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Mass-scale red cell genotyping of blood donors
Transfusion and Apheresis Science 44 (2011) 93–99
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Transfusion and Apheresis Science journal homepage: www.elsevier.com/locate/transci
Mass-scale red cell genotyping of blood donors Gregory A. Denomme a,⇑, Susan T. Johnson b, Bradley C. Pietz c a b c
Immunohematolgy Reference Laboratory, Blood Center of Wisconsin, 638 18th Street, Milwaukee, WI 53201-2178, United States Clinical Education, Blood Center of Wisconsin, 638 18th Street, Milwaukee, WI 53201-2178, United States Product Development Laboratory, Blood Center of Wisconsin, 638 18th Street, Milwaukee, WI 53201-2178, United States
a r t i c l e
i n f o
Keywords: Red cell genotyping Single nucleotide polymorphisms Molecular immunohematology
a b s t r a c t Blood centers are able to recruit and process large numbers of blood donations to meet the demand for antigen-matched blood. However, there are limitations with the use of hemagglutination that can be circumvented with blood group genotyping. Antisera do not exist for several clinically important blood group antigens and many methods have been developed (direct hemagglutination, indirect antiglobulin-dependent, solid phase, or gel column). There is increasing interest to apply mass-scale red cell genotyping of blood donors to find rare (predicted) phenotypes, rare combinations of antigens and locus haplotypes, and to have access to information on the common clinically relevant blood group antigens. This review outlines technological advances, emerging algorithms, and the future of mass-scale red cell genotyping of blood donors. Ó 2011 Elsevier Ltd. All rights reserved.
1. Introduction Transfusion medicine has relied continually on the principles of Landsteiner’s seminal work on the expression of polymorphic structures on human red cells [1]. This early serological work laid the foundation for antibody detection of blood group antigens. For the past 60 years, serological analyses used to confirm the presence (or absence) of blood group antigens on the surface of red blood cells formed the critical steps in the provision of antigen-compatible blood for many transfusion recipients. The transfusion community first applied the serological approach to antigen testing to avoid the immunogenicity of the D antigen. In 1939, serological investigations of ictus gravis/ erythroblastosis fetalis ultimately lead to the discovery of the Rh blood group system [2]. This publication not only hypothesized that the fetus was affected by maternal alloimmunization to the D antigen, but it also outlined the seriousness associated with the transfusion of incompatible blood (unrecognized at the time) after the woman was transfused with her husband’s blood! It was not long ⇑ Corresponding author. Tel.: +1 414 937 6440, fax: +1 414 937 6404. E-mail address: [email protected] (G.A. Denomme). 1473-0502/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.transci.2010.12.012
after this landmark publication that transfusions of Rh positive blood to Rh negative individuals were avoided. For safe transfusions, transfusion service laboratories were formed and ‘blood banks’ evolved into blood centers, with donor recruitment and high volume processes developed to meet the demand for blood. Today, over 300 blood group antigens have been characterized. Nearly all were identified using serological techniques to confirm expression with hemagglutination, which is the ‘gold standard’ for which transfusions are administered. Hemagglutination is sensitive and relatively inexpensive to perform, and when the correct algorithms are applied (e.g. the electronic crossmatch), is an efficient and relatively safe way to provide blood. However, there are limitations with the use of hemagglutination alone as the sole means to ensure that the right patient gets the right blood at the right time [3]. The field of immunohematology is recognizing that blood group genotyping has benefits to the patient as a means to screen and identify blood group antigens. The analysis of the molecular basis for blood group expression (see review in this publication) has unraveled the nucleotide changes responsible for nearly all blood group antigens. Surprisingly, the molecular determinants
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for many clinically important blood group antigens are due to a single nucleotide polymorphism (SNP) [4]. More importantly, the genetic information has led to the realization that there are many more alleles than antigens, and that the analysis for the presence of specific alleles has clinical applications in immunohematology [5]. For example, the RH system has 57 antigens defined, yet RHD has over 200 alleles. Several molecular techniques used to identify SNPs have become very accurate and in some instances are superior to serological methods for resolving serological discrepancies [6–9]. Clinical diagnostic laboratories have adopted molecular techniques to predict blood group antigens and there is increasing interest to apply mass-scale red cell genotyping of blood donors to find rare (predicted) phenotypes, rare combinations of phenotypes, and to have access to the many clinically relevant common blood group antigens. Mass-scale red cell genotyping of blood donors can be designed to screen for multiple blood group antigens using a single method (detecting an A, C, G, or T nucleotide at a specific location) and can be performed more rapidly than serological methods alone. Antisera do not exist for several clinically important blood group antigens and many methods have been developed (direct hemagglutination, indirect antiglobulin-dependent, solid phase, or gel column). However, mass-scale red cell genotyping, when applied correctly, can use identical methodology for all SNP-encoded antigens and therefore has far reaching implication to meet the need for blood transfusion [10,11]. This review will outline technological advances, emerging algorithms, and the future of mass-scale red cell genotyping of blood donors. Within the next few years, red cell genotyping of donors is poised to change how and when antigen-negative and antigen-matched blood is provided to transfusion recipients. It is obvious to envision these technological advances in red cell genotyping playing a central role in the prevention of red cell alloimmunization.
