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Your search keyword '"Dara Manoach"' showing total 9 results
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9 results on '"Dara Manoach"'

1. Electroencephalographic Microstates During Sleep and Wake in Schizophrenia

Author

Michael Murphy, Chenguang Jiang, Lei A. Wang, Nataliia Kozhemiako, Yining Wang, Jun Wang, Jen Q. Pan, Shaun M. Purcell, Guanchen Gai, Kai Zou, Zhe Wang, Xiaoman Yu, Guoqiang Wang, Shuping Tan, Mei Hua Hall, Wei Zhu, Zhenhe Zhou, Lu Shen, Shenying Qin, Hailiang Huang, Lin Zhou, Shen Li, Robert Law, Minitrios Mylonas, Robert Stickgold, Dara Manoach, Mei-Hua Hall, Zhenglin Guo, Sinead Chapman, and Chenaugnag Jiang

Subjects
EEG, Microstates, Resting-state, Schizophrenia, Sleep, Spindles, Psychiatry, RC435-571
Abstract

Background: Aberrant functional connectivity is a hallmark of schizophrenia. The precise nature and mechanism of dysconnectivity in schizophrenia remains unclear, but evidence suggests that dysconnectivity is different in wake versus sleep. Microstate analysis uses electroencephalography (EEG) to investigate large-scale patterns of coordinated brain activity by clustering EEG data into a small set of recurring spatial patterns, or microstates. We hypothesized that this technique would allow us to probe connectivity between brain networks at a fine temporal resolution and uncover previously unknown sleep-specific dysconnectivity. Methods: We studied microstates during sleep in patients with schizophrenia by analyzing high-density EEG sleep data from 114 patients with schizophrenia and 79 control participants. We used a polarity-insensitive k-means analysis to extract a set of 6 microstate topographies. Results: These 6 states included 4 widely reported canonical microstates. In patients and control participants, falling asleep was characterized by a shift from microstates A, B, and C to microstates D, E, and F. Microstate F was decreased in patients during wake, and microstate E was decreased in patients during sleep. The complexity of microstate transitions was greater in patients than control participants during wake, but this reversed during sleep. Conclusions: Our findings reveal behavioral state–dependent patterns of cortical dysconnectivity in schizophrenia. Furthermore, these findings are largely unrelated to previous sleep-related EEG markers of schizophrenia such as decreased sleep spindles. Therefore, these findings are driven by previously undescribed sleep-related pathology in schizophrenia.

Published
2024
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2. Non-rapid eye movement sleep and wake neurophysiology in schizophrenia

Author

Nataliia Kozhemiako, Jun Wang, Chenguang Jiang, Lei A Wang, Guanchen Gai, Kai Zou, Zhe Wang, Xiaoman Yu, Lin Zhou, Shen Li, Zhenglin Guo, Robert Law, James Coleman, Dimitrios Mylonas, Lu Shen, Guoqiang Wang, Shuping Tan, Shengying Qin, Hailiang Huang, Michael Murphy, Robert Stickgold, Dara Manoach, Zhenhe Zhou, Wei Zhu, Mei-Hua Hal, Shaun M Purcell, and Jen Q Pan

Subjects
schizophrenia, wake-sleep, EEG, sleep spindles, auditory ERP, connectivity, Medicine, Science, Biology (General), QH301-705.5
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.

Published
2022
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4. 0652 Subjective and objective sleep disturbances in individuals with psychotic disorders and their first-degree relatives

Author

Hazal Arpaci, Courtney Spitzer, Nicolas Raymond, Christine Talbot, Erin Kohnke, Robert Stickgold, Dara Manoach, Matcheri Keshavan, and Bengi Baran

