Connecting cohorts of Finnish biobanks creates a research resource for the study of healthy ageing
Eklund, Niina; Pätsi, Salla-Maaria; Lehtiniemi, Heli; Rohkimainen, Samppa; Kivelä, Juha; Öhman, Hanna; Sauramo, Minttu; Sutinen, Kyösti; Keskinarkaus, Anja; Terho, Perttu; Seppänen, Tapio; Nyberg, Pia; Männikkö, Minna; Silander, Kaisa (2024-03-04)
Sage publications
04.03.2024
Eklund N, Pätsi S-M, Lehtiniemi H, et al. Connecting cohorts of Finnish biobanks creates a research resource for the study of healthy ageing. Scandinavian Journal of Public Health. 2024;0(0). doi:10.1177/14034948241228482
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© Author(s) 2024. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202405203746
https://urn.fi/URN:NBN:fi:oulu-202405203746
Tiivistelmä
Abstract
Aims:
Connecting cohorts with biobanks is a Finnish biobank collaboration, creating an infrastructure for the study of healthy ageing. We aimed to develop a model for data integration and harmonisation between different biobanks with procedures for joint access.
Methods:
The heart of the collaboration is the integrated datasets formed by using data from three biobanks: (a) Arctic Biobank, hosting regional birth cohorts and cohorts of elderly; (b) hospital-affiliated Borealis Biobank of Northern Finland; and (c) THL Biobank, hosting population-based cohorts. The datasets were created by developing a data dictionary, harmonising cohort data and with a joint pseudonymisation process.
Results:
The connecting cohorts with biobanks resource at its widest consists altogether of almost 1.4 million individuals from collaborating biobanks. Utilising data from 107,000 cohort participants, we created harmonised datasets that contain attributes describing metabolic risk and frailty for studies of healthy ageing. These data can be complemented with medical data available from Biobank Borealis and with samples taken at hospital settings for approximately 38,000 cohort participants. In addition, the harmonised connecting cohorts with biobanks datasets can be expanded with supplementary data and samples from the collaborating biobanks.
Conclusions:
The connecting cohorts with biobanks datasets provide a unique resource for research on ageing-related personalised healthcare and for real-world evidence studies. Following the FAIR principles on findability, accessibility, interoperability, and reusability, the reused and harmonised datasets are findable and made accessible for researchers. The same approach can be further utilised to develop additional datasets for other research topics.
Aims:
Connecting cohorts with biobanks is a Finnish biobank collaboration, creating an infrastructure for the study of healthy ageing. We aimed to develop a model for data integration and harmonisation between different biobanks with procedures for joint access.
Methods:
The heart of the collaboration is the integrated datasets formed by using data from three biobanks: (a) Arctic Biobank, hosting regional birth cohorts and cohorts of elderly; (b) hospital-affiliated Borealis Biobank of Northern Finland; and (c) THL Biobank, hosting population-based cohorts. The datasets were created by developing a data dictionary, harmonising cohort data and with a joint pseudonymisation process.
Results:
The connecting cohorts with biobanks resource at its widest consists altogether of almost 1.4 million individuals from collaborating biobanks. Utilising data from 107,000 cohort participants, we created harmonised datasets that contain attributes describing metabolic risk and frailty for studies of healthy ageing. These data can be complemented with medical data available from Biobank Borealis and with samples taken at hospital settings for approximately 38,000 cohort participants. In addition, the harmonised connecting cohorts with biobanks datasets can be expanded with supplementary data and samples from the collaborating biobanks.
Conclusions:
The connecting cohorts with biobanks datasets provide a unique resource for research on ageing-related personalised healthcare and for real-world evidence studies. Following the FAIR principles on findability, accessibility, interoperability, and reusability, the reused and harmonised datasets are findable and made accessible for researchers. The same approach can be further utilised to develop additional datasets for other research topics.
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