2. Historical perspective Immunohematology laboratories applied manual molecular methods to red cell genotyping that were largely time and resource consuming. The first methods used the polymerase chain reaction (PCR) coupled with restriction fragment length polymorphisms to identify a small number of clinically important antigens [12]. It was quickly realized that other less cumbersome techniques were more rapid but were no less sensitive (allele-specific PCR). Then, direct or ‘real-time’ instruments became available that performed the same tasks without downstream manipulation. In all instances, the methods were designed and validated as laboratory developed tests (LDTs) that had limited use and required statements of claim or disclosure on clinical reports. Red cell genotyping is not without challenges. First, the molecular basis for some blood group antigens is not based on SNPs (e.g. RHD deletion) and therefore, molecular methods must have a built in control in the absence of a PCR product. Second, a few important blood group antigens are not the expressed product of the gene. All carbohydrate
antigens fall into this classification. Some of these antigens can be identified quite simply, but many variants exist in low frequency. Third, multi-genic loci have the additional complication of gene-specific amplification; care must be taken in the assay design to avoid detecting irrelevant homologous genes. Fourth, distant genetic changes can alter expression of the antigen (e.g. FY GATA-1 promoter mutation at position -67), and these changes can fail to predict the appropriate phenotype. Fifth, the presence of hybrid alleles for multi-genic loci and compound heterozygotes (possessing two rare alleles) can complicate the analysis. Finally, variant alleles are continually being discovered for several ethnicities not previously investigated. However, eventually molecular techniques will be applied accurately to account for all of the current challenges. The earliest version of high-throughput red cell genotyping was as a colorimetric-based PCR using a 96-well microplate format [13]. In 2005, four articles were published simultaneously that addressed red cell or platelet genotyping on a mass-scale [14–17]. These techniques could test several dozen samples, but were not linked to laboratory information systems. At the time, the techniques were not robust enough for test-of-record use and regulatory requirements to make the tests valid were onerous. It was proposed that these platforms could be used as screening tools to create large databases of useful genotype information [18]. Now, mass-scale red cell genotyping has progressed to the point where hundreds to thousands of samples can be tested per day. There is a concerted effort to develop validated processes which ensure accurate results and to link the data to donor information. Ultimately, this effort will enable efficiencies both within a blood center and the end user, the transfusion institute. 2.1. Red cell genotyping platforms Platforms for mass-scale genotyping use fall into four general categories (based on the underlying principle): PCR-oligonucleotide single-base extension technology, PCR or allele-specific PCR followed by probe hybridization, PCR followed by capillary electrophoresis (size fractionation), and nanofluidic technology coupled to real-time (TaqMan-based) technology. 2.2. PCR-oligonucleotide extension technology Several groups have reported on the principle of oligonucleotide extension technology coupled to PCR [15,17,18]. The principle for these platforms lies in the amplification primers designed to flank the SNP of interest, PCR performed in a multiplex reaction mixture, and oligonucleotide extension to interrogate the SNP of interest [19]. Primer-design requires careful placement to avoid cross-amplification of homologous genes. Following PCR, a single strand is hybridized to a probe that is directly proximal to the SNP of interest. A round of single-base oligonucleotide extension is performed in the presence of two fluorescent dideoxynucleotides. The probe is captured and laser excitation of the reaction can measure the incorporated nucleotide(s), which reflect the presence of either
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or both SNPs. The technology is robust; it appears that natural misincorporation of nucleotides does not lead to significant background noise or detection errors. It has the limitation of detecting two nucleotides only, although additional fluorochromes are now available. 2.3. PCR-probe hybridization The principle of this technique is also based on multiplex PCR. Design modifications can be made to work specifically with large mixtures of primers, including allele-specific primers and primers containing linkers to enhance specificity. The PCR products are labeled either during or after amplification [20,21]. In one application, hybridization is made to a number of reiterative probes containing either nucleotide of interest and the results are displayed in an array format. Depending on the probe, the amplified products behave differently and therefore, variant alleles can be detected. Moreover, the technology provides more information for subtle nucleotide differences near the SNP due to the reiterative nature of the hybridization. Generally, platforms based on this technology are more robust but sacrifice some level of highthroughput capacity. 2.4. PCR followed by capillary electrophoresis Here, high-fidelity is achieved with the benefit of highthroughput [22,23]. This platform has been designed as a specific screening tool, with more downstream work needed to confirm the potential genotypes of interest. Generally, this technology is appropriate to identify antigennegative donors among high prevalence alleles (e.g. Yta, Coa, Lub, Kpb). Due to the nature of the number of alleles expected, a high volume of confirmatory work is not anticipated. Although the percentage of interpretable results is low (85%), efficiencies are made in terms of costs and staffing needed to perform the tests. 2.5. Nanofluidic technology coupled to real-time PCR True high-throughput technology platforms should evaluate large number of samples for many SNPs in a short period of time with a minimal cost of reagents and hands-on time [24]. Nanofluidic PCR addresses these requirements, with single PCRs used to avoid the problems associated with multiplex design, and a vast increase in numbers due to the nano-scale. The reduction of scale allows arrays consisting of 3072 through-holes (openarrays) designed in 48 sets of 64 nano-wells on a stainless steel plate about ½ the size of a standard microscope slide. Due to the hydrophobic nature of the exterior and hydrophilic nature of the interior, DNA and reaction mixes of 33 nL can be held in the wells and subjected to thermalcycling. Each nano-well is a separate PCR and therefore design is simple. The advantage of this platform is the reduction of cost and the flexibility of design. Various testing layouts can be performed because of the matrix design. Rather than 3072 tests, 64 tests on 48 donor samples, or 32 duplicate tests of 48 samples (and so on) can be performed on a single openarray.
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Regardless of the choice of platform, mass-scale red cell genotyping using high-throughput devices should overcome issues related to the accuracy of the result. Even when used as a screening tool, the cost and the ability to obtain results within a reliable timeframe (<36 h) is possible. Ultimately, to be truly useful, mass-scale red cell genotyping must be completed before a donated unit has been released for transfusion. In this way, even valuable firsttime donors can be evaluated for their constellation of blood group antigen SNPs. 3. Applications of mass-scale red cell genotyping 3.1. Red cell genotyping of clinically significant minor blood group antigens Genomic DNA-based high-throughput assays are attractive alternatives to phenotyping because they are built on a simple common method. Such platforms provide a tool to increase the antigen-negative inventory at a fraction of the cost associated with serology. In reality, phenotyping as a means to confirm antigen-negative units of blood for common antigens is not a problem. The problem lies in testing many units that are antigen positive. Thus, DNAbased testing as a screening tool is akin to the use of an unlicensed non-validated red cell alloantibody (anti-e) in a transfusion recipient’s serum. The difference here is many donors whose red cells are positive for common clinically significant minor blood group antigens can be prescreened out before confirmatory testing. After screening (as with antibody-based testing), the confirmatory serological test need be done only on the identified donors of interest. This approach conserves valuable antisera for those donors whose red cells are likely antigen-negative. The cost and resource efficiencies are further gained when multiple antigen-negative donors are found [e.g. R2R2, K-, S-, Fy(a-), Jk(-a)]. Knowledge of the combined antigen frequency within the donor population, and using binomial distribution, one can predict the number of donors to test to achieve the required number of units. For example, the combined frequency of group O R2R2, K-, S-, Fy(a-), Jk(a-) is
0:4 0:02 0:45 0:9 0:34 0:24 ¼ 2:64 104
ð1Þ
Using binomial distribution such that,
Pðn; r; pÞ ¼
n! pr ð1 pÞnr r!ðn rÞ!
ð2Þ
(where, n = # of donors, r = # of outcomes, p = frequency of outcome)it is estimated that there is only an 75% probability outcome of at least 2 group O positive donors or more with this combined antigen phenotype when 10,000 donors are screened, i.e.
1 ½Pð104 ; 0; 2:64 104 Þ þ Pð104 ; 1; 2:64 104 Þ ¼ 0:741 ð2:1Þ Unfortunately, the calculation does not take into account the probably of the demand for these units. Unpredictable demand requires frozen blood and shared rare donor programs like the American Rare Donor Program
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(ARDP). Nevertheless, given low frequency events, laboratories that use high throughput screening are wise to evaluate their population antigen frequencies before embarking on a search for rare combined antigen-negative donors. Local population frequencies may differ from published frequencies. Targeting donors who are most likely to repeat their donation for testing can maximize the database size. And, as yet to be explored, red cell genotyping could be used as a recruitment tool. All blood donations save lives, but just like O Rh negative, rare antigen-negative donors (identified through genotype screening) could be approached about the value of their multiple antigennegative blood types. The approach, however, has yet to be defined. DNA-based assays are invaluable to predict antigens when antisera are not readily available. Doa/b, Jsa/b, V and VS fall into this category. The ARDP accepts DNA testing information in order to provide antigen-negative blood for special circumstances where serological data is not possible. Compatibility testing and medical oversight are required to coordinate transfusions under these circumstances. One important contribution of red cell genotyping is that a genotype plus a phenotype has more information content than a phenotype alone. In other words, evaluating the underlying genetic basis of blood group expression and the expressed antigen itself is a check for the presence of weak antigens like D and Fyb. A genotype and phenotype may be warranted for blood group systems with a high number of variant alleles or null phenotypes (MNS, RH, JK). 3.2. Red cell genotyping for high-prevalence antigens Mass-scale red cell genotyping also lends itself to the detection of rare antigen-negative phenotypes for some of the high-prevalence antigens Kpb, Lub, Dib, Yta, Coa and Sc1 to which individuals more commonly produce antibodies. It is worthwhile to test for the SNP associated with these antigen-negative phenotypes if large numbers of donors are being tested for common clinically significant blood group genotypes. In fact, red cell genotyping is superior to testing for those antigens where antisera are available, because SNPs can be added to the platform at a small incremental cost to the design. Genotyping for a few high-prevalence antigens awaits the discovery of their molecular basis (Vel, Lan, Ata, and Jra). Once identified, laboratories should target testing for the remaining rare antigen-negative types in areas where founder alleles are most likely to be present. The identification of founder alleles and knowledge of donor demographics such as zip code could be used to maximize the search for such donors. This strategy is similar to the testing of siblings of individuals with rare antigen-negative blood types.