Subjects
Physiology (medical), Neurology (clinical)
Abstract

Introduction Sleep disturbances commonly precede or precipitate psychotic disorders. The primary goals of the present study are to compare self-reports of sleep quality and chronotype with objective measurements and to investigate their relations with clinical symptoms and psychotic-like experiences (PLEs) in early course, minimally treated patients with psychotic disorders (PSY), their young, first-degree relatives (familial high risk: FHR) and matched controls. Methods Seventy-three participants (13-35 yrs, n(PSY)=19, n(Controls)=30, n(FHR)=24) completed self-report measures of sleep quality (PSQI), chronotype (MEQ) and PLEs (Chapman Scales). Sleep quality and chronotype were objectively measured with actigraphy (average duration of measurements: 12 days). Psychosis and FHR groups were rated on the Positive and Negative Syndrome Scale (PANSS) by an expert clinician. Results PSQI was significantly different between the groups (F(2,67)= 11.8, p< .001), this reflected that compared to controls, both the psychosis (p Conclusion While both early-course patients and their first-degree relatives report significant sleep disturbances, objective measurements corroborate this only for day-to-day variability in sleep duration in the patient group. Further, symptom severity and PLEs correlate only with subjective sleep disturbances. These findings highlight the importance of objective assessment of sleep quality in this population and are in line with our polysomnography work that reveals an isolated deficit in NREM sleep in the context of similar sleep duration and architecture in psychosis. Support (if any) K01 MH114012 (Baran)

Published
2023
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5. Author response: Non-rapid eye movement sleep and wake neurophysiology in schizophrenia

Author

Chenguang Jiang, Jun Wang, Nataliia Kozhemiako, Lei A Wang, Guanchen Gai, Kai Zou, Zhe Wang, Xiaoman Yu, Lin Zhou, Shen Li, Zhenglin Guo, Robert Law, James Coleman, Dimitrios Mylonas, Lu Shen, Guoqiang Wang, Shuping Tan, Shengying Qin, Hailiang Huang, Michael Murphy, Robert Stickgold, Dara Manoach, Zhenhe Zhou, Wei Zhu, Mei-Hua Hal, Shaun M Purcell, and Jen Q Pan

Published
2022
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6. Non-rapid eye movement sleep and wake neurophysiology in schizophrenia

Author

Chenguang Jiang, Jun Wang, Nataliia Kozhemiako, Lei A Wang, Guanchen Gai, Kai Zou, Zhe Wang, Xiaoman Yu, Lin Zhou, Shen Li, Zhenglin Guo, Robert Law, James Coleman, Dimitrios Mylonas, Lu Shen, Guoqiang Wang, Shuping Tan, Shengying Qin, Hailiang Huang, Michael Murphy, Robert Stickgold, Dara Manoach, Zhenhe Zhou, Wei Zhu, Mei-Hua Hal, Shaun M Purcell, and Jen Q Pan

Subjects
General Immunology and Microbiology, General Neuroscience, Polysomnography, Schizophrenia, Humans, Neurophysiology, Electroencephalography, General Medicine, Sleep, General Biochemistry, Genetics and Molecular Biology
Abstract

Motivated by the potential of objective neurophysiological markers to index thalamocortical function in patients with severe psychiatric illnesses, we comprehensively characterized key NREM sleep parameters across multiple domains, their interdependencies, and their relationship to waking event-related potentials and symptom severity. In 130 schizophrenia (SCZ) patients and controls, we confirmed a marked reduction in sleep spindle density in SCZ and extended these findings to show that only slow spindles predicted symptom severity, and 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, 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.

