/2024.08.27.24312631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/11/2024]
Abstract
Large-scale genome-wide association studies of schizophrenia have uncovered hundreds of associated loci but with extremely limited representation of African diaspora populations. We surveyed electronic health records of 200,000 individuals of African ancestry in the Million Veteran and All of Us Research Programs, and, coupled with genotype-level data from four case-control studies, realized a combined sample size of 13,012 affected and 54,266 unaffected persons. Three genome-wide significant signals - near PLXNA4, PMAIP1, and TRPA1 - are the first to be independently identified in populations of predominantly African ancestry. Joint analyses of African, European, and East Asian ancestries across 86,981 cases and 303,771 controls, yielded 376 distinct autosomal loci, which were refined to 708 putatively causal variants via multi-ancestry fine-mapping. Utilizing single-cell functional genomic data from human brain tissue and two complementary approaches, transcriptome-wide association studies and enhancer-promoter contact mapping, we identified a consensus set of 94 genes across ancestries and pinpointed the specific cell types in which they act. We identified reproducible associations of schizophrenia polygenic risk scores with schizophrenia diagnoses and a range of other mental and physical health problems. Our study addresses a longstanding gap in the generalizability of research findings for schizophrenia across ancestral populations, underlining shared biological underpinnings of schizophrenia across global populations in the presence of broadly divergent risk allele frequencies.
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Affiliation(s)
- Tim B. Bigdeli
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences and SUNY Downstate Health Sciences University, Brooklyn, NY
- Institute for Genomics in Health (IGH), SUNY Downstate Health Sciences University, Brooklyn, NY
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Chris Chatzinakos
- Department of Psychiatry and Behavioral Sciences and SUNY Downstate Health Sciences University, Brooklyn, NY
- Institute for Genomics in Health (IGH), SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, NY
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, NY
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
| | - Peter B. Barr
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences and SUNY Downstate Health Sciences University, Brooklyn, NY
- Institute for Genomics in Health (IGH), SUNY Downstate Health Sciences University, Brooklyn, NY
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Sanan Venkatesh
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, NY
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, NY
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, USA
| | - Bryan R. Gorman
- Massachusetts Area Veterans Epidemiology, Research, and Information Center (MAVERIC), Jamaica Plain, MA
| | - Tereza Clarence
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, NY
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, NY
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
| | - Giulio Genovese
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA
- Harvard Medical School, Boston, MA
| | - Conrad O. Iyegbe
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
| | - Roseann E. Peterson
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences and SUNY Downstate Health Sciences University, Brooklyn, NY
- Institute for Genomics in Health (IGH), SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Sergios-Orestis Kolokotronis
- Institute for Genomics in Health (IGH), SUNY Downstate Health Sciences University, Brooklyn, NY
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY
- Division of Infectious Diseases, Department of Medicine, College of Medicine, SUNY Downstate Health Sciences University, Brooklyn, NY
- Department of Cell Biology, College of Medicine, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - David Burstein
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, NY
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, NY
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, USA
- Mental Illness Research, Education and Clinical Center VISN2, James J. Peters VA Medical Center, Bronx, NY, USA
| | - Jacquelyn L. Meyers
- Department of Psychiatry and Behavioral Sciences and SUNY Downstate Health Sciences University, Brooklyn, NY
- Institute for Genomics in Health (IGH), SUNY Downstate Health Sciences University, Brooklyn, NY
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Yuli Li
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Nallakkandi Rajeevan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Frederick Sayward
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Kei-Hoi Cheung
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | | | | | | | - Lynn E. DeLisi
- Department of Psychiatry, Cambridge Health Alliance, Cambridge, MA
| | - Thomas R. Kosten
- Michael E. DeBakey VA Medical Center, Houston, TX
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX
| | - Hongyu Zhao
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Eric Achtyes
- Western Michigan University Homer Stryker M.D. School of Medicine, Kalamazoo, MI
| | - Peter Buckley
- University of Tennessee Health Science Center in Memphis, TN
| | - Dolores Malaspina
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
| | - Douglas Lehrer
- Department of Psychiatry, Wright State University, Dayton, OH
| | - Mark H. Rapaport
- Huntsman Mental Health Institute, Department of Psychiatry, University of Utah, Salt Lake City, UT
| | - David L. Braff
- Department of Psychiatry, University of California, San Diego, CA
- VA San Diego Healthcare System, San Diego, CA
| | - Michele T. Pato
- Department of Psychiatry, Robert Wood Johnson Medical School, New Brunswick, NJ
| | - Ayman H. Fanous
- Department of Psychiatry, University of Arizona College of Medicine-Phoenix, Phoenix, AZ
- Department of Psychiatry, VA Phoenix Healthcare System, Phoenix, AZ
| | - Carlos N. Pato
- Department of Psychiatry, Robert Wood Johnson Medical School, New Brunswick, NJ
| | | | | | | | - Grant D. Huang
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - J. Michael Gaziano
- Massachusetts Area Veterans Epidemiology, Research, and Information Center (MAVERIC), Jamaica Plain, MA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Saiju Pyarajan
- Massachusetts Area Veterans Epidemiology, Research, and Information Center (MAVERIC), Jamaica Plain, MA
| | - Kiran Girdhar
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, NY
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, NY
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
| | - Donghoon Lee
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, NY
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, NY
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
| | - Gabriel E. Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, NY
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, NY
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, USA
- Mental Illness Research, Education and Clinical Center VISN2, James J. Peters VA Medical Center, Bronx, NY, USA
| | - Mihaela Aslan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - John F. Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, NY
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, NY
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
| | - Georgios Voloudakis
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, NY
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, NY
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, USA
- Mental Illness Research, Education and Clinical Center VISN2, James J. Peters VA Medical Center, Bronx, NY, USA
| | - Philip D. Harvey
- Bruce W. Carter Miami Veterans Affairs (VA) Medical Center, Miami, FL
- University of Miami School of Medicine, Miami, FL
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, NY
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, NY
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, USA
- Mental Illness Research, Education and Clinical Center VISN2, James J. Peters VA Medical Center, Bronx, NY, USA
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3
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Bigdeli TB, Barr PB, Rajeevan N, Graham DP, Li Y, Meyers JL, Gorman BR, Peterson RE, Sayward F, Radhakrishnan K, Natarajan S, Nielsen DA, Wilkinson AV, Malhotra AK, Zhao H, Brophy M, Shi Y, O'Leary TJ, Gleason T, Przygodzki R, Pyarajan S, Muralidhar S, Gaziano JM, Huang GD, Concato J, Siever LJ, DeLisi LE, Kimbrel NA, Beckham JC, Swann AC, Kosten TR, Fanous AH, Aslan M, Harvey PD. Correlates of suicidal behaviors and genetic risk among United States veterans with schizophrenia or bipolar I disorder. Mol Psychiatry 2024; 29:2399-2407. [PMID: 38491344 DOI: 10.1038/s41380-024-02472-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 01/22/2024] [Accepted: 01/31/2024] [Indexed: 03/18/2024]
Abstract
Persons diagnosed with schizophrenia (SCZ) or bipolar I disorder (BPI) are at high risk for self-injurious behavior, suicidal ideation, and suicidal behaviors (SB). Characterizing associations between diagnosed health problems, prior pharmacological treatments, and polygenic scores (PGS) has potential to inform risk stratification. We examined self-reported SB and ideation using the Columbia Suicide Severity Rating Scale (C-SSRS) among 3,942 SCZ and 5,414 BPI patients receiving care within the Veterans Health Administration (VHA). These cross-sectional data were integrated with electronic health records (EHRs), and compared across lifetime diagnoses, treatment histories, follow-up screenings, and mortality data. PGS were constructed using available genomic data for related traits. Genome-wide association studies were performed to identify and prioritize specific loci. Only 20% of the veterans who reported SB had a corroborating ICD-9/10 EHR code. Among those without prior SB, more than 20% reported new-onset SB at follow-up. SB were associated with a range of additional clinical diagnoses, and with treatment with specific classes of psychotropic medications (e.g., antidepressants, antipsychotics, etc.). PGS for externalizing behaviors, smoking initiation, suicide attempt, and major depressive disorder were associated with SB. The GWAS for SB yielded no significant loci. Among individuals with a diagnosed mental illness, self-reported SB were strongly associated with clinical variables across several EHR domains. Analyses point to sequelae of substance-related and psychiatric comorbidities as strong correlates of prior and subsequent SB. Nonetheless, past SB was frequently not documented in health records, underscoring the value of regular screening with direct, in-person assessments, especially among high-risk individuals.
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Affiliation(s)
- Tim B Bigdeli
- VA New York Harbor Healthcare System, Brooklyn, NY, US.
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, US.
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US.
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US.
| | - Peter B Barr
- VA New York Harbor Healthcare System, Brooklyn, NY, US
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, US
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US
| | - Nallakkandi Rajeevan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - David P Graham
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Yuli Li
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - Jacquelyn L Meyers
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, US
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US
| | - Bryan R Gorman
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA, USA
| | - Roseann E Peterson
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, US
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US
| | - Frederick Sayward
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - Krishnan Radhakrishnan
- National Mental Health and Substance Use Policy Laboratory, Substance Abuse and Mental Health Services Administration, Rockville, MD, USA
| | | | - David A Nielsen
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Anna V Wilkinson
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
- Department of Epidemiology, Human Genetics and Environmental Science, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Anil K Malhotra
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
- Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA
- Department of Psychiatry, Hofstra Northwell School of Medicine, Hempstead, NY, USA
| | - Hongyu Zhao
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - Mary Brophy
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA, USA
- Boston University School of Medicine, Boston, MA, USA
| | - Yunling Shi
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA, USA
| | - Timothy J O'Leary
- Office of Research and Development, Veterans Health Administration, Washington, DC, USA
| | - Theresa Gleason
- Office of Research and Development, Veterans Health Administration, Washington, DC, USA
| | - Ronald Przygodzki
- Office of Research and Development, Veterans Health Administration, Washington, DC, USA
| | - Saiju Pyarajan
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA, USA
| | | | - J Michael Gaziano
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA, USA
- Harvard University, Boston, MA, USA
| | - Grant D Huang
- Office of Research and Development, Veterans Health Administration, Washington, DC, USA
| | - John Concato
- Yale University School of Medicine, New Haven, CT, USA
- Office of Research and Development, Veterans Health Administration, Washington, DC, USA
- Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Larry J Siever
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
| | - Lynn E DeLisi
- Department of Psychiatry, Cambridge Health Alliance, Cambridge, MA, USA
| | - Nathan A Kimbrel
- Durham VA Health Care System, Durham, NC, USA
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC, USA
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Jean C Beckham
- Durham VA Health Care System, Durham, NC, USA
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC, USA
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Alan C Swann
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Thomas R Kosten
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Ayman H Fanous
- VA New York Harbor Healthcare System, Brooklyn, NY, US
- Department of Psychiatry, University of Arizona College of Medicine Phoenix, Phoenix, AZ, USA
| | - Mihaela Aslan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - Philip D Harvey
- Bruce W. Carter Miami Veterans Affairs (VA) Medical Center, Miami, FL, USA
- University of Miami School of Medicine, Miami, FL, USA
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Parrish EM, Harvey PD, Ackerman RA, Moore RC, Depp CA, Gagnier M, Pinkham AE. The Tripartite Model of Depression in Schizophrenia and Bipolar Disorder: A Secondary Analysis. J Nerv Ment Dis 2023; 211:841-847. [PMID: 37734155 PMCID: PMC10615707 DOI: 10.1097/nmd.0000000000001714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/23/2023]
Abstract
ABSTRACT Models of affect, like the tripartite model, suggest that positive affect (PA) and negative affect (NA) are independent between subjects and negatively correlated within. Correlations may differ in bipolar disorder (BD) and schizophrenia. Using ecological momentary assessment (EMA) and clinical ratings, this secondary analysis evaluated the tripartite model by examining PA and NA. Two hundred eighty-one participants with BD or a psychotic disorder completed 30 days of EMA of PA and NA, and clinical raters assessed depression. PA and NA were more related between subjects and less related within subjects among participants with schizophrenia. In BD, lower momentary PA was positively associated with clinical ratings of depression, although greater momentary NA was not significantly associated with clinical ratings. In schizophrenia, the inverse was found. These results suggest that the tripartite model was not confirmed in people with schizophrenia or BD. However, PA and NA manifested associations in BD that were more congruent with population studies than in schizophrenia. These findings may have implications for clinical interventions targeting depression, PA, and NA in these populations.