were found among the 46,133 Rh negative donors [25]. Importantly, some relatively high antigen copy number weak D variants were found including Weak D Type 11 in trans with an r0 allele. Clearly, these donors could be identified and deemed Rh positive to minimize exposure to women of childbearing age and young girls. 4. Validation of red cell genotyping platforms 4.1. Validating genotyping platforms Much like validation of unlicensed antisera, red cell genotyping as a test-of-record will necessitate validation comparing the predicted phenotype to the serological phenotype. Subsequently, it will be more beneficial to simply match the genotype of the patient and the blood donor. Most if not all genotyping platforms use robust chemistries, allowing for the analysis of multiple probes without cross-interference, and can be linked reliably to automated equipment to reduce hands-on time. Of course, the scientific community already has a good understanding of which SNPs are problematic, and have started to build in additional SNPs and logic tables to handle these anomalies. It is somewhat surprising that the validation of red cell genotyping for some SNPs has been slow given that only 500 samples are required to validate a given antibody. For example, the fidelity of KEL⁄1/KEL⁄2 is high and therefore, validation should be simple. But, given the multiple SNPs incorporated along with KEL⁄1/KEL⁄2 into array platforms, and the need for post analytical data handling, validation of a complete platform capable of analyzing and associating SNPs with clinically relevant blood group antigens is forthcoming. Additional problems lie in the validation of these assays for populations where genotypic information is sparse. Several blood group systems have a relatively high number of variants linked to certain ethnicities and arrays must be capable of detecting these variants without fail (or rather be no less accurate than monoclonal antibodies, some of which also have inherent problems) [26–28]. Regulatory requirements also affect how red cell genotyping information can be used. Questions arise related to how the information should be conveyed to the end user, what additional review and reflex testing should accompany the use of the blood on the current donation, the labeling of subsequent donations, and how results are maintained all require careful consideration. The fact that testing can be done in the absence of antisera complicates what constitutes regulatory compliance. Generally speaking, LDTs are restricted to investigational use only and the results should be confirmed with a licensed reagent. A crossmatch is required if no reagent is available.
3.3. RHD red cell genotyping
4.2. Post analytical data handling
An argument should be made for the mass-scale screening of blood donors for the presence of a functional RHD allele. The 6-year experience in Germany attests to the fact that functional RHD alleles are among the apparent Rh negative population of blood donors. A total of 97 RHD alleles
By nature of the design, high throughput testing results in the generation of an enormous amount of information. The genotyping platform itself must be capable of translating signals into output data by using a ‘rules engine’ to display the results in a meaningful way to the operator. At this
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point, the operator should have control over accepting sample, SNP, array and run data. The operator should have clear acceptance criteria by which data is suitable for commitment to the repository of data. Also, suitable controls must be included to evaluate acceptance of the run data. More important in the process is the ability to identify rare alleles for further confirmation, to flag unusual SNP results or combined SNPs (haplotypes), and to trace identification numbers back to the primary sample. Equally important is the ability to display the information in parallel with key donor information; their ABO/Rh blood group, the date of donation, frequency of donation, and the unit ID number. Moreover, placing an electronic flag on the donor’s file can identify the donor for additional confirmatory testing on the next donation.
5. Integration of red cell genotyping High throughput platforms are now poised to allow key patient groups to be transfused with antigen-matched blood. Alloimmunization is reduced for Sickle Cell disease patients when matched transfusions are given [29,30]. But also, myelodysplasia and aplastic anemia could obviously benefit from antigen-matched transfusions [31,32]. In addition, evidenced-based trials may determine that patients in intensive care units who have been transfused or have a history of pregnancy could benefit. The least of which, E, Jsa, Fy and Jk would be likely antigens to match given FDA/CBER and United Kingdom data [33,34]. The transfusion community should prioritize which antigens to match because (1) at present it is not possible to identify which patients will make alloantibodies and (2) it becomes increasingly difficult to find antigen-negative donors as more antigens are considered for a match. As red cell genotyping becomes a standard of practice, additional patients could benefit from genotype-matched transfusion. It would be interesting to quantify the quality-adjusted life year benefit for females in neonatal intensive care units who receive antigen-matched blood. Such an investment in a young population is not unprecedented; pediatric packed red cell units limit the number of donor exposures to the neonatal population [35]. Two issues remain with the use of red cell genotyping as a screening tool in a blood center or for the patient population. First, to be useful in the clinical setting, the turnaround time for results must be more rapid. Genotyping methods that take two or three days to complete do not serve all patients who are in need of matched transfusions. Second, the data from genotyping platforms needs to be integrated into the process of donor collection and routine blood banking. Incorporating red cell genotyping into the routine practice of a blood center and transfusion service could provide a process to control which units are to be tested, and which should be diverted to protected inventory. It should also identify a need and allow queries of the current inventory for available units, and who is available for recall. Ideally, the process should translate the genotype into a predicted phenotype and compare this information to any historical or current serological phenotype. Discrepancies should be reported, investigated and
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resolved if possible. In addition, new carriers of blood group antigen variants may be discovered. Also, an additional feature should include RHD SNPs so that the DNA of each Rh negative donor can be interrogated for the presence of RHD [25]. 5.1. Donor selection and DNA isolation Selection of donors for red cell genotyping can be controlled by existing blood center software systems (MAK Progesa, LifeTrak, etc.). The most important tool for this part of the process is a daily electronic query. The query provides a list of donor samples that qualify for red cell genotyping, based on a pre-determined set of criteria (donor age, ABO, frequency of donation, ethnicity, etc). Extraction platforms that can isolate DNA on up to 1000 samples per day are suitable for high throughput array analysis. Results obtained within 24 h after the unit has been released to inventory minimizes the ‘hold’ time. This is an important feature to realize the benefits of ‘‘on-time’’ red cell genotyping. With on-time testing, selected firsttime donors (e.g. based on ethnicity) can be tested and only rare and desired antigen-negative units are retained for the screened unit inventory before the unit leaves the blood center. 5.2. Integration of red cell genotypes Red cell genotyping information is provided by the high throughput instrument. Data handling is critical to the integration of red cell genotype information. Key to the design of the process is the use of the ISBT 128 barcode from the existing blood sample throughout the process. Importing the instrument data into a ‘‘rules engine’’ allows staging and control of the translation function. The staging area allows an opportunity to build complex rules like haplotypes (combinations of SNPs) before the data is merged with the blood donor’s file. Management of the rules engine can be handled separately by a skilled operator who has a thorough knowledge of blood group genetics. This component also provides control to add new SNPs or refine relationships between SNPs as new knowledge is gained. The rules engine can then package the translations into donor and patient databases (Fig. 1). In addition, clinical trials and research initiatives could be separate database and the rules engine could translate other SNP data like human platelet antigen genotypes. 5.3. Advances in red cell genotyping Enabling a comparison of the predicted phenotype and the known phenotype is the first step in the implementation of red cell genotyping. The next advances are to type both donors and patients rapidly so that the appropriate transfusion is provided. Again, with the goal being the right blood, to the right patient, at the right time. Validation of red cell genotyping as a test-of-record will enable the genotyping of yet larger donor populations where confirmation of the phenotype is not necessary (antigen-matching in place of random ABO/Rh compatible blood). Another advance will be to allow the hospital transfusion service to
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Fig. 1. Operational design of red cell genotyping. Ideally, SNP data (A, C, G and T) is first translated by a rules engine and the data indexed or packaged for downstream use. User interfaces will display the predicted phenotype with any known phenotype information in donor and patient records.
