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Abplanalp SJ, Braff DL, Light GA, Joshi YB, Nuechterlein KH, Green MF. Clarifying directional dependence among measures of early auditory processing and cognition in schizophrenia: leveraging Gaussian graphical models and Bayesian networks. Psychol Med 2024:1-10. [PMID: 38287656 DOI: 10.1017/s0033291724000023] [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] [Indexed: 01/31/2024]
Abstract
BACKGROUND Research using latent variable models demonstrates that pre-attentive measures of early auditory processing (EAP) and cognition may initiate a cascading effect on daily functioning in schizophrenia. However, such models fail to account for relationships among individual measures of cognition and EAP, thereby limiting their utility. Hence, EAP and cognition may function as complementary and interacting measures of brain function rather than independent stages of information processing. Here, we apply a data-driven approach to identifying directional relationships among neurophysiologic and cognitive variables. METHODS Using data from the Consortium on the Genetics of Schizophrenia 2, we estimated Gaussian Graphical Models and Bayesian networks to examine undirected and directed connections between measures of EAP, including mismatch negativity and P3a, and cognition in 663 outpatients with schizophrenia and 630 control participants. RESULTS Chain structures emerged among EAP and attention/vigilance measures in schizophrenia and control groups. Concerning differences between the groups, object memory was an influential variable in schizophrenia upon which other cognitive domains depended, and working memory was an influential variable in controls. CONCLUSIONS Measures of EAP and attention/vigilance are conditionally independent of other cognitive domains that were used in this study. Findings also revealed additional causal assumptions among measures of cognition that could help guide statistical control and ultimately help identify early-stage targets or surrogate endpoints in schizophrenia.
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Affiliation(s)
- Samuel J Abplanalp
- Desert Pacific Mental Illness Research, Education and Clinical Center, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - David L Braff
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Gregory A Light
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Yash B Joshi
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Keith H Nuechterlein
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - Michael F Green
- Desert Pacific Mental Illness Research, Education and Clinical Center, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
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2
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Caponnetto P, Maglia M, Mangione M, Vergopia C, Prezzavento GC, Polosa R, Quattropani MC, DiPiazza J, Signorelli MS. Smoking Addiction in Patients with Schizophrenia Spectrum Disorders and Its Perception and Intervention in Healthcare Personnel Assigned to Psycho-Rehabilitation Programs: A Qualitative Research. Healthcare (Basel) 2022; 10:2275. [PMID: 36421599 PMCID: PMC9690727 DOI: 10.3390/healthcare10112275] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 11/05/2022] [Accepted: 11/07/2022] [Indexed: 08/30/2023] Open
Abstract
Patients with schizophrenia spectrum disorders have a higher prevalence and frequency of smoking rates when compared to the rest of the population; to this, it must be added that they develop a greater dependence and have some worse health consequences than the general population. This is qualitative research on the perception of smoking in healthcare professionals assigned to psycho-rehabilitation programs for patients with schizophrenia spectrum disorders. The point of view of health personnel (Psychologists, Psychiatrists, Pedagogists, and Nurses) about cigarette smoking in these patients was analyzed, focusing on their implications in disturbance and comparing them with e-cigarettes too. The methodology used to collect the data was a semi-structured interview with five questions. The research path was carried out in two assisted therapeutic communities that are clinics for the rehabilitation of serious mental illness in the period between November and July 2022. The results showed that the opinion of health professionals on smoking is very negative. Research has also shown that nearly all patients are smokers; however, their high grade of addiction is caused by periods of high stress due to various factors that lead patients to consume a greater number of cigarettes. Almost all respondents have a positive opinion of the e-cigarette, which was defined as an excellent substitute for traditional cigarettes.
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Affiliation(s)
- Pasquale Caponnetto
- Department of Educational Sciences, Section of Psychology, University of Catania, 95121 Catania, Italy
- Center of Excellence for the Acceleration of Harm Reduction (COEHAR), University of Catania, 95121 Catania, Italy
| | - Marilena Maglia
- Department of Educational Sciences, Section of Psychology, University of Catania, 95121 Catania, Italy
- CTA-Villa Chiara Psychiatric Rehabilitation Clinic and Research, 95030 Mascalucia, Italy
| | - Marta Mangione
- ECLAT Srl, Spin-Off of the University of Catania, 95121 Catania, Italy
| | - Chiara Vergopia
- Department of Educational Sciences, Section of Psychology, University of Catania, 95121 Catania, Italy
| | | | - Riccardo Polosa
- Center of Excellence for the Acceleration of Harm Reduction (COEHAR), University of Catania, 95121 Catania, Italy
- Department of Clinical and Experimental Medicine, University of Catania, 95121 Catania, Italy
| | - Maria Catena Quattropani
- Department of Educational Sciences, Section of Psychology, University of Catania, 95121 Catania, Italy
| | - Jennifer DiPiazza
- Hunter Bellevue School of Nursing, Hunter College, City University of New York, New York, NY 10065, USA
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3
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Underwood R, Mason L, O'Daly O, Dalton J, Simmons A, Barker GJ, Peters E, Kumari V. You read my mind: fMRI markers of threatening appraisals in people with persistent psychotic experiences. NPJ SCHIZOPHRENIA 2021; 7:49. [PMID: 34635671 PMCID: PMC8505497 DOI: 10.1038/s41537-021-00173-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Accepted: 08/06/2021] [Indexed: 11/09/2022]
Abstract
Anomalous perceptual experiences are relatively common in the general population. Evidence indicates that the key to distinguishing individuals with persistent psychotic experiences (PEs) with a need for care from those without is how they appraise their anomalous experiences. Here, we aimed to characterise the neural circuits underlying threatening and non-threatening appraisals in people with and without a need for care for PEs, respectively. A total of 48 participants, consisting of patients with psychosis spectrum disorder (clinical group, n = 16), non-need-for-care participants with PEs (non-clinical group, n = 16), and no-PE healthy control participants (n = 16), underwent functional magnetic resonance imaging while completing the Telepath task, designed to induce an anomalous perceptual experience. Appraisals of the anomalous perceptual experiences were examined, as well as functional brain responses during this window, for significant group differences. We also examined whether activation co-varied with the subjective threat appraisals reported in-task by participants. The clinical group reported elevated subjective threat appraisals compared to both the non-clinical and no-PE control groups, with no differences between the two non-clinical groups. This pattern of results was accompanied by reduced activation in the superior and inferior frontal gyri in the clinical group as compared to the non-clinical and control groups. Precuneus activation scaled with threat appraisals reported in-task. Resilience in the context of persistent anomalous experiences may be explained by intact functioning of fronto-parietal regions, and may correspond to the ability to contextualise and flexibly evaluate psychotic experiences.
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Affiliation(s)
- Raphael Underwood
- King's College London, Institute of Psychiatry, Psychology & Neuroscience, Department of Psychology, London, UK. .,South London and Maudsley NHS Foundation Trust, Bethlem Royal Hospital, Kent, UK.
| | - Liam Mason
- University College London, Max Planck Centre for Computational Psychiatry and Ageing Research, London, UK.,University College London, Research Department of Clinical, Educational and Health Psychology, London, UK
| | - Owen O'Daly
- King's College London, Institute of Psychiatry, Psychology & Neuroscience, Department of Neuroimaging, London, UK
| | - Jeffrey Dalton
- King's College London, Institute of Psychiatry, Psychology & Neuroscience, Department of Neuroimaging, London, UK
| | - Andrew Simmons
- King's College London, Institute of Psychiatry, Psychology & Neuroscience, Department of Neuroimaging, London, UK
| | - Gareth J Barker
- King's College London, Institute of Psychiatry, Psychology & Neuroscience, Department of Neuroimaging, London, UK
| | - Emmanuelle Peters
- King's College London, Institute of Psychiatry, Psychology & Neuroscience, Department of Psychology, London, UK.,South London and Maudsley NHS Foundation Trust, Bethlem Royal Hospital, Kent, UK
| | - Veena Kumari
- King's College London, Institute of Psychiatry, Psychology & Neuroscience, Department of Psychology, London, UK.,Brunel University London, College of Health, Medicine and Life Sciences, Centre for Cognitive Neuroscience, Uxbridge, UK
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4
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Effectiveness of multimodal interventions focused on smoking cessation in patients with schizophrenia: A systematic review. Schizophr Res 2021; 231:145-153. [PMID: 33857662 DOI: 10.1016/j.schres.2021.03.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Accepted: 03/27/2021] [Indexed: 10/21/2022]
Abstract
BACKGROUND Smoking is a significant risk factor for mortality and morbidity among patients with schizophrenia. OBJECTIVE To clarify the effectiveness of multimodal smoking cessation interventions in adult smokers diagnosed with schizophrenia. METHODS A systematic review was conducted according to PRISMA guidelines. Relevant electronic databases were searched for clinical trials that combined pharmacological and non-pharmacological smoking cessation interventions for patients with schizophrenia, published up to October 2020. Primary outcomes were smoking abstinence and smoking reduction. Secondary outcomes consisted in psychiatric symptoms. RESULTS A final sample of nine articles was obtained from a total of 208 studies. All studies reported higher biochemically validated smoking reduction rates after treatment. However, the majority of the studies reported low smoking abstinence rates, which progressively decreased over time. Multimodal interventions did not worsen psychiatric symptoms. CONCLUSION Evidence suggests that multimodal smoking cessation interventions for individuals diagnosed with schizophrenia should be recommended by clinicians, as they showed to be effective in reducing smoking without worsening psychiatric symptoms. Further studies are needed to understand how interventions can become more effective in helping patients achieve long-term smoking abstinence.