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Affiliation(s)
- Emma M. Parrish
- San Diego State University / University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, California
| | - Philip D. Harvey
- University of Miami Miller School of Medicine, Miami, Florida, Research Service Miami VA Medical Center, Miami, FL
| | | | - Raeanne C. Moore
- University of California San Diego Department of Psychiatry, San Diego, California
| | - Colin A. Depp
- University of California San Diego Department of Psychiatry, San Diego, California
- Veterans Affairs San Diego Healthcare System, San Diego, California
| | - Marc Gagnier
- University of Miami Miller School of Medicine, Miami, Florida, Research Service Miami VA Medical Center, Miami, FL
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5
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Bigdeli TB, Barr PB, Rajeevan N, Graham DP, Li Y, Meyers JL, Gorman BR, Peterson RE, Sayward F, Radhakrishnan K, Natarajan S, Nielsen DA, Wilkinson AV, Malhotra AK, Zhao H, Brophy M, Shi Y, O’Leary TJ, Gleason T, Przygodzki R, Pyarajan S, Muralidhar S, Gaziano JM, Huang GD, Concato J, Siever LJ, DeLisi LE, Kimbrel NA, Beckham JC, Swann AC, Kosten TR, Fanous AH, Aslan M, Harvey PD. Correlates of suicidal behaviors and genetic risk among United States veterans with schizophrenia or bipolar I disorder. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.03.06.23286866. [PMID: 36945597 PMCID: PMC10029042 DOI: 10.1101/2023.03.06.23286866] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
Objective Persons diagnosed with schizophrenia (SCZ) or bipolar I disorder (BPI) are at high risk for self-injurious behavior, suicidal ideation, and suicidal behaviors (SB). Characterizing associations between diagnosed mental and physical health problems, prior pharmacological treatments, and aggregate genetic factors has potential to inform risk stratification and mitigation strategies. Methods In this study of 3,942 SCZ and 5,414 BPI patients receiving VA care, self-reported SB and ideation were assessed using the Columbia Suicide Severity Rating Scale (C-SSRS). These cross-sectional data were integrated with electronic health records (EHR), and compared by lifetime diagnoses, treatment histories, follow-up screenings, and mortality data. Polygenic scores (PGS) for traits related to psychiatric disorders, substance use, and cognition were constructed using available genomic data, and exploratory genome-wide association studies were performed to identify and prioritize specific loci. Results Only 20% of veterans who self-reported SB had a corroborating ICD-9/10 code in their EHR; and among those who denied prior behaviors, more than 20% reported new-onset SB at follow-up. SB were associated with a range of psychiatric and non-psychiatric diagnoses, and with treatment with specific classes of psychotropic medications (e.g., antidepressants, antipsychotics, etc.). PGS for externalizing behaviors, smoking, suicide attempt, and major depressive disorder were also associated with attempt and ideation. Conclusions Among individuals with a diagnosed mental illness, a GWAS for SB did not yield any significant loci. Self-reported SB were strongly associated with clinical variables across several EHR domains. Overall, clinical and polygenic analyses point to sequelae of substance-use related behaviors and other psychiatric comorbidities as strong correlates of prior and subsequent SB. Nonetheless, past SB was frequently not documented in clinical settings, underscoring the value of regular screening based on direct, in-person assessments, especially among high-risk individuals.
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Affiliation(s)
- Tim B. Bigdeli
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Peter B. Barr
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Nallakkandi Rajeevan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - David P. Graham
- Michael E. DeBakey VA Medical Center, Houston, TX
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX
| | - Yuli Li
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Jacquelyn L. Meyers
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Bryan R. Gorman
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA
| | - Roseann E. Peterson
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA
| | - Frederick Sayward
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Krishnan Radhakrishnan
- National Mental Health and Substance Use Policy Laboratory, Substance Abuse and Mental Health Services Administration, Rockville, MD
| | | | - David A. Nielsen
- Michael E. DeBakey VA Medical Center, Houston, TX
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX
| | - Anna V. Wilkinson
- Michael E. DeBakey VA Medical Center, Houston, TX
- National Mental Health and Substance Use Policy Laboratory, Substance Abuse and Mental Health Services Administration, Rockville, MD
| | - Anil K. Malhotra
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY
- Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY
- Department of Psychiatry, Hofstra Northwell School of Medicine, Hempstead, NY
| | - Hongyu Zhao
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Mary Brophy
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA
- Boston University School of Medicine, Boston, MA
| | - Yunling Shi
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA
| | - Timothy J. O’Leary
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Theresa Gleason
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Ronald Przygodzki
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Saiju Pyarajan
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - J. Michael Gaziano
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA
- Harvard University, Boston, MA
| | | | | | - Grant D. Huang
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - John Concato
- Yale University School of Medicine, New Haven, CT
- Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD
| | - Larry J. Siever
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
- James J. Peters Veterans Affairs Medical Center, Bronx, NY
| | - Lynn E. DeLisi
- Department of Psychiatry, Cambridge Health Alliance, Cambridge, MA
| | - Nathan A. Kimbrel
- Durham VA Health Care System, Durham, NC
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC
| | - Jean C. Beckham
- Durham VA Health Care System, Durham, NC
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC
| | - Alan C. Swann
- Michael E. DeBakey VA Medical Center, Houston, TX
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX
| | - Thomas R. Kosten
- Michael E. DeBakey VA Medical Center, Houston, TX
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX
- Departments of Neuroscience, Pharmacology, and Immunology and Rheumatology, Baylor College of Medicine, Houston, TX
| | - Ayman H. Fanous
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry, University of Arizona College of Medicine Phoenix, Phoenix, AZ
| | - Mihaela Aslan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Philip D. Harvey
- Bruce W. Carter Miami Veterans Affairs (VA) Medical Center, Miami, FL
- University of Miami School of Medicine, Miami, FL
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6
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Parrish EM, Harvey PD, Ackerman RA, Pinkham AE, Depp CA, Holden J, Granholm E. Time-course and convergence of positive and negative moods in participants with schizophrenia: An ecological momentary assessment study. J Psychiatr Res 2023; 159:76-81. [PMID: 36689853 DOI: 10.1016/j.jpsychires.2023.01.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 10/11/2022] [Accepted: 01/18/2023] [Indexed: 01/21/2023]
Abstract
INTRODUCTION Many people with schizophrenia report low levels of negative affect (NA), which may reflect biases in emotion processing. In the general population there is an inverse correlation between positive affect (PA) and NA. It is possible that this relationship is different among people with schizophrenia. This study aims to understand the relationship between PA and NA among people with schizophrenia, and explore PA and NA variability in relationship to social context. METHOD 105 participants with schizophrenia answered ecological momentary assessment (EMA) surveys seven times/day for seven days. They reported their experiences of mood states on a scale of one to seven: happiness, sadness, relaxation, and anxiety, as well as their social context (alone vs. with someone). Mood variability was calculated using the mean square of successive difference, and multilevel modeling was used to understand the time-course of reported moods within- and between-person. RESULTS 45% of surveys reported the absence of NA, though there was an inverse within-subjects correlation between PA and NA. Between-subjects, there was a large inverse correlation between PA and NA. Greater mood variability was associated with a greater number of social interactions. DISCUSSION The results of this study point to both the role of social context in mood variability, and momentary trends in mood experiences, with some individuals reporting no NA, some indicating both PA and NA, and some indicating a more normative affect pattern. Later research should address the possible impact of emotion perception bias and social interactions on moods states in schizophrenia.
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Affiliation(s)
- Emma M Parrish
- San Diego State University, University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA.
| | - Philip D Harvey
- University of Miami Miller School of Medicine, Research Service Miami VA Medical Center, Miami, FL, USA
| | | | | | - Colin A Depp
- University of California San Diego Department of Psychiatry, San Diego, CA, USA; Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
| | - Jason Holden
- University of California San Diego Department of Psychiatry, San Diego, CA, USA
| | - Eric Granholm
- University of California San Diego Department of Psychiatry, San Diego, CA, USA; Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
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Associations between symptom and neurocognitive dimensions in clinical high risk for psychosis. Schizophr Res Cogn 2022; 29:100260. [PMID: 35677653 PMCID: PMC9168614 DOI: 10.1016/j.scog.2022.100260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 05/27/2022] [Accepted: 05/28/2022] [Indexed: 11/22/2022]
Abstract
Introduction Clinical high risk for psychosis (CHR) is associated with mild cognitive impairments. Symptoms are clustered into positive, negative and disorganization symptoms. The association between specific symptom dimensions and cognitive functions remains unclear. The aim of this study was to investigate the associations between cognitive functions and positive, negative, and disorganization symptoms. Method 53 CHR subjects fulfilling criteria for attenuated psychotic syndrome in the Structural Interview for Prodromal Syndromes (SIPS) were assessed for cognitive function. Five cognitive domain z-scores were defined by contrasting with observed scores of a group of healthy controls (n = 40). Principal Components Analyses were performed to construct general cognitive composite scores; one using all subtests and one using the cognitive domains. Associations between cognitive functions and symptoms are presented as Spearman's rank correlations and partial Spearman's rank correlations adjusted for age and gender. Results Positive symptoms were negatively associated with executive functions and verbal memory, and disorganization symptoms with poorer verbal fluency. Negative symptoms were associated with better executive functioning. There were no significant associations between the general cognitive composites and any of the symptom domains, except for a trend for positive symptoms. Conclusion In line with previous research, data indicated associations between positive symptoms and poorer executive functioning. Negative symptoms may not be related to executive functions in CHR the same way as in psychosis. Our results could indicate that attenuated positive symptoms are more related to cognitive deficits in CHR than positive symptoms in schizophrenia and FEP.
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8
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Kolarcik CL, Bledsoe MJ, O'Leary TJ. Returning Individual Research Results to Vulnerable Individuals. THE AMERICAN JOURNAL OF PATHOLOGY 2022; 192:1218-1229. [PMID: 35750259 DOI: 10.1016/j.ajpath.2022.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2022] [Revised: 05/31/2022] [Accepted: 06/01/2022] [Indexed: 06/15/2023]
Abstract
Although issues associated with returning individual research results to study participants have been well explored, these issues have been less thoroughly investigated in vulnerable individuals and populations. Considerations regarding return of research results to these individuals and populations, including how best to ensure truly informed consent, how to minimize the risks and benefits of the return of research results, and how best to ensure justice may differ from those of the population at large. This article discusses the issues and challenges associated with the return of individual research results (such as genomic, proteomic, or other biomarker data) to potentially vulnerable individuals and populations, including those who may be vulnerable for cognitive, communicative, institutional, social, deferential, medical, economic, or social reasons. It explores factors that should be considered in the design, conduct, and oversight of ethically responsible research involving the return of research results to vulnerable individuals and populations and discuss recommendations for those engaged in this work.
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Affiliation(s)
- Christi L Kolarcik
- Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | | | - Timothy J O'Leary
- Office of Research and Development, Veterans Health Administration, Washington, District of Columbia; Department of Pathology, University of Maryland School of Medicine, Baltimore, Maryland.
