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Published on: July 3, 2021
Genes for Good: Engaging the Public in Genetics Research via Social Media
Katharine Brieger1, Gregory J M Zajac2, Anita Pandit2
1Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA; Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA.
The Genes for Good study recruits over 80,000 participants via social media for genetics research. This large, diverse dataset collected via spit kits enables genetic association studies and health research.
Area of Science:
- Genomic Medicine
- Social and Behavioral Sciences
- Population Health
Background:
- The Genes for Good study leverages social media platforms to recruit a large and diverse participant cohort.
- Traditional research methods face challenges in engaging broad populations for genetic studies.
Purpose of the Study:
- To utilize social media for large-scale genetics research and education.
- To collect DNA samples and health data for genetic association studies.
- To establish a flexible framework for ongoing research and collaboration.
Main Methods:
- Recruitment and engagement of participants through a Facebook application.
- Administration of health history and daily tracking surveys.
- Collection of DNA samples via saliva kits ('spit kits') for genotyping.
- Replication of genome-wide association studies (GWASs) for traits like asthma, diabetes, BMI, and pigmentation.
Main Results:
- Engaged over 80,000 individuals, sent spit kits to over 32,000, and collected over 27,000 DNA samples by March 2019.
- Participants represent all 50 U.S. states with diverse ancestral backgrounds.
- Chronic health indicator rates align with general U.S. population estimates, though the sample is younger and has higher female representation.
Conclusions:
- The Genes for Good study demonstrates the feasibility of using social media for large-scale, diverse genetic research.
- The collected data supports genetic association studies and provides insights into population health.
- The study's flexible framework supports continued growth and future longitudinal genetic analyses.
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