Abstract
The Rhesus (Rh) blood group is a significant and complicated biological system in humans. Incompatible transfusion or pregnancy with Rh antigens can lead to the production of alloantibodies, among which the anti-E antibody is prevalent. The relationship between Anti-E antibody and HLA-II gene polymorphism in Chinese pregnant women is worth exploring. Our aim in this study was to verify the correlation between HLA-II gene polymorphisms and RhE alloimmunization in pregnant Chinese women through HLA-II typing and DR-RhE structural prediction. In total, 94 anti-E-negative pregnant women and 103 anti-E-positive pregnant women were enrolled from Southwest China Second Hospital, and HLA-II genotyping was performed using next-generation sequencing. NetMHCpan software was used to predict the binding of E -derived anchoring peptides to HLA-DRB1 molecules. AlphaFold was used to analyze the differences in antigen presentation based on the structure of major histocompatibility complex peptides. The HLA-DRB1*09:01-DQA1*03:02-DQB1*03:03 haplotype showed a significant positive association with anti-E. One E-derived anchoring peptide (219FWPSVNSPL227) was predicted to bind to the HLA-DRB1*09:01 molecule. The interaction between the 60Ser of DR9 and 226pro of RhE comprised one hydrogen bond. This study demonstrated that HLA-II haplotypes are associated with allo-anti-E antibodies in pregnant women from Sichuan Province, China. The HLA-DRB1*09:01-DQA1*03:02-DQB1*03:03 phenotype may enhance the formation of anti-E alloantibodies, and the HLA-DRB1*09:01 molecule may play a key role in alloimmunity.
Keywords: Rh factor, Blood system, Alloimmune antibody, Antibodies
Introduction
Transfusion or pregnancy can create erythrocyte alloantibodies, which can cause acute or delayed hemolytic transfusion reactions and even fatality. Alloantibody production in pregnant women can cause fetal neonatal hemolytic disease, leading to fetal or newborn hemolytic jaundice or hemolytic anemia. Anti-E antibodies are significant alloantibodies that induce hemolytic disease in the fetus and newborn [1, 2].
Rh antigens expressed on the surfaces of RBCs have abundant antigenic epitopes and strong immunogenicity and are of great clinical significance; the five most common Rh antigens are D, C, c, E, and e. According to serological studies, RhE is the most common antigen in the Chinese population (approximately 50%) [3]. Regarding antibody distribution in Chinese pregnant women, Anti-E is a common irregular antibody (15.39%)[1]. The E antigen is encoded by the RHCE gene located on chromosome 1, and the E/e polymorphism is caused by the 676G > C missense single nucleotide mutation, leading to a Pro226Ala substitution in the fourth extracellular loop [4].
The erythrocyte alloimmunization reaction includes the recognition of RBC antigens, antigen-presenting cell processing and presentation, the activation of CD4+T cells, interactions between T cells and B cells, and B cell proliferation and differentiation into plasma cells and memory B cells. The human leukocyte antigen (HLA) system plays a pivotal role in antigen presentation. HLA-II is a key predictor of RBC antigen responses, can affect the susceptibility of RBC antibody responders, and is composed of α (34 kDa) and β (28 kDa) chains encoded by non-covalent bonds in the genome. The peptide-binding region of HLA-II antigens is important for erythrocyte surface antigen recognition and initiates specific CD4+ T cell immune responses. In the human HLA-II region, including the DR, DQ, and DP genes, there is a relationship between HLA-DRB1*09:01 and the formation of anti-E alloantibodies in the Chinese population [5]. The development of anti-K and anti-E alloantibodies in Iranian thalassemia-dependent transfusion patients was found to be associated with DRB1*11 [6] and HLA-DRB1*12 [7]. Further, HLA-DRB1*15 is associated with RBC antibody multi-responders in the Czech population [8]. HLA-DRB1*15 and other alleles might also enhance the formation of multiple RBC antibody specificities in other populations [9–12].
Except for HLA-DR, there is a certain relationship between the HLA-DQ gene and the production of autoantibodies in transfusion patients. Maluskova et al. found that DQB1*06 is more frequent in multi-responders with anti-E+c antibodies and that DQB1*02 is more prevalent with transfusions, pregnancies, or transplantations with anti-E+Cw transplantations [8] in the Czech population. HLA-DQB1 alleles are also associated with antiplatelet production [13]. These studies suggest that HLA restriction might play an important role in RBC allogeneic immune susceptibility.
As allo-anti-E is the most prevalent and important irregular alloantibody, the association between HLA-II alleles and alloimmunization risk needs to be investigated, especially in Chinese pregnant women, which has not been explored previously. Therefore, this study aimed to verify the correlation between HLA-DR and HLA-DQ gene polymorphisms and RhE alloimmunization in pregnant Chinese women through HLA-II typing and DR-RhE structural prediction.
Methods
Study Population
In total, 197 blood samples were collected from mothers who had given birth to anti-E-positive children in the second affiliated West China Hospital of Sichuan University from 2019 to 2020. Mothers had three or more pregnancies but no history of blood transfusion. All subjects were RhE antigen-negative and had no antibodies against to other RBC antigens. They were divided into two groups according to whether they had E-specific antibodies, as the anti-E positive (n = 103) and anti-E negative control (n = 94) group, comprising all Han Ethnic Chinese individuals from Sichuan province.
HLA Typing Methods
Genomic DNA of peripheral blood leukocytes was extracted using a blood DNA kit from Beijing Tiangen Biotechnology Co. Ltd. (Beijing, China). HLA-DR and HLA-DQ genotyping was performed using a next-generation sequencing (NGS) kit from ThermoFisher Scientific (Waltham, MA, USA) on lon S5.
Prediction of HLA-DRB1 Binding Sites
NetMHCIIpan-4.0 software (https://services.healthtech.dtu.dk/service.php?NetMHCIIpan-4.0) was used to predict the pan-specific binding of peptides to MHC-II class alleles of known sequences [14, 15]. Considering that the specificity of the E distinguishing e antigen is conferred by proline being replaced by alanine, the RhE 53-mer sequence (201R-253I) containing this specific polymorphism was uploaded to the software. Threshold values of 1% were used to define strong binders and 5% was used to define weak binders. The homologous structure was predicted using AlphaFold-multimer [16] by submitting sequences of the HLA-DR and RhE 15-mer peptide according to software results.
Statistical Analysis
The Hardy–Weinberg equilibrium of HLA-DQA1 and DQB1 distributions was examined using Arlequin version 3.5 software. The allele and phenotype frequencies between the anti-E-positive and control groups were directly compared using SPSS (version 20.0, SPSS Inc., Chicago, IL, USA) with Fisher’s exact test. The odds ratios (ORs) and 95% confidence intervals (95% CIs) were also calculated. Multiple testing correction was performed using the Bonferroni method [17, 18], with pc < 0.05 defining statistical significance. The linkage disequilibrium (LD) of the HLA-DR-DQ allele pairs was calculated based on the EM algorithm with Arlequin software.
Results
HLA-DRB1 Allele Frequencies in Anti-E-Positive Pregnant Women and Negative Control Group
We analyzed the results of DR genotyping from 197 samples. The HLA-DRB1 phenotype frequencies in pregnant women with positive anti-E alloantibodies and the control group are shown in Table 1, and 38 HLA-DRB1 total alleles were found. The frequency of the HLA-DRB1*09:01 phenotype was significantly higher in the anti-E-positive pregnant women than in the anti-E-negative group (63.1% vs. 24.5%; OR: 5.3%; 95% CI: 2.8–9.8; pC < 0.038). In contrast, HLA-DRB1*11:01 and HLA-DRB1*11:01 phenotypes, after correcting the p value for the number of comparisons (n = 38), did not show a significant difference between the two groups.
Table 1.
HLA-DR phenotype frequencies in E-immunized patients and controls
| HLA-DR phenotype frequencies | |||||||
|---|---|---|---|---|---|---|---|
| DRa allele | Anti-E group (n = 103) | Control group (n = 94) | OR (95%CI) | p value | pcvalue | ||
| Number of phenotypes | Phenotype frequency (%) | Number of phenotypes | Phenotype frequency (%) | ||||
| DRB1*01:01 | 2 | 1.9 | 3 | 3.2 | 0.6(0.1–3.7) | NS | NS |
| DRB1*03:01 | 9 | 8.7 | 11 | 11.7 | 0.7(0.3–1.8) | NS | NS |
| DRB1*04:01 | 5 | 4.9 | 2 | 2.1 | 2.3(0.4–12.4) | NS | NS |
| DRB1*04:02 | 1 | 1.0 | 1 | 1.1 | 0.9(0.1-14.8) | NS | NS |
| DRB1*04:03 | 2 | 1.9 | 2 | 2.1 | 0.9(0.1–6.6) | NS | NS |
| DRB1*04:04 | 1 | 1.0 | 1 | 1.1 | 0.9(0.1-14.8) | NS | NS |
| DRB1*04:05 | 5 | 4.9 | 9 | 9.6 | 0.5(0.2–1.5) | NS | NS |
| DRB1*04:06 | 6 | 5.8 | 6 | 6.4 | 0.9(0.3–2.9) | NS | NS |
| DRB1*07:01 | 8 | 7.8 | 10 | 10.6 | 0.7(0.3–1.9) | NS | NS |
| DRB1*08:02 | 2 | 1.9 | 1 | 1.1 | 1.8(0.2–20.6) | NS | NS |
| DRB1*08:03 | 10 | 9.7 | 11 | 11.7 | 0.8(0.3–2.0) | NS | NS |
| DRB1*09:01 | 65 | 63.1 | 23 | 24.5 | 5.3(2.8–9.8) | < 0.001 | < 0.038 |
| DRB1*10:01 | 2 | 1.9 | 3 | 3.2 | 0.6(0.1–3.7) | NS | NS |
| DRB1*11:01 | 2 | 1.9 | 14 | 14.9 | 0.1(0.1–0.5) | 0.002 | NS |
| DRB1*12:01 | 6 | 5.8 | 4 | 4.3 | 1.4(0.4–5.1) | NS | NS |
| DRB1*12:02 | 16 | 15.5 | 21 | 22.3 | 0.6(0.3–1.3) | NS | NS |
| DRB1*13:01 | 2 | 1.9 | 1 | 1.1 | 1.8(0.2–20.6) | NS | NS |
| DRB1*13:02 | 1 | 1.0 | 5 | 5.3 | 0.2(0.1–1.5) | NS | NS |
| DRB1*13:12 | 4 | 3.9 | 3 | 3.2 | 1.2(0.3–1.9) | NS | NS |
| DRB1*14:03 | 1 | 1.0 | 2 | 2.1 | 0.5(0.3–5.1) | NS | NS |
| DRB1*14:05 | 2 | 1.9 | 5 | 5.3 | 0.4(0.1–0.9) | NS | NS |
| DRB1*14:54 | 3 | 2.9 | 10 | 10.6 | 0.3(0.1–0.9) | 0.03 | NS |
| DRB1*15:01 | 12 | 11.7 | 14 | 14.9 | 0.8(0.3–1.7) | NS | NS |
| DRB1*15:02 | 4 | 3.9 | 5 | 5.3 | 0.7(0.2–2.8) | NS | NS |
| DRB1*15:04 | 3 | 2.9 | 2 | 2.1 | 1.4(0.2–8.4) | NS | NS |
| DRB1*16:02 | 5 | 4.9 | 4 | 4.3 | 1.1(0.3–4.4) | NS | NS |
aThe list only present DR allele expressed both in patients and controls
HLA-DQ Allele Frequencies in Anti-E Alloantibody-Positive Mothers and Negative Control Group
Upon analyzing the results of DQ genotyping of 167 samples, 31 subtypes of HLA-DQA1 and HLA-DQB1 alleles were identified. The number of alleles and their frequencies were evaluated within the positive and control groups.
The HLA-DQA1 allele frequencies of the two groups are shown in Table 2, and 16 alleles were found. In the anti-E positive group, 35.6% of the anti-E group had HLA-DQA1*03:02 alleles, which was significantly higher than that in the control group (35.6% vs. 12.8%; OR: 3.8%; 95% CI: 2.2–6.5; pc < 0.0016). However, prevalence of the HLA-DQA1*05:03 allele was not significantly different after correcting the p-value for the number of comparisons (n = 16).
Table 2.
HLA-DQA1 allele frequencies in E-immunized patients and controls
| HLA-DQA1 allele frequencies | |||||||
|---|---|---|---|---|---|---|---|
| Allelea | Anti-E group (n = 73) | Control group (n = 94) | OR (95%CI) | p value | pcvalue | ||
| Number of alleles | Allele frequency (%) | Number of alleles | Allele frequency (%) | ||||
| DQA1*01:01 | 4 | 2.7 | 7 | 3.7 | 0.7(0.2–2.5) | NS | NS |
| DQA1*01:02 | 19 | 13.0 | 30 | 16.0 | 0.8(0.4–1.5) | NS | NS |
| DQA1*01:03 | 9 | 6.2 | 14 | 7.4 | 0.8(0.3–1.9) | NS | NS |
| DQA1*01:04 | 7 | 4.8 | 18 | 9.6 | 0.5(0.2–1.2) | NS | NS |
| DQA1*01:05 | 2 | 1.4 | 3 | 1.6 | 0.9(0.1–5.2) | NS | NS |
| DQA1*02:01 | 8 | 5.5 | 10 | 5.3 | 1.0(0.4–2.7) | NS | NS |
| DQA1*03:01 | 8 | 5.5 | 14 | 7.4 | 0.7(0.3–1.8) | NS | NS |
| DQA1*03:02 | 52 | 35.6 | 24 | 12.8 | 3.8(2.2–6.5) | < 0.0001 | < 0.0016 |
| DQA1*03:03 | 7 | 4.8 | 12 | 6.4 | 0.7(0.3–1.9) | NS | NS |
| DQA1*05:01 | 8 | 5.5 | 11 | 5.9 | 0.9(0.4–2.4) | NS | NS |
| DQA1*05:03 | 3 | 2.1 | 5 | 2.7 | 0.8(0.2–3.3) | NS | NS |
| DQA1*05:05 | 5 | 3.4 | 20 | 10.6 | 0.3(0.1–0.8) | 0.013 | NS |
| DQA1*05:08 | 1 | 0.7 | 1 | 0.5 | 1.3(0.1–20.8) | NS | NS |
| DQA1*06:01 | 12 | 8.2 | 18 | 9.6 | 0.8(0.4–1.8) | NS | NS |
aThe list only present DQA1 allele expressed both in patients and controls
The frequency of HLA-DQB1 alleles in pregnant women between the anti-E alloantibody-positive and control group is also shown in Table 3; 15 HLA-DQB1 alleles were found. In the anti-E group (n = 73), 36.3% of individuals expressed the HLA-DQB1*03:03 allele, compared to 13.3% in the negative group (OR: 3.7; 95% CI: 2.2–6.4; pc < 0.0015). In contrast, the HLA-DQB1*03:01 allele had an OR value of 0.6 (95% CI: 0.3–1.0; p = 0.04). However, after correcting for multiple testing (n = 15), there was no significant difference between the groups. There were also no significant differences in the frequencies of other HLA-DQA1 and DQB1 alleles.
Table 3.
HLA-DQB1 allele frequencies in E-immunized patients and controls
| HLA-DQB1 allele frequencies | |||||||
|---|---|---|---|---|---|---|---|
| Allelea | Anti-E group (n = 73) | Control group (n = 94) | OR (95%CI) | p value | pcvalue | ||
| Number of alleles | Allele frequency (%) | Number of alleles | Allele frequency (%) | ||||
| DQB1*02:01 | 8 | 5.5 | 11 | 5.9 | 0.9(0.4–2.4) | NS | NS |
| DQB1*02:02 | 7 | 4.8 | 9 | 4.8 | 1.0(0.4–2.8) | NS | NS |
| DQB1*03:01 | 23 | 15.8 | 47 | 25.0 | 0.6(0.3–1.0) | 0.04 | NS |
| DQB1*03:02 | 8 | 5.5 | 14 | 7.4 | 0.7(0.3–1.8) | NS | NS |
| DQB1*03:03 | 53 | 36.3 | 25 | 13.3 | 3.7(2.2–6.4) | < 0.0001 | < 0.0015 |
| DQB1*04:01 | 4 | 2.7 | 9 | 4.8 | 0.6(0.2–1.9) | NS | NS |
| DQB1*05:01 | 3 | 2.1 | 9 | 4.8 | 0.4(0.1–1.6) | NS | NS |
| DQB1*05:02 | 16 | 10.9 | 20 | 10.6 | 1.0(0.5–2.1) | NS | NS |
| DQB1*05:03 | 4 | 2.7 | 9 | 4.8 | 0.6(0.2–1.9) | NS | NS |
| DQB1*06:01 | 8 | 5.5 | 19 | 10.1 | 0.5(0.2–1.2) | NS | NS |
| DQB1*06:02 | 9 | 6.2 | 11 | 5.9 | 1.1(0.4–2.6) | NS | NS |
| DQB1*06:03 | 1 | 0.7 | 1 | 0.5 | 1.3(0.1–20.8) | NS | NS |
| DQB1*06:04 | 1 | 0.7 | 1 | 0.5 | 1.3(0.1–20.8) | NS | NS |
aThe list only present DQB1 allele expressed both in patients and controls
Distributions of Three-Loci Haplotypes in the Anti-E and Control Groups at High Resolution
The results of testing HLA-DRB1-DQA1-DQB1 haplotypes at high resolution in anti-E and control groups are shown in Table 4. In total, 20 of 82 haplotypes were detected with frequencies higher than 1% in the anti-E group. After Bonferroni correction, the HLA-DRB1*09:01-DQA1*03:02-DQB1*03:03 haplotype exhibited a significantly higher frequency in the anti-E group than in the control group (pc = 0.0012; OR: 8.67; 95% CI: 2.50–30.05).
Table 4.
The haplotypic frequencies of HLA-DRB1-DQA1-DQB1 haplotypes in the Anti-E group and control group at high-resolution
| Haplotype | Anti-E group HF (%) | Control group HF (%) | P | Pc | OR (95%CI) |
|---|---|---|---|---|---|
| DRB1*03:01-DQA1 *01:02--DQB1*02:01 | 1.37 | 0.53 | – | – | – |
| DRB1*03:01-DQA1 *01:04--DQB1*02:01 | 1.37 | 1.06 | – | – | – |
| DRB1*03:01-DQA1 *03:02--DQB1*02:01 | 1.37 | 0.00 | – | – | – |
| DRB1*04:06-DQA1 *03:01--DQB1*03:02 | 1.37 | 0.00 | – | – | – |
| DRB1*07:01-DQA1 *02:01--DQB1*02:02 | 2.05 | 2.13 | – | – | – |
| DRB1*08:03-DQA1 *01:03--DQB1*03:03 | 2.05 | 0.53 | – | – | – |
| DRB1*09:01-DQA1 *01:02--DQB1*03:03 | 7.53 | 3.19 | – | – | – |
| DRB1*09:01-DQA1 *01:04--DQB1*03:03 | 2.74 | 2.66 | – | – | – |
| DRB1*09:01-DQA1 *03:02--DQB1*03:01 | 6.16 | 3.19 | – | – | – |
| DRB1*09:01-DQA1 *03:02--DQB1*03:03 | 12.30 | 2.05 | 0.00006 | 0.0012 | 8.67(2.50–30.05) |
| DRB1*09:01-DQA1 *03:02--DQB1*06:01 | 2.74 | 0.53 | – | – | – |
| DRB1*09:01-DQA1 *03:03--DQB1*03:03 | 1.37 | 1.06 | – | – | – |
| DRB1*09:01-DQA1 *05:01--DQB1*03:03 | 1.37 | 0.53 | – | – | – |
| DRB1*12:02-DQA1 *06:01--DQB1*03:01 | 1.37 | 2.13 | – | – | – |
| DRB1*12:02-DQA1 *06:01--DQB1*03:03 | 4.11 | 1.60 | – | – | – |
| DRB1*14:05-DQA1 *03:02--DQB1*05:03 | 1.37 | 1.06 | – | – | – |
| DRB1*14:54-DQA1 *03:02--DQB1*05:02 | 1.37 | 1.60 | – | – | – |
| DRB1*15:01-DQA1 *03:02--DQB1*05:02 | 1.37 | 0.00 | – | – | – |
| DRB1*15:01-DQA1 *03:02--DQB1*06:02 | 2.74 | 0.53 | – | – | – |
| DRB1*15:04-DQA1 *03:02--DQB1*05:02 | 1.37 | 0.53 | – | – | – |
Predicting Potential Binding Sites of HLA-DQ Based on NetMHCpan-4.0
At a threshold of 1% (strong binder), no sequences were predicted to bind to HLA-DRB1*09:01 with EL+BA prediction mode. However, at a threshold of 5% (weak binder), one E-derived anchoring sequence (219FWPSVNSPL227) was predicted to bind the DRB1*09:01 molecule.
