Our Research
Why HLA-DQ?
Part 5: HLA-DQ Immunogenicity: Where do we go from here?
To recap, so far, we have argued that:
1. HLA-DQ polymorphism differs from that of HLA-DR, and does not lend itself well to ꞵ-chain-derived serologic nomenclature
2. Antibodies targeting HLA-DQ are common and recognize epitopes encompassing both the α- and ꞵ- chain of the molecule
3. Our current inability to appropriately report HLA-DQ antibodies (as the physiologic DQαβ chains) leads to inaccurate measures of sensitization and unjust organ allocation policies.
Despite its importance, HLA-DQ has not been adequately studied
Our research focuses on highlighting the unique characteristics of HLA-DQ and pushing for policy changes that take these characteristics into consideration. This is made even more important by the fact that HLA-DQ antibodies are the most common de novo DSA and most associated with poor graft outcomes. We hope that putting a spotlight on DQ will encourage the development of more equitable organ allocation policies that will ultimately improve long-term patient outcomes.
Studies that confirmed HLA-DQ’s immunological importance lagged behind those for HLA-DR, therefore most of the experimental data that currently exists on the class II antigens is focused on HLA-DR. Early attempts to study HLA-DQ in a laboratory setting also proved challenging, due to fact that cell-surface expression of HLA-DQ is at lower levels than HLA-DR. Luckily, advances such as the SAB assay and the realization that autoimmune disease associations were more commonly linked to HLA-DQ alleles (many of which were originally attributed to linkage with DR) have led to a recent surge in the number of studies focused on the DQ locus. The results of these studies have added to the growing body of evidence that HLA-DR and -DQ have unique immunogenic properties, and may help elucidate why HLA-DQ is the most common and pathogenic target for DSA.
What makes HLA-DQ so immunogenic?
Immunogenicity can essentially be defined as an antigen’s ability to induce a humoral or cell-mediated immune response. In order to do so, the antigen must possess one or more epitopes that can be recognized by the host’s B-cell (humoral) and/or T-cell (cell-mediated) receptors, the latter recognizing processed peptides presented in the context of the host’s HLA molecule. Being able to identify these key epitopes is a fundamental, yet challenging step in studying the immunogenicity of an antigen. In HLA antigens, which form the most polymorphic genetic system in humans, the number of possible epitopes that can be recognized by a B- or T-cell receptor is understandably immense.
There have been several proposed approaches to defining HLA epitopes and incorporating them into clinical decision-making, although none have been universally adopted or accepted. As a result, the concept of “epitope matching” has become one of the most fiercely debated topics in the modern HLA era. One the more popular, and arguably more compelling of these proposals utilizes eplets as defined by the HLAMatchmaker software that was described in an earlier section. Supporters of this approach argue that the eplet load (the total number of eplet mismatches between donor and recipient) can be used to risk-stratify patients for their likelihood of developing de novo antibodies. Similar cases have been made for amino acid mismatch (AAM) load, electrostatic mismatch (EMS) score, and predicted indirectly recognizable HLA epitopes, HLA class II-presented (PIRCHE-II) score.
The aforementioned methods have shown promising effectiveness of risk stratification at the population level, but show limited ability to predict histocompatibility for individual donor/recipient pairs. This is exemplified by recipients with very low scores/loads that still develop de novo DSA, and those with very high scores/loads that never develop de novo DSA.
We have postulated that this phenomenon could be explained by the fact that these methods do not consider variables that could affect the immunogenicity of the mismatched epitopes. We therefore believe that a strategy that considers both mismatch load and the immunogenicity of each mismatch would be a better approach to achieve immune compatibility.
CASE STUDY
The following case study illustrates one of our lab’s first encounters with HLA epitopes in the clinical setting. At the time that this case took place (2006), SAB testing had only recently been introduced in the lab. Similarly, epitope analysis using amino acid sequences of the HLA alleles was in its early stages.
A male patient had a PRA of 0% prior to transplantation with an HLA-A, -B, -DR-matched donor. Unfortunately, shortly after the transplant, he developed BK viremia which required a temporary reduction in immunosuppression. Although the viremia cleared, the patient quickly developed DSA and presented with a class II PRA of 100% using the FlowPRA assay during his next follow-up visit. Single antigen bead analysis was performed, and allowed for a much broader understanding of the antibody specificities present. To our surprise, all reactivity was restricted to HLA-DP. The table below summarizes the results of the SAB assay.
HLA-DP SAB results. Class II PRA was 100%, yet all reactivity was toward DP specificities. Patient DP typing is in blue boxes; donor DP typing is in the pink boxes. Positive beads are highlighted in green, which includes a DSA against DP*0301. Each column shows the amino acid sequences of the seven polymorphic silos found in the HLA-DP coding sequence
The HLA-DPB locus is unique in that all polymorphic residues are confined within only six “silos” of the amino acid sequence. These silos are: residues 8-11, 33-36, 55-57, 65-69, 76, and 84-87. The table shows the polymorphic amino acid sequence of each DPB1 bead specificity included in the SAB assay. The recipient in this case study was typed as a DPB1*04:01 & *04:02, while the donor was DPB1*02:01 & *03:01. Surprisingly, the recipient formed antibodies that targeted not just the donor’s DPB1 allele, but multiple other non-donor-specific DPB1 alleles as well.
