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Hou Y, Qiu G, Xia H, He T, Liu X, Chen A. The specificity of the auditory P300 responses and its association with clinical outcomes in youth with psychosis risk syndrome. Int J Clin Health Psychol 2024; 24:100437. [PMID: 38292829 PMCID: PMC10825643 DOI: 10.1016/j.ijchp.2024.100437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Accepted: 01/02/2024] [Indexed: 02/01/2024] Open
Abstract
Background Schizophrenia often occurs in youth, and psychosis risk syndrome (PRS) occurs before the onset of psychosis. Assessing the neuropsychological abnormalities of PRS individuals can help in early identification and active intervention of mental illness. Auditory P300 amplitude defect is an important manifestation of attention processing abnormality in PRS, but it is still unclear whether there are abnormalities in the attention processing of rhythmic compound tone stimuli in PRS individuals, and whether the P300 amplitude induced by these stimuli is specific to PRS individuals and related to their clinical outcomes. Methods In total, 226 participants, including 122 patients with PRS, 51 patients with emotional disorders (ED), and 53 healthy controls (HC) were assessed. Baseline electroencephalography was recorded during the compound tone oddball task. The event-related potentials (ERPs) induced by rhythmic compound tone stimuli of two frequencies (20-Hz, 40-Hz) were measured. Almost all patients with PRS were followed up for 12 months and reclassified into four groups: PRS-conversion, PRS-symptomatic, PRS-emotional disorder, and PRS-complete remission. The differences in baseline ERPs were compared among the clinical outcome groups. Results Regardless of the stimulation frequency, the average P300 amplitude were significantly higher in patients with PRS than in those with ED (p = 0.003, d = 0.48) and in HC (p = 0.002, d = 0.44) group. The average P300 amplitude of PRS-conversion group was significantly higher than that of the PRS-complete remission (p = 0.016, d = 0.72) and HC group (p = 0.001, d = 0.76), and the average P300 amplitude of PRS-symptomatic group was significantly higher than that of the HC group (p = 0.006, d = 0.48). Regardless of the groups (PRS, ED, HC) or the PRS clinical outcome groups, the average P300 amplitude induced by 20-Hz tone stimulation was significantly higher than that induced by 40-Hz stimulation (ps < 0.001, Ƞ2 = 0.074-0.082). The average reaction times of PRS was significantly faster than that of ED (p = 0.01, d = 0.38), and the average reaction times of the participants to 20-Hz target stimulation was significantly faster than that to 40-Hz target stimulation (p < 0.001, d = 0.21). Conclusion The auditory P300 amplitude induced by rhythmic compound tone stimuli is a specific electrophysiological manifestation of PRS, and the auditory P300 amplitude induced by compound tone stimuli shows promise as a putative prognostic biomarker for PRS clinical outcomes, including conversion to psychosis and clinical complete remission.
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Affiliation(s)
- Yongqing Hou
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
- Mental Health Center of Guangyuan, Sichuan, China
| | - Guiping Qiu
- College of Teacher Education, Ningxia University, Yinchuan, China
| | - Haishuo Xia
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Tianbao He
- Mental Health Center of Guangyuan, Sichuan, China
| | - Xiaoxian Liu
- Faculty of Education, Henan Normal University, Xinxiang, China
| | - Antao Chen
- School of Psychology, Research Center for Exercise and Brain Science, Shanghai University of Sport, Shanghai, China
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Caballero N, Machiraju S, Diomino A, Kennedy L, Kadivar A, Cadenhead KS. Recent Updates on Predicting Conversion in Youth at Clinical High Risk for Psychosis. Curr Psychiatry Rep 2023; 25:683-698. [PMID: 37755654 PMCID: PMC10654175 DOI: 10.1007/s11920-023-01456-2] [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] [Accepted: 09/05/2023] [Indexed: 09/28/2023]
Abstract
PURPOSE OF REVIEW This review highlights recent advances in the prediction and treatment of psychotic conversion. Over the past 25 years, research into the prodromal phase of psychotic illness has expanded with the promise of early identification of individuals at clinical high risk (CHR) for psychosis who are likely to convert to psychosis. RECENT FINDINGS Meta-analyses highlight conversion rates between 20 and 30% within 2-3 years using existing clinical criteria while research into more specific risk factors, biomarkers, and refinement of psychosis risk calculators has exploded, improving our ability to predict psychotic conversion with greater accuracy. Recent studies highlight risk factors and biomarkers likely to contribute to earlier identification and provide insight into neurodevelopmental abnormalities, CHR subtypes, and interventions that can target specific risk profiles linked to neural mechanisms. Ongoing initiatives that assess longer-term (> 5-10 years) outcome of CHR participants can provide valuable information about predictors of later conversion and diagnostic outcomes while large-scale international biomarker studies provide hope for precision intervention that will alter the course of early psychosis globally.