Phase
Solution Objective
I
Find rare and uncommon blood types Enable comparison of predicted phenotype to known serotype
II
Enable genotyping of larger donor populations where phenotype is not known in advance Antigen-matched services becomes a reality for specific patients
III
Blood center provides antigen-matched blood for patients Enable hospital customer to view red cell genotype results
IV
Red cell genotyping validated as a test-of-record
Fig. 2. Stepwise advancements in red cell genotyping. The initial phase for the development showed red cell genotyping is a useful screening tool. Key advancements can occur to provide efficiencies in the provision of matched blood to patients, before red cell genotyping becomes a test-of-record.
view the results of red cell genotyping. Significant resource savings could be realized. Imagine the serological confirmation of the 3 or 4 units that are known to be FYAnegative versus the testing of 20 or more RBC units with anti-Fya. Viewing red cell genotype data could be through a blood center portal or the information could be linked to an RFID tag [36]. Finally, enabling hospitals to order antigen-negative blood through existing channels could optimize end user inventory levels (maximizing flexibility of the overall inventory) because there would be no need to hold large inventories for antigen-negative units. In summary, stepwise advancements for the implementation of red cell genotyping will see the technology move from a screening tool, to the genotyping of large donor populations, providing transfusion services with information to create efficiencies, and finally providing the results as a test-of-record (Fig. 2). 6. The future of red cell genotyping It is not a feasible goal to provide a complete antigenmatch blood transfusion to all patients for all antigens. The inventory for such matches cannot be large enough
to accommodate all scenarios; the example in this review shows the need for more donor blood than is available or feasible. However, patients can be screened for the lack of high-prevalence antigens, and perhaps they should receive antigen-negative blood for these negative types, and also be matched for clinically significant alloantibodies when possible. Although debatable, the transfusion medicine community has sufficient information to make decisions on which antigens are important. Moreover, research should continue to unravel the antigen recognition, presentation, and immune response elements involved in red cell alloimmunization. ‘‘Good responders’’ could be managed differently depending on which antigens their immune system recognize than patients who will not respond, or who will respond to some of the less common alloantigens. Genotyping algorithms will ultimately be as robust as serology given the appropriate knowledge from all the major ethnic groups. The future for red cell genotyping will see an integration of the technology in parallel with existing donor and patient electronic information systems. There will be a reduction in hemolytic transfusion reactions, improvement in the appropriate blood provided to patients with Sickle
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Cell disease, maximized red cell survival for autoimmune hemolytic anemia, and a reduction in red cell alloimmunization. A quality product will be produced that has been screened for weak and variable expression of antigens that serological based assays cannot detect. For patients with complex serological problems, red cell genotyping will create a paradigm shift in their care, and help provide the right blood quicker. Red cell genotyping is a powerful tool that will revolutionize the transfusion of red cells to humans. References [1] Landsteiner K. Agglutinationserscheinungen normalen menschlichen blutes. Wien Klin Wochenschr 1901;14:1132–4. [2] Levine P, Stetson RE. Landmark article July 8, 1939. An unusual case of intra-group agglutination by Philip Levine and Rufus E Stetson. JAMA 1984;251:1316–7. [3] Letowska M. Patient-specific component requirements: ‘right blood, right patient, right time, right place’. ISBT Sci Ser 2009;4:52–5. [4] Daniels G. The molecular genetics of blood group polymorphism. Transpl Immunol 2005;14:143–53. [5] Denomme GA, Flegel WA. Applying molecular immunohematology discoveries to standards of practice in blood banks: now is the time. Transfusion 2008;48:2461–75. [6] Denomme GA, Wagner FF, Fernandes BJ, Li W, Flegel WA. Partial D, weak D types, and novel RHD alleles among 33, 864 multiethnic patients: implications for anti-D alloimmunization and prevention. Transfusion 2005;45:1554–60. [7] Storry JR, Olsson ML. The ABO blood group system revisited: a review and update. Immunohematology 2009;25:48–59. [8] Wester ES, Gustafsson J, Snell B, Spruell P, Hellberg A, Olsson ML, et al. A simple screening assay for the most common JK⁄0 alleles revealed compound heterozygosity in Jk(a-b-) probands from Guam. Immunohematology 2009;25:165–9. [9] Vege S, Westhoff CM. Molecular characterization of GYPB and RH in donors in the American Rare Donor Program. Immunohematology 2006;22:143–7. [10] Veldhuisen B, van der Schoot CE, De HM. Blood group genotyping: from patient to high-throughput donor screening. Vox Sang 2009;97:198–206. [11] Strauss D, Reid ME. Value of DNA-based assays for donor screening and regulatory issues. Immunohematology 2008;24:175–9. [12] Denomme GA, Rios M, Reid ME. Molecular Protocols in Transfusion Medicine. San Diego: Academic Press; 2000. [13] Montpetit A, Phillips MS, Mongrain I, Lemieux R, St-Louis M. Highthroughput molecular profiling of blood donors for minor red blood cell and platelet antigens. Transfusion 2006;46:841–8. [14] Bugert P, McBride S, Smith G, Dugrillon A, Kluter H, Ouwehand WH, et al. Microarray-based genotyping for blood groups: comparison of gene array and 50 -nuclease assay techniques with human platelet antigen as a model. Transfusion 2005;45:654–9. [15] Denomme GA, Van OM. High-throughput multiplex singlenucleotide polymorphism analysis for red cell and platelet antigen genotypes. Transfusion 2005;45:660–6. [16] Beiboer SH, Wieringa-Jelsma T, Maaskant-Van Wijk PA, van der Schoot CE, van ZR, Roos D, et al. Rapid genotyping of blood group antigens by multiplex polymerase chain reaction and DNA microarray hybridization. Transfusion 2005;45:667–79. [17] Hashmi G, Shariff T, Seul M, Vissavajjhala P, Hue-Roye K, CharlesPierre D, et al. A flexible array format for large-scale, rapid blood group DNA typing. Transfusion 2005;45:680–8.
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[18] Perreault J, Lavoie J, Painchaud P, Cote M, Constanzo-Yanez J, Cote R, et al. Set-up and routine use of a database of 10, 555 genotyped blood donors to facilitate the screening of compatible blood components for alloimmunized patients. Vox Sang 2009;97:61–8. [19] Denomme GA. Single base extension in multiplex blood group genotyping. Methods Mol Biol 2009;496:15–24. [20] Avent ND, Martinez A, Flegel WA, Olsson ML, Scott ML, Nogués N, et al. The BloodGen project: toward mass-scale comprehensive genotyping of blood donors in the European union and beyond. Vox Sang 2007;96:40S–6S. [21] Karpasitou K, Drago F, Crespiatico L, Paccapelo C, Truglio F, Frison S, et al. Blood group genotyping for Jk(a)/Jk(b), Fy(a)/Fy(b), S/s, K/k, Kp(a)/Kp(b), Js(a)/Js(b), Co(a)/Co(b), and Lu(a)/Lu(b) with microarray beads. Transfusion 2008;48:505–12. [22] Wagner FF, Bittner R, Petershofen EK, Doescher A, Muller TH. Costefficient sequence-specific priming-polymerase chain reaction screening for blood donors with rare phenotypes. Transfusion 2008;48:1169–73. [23] Palacajornsuk P, Halter C, Isakova V, Tarnawski M, Farmar J, Reid ME, et al. Detection of blood group genes using multiplex SNaPshot method. Transfusion 2009;49:740–9. [24] Hopp K, Weber K, Bellissimo D, Johnson ST, Pietz B. High-throughput red blood cell antigen genotyping using a nanofluidic real-time polymerase chain reaction platform. Transfusion 2010;50:40–6. [25] Flegel WA, Von I Z, Wagner FF. Six years’ experience performing RHD genotyping to confirm D- red blood cell units in Germany for preventing anti-D immunizations. Transfusion 2009;49:465–71. [26] Westhoff CM, Silberstein LE, Wylie DE, Skavdahl M, Reid ME. 16Cys encoded by the RHce gene is associated with altered expression of the e antigen and is frequent in the R0 haplotype. Br J Haematol 2001;113:666–71. [27] Noizat-Pirenne F, Lee K, Pennec PY, Simon P, Kazup P, Bachir D, et al. Rare RHCE phenotypes in black individuals of Afro-Caribbean origin: identification and transfusion safety. Blood 2002;100:4223–31. [28] Noizat-Pirenne F, Le Pennec PY, Mouro I, Rouzaud AM, Juszczak G, Roussel M, et al. Molecular background of D(C)(e) haplotypes within the white population. Transfusion 2002;42:627–33. [29] Castilho L, Rios M, Bianco C, Pellegrino Jr J, Alberto FL, Saad ST, et al. DNA-based typing of blood groups for the management of multiplytransfused sickle cell disease patients. Transfusion 2002;42:232–8. [30] Castro O, Sandler SG, Houston-Yu P, Rana S. Predicting the effect of transfusing only phenotype-matched RBCs to patients with sickle cell disease: theoretical and practical implications. Transfusion 2002;42:684–90. [31] Seyfried H, Walewska I. Analysis of immune response to red blood cell antigens in multitransfused patients with different diseases. Mater Med Pol 1990;22:21–5. [32] Shirey RS, Boyd JS, Parwani AV, Tanz WS, Ness PM, King KE. Prophylactic antigen-matched donor blood for patients with warm autoantibodies: an algorithm for transfusion management. Transfusion 2002;42:1435–41. [33] Chapman CE, Stainsby D, Jones H, Love E, Massey E, Win N, et al. Ten years of hemovigilance reports of transfusion-related acute lung injury in the United Kingdom and the impact of preferential use of male donor plasma. Transfusion 2009;49:440–52. [34] FDA/Center for Biologics Evaluation and Research: Fatalities Reported to FDA Following Blood Collection and Transfusion: Annual Summary for Fiscal Year 2008. www.fda.gov/BiologicsBlood Vaccines/SafetyAvailability/ReportaProblem/TransfusionDonation Fatalities/ucm113649.htm 2010. [35] Luban NL. Neonatal red blood cell transfusions. Curr Opin Hematol 2002;9:533–6. [36] Davis R, Geiger B, Gutierrez A, Heaser J, Veeramani D. Tracking blood products in blood centres using radio frequency identification: a comprehensive assessment. Vox Sang 2009;97:50–60.
Contents lists available at ScienceDirect
Transfusion and Apheresis Science journal homepage: www.elsevier.com/locate/transci
Mass-scale red cell genotyping of blood donors Gregory A. Denomme a,⇑, Susan T. Johnson b, Bradley C. Pietz c a b c
Immunohematolgy Reference Laboratory, Blood Center of Wisconsin, 638 18th Street, Milwaukee, WI 53201-2178, United States Clinical Education, Blood Center of Wisconsin, 638 18th Street, Milwaukee, WI 53201-2178, United States Product Development Laboratory, Blood Center of Wisconsin, 638 18th Street, Milwaukee, WI 53201-2178, United States
a r t i c l e
i n f o
Keywords: Red cell genotyping Single nucleotide polymorphisms Molecular immunohematology
a b s t r a c t Blood centers are able to recruit and process large numbers of blood donations to meet the demand for antigen-matched blood. However, there are limitations with the use of hemagglutination that can be circumvented with blood group genotyping. Antisera do not exist for several clinically important blood group antigens and many methods have been developed (direct hemagglutination, indirect antiglobulin-dependent, solid phase, or gel column). There is increasing interest to apply mass-scale red cell genotyping of blood donors to find rare (predicted) phenotypes, rare combinations of antigens and locus haplotypes, and to have access to information on the common clinically relevant blood group antigens. This review outlines technological advances, emerging algorithms, and the future of mass-scale red cell genotyping of blood donors. Ó 2011 Elsevier Ltd. All rights reserved.
1. Introduction Transfusion medicine has relied continually on the principles of Landsteiner’s seminal work on the expression of polymorphic structures on human red cells [1]. This early serological work laid the foundation for antibody detection of blood group antigens. For the past 60 years, serological analyses used to confirm the presence (or absence) of blood group antigens on the surface of red blood cells formed the critical steps in the provision of antigen-compatible blood for many transfusion recipients. The transfusion community first applied the serological approach to antigen testing to avoid the immunogenicity of the D antigen. In 1939, serological investigations of ictus gravis/ erythroblastosis fetalis ultimately lead to the discovery of the Rh blood group system [2]. This publication not only hypothesized that the fetus was affected by maternal alloimmunization to the D antigen, but it also outlined the seriousness associated with the transfusion of incompatible blood (unrecognized at the time) after the woman was transfused with her husband’s blood! It was not long ⇑ Corresponding author. Tel.: +1 414 937 6440, fax: +1 414 937 6404. E-mail address: [email protected] (G.A. Denomme). 1473-0502/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.transci.2010.12.012
after this landmark publication that transfusions of Rh positive blood to Rh negative individuals were avoided. For safe transfusions, transfusion service laboratories were formed and ‘blood banks’ evolved into blood centers, with donor recruitment and high volume processes developed to meet the demand for blood. Today, over 300 blood group antigens have been characterized. Nearly all were identified using serological techniques to confirm expression with hemagglutination, which is the ‘gold standard’ for which transfusions are administered. Hemagglutination is sensitive and relatively inexpensive to perform, and when the correct algorithms are applied (e.g. the electronic crossmatch), is an efficient and relatively safe way to provide blood. However, there are limitations with the use of hemagglutination alone as the sole means to ensure that the right patient gets the right blood at the right time [3]. The field of immunohematology is recognizing that blood group genotyping has benefits to the patient as a means to screen and identify blood group antigens. The analysis of the molecular basis for blood group expression (see review in this publication) has unraveled the nucleotide changes responsible for nearly all blood group antigens. Surprisingly, the molecular determinants
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for many clinically important blood group antigens are due to a single nucleotide polymorphism (SNP) [4]. More importantly, the genetic information has led to the realization that there are many more alleles than antigens, and that the analysis for the presence of specific alleles has clinical applications in immunohematology [5]. For example, the RH system has 57 antigens defined, yet RHD has over 200 alleles. Several molecular techniques used to identify SNPs have become very accurate and in some instances are superior to serological methods for resolving serological discrepancies [6–9]. Clinical diagnostic laboratories have adopted molecular techniques to predict blood group antigens and there is increasing interest to apply mass-scale red cell genotyping of blood donors to find rare (predicted) phenotypes, rare combinations of phenotypes, and to have access to the many clinically relevant common blood group antigens. Mass-scale red cell genotyping of blood donors can be designed to screen for multiple blood group antigens using a single method (detecting an A, C, G, or T nucleotide at a specific location) and can be performed more rapidly than serological methods alone. Antisera do not exist for several clinically important blood group antigens and many methods have been developed (direct hemagglutination, indirect antiglobulin-dependent, solid phase, or gel column). However, mass-scale red cell genotyping, when applied correctly, can use identical methodology for all SNP-encoded antigens and therefore has far reaching implication to meet the need for blood transfusion [10,11]. This review will outline technological advances, emerging algorithms, and the future of mass-scale red cell genotyping of blood donors. Within the next few years, red cell genotyping of donors is poised to change how and when antigen-negative and antigen-matched blood is provided to transfusion recipients. It is obvious to envision these technological advances in red cell genotyping playing a central role in the prevention of red cell alloimmunization.
