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Li S, Hu R, Yan H, Chu L, Qiu Y, Gao Y, Li M, Li J. 40-Hz auditory steady-state response deficits are correlated with the severity of persistent auditory verbal hallucination in patients with schizophrenia. Psychiatry Res Neuroimaging 2023; 336:111748. [PMID: 37984158 DOI: 10.1016/j.pscychresns.2023.111748] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 09/04/2023] [Accepted: 11/05/2023] [Indexed: 11/22/2023]
Abstract
BACKGROUND Abnormal 40 Hz auditory steady-state response (ASSR) has been observed in some psychiatric disorders. Nevertheless, the role of 40 Hz ASSR in persistent auditory verbal hallucinations (pAVHs) schizophrenia (SCZ) is still unknown. This study aims to investigate whether the 40 Hz ASSR impairment is related to pAVHs and can detect pAVHs severity. METHODS We analyzed high-density electroencephalography data that from 43 pAVHs patients (pAVH group), 20 moderate auditory verbal hallucinations patients (mid-AVH group), and 24 without auditory verbal hallucinations patients (non-AVH group). Event-related spectral perturbation and inter-trial phase coherence (ITPC) were calculated to quantify dynamic changes of the 40 Hz ASSR power and ITPC, respectively. RESULTS Frontal-central, the 40 Hz ASSR power, and ITPC were significantly lower in the pAVH group than in the non-AVH group; There was no significant difference between the pAVH and mid-AVH group. The 40 Hz ASSR was significantly negatively correlated with the severity of pAVHs. The 40 Hz ASSR power, and ITPC could be used as a combinational marker to detect SCZ patients with and without pAVHs. CONCLUSION Our findings have shed light on the pathological mechanism of pAVHs in SCZ patients. These results can provide potential avenues for therapeutic intervention of pAVHs.
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Affiliation(s)
- Shaobing Li
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Road, Hexi District, Tianjin, 300222, China
| | - Ruxin Hu
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Road, Hexi District, Tianjin, 300222, China
| | - Huiming Yan
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Road, Hexi District, Tianjin, 300222, China
| | - Lijun Chu
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Road, Hexi District, Tianjin, 300222, China
| | - Yuying Qiu
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Road, Hexi District, Tianjin, 300222, China
| | - Ying Gao
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Road, Hexi District, Tianjin, 300222, China
| | - Meijuan Li
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Road, Hexi District, Tianjin, 300222, China
| | - Jie Li
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Road, Hexi District, Tianjin, 300222, China.
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Krčmář L, Jäger I, Boudriot E, Hanken K, Gabriel V, Melcher J, Klimas N, Dengl F, Schmoelz S, Pingen P, Campana M, Moussiopoulou J, Yakimov V, Ioannou G, Wichert S, DeJonge S, Zill P, Papazov B, de Almeida V, Galinski S, Gabellini N, Hasanaj G, Mortazavi M, Karali T, Hisch A, Kallweit MS, Meisinger VJ, Löhrs L, Neumeier K, Behrens S, Karch S, Schworm B, Kern C, Priglinger S, Malchow B, Steiner J, Hasan A, Padberg F, Pogarell O, Falkai P, Schmitt A, Wagner E, Keeser D, Raabe FJ. The multimodal Munich Clinical Deep Phenotyping study to bridge the translational gap in severe mental illness treatment research. Front Psychiatry 2023; 14:1179811. [PMID: 37215661 PMCID: PMC10196006 DOI: 10.3389/fpsyt.2023.1179811] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Accepted: 04/14/2023] [Indexed: 05/24/2023] Open
Abstract
Introduction Treatment of severe mental illness (SMI) symptoms, especially negative symptoms and cognitive dysfunction in schizophrenia, remains a major unmet need. There is good evidence that SMIs have a strong genetic background and are characterized by multiple biological alterations, including disturbed brain circuits and connectivity, dysregulated neuronal excitation-inhibition, disturbed dopaminergic and glutamatergic pathways, and partially dysregulated inflammatory processes. The ways in which the dysregulated signaling pathways are interconnected remains largely unknown, in part because well-characterized clinical studies on comprehensive biomaterial are lacking. Furthermore, the development of drugs to treat SMIs such as schizophrenia is limited by the use of operationalized symptom-based clusters for diagnosis. Methods In line with the Research Domain Criteria initiative, the Clinical Deep Phenotyping (CDP) study is using a multimodal approach to reveal the neurobiological underpinnings of clinically relevant schizophrenia subgroups by performing broad transdiagnostic clinical characterization with standardized neurocognitive assessments, multimodal neuroimaging, electrophysiological assessments, retinal investigations, and omics-based analyzes of blood and cerebrospinal fluid. Moreover, to bridge the translational gap in biological psychiatry the study includes in vitro investigations on human-induced pluripotent stem cells, which are available from a subset of participants. Results Here, we report on the feasibility of this multimodal approach, which has been successfully initiated in the first participants in the CDP cohort; to date, the cohort comprises over 194 individuals with SMI and 187 age and gender matched healthy controls. In addition, we describe the applied research modalities and study objectives. Discussion The identification of cross-diagnostic and diagnosis-specific biotype-informed subgroups of patients and the translational dissection of those subgroups may help to pave the way toward precision medicine with artificial intelligence-supported tailored interventions and treatment. This aim is particularly important in psychiatry, a field where innovation is urgently needed because specific symptom domains, such as negative symptoms and cognitive dysfunction, and treatment-resistant symptoms in general are still difficult to treat.
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Affiliation(s)
- Lenka Krčmář
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, Germany
| | - Iris Jäger
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Emanuel Boudriot
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Katharina Hanken
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Vanessa Gabriel
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Julian Melcher
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Nicole Klimas
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Fanny Dengl
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Susanne Schmoelz
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Pauline Pingen
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Mattia Campana
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Joanna Moussiopoulou
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Vladislav Yakimov
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Georgios Ioannou
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Sven Wichert
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Silvia DeJonge
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Peter Zill
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Boris Papazov
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Valéria de Almeida
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Sabrina Galinski
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Nadja Gabellini
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Genc Hasanaj
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Matin Mortazavi
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Temmuz Karali
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Alexandra Hisch
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Marcel S Kallweit
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Verena J. Meisinger
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Lisa Löhrs
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Karin Neumeier
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Stephanie Behrens
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Susanne Karch
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Benedikt Schworm
- Department of Ophthalmology, University Hospital, LMU Munich, Munich, Germany
| | - Christoph Kern
- Department of Ophthalmology, University Hospital, LMU Munich, Munich, Germany
| | | | - Berend Malchow
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Johann Steiner
- Department of Psychiatry and Psychotherapy, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
- Laboratory of Translational Psychiatry, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
- Center for Health and Medical Prevention, Magdeburg, Germany
| | - Alkomiet Hasan
- Department of Psychiatry, Psychotherapy and Psychosomatics of the University Augsburg, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Frank Padberg
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Oliver Pogarell
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- Max Planck Institute of Psychiatry, Munich, Germany
| | - Andrea Schmitt
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- Laboratory of Neurosciences (LIM-27), Institute of Psychiatry, University of São Paulo, São Paulo, Brazil
| | - Elias Wagner
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Daniel Keeser
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- NeuroImaging Core Unit Munich, University Hospital, LMU Munich, Munich, Germany
- Munich Center for Neurosciences, LMU Munich, Munich, Germany
| | - Florian J. Raabe
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, Germany
- Max Planck Institute of Psychiatry, Munich, Germany
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Li S, Chan SY, Higgins A, Hall MH. Sensory gating, neurocognition, social cognition and real-life functioning: a 2-year follow-up of early psychosis. Psychol Med 2023; 53:2540-2552. [PMID: 37310299 DOI: 10.1017/s0033291721004463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Diminished sensory gating (SG) is a robust finding in psychotic disorders, but studies of early psychosis (EP) are rare. It is unknown whether SG deficit leads to poor neurocognitive, social, and/or real-world functioning. This study aimed to explore the longitudinal relationships between SG and these variables. METHODS Seventy-nine EP patients and 88 healthy controls (HCs) were recruited at baseline. Thirty-three and 20 EP patients completed 12-month and 24-month follow-up, respectively. SG was measured using the auditory dual-click (S1 & S2) paradigm and quantified as P50 ratio (S2/S1) and difference (S1-S2). Cognition, real-life functioning, and symptoms were assessed using the MATRICS Consensus Cognitive Battery, Global Functioning: Social (GFS) and Role (GFR), Multnomah Community Ability Scale (MCAS), Awareness of Social Inference Test (TASIT), and the Positive and Negative Syndrome Scale (PANSS). Analysis of variance (ANOVA), chi-square, mixed model, correlation and regression analyses were used for group comparisons and relationships among variables controlling for potential confounding variables. RESULTS In EP patients, P50 ratio (p < 0.05) and difference (p < 0.001) at 24-month showed significant differences compared with that at baseline. At baseline, P50 indices (ratio, S1-S2 difference, S1) were independently associated with GFR in HCs (all p < 0.05); in EP patients, S2 amplitude was independently associated with GFS (p = 0.037). At 12-month and 24-month, P50 indices (ratio, S1, S2) was independently associated with MCAS (all p < 0.05). S1-S2 difference was a trending predictor of future function (GFS or MCAS). CONCLUSIONS SG showed progressive reduction in EP patients. P50 indices were related to real-life functioning.