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Affiliation(s)
- Noe Caballero
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093-0810, USA
| | - Siddharth Machiraju
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093-0810, USA
| | - Anthony Diomino
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093-0810, USA
| | - Leda Kennedy
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093-0810, USA
| | - Armita Kadivar
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093-0810, USA
| | - Kristin S Cadenhead
- Department of Psychiatry, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093-0810, USA.
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Zandbagleh A, Mirzakuchaki S, Daliri MR, Premkumar P, Carretié L, Sanei S. Tensor factorization approach for ERP-based assessment of schizotypy in a novel auditory oddball task on perceived family stress. J Neural Eng 2022; 19. [PMID: 36541455 DOI: 10.1088/1741-2552/aca69f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 11/28/2022] [Indexed: 11/30/2022]
Abstract
Objective. Schizotypy, a potential phenotype for schizophrenia, is a personality trait that depicts psychosis-like signs in the normal range of psychosis continuum. Family communication may affect the social functioning of people with schizotypy. Greater family stress, such as irritability, criticism and less praise, is perceived at a higher level of schizotypy. This study aims to determine the differences between people with high and low levels of schizotypy using electroencephalography (EEG) during criticism, praise and neutral comments. EEGs were recorded from 29 participants in the general community who varied from low schizotypy to high schizotypy (HS) during a novel emotional auditory oddball task.Approach. We consider the difference in event-related potential parameters, namely the amplitude and latency of P300 subcomponents (P3a and P3b), between pairs of target words (standard, positive, negative and neutral). A model based on tensor factorization is then proposed to detect these components from the EEG using the CANDECOMP/PARAFAC decomposition technique. Finally, we employ the mutual information estimation method to select influential features for classification.Main results.The highest classification accuracy, sensitivity, and specificity of 93.1%, 94.73%, and 90% are obtained via leave-one-out cross validation.Significance. This is the first attempt to investigate the identification of individuals with psychometrically-defined HS from brain responses that are specifically associated with perceiving family stress and schizotypy. By measuring these brain responses to social stress, we achieve the goal of improving the accuracy in detection of early episodes of psychosis.
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Affiliation(s)
- Ahmad Zandbagleh
- School of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran
| | - Sattar Mirzakuchaki
- School of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran
| | - Mohammad Reza Daliri
- School of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran
| | - Preethi Premkumar
- Division of Psychology, School of Applied Sciences, London Southbank University, London, United Kingdom
| | - Luis Carretié
- Facultad de Psicología, Universidad Autónoma de Madrid, 28049 Madrid, Spain
| | - Saeid Sanei
- School of Science and Technology, Nottingham Trent University, Clifton Lane, Nottingham, United Kingdom
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4
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Duncan E, Roach BJ, Massa N, Hamilton HK, Bachman PM, Belger A, Carrion RE, Johannesen JK, Light GA, Niznikiewicz MA, Addington JM, Bearden CE, Cadenhead KS, Cannon TD, Cornblatt BA, McGlashan TH, Perkins DO, Tsuang M, Walker EF, Woods SW, Nasiri N, Mathalon DH. Auditory N100 amplitude deficits predict conversion to psychosis in the North American Prodrome Longitudinal Study (NAPLS-2) cohort. Schizophr Res 2022; 248:89-97. [PMID: 35994912 PMCID: PMC10091223 DOI: 10.1016/j.schres.2022.07.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 06/17/2022] [Accepted: 07/25/2022] [Indexed: 12/01/2022]
Abstract
BACKGROUND The auditory N100 is an event related potential (ERP) that is reduced in schizophrenia, but its status in individuals at clinical high risk for psychosis (CHR) and its ability to predict conversion to psychosis remains unclear. We examined whether N100 amplitudes are reduced in CHR subjects relative to healthy controls (HC), and this reduction predicts conversion to psychosis in CHR. METHODS Subjects included CHR individuals (n = 552) and demographically similar HC subjects (n = 236) from the North American Prodrome Longitudinal Study. Follow-up assessments identified CHR individuals who converted to psychosis (CHRC; n = 73) and those who did not (CHR-NC; n = 225) over 24 months. Electroencephalography data were collected during an auditory oddball task containing Standard, Novel, and Target stimuli. N100 peak amplitudes following each stimulus were measured at electrodes Cz and Fz. RESULTS The CHR subjects had smaller N100 absolute amplitudes than HC subjects at Fz (F(1,786) = 4.00, p 0.046). A model comparing three groups (CHRC, CHR-NC, HC) was significant for Group at the Cz electrode (F(2,531) = 3.58, p = 0.029). Both Standard (p = 0.019) and Novel (p = 0.017) stimuli showed N100 absolute amplitude reductions in CHR-C relative to HC. A smaller N100 amplitude at Cz predicted conversion to psychosis in the CHR cohort (Standard: p = 0.009; Novel: p = 0.001) and predicted shorter time to conversion (Standard: p = 0.013; Novel: p = 0.001). CONCLUSION N100 amplitudes are reduced in CHR individuals which precedes the onset of psychosis. N100 deficits in CHR individuals predict a greater likelihood of conversion to psychosis. Our results highlight N100's utility as a biomarker of psychosis risk.