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9
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Selloni A, Bhatia G, Ranganathan M, De Aquino JP. Multimodal Correlates of Cannabis Use among U.S. Veterans with Bipolar Disorder: An Integrated Study of Clinical, Cognitive, and Functional Outcomes. J Dual Diagn 2022; 18:81-91. [PMID: 35430960 PMCID: PMC9794455 DOI: 10.1080/15504263.2022.2053264] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Objective: Cannabis use (CU) is common among persons with bipolar disorder (BD). Evidence suggests that CU is associated with poorer outcomes among persons with BD; however, these findings remain inconsistent. The present exploratory study aims to examine clinical, functional, and cognitive correlates of CU among persons with BD. Methods: U.S. veterans with BD type I who participated in a large-scale, nationwide study were categorized into four groups: current CU, past CU, past other drug use, and no drug use. Bivariate analyses, univariate analyses of covariance, and Levene's Test for Equality of Variance were used to compare groups on clinical, cognitive, and functional measures. Results: Of 254 (84.6% male) veterans with BD type I included in the analyses, 13 (5.1%) had current CU, 37 (14.5%) past CU, 77 (30.3%) past other drug use, and 127 (50%) reported no drug use. BD with CU was associated with post-traumatic stress disorder (PTSD) and experiencing lifetime suicidal ideation. Notably, current CU was associated with higher working memory performance, compared to both past CU and no drug use. Likewise, current CU was associated with higher functional capacity, compared to past CU as well as no drug use. Conclusions: These findings contribute to the growing literature on the complex effects of cannabis on BD. As the commercialization and legalization of cannabis increases, further research in this area is warranted to quantify posed risks to this population, and thereby guide clinical decision-making.
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Affiliation(s)
- Alexandria Selloni
- VA Connecticut Healthcare System, 950 Campbell Avenue, Building 36/116A4, West Haven, CT 06516, USA
- Yale University School of Medicine, Department of Psychiatry, 300 George Street, New Haven, CT 06511, USA
| | | | - Mohini Ranganathan
- VA Connecticut Healthcare System, 950 Campbell Avenue, Building 36/116A4, West Haven, CT 06516, USA
- Yale University School of Medicine, Department of Psychiatry, 300 George Street, New Haven, CT 06511, USA
| | - Joao P. De Aquino
- VA Connecticut Healthcare System, 950 Campbell Avenue, Building 36/116A4, West Haven, CT 06516, USA
- Yale University School of Medicine, Department of Psychiatry, 300 George Street, New Haven, CT 06511, USA
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10
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Harvey PD, Bigdeli TB, Fanous AH, Li Y, Rajeevan N, Sayward F, Radhakrishnan K, Huang G, Aslan M. Cooperative Studies Program (CSP) #572: A Study of Serious Mental Illness in Veterans as a Pathway to personalized medicine in Schizophrenia and Bipolar Illness. PERSONALIZED MEDICINE IN PSYCHIATRY 2021; 27-28:10.1016/j.pmip.2021.100078. [PMID: 34222732 PMCID: PMC8247126 DOI: 10.1016/j.pmip.2021.100078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
BACKGROUND Personalization of psychiatric treatment includes treatment of symptoms, cognition and functional deficits, suicide, and medical co-morbidities. VA Collaborative Study 572 examined a large sample of male and female veterans with schizophrenia (n=3,942) and with bipolar disorder (n=5,414) with phenotyping and genomic analyses. We present the results to date and future directions. METHODS All veterans received a structured diagnostic interview and assessments of suicidal ideation and behavior, PTSD, and health. Veterans with schizophrenia were assessed for negative symptoms and lifetime depression. All were assessed with a cognitive and functional capacity assessment. Data for genome wide association studies were collected. Controls came from the VA Million Veteran Program. RESULTS Suicidal ideation or behavior was present in 66%. Cognitive and functional deficits were consistent with previous studies. 40% of the veterans with schizophrenia had a lifetime major depressive episode and PTSD was present in over 30%. Polygenic risk score (PRS) analyses indicated that cognitive and functional deficits overlapped with PRS for cognition, education, and intelligence in the general population and PRS for suicidal ideation and behavior correlated with previous PRS for depression and suicidal ideation and behavior, as did the PRS for PTSD. DISCUSSION Results to date provide directions for personalization of treatment in SMI, veterans with SMI, and veterans in general. The results of the genomic analyses suggest that cognitive deficits in SMI may be associated with general population features. Upcoming genomic analyses will reexamine the issues above, as well as genomic factors associated with smoking, substance abuse, negative symptoms, and treatment response.
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Affiliation(s)
- Philip D. Harvey
- Bruce W. Carter Miami Veterans Affairs (VA) Medical Center, Miami, FL
- University of Miami School of Medicine, Miami, FL
| | - Tim B. Bigdeli
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY
| | - Ayman H. Fanous
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY
| | - Yuli Li
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Nallakkandi Rajeevan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Frederick Sayward
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Krishnan Radhakrishnan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration
- University of Kentucky School of Medicine, Lexington, KY
| | - Grant Huang
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Mihaela Aslan
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY
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11
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Strassnig MT, Miller ML, Moore R, Depp CA, Pinkham AE, Harvey PD. Evidence for avolition in bipolar disorder? A 30-day ecological momentary assessment comparison of daily activities in bipolar disorder and schizophrenia. Psychiatry Res 2021; 300:113924. [PMID: 33848963 PMCID: PMC8141033 DOI: 10.1016/j.psychres.2021.113924] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Accepted: 04/02/2021] [Indexed: 12/20/2022]
Abstract
OBJECTIVES Disability is common in bipolar disorder (BD) and predicted by persistent sadness. We used ecological momentary assessment (EMA) to examine daily activities in people with BD and schizophrenia. We classified activities as productive, unproductive, or passive recreation, relating them to momentary sadness, location, and social context. METHODS 71 people with BD and 102 people with schizophrenia were sampled 3 times/day for 30 days with an EMA survey. Each survey asked where they were, with whom, what they were doing, and if they were sad. RESULTS People with BD were home more than 50% of the time. There were no differences in prevalence of activity types across diagnoses. People with BD were less likely to report only one activity since the prior survey, but the most surveys still reported only one. For both groups, sadness and being home and alone since the last survey was associated with less productive activity and more passive recreation. CONCLUSIONS Participants with BD and schizophrenia manifested high levels of unproductive and passive activities, predicted by momentary sadness. These activity patterns are consistent with descriptions of avolition and they minimally differentiated people with BD and schizophrenia. Previous reports of negative symptoms in BD may have been identifying these behaviors.
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Affiliation(s)
| | - Michelle L Miller
- University of Miami Miller School of Medicine, Miami, FL, United States
| | - Raeanne Moore
- UCSD Health Sciences Center, La Jolla, CA, United States
| | - Colin A Depp
- UCSD Health Sciences Center, La Jolla, CA, United States; San Diego VA Medical Center La Jolla, CA, United States
| | - Amy E Pinkham
- University of Texas at Dallas, Richardson, TX, United States; University of Texas Southwestern Medical Center, Dallas TX, United States
| | - Philip D Harvey
- University of Miami Miller School of Medicine, Miami, FL, United States; Bruce W. Carter VA Medical Center, Miami, FL, United States.
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12
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Durand D, Strassnig MT, Moore RC, Depp CA, Ackerman RA, Pinkham AE, Harvey PD. Self-reported social functioning and social cognition in schizophrenia and bipolar disorder: Using ecological momentary assessment to identify the origin of bias. Schizophr Res 2021; 230:17-23. [PMID: 33667854 PMCID: PMC8222067 DOI: 10.1016/j.schres.2021.02.011] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Revised: 02/14/2021] [Accepted: 02/14/2021] [Indexed: 12/20/2022]
Abstract
OBJECTIVES People with schizophrenia (SCZ) and bipolar illness (BPI) generate self-reports of their functioning that diverge from objective information. It has been suggested that these participants do not base such reports on daily experiences, relying on other information. We used ecological momentary assessment (EMA) to sample socially relevant daily activities in SCZ and BPI and related them to self-reported and observer-rated social functioning and social cognitive ability. METHODS 71 people with (BPI) were compared to 102 people with SCZ. Participants were sampled 3 times per day for 30 days with a smartphone-based survey. Each survey asked where they were, with whom they were, what they were doing, and if they were sad. Participants and observers were asked to provide ratings on social functioning and social cognitive abilities at the end of the EMA period. RESULTS There was no association between being home or alone and self-reports of everyday social functioning. In contrast observer ratings were highly correlated with the momentary survey results. Reports of very low levels of sadness were associated with overestimated functioning and participants who were commonly home and alone rated their social functioning as better than participants who were commonly away in the presence of others. IMPLICATIONS Both SCZ and BPI were marked by a disconnect between momentary experiences and self-reports. The largest effect was overestimation of functioning by participants who reported no sadness. Experience appears important, as participants who were routinely home and alone reported better social functioning than participants who spent more time others.
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Affiliation(s)
- Dante Durand
- University of Miami Miller School of Medicine, Miami, FL, United States of America
| | - Martin T Strassnig
- University of Miami Miller School of Medicine, Miami, FL, United States of America
| | - Raeanne C Moore
- UCSD Health Sciences Center, La Jolla, CA, United States of America
| | - Colin A Depp
- UCSD Health Sciences Center, La Jolla, CA, United States of America; San Diego VA Medical Center La Jolla, CA, United States of America
| | - Robert A Ackerman
- University of Texas at Dallas, Richardson, TX, United States of America
| | - Amy E Pinkham
- University of Texas at Dallas, Richardson, TX, United States of America; University of Texas Southwestern Medical Center, Dallas, TX, United States of America
| | - Philip D Harvey
- University of Miami Miller School of Medicine, Miami, FL, United States of America; Bruce W. Carter VA Medical Center, Miami, FL, United States of America.
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13
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Ye JY, Yang TX, Lui SSY, Cui JF, Qin XJ, Jia LX, Cheung EFC, Gan MY, Tan SP, Wang Y, Chan RCK. Schizophrenia patients with poor clinical insight report less subjective memory problems. Psych J 2021; 10:437-443. [PMID: 33594832 DOI: 10.1002/pchj.431] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Revised: 08/24/2020] [Accepted: 10/13/2020] [Indexed: 11/06/2022]
Abstract
This study aimed to explore the relationships among clinical insight, subjective memory complaints, and objective memory performance in patients with schizophrenia. We recruited 205 patients with schizophrenia and 221 healthy controls in this study. The participants were administered a subjective-report scale on memory (the Prospective and Retrospective Memory Questionnaire), and several objective memory tasks measuring verbal memory, visual memory, and working memory. Clinical insight was measured with an item in the Positive and Negative Syndrome Scale. We found that when patients with schizophrenia were divided into subgroups with good and poor insight, both subgroups showed impairment in memory performance compared with controls. The schizophrenia patients with good insight reported similar memory complaints as controls whereas patients with poor insight reported less memory complaints than did the controls. These findings suggest that clinical insight may be related to subjective memory complaints, but not objective memory performance.