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5
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Ferreira A, Coentre R. A systematic review of tobacco use in first-episode psychosis. EUROPEAN JOURNAL OF PSYCHIATRY 2020. [DOI: 10.1016/j.ejpsy.2020.03.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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6
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Caponnetto P, Polosa R, Robson D, Bauld L. Tobacco smoking, related harm and motivation to quit smoking in people with schizophrenia spectrum disorders. Health Psychol Res 2020; 8:9042. [PMID: 32510003 PMCID: PMC7267811 DOI: 10.4081/hpr.2020.9042] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Accepted: 05/20/2020] [Indexed: 02/06/2023] Open
Abstract
This narrative review focuses on the topic of tobacco smoking amongst people with schizophrenia spectrum disorders. We searched PubMed, PsycInfo and Scopus databases for schizophrenia spectrum disorders and smoking and included articles about the epidemiology of tobacco smoking in people with schizophrenia spectrum disorders, examining the relationship between smoking and mental health. This narrative review describes that a higher prevalence, frequency and impact of both high nicotine dependence and its harmful effects in patients with schizophrenia spectrum disorders compared with those in the general population. Despite several existent theories, the reasons for high smoking rates, the high dependence on nicotine and severity of nicotine withdrawal symptoms are not fully understood. The main aim of this paper is to inform mental health personnel and particularly clinical and health psychologists about the impact and role of tobacco smoking for smokers with schizophrenia spectrum disorders.
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Affiliation(s)
| | | | | | - Linda Bauld
- Usher Institute, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK
- UK Centre for Tobacco & Alcohol Studies, Nottingham, UK
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7
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The effects of age and sex on cognitive impairment in schizophrenia: Findings from the Consortium on the Genetics of Schizophrenia (COGS) study. PLoS One 2020; 15:e0232855. [PMID: 32401791 PMCID: PMC7219730 DOI: 10.1371/journal.pone.0232855] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Accepted: 04/22/2020] [Indexed: 01/05/2023] Open
Abstract
Recently emerging evidence indicates accelerated age-related changes in the structure and function of the brain in schizophrenia, raising a question about its potential consequences on cognitive function. Using a large sample of schizophrenia patients and controls and a battery of tasks across multiple cognitive domains, we examined whether patients show accelerated age-related decline in cognition and whether an age-related effect differ between females and males. We utilized data of 1,415 schizophrenia patients and 1,062 healthy community collected by the second phase of the Consortium on the Genetics of Schizophrenia (COGS-2). A battery of cognitive tasks included the Letter-Number Span Task, two forms of the Continuous Performance Test, the California Verbal Learning Test, Second Edition, the Penn Emotion Identification Test and the Penn Facial Memory Test. The effect of age and gender on cognitive performance was examined with a general linear model. We observed age-related changes on most cognitive measures, which was similar between males and females. Compared to controls, patients showed greater deterioration in performance on attention/vigilance and greater slowness of processing social information with increasing age. However, controls showed greater age-related changes in working memory and verbal memory compared to patients. Age-related changes (η2p of 0.001 to .008) were much smaller than between-group differences (η2p of 0.005 to .037). This study found that patients showed continued decline of cognition on some domains but stable impairment or even less decline on other domains with increasing age. These findings indicate that age-related changes in cognition in schizophrenia are subtle and not uniform across multiple cognitive domains.
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8
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Greenwood TA, Lazzeroni LC, Maihofer AX, Swerdlow NR, Calkins ME, Freedman R, Green MF, Light GA, Nievergelt CM, Nuechterlein KH, Radant AD, Siever LJ, Silverman JM, Stone WS, Sugar CA, Tsuang DW, Tsuang MT, Turetsky BI, Gur RC, Gur RE, Braff DL. Genome-wide Association of Endophenotypes for Schizophrenia From the Consortium on the Genetics of Schizophrenia (COGS) Study. JAMA Psychiatry 2019; 76:1274-1284. [PMID: 31596458 PMCID: PMC6802253 DOI: 10.1001/jamapsychiatry.2019.2850] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
IMPORTANCE The Consortium on the Genetics of Schizophrenia (COGS) uses quantitative neurophysiological and neurocognitive endophenotypes with demonstrated deficits in schizophrenia as a platform from which to explore the underlying neural circuitry and genetic architecture. Many of these endophenotypes are associated with poor functional outcome in schizophrenia. Some are also endorsed as potential treatment targets by the US Food and Drug Administration. OBJECTIVE To build on prior assessments of heritability, association, and linkage in the COGS phase 1 (COGS-1) families by reporting a genome-wide association study (GWAS) of 11 schizophrenia-related endophenotypes in the independent phase 2 (COGS-2) cohort of patients with schizophrenia and healthy comparison participants (HCPs). DESIGN, SETTING, AND PARTICIPANTS A total of 1789 patients with schizophrenia and HCPs of self-reported European or Latino ancestry were recruited through a collaborative effort across the COGS sites and genotyped using the PsychChip. Standard quality control filters were applied, and more than 6.2 million variants with a genotyping call rate of greater than 0.99 were available after imputation. Association was performed for data sets stratified by diagnosis and ancestry using linear regression and adjusting for age, sex, and 5 principal components, with results combined through weighted meta-analysis. Data for COGS-1 were collected from January 6, 2003, to August 6, 2008; data for COGS-2, from June 30, 2010, to February 14, 2014. Data were analyzed from October 28, 2016, to May 4, 2018. MAIN OUTCOMES AND MEASURES A genome-wide association study was performed to evaluate association for 11 neurophysiological and neurocognitive endophenotypes targeting key domains of schizophrenia related to inhibition, attention, vigilance, learning, working memory, executive function, episodic memory, and social cognition. RESULTS The final sample of 1533 participants included 861 male participants (56.2%), and the mean (SD) age was 41.8 (13.6) years. In total, 7 genome-wide significant regions (P < 5 × 10-8) and 2 nearly significant regions (P < 9 × 10-8) containing several genes of interest, including NRG3 and HCN1, were identified for 7 endophenotypes. For each of the 11 endophenotypes, enrichment analyses performed at the level of P < 10-4 compared favorably with previous association results in the COGS-1 families and showed extensive overlap with regions identified for schizophrenia diagnosis. CONCLUSIONS AND RELEVANCE These analyses identified several genomic regions of interest that require further exploration and validation. These data seem to demonstrate the utility of endophenotypes for resolving the genetic architecture of schizophrenia and characterizing the underlying biological dysfunctions. Understanding the molecular basis of these endophenotypes may help to identify novel treatment targets and pave the way for precision-based medicine in schizophrenia and related psychotic disorders.
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Affiliation(s)
| | - Laura C. Lazzeroni
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California,Sierra Pacific Mental Illness Research Education and Clinical Center, Department of Veterans Affairs (VA) Health Care System, Palo Alto, California
| | - Adam X. Maihofer
- Department of Psychiatry, University of California, San Diego, La Jolla
| | - Neal R. Swerdlow
- Department of Psychiatry, University of California, San Diego, La Jolla
| | | | - Robert Freedman
- Department of Psychiatry, University of Colorado Health Sciences Center, Denver
| | - Michael F. Green
- Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles, California,Desert Pacific Mental Illness Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles, California
| | - Gregory A. Light
- Department of Psychiatry, University of California, San Diego, La Jolla,Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, California
| | | | | | - Allen D. Radant
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle,Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle, Washington
| | - Larry J. Siever
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York,Research & Development, James J. Peters VA Medical Center, New York, New York
| | - Jeremy M. Silverman
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York,Research & Development, James J. Peters VA Medical Center, New York, New York
| | - William S. Stone
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts,Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston
| | - Catherine A. Sugar
- Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles, California,Department of Biostatistics, UCLA School of Public Health
| | - Debby W. Tsuang
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle,Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle, Washington
| | - Ming T. Tsuang
- Department of Psychiatry, University of California, San Diego, La Jolla
| | | | - Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia
| | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia
| | - David L. Braff
- Department of Psychiatry, University of California, San Diego, La Jolla
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9
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Park JH, Hong JS, Kim SM, Min KJ, Chung US, Han DH. Effects of Amisulpride Adjunctive Therapy on Working Memory and Brain Metabolism in the Frontal Cortex of Patients with Schizophrenia: A Preliminary Positron Emission Tomography/Computerized Tomography Investigation. CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE 2019; 17:250-260. [PMID: 30905125 PMCID: PMC6478094 DOI: 10.9758/cpn.2019.17.2.250] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/31/2018] [Revised: 10/07/2018] [Accepted: 10/25/2018] [Indexed: 12/22/2022]
Abstract
Objective Dopamine plays a significant role in working memory by acting as a key neuromodulator between brain networks. Additionally, treatment of patients with schizophrenia using amisulpride, a pure dopamine class 2/3 receptor antagonist, improves their clinical symptoms with fewer side effects. We hypothesized that patients with schizophrenia treated with amisulpride and aripiprazole show increased working memory and glucose metabolism compared with those treated with cognitive behavioral therapy (CBT) and aripiprazole instead. Methods Sixteen patients with schizophrenia (eight in the amisulpride group [aripiprazole+amisulpride] and eight in the CBT group [aripiprazole+CBT]) and 15 age- and sex-matched healthy control subjects were recruited for a 12-week-long prospective trial. An [18F]-fluorodeoxyglucose-positron emission tomography/computerized tomography scanner was used to acquire the images. Results After 12 weeks of treatment, the amisulpride group showed greater improvement in the Letter-Number Span scores than the CBT group. Additionally, although brain metabolism in the left middle frontal gyrus, left occipital lingual gyrus, and right inferior parietal lobe was increased in all patients with schizophrenia, the amisulpride group exhibited a greater increase in metabolism in both the right superior frontal gyrus and right frontal precentral gyrus than the CBT group. Conclusion This study suggests that a small dose of amisulpride improves the general psychopathology, working memory performance, and brain glucose metabolism of patients with schizophrenia treated with aripiprazole.
