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. 2018 Sep 24;45(5):331–340. doi: 10.1159/000493555

Towards a Regional Registry of Extended Typed Blood Donors: Molecular Typing for Blood Group, Platelet and Granulocyte Antigens

Jan Portegys a, Gabi Rink a, Pia Bloos a, Erwin A Scharberg b, Harald Klüter a, Peter Bugert a,*
PMCID: PMC6257148  PMID: 30498411

Abstract

Background

The provision of compatible blood products to patients is the most essential task of transfusion medicine. Besides ABO and Rh, a number of additional blood group antigens often have to be considered for the blood supply of immunized or chronically transfused patients. It also applies for platelet antigens (HPA) and neutrophil antigens (HNA) for patients receiving platelet or granulocyte concentrates. Here, we describe the molecular screening for a number of blood group, HPA, and HNA alleles. Based on the screening results we are building up a regional blood donor registry to provide extended matched blood products on demand.

Methods

We developed and validated TaqMan™ PCR and PCR-SSP methods for genetic markers defining 37 clinically relevant blood group antigens (beyond ABO and Rh), 10 HPA, and 11 HNA. Furthermore, we describe a feasible method for fast molecular screening of the HNA-2null phenotype. All data were statistically evaluated regarding genotype distribution. Allele frequencies were compared to ExAC data from non-Finnish Europeans.

Results

Up to now more than 2,000 non-selected regular blood donors in south-west Germany have been screened for blood group, HPA, and HNA alleles. The screening results were confirmed by serology and PCR-SSP methods for selected numbers of samples. The allele frequencies were similar to non-finnish Europeans in the ExAC database except for the alleles encoding the S, HPA-3b and HNA-4b antigens, with significantly lower prevalence in our cohort, as well as the LU14 and the HNA-3b antigens, with a higher frequency compared to the ExAC data. We identified 71 donors with rare blood groups such as Lu(a+b-), Kp(a+b-), Fy(a-b-) and Vel-, and 169 donors with less prevalent HPA or HNA types.

Conclusion

Molecular screening for blood group alleles by using TaqMan™ PCR is an effective and reliable high-throughput method for establishing a rare donor registry.

Keywords: Molecular blood typing, Genotyping, Polymerase chain reaction, High- and low-prevalence antigens, Granulocytes, Platelets, Blood groups

Introduction

The provision of optimally matched blood products with regard to antigen compatibility is an ongoing challenge in transfusion medicine. Patients who repeatedly need red blood cell concentrates (RBCs) due to e.g. hemoglobinopathy or other diseases and also patients who have developed red cell antibodies often have to be transfused with RBCs compatible not only for ABO and Rh but also for several additional blood group antigens [1]. Blood recipients who are negative for high-prevalence antigens such as Vel are at risk for immunization and subsequent hemolytic transfusion reactions when transfused with antigen-positive blood. On the other hand, blood donors positive for low-prevalence antigens can cause antibody formation in antigen-negative patients [2]. Antibodies to low-prevalence antigens are of risk in pregnancy as they can cause a hemolytic disease of the fetus and the newborn (HDFN) and are often not detected in prenatal antibody screening. It also applies for the immunization to human platelet alloantigens (HPA) causing fetal neonatal alloimmune thrombocytopenia (FNAIT) or neutrophil antigens (HNA) causing neonatal immune neutropenia (NIN) [3, 4]. Furthermore, transfusion-associated acute lung injury (TRALI) can be caused by antibodies to HNA antigens.

With the advent of high-throughput screening in molecular blood typing, there is increasing information regarding the prevalence of rare blood groups and other antigens. Several methods have been developed and used for screening larger numbers of blood donors for common and rare antigens [5, 6, 7, 8, 9, 10, 11, 12, 13]. These studies add further information regarding the frequency of blood group alleles and regional differences in the availability of donors with rare blood groups. These approaches have led to the establishment of regional or national rare donor registries [14, 15, 16, 17]. As national legal and logistical considerations can cause problems and critical delay for import and export of rare blood, it might be reasonable to establish such registries on a local level as well. Our institute is located in the Rhein-Neckar metropolitan region in south-west Germany, an area which is home to a population with different ethnic background [18, 19]. This in turn may lead to a higher incidence of diseases such as thalassemia, which require frequent blood transfusions [20]. In addition, those ethnic differences might well translate into a higher incidence of rare blood groups as well [21].

To improve our ability to provide rare blood RBCs on a regional level, it is important to continue the screening activities and to test significant part of our donor population for alleles coding for rare blood groups. We also focused on the genotypes for the most relevant HPAs and HNAs in order to improve the availability of donors for antigen-selected platelet and granulocyte concentrates and for diagnostic purposes.

