6533b7d8fe1ef96bd1269ad8
RESEARCH PRODUCT
Harmonising and linking biomedical and clinical data across disparate data archives to enable integrative cross-biobank research
Tõnu EskoOla SpjuthOla SpjuthHuei-yi ShenEco J. C. De GeusMats-ake PerssonAndres MetspaluJon HegglandLeif GroopLeif GroopSandra OseIsabel FortierJohan RungJohan RungClaes LadenvallDorret I. BoomsmaCornelia M. Van DuijnSamuli RipattiSamuli RipattiLinda ZaharenkoArnulf LanghammerJouke-jan HottengaAnnette PetersJanis KlovinsChristian GiegerJennifer R. HarrisJoern DietrichKristian HveemInga ProkopenkoInga ProkopenkoInga ProkopenkoJuni PalmgrenJuni PalmgrenMelanie WaldenbergerMark I. MccarthyMark I. MccarthyMark I. MccarthyJani HeikkinenNancy L. PedersenJanina S. RiedJanna HastingsJan-eric LittonJuha KarvanenJuha KarvanenGonneke WillemsenMaria Krestyaninovasubject
0301 basic medicineNetherlands Twin Register (NTR)Databases FactualComputer scienceInformation Storage and RetrievalSample (statistics)Ontology (information science)Endocrinology and DiabetesBioinformaticscomputer.software_genredata archivesArticle03 medical and health sciencesSDG 17 - Partnerships for the GoalsSDG 3 - Good Health and Well-beingGenetics/dk/atira/pure/keywords/cohort_studies/netherlands_twin_register_ntr_Use casebiomedical dataGenetics (clinical)Biological Specimen BanksGenetics & Heredity0604 GeneticsBioinformatics (Computational Biology)ta112ta1184/dk/atira/pure/sustainabledevelopmentgoals/partnershipsData scienceBiobank3. Good healthcross-biotank research030104 developmental biologyProject planningExchange of informationDisparate systemPrivacyBioinformatik (beräkningsbiologi)/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_beingclinical datacomputerData integrationdescription
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. This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
year | journal | country | edition | language |
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2015-08-26 | European Journal of Human Genetics |