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Affiliation(s)
- Shen Li
- Schizophrenia and Bipolar Disorders Program, McLean Hospital, Harvard Medical School, Belmont, MA 02478, USA
- Psychosis Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA 02478, USA
- Department of Psychiatry, College of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Shi Yu Chan
- Schizophrenia and Bipolar Disorders Program, McLean Hospital, Harvard Medical School, Belmont, MA 02478, USA
- Psychosis Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA 02478, USA
- Translational Neurosciences, Singapore Institute for Clinical Sciences 117609, Singapore
| | - Amy Higgins
- Schizophrenia and Bipolar Disorders Program, McLean Hospital, Harvard Medical School, Belmont, MA 02478, USA
- Psychosis Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA 02478, USA
| | - Mei-Hua Hall
- Schizophrenia and Bipolar Disorders Program, McLean Hospital, Harvard Medical School, Belmont, MA 02478, USA
- Psychosis Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA 02478, USA
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Kozhemiako N, Wang J, Jiang C, Wang LA, Gai G, Zou K, Wang Z, Yu X, Zhou L, Li S, Guo Z, Law R, Coleman J, Mylonas D, Shen L, Wang G, Tan S, Qin S, Huang H, Murphy M, Stickgold R, Manoach D, Zhou Z, Zhu W, Hal MH, Purcell SM, Pan JQ. Non-rapid eye movement sleep and wake neurophysiology in schizophrenia. eLife 2022; 11:76211. [PMID: 35578829 PMCID: PMC9113745 DOI: 10.7554/elife.76211] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 04/11/2022] [Indexed: 12/29/2022] Open
Abstract
Motivated by the potential of objective neurophysiological markers to index thalamocortical function in patients with severe psychiatric illnesses, we comprehensively characterized key non-rapid eye movement (NREM) sleep parameters across multiple domains, their interdependencies, and their relationship to waking event-related potentials and symptom severity. In 72 schizophrenia (SCZ) patients and 58 controls, we confirmed a marked reduction in sleep spindle density in SCZ and extended these findings to show that fast and slow spindle properties were largely uncorrelated. We also describe a novel measure of slow oscillation and spindle interaction that was attenuated in SCZ. The main sleep findings were replicated in a demographically distinct sample, and a joint model, based on multiple NREM components, statistically predicted disease status in the replication cohort. Although also altered in patients, auditory event-related potentials elicited during wake were unrelated to NREM metrics. Consistent with a growing literature implicating thalamocortical dysfunction in SCZ, our characterization identifies independent NREM and wake EEG biomarkers that may index distinct aspects of SCZ pathophysiology and point to multiple neural mechanisms underlying disease heterogeneity. This study lays the groundwork for evaluating these neurophysiological markers, individually or in combination, to guide efforts at treatment and prevention as well as identifying individuals most likely to benefit from specific interventions.
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Affiliation(s)
- Nataliia Kozhemiako
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, United States
| | - Jun Wang
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, China
| | - Chenguang Jiang
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, China
| | - Lei A Wang
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, United States
| | - Guanchen Gai
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, China
| | - Kai Zou
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, China
| | - Zhe Wang
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, China
| | - Xiaoman Yu
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, China
| | - Lin Zhou
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, United States
| | - Shen Li
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, United States
| | - Zhenglin Guo
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, United States
| | - Robert Law
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, United States
| | - James Coleman
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, United States
| | - Dimitrios Mylonas
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, United States
| | - Lu Shen
- Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Guoqiang Wang
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, China
| | - Shuping Tan
- Huilong Guan Hospital, Beijing University, Beijing, China
| | - Shengying Qin
- Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Hailiang Huang
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, United States.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Harvard Medical School, Boston, United States
| | - Michael Murphy
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, United States
| | - Robert Stickgold
- Beth Israel Deaconess Medical Center, Boston, United States.,Department of Psychiatry, Harvard Medical School, Boston, United States
| | - Dara Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, United States
| | - Zhenhe Zhou
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, China
| | - Wei Zhu
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, China
| | - Mei-Hua Hal
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, United States
| | - Shaun M Purcell
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, United States.,Department of Psychiatry, Harvard Medical School, Boston, United States
| | - Jen Q Pan
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, United States
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5
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Smoking as a Common Modulator of Sensory Gating and Reward Learning in Individuals with Psychotic Disorders. Brain Sci 2021; 11:brainsci11121581. [PMID: 34942883 PMCID: PMC8699526 DOI: 10.3390/brainsci11121581] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2021] [Revised: 11/23/2021] [Accepted: 11/26/2021] [Indexed: 02/07/2023] Open
Abstract
Motivational and perceptual disturbances co-occur in psychosis and have been linked to aberrations in reward learning and sensory gating, respectively. Although traditionally studied independently, when viewed through a predictive coding framework, these processes can both be linked to dysfunction in striatal dopaminergic prediction error signaling. This study examined whether reward learning and sensory gating are correlated in individuals with psychotic disorders, and whether nicotine—a psychostimulant that amplifies phasic striatal dopamine firing—is a common modulator of these two processes. We recruited 183 patients with psychotic disorders (79 schizophrenia, 104 psychotic bipolar disorder) and 129 controls and assessed reward learning (behavioral probabilistic reward task), sensory gating (P50 event-related potential), and smoking history. Reward learning and sensory gating were correlated across the sample. Smoking influenced reward learning and sensory gating in both patient groups; however, the effects were in opposite directions. Specifically, smoking was associated with improved performance in individuals with schizophrenia but impaired performance in individuals with psychotic bipolar disorder. These findings suggest that reward learning and sensory gating are linked and modulated by smoking. However, disorder-specific associations with smoking suggest that nicotine may expose pathophysiological differences in the architecture and function of prediction error circuitry in these overlapping yet distinct psychotic disorders.