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Affiliation(s)
- Jun-Yan Ye
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Tian-Xiao Yang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | | | - Ji-Fang Cui
- Institute of Educational Information and Statistics, National Institute of Education Sciences, Beijing, China
| | - Xiao-Jing Qin
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Lu-Xia Jia
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | | | | | | | - Ya Wang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Raymond C K Chan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
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Brain morphology does not clearly map to cognition in individuals on the bipolar-schizophrenia-spectrum: a cross-diagnostic study of cognitive subgroups. J Affect Disord 2021; 281:776-785. [PMID: 33246649 DOI: 10.1016/j.jad.2020.11.064] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Accepted: 11/08/2020] [Indexed: 01/11/2023]
Abstract
BACKGROUND Characterisation of brain morphological features common to cognitively similar individuals with bipolar disorder (BD) and schizophrenia spectrum disorders (SSD) may be key to understanding their shared neurobiological deficits. In the current study we examined whether three previously characterised cross-diagnostic cognitive subgroups differed among themselves and in comparison to healthy controls across measures of brain morphology. METHOD T1-weighted structural magnetic resonance imaging scans were obtained for 143 individuals; 65 healthy controls and 78 patients (SSD, n = 40; BD I, n = 38) classified into three cross-diagnostic cognitive subgroups: Globally Impaired (n = 24), Selectively Impaired (n = 32), and Superior/Near-Normal (n = 22). Cognitive subgroups were compared to each other and healthy controls on three separate analyses investigating (1) global, (2) regional, and (3) vertex-wise comparisons of brain volume, thickness, and surface area. RESULTS No significant subgroup differences were evident in global measures of brain morphology. In region of interest analyses, the Selectively Impaired subgroup had greater right accumbens volume than those Superior/Near-Normal subgroup and healthy controls, and the Superior/Near-Normal subgroup had reduced volume of the left entorhinal region compared to all other groups. In vertex-wise comparisons, the Globally Impaired subgroup had greater right precentral volume than the Selectively Impaired subgroup, and thicker cortex in the postcentral region relative to the Superior/Near-Normal subgroup. LIMITATIONS Exploration of medication effects was limited in our data. CONCLUSIONS Although some differences were evident in this sample, generally cross-diagnostic cognitive subgroups of individuals with SSD and BD did not appear to be clearly distinguished by patterns in brain morphology.
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15
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Bigdeli TB, Fanous AH, Li Y, Rajeevan N, Sayward F, Genovese G, Gupta R, Radhakrishnan K, Malhotra AK, Sun N, Lu Q, Hu Y, Li B, Chen Q, Mane S, Miller P, Cheung KH, Gur RE, Greenwood TA, Braff DL, Achtyes ED, Buckley PF, Escamilla MA, Lehrer D, Malaspina DP, McCarroll SA, Rapaport MH, Vawter MP, Pato MT, Pato CN, Zhao H, Kosten TR, Brophy M, Pyarajan S, Shi Y, O’Leary TJ, Gleason T, Przygodzki R, Muralidhar S, Gaziano JM, Huang GD, Concato J, Siever LJ, Aslan M, Harvey PD. Genome-Wide Association Studies of Schizophrenia and Bipolar Disorder in a Diverse Cohort of US Veterans. Schizophr Bull 2020; 47:517-529. [PMID: 33169155 PMCID: PMC7965063 DOI: 10.1093/schbul/sbaa133] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND Schizophrenia (SCZ) and bipolar disorder (BIP) are debilitating neuropsychiatric disorders, collectively affecting 2% of the world's population. Recognizing the major impact of these psychiatric disorders on the psychosocial function of more than 200 000 US Veterans, the Department of Veterans Affairs (VA) recently completed genotyping of more than 8000 veterans with SCZ and BIP in the Cooperative Studies Program (CSP) #572. METHODS We performed genome-wide association studies (GWAS) in CSP #572 and benchmarked the predictive value of polygenic risk scores (PRS) constructed from published findings. We combined our results with available summary statistics from several recent GWAS, realizing the largest and most diverse studies of these disorders to date. RESULTS Our primary GWAS uncovered new associations between CHD7 variants and SCZ, and novel BIP associations with variants in Sortilin Related VPS10 Domain Containing Receptor 3 (SORCS3) and downstream of PCDH11X. Combining our results with published summary statistics for SCZ yielded 39 novel susceptibility loci including CRHR1, and we identified 10 additional findings for BIP (28 326 cases and 90 570 controls). PRS trained on published GWAS were significantly associated with case-control status among European American (P < 10-30) and African American (P < .0005) participants in CSP #572. CONCLUSIONS We have demonstrated that published findings for SCZ and BIP are robustly generalizable to a diverse cohort of US veterans. Leveraging available summary statistics from GWAS of global populations, we report 52 new susceptibility loci and improved fine-mapping resolution for dozens of previously reported associations.
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Affiliation(s)
- Tim B Bigdeli
- VA New York Harbor Healthcare System, Brooklyn, NY,Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY
| | - Ayman H Fanous
- VA New York Harbor Healthcare System, Brooklyn, NY,Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY
| | - Yuli Li
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Nallakkandi Rajeevan
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Frederick Sayward
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Giulio Genovese
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA,Department of Genetics, Harvard Medical School, Boston, MA
| | - Rishab Gupta
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY
| | - Krishnan Radhakrishnan
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,College of Medicine, University of Kentucky, Lexington, KY
| | - Anil K Malhotra
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY,Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY,Department of Psychiatry, Hofstra Northwell School of Medicine, Hempstead, NY
| | - Ning Sun
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Qiongshi Lu
- Department of Medicine, Yale School of Medicine, New Haven, CT,Department of Biostatistics & Medical Informatics, University of Wisconsin-Madison, Madison, WI
| | - Yiming Hu
- Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Boyang Li
- Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Quan Chen
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Shrikant Mane
- Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Perry Miller
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Kei-Hoi Cheung
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Raquel E Gur
- Departments of Psychiatry and Child & Adolescent Psychiatry and Lifespan Brain Institute, University of Pennsylvania Perelman School of Medicine and Children’s Hospital of Philadelphia, Philadelphia, PA
| | | | - David L Braff
- Department of Psychiatry, University of California, La Jolla, San Diego, CA,VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA
| | | | - Eric D Achtyes
- Cherry Health and Michigan State University College of Human Medicine, Grand Rapids, MI
| | - Peter F Buckley
- School of Medicine, Virginia Commonwealth University, Richmond, VA
| | - Michael A Escamilla
- Department of Psychiatry, School of Medicine, University of Texas Rio Grande Valley, Harlingen, TX
| | - Douglas Lehrer
- Department of Psychiatry, Wright State University, Dayton, OH
| | - Dolores P Malaspina
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Steven A McCarroll
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA,Department of Genetics, Harvard Medical School, Boston, MA
| | - Mark H Rapaport
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA
| | - Marquis P Vawter
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA
| | - Michele T Pato
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY
| | - Carlos N Pato
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY
| | | | - Hongyu Zhao
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Thomas R Kosten
- Departments of Psychiatry, Neuroscience, Pharmacology, and Immunology and Rheumatology, Baylor College of Medicine, Houston, TX
| | - Mary Brophy
- Massachusetts Area Veterans Epidemiology, Research, and Information Center (MAVERIC), Jamaica Plain, MA,Section of Hematology and Medical Oncology, Boston University School of Medicine, Boston, MA
| | - Saiju Pyarajan
- Massachusetts Area Veterans Epidemiology, Research, and Information Center (MAVERIC), Jamaica Plain, MA
| | - Yunling Shi
- Massachusetts Area Veterans Epidemiology, Research, and Information Center (MAVERIC), Jamaica Plain, MA
| | - Timothy J O’Leary
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Theresa Gleason
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Ronald Przygodzki
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - J Michael Gaziano
- Massachusetts Area Veterans Epidemiology, Research, and Information Center (MAVERIC), Jamaica Plain, MA,Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | | | - Grant D Huang
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - John Concato
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Larry J Siever
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY,University of Miami Miller School of Medicine, James J. Peters Veterans Affairs Medical Center, Bronx, NY
| | - Mihaela Aslan
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Philip D Harvey
- Research Service Bruce W. Carter VA Medical Center, Miami, FL,Department of Psychiatry, University of Miami Miller School of Medicine, Miami, FL,To whom correspondence should be addressed; Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, 1120 NW 14th Street, Suite 1450 Miami, FL 33136, USA; tel: (305)-243-4094, fax: (305)-243-1619, e-mail:
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16
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Li W, Zhou FC, Zhang L, Ng CH, Ungvari GS, Li J, Xiang YT. Comparison of cognitive dysfunction between schizophrenia and bipolar disorder patients: A meta-analysis of comparative studies. J Affect Disord 2020; 274:652-661. [PMID: 32663999 DOI: 10.1016/j.jad.2020.04.051] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Revised: 04/19/2020] [Accepted: 04/27/2020] [Indexed: 01/01/2023]
Abstract
OBJECTIVE Cognitive dysfunction is common in both schizophrenia and bipolar disorder. This is a meta-analysis of studies that compared cognitive dysfunction between schizophrenia and bipolar disorder. METHODS Both international and Chinese databases were systematically searched. Studies that compared cognitive function between schizophrenia and bipolar disorder with the MATRICS Consensus Cognitive Battery (MCCB) were analyzed using the random-effects model. RESULTS Twelve studies with 9,518 participants (4,411 schizophrenia and 5,107 bipolar patients) were included in the analyses. Schizophrenia patients performed significantly worse than bipolar patients on the MCCB total scores with a large effect size (SMD=-0.80, 95%CI: -1.21 to -0.39), as well as on all the 7 subscale scores; attention (SMD=-2.56, 95%CI: -3.55 to -1.57) and social cognition (SMD=-0.86, 95%CI: -1.13 to -0.58) with large effect sizes; and speed of processing (SMD=-0.75, 95%CI: -1.00 to -0.49), working memory (SMD=-0.68, 95%CI: -0.91 to -0.45), verbal learning (SMD=-0.78, 95%CI: -0.95 to -0.61), visual learning (SMD=-0.65, 95%CI: -0.83 to -0.48), and reasoning and problem solving (SMD=-0.61, 95%CI: -0.93 to -0.29) with medium effect sizes. CONCLUSION Compared to bipolar patients, patients with schizophrenia had more severe cognitive dysfunction in this meta-analysis, particularly in attention and social cognition. Timely assessment and treatment of cognitive dysfunction should be part of standard management protocols in both schizophrenia and bipolar disorder.
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Affiliation(s)
- Wen Li
- Unit of Psychiatry, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao SAR, China; Center for Cognition and Brain Sciences, University of Macau, Macao SAR, China
| | - Fu-Chun Zhou
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Ling Zhang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Chee H Ng
- Department of Psychiatry, The Melbourne Clinic and St Vincent's Hospital, University of Melbourne, Richmond, Victoria, Australia
| | - Gabor S Ungvari
- Division of Psychiatry, School of Medicine, University of Western Australia, Perth, Australia; University of Notre Dame Australia, Fremantle, Australia
| | - Jun Li
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, China
| | - Yu-Tao Xiang
- Unit of Psychiatry, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao SAR, China; Center for Cognition and Brain Sciences, University of Macau, Macao SAR, China.
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17
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Aslan M, Radhakrishnan K, Rajeevan N, Sueiro M, Goulet JL, Li Y, Depp C, Concato J, Harvey PD. Suicidal ideation, behavior, and mortality in male and female US veterans with severe mental illness. J Affect Disord 2020; 267:144-152. [PMID: 32063566 DOI: 10.1016/j.jad.2020.02.022] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2019] [Revised: 12/20/2019] [Accepted: 02/06/2020] [Indexed: 01/17/2023]
Abstract
BACKGROUND We compared male and female American veterans with schizophrenia or bipolar disorder regarding clinical characteristics associated with lifetime suicidal ideation and behavior. Subsequent mortality, including death by suicide, was also assessed. METHODS Data from questionnaires and face-to-face evaluations were collected during 2011-2014 from 8,049 male and 1,290 female veterans with schizophrenia or bipolar disorder. In addition to comparing male-female characteristics, Cox regression models-adjusted for demographic information, medical-psychiatric comorbidities, and self-reported suicidal ideation and behavior-were used to examine gender differences in associations of putative risk factors with suicide-specific and all-cause mortality during up to six years of follow-up. RESULTS Women overall were younger, more likely to report a history of suicidal behavior, less likely to be substance abusers, and had lower overall mortality during follow-up. Among women only, psychiatric comorbidity was paradoxically associated with lower all-cause mortality (hazard ratio [HR]=0.53, 95% CI, 0.29-0.96, p = 0.037 for 1 disorder vs. none; HR=0.44, 95% CI, 0.25-0.77, p = 0.004 for ≥2 disorders vs. none). Suicide-specific mortality involved relatively few events, but crude rates were an order of magnitude higher than in the U.S. general and overall veteran populations. LIMITATIONS Incomplete cause-of-death information and low statistical power for male-female comparisons regarding mortality. CONCLUSIONS Female veterans with SMI differed from females in the general population by having a higher risk of suicide attempts. They also had more lifetime suicide attempts than male veterans with same diagnoses. These differences should inform public policy and clinical planning.
