Dominic Oliver1, Giulia Spada1, Amir Englund2, Edward Chesney2, Joaquim Radua3, Abraham Reichenberg4, Rudolf Uher5, Philip McGuire2, Paolo Fusar-Poli6. 1. Early Psychosis: Interventions and Clinical Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; OASIS Service, South London and the Maudsley NHS Foundation Trust, London, United Kingdom. 2. Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom. 3. Early Psychosis: Interventions and Clinical Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; Imaging of Mood- and Anxiety-Related Disorders (IMARD), Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERSAM, Barcelona, Spain; Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden. 4. Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Frieman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States. 5. Department of Psychiatry, Dalhousie University, Halifax, NS, Canada. 6. Early Psychosis: Interventions and Clinical Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; OASIS Service, South London and the Maudsley NHS Foundation Trust, London, United Kingdom; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy. Electronic address: paolo.fusar-poli@kcl.ac.uk.
Abstract
BACKGROUND: The Psychosis Polyrisk Score (PPS) is a potential biomarker integrating non-purely genetic risk/protective factors for psychosis that may improve identification of individuals at risk and prediction of their outcomes at the individual subject level. Biomarkers that are easy to administer are direly needed in early psychosis to facilitate clinical implementation. This study digitally implements the PPS and pilots its feasibility of use in the real world. METHODS: The PPS was implemented digitally and prospectively piloted across individuals referred for a CHR-P assessment (n = 16) and healthy controls (n = 66). Distribution of PPS scores was further simulated in the general population. RESULTS: 98.8% of individuals referred for a CHR-P assessment and healthy controls completed the PPS assessment with only one drop-out. 96.3% of participants completed the assessment in under 15 min. Individuals referred for a CHR-P assessment had high PPS scores (mean = 6.2, SD = 7.23) than healthy controls (mean = -1.79, SD = 6.78, p < 0.001). In simulated general population data, scores were normally distributed ranging from -15 (lowest risk, RR = 0.03) to 39.5 (highest risk, RR = 8912.51). DISCUSSION: The PPS is a promising biomarker which has been implemented digitally. The PPS can be easily administered to both healthy controls and individuals at potential risk for psychosis on a range of devices. It is feasible to use the PPS in real world settings to assess individuals with emerging mental disorders. The next phase of research should be to include the PPS in large-scale international cohort studies to evaluate its ability to refine the prognostication of outcomes.
BACKGROUND: The Psychosis Polyrisk Score (PPS) is a potential biomarker integrating non-purely genetic risk/protective factors for psychosis that may improve identification of individuals at risk and prediction of their outcomes at the individual subject level. Biomarkers that are easy to administer are direly needed in early psychosis to facilitate clinical implementation. This study digitally implements the PPS and pilots its feasibility of use in the real world. METHODS: The PPS was implemented digitally and prospectively piloted across individuals referred for a CHR-P assessment (n = 16) and healthy controls (n = 66). Distribution of PPS scores was further simulated in the general population. RESULTS: 98.8% of individuals referred for a CHR-P assessment and healthy controls completed the PPS assessment with only one drop-out. 96.3% of participants completed the assessment in under 15 min. Individuals referred for a CHR-P assessment had high PPS scores (mean = 6.2, SD = 7.23) than healthy controls (mean = -1.79, SD = 6.78, p < 0.001). In simulated general population data, scores were normally distributed ranging from -15 (lowest risk, RR = 0.03) to 39.5 (highest risk, RR = 8912.51). DISCUSSION: The PPS is a promising biomarker which has been implemented digitally. The PPS can be easily administered to both healthy controls and individuals at potential risk for psychosis on a range of devices. It is feasible to use the PPS in real world settings to assess individuals with emerging mental disorders. The next phase of research should be to include the PPS in large-scale international cohort studies to evaluate its ability to refine the prognostication of outcomes.
Authors: P Fusar-Poli; M Tantardini; S De Simone; V Ramella-Cravaro; D Oliver; J Kingdon; M Kotlicka-Antczak; L Valmaggia; J Lee; M J Millan; S Galderisi; U Balottin; V Ricca; P McGuire Journal: Eur Psychiatry Date: 2016-12-16 Impact factor: 5.361
Authors: Cheryl M Corcoran; Facundo Carrillo; Diego Fernández-Slezak; Gillinder Bedi; Casimir Klim; Daniel C Javitt; Carrie E Bearden; Guillermo A Cecchi Journal: World Psychiatry Date: 2018-02 Impact factor: 49.548
Authors: Joaquim Radua; Valentina Ramella-Cravaro; John P A Ioannidis; Abraham Reichenberg; Nacharin Phiphopthatsanee; Taha Amir; Hyi Yenn Thoo; Dominic Oliver; Cathy Davies; Craig Morgan; Philip McGuire; Robin M Murray; Paolo Fusar-Poli Journal: World Psychiatry Date: 2018-02 Impact factor: 49.548
Authors: Helga K Ising; Wim Veling; Rachel L Loewy; Marleen W Rietveld; Judith Rietdijk; Sara Dragt; Rianne M C Klaassen; Dorien H Nieman; Lex Wunderink; Don H Linszen; Mark van der Gaag Journal: Schizophr Bull Date: 2012-04-19 Impact factor: 9.306
Authors: Paolo Fusar-Poli; Gonzalo Salazar de Pablo; Christoph U Correll; Andreas Meyer-Lindenberg; Mark J Millan; Stefan Borgwardt; Silvana Galderisi; Andreas Bechdolf; Andrea Pfennig; Lars Vedel Kessing; Therese van Amelsvoort; Dorien H Nieman; Katharina Domschke; Marie-Odile Krebs; Nikolaos Koutsouleris; Philip McGuire; Kim Q Do; Celso Arango Journal: JAMA Psychiatry Date: 2020-07-01 Impact factor: 21.596
Authors: Samuel P Leighton; Rajeev Krishnadas; Kelly Chung; Alison Blair; Susie Brown; Suzy Clark; Kathryn Sowerbutts; Matthias Schwannauer; Jonathan Cavanagh; Andrew I Gumley Journal: PLoS One Date: 2019-03-07 Impact factor: 3.240
Authors: Paolo Fusar-Poli; Nomi Werbeloff; Grazia Rutigliano; Dominic Oliver; Cathy Davies; Daniel Stahl; Philip McGuire; David Osborn Journal: Schizophr Bull Date: 2019-04-25 Impact factor: 9.306
Authors: Paolo Fusar-Poli; Christoph U Correll; Celso Arango; Michael Berk; Vikram Patel; John P A Ioannidis Journal: World Psychiatry Date: 2021-06 Impact factor: 79.683
Authors: Dominic Oliver; Chiew Meng Johnny Wong; Martin Bøg; Linus Jönsson; Bruce J Kinon; Allan Wehnert; Kristian Tore Jørgensen; Jessica Irving; Daniel Stahl; Philip McGuire; Lars Lau Raket; Paolo Fusar-Poli Journal: Transl Psychiatry Date: 2020-10-29 Impact factor: 6.222