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Hederih J, Nuninga JO, van Eijk K, van Dellen E, Smit DJA, Oranje B, Luykx JJ. Genetic underpinnings of schizophrenia-related electroencephalographical intermediate phenotypes: A systematic review and meta-analysis. Prog Neuropsychopharmacol Biol Psychiatry 2021; 104:110001. [PMID: 32525059 DOI: 10.1016/j.pnpbp.2020.110001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Revised: 06/02/2020] [Accepted: 06/03/2020] [Indexed: 02/04/2023]
Abstract
Although substantial research into genetics of psychotic disorders has been conducted, a large proportion of their genetic architecture has remained unresolved. Electroencephalographical intermediate phenotypes (EIP) have the potential to constitute a valuable tool when studying genetic risk loci for schizophrenia, in particular P3b amplitude, P50 suppression, mismatch negativity (MMN) and resting state power spectra of the electroencephalogram (EEG). Here, we systematically reviewed studies investigating the association of single nucleotide polymorphisms (SNPs) with these EIPs and meta-analysed them when appropriate. We retrieved 45 studies (N = 34,971 study participants). Four SNPs investigated in more than one study were genome-wide significant for an association with schizophrenia and three were genome-wide suggestive, based on a lookup in the influential 2014 GWAS (Ripke et al., 2014). However, in our meta-analyses, rs1625579 failed to reach a statistically significant association with p3b amplitude decrease and rs4680 risk allele carrier status was not associated with p3b amplitude decrease or with impaired p50 suppression. In conclusion, evidence for SNP associations with EIPs remains limited to individual studies. Careful selection of EIPs and SNPs, combined with consistent reporting of effect sizes, directions of effect and p-values would aid future meta-analyses.
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Affiliation(s)
- Jure Hederih
- Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, CX 3584, the Netherlands; Medical Sciences Division, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DU, United Kingdom.
| | - Jasper O Nuninga
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, CX 3584, the Netherlands
| | - Kristel van Eijk
- Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, CX 3584, the Netherlands
| | - Edwin van Dellen
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, CX 3584, the Netherlands; Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Dirk J A Smit
- Department of Psychiatry, Academic Medical Centre, Meibergdreef 5, Amsterdam 1105 AZ, the Netherlands
| | - Bob Oranje
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, CX 3584, the Netherlands
| | - Jurjen J Luykx
- Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, CX 3584, the Netherlands; Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, CX 3584, the Netherlands; GGNet Mental Health, Apeldoorn, the Netherlands
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7
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Rovný R, Besterciová D, Riečanský I. Genetic Determinants of Gating Functions: Do We Get Closer to Understanding Schizophrenia Etiopathogenesis? Front Psychiatry 2020; 11:550225. [PMID: 33324248 PMCID: PMC7723973 DOI: 10.3389/fpsyt.2020.550225] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Accepted: 10/12/2020] [Indexed: 11/13/2022] Open
Abstract
Deficits in the gating of sensory stimuli, i.e., the ability to suppress the processing of irrelevant sensory input, are considered to play an important role in the pathogenesis of several neuropsychiatric disorders, in particular schizophrenia. Gating is disrupted both in schizophrenia patients and their unaffected relatives, suggesting that gating deficit may represent a biomarker associated with a genetic liability to the disorder. To assess the strength of the evidence for the etiopathogenetic links between genetic variation, gating efficiency, and schizophrenia, we carried out a systematic review of human genetic association studies of sensory gating (suppression of the P50 component of the auditory event-related brain potential) and sensorimotor gating (prepulse inhibition of the acoustic startle response). Sixty-three full-text articles met the eligibility criteria for inclusion in the review. In total, 117 genetic variants were reported to be associated with gating functions: 33 variants for sensory gating, 80 variants for sensorimotor gating, and four variants for both sensory and sensorimotor gating. However, only five of these associations (four for prepulse inhibition-CHRNA3 rs1317286, COMT rs4680, HTR2A rs6311, and TCF4 rs9960767, and one for P50 suppression-CHRNA7 rs67158670) were consistently replicated in independent samples. Although these variants and genes were all implicated in schizophrenia in research studies, only two polymorphisms (HTR2A rs6311 and TCF4 rs9960767) were also reported to be associated with schizophrenia at a meta-analytic or genome-wide level of evidence. Thus, although gating is widely considered as an important endophenotype of schizophrenia, these findings demonstrate that evidence for a common genetic etiology of impaired gating functions and schizophrenia is yet unsatisfactory, warranting further studies in this field.
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Affiliation(s)
- Rastislav Rovný
- Department of Behavioural Neuroscience, Institute of Normal and Pathological Physiology, Centre of Experimental Medicine, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Dominika Besterciová
- Department of Behavioural Neuroscience, Institute of Normal and Pathological Physiology, Centre of Experimental Medicine, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Igor Riečanský
- Department of Behavioural Neuroscience, Institute of Normal and Pathological Physiology, Centre of Experimental Medicine, Slovak Academy of Sciences, Bratislava, Slovakia
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
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Eser HY, Appadurai V, Eren CY, Yazici D, Chen CY, Ongur D, Pizzagalli DA, Werge T, Hall MH. Association between GLP-1 receptor gene polymorphisms with reward learning, anhedonia and depression diagnosis. Acta Neuropsychiatr 2020; 32:218-225. [PMID: 32213216 PMCID: PMC7351594 DOI: 10.1017/neu.2020.14] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
BACKGROUND Glucagon-like peptide-1 receptors (GLP-1Rs) are widely expressed in the brain. Evidence suggests that they may play a role in reward responses and neuroprotection. However, the association of GLP-1R with anhedonia and depression diagnosis has not been studied. Here, we examined the association of GLP-1R polymorphisms with objective and subjective measures of anhedonia, as well as depression diagnosis. METHODS Objective [response bias assessed by the probabilistic reward task (PRT)] and subjective [Snaith-Hamilton Pleasure Scale (SHAPS)] measures of anhedonia, clinical variables and DNA samples were collected from 100 controls and 164 patients at McLean Hospital. An independent sample genotyped as part of the Psychiatric Genomics Consortium (PGC) was used to study the effect of putative GLP-1R polymorphisms linked to response bias in PRT on depression diagnosis. RESULTS The C allele in rs1042044 was significantly associated with increased PRT response bias, when controlling for age, sex, case-control status and PRT discriminability. AA genotype of rs1042044 showed higher anhedonia phenotype based on SHAPS scores. However, analysis of PGC major depressive disorder data showed no association between rs1042044 and depression diagnosis. CONCLUSION Findings suggest a possible association of rs1042044 with anhedonia but no association with depression diagnosis.
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Affiliation(s)
- Hale Yapici Eser
- Koç University, School of Medicine, İstanbul, Turkey
- Koç University, Research Center for Translational Medicine, İstanbul, Turkey
| | - Vivek Appadurai
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Institute of Biological Psychiatry, Mental Health Center St. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
| | - Candan Yasemin Eren
- Koç University, Research Center for Translational Medicine, İstanbul, Turkey
| | - Dilek Yazici
- Koç University, School of Medicine, İstanbul, Turkey
| | - Chia-Yen Chen
- Psychiatric and Neurodevelopmental Genetics Unit and Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Dost Ongur
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Schizophrenia and Bipolar Disorder Research Program, McLean Hospital, Belmont, MA, USA
| | - Diego A. Pizzagalli
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Thomas Werge
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Institute of Biological Psychiatry, Mental Health Center St. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Mei-Hua Hall
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Schizophrenia and Bipolar Disorder Research Program, McLean Hospital, Belmont, MA, USA
- Psychosis Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA, USA
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9
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Atagun MI, Drukker M, Hall MH, Altun IK, Tatli SZ, Guloksuz S, van Os J, van Amelsvoort T. Meta-analysis of auditory P50 sensory gating in schizophrenia and bipolar disorder. Psychiatry Res Neuroimaging 2020; 300:111078. [PMID: 32361172 DOI: 10.1016/j.pscychresns.2020.111078] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 03/16/2020] [Accepted: 03/19/2020] [Indexed: 11/15/2022]
Abstract
The ability of the brain to reduce the amount of trivial or redundant sensory inputs is called gating function. Dysfunction of sensory gating may lead to cognitive fragmentation and poor real-world functioning. The auditory dual-click paradigm is a pertinent neurophysiological measure of sensory gating function. This meta-analysis aimed to examine the subcomponents of abnormal P50 waveforms in bipolar disorder and schizophrenia to assess P50 sensory gating deficits and examine effects of diagnoses, illness states (first-episode psychosis vs. schizophrenia, remission vs. episodes in bipolar disorder), and treatment status (medication-free vs. medicated). Literature search of PubMed between Jan 1st 1980 and March 31st 2019 identified 2091 records for schizophrenia, 362 for bipolar disorder. 115 studies in schizophrenia (4932 patients), 16 in bipolar disorder (975 patients) and 10 in first-degree relatives (848 subjects) met the inclusion criteria. P50 sensory gating ratio (S2/S1) and S1-S2 difference were significantly altered in schizophrenia, bipolar disorder and their first-degree relatives. First-episode psychosis did not differ from schizophrenia, however episodes altered P50 sensory gating in bipolar disorder. Medications improve P50 sensory gating alterations in schizophrenia significantly and at trend level in bipolar disorder. Future studies should examine longitudinal course of P50 sensory gating in schizophrenia and bipolar disorder.