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Affiliation(s)
- Jeong Ha Park
- Department of Psychiatry, Chung-Ang University Hospital
| | - Ji Son Hong
- Department of Psychiatry, Chung-Ang University Hospital
| | - Sun Mi Kim
- Department of Psychiatry, Chung-Ang University Hospital
| | | | - Un Sun Chung
- Department of Psychiatry, Kyungpook National University Children's
| | - Doug Hyun Han
- Department of Psychiatry, Chung-Ang University Hospital
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10
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Avramopoulos D. Recent Advances in the Genetics of Schizophrenia. MOLECULAR NEUROPSYCHIATRY 2018; 4:35-51. [PMID: 29998117 PMCID: PMC6032037 DOI: 10.1159/000488679] [Citation(s) in RCA: 65] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2017] [Accepted: 03/21/2018] [Indexed: 12/27/2022]
Abstract
The last decade brought tremendous progress in the field of schizophrenia genetics. As a result of extensive collaborations and multiple technological advances, we now recognize many types of genetic variants that increase the risk. These include large copy number variants, rare coding inherited and de novο variants, and over 100 loci harboring common risk variants. While the type and contribution to the risk vary among genetic variants, there is concordance in the functions of genes they implicate, such as those whose RNA binds the fragile X-related protein FMRP and members of the activity-regulated cytoskeletal complex involved in learning and memory. Gene expression studies add important information on the biology of the disease and recapitulate the same functional gene groups. Studies of alternative phenotypes help us widen our understanding of the genetic architecture of mental function and dysfunction, how diseases overlap not only with each other but also with non-disease phenotypes. The challenge is to apply this new knowledge to prevention and treatment and help patients. The data generated so far and emerging technologies, including new methods in cell engineering, offer significant promise that in the next decade we will unlock the translational potential of these significant discoveries.
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Affiliation(s)
- Dimitrios Avramopoulos
- Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland, USA
- Department of Psychiatry, Johns Hopkins University, Baltimore, Maryland, USA
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11
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Blakey R, Ranlund S, Zartaloudi E, Cahn W, Calafato S, Colizzi M, Crespo-Facorro B, Daniel C, Díez-Revuelta Á, Di Forti M, Iyegbe C, Jablensky A, Jones R, Hall MH, Kahn R, Kalaydjieva L, Kravariti E, Lin K, McDonald C, McIntosh AM, Picchioni M, Powell J, Presman A, Rujescu D, Schulze K, Shaikh M, Thygesen JH, Toulopoulou T, Van Haren N, Van Os J, Walshe M, Murray RM, Bramon E. Associations between psychosis endophenotypes across brain functional, structural, and cognitive domains. Psychol Med 2018; 48:1325-1340. [PMID: 29094675 PMCID: PMC6516747 DOI: 10.1017/s0033291717002860] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
BACKGROUND A range of endophenotypes characterise psychosis, however there has been limited work understanding if and how they are inter-related. METHODS This multi-centre study includes 8754 participants: 2212 people with a psychotic disorder, 1487 unaffected relatives of probands, and 5055 healthy controls. We investigated cognition [digit span (N = 3127), block design (N = 5491), and the Rey Auditory Verbal Learning Test (N = 3543)], electrophysiology [P300 amplitude and latency (N = 1102)], and neuroanatomy [lateral ventricular volume (N = 1721)]. We used linear regression to assess the interrelationships between endophenotypes. RESULTS The P300 amplitude and latency were not associated (regression coef. -0.06, 95% CI -0.12 to 0.01, p = 0.060), and P300 amplitude was positively associated with block design (coef. 0.19, 95% CI 0.10-0.28, p 0.38). All the cognitive endophenotypes were associated with each other in the expected directions (all p < 0.001). Lastly, the relationships between pairs of endophenotypes were consistent in all three participant groups, differing for some of the cognitive pairings only in the strengths of the relationships. CONCLUSIONS The P300 amplitude and latency are independent endophenotypes; the former indexing spatial visualisation and working memory, and the latter is hypothesised to index basic processing speed. Individuals with psychotic illnesses, their unaffected relatives, and healthy controls all show similar patterns of associations between endophenotypes, endorsing the theory of a continuum of psychosis liability across the population.
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Affiliation(s)
- R. Blakey
- Division of Psychiatry, University College London, London, UK
| | - S. Ranlund
- Division of Psychiatry, University College London, London, UK
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
| | - E. Zartaloudi
- Division of Psychiatry, University College London, London, UK
| | - W. Cahn
- Department of Psychiatry, Brain Centre Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - S. Calafato
- Division of Psychiatry, University College London, London, UK
| | - M. Colizzi
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
| | - B. Crespo-Facorro
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain
- Department of Psychiatry, University Hospital Marqués de Valdecilla, School of Medicine, University of Cantabria–IDIVAL, Santander, Spain
| | - C. Daniel
- Division of Psychiatry, University College London, London, UK
| | - Á. Díez-Revuelta
- Division of Psychiatry, University College London, London, UK
- Laboratory of Cognitive and Computational Neuroscience – Centre for Biomedical Technology (CTB), Complutense University and Technical University of Madrid, Madrid, Spain
| | - M. Di Forti
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
| | | | - C. Iyegbe
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
| | - A. Jablensky
- Centre for Clinical Research in Neuropsychiatry, The University of Western Australia, Perth, Western Australia, Australia
| | - R. Jones
- Division of Psychiatry, University College London, London, UK
| | - M.-H. Hall
- Psychology Research Laboratory, Harvard Medical School, McLean Hospital, Belmont, MA, USA
| | - R. Kahn
- Department of Psychiatry, Brain Centre Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - L. Kalaydjieva
- Harry Perkins Institute of Medical Research and Centre for Medical Research, The University of Western Australia, Perth, Australia
| | - E. Kravariti
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
| | - K. Lin
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - C. McDonald
- Department of Psychiatry, Clinical Science Institute, National University of Ireland Galway, Ireland
| | - A. M. McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, UK
| | | | - M. Picchioni
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
| | - J. Powell
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
| | - A. Presman
- Division of Psychiatry, University College London, London, UK
| | - D. Rujescu
- Department of Psychiatry, Ludwig-Maximilians University of Munich, Munich, Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Halle Wittenberg, Halle, Germany
| | - K. Schulze
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
| | - M. Shaikh
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
- North East London Foundation Trust, London, UK
| | - J. H. Thygesen
- Division of Psychiatry, University College London, London, UK
| | - T. Toulopoulou
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
- Department of Psychology, Bilkent University, Main Campus, Bilkent, Ankara, Turkey
- Department of Psychology, the University of Hong Kong, Pokfulam Rd, Hong Kong SAR, China
- The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, The Hong Kong Jockey Club Building for Interdisciplinary Research, Hong Kong SAR, China
| | - N. Van Haren
- Department of Psychiatry, Brain Centre Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - J. Van Os
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
- Department of Psychiatry and Psychology, Maastricht University Medical Centre, EURON, Maastricht, The Netherlands
| | - M. Walshe
- Division of Psychiatry, University College London, London, UK
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
| | | | - R. M. Murray
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
| | - E. Bramon
- Division of Psychiatry, University College London, London, UK
- Institute of Psychiatry Psychology and Neuroscience at King’s College London and South London and Maudsley NHS Foundation Trust, London, UK
- Institute of Cognitive Neuroscience, University College London, London, UK
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12
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Ranlund S, Calafato S, Thygesen JH, Lin K, Cahn W, Crespo‐Facorro B, de Zwarte SM, Díez Á, Di Forti M, Iyegbe C, Jablensky A, Jones R, Hall M, Kahn R, Kalaydjieva L, Kravariti E, McDonald C, McIntosh AM, McQuillin A, Picchioni M, Prata DP, Rujescu D, Schulze K, Shaikh M, Toulopoulou T, van Haren N, van Os J, Vassos E, Walshe M, Lewis C, Murray RM, Powell J, Bramon E. A polygenic risk score analysis of psychosis endophenotypes across brain functional, structural, and cognitive domains. Am J Med Genet B Neuropsychiatr Genet 2018; 177:21-34. [PMID: 28851104 PMCID: PMC5763362 DOI: 10.1002/ajmg.b.32581] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2017] [Accepted: 07/24/2017] [Indexed: 12/26/2022]
Abstract
This large multi-center study investigates the relationships between genetic risk for schizophrenia and bipolar disorder, and multi-modal endophenotypes for psychosis. The sample included 4,242 individuals; 1,087 patients with psychosis, 822 unaffected first-degree relatives of patients, and 2,333 controls. Endophenotypes included the P300 event-related potential (N = 515), lateral ventricular volume (N = 798), and the cognitive measures block design (N = 3,089), digit span (N = 1,437), and the Ray Auditory Verbal Learning Task (N = 2,406). Data were collected across 11 sites in Europe and Australia; all genotyping and genetic analyses were done at the same laboratory in the United Kingdom. We calculated polygenic risk scores for schizophrenia and bipolar disorder separately, and used linear regression to test whether polygenic scores influenced the endophenotypes. Results showed that higher polygenic scores for schizophrenia were associated with poorer performance on the block design task and explained 0.2% (p = 0.009) of the variance. Associations in the same direction were found for bipolar disorder scores, but this was not statistically significant at the 1% level (p = 0.02). The schizophrenia score explained 0.4% of variance in lateral ventricular volumes, the largest across all phenotypes examined, although this was not significant (p = 0.063). None of the remaining associations reached significance after correction for multiple testing (with alpha at 1%). These results indicate that common genetic variants associated with schizophrenia predict performance in spatial visualization, providing additional evidence that this measure is an endophenotype for the disorder with shared genetic risk variants. The use of endophenotypes such as this will help to characterize the effects of common genetic variation in psychosis.