Published
2021

9. Rates, distribution and implications of postzygotic mosaic mutations in autism spectrum disorder

Author

Lim, Elaine T., Uddin, Mohammed, De Rubeis, Silvia, Chan, Yingleong, Kamumbu, Anne S., Zhang, Xiaochang, D'Gama, Alissa M., Kim, Sonia N., Hill, Robert Sean, Goldberg, Arthur P., Poultney, Christopher, Minshew, Nancy J., Kushima, Itaru, Aleksic, Branko, Ozaki, Norio, Parellada, Mara, Arango, Celso, Penzol, Maria J., Carracedo, Angel, Kolevzon, Alexander, Hultman, Christina M., Weiss, Lauren A., Fromer, Menachem, Chiocchetti, Andreas G., Freitag, Christine M., Church, George M., Scherer, Stephen W., Buxbaum, Joseph D., Walsh, Christopher A, Aleksic, B, Anney, R, Barbosa, M, Barrett, J, Betancur, C, Bishop, S, Brusco, A, Buxbaum, Jd, Carracedo, A, Chiocchetti, Ag, Chung, Bhy, Cook, E, Coon, H, Cutler, Dj, Daly, M, De Rubeis, S, Doan, R, Fernández-Prieto, M, Ferrero, Gb, Freitag, Cm, Fromer, M, Gargus, J, Geschwind, D, Gill, M, Gómez-Guerrero, L, Hansen-Kiss, E, He, X, Herman, G, Hertz-Picciotto, I, Hultman, C, Iliadou, B, Ionita-Laza, I, Jugessur, A, Knudsen, Gp, Kolevzon, A, Kosmicki, J, Kushima, I, Lee, Sl, Lehner, T, Lennertz, S, Lim, E, Maciel, P, Magnus, P, Manoach, D, Minshew, N, Morrow, E, Mulle, J, Neale, B, Ozaki, N, Palotie, A, Parellada, M, Passos-Bueno, Mr, Pericak-Vance, M, Persico, A, Pessah, I, Reichenberg, A, Reichert, J, Renieri, A, Robinson, E, Samocha, K, Sanders, S, Sandin, S, Santangelo, Sl, Satterstrom, K, Schafer, C, Schellenberg, G, Scherer, S, Senthil, G, Silva, M, Singh, T, Siper, Pm, Soares, G, Stevens, C, Stoltenberg, C, Surén, P, Sutcliffe, Js, Szatmari, P, Tassone, F, Thurm, A, Walsh, C, Weiss, L, Werling, D, Willsey, J, Xu, X, Yu, Tw, Yuen, R, Zwick, Me., Howard Hughes Medical Institute [Boston] (HHMI), Howard Hughes Medical Institute (HHMI)-Harvard Medical School [Boston] (HMS), Boston Children's Hospital, Harvard Medical School [Boston] (HMS), Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], Harvard University [Cambridge], Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU), Icahn School of Medicine at Mount Sinai [New York] (MSSM), University of Pittsburgh (PITT), Pennsylvania Commonwealth System of Higher Education (PCSHE), Nagoya University, Hospital General Universitario 'Gregorio Marañón' [Madrid], Universidad Complutense de Madrid = Complutense University of Madrid [Madrid] (UCM), Centro de Investigación Biomédica en Red Salud Mental [Madrid] (CIBER-SAM), Universidade de Santiago de Compostela [Spain] (USC ), CIBER de Enfermedades Raras (CIBERER), Fundación Pública Galega Medicina Xenómica - SERGAS [Santiago de Compostela, Spain] (Grupo de Medicina Xenómica), CIBER de Enfermedades Raras (CIBERER)-Universidade de Santiago de Compostela [Spain] (USC ), King Abdulaziz University, Karolinska Institutet [Stockholm], University of California [San Francisco] (UCSF), University of California, Goethe-University Frankfurt am Main, Génétique de l'autisme = Genetics of Autism (NPS-01), Neurosciences Paris Seine (NPS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut de Biologie Paris Seine (IBPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut de Biologie Paris Seine (IBPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), The Hospital for sick children [Toronto] (SickKids), University of Toronto, McLaughlin Centre for Population Health Risk Assessment, University of Ottawa [Ottawa], Autism Sequencing Consortium: Branko Aleksic, Richard Anney, Mafalda Barbosa, Jeffrey Barrett, Catalina Betancur, Somer Bishop, Alfredo Brusco, Joseph D Buxbaum, Angel Carracedo, Andreas G Chiocchetti, Brian H Y Chung, Edwin Cook, Hilary Coon, David J Cutler, Mark Daly, Silvia De Rubeis, Ryan Doan, Montserrat Fernández-Prieto, Giovanni Battista Ferrero, Christine M Freitag, Menachem Fromer, Jay Gargus, Dan Geschwind, Michael Gill, Lorena Gómez-Guerrero, Emily Hansen-Kiss, Xin He, Gail Herman, Irva Hertz-Picciotto, Christina Hultman, Bozenna Iliadou, Iuliana Ionita-Laza, Anil Jugessur, Gun Peggy Knudsen, Alexander Kolevzon, Jack Kosmicki, Itaru Kushima, S L Lee, Thomas Lehner, Savannah Lennertz, Elaine Lim, Patricia Maciel, Per Magnus, Dara Manoach, Nancy Minshew, Eric Morrow, Jennifer Mulle, Benjamin Neale, Norio Ozaki, Aarno Palotie, Mara Parellada, Maria Rita Passos-Bueno, Margaret Pericak-Vance, Antonio Persico, Isaac Pessah, Avi Reichenberg, Jennifer Reichert, Alessandra Renieri, Elise Robinson, Kaitlin Samocha, Stephan Sanders, Sven Sandin, Susan L Santangelo, Kyle Satterstrom, Chad Schafer, Gerry Schellenberg, Stephen Scherer, Geetha Senthil, Marisol Silva, Tarjinder Singh, Paige M Siper, Gabriela Soares, Christine Stevens, Camilla Stoltenberg, Pål Surén, James S Sutcliffe, Peter Szatmari, Flora Tassone, Audrey Thurm, Christopher Walsh, Lauren Weiss, Donna Werling, Jeremy Willsey, Xinyi Xu, Timothy W Yu, Ryan Yuen, Michael E Zwick., University of California [San Francisco] (UC San Francisco), University of California (UC), Neuroscience Paris Seine (NPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie Paris Seine (IBPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), and Betancur, Catalina

