Specifics of the Blood Service Biobank data

Due to specific blood donation eligibility criteria, Blood Service Biobank participants share distinct features.

The Blood donor biobank consists of a selected group of individuals with an active and long-standing history of blood donation. Eligibility criteria for blood donation exclude individuals with certain medical conditions, such as severe cardiovascular conditions, cancer and epilepsy, and also require specific health parameters, such as a minimum haemoglobin level. Some conditions that disqualify individuals from donating blood have a well-established genetic basis. For example, HLA gene variants are associated with type 1 diabetes (T1D)¹ and certain autoimmune diseases^2–4.

The combination of blood donation eligibility criteria, the generally healthier lifestyle of blood donors, and self-selection due to temporary illnesses (e.g., the common cold) contributes to a well-known phenomenon called the Healthy Donor Effect (HDE). HDE results in a lower morbidity and mortality rates among blood donors compared to the general population. In addition, recruitment strategies based on blood group antigens can lead to the depletion or enrichment of certain blood group antigens that are associated with specific diseases⁵.

Therefore, GWAS comparing Blood Service Biobank blood donors (N=53,688) with a control population (N=228,060) shows a negative genetic correlation in blood donors in several disease endpoints, extending beyond the conditions excluded by donation criteria⁶. https://userresults-old.finngen.fi/pheno/BloodDonor

Despite of the protective genetic factors, blood donors in the Blood Service Biobank also carry disease-associated genetic variants at frequencies similar to the FinnGen cohort⁸, indicating that blood donor-based biobank is suitable for finding samples from individuals carrying disease-associated variants. Furthermore, the relatively high degree of first-degree consanguinity in the Blood Service Biobank⁷ makes it suitable for trio-based and linkage studies.

While a biobank based on blood donors can be a valuable resource for biomedical research, careful consideration is necessary to control for potential confounding factors, especially when using blood donors exclusively as a control group. It is important to remember that blood donors represent a health-selected population, and in some cases, selection is also influenced by blood type. These selection biases must be appropriately accounted for in research to avoid misleading conclusions.

1. Hu, X. et al. Additive and interaction effects at three amino acid positions in HLA-DQ and HLA-DR molecules drive type 1 diabetes risk. Nat. Genet. 47, 898–905 (2015).

2. De Silvestri, A. et al. The Involvement of HLA Class II Alleles in Multiple Sclerosis: A Systematic Review with Meta-analysis. Dis. Markers 2019, 1409069 (2019).

3. Dendrou, C. A., Petersen, J., Rossjohn, J. & Fugger, L. HLA variation and disease. Nat. Rev. Immunol. 18, 325–339 (2018).

4. Ritari, J., Koskela, S., Hyvärinen, K., FinnGen & Partanen, J. HLA-disease association and pleiotropy landscape in over 235,000 Finns. Hum. Immunol. 83, 391–398 (2022).

5. Dahlén, T., Clements, M., Zhao, J., Olsson, M. L. & Edgren, G. An agnostic study of associations between ABO and RhD blood group and phenome-wide disease risk. Elife 10, (2021).

6. Jonna Clancy, Jarkko Toivonen, J. L. et al. Genome-Wide Association Study Identifies Protective Genetic Factors in Active Blood Donors Against Multiple Diseases. Prepr. Eur. J. Hum. Genet. (2025).

7. Kurki, M. I. et al. FinnGen: Unique genetic insights from combining isolated population and national health register data. medRxiv 2022.03.03.22271360 (2022) doi:10.1101/2022.03.03.22271360.

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