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Affiliation(s)
- Siri Ranlund
- Division of PsychiatryUniversity College LondonLondonUK
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | | | | | - Kuang Lin
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
- Nuffield Department of Population HealthUniversity of OxfordOxfordUK
| | - Wiepke Cahn
- Department of Psychiatry, Brain Centre Rudolf MagnusUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Benedicto Crespo‐Facorro
- CIBERSAMCentro Investigación Biomédica en Red Salud MentalMadridSpain
- Department of Psychiatry, University Hospital Marqués de Valdecilla, School of MedicineUniversity of Cantabria–IDIVALSantanderSpain
| | - Sonja M.C. de Zwarte
- Department of Psychiatry, Brain Centre Rudolf MagnusUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Álvaro Díez
- Division of PsychiatryUniversity College LondonLondonUK
- Laboratory of Cognitive and Computational Neuroscience—Centre for Biomedical Technology (CTB)Complutense University and Technical University of MadridMadridSpain
| | - Marta Di Forti
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | | | - Conrad Iyegbe
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Assen Jablensky
- Centre for Clinical Research in NeuropsychiatryThe University of Western AustraliaPerth, Western AustraliaAustralia
| | - Rebecca Jones
- Division of PsychiatryUniversity College LondonLondonUK
| | - Mei‐Hua Hall
- Psychosis Neurobiology Laboratory, Harvard Medical SchoolMcLean HospitalBelmontMassachusetts
| | - Rene Kahn
- Department of Psychiatry, Brain Centre Rudolf MagnusUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Luba Kalaydjieva
- Harry Perkins Institute of Medical Research and Centre for Medical ResearchThe University of Western AustraliaPerthAustralia
| | - Eugenia Kravariti
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Colm McDonald
- The Centre for Neuroimaging & Cognitive Genomics (NICOG) and NCBES Galway Neuroscience CentreNational University of Ireland GalwayGalwayIreland
| | - Andrew M. McIntosh
- Division of Psychiatry, University of EdinburghRoyal Edinburgh HospitalEdinburghUK
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of EdinburghEdinburghUK
| | | | | | - Marco Picchioni
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Diana P. Prata
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
- Faculdade de Medicina, Instituto de Medicina MolecularUniversidade de LisboaPortugal
| | - Dan Rujescu
- Department of PsychiatryLudwig‐Maximilians University of MunichMunichGermany
- Department of Psychiatry, Psychotherapy and PsychosomaticsUniversity of Halle WittenbergHalleGermany
| | - Katja Schulze
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Madiha Shaikh
- North East London Foundation TrustLondonUK
- Research Department of Clinical, Educational and Health PsychologyUniversity College LondonLondonUK
| | - Timothea Toulopoulou
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
- Department of Psychology, Bilkent UniversityMain CampusBilkent, AnkaraTurkey
- Department of PsychologyThe University of Hong Kong, Pokfulam RdHong Kong SARChina
- The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong KongThe Hong Kong Jockey Club Building for Interdisciplinary ResearchHong Kong SARChina
| | - Neeltje van Haren
- Department of Psychiatry, Brain Centre Rudolf MagnusUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Jim van Os
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
- Department of Psychiatry and Psychology, Maastricht University Medical CentreEURONMaastrichtThe Netherlands
| | - Evangelos Vassos
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Muriel Walshe
- Division of PsychiatryUniversity College LondonLondonUK
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | | | - Cathryn Lewis
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Robin M. Murray
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - John Powell
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Elvira Bramon
- Division of PsychiatryUniversity College LondonLondonUK
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
- Institute of Cognitive NeuroscienceUniversity College LondonLondonUK
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13
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Assessing the Relationship between Performance on the University of California Performance Skills Assessment (UPSA) and Outcomes in Schizophrenia: A Systematic Review and Evidence Synthesis. SCHIZOPHRENIA RESEARCH AND TREATMENT 2018; 2018:9075174. [PMID: 30687553 PMCID: PMC6327277 DOI: 10.1155/2018/9075174] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Revised: 11/12/2018] [Accepted: 12/05/2018] [Indexed: 01/18/2023]
Abstract
OBJECTIVE To perform a systematic review of the published literature to evaluate how functional capacity, as measured by the University of California at San Diego (UCSD) Performance-based Skills Assessment (UPSA), relates to other functional measures and real-world outcomes among individuals with schizophrenia. METHODS The MEDLINE® and Embase® databases were searched to identify joint evaluations with UPSA and key functional outcomes (functional scale measures; generic or disease-specific, health-related quality of life [HRQoL]; or real-world outcomes [residential status; employment status]) in patients with schizophrenia. Pearson correlations were estimated between UPSA scores, HRQoL, other functional scale measures, and real-world outcomes, for outcomes described in at least six studies. RESULTS The synthesis included 76 studies that provided 73 unique data sets. Quantitative assessment between the Specific Level of Function (SLOF) (n=18) scores and UPSA scores demonstrated a moderate borderline-significant correlation (0.45, p=0.06). Quantitative analysis of the relationship between the Global Assessment of Functioning (GAF) (n=11) and the Multidimensional Scale of Independent Functioning (MSIF) (n=6) scales revealed moderate and small nonsignificant Pearson correlations of -0.34 (p=0.31) and 0.12 (p=0.83), respectively. There was a small borderline-significant correlation between UPSA score and residential status (n=36; 0.31; p=0.08), while no correlation was found between UPSA score and employment status (n=19; 0.04; p=0.88). CONCLUSION The SLOF was the most often used functional measure and had the strongest observed correlation with the UPSA. Although knowledge gaps remain, evidence from this review indicates that there is a quantitative relationship between functional capacity and real-world outcomes in individuals with schizophrenia.
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Blokland GAM, Mesholam-Gately RI, Toulopoulou T, del Re EC, Lam M, DeLisi LE, Donohoe G, Walters JTR, Seidman LJ, Petryshen TL. Heritability of Neuropsychological Measures in Schizophrenia and Nonpsychiatric Populations: A Systematic Review and Meta-analysis. Schizophr Bull 2017; 43:788-800. [PMID: 27872257 PMCID: PMC5472145 DOI: 10.1093/schbul/sbw146] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Schizophrenia is characterized by neuropsychological deficits across many cognitive domains. Cognitive phenotypes with high heritability and genetic overlap with schizophrenia liability can help elucidate the mechanisms leading from genes to psychopathology. We performed a meta-analysis of 170 published twin and family heritability studies of >800 000 nonpsychiatric and schizophrenia subjects to accurately estimate heritability across many neuropsychological tests and cognitive domains. The proportion of total variance of each phenotype due to additive genetic effects (A), shared environment (C), and unshared environment and error (E), was calculated by averaging A, C, and E estimates across studies and weighting by sample size. Heritability ranged across phenotypes, likely due to differences in genetic and environmental effects, with the highest heritability for General Cognitive Ability (32%-67%), Verbal Ability (43%-72%), Visuospatial Ability (20%-80%), and Attention/Processing Speed (28%-74%), while the lowest heritability was observed for Executive Function (20%-40%). These results confirm that many cognitive phenotypes are under strong genetic influences. Heritability estimates were comparable in nonpsychiatric and schizophrenia samples, suggesting that environmental factors and illness-related moderators (eg, medication) do not substantially decrease heritability in schizophrenia samples, and that genetic studies in schizophrenia samples are informative for elucidating the genetic basis of cognitive deficits. Substantial genetic overlap between cognitive phenotypes and schizophrenia liability (average rg = -.58) in twin studies supports partially shared genetic etiology. It will be important to conduct comparative studies in well-powered samples to determine whether the same or different genes and genetic variants influence cognition in schizophrenia patients and the general population.