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Affiliation(s)
- Murat Ilhan Atagun
- Department of Psychiatry, Ankara Yildirim Beyazit University Medical School, Universities Region, Ihsan Dogramaci Boulevard. No: 6, Bilkent, Cankaya, Ankara Turkey.
| | - Marjan Drukker
- Department of Psychiatry and Neuropsychology, Maastricht University School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht, the Netherlands
| | - Mei Hua Hall
- Psychosis Neurobiology Laboratory, Harvard Medical School, McLean Hospital, Belmont, Massachusetts, USA
| | - Ilkay Keles Altun
- Department of Psychiatry, Bursa Higher Education Training and Education Hospital, Bursa, Turkey
| | | | - Sinan Guloksuz
- Department of Psychiatry and Neuropsychology, Maastricht University School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht, the Netherlands; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Jim van Os
- Department of Psychiatry and Neuropsychology, Maastricht University School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht, the Netherlands; King's Health Partners Department of Psychosis Studies, King's College London, Institute of Psychiatry, London, United Kingdom; Department of Psychiatry, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht, the Netherlands
| | - Thérèse van Amelsvoort
- Department of Psychiatry and Neuropsychology, Maastricht University School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht, the Netherlands
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10
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Raabe FJ, Slapakova L, Rossner MJ, Cantuti-Castelvetri L, Simons M, Falkai PG, Schmitt A. Oligodendrocytes as A New Therapeutic Target in Schizophrenia: From Histopathological Findings to Neuron-Oligodendrocyte Interaction. Cells 2019; 8:cells8121496. [PMID: 31771166 PMCID: PMC6952785 DOI: 10.3390/cells8121496] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 11/20/2019] [Accepted: 11/21/2019] [Indexed: 12/11/2022] Open
Abstract
Imaging and postmortem studies have revealed disturbed oligodendroglia-related processes in patients with schizophrenia and provided much evidence for disturbed myelination, irregular gene expression, and altered numbers of oligodendrocytes in the brains of schizophrenia patients. Oligodendrocyte deficits in schizophrenia might be a result of failed maturation and disturbed regeneration and may underlie the cognitive deficits of the disease, which are strongly associated with impaired long-term outcome. Cognition depends on the coordinated activity of neurons and interneurons and intact connectivity. Oligodendrocyte precursors form a synaptic network with parvalbuminergic interneurons, and disturbed crosstalk between these cells may be a cellular basis of pathology in schizophrenia. However, very little is known about the exact axon-glial cellular and molecular processes that may be disturbed in schizophrenia. Until now, investigations were restricted to peripheral tissues, such as blood, correlative imaging studies, genetics, and molecular and histological analyses of postmortem brain samples. The advent of human-induced pluripotent stem cells (hiPSCs) will enable functional analysis in patient-derived living cells and holds great potential for understanding the molecular mechanisms of disturbed oligodendroglial function in schizophrenia. Targeting such mechanisms may contribute to new treatment strategies for previously treatment-resistant cognitive symptoms.
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Affiliation(s)
- Florian J. Raabe
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstrasse 7, 80336 Munich, Germany; (F.J.R.); (L.S.); (P.G.F.)
- International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Kraepelinstr, 2-10, 80804 Munich, Germany
- Molecular and Behavioural Neurobiology, Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, 80336 Munich, Germany;
| | - Lenka Slapakova
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstrasse 7, 80336 Munich, Germany; (F.J.R.); (L.S.); (P.G.F.)
- International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Kraepelinstr, 2-10, 80804 Munich, Germany
| | - Moritz J. Rossner
- Molecular and Behavioural Neurobiology, Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, 80336 Munich, Germany;
| | - Ludovico Cantuti-Castelvetri
- German Center for Neurodegenerative Diseases (DZNE), Feodor-Lynen Str. 17, 81377 Munich, Germany; (L.C.-C.); (M.S.)
| | - Mikael Simons
- German Center for Neurodegenerative Diseases (DZNE), Feodor-Lynen Str. 17, 81377 Munich, Germany; (L.C.-C.); (M.S.)
- Munich Cluster for Systems Neurology (SyNergy), 81377 Munich, Germany
- Institute of Neuronal Cell Biology, Technical University Munich, 80805 Munich, Germany
| | - Peter G. Falkai
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstrasse 7, 80336 Munich, Germany; (F.J.R.); (L.S.); (P.G.F.)
| | - Andrea Schmitt
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstrasse 7, 80336 Munich, Germany; (F.J.R.); (L.S.); (P.G.F.)
- Molecular and Behavioural Neurobiology, Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, 80336 Munich, Germany;
- Laboratory of Neuroscience (LIM27), Institute of Psychiatry, University of Sao Paulo, 05453-010 São Paulo, Brazil
- Correspondence: ; Tel.: +49-(0)89-4400-52761; Fax: +49-(0)89-4400-55530
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11
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Wada M, Kurose S, Miyazaki T, Nakajima S, Masuda F, Mimura Y, Nishida H, Ogyu K, Tsugawa S, Mashima Y, Plitman E, Chakravarty MM, Mimura M, Noda Y. The P300 event-related potential in bipolar disorder: A systematic review and meta-analysis. J Affect Disord 2019; 256:234-249. [PMID: 31200163 DOI: 10.1016/j.jad.2019.06.010] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Revised: 04/21/2019] [Accepted: 06/03/2019] [Indexed: 01/09/2023]
Abstract
BACKGROUND Neurophysiology including P300, that is a typical index of event-related potential, may be potential biomarkers for bipolar disorder (BD) and it can be useful towards elucidating the pathophysiology of BD. However, previous findings from P300 studies were inconsistent due to the heterogeneity of research methods, which make it difficult to understand the neurobiological significance of them. The aim of this study is to conduct a meta-analysis on P300 in patients with BD. METHOD A literature search was conducted using PubMed to identify studies that compared P300 event-related potential between patients with BD and healthy controls (HCs). We analyzed P300 indices such as amplitude and latency of P3a and P3b in auditory or visual paradigms. Further, moderator analyses were conducted to investigate the influence of patient characteristics (i.e. history of psychosis, diagnostic subcategories [BD-I/BD-II], and phase of illness [euthymic, manic, or depressive]) on P300 indices. RESULT Out of 124 initial records, we included 30 articles (BD: N = 1331; HCs: N = 1818). Patients with BD showed reduced P3a and P3b amplitude in both paradigms and delayed P3b latency in auditory paradigms compared to HCs. There was no influence on the history of psychosis, diagnostic subcategories, or phase of illness on P300 indices. LIMITATION The difference in medication use was difficult to control and it may affect the results. CONCLUSION This meta-analysis provides evidence for P300 abnormalities in patients with BD compared to HCs. Our results suggest that P300 may be trait markers rather than state markers in this illness.
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Affiliation(s)
- Masataka Wada
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, Japan
| | - Shin Kurose
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, Japan
| | - Takahiro Miyazaki
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, Japan
| | - Shinichiro Nakajima
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, Japan
| | - Fumi Masuda
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, Japan
| | - Yu Mimura
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, Japan
| | - Hana Nishida
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, Japan
| | - Kamiyu Ogyu
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, Japan
| | - Sakiko Tsugawa
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, Japan
| | - Yuuki Mashima
- Center Hospital of the National Center for Global Health and Medicine, Japan
| | - Eric Plitman
- Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada; Department of Psychiatry, McGill University Biological and Biomedical Engineering, McGill University, Canada
| | - Masaru Mimura
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, Japan
| | - Yoshihiro Noda
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, Japan.
