Zornitza Stark, David Glazer, Oliver Hofmann, Augusto Rendon, Christian R. Marshall, Geoffrey S. Ginsburg, Chris Lunt, Naomi Allen, Mark Effingham, Jillian Hastings Ward, Sue L. Hill, Raghib Ali, Peter Goodhand, Angela Page, Heidi L. Rehm, Kathryn N. North, Richard H. Scott
{"title":"A call to action to scale up research and clinical genomic data sharing","authors":"Zornitza Stark, David Glazer, Oliver Hofmann, Augusto Rendon, Christian R. Marshall, Geoffrey S. Ginsburg, Chris Lunt, Naomi Allen, Mark Effingham, Jillian Hastings Ward, Sue L. Hill, Raghib Ali, Peter Goodhand, Angela Page, Heidi L. Rehm, Kathryn N. North, Richard H. Scott","doi":"10.1038/s41576-024-00776-0","DOIUrl":null,"url":null,"abstract":"<p>Genomic data from millions of individuals have been generated worldwide to drive discovery and clinical impact in precision medicine. Lowering the barriers to using these data collectively is needed to equitably realize the benefits of the diversity and scale of population data. We examine the current landscape of global genomic data sharing, including the evolution of data sharing models from data aggregation through to data visiting, and for certain use cases, cross-cohort analysis using federated approaches across multiple environments. We highlight emerging examples of best practice relating to participant, patient and community engagement; evolution of technical standards, tools and infrastructure; and impact of research and health-care policy. We outline 12 actions we can all take together to scale up efforts to enable safe global data sharing and move beyond projects demonstrating feasibility to routinely cross-analysing research and clinical data sets, optimizing benefit.</p>","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"5 1","pages":""},"PeriodicalIF":39.1000,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Reviews Genetics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1038/s41576-024-00776-0","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0
Abstract
Genomic data from millions of individuals have been generated worldwide to drive discovery and clinical impact in precision medicine. Lowering the barriers to using these data collectively is needed to equitably realize the benefits of the diversity and scale of population data. We examine the current landscape of global genomic data sharing, including the evolution of data sharing models from data aggregation through to data visiting, and for certain use cases, cross-cohort analysis using federated approaches across multiple environments. We highlight emerging examples of best practice relating to participant, patient and community engagement; evolution of technical standards, tools and infrastructure; and impact of research and health-care policy. We outline 12 actions we can all take together to scale up efforts to enable safe global data sharing and move beyond projects demonstrating feasibility to routinely cross-analysing research and clinical data sets, optimizing benefit.
期刊介绍:
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