Material and Methods

DNA Samples of Blood Donors

This study was performed in a urban blood donor cohort from the south-western part of Germany. Donors gave written consent to provide additional 4.5 ml EDTA blood samples, and the use of the blood samples for research purposes was approved by the ethics committee II of Heidelberg University, Medical Faculty Mannheim. DNA was isolated in our laboratory from pseudonymized EDTA-anticoagulated blood samples using a commercial system for 96 well plates (Invisorb Blood Mini HTS 96 Kit; Stratec Biomedical AG, Berlin, Germany).

Genotyping

We developed TaqMan™ PCR methods and PCR with sequence-specific primers (PCR-SSP) for 21 blood group-defining SNPs, 5 SNPs defining HPAs, 3 SNPs defining the HNA-3a/b, HNA-4a/b and HNA-5a/b and the CD177 haplotype causing the HNA-2null phenotype (table 1). The FCGR3B*01, *02, and *03 alleles encoding the HNA-1a/b/c/d antigens were screened by PCR-SSP using a previously published protocol [22] and slightly modified primers (table 1). For each genetic marker, we established PCR-SSP methods according to a standard protocol [23] and with primers listed in table 1. The A4GALT SNP rs2143918 has a 100% correlation with the P1/P2 phenotype in all populations, except for rare individuals of African descent [24]. This SNP was addressed for P genotyping.

Table 1.

