<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ju, Dan</style></author><author><style face="normal" font="default" size="100%">Hui, Daniel</style></author><author><style face="normal" font="default" size="100%">Hammond, Dorothy A</style></author><author><style face="normal" font="default" size="100%">Wonkam, Ambroise</style></author><author><style face="normal" font="default" size="100%">Tishkoff, Sarah A</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Importance of Including Non-European Populations in Large Human Genetic Studies to Enhance Precision Medicine.</style></title><secondary-title><style face="normal" font="default" size="100%">Annu Rev Biomed Data Sci</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Annu Rev Biomed Data Sci</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Genetic Predisposition to Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome-Wide Association Study</style></keyword><keyword><style  face="normal" font="default" size="100%">Genotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Human genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Precision Medicine</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2022</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2022 Aug 10</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">321-339</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;One goal of genomic medicine is to uncover an individual&#039;s genetic risk for disease, which generally requires data connecting genotype to phenotype, as done in genome-wide association studies (GWAS). While there may be clinical promise to employing prediction tools such as polygenic risk scores (PRS), it currently stands that individuals of non-European ancestry may not reap the benefits of genomic medicine because of underrepresentation in large-scale genetics studies. Here, we discuss why this inequity poses a problem for genomic medicine and the reasons for the low transferability of PRS across populations. We also survey the ancestry representation of published GWAS and investigate how estimates of ancestry diversity in GWASparticipants might be biased. We highlight the importance of expanding genetic research in Africa, one of the most underrepresented regions in human genomics research, and discuss issues of ethics, resources, and technology for equitable advancement of genomic medicine.&lt;/p&gt;
</style></abstract><custom1><style face="normal" font="default" size="100%">&lt;p&gt;https://www.ncbi.nlm.nih.gov/pubmed/35576557?dopt=Abstract&lt;/p&gt;
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