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12
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Hall MH, Holton KM, Öngür D, Montrose D, Keshavan MS. Longitudinal trajectory of early functional recovery in patients with first episode psychosis. Schizophr Res 2019; 209:234-244. [PMID: 30826261 PMCID: PMC7003957 DOI: 10.1016/j.schres.2019.02.003] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Revised: 01/11/2019] [Accepted: 02/05/2019] [Indexed: 10/27/2022]
Abstract
BACKGROUND There is a large variability in the recovery trajectory and outcome of first episode of psychosis [FEP] patients. To date, individuals' outcome trajectories at early stage of illness and potential risk factors associated with a poor outcome trajectory are largely unknown. This study aims to apply three separate predictors (positive symptoms, negative symptoms, and soft neurological signs) to identify homogeneous function outcome trajectories in patients with FEP using objective data-driven methods, and to explore the potential risk /protective factors associated with each trajectory. METHODS A total of 369 first episode patients (93% antipsychotic naive) were included in the baseline assessments and followed-up at 4-8 weeks, 6 months, and 1 year. K means cluster modeling for longitudinal data (kml3d) was used to identify distinct, homogeneous clusters of functional outcome trajectories. Patients with at least 3 assessments were included in the trajectory analyses (N = 129). The Scale for the Assessment of Negative Symptoms (SANS), Scale for the Assessment of Positive Symptoms (SAPS), and Neurological examination abnormalities (NEA) were used as predictors against Global Assessment of Functioning Scale (GAF). RESULTS In each of the three predictor models, four distinct functional outcome trajectories emerged: "Poor", "Intermediate", High" and "Catch-up". Individuals with male gender; ethnic minority status; low premorbid adjustment; low executive function/IQ, low SES, personality disorder, substance use history may be risk factors for poor recovery. CONCLUSIONS Functioning recovery in individuals with FEP is heterogeneous, although distinct recovery profiles are apparent. Data-driven trajectory analysis can facilitate better characterization of individual longitudinal patterns of functioning recovery.
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Affiliation(s)
- Mei-Hua Hall
- Psychotic Disorders Division, McLean Hospital HMS, Boston, MA, USA.
| | | | - Dost Öngür
- Psychotic Disorders Division, McLean Hospital HMS, Boston, MA, USA
| | - Debra Montrose
- Western Psychiatric Institute and Clinic, University of Pittsburgh School of Medicine, Department of Psychiatry, Pittsburgh, PA, USA
| | - Matcheri S Keshavan
- Western Psychiatric Institute and Clinic, University of Pittsburgh School of Medicine, Department of Psychiatry, Pittsburgh, PA, USA; Beth Israel Deaconess Medical Center and Massachusetts Mental Health Center, HMS, Boston, MA, USA
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13
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Zhou TH, Mueller NE, Spencer KM, Mallya SG, Lewandowski KE, Norris LA, Levy DL, Cohen BM, Öngür D, Hall MH. Auditory steady state response deficits are associated with symptom severity and poor functioning in patients with psychotic disorder. Schizophr Res 2018; 201:278-286. [PMID: 29807805 PMCID: PMC7003536 DOI: 10.1016/j.schres.2018.05.027] [Citation(s) in RCA: 52] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2017] [Revised: 05/14/2018] [Accepted: 05/14/2018] [Indexed: 01/15/2023]
Abstract
OBJECTIVES Gamma oscillation is important for cortico-cortical coordination and the integration of information across neural networks. The 40 Hz auditory steady-state response (ASSR), which reflects neural synchrony in the gamma band (30-100 Hz), is abnormal in patients with schizophrenia (SZ). The present study used the ASSR at multiple frequencies to examine (1) gamma dysfunction in patients with SZ, schizoaffective (SA), and bipolar disorder (BD) compared with controls, (2) the relationship between ASSR measures and clinical symptom severity, and (3) the relationship between ASSR measures and real-life community functioning. METHODS EEG was recorded from 75 controls, 52 SZ, 55 SA, and 89 BD patients during 20-30-40-Hz binaural click trains. ANCOVA was used to compare ASSR measures between groups controlling for age, sex, and education. Associations between ASSR measures, symptom severity, and community functioning were examined using linear regression and Pearson partial correlations. RESULTS ASSR deficits at gamma frequency were observed in all patient groups. SA patients showed additional specific deficit in the 20 Hz ASSR. Severity of manic, depressive, and anxiety symptoms mediated ASSR deficits. Severity of hallucinatory symptom and community functioning, particularly independent living/meaningful activity, were significantly and independently associated with the 40 Hz ASSR. CONCLUSIONS SZ, SA and BD patients are likely to share the same abnormalities in neural processes that generate gamma oscillations. 40 Hz ASSR are associated with community functioning across patients and may serve as a biomarker for predicting functional outcome.
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Affiliation(s)
- Tian-Hang Zhou
- Schizophrenia and Bipolar Disorders Program, McLean Hospital, Harvard Medical School, Belmont, USA,Department of Global Health and Social Medicine, Harvard Medical School, Boston, USA
| | - Nora E. Mueller
- Schizophrenia and Bipolar Disorders Program, McLean Hospital, Harvard Medical School, Belmont, USA,Department of Psychology, Florida State University, Tallahassee, FL, USA
| | - Kevin M. Spencer
- Veterans Affairs Boston Healthcare System, Harvard Medical School, Jamaica Plain, USA
| | - Sonal G. Mallya
- Schizophrenia and Bipolar Disorders Program, McLean Hospital, Harvard Medical School, Belmont, USA
| | - Kathryn Eve Lewandowski
- Schizophrenia and Bipolar Disorders Program, McLean Hospital, Harvard Medical School, Belmont, USA
| | - Lesley A. Norris
- Schizophrenia and Bipolar Disorders Program, McLean Hospital, Harvard Medical School, Belmont, USA
| | - Deborah L. Levy
- Psychology Research Laboratory, McLean Hospital, Harvard Medical School, Belmont, USA
| | - Bruce M. Cohen
- Program for Neuropsychiatric Research, McLean Hospital, Harvard Medical School, Belmont, USA
| | - Dost Öngür
- Schizophrenia and Bipolar Disorders Program, McLean Hospital, Harvard Medical School, Belmont, USA
| | - Mei-Hua Hall
- Schizophrenia and Bipolar Disorders Program, McLean Hospital, Harvard Medical School, Belmont, USA; Psychosis Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, USA.
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14
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Mistry S, Harrison JR, Smith DJ, Escott-Price V, Zammit S. The use of polygenic risk scores to identify phenotypes associated with genetic risk of bipolar disorder and depression: A systematic review. J Affect Disord 2018. [PMID: 29529547 DOI: 10.1016/j.jad.2018.02.005] [Citation(s) in RCA: 76] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
BACKGROUND Identifying the phenotypic manifestations of increased genetic liability for depression (MDD) and bipolar disorder (BD) can enhance understanding of their aetiology. The polygenic risk score (PRS) derived using data from genome-wide-association-studies can be used to explore how genetic risk is manifest in different samples. AIMS In this systematic review, we review studies that examine associations between the MDD and BD polygenic risk scores and phenotypic outcomes. METHODS Following PRISMA guidelines, we searched EMBASE, Medline and PsycINFO (from August 2009 - 14th March 2016) and references of included studies. Study inclusion was based on predetermined criteria and data were extracted independently and in duplicate. RESULTS Twenty-five studies were included. Overall, both polygenic risk scores were associated with other psychiatric disorders (not the discovery sample disorder) such as depression, schizophrenia and bipolar disorder, greater symptom severity of depression, membership of a creative profession and greater educational attainment. Both depression and bipolar polygenic risk scores explained small amounts of variance in most phenotypes (< 2%). LIMITATIONS Many studies did not report standardised effect sizes. This prevented us from conducting a meta-analysis. CONCLUSIONS Polygenic risk scores for BD and MDD are associated with a range of phenotypes and outcomes. However, they only explain a small amount of the variation in these phenotypes. Larger discovery and adequately powered target samples are required to increase power of the PRS approach. This could elucidate how genetic risk for bipolar disorder and depression is manifest and contribute meaningfully to stratified medicine.