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Affiliation(s)
- Gabriëlla A. M. Blokland
- Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry and Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA;,Department of Psychiatry, Harvard Medical School, Boston, MA;,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Raquelle I. Mesholam-Gately
- Department of Psychiatry, Harvard Medical School, Boston, MA;,Commonwealth Research Center, Harvard Medical School, Boston, MA;,Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA
| | - Timothea Toulopoulou
- Psychology Department, Bilkent University, Ankara, Turkey;,Department of Psychology, University of Hong Kong, Pokfulam, Hong Kong;,Department of Psychosis Studies, Institute of Psychiatry, King’s College London, London, UK
| | - Elisabetta C. del Re
- Department of Psychiatry, Harvard Medical School, Boston, MA;,Clinical Neuroscience Division, Laboratory of Neuroscience, Department of Psychiatry, Veterans Affairs Boston Healthcare System, Brockton, MA
| | - Max Lam
- Institute of Mental Health, Woodbridge Hospital, Singapore
| | - Lynn E. DeLisi
- Department of Psychiatry, Harvard Medical School, Boston, MA;,Clinical Neuroscience Division, Laboratory of Neuroscience, Department of Psychiatry, Veterans Affairs Boston Healthcare System, Brockton, MA
| | - Gary Donohoe
- School of Psychology, National University of Ireland, Galway, Ireland;,Neuropsychiatric Genetics Group, Department of Psychiatry and Trinity College Institute of Neuroscience, Trinity College, Dublin, Ireland
| | - James T. R. Walters
- Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | | | - Larry J. Seidman
- Department of Psychiatry, Harvard Medical School, Boston, MA;,Commonwealth Research Center, Harvard Medical School, Boston, MA;,Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA
| | - Tracey L. Petryshen
- Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry and Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA;,Department of Psychiatry, Harvard Medical School, Boston, MA;,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA
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15
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Thomas ML, Patt VM, Bismark A, Sprock J, Tarasenko M, Light GA, Brown GG. Evidence of systematic attenuation in the measurement of cognitive deficits in schizophrenia. JOURNAL OF ABNORMAL PSYCHOLOGY 2017; 126:312-324. [PMID: 28277736 PMCID: PMC5378601 DOI: 10.1037/abn0000256] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Cognitive tasks that are too hard or too easy produce imprecise measurements of ability, which, in turn, attenuates group differences and can lead to inaccurate conclusions in clinical research. We aimed to illustrate this problem using a popular experimental measure of working memory-the N-back task-and to suggest corrective strategies for measuring working memory and other cognitive deficits in schizophrenia. Samples of undergraduates (n = 42), community controls (n = 25), outpatients with schizophrenia (n = 33), and inpatients with schizophrenia (n = 17) completed the N-back. Predictors of task difficulty-including load, number of word syllables, and presentation time-were experimentally manipulated. Using a methodology that combined techniques from signal detection theory and item response theory, we examined predictors of difficulty and precision on the N-back task. Load and item type were the 2 strongest predictors of difficulty. Measurement precision was associated with ability, and ability varied by group; as a result, patients were measured more precisely than controls. Although difficulty was well matched to the ability levels of impaired examinees, most task conditions were too easy for nonimpaired participants. In a simulation study, N-back tasks primarily consisting of 1- and 2-back load conditions were unreliable, and attenuated effect size (Cohen's d) by as much as 50%. The results suggest that N-back tasks, as commonly designed, may underestimate patients' cognitive deficits as a result of nonoptimized measurement properties. Overall, this cautionary study provides a template for identifying and correcting measurement problems in clinical studies of abnormal cognition. (PsycINFO Database Record
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Affiliation(s)
- Michael L. Thomas
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
- VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, United States
| | - Virginie M. Patt
- San Diego State University/University of California, San Diego, Joint Doctoral Program in Clinical Psychology
| | - Andrew Bismark
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
- VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, United States
| | - Joyce Sprock
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
| | - Melissa Tarasenko
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
- VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, United States
| | - Gregory A. Light
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
- VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, United States
| | - Gregory G. Brown
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
- VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, United States
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16
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17
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Grossman M, Bowie CR, Lepage M, Malla AK, Joober R, Iyer SN. Smoking status and its relationship to demographic and clinical characteristics in first episode psychosis. J Psychiatr Res 2017; 85:83-90. [PMID: 27863280 DOI: 10.1016/j.jpsychires.2016.10.022] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2016] [Revised: 09/15/2016] [Accepted: 10/26/2016] [Indexed: 02/08/2023]
Abstract
Elevated rates of cigarette smoking are observed prior to the onset of psychosis and remain stable early in the illness. Cannabis use frequently co-occurs with cigarette smoking and is independently associated with distinct clinical outcomes. However, past research has not controlled for cannabis use in cigarette smokers with first episode psychosis (FEP), limiting conclusions on the unique relationship of cigarette smoking to the demographic and clinical profiles of these patients. The present study therefore aimed to: (1) Determine the prevalence and patterns of cigarette smoking and its co-use with cannabis in FEP, and (2) Examine the demographic, clinical, cognitive, and functional characteristics associated with cigarette smoking status, after adjusting for frequency of cannabis use. Patients entering specialized treatment for FEP (N = 140) were divided into groups according to their current smoking status: 66 non-smokers (0 cigarettes/day), 47 light/moderate smokers (1-19 cigarettes/day; M = 9.81, SD = 3.93), and 27 heavy smokers (≥20 cigarettes/day; M = 26.39, SD = 6.31). The prevalence of cigarette smoking was 53% and smoking status was highly associated with frequency of cannabis use. After adjusting for cannabis use, significant between-group differences emerged. Heavy smokers were older at program entry and had a later age of onset of psychosis than light/moderate and non-smokers. Non-smokers had more education, better neurocognitive performance, and higher levels of functioning than light/moderate and heavy smokers. Prospective, longitudinal studies are needed to better understand the clinical significance of tobacco use and factors that contribute to the initiation and continuation of smoking behaviours in FEP.
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Affiliation(s)
- Michael Grossman
- Department of Psychology, Queen's University, 62 Arch Street, Kingston, ON, K7L 3N6, Canada.
| | - Christopher R Bowie
- Department of Psychology, Queen's University, 62 Arch Street, Kingston, ON, K7L 3N6, Canada.
| | - Martin Lepage
- Prevention and Early Intervention Program for Psychosis (PEPP-Montréal), Douglas Mental Health University Institute, 6875 Boulevard LaSalle, Verdun, QC, H4H 1R3, Canada; Department of Psychiatry, McGill University, 1033 Pine Avenue West, Montréal, QC, H3A 1A1, Canada.
| | - Ashok K Malla
- Prevention and Early Intervention Program for Psychosis (PEPP-Montréal), Douglas Mental Health University Institute, 6875 Boulevard LaSalle, Verdun, QC, H4H 1R3, Canada; ACCESS Open Minds (A Pan-Canadian Youth Mental Health Network), Douglas Mental Health University Institute, 6875 Boulevard LaSalle, Verdun, QC, H4H 1R3, Canada; Department of Psychiatry, McGill University, 1033 Pine Avenue West, Montréal, QC, H3A 1A1, Canada.
| | - Ridha Joober
- Prevention and Early Intervention Program for Psychosis (PEPP-Montréal), Douglas Mental Health University Institute, 6875 Boulevard LaSalle, Verdun, QC, H4H 1R3, Canada; Department of Psychiatry, McGill University, 1033 Pine Avenue West, Montréal, QC, H3A 1A1, Canada.
| | - Srividya N Iyer
- Prevention and Early Intervention Program for Psychosis (PEPP-Montréal), Douglas Mental Health University Institute, 6875 Boulevard LaSalle, Verdun, QC, H4H 1R3, Canada; ACCESS Open Minds (A Pan-Canadian Youth Mental Health Network), Douglas Mental Health University Institute, 6875 Boulevard LaSalle, Verdun, QC, H4H 1R3, Canada; Department of Psychiatry, McGill University, 1033 Pine Avenue West, Montréal, QC, H3A 1A1, Canada.
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18
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Wu BJ, Lan TH. Predictors of smoking reduction outcomes in a sample of 287 patients with schizophrenia spectrum disorders. Eur Arch Psychiatry Clin Neurosci 2017; 267:63-72. [PMID: 26310877 DOI: 10.1007/s00406-015-0636-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2015] [Accepted: 08/11/2015] [Indexed: 12/28/2022]
Abstract
Many studies have investigated whether a type of antipsychotics or type of adjuvant is associated with smoking reduction in patients with schizophrenia. However, there has been no study exploring a comprehensive range of factors related to smoking reduction in schizophrenia patients. We analyzed a dataset of 287 smoking patients with schizophrenia who participated in an 8-week open-label study with high- (n = 90) or low-dose nicotine dermal patches (n = 132) or bupropion (n = 65). A logistic regression model and a linear mixed model were used to explore factors associated with the outcomes of smoking cessation and reduction, i.e., the number of cigarettes smoked and the level of nicotine dependence. The total cessation rate was 6.3 % (18/287). There were no significant predictors of cessation. The time effect of reduction was significant during the program (p = 0.001). Type of antipsychotics (p = 0.018), readiness to quit (p = 0.014), baseline number of cigarettes smoked per day (p = 0.001), and nicotine dependence level (p = 0.001) were significantly associated with smoking reduction. Patients on first-generation antipsychotics (n = 129) or clozapine (n = 70) reduced their smoking more than those on non-clozapine second-generation antipsychotics (n = 74). Patients in the preparation stage (n = 97) or in the contemplation (n = 70) reduced their smoking more than those in the precontemplation stage (n = 120). The mechanisms of tobacco addiction need to be better understood for further development of effective cessation programs in patients with schizophrenia.