2. Historical perspective Immunohematology laboratories applied manual molecular methods to red cell genotyping that were largely time and resource consuming. The first methods used the polymerase chain reaction (PCR) coupled with restriction fragment length polymorphisms to identify a small number of clinically important antigens [12]. It was quickly realized that other less cumbersome techniques were more rapid but were no less sensitive (allele-specific PCR). Then, direct or ‘real-time’ instruments became available that performed the same tasks without downstream manipulation. In all instances, the methods were designed and validated as laboratory developed tests (LDTs) that had limited use and required statements of claim or disclosure on clinical reports. Red cell genotyping is not without challenges. First, the molecular basis for some blood group antigens is not based on SNPs (e.g. RHD deletion) and therefore, molecular methods must have a built in control in the absence of a PCR product. Second, a few important blood group antigens are not the expressed product of the gene. All carbohydrate
antigens fall into this classification. Some of these antigens can be identified quite simply, but many variants exist in low frequency. Third, multi-genic loci have the additional complication of gene-specific amplification; care must be taken in the assay design to avoid detecting irrelevant homologous genes. Fourth, distant genetic changes can alter expression of the antigen (e.g. FY GATA-1 promoter mutation at position -67), and these changes can fail to predict the appropriate phenotype. Fifth, the presence of hybrid alleles for multi-genic loci and compound heterozygotes (possessing two rare alleles) can complicate the analysis. Finally, variant alleles are continually being discovered for several ethnicities not previously investigated. However, eventually molecular techniques will be applied accurately to account for all of the current challenges. The earliest version of high-throughput red cell genotyping was as a colorimetric-based PCR using a 96-well microplate format [13]. In 2005, four articles were published simultaneously that addressed red cell or platelet genotyping on a mass-scale [14–17]. These techniques could test several dozen samples, but were not linked to laboratory information systems. At the time, the techniques were not robust enough for test-of-record use and regulatory requirements to make the tests valid were onerous. It was proposed that these platforms could be used as screening tools to create large databases of useful genotype information [18]. Now, mass-scale red cell genotyping has progressed to the point where hundreds to thousands of samples can be tested per day. There is a concerted effort to develop validated processes which ensure accurate results and to link the data to donor information. Ultimately, this effort will enable efficiencies both within a blood center and the end user, the transfusion institute. 2.1. Red cell genotyping platforms Platforms for mass-scale genotyping use fall into four general categories (based on the underlying principle): PCR-oligonucleotide single-base extension technology, PCR or allele-specific PCR followed by probe hybridization, PCR followed by capillary electrophoresis (size fractionation), and nanofluidic technology coupled to real-time (TaqMan-based) technology. 2.2. PCR-oligonucleotide extension technology Several groups have reported on the principle of oligonucleotide extension technology coupled to PCR [15,17,18]. The principle for these platforms lies in the amplification primers designed to flank the SNP of interest, PCR performed in a multiplex reaction mixture, and oligonucleotide extension to interrogate the SNP of interest [19]. Primer-design requires careful placement to avoid cross-amplification of homologous genes. Following PCR, a single strand is hybridized to a probe that is directly proximal to the SNP of interest. A round of single-base oligonucleotide extension is performed in the presence of two fluorescent dideoxynucleotides. The probe is captured and laser excitation of the reaction can measure the incorporated nucleotide(s), which reflect the presence of either
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or both SNPs. The technology is robust; it appears that natural misincorporation of nucleotides does not lead to significant background noise or detection errors. It has the limitation of detecting two nucleotides only, although additional fluorochromes are now available. 2.3. PCR-probe hybridization The principle of this technique is also based on multiplex PCR. Design modifications can be made to work specifically with large mixtures of primers, including allele-specific primers and primers containing linkers to enhance specificity. The PCR products are labeled either during or after amplification [20,21]. In one application, hybridization is made to a number of reiterative probes containing either nucleotide of interest and the results are displayed in an array format. Depending on the probe, the amplified products behave differently and therefore, variant alleles can be detected. Moreover, the technology provides more information for subtle nucleotide differences near the SNP due to the reiterative nature of the hybridization. Generally, platforms based on this technology are more robust but sacrifice some level of highthroughput capacity. 2.4. PCR followed by capillary electrophoresis Here, high-fidelity is achieved with the benefit of highthroughput [22,23]. This platform has been designed as a specific screening tool, with more downstream work needed to confirm the potential genotypes of interest. Generally, this technology is appropriate to identify antigennegative donors among high prevalence alleles (e.g. Yta, Coa, Lub, Kpb). Due to the nature of the number of alleles expected, a high volume of confirmatory work is not anticipated. Although the percentage of interpretable results is low (85%), efficiencies are made in terms of costs and staffing needed to perform the tests. 2.5. Nanofluidic technology coupled to real-time PCR True high-throughput technology platforms should evaluate large number of samples for many SNPs in a short period of time with a minimal cost of reagents and hands-on time [24]. Nanofluidic PCR addresses these requirements, with single PCRs used to avoid the problems associated with multiplex design, and a vast increase in numbers due to the nano-scale. The reduction of scale allows arrays consisting of 3072 through-holes (openarrays) designed in 48 sets of 64 nano-wells on a stainless steel plate about ½ the size of a standard microscope slide. Due to the hydrophobic nature of the exterior and hydrophilic nature of the interior, DNA and reaction mixes of 33 nL can be held in the wells and subjected to thermalcycling. Each nano-well is a separate PCR and therefore design is simple. The advantage of this platform is the reduction of cost and the flexibility of design. Various testing layouts can be performed because of the matrix design. Rather than 3072 tests, 64 tests on 48 donor samples, or 32 duplicate tests of 48 samples (and so on) can be performed on a single openarray.
