Literature DB >> 31204010

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

Katharine Brieger1, Gregory J M Zajac2, Anita Pandit3, Johanna R Foerster2, Kevin W Li2, Aubrey C Annis2, Ellen M Schmidt4, Chris P Clark2, Karly McMorrow2, Wei Zhou5, Jingjing Yang6, Alan M Kwong2, Andrew P Boughton2, Jinxi Wu7, Chris Scheller2, Tanvi Parikh8, Alejandro de la Vega8, David M Brazel9, Maia Frieser10, Gianna Rea-Sandin11, Lars G Fritsche2, Scott I Vrieze12, Gonçalo R Abecasis13.   

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.
Copyright © 2019 American Society of Human Genetics. All rights reserved.

Entities:  

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

Year:  2019        PMID: 31204010      PMCID: PMC6612519          DOI: 10.1016/j.ajhg.2019.05.006

Source DB:  PubMed          Journal:  Am J Hum Genet        ISSN: 0002-9297            Impact factor:   11.025


  46 in total

1.  Ancestry informative markers for fine-scale individual assignment to worldwide populations.

Authors:  Peristera Paschou; Jamey Lewis; Asif Javed; Petros Drineas
Journal:  J Med Genet       Date:  2010-10-04       Impact factor: 6.318

2.  A simple model for potential use with a misclassified binary outcome in epidemiology.

Authors:  S W Duffy; J Warwick; A R W Williams; H Keshavarz; F Kaffashian; T E Rohan; F Nili; A Sadeghi-Hassanabadi
Journal:  J Epidemiol Community Health       Date:  2004-08       Impact factor: 3.710

3.  Inferring genetic ancestry: opportunities, challenges, and implications.

Authors:  Charmaine D Royal; John Novembre; Stephanie M Fullerton; David B Goldstein; Jeffrey C Long; Michael J Bamshad; Andrew G Clark
Journal:  Am J Hum Genet       Date:  2010-05-14       Impact factor: 11.025

4.  Eye color and the prediction of complex phenotypes from genotypes.

Authors:  Fan Liu; Kate van Duijn; Johannes R Vingerling; Albert Hofman; André G Uitterlinden; A Cecile J W Janssens; Manfred Kayser
Journal:  Curr Biol       Date:  2009-03-10       Impact factor: 10.834

5.  Fast model-based estimation of ancestry in unrelated individuals.

Authors:  David H Alexander; John Novembre; Kenneth Lange
Journal:  Genome Res       Date:  2009-07-31       Impact factor: 9.043

6.  Facebook: an effective tool for participant retention in longitudinal research.

Authors:  R Mychasiuk; K Benzies
Journal:  Child Care Health Dev       Date:  2011-10-11       Impact factor: 2.508

7.  Movement toward a novel activity monitoring device.

Authors:  Hawley E Montgomery-Downs; Salvatore P Insana; Jonathan A Bond
Journal:  Sleep Breath       Date:  2011-10-06       Impact factor: 2.816

8.  Worldwide human relationships inferred from genome-wide patterns of variation.

Authors:  Jun Z Li; Devin M Absher; Hua Tang; Audrey M Southwick; Amanda M Casto; Sohini Ramachandran; Howard M Cann; Gregory S Barsh; Marcus Feldman; Luigi L Cavalli-Sforza; Richard M Myers
Journal:  Science       Date:  2008-02-22       Impact factor: 47.728

9.  The PhenX Toolkit: get the most from your measures.

Authors:  Carol M Hamilton; Lisa C Strader; Joseph G Pratt; Deborah Maiese; Tabitha Hendershot; Richard K Kwok; Jane A Hammond; Wayne Huggins; Dean Jackman; Huaqin Pan; Destiney S Nettles; Terri H Beaty; Lindsay A Farrer; Peter Kraft; Mary L Marazita; Jose M Ordovas; Carlos N Pato; Margaret R Spitz; Diane Wagener; Michelle Williams; Heather A Junkins; William R Harlan; Erin M Ramos; Jonathan Haines
Journal:  Am J Epidemiol       Date:  2011-07-11       Impact factor: 4.897

10.  The relationship of body mass index to diabetes mellitus, hypertension and dyslipidaemia: comparison of data from two national surveys.

Authors:  H E Bays; R H Chapman; S Grandy
Journal:  Int J Clin Pract       Date:  2007-05       Impact factor: 2.503

View more
  6 in total

1.  The emerging landscape of health research based on biobanks linked to electronic health records: Existing resources, statistical challenges, and potential opportunities.

Authors:  Lauren J Beesley; Maxwell Salvatore; Lars G Fritsche; Anita Pandit; Arvind Rao; Chad Brummett; Cristen J Willer; Lynda D Lisabeth; Bhramar Mukherjee
Journal:  Stat Med       Date:  2019-12-20       Impact factor: 2.373

2.  Decisional conflict among adolescents and parents making decisions about genomic sequencing results.

Authors:  Preethi Raghuram Pillai; Cynthia A Prows; Lisa J Martin; Melanie F Myers
Journal:  Clin Genet       Date:  2019-12-02       Impact factor: 4.438

Review 3.  Axes of a revolution: challenges and promises of big data in healthcare.

Authors:  Smadar Shilo; Hagai Rossman; Eran Segal
Journal:  Nat Med       Date:  2020-01-13       Impact factor: 53.440

Review 4.  Population genetic considerations for using biobanks as international resources in the pandemic era and beyond.

Authors:  Hannah Carress; Daniel John Lawson; Eran Elhaik
Journal:  BMC Genomics       Date:  2021-05-17       Impact factor: 3.969

5.  Changing the mindset for precision medicine: from incentivized biobanking models to genomic data.

Authors:  Daniel Tigard
Journal:  Genet Res (Camb)       Date:  2019-10-31       Impact factor: 1.588

6.  A survey of direct-to-consumer genotype data, and quality control tool (GenomePrep) for research.

Authors:  Chang Lu; Bastian Greshake Tzovaras; Julian Gough
Journal:  Comput Struct Biotechnol J       Date:  2021-06-27       Impact factor: 7.271

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.