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Affiliation(s)
- Mihaela Aslan
- VA Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT, United States; Department of Medicine, Yale School of Medicine, New Haven, CT, United States
| | - Krishnan Radhakrishnan
- VA Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT, United States; College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Nallakkandi Rajeevan
- VA Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT, United States; Yale Center for Medical Informatics, Yale School of Medicine, New Haven, CT, United States
| | - Melyssa Sueiro
- Research Service, Bruce W. Carter Veterans Affairs (VA) Medical Center, Miami, FL, United States
| | - Joseph L Goulet
- Yale Center for Medical Informatics, Yale School of Medicine, New Haven, CT, United States; Pain, Research, Informatics, Multimorbidities, & Education Center, West Haven, CT, United States
| | - Yuli Li
- VA Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT, United States; Yale Center for Medical Informatics, Yale School of Medicine, New Haven, CT, United States
| | - Colin Depp
- VA San Diego Healthcare System, San Diego, CA, United States; Department of Psychiatry, UC San Diego, La Jolla, CA, United States
| | - John Concato
- VA Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT, United States; Department of Medicine, Yale School of Medicine, New Haven, CT, United States
| | - Philip D Harvey
- Research Service, Bruce W. Carter Veterans Affairs (VA) Medical Center, Miami, FL, United States; Department of Psychiatry, University of Miami Miller School of Medicine, Miami, FL, United States.
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18
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Harvey PD, Sun N, Bigdeli TB, Fanous AH, Aslan M, Malhotra AK, Lu Q, Hu Y, Li B, Chen Q, Mane S, Miller P, Rajeevan N, Sayward F, Cheung KH, Li Y, Greenwood TA, Gur RE, Braff DL, Brophy M, Pyarajan S, O'Leary TJ, Gleason T, Przygodszki R, Muralidhar S, Gaziano JM, Concato J, Zhao H, Siever LJ. Genome-wide association study of cognitive performance in U.S. veterans with schizophrenia or bipolar disorder. Am J Med Genet B Neuropsychiatr Genet 2020; 183:181-194. [PMID: 31872970 DOI: 10.1002/ajmg.b.32775] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Revised: 11/22/2019] [Accepted: 12/09/2019] [Indexed: 12/25/2022]
Abstract
Cognitive impairment is a frequent and serious problem in patients with various forms of severe mental illnesses (SMI), including schizophrenia (SZ) and bipolar disorder (BP). Recent research suggests genetic links to several cognitive phenotypes in both SMI and in the general population. Our goal in this study was to identify potential genomic signatures of cognitive functioning in veterans with severe mental illness and compare them to previous findings for cognition across different populations. Veterans Affairs (VA) Cooperative Studies Program (CSP) Study #572 evaluated cognitive and functional capacity measures among SZ and BP patients. In conjunction with the VA Million Veteran Program, 3,959 European American (1,095 SZ, 2,864 BP) and 2,601 African American (1,095 SZ, 2,864 BP) patients were genotyped using a custom Affymetrix Axiom Biobank array. We performed a genome-wide association study of global cognitive functioning, constructed polygenic scores for SZ and cognition in the general population, and examined genetic correlations with 2,626 UK Biobank traits. Although no single locus attained genome-wide significance, observed allelic effects were strongly consistent with previous studies. We observed robust associations between global cognitive functioning and polygenic scores for cognitive performance, intelligence, and SZ risk. We also identified significant genetic correlations with several cognition-related traits in UK Biobank. In a diverse cohort of U.S. veterans with SZ or BP, we demonstrate broad overlap of common genetic effects on cognition in the general population, and find that greater polygenic loading for SZ risk is associated with poorer cognitive performance.
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Affiliation(s)
- Philip D Harvey
- Research Service, Bruce W. Carter Miami Veterans Affairs (VA) Medical Center, Miami, Florida.,Department of Psychiatry and Behavioral Sciences, University of Miami School of Medicine, Miami, Florida
| | - Ning Sun
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut.,Yale University School of Medicine, New Haven, Connecticut
| | - Tim B Bigdeli
- Department of Psychiatry, VA New York Harbor Healthcare System, Brooklyn, New York.,Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, New York
| | - Ayman H Fanous
- Department of Psychiatry, VA New York Harbor Healthcare System, Brooklyn, New York.,Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, New York
| | - Mihaela Aslan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut.,Yale University School of Medicine, New Haven, Connecticut
| | - Anil K Malhotra
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, New York.,Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, New York.,Department of Psychiatry, Hofstra Northwell School of Medicine, Hempstead, New York
| | - Qiongshi Lu
- Yale University School of Medicine, New Haven, Connecticut.,Department of Biostatistics & Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin
| | - Yiming Hu
- Yale University School of Medicine, New Haven, Connecticut
| | - Boyang Li
- Yale University School of Medicine, New Haven, Connecticut
| | - Quan Chen
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut.,Yale University School of Medicine, New Haven, Connecticut
| | - Shrikant Mane
- Yale University School of Medicine, New Haven, Connecticut
| | - Perry Miller
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut.,Yale University School of Medicine, New Haven, Connecticut
| | - Nallakkandi Rajeevan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut.,Yale University School of Medicine, New Haven, Connecticut
| | - Frederick Sayward
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut.,Yale University School of Medicine, New Haven, Connecticut
| | - Kei-Hoi Cheung
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut.,Yale University School of Medicine, New Haven, Connecticut
| | - Yuli Li
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut.,Yale University School of Medicine, New Haven, Connecticut
| | | | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine and Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.,Department of Child & Adolescent Psychiatry and Lifespan Brain Institute, University of Pennsylvania Perelman School of Medicine and Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - David L Braff
- Department of Psychiatry, University of California, San Diego, California.,VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, California
| | | | - Mary Brophy
- Massachusetts Area Veterans Epidemiology Research, and Information Center (MAVERIC), Jamaica Plain, Massachusetts.,Boston University School of Medicine, Boston, Massachusetts
| | - Saiju Pyarajan
- Massachusetts Area Veterans Epidemiology Research, and Information Center (MAVERIC), Jamaica Plain, Massachusetts
| | - Timothy J O'Leary
- Office of Research and Development, Veterans Health Administration, Washington, District of Columbia
| | - Theresa Gleason
- Office of Research and Development, Veterans Health Administration, Washington, District of Columbia
| | - Ronald Przygodszki
- Office of Research and Development, Veterans Health Administration, Washington, District of Columbia
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, District of Columbia
| | - J Michael Gaziano
- Massachusetts Area Veterans Epidemiology Research, and Information Center (MAVERIC), Jamaica Plain, Massachusetts.,Department of Medicine, Harvard University, Boston, Massachusetts
| | - John Concato
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut.,Yale University School of Medicine, New Haven, Connecticut
| | - Hongyu Zhao
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut.,Yale University School of Medicine, New Haven, Connecticut
| | - Larry J Siever
- James J. Peters Veterans Affairs Medical Center, Bronx, New York.,Department of Psychiatry, Mount Sinai School of Medicine, New York, New York
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19
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Oliveri LN, Awerbuch AW, Jarskog LF, Penn DL, Pinkham A, Harvey PD. Depression predicts self assessment of social function in both patients with schizophrenia and healthy people. Psychiatry Res 2020; 284:112681. [PMID: 31740212 PMCID: PMC7012719 DOI: 10.1016/j.psychres.2019.112681] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Revised: 11/02/2019] [Accepted: 11/04/2019] [Indexed: 12/01/2022]
Abstract
BACKGROUND Impairments in social functioning are central to Schizophrenia (SCZ). Patients with SCZ have challenges in the ability to evaluate their functioning. A correlate of self-assessments in SCZ is depression, wherein negligible depression predicts overestimation. Healthy individuals misestimate their functioning, but mild dysthymia predicts accuracy. We examined depression, gender, and schizophrenia as predictors of self-reported everyday functioning. METHODS 218 people with SCZ and 154 healthy controls self-reported their social functioning. They self-reported their depression with the Beck Depression Inventory (BDI) and their social cognitive ability on the Observable Social Cognition Rating Scale (OSCARS). RESULTS 64% of subjects were male. Schizophrenia patients reported more depression, poorer social functioning, and worse social cognition. Linear regression analyses revealed significant correlations between self-reported social functioning and BDI scores, which also predicted self-reported social cognition. There was no significant effect of sex on self-reports of social functioning or social cognition. Finally, when BDI and OSCARS were directly compared to diagnosis and sex for prediction of self-reported social functioning, there was no impact of diagnosis or sex. IMPLICATIONS Self-reported interpersonal functioning is determined by current depression. Both healthy people and people with schizophrenia index their social functioning and their social cognitive by their level of depression.
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Affiliation(s)
- Lisa N. Oliveri
- Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL
| | - Adam W. Awerbuch
- Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL
| | | | - David L. Penn
- Department of Psychology, University of North Carolina, Chapel Hill, NC,School of Behavioural and Health Sciences, Australian Catholic University, Melbourne, VIC
| | - Amy Pinkham
- School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX.,Department of Psychiatry, University of Texas Southwestern Medical School, Dallas, TX
| | - Philip D. Harvey
- Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL,Research Service, Miami VA Healthcare System, Miami, FL
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20
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Abstract
Cognitive dysfunction is common in many psychiatric disorders. While it has long been described as a core feature in schizophrenia, more recent data suggest qualitatively similar impairments in patients with bipolar disorder and major depressive disorder. There is compelling evidence to suggest that cognitive impairment contributes directly to functional disability and reduced quality of like across these disorders. As current treatments focus heavily on "primary" symptoms of mood and psychosis, the standard of care typically leaves cognitive deficits unmanaged. With this in mind, the field has recently begun to consider intervening directly on this important symptom domain, with several ongoing trials in schizophrenia. Fewer studies have targeted cognition in bipolar disorder and still fewer in MDD. With progress toward considering this domain as a target for treatment comes the need for consensus guidelines and methodological recommendations on cognitive trial design. In this manuscript, we first summarize the work conducted to date in this area for schizophrenia and for bipolar disorder. We then begin to address these same issues in MDD and emphasize the need for additional work in this area.
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21
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Van Rheenen TE, Lewandowski KE, Tan EJ, Ospina LH, Ongur D, Neill E, Gurvich C, Pantelis C, Malhotra AK, Rossell SL, Burdick KE. Characterizing cognitive heterogeneity on the schizophrenia-bipolar disorder spectrum. Psychol Med 2017; 47:1848-1864. [PMID: 28241891 DOI: 10.1017/s0033291717000307] [Citation(s) in RCA: 130] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
BACKGROUND Current group-average analysis suggests quantitative but not qualitative cognitive differences between schizophrenia (SZ) and bipolar disorder (BD). There is increasing recognition that cognitive within-group heterogeneity exists in both disorders, but it remains unclear as to whether between-group comparisons of performance in cognitive subgroups emerging from within each of these nosological categories uphold group-average findings. We addressed this by identifying cognitive subgroups in large samples of SZ and BD patients independently, and comparing their cognitive profiles. The utility of a cross-diagnostic clustering approach to understanding cognitive heterogeneity in these patients was also explored. METHOD Hierarchical clustering analyses were conducted using cognitive data from 1541 participants (SZ n = 564, BD n = 402, healthy control n = 575). RESULTS Three qualitatively and quantitatively similar clusters emerged within each clinical group: a severely impaired cluster, a mild-moderately impaired cluster and a relatively intact cognitive cluster. A cross-diagnostic clustering solution also resulted in three subgroups and was superior in reducing cognitive heterogeneity compared with disorder clustering independently. CONCLUSIONS Quantitative SZ-BD cognitive differences commonly seen using group averages did not hold when cognitive heterogeneity was factored into our sample. Members of each corresponding subgroup, irrespective of diagnosis, might be manifesting the outcome of differences in shared cognitive risk factors.
