gms | German Medical Science

65th Annual Meeting of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS), Meeting of the Central European Network (CEN: German Region, Austro-Swiss Region and Polish Region) of the International Biometric Society (IBS)

06.09. - 09.09.2020, Berlin (online conference)

Polygenic risk scores – Is there a need for a more accurate classification within ethnicities?

Meeting Abstract

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  • Tanja K. Rausch - Institut für Medizinische Biometrie und Statistik, Universität zu Lübeck, Universitätsklinikum Schleswig-Holstein, Campus Lübeck, Lübeck, GermanyKlinik für Kinder- und Jugendmedizin, Universität zu Lübeck, Universitätsklinikum Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
  • Inke R. König - Institut für Medizinische Biometrie und Statistik, Universität zu Lübeck, Universitätsklinikum Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
  • Wolfgang Göpel - Klinik für Kinder- und Jugendmedizin, Universität zu Lübeck, Universitätsklinikum Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
  • Damian Gola - Institut für Medizinische Biometrie und Statistik, Universität zu Lübeck, Universitätsklinikum Schleswig-Holstein, Campus Lübeck, Lübeck, Germany

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 65th Annual Meeting of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS), Meeting of the Central European Network (CEN: German Region, Austro-Swiss Region and Polish Region) of the International Biometric Society (IBS). Berlin, 06.-09.09.2020. Düsseldorf: German Medical Science GMS Publishing House; 2021. DocAbstr. 367

doi: 10.3205/20gmds251, urn:nbn:de:0183-20gmds2511

Veröffentlicht: 26. Februar 2021

© 2021 Rausch et al.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe http://creativecommons.org/licenses/by/4.0/.


Gliederung

Text

Polygenic risk scores for complex diseases are widely used in preclinical and clinical research to stratify individuals according to their genetic risk for targeted prevention, therapy, or prognosis. However, they are usually derived and validated within a specific ethnic background, and translation into other ethnicities has been shown to be problematic. Furthermore, even the transfer between populations in the same country can be challenging, as shown, for instance, for Finland [1] and Great Britain [2].

According to former studies, at least slight genetic differences are present between different parts of Germany [3]. However, the implications for polygenic risk scores have not been evaluated so far. Therefore, this study aims at investigating the impact of geographic regions within Germany on the distribution of polygenic risk scores for common complex diseases.

The German Neonatal Network examines the development of very low birth weight infants with 64 study centers spread across Germany. Umbilical cord tissue frozen after birth is used to genotype the DNA of the infants. Affymetrix AxiomTM Genome-Wide CEU 1 Array Plate 2.0 and Illumina Infinium® Global Screening Array-24 v1.0/v2.0 were used for chip genotyping.

The continuously growing database already contains genetic data of 10,259 (51,2%) from 20,000 included very low birth weight infants. Within this database, we construct polygenic risk scores for common complex diseases, based on the GWAS Catalog, and compare their distributions between various areas within Germany. Results will provide insight into the transferability of polygenic risk scores between populations but also into the genetic architecture of the investigated traits.

The authors declare that they have no competing interests.

The authors declare that a positive ethics committee vote has been obtained.


References

1.
Kerminen S, Martin AR, et al. Geographic Variation and Bias in the Polygenic Scores of Complex Diseases and Traits in Finland. Am J Hum Genet. 2019; 104(6):1169-81.
2.
Haworth S, Mitchell R et al. Apparent latent structure within the UK Biobank sample has implications for epidemiological analysis. Nat Commun. 2019; 10:333.
3.
Steffens M, Lamina C, et al. SNP-Based Analysis of Genetic Substructure in the German Population. Hum Hered. 2006; 62(1):20-9.