David Pagliaccio, Ph.D. - US grants

Project summary: The main objectives of this project are to perform longitudinal collection of clinical, behavioral, and neuroimaging data from a cohort of adolescents with depression and anxiety disorders, as well as healthy controls; and to develop a set of analytical tools that can be used to study the developmental trajectory of brain structure and function in this population. The project builds on the ongoing collaboration of our team in a Connectomes Related to Human Disease U01 project, the Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA) study, where we have been performing extensive clinical characterization and MRI scanning with Human Connectome Project (HCP) protocols on adolescents with depression and/or anxiety disorders and healthy controls. These baseline data (current total: N=170; final target: N=225) are set to become available publicly through the HCP database. Here we propose to collect longitudinal data on this unique, thoroughly characterized cohort. Following up on these subjects will allow us to investigate the complex relationship between longitudinal changes in neural circuitry and the onset, persistence, or recurrence of depression and anxiety disorders. We will tackle this by bringing together an investigative team with strong expertise in adolescent mood disorders and in neuroimaging data analysis. The MPIs have extensive experience in developing publicly available software tools for the analysis of brain connections from diffusion MRI (Yendiki) and functional MRI (Whitfield-Gabrieli). In this project, we propose to develop robust, automated tools for segmenting deep-brain structures and white-matter pathways that are of interest in psychiatric disorders. This development will build on our prior work in unbiased methods for longitudinal morphometric and tractography analyses. We will leverage the proposed longitudinal dataset and tools for accurate delineation of individual anatomy to perform a number of novel analyses that will go beyond conventional group-wise comparisons. Specifically, we will focus on analyses that allow us to predict clinical outcomes in individual subjects based on their neural circuitry. We will use machine-learning techniques to map the normative developmental trajectory of brain structure and function in healthy adolescents, including our controls and those from the development HCP. We will then investigate how and when the trajectories of individual adolescents with depression and/or anxiety disorders deviate from this normative trajectory. The longitudinal data set that we will collect and the software tools that we will develop will be shared with the research community. Our analysis methods will be applicable beyond this cohort, and could be used to study disease mechanisms and predict outcomes in a wide range of brain-related disorders across the human lifespan.

Project Summary Major depressive disorder (MDD) is a leading cause of disability worldwide and has a peak period of onset during adolescence. Most individuals with MDD will experience multiple episodes over their life course, relating to poor outcomes, suicide risk, and large personal and public health burden. Thus, identifying mechanisms of MDD illness and course is critical to identify novel intervention targets. MDD is characterized by deficits within the RDoC Positive Valence System (PVS), particularly reward-related and motivational alterations that rely on dopamine (DA) brain systems. While DA functioning has been examined in adults using Position Emission Tomography (PET), the use of radioisotope tracers makes PET invasive and untenable for pediatric research. As an alternative, the current study leverages a novel, fast, and non-invasive MRI acquisition sensitive to neuromelanin (NM) to probe midbrain DA function in youth with remitted MDD. Further, we expect midbrain DA to contribute to alterations in key PVS domains disrupted in depression. Specifically, the current study examines effort discounting?the process by which individuals calculate the cost- benefit of expending effort to achieve reward. Effort discounting is shown in animal work to rely on midbrain DA and to activate striatal regions in human MRI studies. Deficits in effort discounting, a critical part of motivation, likely contributes to anhedonic symptoms in depression. Although alterations are noted in adult MDD, the neural encoding of effort discounting has yet to be tested in adolescents with depression. The current R21 aims to address several critical gaps by probing the PVS across multiple units of analysis in 14-17-year-olds with depression (MDD = 30) and matched healthy controls (HC = 30), capitalizing on a recently funded R01 (MH119771-01A1) for recruitment and clinical assessment. First, Aim 1 will test, for the first time, whether adolescents with MDD exhibit hypothesized reductions in DA functioning in key midbrain regions, the substantia nigra and ventral tegmental area, as indexed by NM-MRI. Further, we will examine whether adolescents with MDD exhibit blunted neural encoding of effort discounting in the ventral striatum via fMRI and will explore whether midbrain NM mediates these differences. Second, Aim 2 will test whether these neural markers improve prediction of real-world functioning in these adolescents using an innovative smartphone app for deep, digital phenotyping. This will include both unobtrusive, passive sensing of daily physical activity, as an index for motivational capacity, as well as repeated self-report of positive affective and anhedonic symptoms during everyday functioning via ecological momentary assessment. Last, Aim 3 will test the ability of these neural markers to predict the worsening of depressive and anhedonic symptoms over a 6-month follow-up. In summary, this project has the promise to identify DA and PVS deficits that contribute to depression, which, ultimately, will lead to clinical translation for innovative biological risk markers and intervention targets.