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Affiliation(s)
- T E Van Rheenen
- Melbourne Neuropsychiatry Centre,Department of Psychiatry,University of Melbourne and Melbourne Health,Carlton,VIC,Australia
| | - K E Lewandowski
- Schizophrenia and Bipolar Disorder Program,McLean Hospital,Belmont, MA,USA
| | - E J Tan
- Brain and Psychological Sciences Research Centre,Faculty of Health, Arts and Design,School of Health Sciences, Swinburne University,Hawthorn,VIC,Australia
| | - L H Ospina
- Icahn School of Medicine,Mount Sinai, NY,USA
| | - D Ongur
- Schizophrenia and Bipolar Disorder Program,McLean Hospital,Belmont, MA,USA
| | - E Neill
- Brain and Psychological Sciences Research Centre,Faculty of Health, Arts and Design,School of Health Sciences, Swinburne University,Hawthorn,VIC,Australia
| | - C Gurvich
- Cognitive Neuropsychiatry Laboratory,Monash Alfred Psychiatry Research Centre, The Alfred Hospital and Central Clinical School, Monash University,Melbourne,VIC,Australia
| | - C Pantelis
- Melbourne Neuropsychiatry Centre,Department of Psychiatry,University of Melbourne and Melbourne Health,Carlton,VIC,Australia
| | - A K Malhotra
- Hofstra Northwell School of Medicine,Hempstead, NY,USA
| | - S L Rossell
- Brain and Psychological Sciences Research Centre,Faculty of Health, Arts and Design,School of Health Sciences, Swinburne University,Hawthorn,VIC,Australia
| | - K E Burdick
- Icahn School of Medicine,Mount Sinai, NY,USA
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22
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Ishisaka N, Shimano S, Miura T, Motomura K, Horii M, Imanaga H, Kishimoto J, Kaneda Y, Sora I, Kanba S. Neurocognitive profile of euthymic Japanese patients with bipolar disorder. Psychiatry Clin Neurosci 2017; 71:373-382. [PMID: 28025861 DOI: 10.1111/pcn.12500] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2016] [Revised: 11/17/2016] [Accepted: 12/19/2016] [Indexed: 12/01/2022]
Abstract
AIM Neurocognitive impairment is one of the core symptoms of bipolar disorder (BD). The MATRICS Cognitive Consensus Battery (MCCB) is a potential consensus assessment tool to evaluate cognitive function in patients with BD. Here, we report on cognitive deficits evaluated using the MCCB Japanese version (MCCB-J) in euthymic Japanese patients with BD, and compare them with scores in previous studies. METHODS We compared neurocognitive function in 25 patients with euthymic BD and 53 healthy controls (HC). Additionally, we searched all available databases for studies that have evaluated cognitive function in BD using the MCCB, and conducted a meta-analysis. RESULTS Canonical discriminant analysis revealed significant differences in MCCB-J domain scores between BD and HC. Patients with BD performed significantly worse on visual learning, social cognition, speed of processing, and MCCB composite scores. Our meta-analysis revealed that patients with BD performed worse than HC, as reflected by MCCB composite scores and scores on all seven cognitive domains. However, there are differences in the cognitive deficits identified in previous studies compared with our participants, particularly social cognition. CONCLUSION As reported in previous studies, neurocognitive deficits were observed in Japanese euthymic BD patients assessed using the MCCB-J. Further study is needed to clarify whether differences in social cognition between this study and previous studies are a result of coping mechanisms for social settings in Japanese populations.
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Affiliation(s)
- Nozomi Ishisaka
- Department of Neuropsychiatry, Kyushu University, Fukuoka, Japan
| | - Satomi Shimano
- Department of Neuropsychiatry, Kyushu University, Fukuoka, Japan
| | - Tomofumi Miura
- Department of Neuropsychiatry, Kyushu University, Fukuoka, Japan
| | - Keisuke Motomura
- Department of Neuropsychiatry, Kyushu University, Fukuoka, Japan
| | - Machiko Horii
- Department of Neuropsychiatry, Kyushu University, Fukuoka, Japan
| | - Hisako Imanaga
- Department of Neuropsychiatry, Kyushu University, Fukuoka, Japan
| | - Junji Kishimoto
- Department of Research and Development of Next Generation Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | | | - Ichiro Sora
- Department of Psychiatry, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Shigenobu Kanba
- Department of Neuropsychiatry, Kyushu University, Fukuoka, Japan
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23
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Harvey PD, Twamley EW, Pinkham AE, Depp CA, Patterson TL. Depression in Schizophrenia: Associations With Cognition, Functional Capacity, Everyday Functioning, and Self-Assessment. Schizophr Bull 2017; 43:575-582. [PMID: 27440672 PMCID: PMC5463852 DOI: 10.1093/schbul/sbw103] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Depressed mood has a complex relationship with self-evaluation of personal competence in multiple populations. The absence of depression may be associated with overestimation of abilities, while mild depression seems to lead to accurate self-assessment. Significant depression may lead to underestimation of functioning. In this study, we expand on our previous work by directly comparing the association between different levels of depression, everyday functioning, cognitive and functional capacity performance, and self-assessment of everyday functioning in a large (n = 406) sample of outpatients with schizophrenia. Participants with very low self-reported depression overestimated their everyday functioning compared with informant reports. Higher levels of depression were associated with more accurate self-assessment, but no subgroup of patients underestimated their functioning. Depressive symptom severity was associated with poorer informant-rated social functioning, but there were no differences in vocational functioning, everyday activities, cognitive performance, and functional capacity associated with the severity of self-reported depression. There was minimal evidence of impact of depression on most aspects of everyday functioning and objective test performance and a substantial relationship between depression and accuracy of self-assessment.
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Affiliation(s)
- Philip D. Harvey
- Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, 1120 NW 14th Street, Miami, FL;,Research Service, Bruce W. Carter VA Medical Center, Miami, FL
| | - Elizabeth W. Twamley
- Department of Psychiatry, University of California, San Diego, La Jolla, CA;,Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, La Jolla, CA
| | - Amy E. Pinkham
- School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX;,Department of Psychiatry, The University of Texas Southwestern Medical School, Dallas, TX
| | - Colin A. Depp
- Department of Psychiatry, University of California, San Diego, La Jolla, CA;,Psychology Service, San Diego VA Healthcare System, La Jolla, CA
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Harvey PD. Inflammation in Schizophrenia: What It Means and How to Treat It. Am J Geriatr Psychiatry 2017; 25:62-63. [PMID: 27876351 DOI: 10.1016/j.jagp.2016.10.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2016] [Accepted: 10/25/2016] [Indexed: 11/28/2022]
Affiliation(s)
- Philip D Harvey
- Miller School of Medicine, University of Miami, Miami, FL 33136; Research Service, Bruce W. Carter VA Medical Center, Miami, FL 33136.
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Hou L, Sun N, Mane S, Sayward F, Rajeevan N, Cheung KH, Cho K, Pyarajan S, Aslan M, Miller P, Harvey PD, Gaziano JM, Concato J, Zhao H. Impact of genotyping errors on statistical power of association tests in genomic analyses: A case study. Genet Epidemiol 2016; 41:152-162. [PMID: 28019059 DOI: 10.1002/gepi.22027] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2016] [Revised: 08/15/2016] [Accepted: 10/10/2016] [Indexed: 12/13/2022]
Abstract
A key step in genomic studies is to assess high throughput measurements across millions of markers for each participant's DNA, either using microarrays or sequencing techniques. Accurate genotype calling is essential for downstream statistical analysis of genotype-phenotype associations, and next generation sequencing (NGS) has recently become a more common approach in genomic studies. How the accuracy of variant calling in NGS-based studies affects downstream association analysis has not, however, been studied using empirical data in which both microarrays and NGS were available. In this article, we investigate the impact of variant calling errors on the statistical power to identify associations between single nucleotides and disease, and on associations between multiple rare variants and disease. Both differential and nondifferential genotyping errors are considered. Our results show that the power of burden tests for rare variants is strongly influenced by the specificity in variant calling, but is rather robust with regard to sensitivity. By using the variant calling accuracies estimated from a substudy of a Cooperative Studies Program project conducted by the Department of Veterans Affairs, we show that the power of association tests is mostly retained with commonly adopted variant calling pipelines. An R package, GWAS.PC, is provided to accommodate power analysis that takes account of genotyping errors (http://zhaocenter.org/software/).
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Affiliation(s)
- Lin Hou
- Clinical Epidemiology Research Center (CERC), Veterans Affairs (VA) Cooperative Studies Program, VA Connecticut Healthcare System, West Haven, Connecticut, United States of America.,Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Ning Sun
- Clinical Epidemiology Research Center (CERC), Veterans Affairs (VA) Cooperative Studies Program, VA Connecticut Healthcare System, West Haven, Connecticut, United States of America.,Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Shrikant Mane
- Department of Genetics, Yale University School of Medicine, New Haven, Connecticut, United States of America
| | - Fred Sayward
- Clinical Epidemiology Research Center (CERC), Veterans Affairs (VA) Cooperative Studies Program, VA Connecticut Healthcare System, West Haven, Connecticut, United States of America.,Center for Medical Informatics, Yale University School of Medicine, New Haven, Connecticut, United States of America
| | - Nallakkandi Rajeevan
- Clinical Epidemiology Research Center (CERC), Veterans Affairs (VA) Cooperative Studies Program, VA Connecticut Healthcare System, West Haven, Connecticut, United States of America.,Center for Medical Informatics, Yale University School of Medicine, New Haven, Connecticut, United States of America
| | - Kei-Hoi Cheung
- Clinical Epidemiology Research Center (CERC), Veterans Affairs (VA) Cooperative Studies Program, VA Connecticut Healthcare System, West Haven, Connecticut, United States of America.,Center for Medical Informatics, Yale University School of Medicine, New Haven, Connecticut, United States of America
| | - Kelly Cho
- Massachusetts Area Veterans Epidemiology Research and Information Center (MAVERIC), VA Cooperative Studies Program, VA Boston Healthcare System, Boston, Massachusetts, United States of America.,Department of Medicine, Harvard University School of Medicine, Boston, Massachusetts, United States of America
| | - Saiju Pyarajan
- Massachusetts Area Veterans Epidemiology Research and Information Center (MAVERIC), VA Cooperative Studies Program, VA Boston Healthcare System, Boston, Massachusetts, United States of America.,Department of Medicine, Harvard University School of Medicine, Boston, Massachusetts, United States of America
| | - Mihaela Aslan
- Clinical Epidemiology Research Center (CERC), Veterans Affairs (VA) Cooperative Studies Program, VA Connecticut Healthcare System, West Haven, Connecticut, United States of America.,Department of Medicine, Yale University School of Medicine, New Haven, Connecticut, United States of America
| | - Perry Miller
- Clinical Epidemiology Research Center (CERC), Veterans Affairs (VA) Cooperative Studies Program, VA Connecticut Healthcare System, West Haven, Connecticut, United States of America.,Center for Medical Informatics, Yale University School of Medicine, New Haven, Connecticut, United States of America
| | - Philip D Harvey
- Bruce W. Carter Miami Veterans Affairs (VA) Medical Center, Miami, Florida, United States of America.,Department of Psychiatry, University of Miami Miller School of Medicine, Miami, Florida, United States of America
| | - J Michael Gaziano
- Massachusetts Area Veterans Epidemiology Research and Information Center (MAVERIC), VA Cooperative Studies Program, VA Boston Healthcare System, Boston, Massachusetts, United States of America.,Department of Medicine, Harvard University School of Medicine, Boston, Massachusetts, United States of America
| | - John Concato
- Clinical Epidemiology Research Center (CERC), Veterans Affairs (VA) Cooperative Studies Program, VA Connecticut Healthcare System, West Haven, Connecticut, United States of America.,Department of Medicine, Yale University School of Medicine, New Haven, Connecticut, United States of America
| | - Hongyu Zhao
- Clinical Epidemiology Research Center (CERC), Veterans Affairs (VA) Cooperative Studies Program, VA Connecticut Healthcare System, West Haven, Connecticut, United States of America.,Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America
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Seow LSE, Ong C, Mahesh MV, Sagayadevan V, Shafie S, Chong SA, Subramaniam M. A systematic review on comorbid post-traumatic stress disorder in schizophrenia. Schizophr Res 2016; 176:441-451. [PMID: 27230289 DOI: 10.1016/j.schres.2016.05.004] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2015] [Revised: 05/05/2016] [Accepted: 05/05/2016] [Indexed: 12/21/2022]
Abstract
Post-traumatic stress disorder (PTSD) appears to commonly co-occur with schizophrenia, which is widely considered the most disabling mental illness. Both conditions share neurological risk factors, and present with symptoms that are superficially similar, complicating diagnostic accuracy. The presence of comorbid PTSD is also of concern as additional diagnoses tend to worsen functioning and quality of life. In the current review, EMBASE, Medline, and PsycINFO were searched for articles pertaining to PTSD comorbidity in schizophrenia spectrum disorders. Articles went through two stages of review prior to inclusion - one at the abstract level and another at the full-text level. Thirty-four articles were ultimately included in the present review. Prevalence of PTSD in schizophrenia ranged from 0 to 57%, likely due to study heterogeneity. Findings generally indicated that comorbid PTSD was associated with higher levels of positive symptoms, general psychopathology, and neurocognitive impairment, as well as worse functioning and quality of life. As such, it is important for clinicians to differentiate between psychotic and PTSD symptoms, and to pay attention to the associated features of comorbid PTSD in order to provide the most appropriate intervention. Unfortunately, epidemiological and longitudinal studies in this area are lacking.