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Affiliation(s)
- Bo-Jian Wu
- Department of Psychiatry, Yuli Hospital, Ministry of Health and Welfare, Hualien, Taiwan.,Institute of Clinical Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Tsuo-Hung Lan
- Institute of Clinical Medicine, National Yang-Ming University, Taipei, Taiwan. .,Department of Psychiatry, School of Medicine, National Yang-Ming University, Taipei, Taiwan. .,Center for Neuropsychiatric Research, NHRI, Miaoli, Taiwan. .,Department of Psychiatry, Taichung Veterans General Hospital, 160, Sec.3, Chung-Kang Rd, Taichung, 40705, Taiwan.
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19
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Thomas ML, Green MF, Hellemann G, Sugar CA, Tarasenko M, Calkins ME, Greenwood TA, Gur RE, Gur RC, Lazzeroni LC, Nuechterlein KH, Radant AD, Seidman LJ, Shiluk AL, Siever LJ, Silverman JM, Sprock J, Stone WS, Swerdlow NR, Tsuang DW, Tsuang MT, Turetsky BI, Braff DL, Light GA. Modeling Deficits From Early Auditory Information Processing to Psychosocial Functioning in Schizophrenia. JAMA Psychiatry 2017; 74:37-46. [PMID: 27926742 PMCID: PMC5453308 DOI: 10.1001/jamapsychiatry.2016.2980] [Citation(s) in RCA: 149] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
IMPORTANCE Neurophysiologic measures of early auditory information processing (EAP) are used as endophenotypes in genomic studies and biomarkers in clinical intervention studies. Research in schizophrenia has established correlations among measures of EAP, cognition, clinical symptoms, and functional outcome. Clarifying these associations by determining the pathways through which deficits in EAP affect functioning would suggest when and where to therapeutically intervene. OBJECTIVES To characterize the pathways from EAP to outcome and to estimate the extent to which enhancement of basic information processing might improve cognition and psychosocial functioning in schizophrenia. DESIGN, SETTING, AND PARTICIPANTS Cross-sectional data were analyzed using structural equation modeling to examine the associations among EAP, cognition, negative symptoms, and functional outcome. Participants were recruited from the community at 5 geographically distributed laboratories as part of the Consortium on the Genetics of Schizophrenia 2 from July 1, 2010, through January 31, 2014. This well-characterized cohort of 1415 patients with schizophrenia underwent EAP, cognitive, and thorough clinical and functional assessment. MAIN OUTCOME AND MEASURES Mismatch negativity, P3a, and reorienting negativity were used to measure EAP. Cognition was measured by the Letter Number Span test and scales from the California Verbal Learning Test-Second Edition, the Wechsler Memory Scale-Third Edition, and the Penn Computerized Neurocognitive Battery. Negative symptoms were measured by the Scale for the Assessment of Negative Symptoms. Functional outcome was measured by the Role Functioning Scale. RESULTS Participants included 1415 unrelated outpatients diagnosed with schizophrenia or schizoaffective disorder (mean [SD] age, 46 [11] years; 979 males [69.2%] and 619 white [43.7%]). Early auditory information processing had a direct effect on cognition (β = 0.37, P < .001), cognition had a direct effect on negative symptoms (β = -0.16, P < .001), and both cognition (β = 0.26, P < .001) and experiential negative symptoms (β = -0.75, P < .001) had direct effects on functional outcome. The indirect effect of EAP on functional outcome was significant as well (β = 0.14, P < .001). Overall, EAP had a fully mediated effect on functional outcome, engaging general rather than modality-specific cognition, with separate pathways that involved or bypassed negative symptoms. CONCLUSIONS AND RELEVANCE The data support a model in which EAP deficits lead to poor functional outcome via impaired cognition and increased negative symptoms. Results can be used to help guide mechanistically informed, personalized treatments and support the strategy of using EAP measures as surrogate end points in early-stage procognitive intervention studies.
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Affiliation(s)
- Michael L. Thomas
- Department of Psychiatry, University of California San Diego, La Jolla, CA,VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA
| | - Michael F. Green
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA,VA Greater Los Angeles Healthcare System, Los Angeles, CA
| | - Gerhard Hellemann
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA,VA Greater Los Angeles Healthcare System, Los Angeles, CA
| | - Catherine A. Sugar
- Department of Biostatistics, University of California Los Angeles School of Public Health, Los Angeles, CA
| | - Melissa Tarasenko
- Department of Psychiatry, University of California San Diego, La Jolla, CA,VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA
| | - Monica E. Calkins
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | | | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | - Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | - Laura C. Lazzeroni
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA
| | - Keith H. Nuechterlein
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA
| | - Allen D. Radant
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA,VA Puget Sound Health Care System, Seattle, WA
| | - Larry J. Seidman
- Department of Psychiatry, Harvard Medical School, Boston, MA,Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA
| | | | - Larry J. Siever
- Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY,James J. Peters VA Medical Center, New York, NY
| | - Jeremy M. Silverman
- Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY,James J. Peters VA Medical Center, New York, NY
| | - Joyce Sprock
- Department of Psychiatry, University of California San Diego, La Jolla, CA
| | - William S. Stone
- Department of Psychiatry, Harvard Medical School, Boston, MA,Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA
| | - Neal R. Swerdlow
- Department of Psychiatry, University of California San Diego, La Jolla, CA
| | - Debby W. Tsuang
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA,VA Puget Sound Health Care System, Seattle, WA
| | - Ming T. Tsuang
- Department of Psychiatry, University of California San Diego, La Jolla, CA,Center for Behavioral Genomics, and Institute for Genomic Medicine, University of California San Diego, La Jolla, CA,Harvard Institute of Psychiatric Epidemiology and Genetics, Boston, MA
| | - Bruce I. Turetsky
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | - David L. Braff
- Department of Psychiatry, University of California San Diego, La Jolla, CA
| | - Gregory A. Light
- Department of Psychiatry, University of California San Diego, La Jolla, CA,VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA
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20
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Measuring the capacity for auditory system plasticity: An examination of performance gains during initial exposure to auditory-targeted cognitive training in schizophrenia. Schizophr Res 2016; 172:123-30. [PMID: 26851143 PMCID: PMC5072522 DOI: 10.1016/j.schres.2016.01.019] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/02/2015] [Revised: 01/07/2016] [Accepted: 01/10/2016] [Indexed: 12/28/2022]
Abstract
UNLABELLED Auditory-Targeted Cognitive Training (ATCT), which aims to improve auditory information processing efficiency, has shown great promise for remediating cognitive deficits in schizophrenia (SZ). However, there is substantial heterogeneity in the degree of cognitive gains made during ATCT, and some patients show negligible benefit after completing therapeutic doses of training. Identifying individual differences that can be measured early in the course of ATCT and that predict subsequent cognitive benefits from the intervention is therefore important. The present study calculated a variety of performance metrics during the initial hour of exposure to ATCT Sound Sweeps, a frequency discrimination time-order judgment task, and investigated the relationships of these metrics to demographic, clinical, and cognitive characteristics of SZ patients. Thirty-seven SZ outpatients completed measures of auditory attention, working memory, verbal memory, and executive functioning, followed by 1h of Sound Sweeps training. Performance metrics, calculated after the first training level, the first training stage (Levels 1-4), and the entire hour of training included baseline and best auditory processing speed (APS) scores, as well as percent improvement in APS after training. The number of training levels completed by each participant was also calculated. Baseline and best APS correlated with performance in all cognitive domains, whereas APS improvements only correlated with verbal memory. Number of training levels completed was marginally associated with auditory attention only. CONCLUSIONS Sound Sweeps performance correlates with a range of neurocognitive abilities. APS improvement may provide a particularly sensitive index of "plasticity potential" within the neural network underlying verbal learning and memory.
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21
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Light GA, Swerdlow NR. Future clinical uses of neurophysiological biomarkers to predict and monitor treatment response for schizophrenia. Ann N Y Acad Sci 2015. [PMID: 25752648 DOI: 10.llll/nyas.12730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Advances in psychiatric neuroscience have transformed our understanding of impaired and spared brain functions in psychotic illnesses. Despite substantial progress, few (if any) laboratory tests have graduated to clinics to inform diagnoses, guide treatments, and monitor treatment response. Providers must rely on careful behavioral observation and interview techniques to make inferences about patients' inner experiences and then secondary deductions about impacted neural systems. Development of more effective treatments has also been hindered by a lack of translational quantitative biomarkers that can span the brain-behavior treatment knowledge gap. Here, we describe an example of a simple, low-cost, and translatable electroencephalography (EEG) measure that offers promise for improving our understanding and treatment of psychotic illnesses: mismatch negativity (MMN). MMN is sensitive to and/or predicts response to some pharmacologic and nonpharmacologic interventions and accounts for substantial portions of variance in clinical, cognitive, and psychosocial functioning in schizophrenia (SZ). This measure has recently been validated for use in large-scale multisite clinical studies of SZ. Finally, MMN greatly improves our ability to forecast which individuals at high clinical risk actually develop a psychotic illness. These attributes suggest that MMN can contribute to personalized biomarker-guided treatment strategies aimed at ameliorating or even preventing the onset of psychosis.
