Understanding Longitudinal Trajectories of Depression and Externalizing Psychopathology

Studies in this research arm utilize data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) (http://www.cpc.unc.edu/projects/addhealth), an on-going longitudinal study that recruited ~20,000 adolescents to follow repeatedly into their adult years. The study has just completed its fifth Wave of data collection.

We are primarily motivated to understand the precursors, including genetic, psychosocial, and psychological, of risk and protection from the development of depression and externalizing outcomes (e.g., substance use, antisocial behaviors). We utilize advanced longitudinal modeling techniques, such as latent class analysis and latent growth curve models, to characterize long-term, 20+ year trajectories of these outcomes in our research. We also incorporate powerful genome-wide tools (e.g., polygenic scores) to investigate the ways in which genes and psychosocial development might influence how a person develops mental health outcomes over time.

Developmental trajectories of depression in Add Health. From Li, Zhang, & Lu, 2020.

Key collaborators:

UW-Madison

Jason Fletcher (LaFollette School of Public Policy)

Lauren Schmitz (LaFollette School of Public Policy)

Qiongshi Lu, Ph.D. (Biostatistics & Medical Informatics, UW-Madison)

The DREAM BIG Research Team at McGill University

Ashley Wazana, M.D. (Psychiatry)

Alexia Jolicoeur-Martineau (Psychiatry)

Ezster Szekely, Ph.D. (Statistics & Artificial Intelligence)

California State University-Northridge

Jonathan Martinez, Ph.D. (Psychology)

Representative articles: