Skip to main content

Constructing a potential HLA haplo-homozygous induced pluripotent stem cell haplobank using data from an umbilical cord blood bank

Abstract

Background

Induced pluripotent stem cells (iPSCs) can differentiate into any type of cell and have potential uses in regenerative medicine for the treatment of many diseases. However, reducing immune rejection is a key problem in the application of iPSCs that can be solved by the development of haplobanks containing specially selected iPSC lines.

Methods

To study the feasibility of constructing an HLA (human leukocyte antigen)-matched induced pluripotent stem cell haplobank in China, 5421 umbilical cord blood samples were randomly collected from the Umbilical Cord Blood Bank of Zhejiang Province, China. The HLA-A, HLA-B, HLA-C, HLA-DRB1, and HLA-DQB1 loci were genotyped using next-generation sequencing. Using HLA genotype data at the high-resolution level, the number of HLA homozygous donors needed to cover a certain percentage of the Chinese population and the feasibility of constructing a high-matching iPSC haplobank were estimated.

Results

Thirteen HLA-A, -B, and -DRB1 and 11 HLA-A, -B, -C, -DRB1, and -DQB1 haplotype homozygotes were observed among the stored umbilical CB units which were as HLA zero-mismatched iPSC donors cumulatively matched 37.01% and 32.99% of 5421 potential patients respectively. The analysis showed that 100 distinct HLA-A, -B, and -DRB1 and HLA-A, -B, -C, -DRB1, and -DQB1 homozygous haplotypes would cover 72.74% and 67.87% of Chinese populations, respectively, and 600 HLA-A, -B, -C, -DRB1, and -DQB1 homozygous haplotypes would cover more than 90% of Chinese populations. PCA (principal component analysis) of published HLA data from different populations revealed that the frequency of these haplotypes in Asian populations is different from those in European populations.

Conclusion

The results suggested that at least some HLA-homozygous iPSC lines developed from Chinese individuals will not only be useful for covering the Chinese population but will also cover other Asian populations. A high-matching iPSC haplobank generated from umbilical CB units may be an economical and effective option in an allogeneic model of iPSC therapy.

Background

Induced pluripotent stem cell (iPSC) technology has been used to treat a wide variety of diseases and injuries [1,2,3,4,5,6]. With the success of clinical trials, it will be necessary to consider how to deliver these treatments to the large numbers of patients who will need them. Currently, allogeneic iPSC cell lines are used to derive grafts for transplantation. However, to avoid graft rejection by the allogeneic host, immunological HLA compatibility between the graft and host needs to be considered. Therefore, the creation of a haplobank of homozygous iPSC (hiPSC) lines for a variety of HLA types could simplify HLA matching, provide matches for reasonable percentages of target populations and extend iPSC-derived therapies beyond the autologous setting.

hiPSC technology facilitates the prospective selection of donors based on their specific HLA haplotypes for the creation of a haplobank of iPSC lines [7,8,9,10]. One feasible approach is to prospectively search for potential stem cell donors in registries/banks of bone marrow (BM) and umbilical cord blood (UCB) since these donations are already genotyped for HLA loci. UCB cells have some advantages for generating homozygous HLA haplotype hiPSC collections [8, 9]. Although hematopoietic stem cell units from UCB are designated for clinical application for hematological pathologies, surplus stem cell units stored in many UCB banks can be used to generate hiPSC lines, and stem cell units with an insufficient number of hematological progenitors that are not suitable for transplantation can also be used.

The preparation of clinical-grade iPSCs for allotransplantation has been reported in some studies [7, 10]. One promising approach is to store iPSCs from donors with homozygous HLA loci at high resolution. Through this approach, using a relatively small number of specific selection donors enables HLA matching coverage for a large number of patients [8]. It was reported that only 30 iPSC lines homozygous for HLA-A, HLA-B, and HLA-DRB1 loci would be able to cover 82.2% of the Japanese population, and 50 lines would be able to cover 90.7% of the population [11]. However, more iPSC lines would be needed to achieve a coverage level greater than 80% for patients in other populations because HLA is highly polymorphic in the diverse populations [12, 13]. In Korea, 41.07% of the Korean population would be matched with 10 iPSC lines homozygous for HLA-A, HLA-B, and HLA-DRB1 loci, and 70% of the patients would be covered with HLA-matched material from 50 donors [9]. Lin G et al. [14] reported that full HLA-A, HLA-B, and HLA-DRB1 matching was obtained for 24.9% of the Chinese Han population using 174 human embryonic stem cell (hESC) lines.

Currently, most HLA homozygous iPSCs are analyzed for HLA-A, HLA-B, and HLA-DRB1 loci [11,12,13]. However, the HLA-C and HLA-DQB1 loci also play important roles in hematopoietic stem cell transplantation, and mismatches at these loci will affect the outcome. Now the data for the coverage level for HLA-A, HLA-B, HLA-C, HLA-DRB1 and HLA-DQB1 homozygous iPSCs over the population are limited. In addition, the resolution of HLA genotyping also impacts matching coverage analysis for HLA homozygous iPSCs. The methods for HLA genotyping can achieve resolution at the allelic, ultrahigh, high, low and other levels. Therefore, the number of HLA homozygous iPSC lines varies at different HLA genotyping resolution levels. Here, the coverage of an HLA-A, -B, -C, -DRB1, and -DQB1 homozygous iPSC haplobank was evaluated for the first time by high-resolution HLA genotyping using data from the Umbilical Cord Blood Bank of Zhejiang Province, China to address some challenges in the establishment of iPSC haplobanks in the Chinese Han population, including how many homozygous cell lines are needed to match most patients in the Chinese Han population.

Materials and methods

Specimens

A total of 5421 umbilical cord blood specimens were collected from May 2017 to September 2022 at the Umbilical Cord Blood Bank of Zhejiang Province, which is located in eastern China. All individuals were of Han nationality and were not related according to the maternal information and family analysis. The study was approved by the Ethical Review Committee of Zhejiang Provincial Blood Center, and informed consent was obtained from all individuals. Specimens were collected in 5 ml tubes with EDTA-Na2 anticoagulant and stored at − 20 °C until processing.

Genomic DNA extraction

Genomic DNA was extracted using commercial MagNA Pure LC DNA Isolation Kits (Roche Diagnostics, Indianapolis, IN, USA) according to the manufacturer’s instructions. The final DNA concentration was adjusted to 15–30 ng/μl, and the optical density at 260/280 nm was 1.6–1.8.

HLA genotyping

A total of 5421 specimens were genotyped for HLA-A, HLA-B, HLA-C, HLA-DRB1 and HLA-DQB1 loci using a Type™ NGS 9-Loci Amplification Kit (One Lambda Inc., Canoga Park, CA, USA) according to our previous report [15]. Briefly, the full-length sequences of the HLA-A, HLA-B, and HLA-C loci and the sequences from exon 2 to the 3′ untranslated region (UTR) of the HLA-DRB1 and HLA-DQB1 loci were amplified by single multiplexed PCR. Then, the library was prepared using an Ion Shear Plus Reagents Kit and an Ion Plus Fragment Library Kit (One Lambda Inc., Canoga Park, CA, USA). All the steps of amplicon purification, amplicon dilution and library pooling were performed with an automated Microlab STAR (Hamilton, Bonaduz, Switzerland). The expected size of the amplicons in the library ranged from 300 to 1000 bp. The sequencing step was performed on an Ion Torrent S5 platform (Thermo Fisher Scientific, Waltham, MA, USA), and 48 specimens were pooled and loaded on an Ion S5 530 chip. The sequence reads were analyzed, and the genotypes of the specimens were assigned using HLA TypeStream Visual Software version 2.0 (One Lambda Inc., Canoga Park, CA, USA).

Haplotype frequency determination

The allele frequencies (AFs) of the HLA-A, HLA-C, HLA-B, HLA-DRB1, and HLA-DQB1 loci and the deviations from Hardy‒Weinberg equilibrium (HWE) were determined for each locus using Fisher’s exact test implemented in Arlequin software 3.5.2.2 [16]. The haplotype frequencies (HFs) were also estimated based on the expectation–maximization (EM) algorithm with Arlequin software 3.5.2.2. A value of p < 0.05 was regarded as significant.

Screening and selection of HLA homozygous haplotype donors

All umbilical cord blood samples were tested for the identification of HLA-A, HLA-C, HLA-B, HLA-DRB1, and HLA-DQB1 homozygous donors. The selection and classification of homozygous units were performed by direct counts.

Calculation of the matching potential of the most frequent haplotype homozygotes

The HLA-A, -C, -B, -DRB1 and -DQB1 homozygotes were assumed to be iPS homozygous haploid cell bank donors, and randomly chosen umbilical cord blood donors were classified as patients. As the number of iPS homozygous haploids increased, the odds of a patient finding an exact match in the iPS homozygous haploid cell bank were calculated. The calculation formula is as follows:

$$\begin{gathered} {\text{Pi }} = \left( {{\text{M1 }} + {\text{ M2 }} + {\text{ M3 }} + \cdots \, + {\text{ Mi}}} \right) \times { 1}00\% /{5421}({\text{Pi}}:{\text{cumulative}}\,{\text{matching}}\,\,{\text{probability}}; \hfill \\ {\text{Mi}}:{\text{Number}}\,\,{\text{of}}\,\,{\text{newly}}\,\,{\text{matched}}\,\,{\text{patients}}\,\,{\text{for}}\,\,{\text{the}}\,\,{\text{cell}}\,\,{\text{line}}) \hfill \\ \end{gathered}$$

Calculation of match coverage

To estimate the HLA matching coverage of the haplotypes, the best haplotypes and all matched individuals were extracted from the database, and the genotypes that already matched the haplotypes were removed from subsequent searches to avoid double counting. The coverage was recalculated from the remaining data. If the genotype of the individual contained all alleles present in the HLA haplotype of the iPSCs, it was considered a match. This matching was performed for all genotypes in the study population, and a curve depicting the matching coverage was produced.

Principal component analysis (PCA)

PCA was performed on different haplotype frequencies to estimate the degree of relatedness between 13 population groups. Frequency data for other populations were obtained from previous studies: Korean (http://allelefrequencies.net), Japanese (https://hla.or.jp/med/frequency_search/en/haplo/), Indian [17], Malaysian Indian, Malaysian Chinese (http://www.allelefrequencies.net/hla6003a.asp) [18], Vietnamese [19], Chinese Taiwanese [20], Spanish [10], Italian, Turkish, Polish, and Russian [21]. Corrplot was used to analyze the correlations of haplotype frequencies to measure the similarity of each population against all others.

Statistical methods

The validation data were processed by GraphPad Prism 9.0 software. p < 0.05 was considered to indicate statistical significance.

Results

Hardy–Weinberg equilibrium

In total, 5421 specimens were genotyped for the HLA-A, -C, -B, -DRB1, and -DQB1 loci. According to the HWE analysis, the allele distributions of the HLA-A, -C, -B, -DRB1, and -DQB1 loci were consistent with HWE. The observed heterozygosity, expected heterozygosity and p values are summarized in Supplemental 1 Table 1.

Distribution of the HLA-A, -B, -C, -DRB1 and -DQB1 alleles

There were 52, 109, 52, 63, and 23 HLA-A, HLA-B, HLA-C, HLA-DRB1, and HLA-DQB1 alleles, respectively, detected in the 5421 specimens (Supplemental 1 Table 2). The three most frequent alleles of the HLA-A, HLA-B, HLA-C, HLA-DRB1, and HLA-DQB1 loci were as follows: HLA-A*11:01 (25.83%), HLA-A*24:02 (16.66%), and HLA-A*02:01 (10.87%); HLA-B*40:01 (15.97%), HLA-B*46:01 (12.02%), and HLA-B*58:01 (7.35%); HLA-C*07:02 (20.05%), HLA-C*01:02 (18.14%), and HLA-C*03:04 (10.43%); HLA-DRB1*09:01 (17.34%), HLA-DRB1*12:02 (9.70%), and HLA-DRB1*15:01 (9.65%); and HLA-DQB1*03:01:01 (22.36%), HLA-DQB1*03:03:02 (18.31%), and HLA-DQB1*06:01:01 (11.94%).

Haplotype frequency

A total of 2371 distinct HLA-A, -B, and -DRB1 haplotypes were obtained, and those with frequencies greater than 0.1% are listed in Supplemental 1 Table 3. Nine haplotypes had frequencies greater than 1.0%. A total of 3326 distinct HLA-A, -B, -C, -DRB1, and -DQB1 haplotypes were obtained, and those with frequencies greater than 0.1% are listed in Supplemental 1 Table 4. Only 8 haplotypes had a frequency greater than 1.0%.

Haplotype homozygote distribution and matching potential with patients

Thirteen HLA-A, HLA-B, and HLA-DRB1 haplotype homozygotes matched 37.01% of of the 5421 umbilical cord blood donors, and 11 HLA-A, HLA-B, HLA-C, HLA-DRB1, and HLA-DQB1 haplotype homozygotes matched 32.99% (Table 1).

Table 1 HLA-A, -B, and -DRB1 and HLA-A, -B, -C, -DRB1, and -DQB1 homozygote haplotypes

Evaluation of the coverage of the homozygous induced pluripotent stem cell haplobank

Haplotype analysis of existing HLA genotype umbilical cord blood databases from 5,421 individuals yielded a list of different HLA haplotypes found in the Chinese Han population. Using these data, the number of HLA homozygous donors needed to cover a certain percentage of the Chinese population was estimated. The analysis showed that 100 distinct HLA-A, HLA-B, and HLA-DRB1 and HLA-A, HLA-B, HLA-C, HLA-DRB1, and HLA-DQB1 homozygous haplotypes at the high-resolution level would cover 72.74% and 67.87 of those populations, respectively, and 600 HLA-A, HLA-B, HLA-C, HLA-DRB1, and HLA-DQB1 homozygous haplotypes would cover more than 90% (Fig. 1). There was a significant difference between triple homozygotes and quintuple homozygotes (p < 0.0001, t = 7.989). The figure shows the relationship between the number of haplotypes and the percentage of phenotypes covered by those haplotypes; the results are also shown numerically in Table 2.

Fig. 1
figure 1

Estimated numbers of HLA homozygote donors needed to cover the Chinese Han population. Graph showing the relationship between the number of haplotypes (x-axis) and the percentage of phenotypes covered by these haplotypes (y-axis)

Table 2 Coverage of HLA-A, HLA-B, and HLA-DRB1 and HLA-A, HLA-B, HLA-C, HLA-DRB1, and HLA-DQB1 haplotypes

Comparison of the Chinese HLA homozygous iPSC lines to other populations

To investigate the potential usefulness of our 10 HLA homozygous iPSC lines from the Chinese population internationally, we compared the Chinese HLA homozygous iPSC lines to those of 12 other populations, including Korean, Japanese, Indian, Malaysian Indian, Malaysian Chinese, Vietnamese, Chinese Taiwanese, Spanish, Italian, Turkish, Polish and Russian populations (Supplemental 1 Table 5). Figure 2A, B shows the 1st versus 2nd and 1st versus 3rd components of the PCA and highlights that the study populations analyzed clustered according to previously published populations. Thirteen populations, including Asian and European populations, were analyzed. The first principal component accounted for 27.24% of the total variance, and the second and third components accounted for 18.35% and 13.97%, respectively. As visualized by the plot, the first principal component effectively distinguishes between the Asian and European groups. The European data are clustered, while the Asian data are scattered. Our data (Chinese) and the Chinese Taiwanese data are almost identical. The second principal component showed that the Asian population can be divided into three groups. Our data are closer to those of the Chinese Taiwanese, Malaysian Chinese, and Vietnamese populations; the Japanese data are closer to those of the Korean population; and the Indian data are closer to those of the Malaysian Indian population. The correlation plot of haplotype frequencies similarly measures the relationship of each population to all other populations (Fig. 3).

Fig. 2
figure 2

Principal component analysis for HLA-A, HLA-B, HLA-C, HLA-DRB1, and HLA-DQB1 haplotypes showing the relationships between Chinese individuals (our data in this study) and other populations. A The first and second principal components and B the first and third principal components

Fig. 3
figure 3

The correlation plot of the population haplotype frequency from high correlation (red) to low correlation (blue)

Discussion

The construction of an iPS cell line biobank using HLA homozygous haplotype donors for the generation of iPSC lines, which are immunologically compatible with many individuals and can achieve cell therapy without immune rejection and minimal use of immunosuppressants, has important clinical significance [22,23,24]. In Japan and the United Kingdom [3, 11], 50 and 100 different trihomozygous haplotypes of HLA-A, HLA-B and HLA-DRB1, respectively, cover 90% of the population. In Brazil [25], 559 trihomozygous cell lines cover 95% of the population, and 630 haploid lines cover 90% of potential recipients. China has complex and valuable resources of human genetic diversity [14, 26]. Due to the high HLA diversity in the Chinese population, many patients who need hematopoietic stem cell transplantation or cell therapy are still unable to find perfectly matched donors at the five loci of HLA-A, HLA-B, HLA-C, HLA-DRB1 and HLA-DQB1. Therefore, there is a clear need to increase the diversity of the donation pool and improve irrelevant donation search strategies.

HLA matching is a long-established and well-studied standard in the field of hematopoietic stem cell transplantation [27, 28] and can be a key determinant of cell therapy success. Therefore, high-resolution matching of the HLA-A, HLA-B, HLA-C, HLA-DRB1 and HLA-DQB1 loci was performed to minimize rejection in this study. Currently, there are few data on haplotype homozygous donors at the HLA-A, HLA-B, HLA-C, HLA-DRB1 and HLA-DQB1 loci for iPSC line generation. A total of 33 cases containing 11 HLA-A, HLA-B, HLA-C, HLA-DRB1, and HLA-DQB1 homozygotes were found among 5421 samples of umbilical cord blood, and the zero-mismatch probability of 5421 UCB units was calculated. To our knowledge, this is the first study to provide data on HLA-A, HLA-B, HLA-C, HLA-DRB1 and HLA-DQB1 haplotype homozygous donors for iPSC generation. Treating the 5421 preserved UCB unit donors as potential patients, the 11 homozygous HLA-A, -B, -C, -DRB1, and -DQB1 haplotypes underwent cumulative HLA zero-mismatching, accounting for 32.99% of the 5421 potential patients. Similarly, the 13 HLA-A, HLA-B, and HLA-DRB1 haplotype homozygotes could be considered zero-mismatch iPSC sources for 37.01% of the patients; however, the coverage ratio was lower than that in the Korean population. Further analysis revealed that 100 distinct HLA-A, HLA-B, and HLA-DRB1 and HLA-A, HLA-B, HLA-C, HLA-DRB1, and HLA-DQB1 homozygous haplotypes would cover 72.74% and 67.87 of Chinese population, respectively. There was a significant difference between triple homozygotes and quintuple homozygotes in this study. These results showed that the resolution level for HLA genotyping and numers of the loci have an impact on the matching coverage analysis for HLA homozygous iPSCs. Using these data, it was estimated that.to cover 90% of the Chinese population, approximately 600 unique HLA-A, HLA-B, HLA-C, HLA-DRB1, and HLA-DQB1 homozygous donors are needed, for which 1.303 million people need to be screened.

In this study, a comparative analysis of the matching of the top 10 haplotypes was conducted between the Chinese population (our data) and Korean, Japanese, Indian, Malaysian Indian, Malaysian Chinese, Vietnamese, Chinese Taiwan, Italian, Turkish, Polish, Russian and Spanish (only the top 7 haplotypes) populations. PCA revealed that there was a distinct difference between the Asian and European groups. In the Asian group, one cluster contained our data and the data from the Chinese Taiwan, Malaysian Chinese, and Vietnamese populations, while the Japanese population was close to the Korean population, and the Indian population was close to the Malaysian Indian population. Interestingly, among the top 10 haplotypes in our data, HLA-A*02:07-C*46:01-B*01:02-DRB1*08:03-DQB1*06:01 and HLA-A*11:01-C*15:01-B*04:01-DRB1*04:06-DQB1*03:02 were also present in both the Korean and Japanese populations, with frequencies of 1.0162%, 1.9719% and 1.237%, respectively, and 0.881%, 1.4706%, and 1.7%, respectively. These results suggested that at least some of the HLA homozygous iPSC lines developed from Chinese individuals will be useful for covering not only the Chinese population but also other Asian populations but will not cover European populations. These haplotypes may be particularly useful for covering diverse Asian populations living in the USA, Canada, Australia, and Western European countries.

To date, nearly 800,000 fully identified UCB units worldwide are stored in public umbilical cord blood banks and are available to be used to construct a homozygous iPSC haploid library of multiple HLA types representing diverse geographic and ethnic groups [29]. The umbilical cord blood bank records each donor's HLA profile, medical history, and laboratory test results for infectious diseases, making it easy to identify suitable individual UCB units without the effort and expense of recruiting and screening donors. Therefore, umbilical cord blood units are believed to be a better source for iPSC production. Here, we built an HLA-matched iPSC bank using cord blood data from Zhejiang Province, China. The top five haplotypes were also found in other regional Chinese population [26] and some haplotypes were found in Asian populations [18,19,20]. It was suggested the data may be useful for covering partial Chinese population and Asian populations. However, its geographic and demographic representation still has shortcoming due to the HLA high polymorphism in the various populations, and it can only cover partial population for therapeutic applications. In additional, the analysis focuses on homozygous HLA haplotypes in this study. Heterozygous haplotypes comprise a larger percentage of the population, but it need to match both haplotypes of the patient when using heterozygous HLA haplotypes. Therefore, the probability of match is greatly reduced using heterozygous haplotypes, and homozygous HLA haplotypes are generally selected for iPS haplobank construction.

The use of allogeneic iPSC-derived grafts for transplantation and cell therapy has been considered [30, 31]. In additional for hematopoietic stem cell transplantation, HLA homozygous donor bank or stored cells, may be useful not only for the production of iPSC, but also for other cell therapies utilizing. Now immune cell therapies, especially chimeric antigen receptor T cells, mainly rely on autologous cells, but allogeneic cells may also be an option in the future. HLA homozygous donors are also valuable for patients such as those with leukemia who require large amounts of platelet transfusions [32,33,34]. Matching of HLA-A and -B loci signifcantly lowers the risk of platelet transfusion refractoriness. With the recent development of the CRISPR/Cas9 system, establishment of universal iPSCs can rapidly advance the clinical application of regenerative medicine-based therapies using off-the-shelf iPSCs, and can contribute greatly to medical care. However, some challenges were existed in the HLA-homozygote iPSC repository. At firstly, it need high cost for HLA-homozygote donor recruitment, donor screening and long-term maintenance of iPSC lines in the bank. The second, each iPSC haplobank can only cover partial region populations due to HLA high polymorphism. Finally, some regulations for manufacturing and quality control of iPSC lines, ethics approval for application and regulatory need to further improve.

Conclusions

Due to the high HLA diversity in the Chinese population, some patients in need of unrelated allogeneic hematopoietic stem cell transplantation are still unable to find fully matched donors at the five HLA-A, HLA-B, HLA-C, HLA-DRB1, and HLA-DQB1 loci at high resolution. Consequently, there is a clear need to increase the diversity of the donor pool and improve unrelated donor search strategies. Here, the feasibility of using banked umbilical cord blood units to create an iPSC haplobank was analyzed, and the developed iPSC haplobank can cover a significant percentage of the Chinese and international population for future advanced therapy replacement strategies.

Availability of data and materials

All the presented data are available for consultation. HLA-A, -C, -B, -DRB1, and -DQB1 raw typing data of 5421 samples are provided as Supplementary Material 2.

Abbreviations

iPSCs:

Induced pluripotent stem cells

HLA:

Human leukocyte antigen

PCA:

Principal component analysis

hiPSC:

Haplobank of homozygous iPSC

BM:

Bone marrow

UCB:

Umbilical cord blood

hESC:

Human embryonic stem cell

AFs:

Allele frequencies

HWE:

Hardy‒Weinberg equilibrium

HFs:

Haplotype frequencies

EM:

Expectation–maximization

References

  1. Takahashi K, Yamanaka S. Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell. 2006;126(4):663–76. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.cell.2006.07.024.

    Article  CAS  PubMed  Google Scholar 

  2. Goncu B, Salepcioglu Kaya H, Yucesan E, Ersoy YE, Akcakaya A. Graft survival effect of HLA -A allele matching parathyroid allotransplantation. J Investig Med. 2021;69(3):785–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1136/jim-2020-001648.

    Article  PubMed  Google Scholar 

  3. Jang Y, Choi J, Park N, Kang J, Kim M, Kim Y, Ju JH. Development of immunocompatible pluripotent stem cells via CRISPR -based human leukocyte antigen engineering. Exp Mol Med. 2019;51(1):1–11. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/s12276-018-0190-2.

    Article  CAS  PubMed  Google Scholar 

  4. Zakrzewski W, Dobrzyński M, Szymonowicz M, Rybak Z. Stem cells: past, present, and future. Stem Cell Res Ther. 2019;10(1):68. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13287-019-1165-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Stoddard-Bennett T, Reijo PR. Treatment of Parkinson’s disease through personalized medicine and induced pluripotent stem cells. Cells. 2019;8(1):26. https://doiorg.publicaciones.saludcastillayleon.es/10.3390/cells8010026.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Chari S, Mao S. Timeline: iPSCs–the first decade. Cell Stem Cell. 2016;18(2):294. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.stem.2016.01.005.

    Article  CAS  PubMed  Google Scholar 

  7. Wilmut I, Leslie S, Martin NG, Peschanski M, Rao M, Trounson A, Turner D, Turner ML, Yamanaka S, Taylor CJ. Development of a global network of induced pluripotent stem cell haplobanks. Regen Med. 2015;10(3):235–8. https://doiorg.publicaciones.saludcastillayleon.es/10.2217/rme.15.1.

    Article  CAS  PubMed  Google Scholar 

  8. Stacey GN. An HLA-homozygous haplobank resource to promote safer cell therapies. Cell Stem Cell. 2023;30(2):118–9. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.stem.2023.01.003.

    Article  CAS  PubMed  Google Scholar 

  9. Lee S, Huh JY, Turner DM, Lee S, Robinson J, Stein JE, Shim SH, Hong CP, Kang MS, Nakagawa M, Kaneko S, Nakanishi M, Rao MS, Kurtz A, Stacey GN, Marsh SGE, Turner ML, Song J. Repurposing the cord blood bank for haplobanking of HLA-Homozygous iPSCs and their usefulness to multiple populations. Stem Cells. 2018;36(10):1552–66. https://doiorg.publicaciones.saludcastillayleon.es/10.1002/stem.2865.

    Article  CAS  PubMed  Google Scholar 

  10. Kuebler B, Alvarez-Palomo B, Aran B, Castaño J, Rodriguez L, Raya A, QuerolGiner S, Veiga A. Generation of a bank of clinical-grade, HLA-homozygous iPSC lines with high coverage of the Spanish population. Stem Cell Res Ther. 2023;14(1):366. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13287-023-03576-1.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Yoshida S, Kato TM, Sato Y, Umekage M, Ichisaka T, Tsukahara M, Takasu N, Yamanaka S. A clinical-grade HLA haplobank of human induced pluripotent stem cells matching approximately 40% of the Japanese population. Med. 2023;4(1):51-66.e10. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.medj.2022.10.003.

    Article  CAS  PubMed  Google Scholar 

  12. Álvarez-Palomo B, García-Martinez I, Gayoso J, Raya A, Veiga A, Abad ML, Eiras A, Guzmán-Fulgencio M, Luis-Hidalgo M, Eguizabal C, Santos S, Balas A, Alenda R, Sanchez-Gordo F, Verdugo LP, Villa J, Carreras E, Vidal F, Madrigal A, Herrero MJ, Rudilla F, Querol S. Evaluation of the Spanish population coverage of a prospective HLA haplobank of induced pluripotent stem cells. Stem Cell Res Ther. 2021;12(1):233. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13287-021-02301-0.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Pappas DJ, Gourraud PA, Le Gall C, Laurent J, Trounson A, DeWitt N, Talib S. Proceedings: human leukocyte antigen haplo-homozygous induced pluripotent stem cell haplobank modeled after the california population: evaluating matching in a multiethnic and admixed population. Stem Cells Transl Med. 2015;4(5):413–8. https://doiorg.publicaciones.saludcastillayleon.es/10.5966/sctm.2015-0052.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Lin G, Xie Y, Ouyang Q, Qian X, Xie P, Zhou X, Xiong B, Tan Y, Li W, Deng L, Zhou J, Zhou D, Du L, Cheng D, Liao Y, Gu Y, Zhang S, Liu T, Sun Y, Lu G. HLA-matching potential of an established human embryonic stem cell bank in China. Cell Stem Cell. 2009;5(5):461–5. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.stem.2009.10.009.