Primers for PCR-SSP and TaqMan™-PCR assays

Antigen system dbSNP No. Primer sequences for PCR-SSP (5′−3′) Specificity TaqMan™ PCR assay*
MNS (MN) rs7687256, rev: GGCAAGAATTCCTCCATAGTAG GYPA (self-designed assay1)
rs7658293 for: CATATCAGCATTAAGTACCACTGGT c.71G, c.72T
for: CATATCAGCATTAAGTACCACTGAG c.71A, c.72G
MNS (Ss) rs7683365 for: caaaatatgattaagaaaaggaaacccg GYPB C__34183121_10
rev: cgatggacaagttgtccca c.143T
rev: cgatggacaagttgtcccg c.143C
P1PK (P1/P2) rs2143918 rev: CACAAAGAACCTGGCTTCTCG A4GALT C__16072990_20
for: CACATCTTTCCTGGGAAGGAATT +2857T
for: CACATCTTTCCTGGGAAGGAATG +2857G
LU (Lua/b) rs28399653 for: CCAGGGAGACCCATAACAAG BCAM C__25764173_10
rev: TCTCAGCCGAGGCTAGGT c.230A
rev: TCTCAGCCGAGGCTAGGC c.230G
LU (LU8/14) rs28399656 rev: GAGGTCAAAGGCCAGCACAG BCAM C__32363989_10
for: CTCTCCCAGAGGGCTACAT c.611T
for: GATCTCTCCCAGAGGGCTACAA c.611A
LU (Aua/b) rs1135062 rev: ggttaagctatggtggtcattgc BCAM C__1846428_10
for: ccatgtcttccacttcggca c.1615A
for: ccatgtcttccacttcggcg c.1615G
KEL (K/k) rs8176058 for: GGGAGATGGAGATGGAAATGG KEL C__1719_20
rev: GACTCATCAGAAGTCTCAGCG c.578C
rev: GACTCATCAGAAGTCTCAGCA c.578T
KEL (Kpa/b) rs8176059 rev: AGGGCACTAGGAGGAAGAAG KEL C__25596888_20
for: CTTGTCAATCTCCATCACTTCAC c.841C
for: CTTGTCAATCTCCATCACTTCAT c.841T
KEL (Jsa/b) rs8176038 rev: ggcccttgacacttgcatac KEL C__25596899_20
for: tgcctgggggctgcct c.1790T
for: tgcctgggggctgccc c.1790C
KEL (11/17) rs61729034 rev: CCTTAGAGGAGGGACACAAAG KEL C__27862879_10
for: GGCAAGCTCTTCCAGATGGT c.905T
for: GGCAAGCTCTTCCAGATGGC c.905C
FY (Fya/b) rs12075 rev: GGCACCACAATGCTGAAGAG DARC C__2493442_10
for: CTTCCCAGATGGAGACTATGG c.125G
for: CTTCCCAGATGGAGACTATGA c.125A
FY (Fy0) rs2814778 rev: CAAAGGGAGGGACACAAGAG DARC C__15769614_10
for: CCTCATTAGTCCTTGGCTCTTAT -67T
for: CCTCATTAGTCCTTGGCTCTTAC -67C
JK (Jka/b) rs1058396 rev: AGACAGCAAGTGGGCTCAAG SLC14A1 C__1727582_10
for: TCTTTCAGCCCCATTTGAGG c.838G
for: GTCTTTCAGCCCCATTTGAGA c.838A
DI (Dia/b) rs2285644 rev: TCCTGCCTGCCCTAGTTCTG SLC4A1 C__26654865_10
for: GGGTGGTGAAGTCCACGCT c.2561T
for: GGTGGTGAAGTCCACGCC c.2561C
DI (Wra/b) rs75731670 rev: TGGGAGAATGCCAGGGAAAG SLC4A1 C__2259533_10
for: CACTGGGCTTGCGTTCCA c.1972A
for: CACTGGGCTTGCGTTCCG c.1972G
YT (Yta/b) rs1799805 rev: GGGAGGACTTCTGGGACTTC ACHE C__8786419_20
for: CATCAACGCGGGAGACTTCC c.1057C
for: CATCAACGCGGGAGACTTCA c.1057A
SC (SC1/2) rs56025238 rev: CCCTTATATTCCGGCATCAGATC ERMAP C__32292873_10
for: CTCTCTCCCTCTGGCCCG c.169G
for: CTCTCTCCCTCTGGCCCA c.169A
DO (Doa/b) rs11276 for: CTCCACATCCCTCCTGAAAG ART4 C__2687344_20
rev: GTTGACCTCAACTGCAACCAGTT c.793A
rev: GTTGACCTCAACTGCAACCAGTC c.793G
CO (Coa/b) rs28362692 rev: GCACGGAAGATGCTGATCTGG AQP1 C__27536484_20
for: GGGGAACAACCAGACGGC c.134C
for: GGGGAACAACCAGACGGT c.134T
LAN (+/–) rs149202834 rev: AGGTGTACCTGGCTCCTTTC ABCB6 C_168788417_10
for: TTTAGCCTGTGGGTGCTGC c.574C
for: TTTAGCCTGTGGGTGCTGT c.574T
VEL (+/–) rs566629828 rev: CCAAAGGCTGCGGTTTGCTG SMIM1 see [7]
for: GCAGCAGGGACGGAGTCA c.64–80ins
for: GCAGCAGGGACGGAGTCC c.64–80del
HPA-1a/b rs5918 rev: gtgcaatcctctggggact ITGB3 C__818008_30
for: gacttacaggccctgcctct ITGB3*176T
for: acttacaggccctgcctcc ITGB3*176C
HPA-2a/b rs6065 rev: gccagcgacgaaaatagagg GP1BA C__11442703_10
for: cccccagggctcctgac GP1BA*482C
for: cccccagggctcctgat GP1BA*482T
HPA-3a/b rs5911 rev: accagagagcctgctcactac ITGA2B C__3017440_10
for: ggactgggggctgcccat ITGA2B*2621T
for: ggactgggggctgcccag ITGA2B*2621G
HPA-5a/b rs1801106 rev: ggcagtacactatacattcaactc ITGA2 C__27862812_10
for: aaggaagagtctacctgtttactatcaaag ITGA2*1600G
for: aaggaagagtctacctgtttactatcaaaa ITGA2*1600A
HPA-15a/b rs10455097 for: cagtattatgaccttatgatgacctattc CD109 C__3226894_10
rev: gttacttcaaattcttggtaaatcctgg CD109*2108C
rev: gttacttcaaattcttggtaaatcctgt CD109*2108A
HNA-1a rs448740 for: cacagtggtttcacaatgagaa FCGR3B*01 none
rs368410676 rev: atggacttctagctgcacc
HNA-1b/d rs527909462 for: gcctcaatggtacagcgtgctt FCGR3B*02 none
rs5030738 rev: ctgtcgttgactgtggcag
HNA-1b/c rs527909462 for: gcctcaatggtacagcgtgctt FCGR3B*03 none
rs5030738 rev: ctgtcgttgactgtggcaT
HNA-2 (+/–) rs1164364335 for: catggagaaggtgacctttgag CD177 (self-designed assay2)
rev: CAACAGTGCTGCAGCCTTT CD177*787A
rev: CAACAGCGCTGCAGCTTTA CD177*787T
HNA-3a/b rs2288904 rev: ctgcatggagcagaggatgg SLC44A2 C__11789692_10
for: GAGTGGCTGAGGTGCTTCG SLC44A2*461G
for: GGAGTGGCTGAGGTGCTTCA SLC44A2*461A
HNA-4a/b rs1143679 rev: aaggaggtctgacggtgaag ITGAM C__2847895_1_
for: ctcatgcgagcccatccg ITGAM*230G
for: ctcatgcgagcccatcca ITGAM*230A
HNA-5a/b rs2230433 rev: tccaccttgcggaaggagagtc ITGAL C___25754090_10
for: atcatcccccacagatccag ITGAL*2372G
for: catcccccacagatccac ITGAL*2372C
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*

