Computational examination of RDoC threat and reward constructs in a representative, predominantly low-income, longitudinal sample at increased risk for internalizing disorders (Admin Supplement)

NIH RePORTER · NIH · R01 · $311,501 · view on reporter.nih.gov ↗

Abstract

ABSTRACT Depression and anxiety are prevalent, debilitating, and poorly understood disorders. RDoC charts the nature of these conditions across multiple units, but the domains are based on expert consensus, permitting bias and missed opportunities. Moreover, little is known about how adversity affects RDoC constructs and contributes to psychopathology. Thus, there is a critical need to rigorously evaluate RDoC domains in developmental samples from diverse backgrounds at increased risk for exposure to adversity and later psychopathology. We will use data-driven analytics to design, apply and validate multilevel-multimodal models of Threat and Reward constructs in an existing longitudinal cohort at risk for psychopathology. To predict internalizing symptoms, we will identify biotypes cross-sectionally and examine the longitudinal plasticity of RDoC-informed biotypes. Harsh social-ecological conditions will be deeply assessed and used to forecast the onset/intensification of internalizing symptoms at multiple units. We will assess 500 young adults from The Future of Families and Child Wellbeing Study (FFCWS), an ongoing study of children born to predominantly low-income families. Attributes of the FFCWS are: 1) children were assessed at birth, 1, 3, 5, 9, 15 years; 2) the sample is representative of people born in cities and, thus, unlike almost all other neuroimaging research, findings are generalizable; 3) Although a full range of incomes and race/ethnicities are represented, there is substantial representation of low-income families and Black/African-American families, populations often under-represented in research; and 4) participants are entering early adulthood, a period of heightened risk for psychopathology. We will assess Threat and Reward at four units of analysis: symptoms, task-based behaviors, and brain and link these units to exposure to adversity. The central hypothesis is that the RDoC Threat and Reward constructs will each cluster across individuals and units, are distinct from each other, and have specific socio-ecological predictors. We will examine multisource/multimodal data structure in 500 participants longitudinally at two timepoints, ages 22 and 24. Our transdisciplinary team of experts positions us well to elucidate the structure of the Threat and Reward constructs and map risk for internalizing biotypes. However, due to 18+ months of COVID restrictions and impacts on participation, as well as increased costs for participation, recruitment requires more resources than pre-COVID, particularly to recover recruitment milestones after 18+ lost months of recruitment time. To achieve our recruitment goals and obtain necessary statistical power, the current supplement will add three more recruiters and three more staff members for data collection to increase our recruitment and visits capacity dramatically. By deeply phenotyping a large cohort enriched for low income and African American participants, we will determine the validi...

Key facts

NIH application ID
10978276
Project number
3R01MH121079-05S1
Recipient
UNIVERSITY OF MICHIGAN AT ANN ARBOR
Principal Investigator
Luke Williamson Hyde
Activity code
R01
Funding institute
NIH
Fiscal year
2024
Award amount
$311,501
Award type
3
Project period
2019-08-15 → 2025-06-30