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Regardless of the choice of platform, mass-scale red cell genotyping using high-throughput devices should overcome issues related to the accuracy of the result. Even when used as a screening tool, the cost and the ability to obtain results within a reliable timeframe (<36 h) is possible. Ultimately, to be truly useful, mass-scale red cell genotyping must be completed before a donated unit has been released for transfusion. In this way, even valuable firsttime donors can be evaluated for their constellation of blood group antigen SNPs. 3. Applications of mass-scale red cell genotyping 3.1. Red cell genotyping of clinically significant minor blood group antigens Genomic DNA-based high-throughput assays are attractive alternatives to phenotyping because they are built on a simple common method. Such platforms provide a tool to increase the antigen-negative inventory at a fraction of the cost associated with serology. In reality, phenotyping as a means to confirm antigen-negative units of blood for common antigens is not a problem. The problem lies in testing many units that are antigen positive. Thus, DNAbased testing as a screening tool is akin to the use of an unlicensed non-validated red cell alloantibody (anti-e) in a transfusion recipient’s serum. The difference here is many donors whose red cells are positive for common clinically significant minor blood group antigens can be prescreened out before confirmatory testing. After screening (as with antibody-based testing), the confirmatory serological test need be done only on the identified donors of interest. This approach conserves valuable antisera for those donors whose red cells are likely antigen-negative. The cost and resource efficiencies are further gained when multiple antigen-negative donors are found [e.g. R2R2, K-, S-, Fy(a-), Jk(-a)]. Knowledge of the combined antigen frequency within the donor population, and using binomial distribution, one can predict the number of donors to test to achieve the required number of units. For example, the combined frequency of group O R2R2, K-, S-, Fy(a-), Jk(a-) is
0:4 0:02 0:45 0:9 0:34 0:24 ¼ 2:64 104
ð1Þ
Using binomial distribution such that,
Pðn; r; pÞ ¼
n! pr ð1 pÞnr r!ðn rÞ!
ð2Þ
(where, n = # of donors, r = # of outcomes, p = frequency of outcome)it is estimated that there is only an 75% probability outcome of at least 2 group O positive donors or more with this combined antigen phenotype when 10,000 donors are screened, i.e.
1 ½Pð104 ; 0; 2:64 104 Þ þ Pð104 ; 1; 2:64 104 Þ ¼ 0:741 ð2:1Þ Unfortunately, the calculation does not take into account the probably of the demand for these units. Unpredictable demand requires frozen blood and shared rare donor programs like the American Rare Donor Program
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(ARDP). Nevertheless, given low frequency events, laboratories that use high throughput screening are wise to evaluate their population antigen frequencies before embarking on a search for rare combined antigen-negative donors. Local population frequencies may differ from published frequencies. Targeting donors who are most likely to repeat their donation for testing can maximize the database size. And, as yet to be explored, red cell genotyping could be used as a recruitment tool. All blood donations save lives, but just like O Rh negative, rare antigen-negative donors (identified through genotype screening) could be approached about the value of their multiple antigennegative blood types. The approach, however, has yet to be defined. DNA-based assays are invaluable to predict antigens when antisera are not readily available. Doa/b, Jsa/b, V and VS fall into this category. The ARDP accepts DNA testing information in order to provide antigen-negative blood for special circumstances where serological data is not possible. Compatibility testing and medical oversight are required to coordinate transfusions under these circumstances. One important contribution of red cell genotyping is that a genotype plus a phenotype has more information content than a phenotype alone. In other words, evaluating the underlying genetic basis of blood group expression and the expressed antigen itself is a check for the presence of weak antigens like D and Fyb. A genotype and phenotype may be warranted for blood group systems with a high number of variant alleles or null phenotypes (MNS, RH, JK). 3.2. Red cell genotyping for high-prevalence antigens Mass-scale red cell genotyping also lends itself to the detection of rare antigen-negative phenotypes for some of the high-prevalence antigens Kpb, Lub, Dib, Yta, Coa and Sc1 to which individuals more commonly produce antibodies. It is worthwhile to test for the SNP associated with these antigen-negative phenotypes if large numbers of donors are being tested for common clinically significant blood group genotypes. In fact, red cell genotyping is superior to testing for those antigens where antisera are available, because SNPs can be added to the platform at a small incremental cost to the design. Genotyping for a few high-prevalence antigens awaits the discovery of their molecular basis (Vel, Lan, Ata, and Jra). Once identified, laboratories should target testing for the remaining rare antigen-negative types in areas where founder alleles are most likely to be present. The identification of founder alleles and knowledge of donor demographics such as zip code could be used to maximize the search for such donors. This strategy is similar to the testing of siblings of individuals with rare antigen-negative blood types.
were found among the 46,133 Rh negative donors [25]. Importantly, some relatively high antigen copy number weak D variants were found including Weak D Type 11 in trans with an r0 allele. Clearly, these donors could be identified and deemed Rh positive to minimize exposure to women of childbearing age and young girls. 4. Validation of red cell genotyping platforms 4.1. Validating genotyping platforms Much like validation of unlicensed antisera, red cell genotyping as a test-of-record will necessitate validation comparing the predicted phenotype to the serological phenotype. Subsequently, it will be more beneficial to simply match the genotype of the patient and the blood donor. Most if not all genotyping platforms use robust chemistries, allowing for the analysis of multiple probes without cross-interference, and can be linked reliably to automated equipment to reduce hands-on time. Of course, the scientific community already has a good understanding of which SNPs are problematic, and have started to build in additional SNPs and logic tables to handle these anomalies. It is somewhat surprising that the validation of red cell genotyping for some SNPs has been slow given that only 500 samples are required to validate a given antibody. For example, the fidelity of KEL⁄1/KEL⁄2 is high and therefore, validation should be simple. But, given the multiple SNPs incorporated along with KEL⁄1/KEL⁄2 into array platforms, and the need for post analytical data handling, validation of a complete platform capable of analyzing and associating SNPs with clinically relevant blood group antigens is forthcoming. Additional problems lie in the validation of these assays for populations where genotypic information is sparse. Several blood group systems have a relatively high number of variants linked to certain ethnicities and arrays must be capable of detecting these variants without fail (or rather be no less accurate than monoclonal antibodies, some of which also have inherent problems) [26–28]. Regulatory requirements also affect how red cell genotyping information can be used. Questions arise related to how the information should be conveyed to the end user, what additional review and reflex testing should accompany the use of the blood on the current donation, the labeling of subsequent donations, and how results are maintained all require careful consideration. The fact that testing can be done in the absence of antisera complicates what constitutes regulatory compliance. Generally speaking, LDTs are restricted to investigational use only and the results should be confirmed with a licensed reagent. A crossmatch is required if no reagent is available.