TaqMan™-PCR assays were commercially available (Life Technologies) under the given assay number

1

self-designed TaqMan™-PCR assay for MN genotyping with forward primer CTCAGTCACCTCGTTCTTAATC, reverse primer GGCAAGAATTCCTCCATAGTAG, FAM-probe CACTGGTGTGGCAA (M), VIC-probe CACTGAGGTGGCAA (N)

2

self-designed TaqMan™-PCR assay for HNA-2 genotyping with forward primer CCCTCAGGACTCACATCAAC, reverse primer CTGAGTGGATGGTGGTCTTC, FAM-probe CAGCCTTTTGTCCC (CD177 wild type), VIC-probe CAGCTTTAGGTCGC (CD177 null variant).

For screening by TaqMan™ PCR we used commercial assays (Life Technologies, Darmstadt, Germany), except for the alleles encoding the M/N, VEL, and HNA-2 antigens. All TaqMan™ PCR analyses were performed by endpoint fluorescence detection on a ABI 7000 real-time PCR cycler using the standard program for genotyping (Applied Biosystems, Darmstadt, Germany). The method for VEL screening was described before [12]. For the M/N antigens we developed primers specific for GYPA and probes specific for the corresponding GYPA*01 and GYPA*02 alleles (table 1).

Homozygosity for a nonsense mutation c.787A>T in CD177 was identified as the most frequent cause of the HNA-2null phenotype [25]. But genotyping is hampered by the CD177P1 pseudogene with identical DNA sequence in the corresponding region. The 787A>T mutation can also occur in the CD177P1 gene but does not affect the HNA-2 phenotype. In order to differentiate between the CD177*c.787A>T and the CD177P1*787A>T genotype, a long-range PCR for the specific amplification of the CD177 gene followed by PCR-SSP was described [26]. However, this method is not appropriate for screening of samples in larger scales. We developed a TaqMan™ PCR method with primers and probes listed in table 1 by which individuals homozygous for the 787A>T mutation in both genes CD177 and CD177P1 can be identified.

Validation

The results from TaqMan™ PCR screening were verified by PCR-SSP for significant numbers of samples representing the different genotypes and for all samples with rare genotypes. Donors homozygous for the CD177*c.787A>T mutation were re-analyzed using the long-range and PCR-SSP method described recently [26] with slightly modified primers for the PCR-SSP (table 1). As far as available genotyping data were confirmed by serology for some of the antigens such as MNS, P, K/k, Aua/b, Vel, HPA-1, and HPA-5. In all validation samples the serologically determined phenotype matched the genotype. In addition, 8 donors homozygous for the CD177*c.787A>T mutation identified by the TaqMan™-PCR method were phenotyped for the HNA-2 antigen (flow cytometry using the monoclonal anti-CD177 MEM-166) and the HNA-2null phenotype was confirmed in all samples.

Statistics

The typing data for each genetic marker was reviewed with regard to deviation from the Hardy-Weinberg equilibrium. The minor allele frequencies (MAF) in our donor cohort were compared to the allele frequencies of non-Finnish Europeans in the ExAC database [27]. Significance of differences was calculated by using appropriate tests in the SPSS software package (SPSS Vers. 12.0; IBM, Armonk, NY, USA).

Results

Blood donors of our institute have been enrolled in the genotyping study since June 2016 irrespective of age, gender or ABO and Rh blood group (table 2). Using TaqMan™ PCR, the donors were screened for alleles defining 37 blood group antigens, 10 HPAs, and 11 HNAs including the HNA-2null phenotype. In total, 2,084 donors were typed for all antigens (table 3). Some antigens have already been typed in higher numbers of donors.

Table 2.

Demographic characteristics of the screened donor population

% of all donors
Age, years
 <20 6.7
 20–29 37.8
 30–39 15.9
 40–49 17.2
 50–59 14.5
 >60 7.9
Sex
 Male 60.4
 Female 39.6
Blood groups
 O pos 31.0
 O neg 11.4
 A pos 30.8
 A neg 8.9
 B pos 9.1
 B neg 2.7
 AB pos 4.8
 AB neg 1.3
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Table 3.

