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Behavioral and Neural Heterogeneity in OCD and Depression

强迫症和抑郁症的行为和神经异质性

基本信息

批准号：
10276501
负责人：
Emily R Stern
金额：
$ 73.7万
依托单位：
NEW YORK UNIVERSITY SCHOOL OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-08-05 至 2026-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10276501
关键词：
Address Anterior Behavior Behavioral Brain Characteristics Clinical Communities Complement Data Data Analyses Depressed mood Development Diagnosis Diagnostic Dimensions Disease Equipment and supply inventories Esthesia Etiology Functional Magnetic Resonance Imaging Future Goals Heterogeneity Human Individual Insula of Reil Interoception Intervention Investigation Link Machine Learning Major Depressive Disorder Measures Mediating Mental Depression Mental disorders Modeling Neurobiology Obsessive compulsive behavior Obsessive-Compulsive Disorder Patients Pattern Phenotype Prediction of Response to Therapy Prefrontal Cortex Prevalence Protocols documentation Research Research Domain Criteria Rest Sampling Severities Source Subgroup Symptoms Thinking Work base behavior measurement brain circuitry clinical heterogeneity comorbidity connectome data acquisition depressive symptoms disability effective therapy individual patient neurobehavioral neurobiological mechanism neuroimaging novel personalized intervention personalized medicine psychologic recruit relating to nervous system symptom cluster unsupervised learning

项目摘要

Project Summary This project investigates behavioral and neural heterogeneity in obsessive-compulsive disorder (OCD) and major depressive disorder (MDD) using hypothesis- and data-driven approaches. OCD and MDD are major sources of disability worldwide, with fewer than half of patients responding adequately to first-line treatments. Treatment may be impeded by the fact that OCD and MDD are both highly heterogeneous, with clusters of symptoms likely derived from differing psychological and neurobiological etiologies. The Research Domain Criteria (RDoC) framework seeks to address this problem in part by investigating dimensional components of behavior that span across disorders and more closely align with brain circuitry than does the multifaceted diagnostic phenotype. In the present project, we follow an RDoC approach to the study of heterogeneity by investigating relationships between behavior, clinical symptoms, and brain function using task-based and resting-state fMRI in a sample of 75 OCD patients and 75 MDD patients. Our preliminary data in OCD patients and individuals with depressive symptoms point to interoceptive sensitivity (IS) and perseverative negative thinking (PT) as dimensional components of behavior that are not only transdiagnostic but also explain important within-disorder heterogeneity; the first aim of this proposal builds on these findings by investigating associations of IS and PT with clinical symptoms, behavior, and brain function in OCD and MDD. Complementing this hypothesis-driven approach, the second aim of the project is a data-driven investigation using unsupervised machine learning (ML) to uncover neurobiological profiles that characterize variability in brain function across OCD and MDD. Building on our preliminary analysis identifying three subgroups within OCD distinguished by differential patterns of resting-state functional connectivity, we will investigate neurobiological heterogeneity across OCD and MDD and link clinical and behavioral data to neurobiological subgroups using a comprehensive ‘deep phenotyping’ approach to data acquisition and analysis. The overarching goals of both aims are to identify factors contributing to heterogeneity that can be developed as novel targets for personalized treatments based on an individual patient’s neurobehavioral profile.

项目总结