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Affiliation(s)
- Sumit Mistry
- Institute of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK.
| | - Judith R Harrison
- Institute of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK
| | - Daniel J Smith
- Institute of Health and Wellbeing, University of Glasgow, I Lilybank Gardens, UK
| | - Valentina Escott-Price
- Institute of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK
| | - Stanley Zammit
- Institute of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK; Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, UK
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15
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Mistry S, Harrison JR, Smith DJ, Escott-Price V, Zammit S. The use of polygenic risk scores to identify phenotypes associated with genetic risk of schizophrenia: Systematic review. Schizophr Res 2018; 197:2-8. [PMID: 29129507 DOI: 10.1016/j.schres.2017.10.037] [Citation(s) in RCA: 84] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2017] [Revised: 10/27/2017] [Accepted: 10/28/2017] [Indexed: 12/12/2022]
Abstract
Studying the phenotypic manifestations of increased genetic liability for schizophrenia can increase our understanding of this disorder. Specifically, information from alleles identified in genome-wide association studies can be collapsed into a polygenic risk score (PRS) to explore how genetic risk is manifest within different samples. In this systematic review, we provide a comprehensive assessment of studies examining associations between schizophrenia PRS (SZ-PRS) and several phenotypic measures. We searched EMBASE, Medline and PsycINFO (from August 2009-14th March 2016) plus references of included studies, following PRISMA guidelines. Study inclusion was based on predetermined criteria and data were extracted independently and in duplicate. Overall, SZ-PRS was associated with increased risk for psychiatric disorders such as depression and bipolar disorder, lower performance IQ and negative symptoms. SZ-PRS explained up to 6% of genetic variation in psychiatric phenotypes, compared to <0.7% in measures of cognition. Future gains from using the PRS approach may be greater if used for examining phenotypes that are more closely related to biological substrates, for scores based on gene-pathways, and where PRSs are used to stratify individuals for study of treatment response. As it was difficult to interpret findings across studies due to insufficient information provided by many studies, we propose a framework to guide robust reporting of PRS associations in the future.
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Affiliation(s)
- Sumit Mistry
- Institute of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK.
| | - Judith R Harrison
- Institute of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK
| | - Daniel J Smith
- Institute of Health and Wellbeing, 1 Lilybank Gardens, University of Glasgow, UK
| | - Valentina Escott-Price
- Institute of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK
| | - Stanley Zammit
- Institute of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK; Centre for Academic Mental Health, School of Social and Community Medicine, University of Bristol, UK
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16
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Grove TB, Yao B, Mueller SA, McLaughlin M, Ellingrod VL, McInnis MG, Taylor SF, Deldin PJ, Tso IF. A Bayesian model comparison approach to test the specificity of visual integration impairment in schizophrenia or psychosis. Psychiatry Res 2018; 265:271-278. [PMID: 29768190 PMCID: PMC6448399 DOI: 10.1016/j.psychres.2018.04.061] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2017] [Revised: 02/23/2018] [Accepted: 04/22/2018] [Indexed: 10/17/2022]
Abstract
Impaired visual integration is well documented in schizophrenia and related to functional outcomes. However, it is unclear if this deficit is specific to schizophrenia, or characteristic of psychosis more broadly. To address this question, this study used a Bayesian model comparison approach to examine the evidence of three grouping models of visual integration performance in 116 individuals with schizophrenia (SZ), schizoaffective disorder (SA), bipolar disorder (BD) with or without a history of prominent psychosis (BDP+ and BDP-, respectively), or no psychiatric diagnosis (healthy controls; HC). We compared: (1) Psychosis Model (psychosis, non-psychosis), where the psychosis group included SZ, SA, and BDP+, and the non-psychosis group included BDP- and HC; (2) Schizophrenia Model (SZ, non-SZ); and (3) DSM Model (SZ, SA, BD, HC). The relationship between visual integration and general cognition was also explored. The Psychosis Model showed the strongest evidence, and visual integration was associated with general cognition in participants with psychosis. The results were consistent with the Research Domain Criteria (RDoC) framework, indicating that visual integration impairment is characteristic of psychosis and not specific to SZ or DSM categories, and may share similar disease pathways with observed neurocognitive deficits in psychotic disorders.
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Affiliation(s)
- Tyler B. Grove
- Department of Psychology, University of Michigan, Ann Arbor, Michigan, USA,Correspondence concerning this article should be addressed to Tyler Grove, Department of Psychology, University of Michigan, 530 Church Street, Ann Arbor, Michigan 48109, USA. . Tel: 1-(734)-647-3872
| | - Beier Yao
- Department of Psychology, Michigan State University, East Lansing, Michigan, USA
| | - Savanna A. Mueller
- Department of Psychology, University of Michigan, Ann Arbor, Michigan, USA
| | | | - Vicki L. Ellingrod
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA,College of Pharmacy, University of Michigan, Ann Arbor, Michigan, USA
| | - Melvin G. McInnis
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
| | - Stephan F. Taylor
- Department of Psychology, University of Michigan, Ann Arbor, Michigan, USA,Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
| | - Patricia J. Deldin
- Department of Psychology, University of Michigan, Ann Arbor, Michigan, USA,Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
| | - Ivy F. Tso
- Department of Psychology, University of Michigan, Ann Arbor, Michigan, USA,Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
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Lin YF, Chen CY, Öngür D, Betensky R, Smoller JW, Blacker D, Hall MH. Polygenic pleiotropy and potential causal relationships between educational attainment, neurobiological profile, and positive psychotic symptoms. Transl Psychiatry 2018; 8:97. [PMID: 29765027 PMCID: PMC5954124 DOI: 10.1038/s41398-018-0144-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Revised: 01/30/2018] [Accepted: 04/03/2018] [Indexed: 11/23/2022] Open
Abstract
Event-related potential (ERP) components have been used to assess cognitive functions in patients with psychotic illness. Evidence suggests that among patients with psychosis there is a distinct heritable neurophysiologic phenotypic subtype captured by impairments across a range of ERP measures. In this study, we investigated the genetic basis of this "globally impaired" ERP cluster and its relationship to psychosis and cognitive abilities. We applied K-means clustering to six ERP measures to re-derive the globally impaired (n = 60) and the non-globally impaired ERP clusters (n = 323) in a sample of cases with schizophrenia (SCZ = 136) or bipolar disorder (BPD = 121) and healthy controls (n = 126). We used genome-wide association study (GWAS) results for SCZ, BPD, college completion, and childhood intelligence as the discovery datasets to derive polygenic risk scores (PRS) in our study sample and tested their associations with globally impaired ERP. We conducted mediation analyses to estimate the proportion of each PRS effect on severity of psychotic symptoms that is mediated through membership in the globally impaired ERP. Individuals with globally impaired ERP had significantly higher PANSS-positive scores (β = 3.95, P = 0.005). The SCZ-PRS was nominally associated with globally impaired ERP (unadjusted P = 0.01; R2 = 3.07%). We also found a significant positive association between the college-PRS and globally impaired ERP (FDR-corrected P = 0.004; R2 = 6.15%). The effect of college-PRS on PANSS positivity was almost entirely (97.1%) mediated through globally impaired ERP. These results suggest that the globally impaired ERP phenotype may represent some aspects of brain physiology on the path between genetic influences on educational attainment and psychotic symptoms.