Results from genotype screening of blood donors

Antigen system dbSNP No. Allele Genotype Phenotype1 Number of donors % of donors
Blood groups
MNS rs7687256, GYPA*01 c.71G, c.72T M+N– 589 28.26
(002) rs7658293 GYPA*02 c.71G/A, c.72T/G M+N+ 1,078 51.58
c.71A, c.72G M–N+ 420 20.15
MNS rs7683365 GYPB*03 c.143T S+s– 212 9.33
(002) GYPB*04 c.143T/C S+s+ 995 43.77
c.143C S–s+ 1,066 46.90
P1PK rs21439182 A4GALT*P1.01 +2857T P1 555 26.58
(003) A4GALT*P2.01 +2857T/G P1 1,017 48.56
+2857G P2 518 24.86
LU rs28399653 LU*01 c.230A Lu(a+b–) 4 0.19
(005) LU*02 c.230A/G Lu(a+b+) 153 7.34
c.230G Lu(a–b+) 1,927 92.47
LU rs28399656 LU*02 c.611T LU:8,–14 1,987 95.35
(005) LU*02.14 c.611T/A LU:8,14 96 4.61
c.611A LU:–8,14 1 0.05
LU rs1135062 LU*02 c.1615A Au(a+b–) 1,000 47.98
(005) LU*02.19 c.1615A/G Au(a+b+) 933 44.77
c.1615G Au(a–b+) 151 7.25
KEL rs8176058 KEL*01 c.578C K+k– 7 0.25
(006) KEL*02 c.578C/T K+k+ 222 8.08
c.578T K–k+ 2,518 91.67
KEL rs8176059 KEL*02 c.841C Kp(a–b+c–) 2,047 98.22
(006) KEL*02.03 c.841C/T Kp(a+b+c–) 36 1.73
c.841T Kp(a+b–c–) 1 0.05
KEL rs8176038 KEL*02 c.1790T Js(a–b+) 2,083 99.95
(006) KEL*02.06 c.1790T/C Js(a+b+) 1 0.05
c.1790C Js(a+b–) 0 0.00
KEL rs61729034 KEL*02 c.905T KEL:11,–17 2,078 99.71
(006) KEL*02.17 c.905T/C KEL:11,17 6 0.29
c.905C KEL:–11,17 0 0.00
FY rs12075 FY*01 c.125G Fy(a+b–) 402 19.29
(008) FY*02 c.125G/A Fy(a+b+) 998 47.89
c.125A Fy(a–b+) 684 32.82
FY rs2814778 FY*01N.01 or -67T 2,032 97.50
(008) FY02N.01 -67T/C 46 2.21
-67C Fy(a–b–) 6 0.29
JK rs1058396 JK*01 c.838G Jk(a+b–) 564 27.06
(009) JK*02 c.838G/A Jk(a+b+) 999 47.94
c.838A Jk(a–b+) 521 25.00
DI rs2285644 DI*01 c.2561T Di(a+b–) 0 0.00
(010) DI*02 c.2561T/C Di(a+b+) 3 0.11
c.2561C Di(a–b+) 2,746 99.89
DI rs75731670 DI*02 c.1972A Wr(a+b–) 0 0.00
(010) DI*02.03 c.1972A/G Wr(a+b+) 3 0.14
c.1972G Wr(a–b+) 2,081 99.86
YT rs1799805 YT*01 c.1057C Yt(a+b–) 2,427 88.64
(011) YT*02 c.1057C/A Yt(a+b+) 295 10.77
c.1057A Yt(a–b+) 16 0.58
SC rs56025238 SC*01 c.169G SC:1,–2 2,727 99.27
(013) SC*02 c.169G/A SC:1,2 20 0.73
c.169A SC:–1,2 0 0.00
DO rs11276 DO*01 c.793A Do(a+b–) 319 15.31
(014) DO*02 c.793A/G Do(a+b+) 1,029 49.38
c.793G Do(a−b+) 736 35.32
CO rs28362692 CO*01 c.134C Co(a+b−) 1,931 92.66
(015) CO*02 c.134C/T Co(a+b+) 151 7.25
c.134T Co(a–b+) 2 0.10
LAN rs149202834 ABCB6*01 c.574C Lan+ 2,064 99.04
(033) ABCB6*01N.13 c.574C/T Lan+ 20 0.96
c.574T Lan– 0 0.00
VEL rs566629828 VEL*01 c.64–80ins Vel+ 2,653 96.54
(034) VEL*-01 c.64–80ins/del Vel+ 94 3.42
c.64–80del Vel– 1 0.04
Platelet antigens (HPA)
HPA-1 rs5918 ITGB3*176T c.176T HPA-1(a+b–) 1,764 72.03
ITGB3*176C c.176T/C HPA-1(a+b+) 636 25.97
c.176C HPA-1(a–b+) 49 2.00
HPA-2 rs6065 GP1BA*482C c.482C HPA-2(a+b–) 2,040 82.93
GP1BA*482T c.482C/T HPA-2(a+b+) 395 16.06
c.482T HPA-2(a–b+) 25 1.02
HPA-3 rs5911 ITGA2B*2621T c.2621T HPA-3(a+b–) 909 38.47
ITGA2B*2621G c.2621T/G HPA-3(a+b+) 1,116 47.23
c.2621G HPA-3(a–b+) 338 14.30
HPA-5 rs1801106 ITGA2*1600G c.1600G HPA-5(a+b–) 1,925 81.33
ITGA2*1600A c.1600G/A HPA-5(a+b+) 422 17.83
c.1600A HPA-5(a–b+) 20 0.84
HPA-15 rs10455097 CD109*2108C c.2108C HPA-15(a+b–) 598 24.28
CD109*2108A c.2108C/A HPA-15(a+b+) 1,227 49.82
c.2108A HPA-15(a–b+) 638 25.90
Neutrophil antigens (HNA)
HNA-1 rs448740 FCGR3B*01 c.227A HNA-1(a+b–c–d–) 349 12.71
rs368410676 FCGR3B*02 c.227A/c.147T,266C HNA-1(a+b+c–d+) 1,174 42.75
rs527909462 FCGR3B*03 c.147T,266C HNA-1(a–b+c–d+) 1,100 40.06
rs5030738 c.227A/c.147T,266A HNA-1(a+b+c+d–) 41 1.49
c.227A/c.147T,266C/A HNA-1(a+b+c+d+) 64 2.33
c.147T,266C/A HNA-1(a–b+c+d+) 18 0.66
HNA-2 rs1164364335 CD177/CD177P1 c.787A, c.787A/T HNA-2(+/–) 3,315 97.53
c.787T HNA-2(–) 84 2.47
HNA-3 rs2288904 SLC44A2*461G c.461G HNA-3(a+b–) 1,329 58.42
SLC44A2*461A c.461G/A HNA-3(a+b+) 819 36.00
c.461A HNA-3(a–b+) 126 5.58
HNA-4 rs1143679 ITGAM*230G c.230G HNA-4(a+b–) 1,797 79.06
ITGAM*230A c.230G/A HNA-4(a+b+) 454 19.97
c.230A HNA-4(a–b+) 22 0.97
HNA-5 rs2230433 ITGAL*2372G c.2372G HNA-5(a+b–) 1,151 50.66
ITGAL*2372C c.2372G/C HNA-5(a+b+) 934 41.11
c.2372C HNA-5(a–b+) 187 8.23
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Phenotype deduced from the genotype