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Affiliation(s)
- Erica Duncan
- Atlanta VA Health Care System, Decatur, GA, United States; Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States.
| | - Brian J Roach
- San Francisco VA Health Care System, San Francisco, CA, United States
| | - Nicholas Massa
- Atlanta VA Health Care System, Decatur, GA, United States
| | - Holly K Hamilton
- San Francisco VA Health Care System, San Francisco, CA, United States; Department of Psychiatry, University of California, San Francisco, San Francisco, CA, United States
| | - Peter M Bachman
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Aysenil Belger
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, United States
| | - Ricardo E Carrion
- Department of Psychiatry, Zucker Hillside Hospital, New York, NY, United States
| | - Jason K Johannesen
- Department of Psychology, Yale University, New Haven, CT, United States; Department of Psychiatry, Yale University, New Haven, CT, United States
| | - Gregory A Light
- Department of Psychiatry, University of California, San Diego, San Diego, CA, United States
| | | | - Jean M Addington
- Department of Psychiatry, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Carrie E Bearden
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States; Department of Psychology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Kristin S Cadenhead
- Department of Psychiatry, University of California, San Diego, San Diego, CA, United States
| | - Tyrone D Cannon
- Department of Psychology, Yale University, New Haven, CT, United States; Department of Psychiatry, Yale University, New Haven, CT, United States
| | - Barbara A Cornblatt
- Department of Psychiatry, Zucker Hillside Hospital, New York, NY, United States
| | - Thomas H McGlashan
- Department of Psychology, Yale University, New Haven, CT, United States; Department of Psychiatry, Yale University, New Haven, CT, United States
| | - Diana O Perkins
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, United States
| | - Ming Tsuang
- Department of Psychiatry, University of California, San Diego, San Diego, CA, United States
| | - Elaine F Walker
- Department of Psychology, Emory University, Atlanta, GA, United States
| | - Scott W Woods
- Department of Psychology, Yale University, New Haven, CT, United States; Department of Psychiatry, Yale University, New Haven, CT, United States
| | - Nima Nasiri
- Atlanta VA Health Care System, Decatur, GA, United States
| | - Daniel H Mathalon
- San Francisco VA Health Care System, San Francisco, CA, United States; Department of Psychiatry, University of California, San Francisco, San Francisco, CA, United States
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Jutla A, Foss-Feig J, Veenstra-VanderWeele J. Autism spectrum disorder and schizophrenia: An updated conceptual review. Autism Res 2022; 15:384-412. [PMID: 34967130 PMCID: PMC8931527 DOI: 10.1002/aur.2659] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 11/08/2021] [Accepted: 12/12/2021] [Indexed: 12/19/2022]
Abstract
Autism spectrum disorder (ASD) and schizophrenia (SCZ) are separate disorders, with distinct clinical profiles and natural histories. ASD, typically diagnosed in childhood, is characterized by restricted or repetitive interests or behaviors and impaired social communication, and it tends to have a stable course. SCZ, typically diagnosed in adolescence or adulthood, is characterized by hallucinations and delusions, and tends to be associated with declining function. However, youth with ASD are three to six times more likely to develop SCZ than their neurotypical counterparts, and increasingly, research has shown that ASD and SCZ converge at several levels. We conducted a systematic review of studies since 2013 relevant to understanding this convergence, and present here a narrative synthesis of key findings, which we have organized into four broad categories: symptoms and behavior, perception and cognition, biomarkers, and genetic and environmental risk. We then discuss opportunities for future research into the phenomenology and neurobiology of overlap between ASD and SCZ. Understanding this overlap will allow for researchers, and eventually clinicians, to understand the factors that may make a child with ASD vulnerable to developing SCZ. LAY SUMMARY: Autism spectrum disorder and schizophrenia are distinct diagnoses, but people with autism and people with schizophrena share several characteristics. We review recent studies that have examined these areas of overlap, and discuss the kinds of studies we will need to better understand how these disorders are related. Understanding this will be important to help us identify which autistic children are at risk of developing schizophrenia.
