MSGID: 1:317/3 64b0cfa1   
   PID: hpt/lnx 1.9.0-cur 2019-01-08   
   TID: hpt/lnx 1.9.0-cur 2019-01-08   
    Participating in genetic studies is in your genes    
      
     Date:   
         July 13, 2023   
     Source:   
         University of Oxford   
     Summary:   
         Why do some people take part in genetic studies while others do   
         not? The answer may lie within our genetic makeup. According to a   
         groundbreaking study, people who participate in genetic studies are   
         genetically more likely to do so, leaving detectable 'footprints'   
         in genetics data. This breakthrough equips researchers with the   
         ability to identify and address participation bias, a significant   
         challenge in genetic research.   
      
      
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   Why do some people take part in genetic studies while others do not? The   
   answer may lie within our genetic makeup. According to a groundbreaking   
   study by Oxford's Leverhulme Centre for Demographic Science and Big Data   
   Institute, people who participate in genetic studies are genetically more   
   likely to do so, leaving detectable 'footprints' in genetics data. This   
   breakthrough equips researchers with the ability to identify and address   
   participation bias, a significant challenge in genetic research.   
      
   Stefania Benonisdottir, lead author of the study and a Doctoral candidate   
   from Oxford's Big Data Institute, explains, 'Currently, most genetic   
   studies are based on genetic databases which contain large numbers of   
   participants and a wealth of information. However, some people are more   
   likely to be included in these databases than others, which can create   
   a problem called ascertainment bias, where the genetic data collected   
   is not representative of the intended study population.'  To study this   
   link between genetics data and participation bias, the researchers turned   
   to one of the largest biomedical databases in the world, the UK Biobank   
   which contains information from half a million participants.   
      
   Using UK Biobank data, it was found there is a genetic component to   
   people's probability to participate -- that is correlated but distinct   
   from other human traits. Published today in Nature Genetics, the study   
   highlights that participation could be an important human trait that has   
   been previously underappreciated and introduces a statistical framework   
   that could lead to more accurate analyses of genetic data.   
      
   Professor Augustine Kong, senior author from the Leverhulme Centre for   
   Demographic Science and the Big Data Institute, notes, 'Ascertainment   
   bias poses a statistical challenge in genetics research, particularly   
   in the era of big data. Adjustments for this bias often rely on known   
   differences between participants and non-participants, introducing   
   imperfections when answering questions involving variables only observed   
   for participants, such as genotypes. Our study identifies detectable   
   footprints of participation bias in the genetic data of participants,   
   which can be exploited statistically to enhance research accuracy for   
   both participants and non-participants alike.'  Genome-wide association   
   studies offer important insights into the role of genetics in human   
   health and diseases. However, such studies can be affected by biases,   
   which arise when genetic databases are not representative of the intended   
   study population. Now, the identified genetic inclination to participate   
   can help scientists assess the representativeness of their study sample.   
      
   By analysing the genetic data of over 30,000 related participants   
   with white British descent from the UK Biobank, the researchers found   
   that the genetic component underlying participation in the study is   
   correlated with, but distinct from, the genetic components of traits   
   such as educational attainment and body mass index.   
      
   For example, the estimated correlation between the genetic components   
   underlying participation in the UK Biobank and educational attainment   
   is estimated to be 36.6%. This result is consistent with some of   
   the previously reported differences between the participants and the   
   non-participants, but it also shows that the participation bias is not   
   fully captured by these previously known differences. In other words,   
   participation is not simply a consequence of these other traits and   
   characteristics.   
      
   The study also found the genetic component of participation can be   
   passed down through families and may affect people's participation   
   in many different studies over their lifetimes. This highlights the   
   potential for bias in genetic research and underscores the importance   
   of accounting for such biases in study design and analysis.   
      
   Professor Melinda Mills, Director of the Leverhulme Centre for Demographic   
   Science concludes, 'As our GWAS Diversity Monitor shows, the road to   
   improve diversity in genome-wide association studies is long. However,   
   this statistical framework is a huge step in the right direction to   
   mitigate the risk of incomplete or inaccurate data analysis and ensure   
   that genetic research truly benefits everyone.'   
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   Materials provided by University_of_Oxford. Note: Content may be edited   
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   Journal Reference:   
      1. Stefania Benonisdottir, Augustine Kong. Studying the genetics of   
         participation using footprints left on the ascertained   
         genotypes. Nature Genetics, 2023; DOI: 10.1038/s41588-023-01439-2   
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   Link to news story:   
   https://www.sciencedaily.com/releases/2023/07/230713141947.htm   
      
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