2

rs2143918 has a 100 % correlation with the P1/P2 phenotype in all populations except for rare individuals of African descent [21]. It was therefore used to determine the P1/P2 genotype even though it is not the causative mutation.

The most frequent cause of the HNA-2null phenotype is the CD177 haplotype carrying the nonsense mutation c.787A>T (linked to additional 4 SNPs) in exon 7 [25]. However, the CD177P1 pseudogene with almost identical DNA sequence in the exon 4 to 9 region can also harbor this haplotype making CD177-specific genotyping difficult. Pre-amplification of the CD177 gene using long-range PCR followed by PCR-SSP typing of the c.787A>T mutation was described as a genotyping method [26]. Due to the long-range PCR this method is, however, time-consuming and cost-intensive. With our fast (70 min) and easy TaqMan™ PCR method we were able to screen 3,399 donors within a short period of time and identified 84 donors (2.47%) homozygous for the null haplotype in both genes CD177 and CD177P1 (fig. 1). Because this screening method does not distinguish between CD177 and CD177P1, individuals homozygous for the c.787A>T mutation in the CD177 gene, but with one or two wild-type alleles in the CD177P1 gene, are not identified as HNA-2null. For all 84 donors we could confirm the CD177*c.787T homozygosity using the CD177-specific long-range PCR and PCR-SSP. For 8 of the donors we obtained fresh blood samples and confirmed the HNA-2null phenotype by flow cytometry (data not shown). Thus, we describe here a suitable method for fast molecular screening of the HNA-2null phenotype.

Fig. 1.

Fig. 1

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Representative result of TaqMan™ PCR-based typing of 96 samples for the c.787A>T mutation in CD177 and CD177P1. Primers were designed to amplify a 88 bp fragment from both genes CD177 and CD177P1. The FAM-labeled probe detects the wild-type allele and the VIC-labeled probe is specific for the null haplotype including the c.787A>T mutation. FAM signals below the threshold (dashed line) indicate absence of the wild type allele in both genes and, therefore, indicate the HNA-2null phenotype. Control: donor sample with confirmed homozygosity for the c.787A>T mutation by CD177 genomic sequencing and confirmed HNA-2null phenotype by flow cytometry. In addition to the control three donors revealed absence of the wild type allele, i.e. homozygosity for the c.787A>T mutation. As expected, the HNA-2null phenotype was confirmed for these samples.

The prevalence of the different genotypes was within the expected range, with a few exceptions. For each measured distribution, basic probability testing was performed using a chi-square test comparing the observed distribution of genotypes to the expected distribution based on observed allele frequencies and the Hardy-Weinberg equilibrium. All but two results (Aua/b and Fynull) were in line with the expected genotype frequencies. For the Aua/b-encoding SNP we identified a trend (p = 0.054) for more heterozygotes (933 vs. 869) and less Aub homozygotes (151 vs. 183) as expected. Re-typing of 144 selected samples using PCR-SSP confirmed the result from TaqMan™ PCR. In addition, phenotyping of 11 samples for the Aua/b antigens by means of serology also confirmed the genotyping results. The overrepresentation of Aua/b donors in our cohort could be a characteristic of our donor population or is just a coincidental finding. The promoter mutation FY*-67T>C was screened for identification of the Fynull phenotype. Based on the allele frequency of 0.0139 for the mutation, we could expect one homozygote in 5,164 donors. We found 6 homozygotes in 2,084 typed donors leading to a significant deviation (p < 0.0001) from the Hardy-Weinberg equilibrium. Most likely, the Fynull donors are of African ancestry because the mutation is very common in this population.

The MAF of blood group antigens, HPAs, and HNAs in our study cohort were compared to the data of non-Finnish Europeans in the ExAC exome sequencing study [27]. The S antigen encoding GYPB*c.143T allele, the HPA-3b antigen encoding ITGA2B*c.2621G allele, and the HNA-4b antigen encoding ITGAM*c.230A allele was significantly less prevalent in our cohort (table 4). The LU*c.611T allele encoding the LU14 antigen and the SLC44A2*c.461A allele encoding the HNA-3b antigen showed a higher frequency compared to the ExAC data.

Table 4.

Minor allele frequencies in our donor population compared to the non-Finnish European population in the ExAC database

Antigen dbSNP No. Minor allele MAF in our cohort MAF in ExAC Significance*
Blood groups
S rs7683365 GYPB*c.143T 0.3121 0.3802 <0.001
Lu(a) rs28399653 LU*c.230A 0.0390 0.0382 0.935
LU14 rs28399656 LU*c.611T 0.0234 0.0146 0.048
Au(b) rs1135062 LU*c.1615G 0.2962 0.2993 0.809
K rs8176058 KEL*c.578T 0.0430 0.0412 0.753
Kp(a) rs8176059 KEL*c.841T 0.0091 0.0105 0.634
Js(a) rs8176038 KEL*c.1790C 0.0002 0.0005 0.548
KEL17 rs61729034 KEL*c.905C 0.0014 0.0018 0.726
Fy(a) rs12075 FY*c.125G 0.4325 0.4244 0.632
Jk(b) rs1058396 SLC14A1*c.838A 0.4897 0.4912 0.950
Di(a) rs2285644 SLC4A1*c.2561T 0.0005 0.0004 0.823
Wr(a) rs75731670 SLC4A1*c.1972A 0.0007 0.0002 0.114
Yt(b) rs1799805 ACHE*c.1057A 0.0597 0.0502 0.211
Sc2 rs56025238 ERMAP*c.169A 0.0036 0.0050 0.628
Do(a) rs11276 ART4*c.793A 0.4000 0.3849 0.348
Co(b) rs28362692 AQP1*c.134T 0.0372 0.0398 0.623
LAN- rs149202834 ABCB6*c.574T 0.0048 0.0030 0.454
Platelet antigens (HPA)
HPA-1b rs5918 ITGB3*c.176C 0.1499 0.1553 0.629
HPA-2b rs6065 GP1BA*c.482T 0.0904 0.0865 0.697
HPA-3b rs5911 ITGA2B*c.2621G 0.3792 0.4443 <0.001
HPA-5b rs1801106 ITGA2*c.1600A 0.0976 0.0918 0.553
HPA-15a rs10455097 CD109*c.2108C 0.4919 0.4975 0,752
Neutrophil antigens (HNA)
HNA-3b rs2288904 SLC44A2*c.461A 0.2358 0.2094 0.048
HNA-4b rs1143679 ITGAM*c.230A 0.1095 0.1769 <0.001
HNA-5b rs2230433 ITGAL*c.2372C 0.2879 0.2856 0.889
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*

Bold numbers indicate significant differences (p < 0.05) of MAF between both populations.

