Dimensional RDoC Modeling across the Range of Negative Mood Dysfunction

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DESCRIPTION (provided by applicant): Integration of dimensional parameters from brain, performance, and self and other-report measures is key towards refining intermediate phenotypes (IPs) within the Research Domain Criteria (RDoC) proposal by NIMH. Currently, IPs do not align well with the disjunctive categorical diagnostic systems. In reality, the symptoms of Major Depressive Disorder (MDD) and Bipolar Disorder (BD) NOS and subthreshold conditions have significant overlap in symptoms and impact. There are likely shared disruptions in cognitive and affective systems (IPs) that may confer risk for these disruptions in negative mood. IPs link genes to brain biology and physiology; IPs also link to subsets of different mood disorder groups. The proposal is a synergistic, integrated and applied series of investigations of core domains in any mood disorders (AMD) for 120 individuals, in remission to diminish state symptom confounds, including all BD, MDD, Mood Disorder, NOS, Adjustment Disorder with Depressed Mood, and subthreshold Mood groups. These AMD subjects will be combined with a healthy control (HC) group of 55 individuals. Domains of the RDoC matrix are measured using self-other- report, other/clinician report, lab-based performance, and brain physiology/circuit (fMRI) biomarker measures to address two Aims and two Exploratory Aims. Scale development tools are used to demonstrate scale reliability and construct validity. Advanced modeling and stratification techniques from biomedical engineering and statistical machine learning will identify across-diagnosis subgroups that share core dimensions of dysfunction, which can be linked to domain and subdomain abnormalities and impact of illness. Aim 1 studies core (shared) dysfunction in elevated Fear to Acute Threat (1.1) using anxiety measures/Neuroticism facets, emotion processing biases, amygdala and limbic reactivity to negative faces in the Emotion Faces Matching Task, and functional connectivity approaches. There is also a core dysfunction in Loss and Loss anticipation (1.2) using negative environmental loss/stresses, negative memory biases, and NAcc and OFC activation to anticipation of loss in the Monetary Incentive Delay (MID) task, and functional connectivity approaches. Aim 2 studies core dysfunction in four Cognitive System subdomains, Attention (2.1), Working Memory (2.2), Cognitive Control (Inhibition, 2.3), and Cognitive Control (Interference, 2.4) measured with self and observer reports, performance, and VL and DLPFC and DACC activation in the N-Back and Parametric Go/No-go/Stop tasks during fMRI. An Exploratory Aim in subdomain stability is conducted in 40 AMD stratified on functional outcome plus 20 HC. Exploratory Aim 2 is collection of blood for later targeted gene experiments and/or sharing in larger GWAS studies. In summary, the present proposal uses dimensional modeling anchored in core features of dysfunction across AMD spectrum, but also pursues areas of differentiation based upon diagnosis, domain and functioning. Our strategy is optimal for the study of RDoC dimensional approaches for classification of AMD spectrum by integrating and extending the existing knowledge base, and integrating with commonly used clinical tools and genetic studies for ready translation of novel findings.