Harmonising and linking biomedical and clinical data across disparate data archives to enable integrative cross-biobank research

A wealth of biospecimen samples are stored in modern globally distributed biobanks. Biomedical researchers worldwide need to be able to combine the available resources to improve the power of large-scale studies. A prerequisite for this effort is to be able to search and access phenotypic, clinical...

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Published in:European journal of human genetics : EJHG Vol. 24; no. 4; pp. 521 - 528
Main Authors: Spjuth, Ola, Krestyaninova, Maria, Hastings, Janna, Shen, Huei-Yi, Heikkinen, Jani, Waldenberger, Melanie, Langhammer, Arnulf, Ladenvall, Claes, Esko, Tõnu, Persson, Mats-Åke, Heggland, Jon, Dietrich, Joern, Ose, Sandra, Gieger, Christian, Ried, Janina S, Peters, Annette, Fortier, Isabel, de Geus, Eco J C, Klovins, Janis, Zaharenko, Linda, Willemsen, Gonneke, Hottenga, Jouke-Jan, Litton, Jan-Eric, Karvanen, Juha, Boomsma, Dorret I, Groop, Leif, Rung, Johan, Palmgren, Juni, Pedersen, Nancy L, McCarthy, Mark I, van Duijn, Cornelia M, Hveem, Kristian, Metspalu, Andres, Ripatti, Samuli, Prokopenko, Inga, Harris, Jennifer R
Format: Journal Article
Language:English
Published: England Nature Publishing Group 01-04-2016
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Summary:A wealth of biospecimen samples are stored in modern globally distributed biobanks. Biomedical researchers worldwide need to be able to combine the available resources to improve the power of large-scale studies. A prerequisite for this effort is to be able to search and access phenotypic, clinical and other information about samples that are currently stored at biobanks in an integrated manner. However, privacy issues together with heterogeneous information systems and the lack of agreed-upon vocabularies have made specimen searching across multiple biobanks extremely challenging. We describe three case studies where we have linked samples and sample descriptions in order to facilitate global searching of available samples for research. The use cases include the ENGAGE (European Network for Genetic and Genomic Epidemiology) consortium comprising at least 39 cohorts, the SUMMIT (surrogate markers for micro- and macro-vascular hard endpoints for innovative diabetes tools) consortium and a pilot for data integration between a Swedish clinical health registry and a biobank. We used the Sample avAILability (SAIL) method for data linking: first, created harmonised variables and then annotated and made searchable information on the number of specimens available in individual biobanks for various phenotypic categories. By operating on this categorised availability data we sidestep many obstacles related to privacy that arise when handling real values and show that harmonised and annotated records about data availability across disparate biomedical archives provide a key methodological advance in pre-analysis exchange of information between biobanks, that is, during the project planning phase.
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These authors contributed equally to this work.
ISSN:1018-4813
1476-5438
1476-5438
DOI:10.1038/ejhg.2015.165