By screening of more than 2,000 donors we found a number of rare blood types, such as Lu(a+b-), Kp(a+b-), Fynull, Vel-, HPA-1(a-b+), and HNA-2null (table 5).

Table 5.

Rare blood types identified in the screened donor cohort

Phenotype* Number of donors
Negative for HP blood groups
Lu(a+b–) 4
LU:–8,14 1
K+k– 7
Kp(a+b–) 1
Fy(a–b–) 6
Yt(a–b+) 16
Co(a–b+) 2
Vel– 1
Positive for LP blood groups
Js(a+) 1
KEL:17 6
Di(a+) 3
Wr(a+) 3
SC:2 20
HPA / HNA
HPA-1(a–b+) 49
HPA-2(a–b+) 25
HPA-5(a–b+) 20
HNA-2null 84
HNA-4(a–b+) 22
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*

Negative for high-prevalence (HP) antigens; positive for low-prevalence (LP) antigens.

Discussion

Molecular screening of the local blood donor population is an approach to enable a compatible blood supply on demand. We describe a TaqMan™ PCR-based typing of the corresponding genetic markers (mostly SNPs). This method is feasible, as it is associated with limited workload and can be easily adapted with regard to higher throughput of samples and additional alleles.

Up to now we obtained 72,337 genotypes from 33 genetic markers in more than 2,000 donors, and it is an ongoing screening program including all new donors at our institute. Based on the genotyping data we were able to deduce the phenotypes for 37 blood group antigens, 10 HPAs, and 11 HNAs including the HNA-2null phenotype. The complete antigen profile could be achieved for 2,084 donors. Some of the antigens are already typed in higher numbers of donors such as Vel (2,748 donors), Yta/b (2,738), HPA-1 (2,449), HNA-1 (2,746), HNA-2 (3,399) and others (table 3).

In this study we also describe a feasible method for fast and easy molecular screening to identify HNA-2null individuals. The method is based on TaqMan™ PCR with endpoint fluorescence detection and can be easily adapted to medium or high throughput. Using the 96-well format in standard PCR cyclers more than 1,000 donors can be typed per day. CAVE: only individuals homozygous for the null mutation c.787A>T in both genes CD177 and CD177P1 are typed as HNA-2null. If the mutation is homozygous in CD177 but heterozygous or absent in CD177P1, these individuals are also HNA-2null, but are not recognized by the TaqMan™ PCR method. Other null variants of CD177 are also not detected.

Most of the allele frequencies observed in our cohort were similar to the frequencies reported for non-Finnish Europeans in the ExAC database [27]. Only 5 of the 25 alleles with clear information in the database revealed a significant difference. This probably results from the demographic characteristics of the urban area in which our institute is located. As of 2016, the population of Mannheim includes 44.7% immigrants, of which at least 70% belong to countries with a predominantly Caucasian population [18]. About 12% have Asian ancestry and 5% are African. However, we do not know the portion of immigrants in our donor population. At least for the Fynull phenotype that is most prevalent in Africans and which we found in 6 of our donors (0.3%), we can assume a significant number of donors with African ancestry. Another example could be the SLC44A2*c.461A allele encoding the HNA-3b antigen. According to ExAC data it is more prevalent in East Asians (0.3091) than in non-Finnish Europeans (0.2094), and the MAF was 0.2358 in our cohort. Thus, the differences in allele frequencies in our donor population compared to the general European population could be attributed to a certain number of donors with African or Asian ancestry.

Immigration to Central Europe in general may increase the number of patients with sickle cell anemia or other hemoglobinopathies. The transfusion therapy of such patients is challenging because of a frequent blood demand and because of antigens with different prevalence in other populations. The concept of extended matching in transfusion therapy of such patients is appropriate to prevent alloimmunization events [28, 29, 30]. Especially, patients who were already immunized by past transfusion could benefit from extensive antigen matching beyond C/c, E/e, and K [31, 32]. As recently reported in a large cohort of transfused patients, the most immunogenic antigens were in order K, E, CW, e, Jka, c, and Fya[33]. Among the 2,084 donors typed for these antigens, we could identify 22 donors negative for K, E, Jka, c, and Fya as well as 22 donors negative for D, K, E, Jka, and Fya. Three donors were negative for a number of clinically relevant antigens: A, B, C, D, E, K, Jka, Fya, M, and S.

Based on our experiences we attempt to establish a regional registry of extended typed blood donors to provide fresh RBC units with special blood types on demand. Similar concepts for the extended matched blood supply are established in different countries worldwide [34, 35, 36, 37].

Disclosure Statement

The authors declare no conflict of interest.

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