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Affiliation(s)
| | - Clarissa Ong
- Research Division, Institute of Mental Health, Singapore
| | | | | | - Saleha Shafie
- Research Division, Institute of Mental Health, Singapore
| | - Siow Ann Chong
- Research Division, Institute of Mental Health, Singapore
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Harvey PD, Aslan M, Du M, Zhao H, Siever LJ, Pulver A, Gaziano JM, Concato J. Factor structure of cognition and functional capacity in two studies of schizophrenia and bipolar disorder: Implications for genomic studies. Neuropsychology 2016; 30:28-39. [PMID: 26710094 DOI: 10.1037/neu0000245] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
OBJECTIVE Impairments in cognition and everyday functioning are common in schizophrenia and bipolar disorder (BPD). In this article, we present factor analyses of cognitive and functional capacity (FC) measures based on 2 studies of schizophrenia (SCZ) and bipolar I disorder (BPI) using similar methods. The overall goal of these analyses was to determine whether performance-based assessments should be examined individually, or aggregated on the basis of the correlational structure of the tests, as well as to evaluate the similarity of factor structures of SCZ and BPI. METHOD Veterans Affairs Cooperative Studies Program Study #572 (Harvey et al., 2014) evaluated cognitive and FC measures among 5,414 BPI and 3,942 SCZ patients. A 2nd study evaluated similar neuropsychological (NP) and FC measures among 368 BPI and 436 SCZ patients. Principal components analysis, as well as exploratory and CFAs, were used to examine the data. RESULTS Analyses in both datasets suggested that NP and FC measures were explained by a single underlying factor in BPI and SCZ patients, both when analyzed separately or as in a combined sample. The factor structure in both studies was similar, with or without inclusion of FC measures; homogeneous loadings were observed for that single factor across cognitive and FC domains across the samples. CONCLUSION The empirically derived factor model suggests that NP performance and FC are best explained as a single latent trait applicable to people with SCZ and BPD. This single measure may enhance the robustness of the analyses relating genomic data to performance-based phenotypes.
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Affiliation(s)
- Philip D Harvey
- Department of Research Service, Bruce W. Carter Miami Veterans Affairs Medical Center
| | - Mihaela Aslan
- Clinical Epidemiology Research Center, Veterans Affairs Connecticut Healthcare System
| | - Mengtian Du
- Department of Statistics, Yale Graduate School of Arts and Sciences, Yale University
| | - Hongyu Zhao
- Clinical Epidemiology Research Center, Veterans Affairs Connecticut Healthcare System
| | - Larry J Siever
- Department of Psychiatry Service, James J. Peters Veterans Affairs Medical Center
| | - Ann Pulver
- Department of Epidemiology, Bloomberg School of Public Health
| | - J Michael Gaziano
- Massachusetts Veteran Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System
| | - John Concato
- Clinical Epidemiology Research Center, Veterans Affairs Connecticut Healthcare System
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Van Rheenen TE, Bryce S, Tan EJ, Neill E, Gurvich C, Louise S, Rossell SL. Does cognitive performance map to categorical diagnoses of schizophrenia, schizoaffective disorder and bipolar disorder? A discriminant functions analysis. J Affect Disord 2016; 192:109-15. [PMID: 26720009 DOI: 10.1016/j.jad.2015.12.022] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2015] [Revised: 12/13/2015] [Accepted: 12/14/2015] [Indexed: 01/25/2023]
Abstract
OBJECTIVES Despite known overlaps in the pattern of cognitive impairments in individuals with bipolar disorder (BD), schizophrenia (SZ) and schizoaffective disorder (SZA), few studies have examined the extent to which cognitive performance validates traditional diagnostic boundaries in these groups. METHOD Individuals with SZ (n=49), schizoaffective disorder (n=33) and BD (n=35) completed a battery of cognitive tests measuring the domains of processing speed, immediate memory, semantic memory, learning, working memory, executive function and sustained attention. RESULTS A discriminant functions analysis revealed a significant function comprising semantic memory, immediate memory and processing speed that maximally separated patients with SZ from those with BD. Initial classification scores on the basis of this function showed modest diagnostic accuracy, owing in part to the misclassification of SZA patients as having SZ. When SZA patients were removed from the model, a second cross-validated classifier yielded slightly improved diagnostic accuracy and a single function solution, of which semantic memory loaded most heavily. CONCLUSIONS A cluster of non-executive cognitive processes appears to have some validity in mapping onto traditional nosological boundaries. However, since semantic memory performance was the primary driver of the discrimination between BD and SZ, it is possible that performance differences between the disorders in this cognitive domain in particular, index separate underlying aetiologies.
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Affiliation(s)
- Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Melbourne, Australia; Brain and Psychological Sciences Research Centre (BPsyC), Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia; Cognitive Neuropsychiatry Laboratory, Monash Alfred Psychiatry Research Centre (MAPrc), The Alfred Hospital and Central Clinical School, Monash University, Melbourne, Australia.
| | - Shayden Bryce
- Brain and Psychological Sciences Research Centre (BPsyC), Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia; School of Psychological Sciences, Monash University, Melbourne, Australia
| | - Eric J Tan
- Brain and Psychological Sciences Research Centre (BPsyC), Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia; Cognitive Neuropsychiatry Laboratory, Monash Alfred Psychiatry Research Centre (MAPrc), The Alfred Hospital and Central Clinical School, Monash University, Melbourne, Australia
| | - Erica Neill
- Brain and Psychological Sciences Research Centre (BPsyC), Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia; Cognitive Neuropsychiatry Laboratory, Monash Alfred Psychiatry Research Centre (MAPrc), The Alfred Hospital and Central Clinical School, Monash University, Melbourne, Australia
| | - Caroline Gurvich
- Cognitive Neuropsychiatry Laboratory, Monash Alfred Psychiatry Research Centre (MAPrc), The Alfred Hospital and Central Clinical School, Monash University, Melbourne, Australia
| | - Stephanie Louise
- Brain and Psychological Sciences Research Centre (BPsyC), Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia; Cognitive Neuropsychiatry Laboratory, Monash Alfred Psychiatry Research Centre (MAPrc), The Alfred Hospital and Central Clinical School, Monash University, Melbourne, Australia
| | - Susan L Rossell
- Brain and Psychological Sciences Research Centre (BPsyC), Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia; Cognitive Neuropsychiatry Laboratory, Monash Alfred Psychiatry Research Centre (MAPrc), The Alfred Hospital and Central Clinical School, Monash University, Melbourne, Australia; Department of Psychiatry, St Vincent's Hospital, Melbourne, Australia
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Gaziano JM, Concato J, Brophy M, Fiore L, Pyarajan S, Breeling J, Whitbourne S, Deen J, Shannon C, Humphries D, Guarino P, Aslan M, Anderson D, LaFleur R, Hammond T, Schaa K, Moser J, Huang G, Muralidhar S, Przygodzki R, O'Leary TJ. Million Veteran Program: A mega-biobank to study genetic influences on health and disease. J Clin Epidemiol 2015; 70:214-23. [PMID: 26441289 DOI: 10.1016/j.jclinepi.2015.09.016] [Citation(s) in RCA: 618] [Impact Index Per Article: 68.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2015] [Revised: 08/04/2015] [Accepted: 09/22/2015] [Indexed: 12/13/2022]
Abstract
OBJECTIVE To describe the design and ongoing conduct of the Million Veteran Program (MVP), as an observational cohort study and mega-biobank in the Department of Veterans Affairs (VA) health care system. STUDY DESIGN AND SETTING Data are being collected from participants using questionnaires, the VA electronic health record, and a blood sample for genomic and other testing. Several ongoing projects are linked to MVP, both as peer-reviewed research studies and as activities to help develop an infrastructure for future, broad-based research uses. RESULTS Formal planning for MVP commenced in 2009; the protocol was approved in 2010, and enrollment began in 2011. As of August 3, 2015, and with a steady state of ≈50 recruiting sites nationwide, N = 397,104 veterans have been enrolled. Among N = 199,348 with currently available genotyping data, most participants (as expected) are male (92.0%) between the ages of 50 and 69 years (55.0%). On the basis of self-reported race, white (77.2%) and African American (13.5%) populations are well represented. CONCLUSIONS By helping to promote the future integration of genetic testing in health care delivery, including clinical decision making, the MVP is designed to contribute to the development of precision medicine.