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Affiliation(s)
- Yen-Feng Lin
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA. .,Department of Psychiatry, Taipei City Psychiatric Center, Taipei City Hospital, Taipei, Taiwan.
| | - Chia-Yen Chen
- 0000 0004 0386 9924grid.32224.35Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA USA ,grid.66859.34Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA USA ,000000041936754Xgrid.38142.3cDepartment of Psychiatry, Harvard Medical School, Boston, MA USA
| | - Dost Öngür
- 000000041936754Xgrid.38142.3cDepartment of Psychiatry, Harvard Medical School, Boston, MA USA ,0000 0000 8795 072Xgrid.240206.2Psychotic Disorders Division, McLean Hospital, Belmont, MA USA
| | - Rebecca Betensky
- 000000041936754Xgrid.38142.3cDepartment of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA USA
| | - Jordan W. Smoller
- 000000041936754Xgrid.38142.3cDepartment of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA USA ,0000 0004 0386 9924grid.32224.35Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA USA ,grid.66859.34Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA USA ,000000041936754Xgrid.38142.3cDepartment of Psychiatry, Harvard Medical School, Boston, MA USA
| | - Deborah Blacker
- 000000041936754Xgrid.38142.3cDepartment of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA USA ,000000041936754Xgrid.38142.3cDepartment of Psychiatry, Harvard Medical School, Boston, MA USA ,0000 0004 0386 9924grid.32224.35Gerontology Research Unit, Massachusetts General Hospital, Boston, MA USA
| | - Mei-Hua Hall
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA. .,Psychosis Neurobiology Laboratory, McLean Hospital, Belmont, MA, USA.
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18
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Bogdan R, Baranger DAA, Agrawal A. Polygenic Risk Scores in Clinical Psychology: Bridging Genomic Risk to Individual Differences. Annu Rev Clin Psychol 2018; 14:119-157. [PMID: 29579395 PMCID: PMC7772939 DOI: 10.1146/annurev-clinpsy-050817-084847] [Citation(s) in RCA: 87] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Genomewide association studies (GWASs) across psychiatric phenotypes have shown that common genetic variants generally confer risk with small effect sizes (odds ratio < 1.1) that additively contribute to polygenic risk. Summary statistics derived from large discovery GWASs can be used to generate polygenic risk scores (PRS) in independent, target data sets to examine correlates of polygenic disorder liability (e.g., does genetic liability to schizophrenia predict cognition?). The intuitive appeal and generalizability of PRS have led to their widespread use and new insights into mechanisms of polygenic liability. However, when currently applied across traits they account for small amounts of variance (<3%), are relatively uninformative for clinical treatment, and, in isolation, provide no insight into molecular mechanisms. Larger GWASs are needed to increase the precision of PRS, and novel approaches integrating various data sources (e.g., multitrait analysis of GWASs) may improve the utility of current PRS.
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Affiliation(s)
- Ryan Bogdan
- BRAINLab, Department of Psychological and Brain Sciences, and Division of Biology and Biomedical Sciences, Washington University in St. Louis, St. Louis, Missouri 63110, USA;
| | - David A A Baranger
- BRAINLab, Department of Psychological and Brain Sciences, and Division of Biology and Biomedical Sciences, Washington University in St. Louis, St. Louis, Missouri 63110, USA;
| | - Arpana Agrawal
- Department of Psychiatry, Washington University in St. Louis School of Medicine, St. Louis, Missouri 63110, USA
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19
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Chalmer MA, Esserlind AL, Olesen J, Hansen TF. Polygenic risk score: use in migraine research. J Headache Pain 2018; 19:29. [PMID: 29623444 PMCID: PMC5887014 DOI: 10.1186/s10194-018-0856-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2018] [Accepted: 03/21/2018] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND The latest Genome-Wide Association Study identified 38 genetic variants associated with migraine. In this type of studies the significance level is very difficult to achieve (5 × 10- 8) due to multiple testing. Thus, the identified variants only explain a small fraction of the genetic risk. It is expected that hundreds of thousands of variants also confer an increased risk but do not reach significance levels. One way to capture this information is by constructing a Polygenic Risk Score. Polygenic Risk Score has been widely used with success in genetics studies within neuropsychiatric disorders. The use of polygenic scores is highly relevant as data from a large migraine Genome-Wide Association Study are now available, which will form an excellent basis for Polygenic Risk Score in migraine studies. RESULTS Polygenic Risk Score has been used in studies of neuropsychiatric disorders to assess prediction of disease status in case-control studies, shared genetic correlation between co-morbid diseases, and shared genetic correlation between a disease and specific endophenotypes. CONCLUSION Polygenic Risk Score provides an opportunity to investigate the shared genetic risk between known and previously unestablished co-morbidities in migraine research, and may lead to better and personalized treatment of migraine if used as a clinical assistant when identifying responders to specific drugs. Polygenic Risk Score can be used to analyze the genetic relationship between different headache types and migraine endophenotypes. Finally, Polygenic Risk Score can be used to assess pharmacogenetic effects, and perhaps help to predict efficacy of the Calcitonin Gene-Related Peptide monoclonal antibodies that soon become available as migraine treatment.
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Affiliation(s)
- Mona Ameri Chalmer
- Department of Neurology, Danish Headache Center, Copenhagen University Hospital, DK-2600, Glostrup, Denmark.
| | - Ann-Louise Esserlind
- Department of Neurology, Danish Headache Center, Copenhagen University Hospital, DK-2600, Glostrup, Denmark
| | - Jes Olesen
- Department of Neurology, Danish Headache Center, Copenhagen University Hospital, DK-2600, Glostrup, Denmark
| | - Thomas Folkmann Hansen
- Department of Neurology, Danish Headache Center, Copenhagen University Hospital, DK-2600, Glostrup, Denmark
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20
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Abstract
Imaging genetics is a research methodology studying the effect of genetic variation on brain structure, function, behavior, and risk for psychopathology. Since the early 2000s, imaging genetics has been increasingly used in the research of schizophrenia (SZ). SZ is a severe mental disorder with no precise knowledge of its underlying neurobiology, however, new genetic and neurobiological data generate a climate for new avenues. The accumulating data of genome wide association studies (GWAS) continuously decode SZ risk genes. Global neuroimaging consortia produce collections of brain phenotypes from tens of thousands of people. In this context, imaging genetics will be strategically important both for the validation and discovery of SZ related findings. Thus, the study of GWAS supported risk variants as candidate genes to validate by neuroimaging is one trend. The study of epigenetic differences in relation to variations of brain phenotypes and the study of large scale multivariate analysis of genome wide and brain wide associations are other trends. While these studies hold a big potential for understanding the neurobiology of SZ, the problem of reproducibility appears as a major challenge, which requires standardizations in study designs and compensations of methodological limitations such as sensitivity and specificity. On the other hand, advancements of neuroimaging, optical and electron microscopy along with the use of genetically encoded fluorescent probes and robust statistical approaches will not only catalyze integrative methodologies but also will help better design the imaging genetics studies. In this invited paper, I will discuss the current perspective of imaging genetics and emerging opportunities of SZ research.
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Affiliation(s)
- Ayla Arslan
- Faculty of Engineering and Natural Sciences, Department of Genetics and Bioengineering, International University of Sarajevo, Sarajevo, Bosnia and Herzegovina; Faculty of Engineering and Natural Sciences, Department of Molecular Biology and Genetics, Uskudar University, Istanbul, Turkey.
