Data
Our current projects:
Can social connection, acceptance, and belonging reduce disparities in depression symptoms?
Project leads: Katherine N. Thompson
Major collaborators: Moritz Herle (King’s College London), Erin Dunn (Purdue, Dept of Sociology), Evalina T. Akimova (Purdue, Dept of Sociology), Shawn Bauldry (Purdue, Dept of Sociology), and Elisabeth Noland (University of Illinois Chicago)
Objective: The overall aim of this project is to understand how social connection, acceptance, and inclusion in adolescence can mitigate the association between at-risk characteristics and depression symptoms in the short (one-year) and long term (one decade). We use the health disparity framework to estimate how social connection can mediate the association between genetic vulnerability, socio-economic position, sex, and race, and depression symptoms.
Illuminating the complex interplay of risk factors for depression within a large-scale US longitudinal cohort
Project leads: Katherine N. Thompson
Major collaborators: Felix C Tropf (University College London), Baptist Couvy-Duchesne (University of Queensland), and Hong Lee (University of South Australia)
Research questions:
How do prominent individual-level risk factors for depression contribute to concurrent and longitudinal symptom occurrence?
To what extent does the wider environment add to the explanation of depression symptoms
Objective: We leverage data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) and use innovative matrix-based methods to assess how large-scale environmental data can influence depression symptoms in adolescence and adulthood.
Preprint: Thompson, K. N., Couvy-Duchesne, B., Geurgas, R., Newman, S., Sheppard, L., Wedow, R., & Tropf, F. C. (2024, July 23). Drawing parallels across complex trait genomics and social science to combine environmental and genetic risk factors for depression in a longitudinal US cohort. OSF. doi: 10.17605/OSF.IO/AKZHD
Gene-by-environment interactions in smoking: Insights from human genetics
Project leads: Yeongmi Jeong
Major collaborators: Michel Nivard (The University of Bristol), Andrea Ganna (University of Helsinki), Brad Verhulst (Texas A&M)
Objective: We explore gene by environment (G×E) interactions using the GWAS summary statistics for smoking initiation across contextual subgroups, including gender, region, and birthyear cohort.
Summary: This project investigates gene-by-environment (G×E) interactions in smoking behavior, with a focus on smoking initiation. While both genetic and environmental influences on smoking are well established, evidence for their interaction remains limited. The study aims to explore whether individuals with different genetic predispositions respond differently to environmental contexts that influence smoking behavior. Using GWAS summary statistics, the project examines smoking initiation across contextual subgroups defined by region, gender, and birth year. If confirmed, such interactions could provide valuable insights into the development of smoking, address public health concerns, and shed light on the broader debate over the relative roles of nature and nurture in shaping human behavior.
