1 Victor TA, et al. BMJ Open 2018;8:e016620. doi:10.1136/bmjopen-2017-016620 Open Access Tulsa 1000: a naturalistic study protocol for multilevel assessment and outcome prediction in a large psychiatric sample Teresa A Victor, 1 Sahib S Khalsa, 1,2 W Kyle Simmons, 1,2 Justin S Feinstein, 1,2 Jonathan Savitz, 1,2 Robin L Aupperle, 1,2 Hung-Wen Yeh, 1 Jerzy Bodurka, 1,3 Martin P Paulus 1 To cite: Victor TA, Khalsa SS, Simmons WK, et al. Tulsa 1000: a naturalistic study protocol for multilevel assessment and outcome prediction in a large psychiatric sample. BMJ Open 2018;8:e016620. doi:10.1136/ bmjopen-2017-016620 ► Prepublication history and additional material for this paper are available online. To view these fles, please visit the journal online (http://dx.doi. org/10.1136/bmjopen-2017- 016620). Received 3 March 2017 Revised 7 November 2017 Accepted 9 November 2017 1 Laureate Institute for Brain Research, Tulsa, Oklahoma, USA 2 Oxley College of Health Sciences, University of Tulsa, Tulsa, Oklahoma, USA 3 Stephenson School of Biomedical Engineering, The University of Oklahoma, Tulsa, Oklahoma, USA Correspondence to Dr Teresa A Victor; tvictor@laureateinstitute.org Protocol ABSTRACT Introduction Although neuroscience has made tremendous progress towards understanding the basic neural circuitry underlying important processes such as attention, memory and emotion, little progress has been made in applying these insights to psychiatric populations to make clinically meaningful treatment predictions. The overall aim of the Tulsa 1000 (T-1000) study is to use the NIMH Research Domain Criteria framework in order to establish a robust and reliable dimensional set of variables that quantifes the positive and negative valence, cognition and arousal domains, including interoception, to generate clinically useful treatment predictions. Methods and analysis The T-1000 is a naturalistic study that will recruit, assess and longitudinally follow 1000 participants, including healthy controls and treatment- seeking individuals with mood, anxiety, substance use and eating disorders. Each participant will undergo interview, behavioural, biomarker and neuroimaging assessments over the course of 1 year. The study goal is to determine how disorders of affect, substance use and eating behaviour organise across different levels of analysis (molecules, genes, cells, neural circuits, physiology, behaviour and self-report) to predict symptom severity, treatment outcome and long-term prognosis. The data will be used to generate computational models based on Bayesian statistics. The fnal end point of this multilevel latent variable analysis will be standardised assessments that can be developed into clinical tools to help clinicians predict outcomes and select the best intervention for each individual, thereby reducing the burden of mental disorders, and taking psychiatry a step closer towards personalised medicine. Ethics and dissemination Ethical approval was obtained from Western Institutional Review Board screening protocol #20101611. The dissemination plan includes informing health professionals of results for clinical practice, submitting results to journals for peer-reviewed publication, presenting results at national and international conferences and making the dataset available to researchers and mental health professionals. Trial registration number NCT02450240; Pre-results. INTRODUCTION  Mood 1 and anxiety 2 disorders are the most common form of mental illness and represent one of the biggest health issues worldwide, accounting for approximately US$16 trillion in lost productivity or 25% of the global gross domestic product over the next 20 years. 3 Epidemiological data estimate the lifetime prevalence of major depressive disorder (MDD) at about 18% and the 12-month prev- alence at 7%. 4 Both MDD and anxiety disor- ders are associated with significant medical comorbidities 5 including substance use (SU) and eating disorders (ED), which further exacerbate the cost and suffering associated with these disorders. The lifetime preva- lence of ED is comparatively lower at <3.5% 6 ; however, individuals exhibit extreme changes in body physique together with some of the highest mortality rates of all psychiatric disor- ders. 7 8 Furthermore, most patients fail to remit or recover following treatment and up Strengths and limitations of this study ► The study uses a comprehensive approach across multiple units of analysis for phenotyping. ► The study focuses on a dimensional psychopathology that cuts across traditional psychiatric diagnoses. ► The study uses novel statistical approaches to identify and replicate latent constructs within a large and complex dataset. ► The study does not include controlled treatment interventions and is a longitudinal observational study, which requires large numbers of participants to yield statistically signifcant results and may experience higher attrition rates over the course of the study compared with a cross-sectional study. ► The study recruitment aims to generate a representative sample of a local Midwestern community in the USA, including subsamples selected to represent the US community at large, however the results may not be generalisable to individuals with mood, substance use and eating disorders in other regions of the USA or worldwide due to factors such as access to and quality of healthcare or demographic, social or cultural differences.