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Sökning: WFRF:(Lepamets Maarja)

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1.
  • Laisk, Triin, et al. (författare)
  • The genetic architecture of sporadic and multiple consecutive miscarriage.
  • 2020
  • Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Miscarriage is a common, complex trait affecting ~15% of clinically confirmed pregnancies. Here we present the results of large-scale genetic association analyses with 69,054 cases from five different ancestries for sporadic miscarriage, 750 cases of European ancestry for multiple (≥3) consecutive miscarriage, and up to 359,469 female controls. We identify one genome-wide significant association (rs146350366, minor allele frequency (MAF) 1.2%, P=3.2 × 10-8, odds ratio (OR)=1.4) for sporadic miscarriage in our European ancestry meta-analysis and three genome-wide significant associations for multiple consecutive miscarriage (rs7859844, MAF=6.4%, P=1.3 × 10-8, OR=1.7; rs143445068, MAF=0.8%, P=5.2 × 10-9, OR=3.4; rs183453668, MAF=0.5%, P=2.8 × 10-8, OR=3.8). We further investigate the genetic architecture of miscarriage with biobank-scale Mendelian randomization, heritability, and genetic correlation analyses. Our results show that miscarriage etiopathogenesis is partly driven by genetic variation potentially related to placental biology, and illustrate the utility of large-scale biobank data for understanding this pregnancy complication.
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2.
  • Reisberg, Sulev, et al. (författare)
  • Translating genotype data of 44,000 biobank participants into clinical pharmacogenetic recommendations : challenges and solutions
  • 2019
  • Ingår i: Genetics in Medicine. - : NATURE PUBLISHING GROUP. - 1098-3600 .- 1530-0366. ; 21:6, s. 1345-1354
  • Tidskriftsartikel (refereegranskat)abstract
    • Purpose: Biomedical databases combining electronic medical records and 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. Methods: We developed and tested algorithms for translation of preexisting genotype data of over 44,000 participants of the Estonian biobank into pharmacogenetic recommendations. We compared the results obtained by genome sequencing, exome sequencing, and genotyping using microarrays, and evaluated the impact of pharmacogenetic reporting based on drug prescription statistics in the Nordic countries and Estonia. Results: Our most striking result was that the performance of genotyping arrays is similar to that of 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. Conclusion: We find that microarrays are a cost-effective solution for creating preemptive pharmacogenetic reports, and with slight modifications, existing databases can be applied for automated pharmacogenetic decision support for clinicians.
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