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Affiliation(s)
- John Michael Gaziano
- Massachusetts Area Veterans Epidemiology Research and Information Center (MAVERIC), VA Cooperative Studies Program, VA Boston Healthcare System, 150 S. Huntington Avenue, Boston, MA 02130, USA; Department of Internal Medicine, Harvard Medical School, Boston, MA, USA
| | - John Concato
- Clinical Epidemiology Research Center (CERC), VA Cooperative Studies Program, VA Connecticut Healthcare System, 950 Campbell Avenue, 151B, West Haven, CT 06516, USA; Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA.
| | - Mary Brophy
- Massachusetts Area Veterans Epidemiology Research and Information Center (MAVERIC), VA Cooperative Studies Program, VA Boston Healthcare System, 150 S. Huntington Avenue, Boston, MA 02130, USA; Department of Internal Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Louis Fiore
- Massachusetts Area Veterans Epidemiology Research and Information Center (MAVERIC), VA Cooperative Studies Program, VA Boston Healthcare System, 150 S. Huntington Avenue, Boston, MA 02130, USA; Department of Internal Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Saiju Pyarajan
- Massachusetts Area Veterans Epidemiology Research and Information Center (MAVERIC), VA Cooperative Studies Program, VA Boston Healthcare System, 150 S. Huntington Avenue, Boston, MA 02130, USA
| | - James Breeling
- Massachusetts Area Veterans Epidemiology Research and Information Center (MAVERIC), VA Cooperative Studies Program, VA Boston Healthcare System, 150 S. Huntington Avenue, Boston, MA 02130, USA
| | - Stacey Whitbourne
- Massachusetts Area Veterans Epidemiology Research and Information Center (MAVERIC), VA Cooperative Studies Program, VA Boston Healthcare System, 150 S. Huntington Avenue, Boston, MA 02130, USA
| | - Jennifer Deen
- Massachusetts Area Veterans Epidemiology Research and Information Center (MAVERIC), VA Cooperative Studies Program, VA Boston Healthcare System, 150 S. Huntington Avenue, Boston, MA 02130, USA
| | - Colleen Shannon
- Massachusetts Area Veterans Epidemiology Research and Information Center (MAVERIC), VA Cooperative Studies Program, VA Boston Healthcare System, 150 S. Huntington Avenue, Boston, MA 02130, USA
| | - Donald Humphries
- Massachusetts Area Veterans Epidemiology Research and Information Center (MAVERIC), VA Cooperative Studies Program, VA Boston Healthcare System, 150 S. Huntington Avenue, Boston, MA 02130, USA
| | - Peter Guarino
- Clinical Epidemiology Research Center (CERC), VA Cooperative Studies Program, VA Connecticut Healthcare System, 950 Campbell Avenue, 151B, West Haven, CT 06516, USA; Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Mihaela Aslan
- Clinical Epidemiology Research Center (CERC), VA Cooperative Studies Program, VA Connecticut Healthcare System, 950 Campbell Avenue, 151B, West Haven, CT 06516, USA; Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Daniel Anderson
- Clinical Epidemiology Research Center (CERC), VA Cooperative Studies Program, VA Connecticut Healthcare System, 950 Campbell Avenue, 151B, West Haven, CT 06516, USA
| | - Rene LaFleur
- Clinical Epidemiology Research Center (CERC), VA Cooperative Studies Program, VA Connecticut Healthcare System, 950 Campbell Avenue, 151B, West Haven, CT 06516, USA
| | - Timothy Hammond
- Office of Research and Development, Veterans Health Administration, 810 Vermont Avenue N.W., 10P9, Washington, DC 20420, USA
| | - Kendra Schaa
- Office of Research and Development, Veterans Health Administration, 810 Vermont Avenue N.W., 10P9, Washington, DC 20420, USA
| | - Jennifer Moser
- Office of Research and Development, Veterans Health Administration, 810 Vermont Avenue N.W., 10P9, Washington, DC 20420, USA
| | - Grant Huang
- Office of Research and Development, Veterans Health Administration, 810 Vermont Avenue N.W., 10P9, Washington, DC 20420, USA
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, 810 Vermont Avenue N.W., 10P9, Washington, DC 20420, USA
| | - Ronald Przygodzki
- Office of Research and Development, Veterans Health Administration, 810 Vermont Avenue N.W., 10P9, Washington, DC 20420, USA
| | - Timothy J O'Leary
- Office of Research and Development, Veterans Health Administration, 810 Vermont Avenue N.W., 10P9, Washington, DC 20420, USA
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Sabbag S, Prestia D, Robertson B, Ruiz P, Durand D, Strassnig M, Harvey PD. Absence of bias in clinician ratings of everyday functioning among African American, Hispanic and Caucasian patients with schizophrenia. Psychiatry Res 2015; 229:347-52. [PMID: 26160197 PMCID: PMC4546870 DOI: 10.1016/j.psychres.2015.06.042] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2015] [Revised: 05/20/2015] [Accepted: 06/30/2015] [Indexed: 11/30/2022]
Abstract
A substantial research literature implicates potential racial/ethnic bias in the diagnosis of schizophrenia and in clinical ratings of psychosis. There is no similar information regarding bias effects on ratings of everyday functioning. Our aims were to determine if Caucasian raters vary in their ratings of the everyday functioning of schizophrenia patients of different ethnicities, to find out which factors determine accurate self-report of everyday functioning in different ethnic groups, and to know if depression has similar effects on the way people of different ethnicities self-report their current functionality. We analyzed data on 295 patients with schizophrenia who provided their self-report of their everyday functioning and also had a Caucasian clinician rating their functionality. Three racial/ethnic groups (African American (AA), Hispanic and Caucasian) were studied and analyzed on the basis of neurocognition, functional capacity, depression and real-world functional outcomes. No differences based on racial/ethnic status in clinician assessments of patients' functionality were found. Differences between racial groups were found in personal and maternal levels of education. Severity of depression was significantly correlated with accuracy of self-assessment of functioning in Caucasians, but not in AAs. Higher scores on neurocognition and functional capacity scales correlated with reduced overestimation of functioning in AAs, but not in Hispanics. This data might indicate that measurement of everyday functionality is less subject to rater bias than measurement of symptoms of schizophrenia.
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Affiliation(s)
- Samir Sabbag
- Deparcmenr of Psydtiarry and Behavioral Sciences, Universiry of Miami Miller School of Medicine, Miami, FL, USA
| | - Davide Prestia
- Deparcmenr of Psydtiarry and Behavioral Sciences, Universiry of Miami Miller School of Medicine, Miami, FL, USA
| | - Belinda Robertson
- Deparcmenr of Psydtiarry and Behavioral Sciences, Universiry of Miami Miller School of Medicine, Miami, FL, USA
| | - Pedro Ruiz
- Deparcmenr of Psydtiarry and Behavioral Sciences, Universiry of Miami Miller School of Medicine, Miami, FL, USA
| | - Dante Durand
- Deparcmenr of Psydtiarry and Behavioral Sciences, Universiry of Miami Miller School of Medicine, Miami, FL, USA
| | - Martin Strassnig
- Deparcmenr of Psydtiarry and Behavioral Sciences, Universiry of Miami Miller School of Medicine, Miami, FL, USA
| | - Philip D. Harvey
- Deparcmenr of Psydtiarry and Behavioral Sciences, Universiry of Miami Miller School of Medicine, Miami, FL, USA, Research Service, Bruce W Career VAMedical Cenrer, Miami, FL, USA, Corresponding author at: University of Miami Miller School of Medicine. Department of Psychiatiy and Behavioral Sciences. 1120 NW 14th Street. Suite 1450, Miami. FL 33136, USA. fax: +1 305 243 1619. (P.D. Harvey)
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Gould F, Kaplan S, Harvey PD. Latest Developments in Cognitive Functioning in Mood and Anxiety Disorders. Curr Behav Neurosci Rep 2015. [DOI: 10.1007/s40473-015-0045-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Harvey PD, Paschall G, Depp C. Factors influencing self-assessment of cognition and functioning in bipolar disorder: a preliminary study. Cogn Neuropsychiatry 2015; 20:361-71. [PMID: 26057868 PMCID: PMC4477193 DOI: 10.1080/13546805.2015.1044510] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
INTRODUCTION Self-assessment deficits are common in schizophrenia and span multiple aspects of functioning, including awareness of symptoms, and the ability to assess objective levels of cognitive deficits and everyday functioning. Whereas impaired awareness of illness in bipolar disorder during symptomatic periods is well understood, awareness of disability and cognitive deficits has been less well studied. METHODS In this pilot study, 30 patients with a lifetime history of bipolar I disorder and current bipolar depression completed performance-based tests of cognition and functional capacity and self-reported their opinions of their cognitive abilities, everyday functioning and symptoms. High contact clinicians also provided impressions of the patients' cognitive performance and everyday functioning. RESULTS Clinician impressions of cognition and everyday functioning were correlated with the results of the performance-based assessments, whereas the patient self-reports of cognition and functioning were uncorrelated both with their own performance and with the clinician impressions. However, severity of depressive symptoms was correlated with self-reports of functioning in cognitive and functional domains, but not with either performance-based data or clinician impressions of cognition or functioning. CONCLUSIONS Depression appears to be a factor affecting self-assessment in bipolar disorder and reports of cognition and functioning were minimally related to objective information and clinician impressions. Symptoms of mania were minimal and not correlated with performance-based assessments or clinician impressions.
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Affiliation(s)
- Philip D. Harvey
- University of Miami Miller School of Medicine, Research Service, Bruce W. Carter VA Medical Center, Miami, FL
| | - Gayla Paschall
- Research Service, Little Rock, Arkansas, VA Medical Center, Department of Psychiatry, University of Arkansas Medical Center
| | - Colin Depp
- UCSD Medical Center, San Diego VA Medical Center
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Utility of the UCSD Performance-based Skills Assessment-Brief Japanese version: discriminative ability and relation to neurocognition. SCHIZOPHRENIA RESEARCH-COGNITION 2014; 1:137-143. [PMID: 29379746 PMCID: PMC5779073 DOI: 10.1016/j.scog.2014.08.002] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2014] [Revised: 08/24/2014] [Accepted: 08/29/2014] [Indexed: 11/29/2022]
Abstract
The UCSD Performance-based Skills Assessment Brief (the UPSA-B) has been widely used for evaluating functional capacity in patients with schizophrenia. The utility of the battery in a wide range of cultural contexts has been of concern among developers. The current study investigated the validity of the Japanese version of the UPSA-B as a measure of functional capacity and as a co-primary for neurocognion. Sixty-four Japanese patients with schizophrenia and 83 healthy adults entered the study. The Japanese version of the UPSA-B (UPSA-B Japanese version) and the MATRICS Cognitive Consensus Battery Japanese version (MCCB Japanese version) were administered. Normal controls performed significantly better than patients, with large effect sizes for the Total and the subscale scores of the UPSA-B. Receiver Operating Characteristic (ROC) curve analysis revealed that the optimal cut-off point for the UPSA-B Total score was estimated at around 80. The UPSA-B Total score was significantly correlated with the MCCB Composite score and several domain scores, indicating the relationship between this co-primary measure and overall cognitive functioning in Japanese patients with schizophrenia. The results obtained here suggest that the UPSA-B Japanese version is an effective tool for evaluating disturbances of daily-living skills linked to cognitive functioning in schizophrenia, providing an identifiable cut-off point and relationships to neurocognition. Further research is warranted to evaluate the psychometrical properties and response to treatment of the Japanese version of the UPSA-B.
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Best MW, Gupta M, Bowie CR, Harvey PD. A Longitudinal Examination of the Moderating Effects of Symptoms on the Relationship between Functional Competence and Real World Functional Performance in Schizophrenia. SCHIZOPHRENIA RESEARCH-COGNITION 2014; 1:90-95. [PMID: 25267939 DOI: 10.1016/j.scog.2014.03.002] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
BACKGROUND Many individuals with schizophrenia experience remission of prominent positive symptoms but continue to experience impairments in real world functioning. Residual negative and depressive symptoms may have a direct impact on functioning and impair patients' ability to use the cognitive and functional skills that they possess (competence) in the real world (functional performance). METHODS 136 individuals (100 men, 36 women) with schizophrenia were classified as having primarily positive symptoms, primarily negative symptoms, primarily depressive symptoms, or undifferentiated symptom profiles. Performance based measures of cognition and adaptive and interpersonal functional competence were used, along with ratings of real world behavior by high contact clinicians. Assessments were performed at baseline and at an 18-month follow-up. RESULTS The relationships between neurocognition and capacity / performance were not moderated by symptom group ps > .091; neurocognition predicted capacity and performance for all groups ps < .001. The relationship between adaptive competence and adaptive performance was moderated by symptom group, ps < .01, such that baseline competence only predicted future performance ratings for participants with primarily positive or undifferentiated symptoms, and not for individuals with primarily negative or depressive symptoms. This same moderation effect was found on the relationship between interpersonal competence and interpersonal performance, ps < .002. CONCLUSIONS Residual negative and depressive symptoms are distinct constructs that impede the use of functional skills in the real world. Depressive symptoms are often overlooked in schizophrenia but appear to be an important factor that limits the use of functional ability in real world environments.
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Affiliation(s)
- Michael W Best
- Department of Psychology, Queen's University, Ontario, Canada
| | - Maya Gupta
- Department of Psychology, Queen's University, Ontario, Canada
| | | | - Philip D Harvey
- Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami, USA ; Research Service Bruce Carter VA Medical Center, Miami, FL
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