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21
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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: 51] [Impact Index Per Article: 7.3] [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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22
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Iacono WG, Malone SM, Vrieze SI. Endophenotype best practices. Int J Psychophysiol 2017; 111:115-144. [PMID: 27473600 PMCID: PMC5219856 DOI: 10.1016/j.ijpsycho.2016.07.516] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2016] [Revised: 07/21/2016] [Accepted: 07/24/2016] [Indexed: 01/19/2023]
Abstract
This review examines the current state of electrophysiological endophenotype research and recommends best practices that are based on knowledge gleaned from the last decade of molecular genetic research with complex traits. Endophenotype research is being oversold for its potential to help discover psychopathology relevant genes using the types of small samples feasible for electrophysiological research. This is largely because the genetic architecture of endophenotypes appears to be very much like that of behavioral traits and disorders: they are complex, influenced by many variants (e.g., tens of thousands) within many genes, each contributing a very small effect. Out of over 40 electrophysiological endophenotypes covered by our review, only resting heart, a measure that has received scant advocacy as an endophenotype, emerges as an electrophysiological variable with verified associations with molecular genetic variants. To move the field forward, investigations designed to discover novel variants associated with endophenotypes will need extremely large samples best obtained by forming consortia and sharing data obtained from genome wide arrays. In addition, endophenotype research can benefit from successful molecular genetic studies of psychopathology by examining the degree to which these verified psychopathology-relevant variants are also associated with an endophenotype, and by using knowledge about the functional significance of these variants to generate new endophenotypes. Even without molecular genetic associations, endophenotypes still have value in studying the development of disorders in unaffected individuals at high genetic risk, constructing animal models, and gaining insight into neural mechanisms that are relevant to clinical disorder.
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23
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Cheng CH, Chan PYS, Liu CY, Hsu SC. Auditory sensory gating in patients with bipolar disorders: A meta-analysis. J Affect Disord 2016; 203:199-203. [PMID: 27295376 DOI: 10.1016/j.jad.2016.06.010] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2016] [Revised: 05/29/2016] [Accepted: 06/03/2016] [Indexed: 12/11/2022]
Abstract
BACKGROUND Sensory gating (SG) refers to the attenuation of neural response to the second identical stimulus and is conceptualized as an automatic process to inhibit redundant information. Although its deficit in schizophrenia has been well-documented, the degree to which SG is modulated by bipolar disorders (BD) remains elusive. Thus, the present meta-analysis study aimed to explore the pooled effect sizes of SG ability in BD patients. METHODS Ten studies consisting of 14 individual investigations were included, consisting of 699 healthy controls and 568 BD patients. The effect sizes, calculated as Cohen's d, were estimated individually for S2/S1 ratio and S1-S2 difference. Additionally, S2/S1 ratio was examined in two conditions: BD with and without a history of psychosis. RESULTS We found that BD patients with (d=0.847, p<0.001) or without (d=0.589, p<0.001) a psychotic history exhibited an impaired SG ability compared to the healthy controls. Furthermore, both S1-S2 difference score and S2/S1 ratio, at a group level, can differentiate BD patients from healthy controls. LIMITATIONS We were not able to divide patients with BD into different subtypes, and thus our data should be interpreted with cautions. CONCLUSION These findings suggest BD itself impairs SG ability, which worsens with a psychotic history. The current understanding invites future research to ascertain the role of SG in subtypes of BD.
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Affiliation(s)
- Chia-Hsiung Cheng
- Department of Occupational Therapy and Graduate Institute of Behavioral Sciences, Chang Gung University, Taoyuan, Taiwan; Healthy Aging Research Center, Chang Gung University, Taoyuan, Taiwan; Laboratory of Brain Imaging and Neural Dynamics (BIND Lab), Chang Gung University, Taoyuan, Taiwan; Department of Psychiatry, Chang Gung Memorial Hospital, Linkou, Taiwan.
| | - Pei-Ying S Chan
- Department of Occupational Therapy and Graduate Institute of Behavioral Sciences, Chang Gung University, Taoyuan, Taiwan; Healthy Aging Research Center, Chang Gung University, Taoyuan, Taiwan; Department of Psychiatry, Chang Gung Memorial Hospital, Linkou, Taiwan
| | - Chia-Yih Liu
- Department of Psychiatry, Chang Gung Memorial Hospital, Linkou, Taiwan; School of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Shih-Chieh Hsu
- Department of Psychiatry, Chang Gung Memorial Hospital, Linkou, Taiwan; School of Medicine, Chang Gung University, Taoyuan, Taiwan
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24
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Buoli M, Caldiroli A, Cumerlato Melter C, Serati M, de Nijs J, Altamura AC. Biological aspects and candidate biomarkers for psychotic bipolar disorder: A systematic review. Psychiatry Clin Neurosci 2016; 70:227-44. [PMID: 26969211 DOI: 10.1111/pcn.12386] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2015] [Revised: 01/24/2016] [Accepted: 03/06/2016] [Indexed: 12/23/2022]
Abstract
AIM We carried out a systematic review of the available literature about potential biomarkers of psychotic bipolar disorder (BD-P), a specific subset presenting worse outcome and greater risk of relapse than non-psychotic bipolar disorder (BD-NP). METHODS We searched the main psychiatric databases (PubMed, ISI Web of Knowledge, PsychInfo). Only original articles with the main topic of BD-P compared to schizophrenia/BD-NP/healthy controls (HC) written in English from 1994 to 2015 were included. RESULTS BD-P patients presented higher kynurenic acid levels in the cerebrospinal fluid, elevated anti- S accharomyces cerevisiae antibodies levels, and lower serum levels of dehydroepiandrosterone sulfate and progesterone than BD-NP/HC. Event-related potentials abnormalities have been identified in BD-P with respect to BD-NP. BD-P patients also presented bigger ventricles but similar hippocampal volumes compared to BD-NP/HC. Although the results are contrasting, some cognitive deficits seemed to be related to the psychotic dimension of bipolar affective disorder, such as impairment in verbal/logical memory, working memory, verbal and semantic fluency and executive functioning. Finally, polymorphisms of genes, such as NRG1, 5HTTLPR (s), COMT, DAOA and some chromosome regions (16p12 and 13q), were positively associated with BD-P. CONCLUSION Data about the identification of specific biomarkers for BD-P are promising, but most of them have not yet been replicated. They could lead the clinicians to an early diagnosis and proper treatment, thus ameliorating outcome of BD-P and reducing the biological changes associated with a long duration of illness. Further studies with bigger samples are needed to detect more specific biological markers of the psychotic dimension of bipolar affective disorder.
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Affiliation(s)
- Massimiliano Buoli
- Department of Psychiatry, University of Milan, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy.,Department of Psychiatry, University Medical Center Utrecht - Brain Centre Rudolf Magnus, Utrecht, The Netherlands
| | - Alice Caldiroli
- Department of Psychiatry, University of Milan, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | - Claudia Cumerlato Melter
- Department of Psychiatry, University of Milan, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | - Marta Serati
- Department of Psychiatry, University of Milan, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | - Jessica de Nijs
- Department of Psychiatry, University Medical Center Utrecht - Brain Centre Rudolf Magnus, Utrecht, The Netherlands
| | - A Carlo Altamura
- Department of Psychiatry, University of Milan, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy
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25
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Abstract
Endophenotypes are quantitative, heritable traits that may help to elucidate the pathophysiologic mechanisms underlying complex disease syndromes, such as schizophrenia. They can be assessed at numerous levels of analysis; here, we review electrophysiological endophenotypes that have shown promise in helping us understand schizophrenia from a more mechanistic point of view. For each endophenotype, we describe typical experimental procedures, reliability, heritability, and reported gene and neurobiological associations. We discuss recent findings regarding the genetic architecture of specific electrophysiological endophenotypes, as well as converging evidence from EEG studies implicating disrupted balance of glutamatergic signaling and GABAergic inhibition in the pathophysiology of schizophrenia. We conclude that refining the measurement of electrophysiological endophenotypes, expanding genetic association studies, and integrating data sets are important next steps for understanding the mechanisms that connect identified genetic risk loci for schizophrenia to the disease phenotype.
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Affiliation(s)
- Emily Owens
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA
| | - Peter Bachman
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA
| | - David C Glahn
- Olin Neuropsychiatric Research Center, Institute of Living, Hartford, CT,Department of Psychiatry, Yale University School of Medicine, New Haven, CT
| | - Carrie E Bearden
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA
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