    Article  CAS  PubMed  Google Scholar 

  15. Wang F, Dong L, Wang W, Chen N, Zhang W, He J, Zhu F. The polymorphism of HLA -A, -C, -B, -DRB3/4/5, -DRB1, -DQB1 loci in Zhejiang Han population, China using NGS technology. Int J Immunogenet. 2021;48(6):485–9. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/iji.12554.

    Article  CAS  PubMed  Google Scholar 

  16. Excoffier L, Lischer HE. Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Mol Ecol Resour. 2010;10(3):564–7. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/j.1755-0998.2010.02847.x.

    Article  PubMed  Google Scholar 

  17. Narayan S, Maiers M, Halagan M, Sathishkannan A, Naganathan C, Madbouly A, Periathiruvadi S. Human leucocyte antigen (HLA)-A, -B, -C, -DRB1 and -DQB1 haplotype frequencies from 2491 cord blood units from Tamil speaking population from Tamil Nadu, India. Mol Biol Rep. 2018;45(6):2821–9. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s11033-018-4382-6.

    Article  CAS  PubMed  Google Scholar 

  18. Nurul-Aain AF, Tan LK, Heselynn H, Nor-Shuhaila S, Eashwary M, Wahinuddin S, Lau IS, Gun SC, Mohd-Shahrir MS, Ainon MM, Azmillah R, Muhaini O, Shahnaz M, Too CL. HLA-A, -B, -C, -DRB1 and -DQB1 alleles and haplotypes in 271 Southeast Asia Indians from Peninsular Malaysia. Hum Immunol. 2020;81(6):263–4. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.humimm.2020.04.004.

    Article  CAS  PubMed  Google Scholar 

  19. Hoa BK, Hang NT, Kashiwase K, Ohashi J, Lien LT, Horie T, Shojima J, Hijikata M, Sakurada S, Satake M, Tokunaga K, Sasazuki T, Keicho N. HLA-A, -B, -C, -DRB1 and -DQB1 alleles and haplotypes in the Kinh population in Vietnam. Tissue Antigens. 2008;71(2):127–34. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/j.1399-0039.2007.00982.x.

    Article  CAS  PubMed  Google Scholar 

  20. Yang KL, Chen HB. Using high-resolution human leukocyte antigen typing of 11,423 randomized unrelated individuals to determine allelic varieties, deduce probable human leukocyte antigen haplotypes, and observe linkage disequilibria between human leukocyte antigen-B and-C and human leukocyte antigen-DRB1 and-DQB1 alleles in the Taiwanese Chinese population. Ci Ji Yi Xue Za Zhi. 2017;29(2):84–90. https://doiorg.publicaciones.saludcastillayleon.es/10.4103/tcmj.tcmj_35_17.

    Article  Google Scholar 

  21. Pingel J, Solloch UV, Hofmann JA, Lange V, Ehninger G, Schmidt AH. High-resolution HLA haplotype frequencies of stem cell donors in Germany with foreign parentage: how can they be used to improve unrelated donor searches? Hum Immunol. 2013;74(3):330–40. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.humimm.2012.10.029.

    Article  CAS  PubMed  Google Scholar 

  22. Koga K, Wang B, Kaneko S. Current status and future perspectives of HLA -edited induced pluripotent stem cells. Inflamm Regen. 2020;40:23. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s41232-020-00132-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Sullivan S, Fairchild PJ, Marsh SGE, Müller CR, Turner ML, Song J, Turner D. Haplobanking induced pluripotent stem cells for clinical use. Stem Cell Res. 2020;49:102035. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.scr.2020.102035.

    Article  CAS  PubMed  Google Scholar 

  24. Alvarez-Palomo B, Vives J, Casaroli-Marano RPP, Gomez SG, Rodriguez Gómez L, Edel MJ, Querol-Giner S. Adapting cord blood collection and banking standard operating procedures for HLA-homozygous induced pluripotent stem cells production and banking for clinical application. J Clin Med. 2019;8(4):476. https://doiorg.publicaciones.saludcastillayleon.es/10.3390/jcm8040476.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Martins de Oliveira ML, Tura BR, Meira-Leite M, Melo Dos Santos EJ, Pôrto LC, Pereira LV, Campos de Carvalho AC. Creating an HLA-homozygous iPS cell bank for the Brazilian population: Challenges and opportunities. Stem Cell Rep. 2023;18(10):1905–12. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.stemcr.2023.09.001.