Using Alpha-Fold to Predict the MHC-Peptide Complex Structure
The interaction between the peptide side chain and the polymorphic residues in the MHC binding pocket occurs through hydrogen bonds, Van der Waals forces, and other interactions. After predicting the HLA-DR antigen-binding pocket with AlphaFold-multimer, it was found that there is one hydrogen bond between DRB1*09:01 and 226proline of antigen peptides (Fig. 1a). One end of the hydrogen bond was found to be connected to the 60Ser residue of the DR9 molecule. Through a query of the IPD-IMGT/HLA database, the DRB1 molecules with 60Ser (phenotype frequency > 5%) are DRB1*07:01, DRB1*09:01, DRB1*12:01, and DRB1*12:02 (Fig. 1b). Because HLA-II is stabilized by the hydrogen bonds between peptide skeletons and binding grooves, the nitrogen atoms of proline residues lose hydrogen bonding potential, and proline side chains interact through covalent bonds [19]. The binding of proline-containing RhE15 peptides might be weakened, but the structure of DR molecules and antigenic peptide side-chain residues participate in constructing the MHC class II peptide binding trough, which could compensate for the decrease in intermolecular interactions caused by the structure of proline. The key amino acid might play a role in the ability of HLA-DRB1 to present the RhE antigen.
Fig. 1.
The interaction about HLA-DRA1*01:01/DRB1*09:01 in RhE 15-mer peptide complex. a The interaction between DR9 and 216L-230S peptide, there were 6 H-bonds. b Sequence alignment of the five HLA-DRB1 alleles showing amino acid polymorphisms. “-” indicates residue conserved with that of HLA-DRB1*01:01. The α and β chains are shown in cartoon representation, and colored in green and bule respectively, with carbons colored in yellow, nitrogens colored in blue, and oxygens colored in red (color figure online)
Discussion
This study was the first to investigate the correlation between HLA-II molecules and erythrocyte alloantigen antibody responses in pregnant women in Southwest China and to demonstrate the binding characteristics of HLA-II gene polymorphisms in terms of the RhE antigen.
At present, there are many studies on the relationship between HLA-DRB1 and human alloimmunization, including red blood cell antibodies [9, 20–22]. Previous studies have shown that alloimmunization with the E antigen is associated with HLA-DRB1 gene polymorphisms in European populations. There is a strong correlation between anti-E-immunity and HLA-DRB1*09 in the Czech population [8, 23]. In Southwest China, it was also confirmed that there is a strong correlation between HLA-DRB1*09:01 and the induction of anti-E immune responses. The DRB1*09:01 molecule interacts with 217-WMFWPSVNS-225 from the sequence containing the polymorphic determinants of the E antigen with high affinity [24]. In contrast, current studies have found that DQB1 is mostly associated with some autoimmune diseases; DQ2 and DQ8 are risk factors for type 1 diabetes, whereas DQB1*06:02 alleles play an important role in the prevention of type 1 diabetes [25]. DQ9 also confers susceptibility to celiac disease [26].
Moreover, HLA-DQ is closely related to the outbreak of hydrolytic wheat allergy [27], the HLA-DQB1*03:03 allele is associated with pityriasis rose [28], DQA1*03:02/DQB1*03:03:02 (DQ9) is positively associated with childhood myasthenia gravis [29], and there might be a close relationship between DQB1*03:03 and immune-related diseases. However, there are few studies on alloimmunity against HLA-II and erythrocyte E antigens in pregnant women.
Therefore, we used NGS to detect the phenotype of this research direction, which is aimed at determining the relationship between the RhE allogenic immune response and HLA-DR and DQ molecules. Our results showed that the phenotypic frequency of HLA-DRB1*09:01, DQA1*03:02, and DQB1*03:03 in Chinese pregnant women immunized with the E-antigen is significantly higher than that in the control group, and the difference was statistically significant. The distribution of the HLA-II gene in the control group was similar to that in the normal population [30], whereas that of HLA-DRB1*09:01, DQA1*03:02, and DQB1*03:03 in the anti-E group was abnormally increased, suggesting that these three genes might represent susceptible alleles promoting the formation of anti-E alloantibodies. Moreover, the HLA-DRB1*09:01-DQA1*03:02-DQB1*03:03 haplotype had strong linkage disequilibrium (LD) in our research. Therefore, it is necessary to verify further whether there is a correlation between HLA-II epitopes and immunity after collecting a larger sample size in the future.
