Utilization of genome data

We make extensive use the genome data from blood donors available from the Blood Service Biobank. In particular, the FinnGen project has returned genome data from over 58,000 blood donors to the Blood Service Biobank. We are now utilizing these data for the benefits of blood service activities. We also are active participants in the immunogenetics studies of FinnGen (Kurki et al 2023).

We have developed a range of bioinformatics tools for predicting major blood cell alloantigens from genome‑wide array data. We make all software tools publicly available under open-source licenses via Blood Service GitHub repositories. These include tools for:

• Extended blood groups (Hyvärinen et al. 2024)
• Blood groups, HLA, and platelet HPA types (Gleadall et al. 2025)
• KIR gene content (Ritari et al. 2022)
• Classical HLA alleles (Ritari et al. 2020)
• HLA‑E, HLA‑F, HLA‑G and MICA and MICB alleles (Tammi et al. 2024)

These tools are now used in development projects within the Blood Service to identify blood donors with rare blood and HLA types. This enables us to increase the critical number of appropriately matched blood donors matched for patients in need of rare blood groups or for leukemia patients in need of HLA-typed thrombocytes. The tools have been utilized in dissecting the genetic structure of our blood donor biobank (Clancy et al 2022; 2024).

We utilize these tools in collaborative FinnGen studies. We systematically screened the roles of KIR and HLA systems over all FinnGen phenotypes (Ritari et al 2022; 2024). We have participated in collaborative fine mapping studies on diseases such as lichen planus (Reeve et al 2024), autoimmune hypothyroidism (Reeve et al 2026), type I diabetes (Wang et al 2025) parodontitis (Salminen et al 2025) and infertility (Ruotsalainen et al 2025), all producing high-impact publications.

We are members of The Blood transfusion Genomics Consortium (BGC), an international initiative launched by Professor Willem Ouwehand (University of Cambridge, UK). BGC has developed an SNP array integrated with interpretive software that can be used to type all relevant blood groups and HLA alleles relevant in transfusion medicine. The flagship publication describing the results was published in the Blood journal (Gleadall et al 2025). The typing kit including both the array and interpretation software is now available through ThermoFisher.

Our key publications

Kurki, M. I. et al. FinnGen provides genetic insights from a well-phenotyped isolated population. Nature 613, 508–519 (2023).

Hyvärinen, K. et al. A machine-learning method for biobank-scale genetic prediction of blood group antigens. PLoS Comput. Biol. 20, e1011977 (2024).

Gleadall, N. S. et al. Array genotyping of transfusion-relevant blood cell antigens in 6946 ancestrally diverse study participants. Blood 146, 1511–1524 (2025).

Ritari, J., Hyvärinen, K., Partanen, J. & Koskela, S. KIR gene content imputation from single-nucleotide polymorphisms in the Finnish population. PeerJ 10, e12692 (2022).

Ritari, J. et al. Increasing accuracy of HLA imputation by a population-specific reference panel in a FinnGen biobank cohort. NAR Genom. Bioinform. 2, e12692 (2020).

Tammi, S. et al. Accurate multi-population imputation of MICA, MICB, HLA-E, HLA-F and HLA-G alleles from genome SNP data. PLoS Comput. Biol. 20, e1011718 (2024).

Clancy, J. et al. Blood donor biobank and HLA imputation as a resource for HLA homozygous cells for therapeutic and research use. Stem Cell Res. Ther. 13, 1–11 (2022).

Clancy, J. et al. Blood donor biobank as a resource in personalised biomedical genetic research. Eur J Hum Genet 2024 1–9 (2024) doi:10.1038/s41431-023-01528-0.

Ritari, J., Koskela, S., Hyvärinen, K. & Partanen, J. HLA-disease association and pleiotropy landscape in over 235,000 Finns. Hum. Immunol. https://doi.org/10.1016/j.humimm.2022.02.003 (2022).

Ritari, J. et al. Disease associations of natural killer (NK) cell KIR gene content variation in 352,783 Finns. Hum. Immunol. 85, 111177 (2024).

Reeve, M. P. et al. Oral and non-oral lichen planus show genetic heterogeneity and differential risk for autoimmune disease and oral cancer. Am. J. Hum. Genet. 111, 1047–1060 (2024).

Reeve, M. P. et al. Genome-wide association analyses of autoimmune hypothyroidism reveal autoimmune and thyroid-specific contributions and an inverse relationship with cancer risk. Nature Genet 2026 1–10 (2026) doi:10.1038/s41588-026-02521-1.

Wang, F. et al. Effects of parental autoimmune diseases on type 1 diabetes in offspring can be partially explained by HLA and non-HLA polymorphisms. Cell Genomics 100854 (2025) doi:10.1016/J.XGEN.2025.100854.

Salminen, A. et al. Genome-wide association study of pulpal and apical diseases. Nature Comm 2025 16:1 16, 6774- (2025).

Ruotsalainen, S. et al. Inherited infertility: Mapping loci associated with impaired female reproduction. Am. J. Hum. Genet. 111, 2789–2798 (2024).