    Article  CAS  Google Scholar 

  26. Zhou XY, Zhu FM, Li JP, Mao W, Zhang DM, Liu ML, Hei AL, Dai DP, Jiang P, Shan XY, Zhang BW, Zhu CF, Shen J, Deng ZH, Wang ZL, Yu WJ, Chen Q, Qiao YH, Zhu XM, Lv R, Li GY, Li GL, Li HC, Zhang X, Pei B, Jiao LX, Shen G, Liu Y, Feng ZH, Su YP, Xu ZX, Di WY, Jiang YQ, Fu HL, Liu XJ, Liu X, Zhou MZ, Du D, Liu Q, Han Y, Zhang ZX, Cai JP. High-resolution analyses of human leukocyte antigens allele and haplotype frequencies based on 169,995 volunteers from the China bone marrow donor registry program. PLoS ONE. 2015;10(9):e0139485. https://doiorg.publicaciones.saludcastillayleon.es/10.1371/journal.pone.0139485.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Fürst D, Müller C, Vucinic V, Bunjes D, Herr W, Gramatzki M, Schwerdtfeger R, Arnold R, Einsele H, Wulf G, Pfreundschuh M, Glass B, Schrezenmeier H, Schwarz K, Mytilineos J. High-resolution HLA matching in hematopoietic stem cell transplantation: a retrospective collaborative analysis. Blood. 2013;122(18):3220–9. https://doiorg.publicaciones.saludcastillayleon.es/10.1182/blood-2013-02-482547.

    Article  CAS  PubMed  Google Scholar 

  28. Dehn J, Spellman S, Hurley CK, Shaw BE, Barker JN, Burns LJ, Confer DL, Eapen M, Fernandez-Vina M, Hartzman R, Maiers M, Marino SR, Mueller C, Perales MA, Rajalingam R, Pidala J. Selection of unrelated donors and cord blood units for hematopoietic cell transplantation: guidelines from the NMDP/CIBMTR. Blood. 2019;134(12):924–34. https://doiorg.publicaciones.saludcastillayleon.es/10.1182/blood.2019001212.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Barry J, Hyllner J, Stacey G, Taylor CJ, Turner M. Setting up a haplobank: issues and solutions. Curr Stem Cell Rep. 2015;1(2):110–7. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s40778-015-0011-7.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Abberton KM, McDonald TL, Diviney M, Holdsworth R, Leslie S, Delatycki MB, Liu L, Klamer G, Johnson P, Elwood NJ. Identification and re-consent of existing cord blood donors for creation of induced pluripotent stem cell lines for potential clinical applications. Stem Cells Transl Med. 2022;11(10):1052–60. https://doiorg.publicaciones.saludcastillayleon.es/10.1093/stcltm/szac060.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Roh EY, Oh S, Yoon JH, Kim BJ, Song EY, Shin S. Umbilical cord blood units cryopreserved in the public cord blood bank: a breakthrough in iPSC haplobanking? Cell Transpl. 2020;29:963689720926151. https://doiorg.publicaciones.saludcastillayleon.es/10.1177/0963689720926151.

    Article  Google Scholar 

  32. Gmür J, von Felten A, Frick P. Platelet support in polysensitized patients: role of HLA specificities and crossmatch testing for donor selection. Blood. 1978;51(5):903–9.

    Article  PubMed  Google Scholar 

  33. Stanworth SJ, Navarrete C, Estcourt L, Marsh J. Platelet refractoriness–practical approaches and ongoing dilemmas in patient management. Br J Haematol. 2015;171(3):297–305. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/bjh.13597.

    Article  PubMed  Google Scholar 

  34. Karlström C, Linjama T, Edgren G, Lauronen J, Wikman A, Höglund P. HLA-selected platelets for platelet refractory patients with HLA antibodies: a single-center experience. Transfusion. 2019;59(3):945–52. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/trf.15108.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We would like to acknowledge the technical staff in the institue of transfusion medicine of Blood Center of Zhejiang Province. We would also like to thank the cord blood donors, the donation program professionals and all the cord blood bank staff for their invaluable dedication to helping bring hope to many patients in need. The authors declare that they have not used Artificial Intelligence in this study.

Funding

This project was funded by the Zhejiang Provincial Natural Science Foundation of China (LTGY23H080002), and Science Research Foundation of Zhejiang Healthy Commission (2023KY087).

Author information

Authors and Affiliations

Authors

Contributions

JH and YMH helped in conception and design, collection and assembly of data, data analysis and interpretation, manuscript writing. QGZ and QS was involved in provision of study material or patients, collection and assembly of data, data analysis and interpretation. ZPW and WZ contributed to collection and assembly of data, data analysis and interpretation. FMZ performed conception and design, provision of study material or patients, data analysis and interpretation, manuscript writing and final approval of manuscript.

Corresponding author

Correspondence to Faming Zhu.

Ethics declarations

Ethics approval and consent to participate

The Project entitled: “Establishment and application of high-resolution genotyping method for simultaneous detection of all exons of 11 HLA genes using capture technology” was approved by the Ethical Committee of the Blood Center of Zhejiang Province, with approval number 005 on February 3th, 2023. All participating donors had signed the informed consent document, provided written informed consent for participation in the use of samples.

Consent for publication

All authors confirm their consent for publication

Competing interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

He, J., He, Y., Zhan, Q. et al. Constructing a potential HLA haplo-homozygous induced pluripotent stem cell haplobank using data from an umbilical cord blood bank. Stem Cell Res Ther 16, 42 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13287-025-04159-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13287-025-04159-y

Keywords