Toward identifying reproducible brain signatures of obsessive-compulsive profiles: rationale and methods for a new global initiative
Authors: Simpson Helen Blair , van den Heuvel Odile A. , Miguel Euripedes C. , Reddy Y. C. Janardhan , Stein Dan J. , Lewis-Fernández Roberto , Shavitt Roseli Gedanke , Lochner Christine , Pouwels Petra J. W. , Narayanawamy Janardhanan C. , Venkatasubramanian Ganesan , Hezel Dianne M. , Vriend Chris , Batistuzzo Marcelo C. , Hoexter Marcelo Q. , de Joode Niels T. , Costa Daniel Lucas , de Mathis Maria Alice , Sheshachala Karthik , Narayan Madhuri , van Balkom Anton J. L. M. , Batelaan Neeltje M. , Venkataram Shivakumar , Cherian Anish , Marincowitz Clara , Pannekoek Nienke , Stovezky Yael R. , Mare Karen , Liu Feng , Otaduy Maria Concepcion Garcia , Pastorello Bruno , Rao Rashmi , Katechis Martha , Van Meter Page , Wall Melanie 
Published: February 2020

AbstractBackgroundObsessive-compulsive disorder (OCD) has a lifetime prevalence of 2–3% and is a leading cause of global disability. Brain circuit abnormalities in individuals with OCD have been identified, but important knowledge gaps remain. The goal of the new global initiative described in this paper is to identify robust and reproducible brain signatures of measurable behaviors and clinical symptoms that are common in individuals with OCD. A global approach was chosen to accelerate discovery, to increase rigor and transparency, and to ensure generalizability of results.MethodsWe will study 250 medication-free adults with OCD, 100 unaffected adult siblings of individuals with OCD, and 250 healthy control subjects at five expert research sites across five countries (Brazil, India, Netherlands, South Africa, and the U.S.). All participants will receive clinical evaluation, neurocognitive assessment, and magnetic resonance imaging (MRI). The imaging will examine multiple brain circuits hypothesized to underlie OCD behaviors, focusing on morphometry (T1-weighted MRI), structural connectivity (Diffusion Tensor Imaging), and functional connectivity (resting-state fMRI). In addition to analyzing each imaging modality separately, we will also use multi-modal fusion with machine learning statistical methods in an attempt to derive imaging signatures that distinguish individuals with OCD from unaffected siblings and healthy controls (Aim #1). Then we will examine how these imaging signatures link to behavioral performance on neurocognitive tasks that probe these same circuits as well as to clinical profiles (Aim #2). Finally, we will explore how specific environmental features (childhood trauma, socioeconomic status, and religiosity) moderate these brain-behavior associations.DiscussionUsing harmonized methods for data collection and analysis, we will conduct the largest neurocognitive and multimodal-imaging study in medication-free subjects with OCD to date. By recruiting a large, ethno-culturally diverse sample, we will test whether there are robust biosignatures of core OCD features that transcend countries and cultures. If so, future studies can use these brain signatures to reveal trans-diagnostic disease dimensions, chart when these signatures arise during development, and identify treatments that target these circuit abnormalities directly. The long-term goal of this research is to change not only how we conceptualize OCD but also how we diagnose and treat it.