3.3. RHD red cell genotyping
4.2. Post analytical data handling
An argument should be made for the mass-scale screening of blood donors for the presence of a functional RHD allele. The 6-year experience in Germany attests to the fact that functional RHD alleles are among the apparent Rh negative population of blood donors. A total of 97 RHD alleles
By nature of the design, high throughput testing results in the generation of an enormous amount of information. The genotyping platform itself must be capable of translating signals into output data by using a ‘rules engine’ to display the results in a meaningful way to the operator. At this
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point, the operator should have control over accepting sample, SNP, array and run data. The operator should have clear acceptance criteria by which data is suitable for commitment to the repository of data. Also, suitable controls must be included to evaluate acceptance of the run data. More important in the process is the ability to identify rare alleles for further confirmation, to flag unusual SNP results or combined SNPs (haplotypes), and to trace identification numbers back to the primary sample. Equally important is the ability to display the information in parallel with key donor information; their ABO/Rh blood group, the date of donation, frequency of donation, and the unit ID number. Moreover, placing an electronic flag on the donor’s file can identify the donor for additional confirmatory testing on the next donation.
5. Integration of red cell genotyping High throughput platforms are now poised to allow key patient groups to be transfused with antigen-matched blood. Alloimmunization is reduced for Sickle Cell disease patients when matched transfusions are given [29,30]. But also, myelodysplasia and aplastic anemia could obviously benefit from antigen-matched transfusions [31,32]. In addition, evidenced-based trials may determine that patients in intensive care units who have been transfused or have a history of pregnancy could benefit. The least of which, E, Jsa, Fy and Jk would be likely antigens to match given FDA/CBER and United Kingdom data [33,34]. The transfusion community should prioritize which antigens to match because (1) at present it is not possible to identify which patients will make alloantibodies and (2) it becomes increasingly difficult to find antigen-negative donors as more antigens are considered for a match. As red cell genotyping becomes a standard of practice, additional patients could benefit from genotype-matched transfusion. It would be interesting to quantify the quality-adjusted life year benefit for females in neonatal intensive care units who receive antigen-matched blood. Such an investment in a young population is not unprecedented; pediatric packed red cell units limit the number of donor exposures to the neonatal population [35]. Two issues remain with the use of red cell genotyping as a screening tool in a blood center or for the patient population. First, to be useful in the clinical setting, the turnaround time for results must be more rapid. Genotyping methods that take two or three days to complete do not serve all patients who are in need of matched transfusions. Second, the data from genotyping platforms needs to be integrated into the process of donor collection and routine blood banking. Incorporating red cell genotyping into the routine practice of a blood center and transfusion service could provide a process to control which units are to be tested, and which should be diverted to protected inventory. It should also identify a need and allow queries of the current inventory for available units, and who is available for recall. Ideally, the process should translate the genotype into a predicted phenotype and compare this information to any historical or current serological phenotype. Discrepancies should be reported, investigated and
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resolved if possible. In addition, new carriers of blood group antigen variants may be discovered. Also, an additional feature should include RHD SNPs so that the DNA of each Rh negative donor can be interrogated for the presence of RHD [25]. 5.1. Donor selection and DNA isolation Selection of donors for red cell genotyping can be controlled by existing blood center software systems (MAK Progesa, LifeTrak, etc.). The most important tool for this part of the process is a daily electronic query. The query provides a list of donor samples that qualify for red cell genotyping, based on a pre-determined set of criteria (donor age, ABO, frequency of donation, ethnicity, etc). Extraction platforms that can isolate DNA on up to 1000 samples per day are suitable for high throughput array analysis. Results obtained within 24 h after the unit has been released to inventory minimizes the ‘hold’ time. This is an important feature to realize the benefits of ‘‘on-time’’ red cell genotyping. With on-time testing, selected firsttime donors (e.g. based on ethnicity) can be tested and only rare and desired antigen-negative units are retained for the screened unit inventory before the unit leaves the blood center. 5.2. Integration of red cell genotypes Red cell genotyping information is provided by the high throughput instrument. Data handling is critical to the integration of red cell genotype information. Key to the design of the process is the use of the ISBT 128 barcode from the existing blood sample throughout the process. Importing the instrument data into a ‘‘rules engine’’ allows staging and control of the translation function. The staging area allows an opportunity to build complex rules like haplotypes (combinations of SNPs) before the data is merged with the blood donor’s file. Management of the rules engine can be handled separately by a skilled operator who has a thorough knowledge of blood group genetics. This component also provides control to add new SNPs or refine relationships between SNPs as new knowledge is gained. The rules engine can then package the translations into donor and patient databases (Fig. 1). In addition, clinical trials and research initiatives could be separate database and the rules engine could translate other SNP data like human platelet antigen genotypes. 5.3. Advances in red cell genotyping Enabling a comparison of the predicted phenotype and the known phenotype is the first step in the implementation of red cell genotyping. The next advances are to type both donors and patients rapidly so that the appropriate transfusion is provided. Again, with the goal being the right blood, to the right patient, at the right time. Validation of red cell genotyping as a test-of-record will enable the genotyping of yet larger donor populations where confirmation of the phenotype is not necessary (antigen-matching in place of random ABO/Rh compatible blood). Another advance will be to allow the hospital transfusion service to
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Fig. 1. Operational design of red cell genotyping. Ideally, SNP data (A, C, G and T) is first translated by a rules engine and the data indexed or packaged for downstream use. User interfaces will display the predicted phenotype with any known phenotype information in donor and patient records.
Phase
Solution Objective
I
Find rare and uncommon blood types Enable comparison of predicted phenotype to known serotype
II
Enable genotyping of larger donor populations where phenotype is not known in advance Antigen-matched services becomes a reality for specific patients
III
Blood center provides antigen-matched blood for patients Enable hospital customer to view red cell genotype results
IV
Red cell genotyping validated as a test-of-record
Fig. 2. Stepwise advancements in red cell genotyping. The initial phase for the development showed red cell genotyping is a useful screening tool. Key advancements can occur to provide efficiencies in the provision of matched blood to patients, before red cell genotyping becomes a test-of-record.
view the results of red cell genotyping. Significant resource savings could be realized. Imagine the serological confirmation of the 3 or 4 units that are known to be FYAnegative versus the testing of 20 or more RBC units with anti-Fya. Viewing red cell genotype data could be through a blood center portal or the information could be linked to an RFID tag [36]. Finally, enabling hospitals to order antigen-negative blood through existing channels could optimize end user inventory levels (maximizing flexibility of the overall inventory) because there would be no need to hold large inventories for antigen-negative units. In summary, stepwise advancements for the implementation of red cell genotyping will see the technology move from a screening tool, to the genotyping of large donor populations, providing transfusion services with information to create efficiencies, and finally providing the results as a test-of-record (Fig. 2). 6. The future of red cell genotyping It is not a feasible goal to provide a complete antigenmatch blood transfusion to all patients for all antigens. The inventory for such matches cannot be large enough
to accommodate all scenarios; the example in this review shows the need for more donor blood than is available or feasible. However, patients can be screened for the lack of high-prevalence antigens, and perhaps they should receive antigen-negative blood for these negative types, and also be matched for clinically significant alloantibodies when possible. Although debatable, the transfusion medicine community has sufficient information to make decisions on which antigens are important. Moreover, research should continue to unravel the antigen recognition, presentation, and immune response elements involved in red cell alloimmunization. ‘‘Good responders’’ could be managed differently depending on which antigens their immune system recognize than patients who will not respond, or who will respond to some of the less common alloantigens. Genotyping algorithms will ultimately be as robust as serology given the appropriate knowledge from all the major ethnic groups. The future for red cell genotyping will see an integration of the technology in parallel with existing donor and patient electronic information systems. There will be a reduction in hemolytic transfusion reactions, improvement in the appropriate blood provided to patients with Sickle
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