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Affiliation(s)
- Amandeep Jutla
- Columbia University Vagelos College of Physicians and
Surgeons, 630 W 168th St, New York, NY 10032, United States
- New York State Psychiatric Institute, 1051 Riverside
Drive, Mail Unit 78, New York, NY 10032, United States
| | - Jennifer Foss-Feig
- Seaver Autism Center for Research and Treatment, Icahn
School of Medicine at Mount Sinai, Department of Psychiatry, 1 Gustave L. Levy
Place, Box 1230, New York, NY 10029, United States
| | - Jeremy Veenstra-VanderWeele
- Columbia University Vagelos College of Physicians and
Surgeons, 630 W 168th St, New York, NY 10032, United States
- New York State Psychiatric Institute, 1051 Riverside
Drive, Mail Unit 78, New York, NY 10032, United States
- Center for Autism and the Developing Brain, New
York-Presbyterian Westchester Behavioral Health Center, 21 Bloomingdale Road, White
Plains, NY 10605, United States
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Riccioni A, Siracusano M, Vasta M, Ribolsi M, Nastro FF, Gialloreti LE, Di Lorenzo G, Mazzone L. Clinical profile and conversion rate to full psychosis in a prospective cohort study of youth affected by autism spectrum disorder and attenuated psychosis syndrome: A preliminary report. Front Psychiatry 2022; 13:950888. [PMID: 36213900 PMCID: PMC9542639 DOI: 10.3389/fpsyt.2022.950888] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 08/18/2022] [Indexed: 11/13/2022] Open
Abstract
Psychosis can occur at high rates in individuals with autism spectrum disorder (ASD). However, the detection of prodromal psychotic symptoms, including attenuated psychosis syndrome (APS), conditions at high risk of converting to full psychosis, has not been extensively investigated in ASD. We longitudinally evaluate a sample of young ASD individuals (age, mean ± SD: 13 ± 2.9) with (n = 13) or without (n = 18) concomitant APS through a standardized assessment of autistic (Autism Diagnostic Observation Schedule-Second Edition; ADOS-2) and psychotic (Structured Interview for Psychosis-Risk Syndromes, SIPS) symptoms and cognitive and adaptive skills. Individuals with other neuropsychiatric disorders were excluded. We estimated the conversion rate to full psychosis (according to SIPS criteria) over time (39.6 ± 11.5 months) and explored the role of clinical variables at baseline in the transition to full psychosis. A conversion rate to full psychosis of 30.7% was found in ASD/APS. Conversion to full psychosis was not affected by the severity of the autistic and psychotic symptoms. At baseline, young individuals with ASD/APS who later converted to full psychosis showed lower cognitive performance (d = 2.05) and greater impairment of adaptive social functioning profile (d = 1.2) than those with ASD. The results of this preliminary report revealed that nearly a third of young individuals with ASD/APS convert to full psychosis over time. Conversion to full psychosis is affected by decreased cognitive and adaptive skills. Further investigations are needed to confirm the utility of APS detection and to better characterize the psychotic developmental trajectory in ASD, with consequent important implications on prognosis and therapeutic strategies.