An initial look at amino acid mismatches between the recipient and donor DPB1 typing reveals mismatches in 5/6 silos to the donor’s DPB1*03:01 allele, but only 1/6 silos to the DPB1*02:01 allele. Indeed, the DSA formed by the patient targeted the DPB1*03:01 donor allele, supporting the notion that a higher mismatch load is more likely to lead to de novo DSA formation. However, upon closer examination of the full reactivity pattern seen in the SAB assay, it is revealed that all positively reacting beads shared a common amino acid sequence in the sixth polymorphic silo: 84-87DEAV. If the patient only developed antibodies against a single epitope containing the residues 84-87DEAV, it suggests that this particular epitope mismatch was more immunogenic than the other epitope mismatches for the recipient.
While the patient exhibited antibodies against four out of the five DQ7 specificities on the SAB panel, he did not show reactivity with the DQ7 antigen containing a DQA*03:01 α-chain. High-resolution typing of the donor and Flow PRA bead revealed a DQ7 phenotype of DQA1*03:01~DQB1*03:01 and DQA1*05~DQB1*03:01, respectively, explaining the initially discrepant positive Flow PRA antibody screen and negative FCXM.
It becomes clear that using DQ serologic nomenclature is not sufficient when reviewing antibody and typing information for virtual crossmatch assessments. In the discussed case, it was assumed that the patient possessed DSA against the potential donor when in fact he did not. If this phenomenon – that patients could develop antibodies directed against only a subset of a serotype defined by specific α-chains – proved to be more prevalent, serologic nomenclature would be unable to capture this. The next question, naturally, then became “how common is this?”
Reviewing the evidence leaves us with a few lingering questions:
- Was it the higher mismatch load of the DPB1*03:01 allele that drove antibody formation? Or was it the higher immunogenicity of the 84-87DEAV epitope?
- Was it both?
- Would a 4/6 mismatch load that didn’t mismatch at the sixth silo have prevented DSA formation?
- Conversely, would a single mismatch at the sixth silo still result in DSA?
These are all questions that propelled our interest in understanding HLA immunogenicity. The case study was one of the first instances for our lab that brought role of shared epitopes in de novo antibody formation into sharp focus. It also presented the notion that certain epitopes can be perceived as more immunogenic than others by the recipient. We therefore believe it is critical to consider epitope mismatches through the “eyes” of the recipient’s immune system in order to best evaluate the immunogenicity of the mismatch. Read more about this concept and some of our current research projects here.
Inhibition patterns may shed light on epitope characteristics
Defining epitope immunogenicity will likely require a combined knowledge of eplet/amino acid sequences, electrostatic potential, and the recipient’s own HLA typing. HLA epitopes are still poorly defined and identifying the factors that contribute to their immunogenicity has been challenging. In our quest to understand HLA epitopes and their immunogenicity, we re-analyzed dozens of serum samples from highly sensitized patients. Further examination of titration studies on these patients revealed a potential new tool for investigating antibody and epitope characteristics, one that was hiding in plain sight and which takes advantage of one of the limitations of the SAB assay discussed earlier.
Figure: Antibody reactivity patterns for HLA-DQ from a highly sensitized patient. The patient showed reactivity against 25/28 DQ specificities included in the panel, all with a peak MFI of at least 8,000. A closer look at the titration plot reveals several distinct groups that follow the same reactivity pattern. Although some fall within conventional DQ serotype groups, others show more diverse groupings.
Source: Tambur AR. 2016. Hiding in plain sight – A new look at HLA epitopes: A case report. Am J Transplant 16:3286-3291
In our study, we discussed a highly sensitized female patient that exhibited several HLA-DQ antibodies that showed inhibition. Upon titration of her serum, it was revealed that the DQ antibodies displayed a handful of distinct patterns of reactivity. The figure above shows the overall titration pattern, as well as the individual patterns that were extracted from it. Patterns A and B contained antibody specificities within the DQ serologic groups DQ6 and DQ3, respectively, suggesting antibody binding to an epitope shared by those alleles. However, patterns C and D include specificities from at least two distinct DQ serotypes (and distinct DQA chains). The nearly identical patterns suggest that these antigens share some physiologic similarities. While the implications of these findings are not yet clear, we have observed this phenomenon in numerous patient sera and have amassed a large collection of this serum for future testing. You can read more about our current research projects that utilize these samples here.
We hope that a deeper understanding of antibody responses using tools like this one may help to elucidate the antigenic and immunogenic properties of HLA epitopes. This knowledge could then one day be used to predict the likelihood of epitope mismatches to trigger humoral alloresponses and reduce the risk of antibody-mediated rejection.