Linking a Population Biobank with National Health  Registries—The Estonian Experience

Leitsalu, Liis; Alavere, Helene; Tammesoo, Mari‐Liis; Leego, Erkki; Metspalu, Andres

doi:10.3390/jpm5020096

Cited by 51 publications

(41 citation statements)

References 5 publications

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“…The population-based EGCUT biobank maintains blood DNA samples and a multitude of associated phenotypic features (including demographic info) from all over Estonia [18,19]. Genotype information for the EGCUT cohort ( Estonian cohort ) was collected with Illumina Human OMNIExpress or 370CNV BeadChip genome-wide chips.…”

Section: Methodsmentioning

confidence: 99%

MixFit: Methodology for Computing Ancestry-Related Genetic Scores at the Individual Level and Its Application to the Estonian and Finnish Population Studies

et al. 2017

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Ancestry information at the individual level can be a valuable resource for personalized medicine, medical, demographical and history research, as well as for tracing back personal history. We report a new method for quantitatively determining personal genetic ancestry based on genome-wide data. Numerical ancestry component scores are assigned to individuals based on comparisons with reference populations. These comparisons are conducted with an existing analytical pipeline making use of genotype phasing, similarity matrix computation and our addition—multidimensional best fitting by MixFit. The method is demonstrated by studying Estonian and Finnish populations in geographical context. We show the main differences in the genetic composition of these otherwise close European populations and how they have influenced each other. The components of our analytical pipeline are freely available computer programs and scripts one of which was developed in house (available at: www.geenivaramu.ee/en/tools/mixfit).

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Section: Methodsmentioning

confidence: 99%

MixFit: Methodology for Computing Ancestry-Related Genetic Scores at the Individual Level and Its Application to the Estonian and Finnish Population Studies

et al. 2017

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“…The Estonian Biobank is a research-oriented biobank containing longitudinal data and biological samples, including DNA, for 5% of the adult population of Estonia. Participants of the biobank have signed a broad informed consent which allows the Estonian Genome Center to continuously update their records through periodical linking to central electronic health record databases and local hospital information systems 11 . Of the biobank participants, 8,132 have been genotyped using the HumanOmniExpress beadchip (OMNI) and 33,157 using the Global Screening Array (GSA) from Illumina.…”

Section: Overview Of Genetic Datamentioning

confidence: 99%

Translating genotype data of 44,000 biobank participants into clinical pharmacogenetic recommendations: challenges and solutions

Reisberg

Krebs

Kals

et al. 2018

Preprint

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A telephone number and e-mail address to whom correspondence concerning the manuscript should be sent lili.milani@ut.ee +372 5304 5400 2 Conflict of interest notification pageConflict of interest V.M.L is a co-founder and owner of HepaPredict AB. Other authors have no conflict of interest to declare. ABSTRACT AND KEYWORDS PurposeBiomedical databases combining electronic medical records, phenotypic and genomic data constitute a powerful resource for the personalization of treatment. To leverage the wealth of information provided, algorithms are required that systematically translate the contained information into treatment recommendations based on existing genotype-phenotype associations. MethodsWe developed and tested algorithms for translation of pre-existing genotype data of over 44,000 participants of the Estonian biobank into pharmacogenetic recommendations. We compared the results obtained by whole genome sequencing, whole exome sequencing and genotyping using microarrays, and evaluated the impact of pharmacogenetic reporting based on drug prescription statistics in the Nordic countries and Estonia. ResultsOur most striking result was that the performance of genotyping arrays is similar to that of whole genome sequencing, whereas exome sequencing is not suitable for pharmacogenetic predictions. Interestingly, 99.8% of all assessed individuals had a genotype associated with increased risks to at least one medication, and thereby the implementation of pharmacogenetic recommendations based on genotyping affects at least 50 daily drug doses per 1000 inhabitants. ConclusionWe find that microarrays are a cost-effective solution for creating pre-emptive pharmacogenetic reports, and with slight modifications, existing databases can be applied for automated pharmacogenetic decision support for clinicians.

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“…The Estonian Biobank is a population-based biobank that has collected DNA samples from 51,535 individuals representing approximately 5% of the Estonian population (5). This cohort is composed of adults representative of the larger Estonian population in terms of age, sex, and geographic distribution.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive population-based genome sequencing provides insight into hematopoietic regulatory mechanisms

Guo

Nandakumar²,

Ulirsch³

et al. 2016

Preprint

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Genetic variants affecting hematopoiesis can influence commonly measured blood cell traits. To identify factors that affect hematopoiesis, we performed association studies for blood cell traits in the population-based Estonian Biobank using high coverage whole genome sequencing (WGS) in 2,284 samples and SNP genotyping in an additional ~17,000 samples.Our analyses identified 17 associations across 14 blood cell traits. Integration of WGS-based fine-mapping and complementary epigenomic data sets provided evidence for causal mechanisms at several loci, including at a novel basophil count-associated locus near the master hematopoietic transcription factor CEBPA. The fine-mapped variant at this basophil count association near CEBPA overlapped an enhancer active in common myeloid progenitors and influenced its activity. In situ perturbation of this enhancer by CRISPR/Cas9 mutagenesis in hematopoietic stem and progenitor cells demonstrated that it is necessary for and specifically regulates CEBPA expression during basophil differentiation. We additionally identified basophil count-associated variation at another more pleiotropic myeloid enhancer near GATA2, highlighting regulatory mechanisms for ordered expression of master hematopoietic regulators during lineage specification. Our study illustrates how population-based genetic studies can provide key insights into poorly understood cell differentiation processes of considerable physiologic relevance.

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Linking a Population Biobank with National Health Registries—The Estonian Experience

Cited by 51 publications

References 5 publications

MixFit: Methodology for Computing Ancestry-Related Genetic Scores at the Individual Level and Its Application to the Estonian and Finnish Population Studies

MixFit: Methodology for Computing Ancestry-Related Genetic Scores at the Individual Level and Its Application to the Estonian and Finnish Population Studies

Translating genotype data of 44,000 biobank participants into clinical pharmacogenetic recommendations: challenges and solutions

Comprehensive population-based genome sequencing provides insight into hematopoietic regulatory mechanisms

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