
Methods
Team
Emma Nichols
University of Southern California
Epidemiologist & Domain Lead
Kayleigh Keller
Colorado State University
Biostatistician
Yao-Yi Chiang
University of Minnesota
Computer Scientist
Erik Meijer
University of Southern California
Economist
Birgit G. Claus Henn
Boston University
Environmental Epidemiologist
Overview
The Methods team focuses on key statistical and methodological issues that pose important challenges to research on Alzheimer’s disease and related dementias (AD/ADRD) and the exposome across the six substantive GECC exposome domains.
Research in this area is cross-cutting, multidisciplinary, and collaborative, focusing on topics impacting multiple domains, including the appropriate measurement of exposome domains, and the development and use of appropriate models to describe the associations between exposures and AD/ADRD outcomes.
The Methods core has three overarching aims:
Priorities
Community Insights
In the fall of 2024, the GECC hosted a series of town hall meetings with hundreds of unique participants. These meetings yielded critical insights for the Methods domain, including highlighting key themes and gaps in research. Even among conversations that focused on specific exposome domains, such as the social environment, questions related to methodological approaches were pervasive throughout discussions.
Key Themes
- Measurement of exposures and outcomes
- Lifecourse research and cumulative exposures
- Interactions between exposures
- Mixture methods
- Harmonization
Gaps in research
- Comparisons and documentation of methods for assessing lifecourse exposures and interactions or mixtures,
- Best practices for conducting harmonized research across cohorts or contexts.
- Consideration of mixtures across and within domains
Steps to Improve Methods in Exposome Research
- Create documentation regarding best practices
- Discuss comparisons of different existing methodologic approaches
- Conduct simulation studies to evaluate the performance of different methods for different questions or types of data
- Evaluate the performance of innovative approaches to address the limitations of existing methods