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Affiliation(s)
- Assia Riccioni
- Child Neurology and Psychiatry Unit, Tor Vergata University Hospital, Fondazione PTV - Policlinico Tor Vergata, Rome, Italy.,Chair of Child Neurology and Psychiatry, Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy
| | - Martina Siracusano
- Child Neurology and Psychiatry Unit, Tor Vergata University Hospital, Fondazione PTV - Policlinico Tor Vergata, Rome, Italy.,Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy
| | - Michelangelo Vasta
- Child Neurology and Psychiatry Unit, Tor Vergata University Hospital, Fondazione PTV - Policlinico Tor Vergata, Rome, Italy.,Chair of Child Neurology and Psychiatry, Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy
| | - Michele Ribolsi
- Unit of Neurology, Neurophysiology, Neurobiology, and Psychiatry, Department of Medicine, University Campus Bio-Medico of Rome, Rome, Italy
| | - Federico Fiori Nastro
- Chair of Psychiatry, Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy.,Psychiatry and Clinical Psychology Unit, Fondazione PTV - Policlinico Tor Vergata, Rome, Italy
| | | | - Giorgio Di Lorenzo
- Chair of Psychiatry, Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy.,IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Luigi Mazzone
- Child Neurology and Psychiatry Unit, Tor Vergata University Hospital, Fondazione PTV - Policlinico Tor Vergata, Rome, Italy.,Chair of Child Neurology and Psychiatry, Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy
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7
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Kerins S, Nottage J, Salazar de Pablo G, Kempton MJ, Tognin S, Niemann DH, de Haan L, van Amelsvoort T, Kwon JS, Nelson B, Mizrahi R, McGuire P, Fusar-Poli P. Identifying Electroencephalography Biomarkers in Individuals at Clinical High Risk for Psychosis in an International Multi-Site Study. Front Psychiatry 2022; 13:828376. [PMID: 35370849 PMCID: PMC8970279 DOI: 10.3389/fpsyt.2022.828376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 02/10/2022] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND The clinical high-risk for psychosis (CHR-P) paradigm was introduced to detect individuals at risk of developing psychosis and to establish preventive strategies. While current prediction of outcomes in the CHR-P state is based mostly on the clinical assessment of presenting features, several emerging biomarkers have been investigated in an attempt to stratify CHR-P individuals according to their individual trajectories and refine the diagnostic process. However, heterogeneity across subgroups is a key challenge that has limited the impact of the CHR-P prediction strategies, as the clinical validity of the current research is limited by a lack of external validation across sites and modalities. Despite these challenges, electroencephalography (EEG) biomarkers have been studied in this field and evidence suggests that EEG used in combination with clinical assessments may be a key measure for improving diagnostic and prognostic accuracy in the CHR-P state. The PSYSCAN EEG study is an international, multi-site, multimodal longitudinal project that aims to advance knowledge in this field. METHODS Participants at 6 international sites take part in an EEG protocol including EEG recording, cognitive and clinical assessments. CHR-P participants will be followed up after 2 years and subcategorised depending on their illness progression regarding transition to psychosis. Differences will be sought between CHR-P individuals and healthy controls and between CHR-P individuals who transition and those who do not transition to psychosis using data driven computational analyses. DISCUSSION This protocol addresses the challenges faced by previous studies of this kind to enable valid identification of predictive EEG biomarkers which will be combined with other biomarkers across sites to develop a prognostic tool in CHR-P. The PSYSCAN EEG study aims to pave the way for incorporating EEG biomarkers in the assessment of CHR-P individuals, to refine the diagnostic process and help to stratify CHR-P subjects according to risk of transition. This may improve our understanding of the CHR-P state and therefore aid the development of more personalized treatment strategies.
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Affiliation(s)
- Sarah Kerins
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.,Early Psychosis: Interventions and Clinical-Detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Judith Nottage
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Gonzalo Salazar de Pablo
- Early Psychosis: Interventions and Clinical-Detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.,Institute of Psychiatry and Mental Health, CIBERSAM, Madrid, Spain.,Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón School of Medicine, Instituto de Investigación Sanitaria Gregorio Marañón, Universidad Complutense, CIBERSAM, Madrid, Spain
| | - Matthew J Kempton
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Stefania Tognin
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.,Outreach and Support in South London (OASIS), South London and Maudsley NHS Foundation Trust, London, United Kingdom.,Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht, Netherlands
| | - Dorien H Niemann
- Department of Psychiatry, Early Psychosis Section, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Lieuwe de Haan
- Department of Psychiatry, Early Psychosis Section, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Thérèse van Amelsvoort
- Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, Netherlands
| | - Jun Soo Kwon
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
| | - Barnaby Nelson
- Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, VIC, Australia.,Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia
| | - Romina Mizrahi
- Douglas Mental Health University Institute, Montreal, QC, Canada.,Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.,National Institute for Health Research, Mental Health Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, King's College London, London, United Kingdom
| | - Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical-Detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.,Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón School of Medicine, Instituto de Investigación Sanitaria Gregorio Marañón, Universidad Complutense, CIBERSAM, Madrid, Spain.,National Institute for Health Research, Mental Health Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, King's College London, London, United Kingdom.,Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
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