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Affiliation(s)
- Gregory A Light
- VISN 22 Mental Illness, Research, Education, and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, California; Department of Psychiatry, University of California San Diego, La Jolla, California
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22
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Stone WS, Mesholam-Gately RI, Braff DL, Calkins ME, Freedman R, Green MF, Greenwood TA, Gur RE, Gur RC, Lazzeroni LC, Light GA, Nuechterlein KH, Olincy A, Radant AD, Siever LJ, Silverman JM, Sprock J, Sugar CA, Swerdlow NR, Tsuang DW, Tsuang MT, Turetsky BI, Seidman LJ. California Verbal Learning Test-II performance in schizophrenia as a function of ascertainment strategy: comparing the first and second phases of the Consortium on the Genetics of Schizophrenia (COGS). Schizophr Res 2015; 163:32-7. [PMID: 25497440 PMCID: PMC5954831 DOI: 10.1016/j.schres.2014.10.029] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2014] [Revised: 10/16/2014] [Accepted: 10/19/2014] [Indexed: 12/21/2022]
Abstract
The first phase of the Consortium on the Genetics of Schizophrenia (COGS-1) showed performance deficits in learning and memory on the California Verbal Learning Test, Second Edition (CVLT-II) in individuals with schizophrenia (SZ), compared to healthy comparison subjects (HCS). A question is whether the COGS-1 study, which used a family study design (i.e. studying relatively intact families), yielded "milder" SZ phenotypes than those acquired subsequently in the COGS-2 case-control design that did not recruit unaffected family members. CVLT-II performance was compared for the COGS-1 and COGS-2 samples. Analyses focused on learning, recall and recognition variables, with age, gender and education as covariates. Analyses of COGS-2 data explored effects of additional covariates and moderating factors in CVLT-II performance. 324 SZ subjects and 510 HCS had complete CVLT-II and covariate data in COGS-1, while 1356 SZ and 1036 HCS had complete data in COGS-2. Except for recognition memory, analysis of covariance showed significantly worse performance in COGS-2 on all CVLT-II variables for SZ and HCS, and remained significant in the presence of the covariates. Performance in each of the 5 learning trials differed significantly. However, effect sizes comparing cases and controls were comparable across the two studies. COGS-2 analyses confirmed SZ performance deficits despite effects of multiple significant covariates and moderating factors. CVLT-II performance was worse in COGS-2 than in COGS-1 for both the SZ and the HCS in this large cohort, likely due to cohort effects. Demographically corrected data yield a consistent pattern of performance across the two studies in SZ.
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Affiliation(s)
- William S Stone
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA, United States.
| | - Raquelle I Mesholam-Gately
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - David L Braff
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States; VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, United States
| | - Monica E Calkins
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, United States
| | - Robert Freedman
- Department of Psychiatry, University of Colorado Health Sciences Center, Denver, CO, United States
| | - Michael F Green
- Department of Psychiatry and Biobehavioral Sciences, Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States; VA Greater Los Angeles Healthcare System, Los Angeles, CA, United States
| | - Tiffany A Greenwood
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
| | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, United States
| | - Ruben C Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, United States
| | - Laura C Lazzeroni
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, United States; Department of Pediatrics, Stanford University, Stanford, CA, United States
| | - Gregory A Light
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States; VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, United States
| | - Keith H Nuechterlein
- Department of Psychiatry and Biobehavioral Sciences, Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - Ann Olincy
- Department of Psychiatry, University of Colorado Health Sciences Center, Denver, CO, United States
| | - Allen D Radant
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States; VA Puget Sound Health Care System, Seattle, WA, United States
| | - Larry J Siever
- Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY, United States; James J. Peters VA Medical Center, New York, NY, United States
| | - Jeremy M Silverman
- Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY, United States; James J. Peters VA Medical Center, New York, NY, United States
| | - Joyce Sprock
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
| | - Catherine A Sugar
- Department of Biostatistics, University of California Los Angeles School of Public Health, Los Angeles, CA, United States
| | - Neal R Swerdlow
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
| | - Debby W Tsuang
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States; VA Puget Sound Health Care System, Seattle, WA, United States
| | - Ming T Tsuang
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States; Harvard Institute of Psychiatric Epidemiology and Genetics, Boston, MA, United States; VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, United States; Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, United States
| | - Bruce I Turetsky
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, United States
| | - Larry J Seidman
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA, United States
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23
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The importance of endophenotypes in schizophrenia research. Schizophr Res 2015; 163:1-8. [PMID: 25795083 DOI: 10.1016/j.schres.2015.02.007] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2014] [Revised: 02/06/2015] [Accepted: 02/06/2015] [Indexed: 11/21/2022]
Abstract
Endophenotypes provide a powerful neurobiological platform from which we can understand the genomic and neural substrates of schizophrenia and other common complex neuropsychiatric disorders. The Consortium on the Genetics of Schizophrenia (COGS) has conducted multisite studies on carefully selected key neurocognitive and neurophysiological endophenotypes in 300 families (COGS-1) and then in a follow up multisite case-control study of 2471 subjects (COGS-2). Endophenotypes are neurobiologically informed quantitative measures that show deficits in probands and their first degree relatives. They are more amenable to statistical analysis than are "fuzzy" qualitative clinical traits or confoundingly heterogeneous diagnostic categories. Endophenotypes are also viewed as uniquely informative in traditional diagnosis-based as well as emerging NIMH Research Domain (RDoC) contexts, offering a bridge between the two approaches to psychopathology classification and research. Endo- or intermediate phenotypes are heritable, and in the COGS-1 cohort their level of heritability is in the same range as is the heritability of schizophrenia itself, using the same statistical methods and subjects to assess both. Because we can demonstrate endophenotypes link to both gene networks and neural circuits on the one hand and also to real-life function, endophenotypes provide a critically important bridge for "connecting the dots" between genes, cells, circuits, information processing, neurocognition and functional impairment and personalized treatment selection in schizophrenia patients. By connecting schizophrenia risk genes with neurobiologically informed endophenotypes, and via the use of association, linkage, sequencing, stem cell and other strategies, we can provide our field with new neurobiologically informed information in our efforts to understand and treat schizophrenia. Evolving views, data and new analytic strategies about schizophrenia risk, pathology and treatment are described in this Viewpoint and in the accompanying Special Issue reports.
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24
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Nuechterlein KH, Green MF, Calkins ME, Greenwood TA, Gur RE, Gur RC, Lazzeroni LC, Light GA, Radant AD, Seidman LJ, Siever LJ, Silverman JM, Sprock J, Stone WS, Sugar CA, Swerdlow NR, Tsuang DW, Tsuang MT, Turetsky BI, Braff DL. Attention/vigilance in schizophrenia: performance results from a large multi-site study of the Consortium on the Genetics of Schizophrenia (COGS). Schizophr Res 2015; 163:38-46. [PMID: 25749017 PMCID: PMC4382444 DOI: 10.1016/j.schres.2015.01.017] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2014] [Revised: 01/07/2015] [Accepted: 01/09/2015] [Indexed: 12/31/2022]
Abstract
Attention/vigilance impairments are present in individuals with schizophrenia across psychotic and remitted states and in their first-degree relatives. An important question is whether deficits in attention/vigilance can be consistently and reliably measured across sites varying in many participant demographic, clinical, and functional characteristics, as needed for large-scale genetic studies of endophenotypes. We examined Continuous Performance Test (CPT) data from phase 2 of the Consortium on the Genetics of Schizophrenia (COGS-2), the largest-scale assessment of cognitive and psychophysiological endophenotypes relevant to schizophrenia. The CPT data from 2251 participants from five sites were examined. A perceptual-load vigilance task (the Degraded Stimulus CPT or DS-CPT) and a memory-load vigilance task (CPT-Identical Pairs or CPT-IP) were utilized. Schizophrenia patients performed more poorly than healthy comparison subjects (HCS) across sites, despite significant site differences in participant age, sex, education, and racial distribution. Patient-HCS differences in signal/noise discrimination (d') in the DS-CPT varied significantly across sites, but averaged a medium effect size. CPT-IP performance showed large patient-HCS differences across sites. Poor CPT performance was independent of or weakly correlated with symptom severity, but was significantly associated with lower educational achievement and functional capacity. Current smoking was associated with poorer CPT-IP d'. Patients taking both atypical and typical antipsychotic medication performed more poorly than those on no or atypical antipsychotic medications, likely reflecting their greater severity of illness. We conclude that CPT deficits in schizophrenia can be reliably detected across sites, are relatively independent of current symptom severity, and are related to functional capacity.
