Genes for Good: Engaging the Public in Genetics Research via Social Media

Katharine Brieger, Gregory J.M. Zajac, Anita Pandit, Johanna R. Foerster, Kevin W. Li, Aubrey C. Annis, Ellen M. Schmidt, Chris P. Clark, Karly McMorrow, Wei Zhou, Jingjing Yang, Alan M. Kwong, Andrew P. Boughton, Jinxi Wu, Chris Scheller, Tanvi Parikh, Alejandro de la Vega, David M. Brazel, Maia Frieser, Gianna Rea-SandinLars G. Fritsche, Scott I. Vrieze, Gonçalo R. Abecasis

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The Genes for Good study uses social media to engage a large, diverse participant pool in genetics research and education. Health history and daily tracking surveys are administered through a Facebook application, and participants who complete a minimum number of surveys are mailed a saliva sample kit (“spit kit”) to collect DNA for genotyping. As of March 2019, we engaged >80,000 individuals, sent spit kits to >32,000 individuals who met minimum participation requirements, and collected >27,000 spit kits. Participants come from all 50 states and include a diversity of ancestral backgrounds. Rates of important chronic health indicators are consistent with those estimated for the general U.S. population using more traditional study designs. However, our sample is younger and contains a greater percentage of females than the general population. As one means of verifying data quality, we have replicated genome-wide association studies (GWASs) for exemplar traits, such as asthma, diabetes, body mass index (BMI), and pigmentation. The flexible framework of the web application makes it relatively simple to add new questionnaires and for other researchers to collaborate. We anticipate that the study sample will continue to grow and that future analyses may further capitalize on the strengths of the longitudinal data in combination with genetic information.

Original languageEnglish (US)
Pages (from-to)65-77
Number of pages13
JournalAmerican Journal of Human Genetics
Volume105
Issue number1
DOIs
StatePublished - Jul 3 2019

Keywords

  • asthma
  • body mass index
  • complex traits
  • diabetes
  • direct to participant research
  • genome-wide association study
  • genotyping array
  • participant engagement
  • population study
  • social media

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't

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