Subjects
0301 basic medicine, Proband, Nonsynonymous substitution, Autism Spectrum Disorder, Databases, Genetic, Genetic Predisposition to Disease, Genetic Variation, Humans, Mosaicism, Mutation, Missense, Zygote, Neuroscience (all), Mutation, Missense, Epigenetics of autism, Biology, [SDV.GEN.GH] Life Sciences [q-bio]/Genetics/Human genetics, medicine.disease_cause, Article, 03 medical and health sciences, Genetic variation, mental disorders, Databases, Genetic, medicine, Missense mutation, Heritability of autism, MESH: Genetic Variation, MESH: Databases, Genetic, Genetics, MESH: Autism Spectrum Disorder, MESH: Mutation, Missense, [SDV.GEN]Life Sciences [q-bio]/Genetics, MESH: Humans, General Neuroscience, MESH: Genetic Predisposition to Disease, medicine.disease, 030104 developmental biology, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, Autism spectrum disorder, MESH: Zygote, MESH: Mosaicism
Abstract

International audience; We systematically analyzed postzygotic mutations (PZMs) in whole-exome sequences from the largest collection of trios (5,947) with autism spectrum disorder (ASD) available, including 282 unpublished trios, and performed resequencing using multiple independent technologies. We identified 7.5% of de novo mutations as PZMs, 83.3% of which were not described in previous studies. Damaging, nonsynonymous PZMs within critical exons of prenatally expressed genes were more common in ASD probands than controls (P < 1 × 10-6), and genes carrying these PZMs were enriched for expression in the amygdala (P = 5.4 × 10-3). Two genes (KLF16 and MSANTD2) were significantly enriched for PZMs genome-wide, and other PZMs involved genes (SCN2A, HNRNPU and SMARCA4) whose mutation is known to cause ASD or other neurodevelopmental disorders. PZMs constitute a significant proportion of de novo mutations and contribute importantly to ASD risk.

Published
2017
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