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Affiliation(s)
- Keith H. Nuechterlein
- Department of Psychiatry and Biobehavioral Science, Geffen School of Medicine, University of California, Los Angeles, CA, United States,Corresponding author: Keith H. Nuechterlein, Department of Psychiatry and Biobehavioral Science, David Geffen School of Medicine at UCLA, 300 UCLA Medical Plaza, Room 2240, Los Angeles, CA 90095-6968.
| | - Michael F. Green
- Department of Psychiatry and Biobehavioral Science, Geffen School of Medicine, University of California, Los Angeles, CA, United States, VA Greater Los Angeles Healthcare System, Los Angeles, CA, United States
| | - Monica E. Calkins
- Department of Psychiatry, University of Pennsylvania, Philadelphia, United States
| | - Tiffany A. Greenwood
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
| | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, United States
| | - Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, United States
| | - Laura C. Lazzeroni
- Department of Psychiatry and Behavioral Science, Stanford University, Stanford, CA United States, Department of Pediatrics, Stanford University, Stanford, CA, United States
| | - Gregory A. Light
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States, VISN22, Mental Illness Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, United States
| | - Allen D. Radant
- Department of Psychiatry and Behavioral Science, University of Washington, Seattle, WA, United States, VA Puget Sound Healthcare System, Seattle, WA, United States
| | - Larry J. Seidman
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States, Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - Larry J. Siever
- Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY, United States, James J. Peters VA Medical Center, New York, NY, United States
| | - Jeremy M. Silverman
- Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY, United States, James J. Peters VA Medical Center, New York, NY, United States
| | - Joyce Sprock
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States, VISN22, Mental Illness Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, United States
| | - William S. Stone
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States, Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - Catherine A. Sugar
- Department of Psychiatry and Biobehavioral Science, Geffen School of Medicine, University of California, Los Angeles, CA, United States, VA Greater Los Angeles Healthcare System, Los Angeles, CA, United States, Department of Biostatistics, University of California, Los Angeles, CA, United States
| | - Neal R. Swerdlow
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
| | - Debby W. Tsuang
- Department of Psychiatry and Behavioral Science, University of Washington, Seattle, WA, United States, VA Puget Sound Healthcare System, Seattle, WA, United States
| | - Ming T. Tsuang
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States, Institute for Genomic Medicine, University of California, San Diego, CA, United States,The Center for Behavioral Genomics, Department of Psychiatry, University of California, San Diego, CA, United States, Harvard Institute of Psychiatry Epidemiology and Genetics, Boston, MA, United States
| | - Bruce I. Turetsky
- Department of Psychiatry, University of Pennsylvania, Philadelphia, United States
| | - David L. Braff
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States, VISN22, Mental Illness Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, United States
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25
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Gur RC, Braff DL, Calkins ME, Dobie DJ, Freedman R, Green MF, Greenwood TA, Lazzeroni LC, Light GA, Nuechterlein KH, Olincy A, Radant AD, Seidman LJ, Siever LJ, Silverman JM, Sprock J, Stone WS, Sugar CA, Swerdlow NR, Tsuang DW, Tsuang MT, Turetsky BI, Gur RE. Neurocognitive performance in family-based and case-control studies of schizophrenia. Schizophr Res 2015; 163:17-23. [PMID: 25432636 PMCID: PMC4441547 DOI: 10.1016/j.schres.2014.10.049] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2014] [Revised: 10/19/2014] [Accepted: 10/21/2014] [Indexed: 11/19/2022]
Abstract
BACKGROUND Neurocognitive deficits in schizophrenia (SZ) are established and the Consortium on the Genetics of Schizophrenia (COGS) investigated such measures as endophenotypes in family-based (COGS-1) and case-control (COGS-2) studies. By requiring family participation, family-based sampling may result in samples that vary demographically and perform better on neurocognitive measures. METHODS The Penn computerized neurocognitive battery (CNB) evaluates accuracy and speed of performance for several domains and was administered across sites in COGS-1 and COGS-2. Most tests were included in both studies. COGS-1 included 328 patients with SZ and 497 healthy comparison subjects (HCS) and COGS-2 included 1195 patients and 1009 HCS. RESULTS Demographically, COGS-1 participants were younger, more educated, with more educated parents and higher estimated IQ compared to COGS-2 participants. After controlling for demographics, the two samples produced very similar performance profiles compared to their respective controls. As expected, performance was better and with smaller effect sizes compared to controls in COGS-1 relative to COGS-2. Better performance was most pronounced for spatial processing while emotion identification had large effect sizes for both accuracy and speed in both samples. Performance was positively correlated with functioning and negatively with negative and positive symptoms in both samples, but correlations were attenuated in COGS-2, especially with positive symptoms. CONCLUSIONS Patients ascertained through family-based design have more favorable demographics and better performance on some neurocognitive domains. Thus, studies that use case-control ascertainment may tap into populations with more severe forms of illness that are exposed to less favorable factors compared to those ascertained with family-based designs.
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Affiliation(s)
- Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania,
Philadelphia, PA
| | - David L. Braff
- Department of Psychiatry, University of California San
Diego, La Jolla, CA; VISN-22 Mental Illness, Research, Education and Clinical Center
(MIRECC), VA San Diego Healthcare System
| | - Monica E. Calkins
- Department of Psychiatry, University of Pennsylvania,
Philadelphia, PA
| | - Dorcas J. Dobie
- Department of Psychiatry and Behavioral Sciences,
University of Washington, Seattle, WA; VA Puget Sound Health Care System, Seattle,
WA
| | - Robert Freedman
- Department of Psychiatry, University of Colorado Denver,
Aurora, CO
| | - Michael F. Green
- Department of Psychiatry and Biobehavioral Sciences, Geffen
School of Medicine, University of California Los Angeles, Los Angeles, CA; VA
Greater Los Angeles Healthcare System, Los Angeles, CA
| | - Tiffany A. Greenwood
- Department of Psychiatry, University of California San
Diego, La Jolla, CA; VISN-22 Mental Illness, Research, Education and Clinical Center
(MIRECC), VA San Diego Healthcare System
| | | | - Gregory A. Light
- Department of Psychiatry, University of California San
Diego, La Jolla, CA; VISN-22 Mental Illness, Research, Education and Clinical Center
(MIRECC), VA San Diego Healthcare System
| | - Keith H. Nuechterlein
- Department of Psychiatry and Biobehavioral Sciences, Geffen
School of Medicine, University of California Los Angeles, Los Angeles, CA; VA
Greater Los Angeles Healthcare System, Los Angeles, CA
| | - Ann Olincy
- Department of Psychiatry, University of Colorado Denver,
Aurora, CO
| | - Allen D. Radant
- Department of Psychiatry and Behavioral Sciences,
University of Washington, Seattle, WA; VA Puget Sound Health Care System, Seattle,
WA
| | - Larry J. Seidman
- Department of Psychiatry, Harvard Medical School, Boston,
MA; Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel
Deaconess Medical Center, Boston, MA
| | - Larry J. Siever
- Department of Psychiatry, The Mount Sinai School of
Medicine, New York, NY; 13James J. Peters VA Medical Center, New York, NY
| | - Jeremy M. Silverman
- Department of Psychiatry, The Mount Sinai School of
Medicine, New York, NY; 13James J. Peters VA Medical Center, New York, NY
| | - Joyce Sprock
- Department of Psychiatry, University of California San
Diego, La Jolla, CA; VISN-22 Mental Illness, Research, Education and Clinical Center
(MIRECC), VA San Diego Healthcare System
| | - William S. Stone
- Department of Psychiatry, Harvard Medical School, Boston,
MA; Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel
Deaconess Medical Center, Boston, MA
| | - Catherine A. Sugar
- Department of Biostatistics, University of California Los
Angeles School of Public Health, Los Angeles, CA
| | - Neal R. Swerdlow
- Department of Psychiatry, University of California San
Diego, La Jolla, CA; VISN-22 Mental Illness, Research, Education and Clinical Center
(MIRECC), VA San Diego Healthcare System
| | - Debby W. Tsuang
- Department of Psychiatry and Behavioral Sciences,
University of Washington, Seattle, WA; VA Puget Sound Health Care System, Seattle,
WA
| | - Ming T. Tsuang
- Department of Psychiatry, University of California San
Diego, La Jolla, CA; VISN-22 Mental Illness, Research, Education and Clinical Center
(MIRECC), VA San Diego Healthcare System
| | - Bruce I. Turetsky
- Department of Psychiatry, University of Pennsylvania,
Philadelphia, PA
| | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania,
Philadelphia, PA
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26
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Light GA, Swerdlow NR. Future clinical uses of neurophysiological biomarkers to predict and monitor treatment response for schizophrenia. Ann N Y Acad Sci 2015; 1344:105-19. [PMID: 25752648 DOI: 10.1111/nyas.12730] [Citation(s) in RCA: 109] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Advances in psychiatric neuroscience have transformed our understanding of impaired and spared brain functions in psychotic illnesses. Despite substantial progress, few (if any) laboratory tests have graduated to clinics to inform diagnoses, guide treatments, and monitor treatment response. Providers must rely on careful behavioral observation and interview techniques to make inferences about patients' inner experiences and then secondary deductions about impacted neural systems. Development of more effective treatments has also been hindered by a lack of translational quantitative biomarkers that can span the brain-behavior treatment knowledge gap. Here, we describe an example of a simple, low-cost, and translatable electroencephalography (EEG) measure that offers promise for improving our understanding and treatment of psychotic illnesses: mismatch negativity (MMN). MMN is sensitive to and/or predicts response to some pharmacologic and nonpharmacologic interventions and accounts for substantial portions of variance in clinical, cognitive, and psychosocial functioning in schizophrenia (SZ). This measure has recently been validated for use in large-scale multisite clinical studies of SZ. Finally, MMN greatly improves our ability to forecast which individuals at high clinical risk actually develop a psychotic illness. These attributes suggest that MMN can contribute to personalized biomarker-guided treatment strategies aimed at ameliorating or even preventing the onset of psychosis.
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Affiliation(s)
- Gregory A Light
- VISN 22 Mental Illness, Research, Education, and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, California; Department of Psychiatry, University of California San Diego, La Jolla, California
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