Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2020 Feb;47(1):13-23.
doi: 10.1111/iji.12471. Epub 2020 Jan 6.

Immunogenetics in stem cell donor registry work: The DKMS example (Part 1)

Alexander H Schmidt  1   2   3 , Jürgen Sauter  1 , Daniel M Baier  1 , Jessica Daiss  1 , Andreas Keller  1 , Anja Klussmeier  2 , Thilo Mengling  1 , Gabi Rall  1 , Tobias Riethmüller  1 , Gerhard Schöfl  2 , Ute V Solloch  1 , Tigran Torosian  4 , David Means  5 , Helen Kelly  6 , Latha Jagannathan  7   8 , Patrick Paul  7 , Anette S Giani  9 , Sabine Hildebrand  1 , Stephan Schumacher  1 , Jan Markert  1 , Monika Füssel  2 , Jan A Hofmann  1 , Thomas Schäfer  2 , Julia Pingel  1 , Vinzenz Lange  2 , Johannes Schetelig  3   10
Affiliations
Review

Immunogenetics in stem cell donor registry work: The DKMS example (Part 1)

Alexander H Schmidt et al. Int J Immunogenet. 2020 Feb.

Abstract

Currently, stem cell donor registries include more than 35 million potential donors worldwide to provide HLA-matched stem cell products for patients in need of an unrelated donor transplant. DKMS is a leading stem cell donor registry with more than 9 million donors from Germany, Poland, the United States, the United Kingdom, India and Chile. DKMS donors have donated hematopoietic stem cells more than 80,000 times. Many aspects of donor registry work are closely related to topics from immunogenetics or population genetics. In this two-part review article, we describe, analyse and discuss these areas of donor registry work by using the example of DKMS. Part 1 of the review gives a general overview on DKMS and includes typical donor registry activities with special focus on the HLA system: high-throughput HLA typing of potential stem cell donors, HLA haplotype frequencies and resulting matching probabilities, and donor file optimization with regard to HLA diversity.

Keywords: DKMS; HLA; donor registry; unrelated hematopoietic stem cell transplantation.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Number of registered DKMS donors by country and year. Germany: orange; United States: grey; Poland: yellow; United Kingdom: light blue; Chile: red; India: dark blue. Cut‐off date: 30 September 2019 [Colour figure can be viewed at http://wileyonlinelibrary.com]
Figure 2
Figure 2
Postcode areas in the United Kingdom. For each area, the number of DKMS donors is represented by the size of the corresponding pie chart. Slices of the pie charts indicate the area‐specific ethnic composition of the DKMS donor file. The share of donors of non‐European descent ranges from 0.3% (postcode area KW = Kirkwall) to 85.3% (HA = Harrow). Colouring of the areas indicates the ratio between DKMS donors and the total population. The proportion of registered donors ranges from 0.3% (postcode area HS = Outer Hebrides) to 3.2% (WR = Worcester). The map was created with QGIS 2.12 software (QGIS Development Team, 2015). Shapefile © 2015 by Open Door Logistics (http://www.opendoorlogistics.com) [Colour figure can be viewed at http://wileyonlinelibrary.com]
Figure 3
Figure 3
Two‐digit postcode areas in Germany. For each region, the number of DKMS donors is represented by the size of the corresponding pie chart. Slices of the pie charts indicate the area‐specific ethnic composition of the DKMS donor file. The share of donors of non‐German descent ranges from 1.2% (postcode area 08 = Plauen) to 22.1% (70 = Stuttgart). Colouring of the areas indicates the ratio between DKMS donors and the total population. The proportion of registered donors ranges from 3.8% (postcode area 06 = Halle (Saale)) to 15.0% (56 = Koblenz and 49 = Osnabrück). The map was created with QGIS 2.12 software (QGIS Development Team, 2015). Shapefile © 2015 by Open Door Logistics (http://www.opendoorlogistics.com) [Colour figure can be viewed at http://wileyonlinelibrary.com]
Figure 4
Figure 4
Number of stem cell donations by DKMS donors by country and year. Germany: orange; United States: grey; Poland: yellow; United Kingdom: light blue; Chile: red; India: dark blue. Cut‐off date: 30 September 2019 [Colour figure can be viewed at http://wileyonlinelibrary.com]
Figure 5
Figure 5
Typing costs at DKMS LSL by typing method. Red: HLA (6 loci at high resolution); grey: CCR5Δ32; green: ABO, Rh; purple: KIR (allele groups); blue: MICA/MICB; black: HLA‐E; yellow: CMV (from swabs) [Colour figure can be viewed at http://wileyonlinelibrary.com]
Figure 6
Figure 6
Matching probabilities by donor registry size for various populations (all sample sizes n = 100,000). Red: Germany (country of recruitment), German (population); green: Germany, Turkish; orange: Poland, Polish; blue: United Kingdom, English/Scottish/Welsh; purple: United States, European [Colour figure can be viewed at http://wileyonlinelibrary.com]
Figure 7
Figure 7
Matching probabilities by donor registry size for various populations (all samples from DKMS UK donors, all sample sizes n = 20,000). Red: English; orange: Indian; blue: Scottish; green: Welsh [Colour figure can be viewed at http://wileyonlinelibrary.com]
Figure 8
Figure 8
Haplotype frequencies (HF) for two populations and two sample sizes. Red: Germany (country of recruitment), German (population); blue: United Kingdom, English/Scottish/Welsh. Solid: sample size n = 100,000; dashed: n = 20,000. Horizontal lines indicate HF that correspond to one (black), two (dark grey) or three (light grey) haplotype occurrence(s) in the samples with size n = 100,000 (solid) or n = 20,000 (dashed) [Colour figure can be viewed at http://wileyonlinelibrary.com]
See this image and copyright information in PMC

References

    1. Albrecht, V. , Zweiniger, C. , Surendranath, V. , Lang, K. , Schöfl, G. , Dahl, A. , … Schmidt, A. H. (2017). Dual redundant sequencing strategy: Full‐length gene characterisation of 1056 novel and confirmatory HLA alleles. HLA, 90(2), 79–87. 10.1111/tan.13057 - DOI - PMC - PubMed
    1. Baier, D. M. , Hofmann, J. A. , Fischer, H. , Rall, G. , Stolze, J. , Ruhner, K. , … Schmidt, A. H. (2019). Very low error rates of NGS‐based HLA typing at stem cell donor recruitment question the need for a standard confirmatory typing step before donor work‐up. Bone Marrow Transplantation, 54(6), 928–930. 10.1038/s41409-018-0411-2 - DOI - PMC - PubMed
    1. Beatty, P. G. , Mori, M. , & Milford, E. (1995). Impact of racial genetic polymorphism on the probability of finding an HLA‐matched donor. Transplantation, 60(8), 778–783. 10.1097/00007890-199510270-00003 - DOI - PubMed
    1. Bergstrom, T. C. , Garratt, R. J. , & Sheehan‐Connor, D. (2009). One chance in a million: Altruism and the bone marrow registry. The American Economic Review, 99(4), 1309–1334. 10.1257/aer.99.4.1309 - DOI - PubMed
    1. Bochtler, W. , Beth, M. , Eberhard, H. P. , & Müller, C. R. (2008). OptiMatch – a universally configurable HLA matching framework. HLA, 71(4), 321 10.1111/j.1399-0039.2008.01015.x - DOI