The NetMHCIIpan-4.0 server is professional software used to predict the known peptide binding sequence of HLA-II molecules using artificial neural networks. It was predicted that the HLA-DRB1*09:01 molecule binds to RhE-derived anchor peptides containing the E antigen P226 polymorphism at a low (5%) threshold, whereas the HLA-DQA1*03:02/DQB1*03:03 molecule cannot bind to any peptide at a low (10%) or high (2%) threshold. In addition to the differences among HLA-II molecules, the specific polymorphism itself might also affect the processing of antigens and the selection presented by HLA-II molecules. The antigenic immunogenicity of peptides could also be affected by the flanking polymorphic residues.
Fortunately, AlphaFold provided us with a good platform to predict the structure of proteins with homologous structures, and not only single proteins but also complexes could be predicted using AlphaFold-multimer. We used this tool to verify the known structure of the MHC-peptide complex (PDB:1JK8), and the root mean square deviation (RMSD) of two structure alignment scores was lower than 1. The RMSD is used to quantitatively measure the similarity between two or more protein structures and is usually as low as possible. When the RMSD is less than 1, the structure between the two proteins is considered highly similar, indicating that it is precise enough to predict the DRB1-RhE structure.
The exact binding sites of HLA-II with RhE should be verified based on the HLA-II-RhE complex structure in the future, and their binding force should also be tested based on the structure. The complex structure of the RhE-sequence and DRB1*09:01 was founded on one hydrogen bond connected to 226Pro and DRβ-Ser-60, and the interaction with key amino acids might compensate for the decrease in intermolecular force caused by the structure of proline. Position 60 of HLA-DRB1*09, DRB1*07:01, DRB1*12:01, and DRB1*12:02 is serine, which is different from that of other DRB1 molecules. It is probably a critical amino acid position in the development of anti-E antibodies. Although AlphaFold is a structural prediction method with high precision, the gold standard is still the analysis of specific results. More powerful tools for further research might include transgenic animal models and protein structure analyses.
In the HLA class II gene and haplotype analysis in the Han population of Southern China [31], it was found that the DR-DQ haplotype is almost in an LD state, and the most common DRB1-DQB1 haplotype was DRB1*09:01-DQB1*03:03, which agrees with the results of Zhou et al. [32]. DQB1*03:03 is one of the most common HLA-DQ haplotypes in the Chinese Han population. Studies by Tian and our studies have found that DR9 (or DRB1*09:01) is strongly related to the production of anti-E antibodies in Southwest China. DR9, DQA1*03:02, and DQB1*03:03 might be susceptible epitopes produced by anti-E antibodies. The study by Kumánovics suggested that HLA-DQB1*03:03 can be used as a genetic marker of DR9[33]. The link between DR9 and DQ9 could be associated with common susceptibility to RhE immunity.
The study of the relationship between DR9 and anti-E helps to reduce the risk of specific antibodies produced by blood transfusions or exposure to red blood cell antigens during pregnancy. The limitation of this study is that it does not track the associated neonatal outcomes between the two groups. However, it is necessary to further study the complex structure and immune information pathways that are related to erythrocyte alloimmunization between the HLA-II allele and E antigen.
Conclusions
In summary, the HLA-DRB1*09:01-DQA1*03:02-DQB1*03:03 phenotype is more common in anti-E immunity in Chinese pregnant women.
Acknowledgements
This work was supported by the Science andTechnology Department of Sichuan Province (No. 2022YFS0239), the Science andTechnology Department, West China Second University Hospital, Sichuan University (No. KL066), Cadres Healthcare Research Projects in Sichuan Province (No. 2021-1703). We would like to thank Editage (www.editage.cn) for English language editing.
Author Contributions
Designing experiments, conducting experiments and data analysis: WLS and GJO; Writing the manuscript: WLS; Data analysis and providing critical technical and scientific debate: WLS, GJO, XJ, JC, JW and YMJ. All authors read and approved the final manuscript.
Declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Ethics Approval and Consent to Participate
This study was approved by the local research ethics committee.
Footnotes
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Contributor Information
Wenling Shang, Email: sj1153760994@163.com.
Guojin Ou, Email: jiaozhu327@163.com.
Xin Ji, Email: 380394746@qq.com.
Jian Chen, Email: 896268307@qq.com.
Jue Wang, Email: wangjue@ibt.pumc.edu.cn.
Yongmei Jiang, Email: jiangyongmeiwst@163.com.
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