HLA-DQ Mismatches Lead to More Unacceptable Antigens, Greater Sensitization, and Increased Disparities in Repeat Transplant Candidates

Dylan Isaacson; Jesse D Schold; Michael W Gmeiner; Hannah C Copley; Vasilis Kosmoliaptsis; Anat R Tambur

doi:10.1681/ASN.2022030296

. 2022 Dec;33(12):2293–2305. doi: 10.1681/ASN.2022030296

HLA-DQ Mismatches Lead to More Unacceptable Antigens, Greater Sensitization, and Increased Disparities in Repeat Transplant Candidates

Dylan Isaacson ^1,², Jesse D Schold ^3,⁴, Michael W Gmeiner ⁵, Hannah C Copley ⁶, Vasilis Kosmoliaptsis ^6,⁷, Anat R Tambur ^1,^✉

PMCID: PMC9731640 PMID: 36450598

Significance Statement

HLA-DQ donor-specific antibodies are associated with antibody-mediated rejection and renal graft loss in single-center studies. However, HLA-DQ remains largely unaccounted for in kidney allocation. US transplant registries do not include donor-specific antibody data, precluding direct analysis of HLA-DQ mismatches and transplant outcomes. The authors examined data from patients in the Scientific Registry of Transplant Recipients who were relisted after graft failure with unacceptable antigens corresponding to the HLA typing of their previous donor as a proxy for donor-specific antibodies. Mismatched HLA-DQ antigens were the most likely to be designated as unacceptable, especially in African American and Hispanic patients. Unacceptable HLA-DQ antigens precipitated sensitization greater than or equal to any other HLA locus. These findings underscore the immunogenicity of HLA-DQ mismatches, which ultimately serves as a barrier to transplantation.

Keywords: cadaver organ transplantation, chronic rejection, end stage renal disease, kidney donation, kidney transplantation, organ transplant, renal transplantation, transplantation, transplant outcomes, transplant pathology

Visual Abstract

graphic file with name ASN.2022030296absf1.jpg

Abstract

Background

In single-center studies, HLA-DQ mismatches stimulate the most pathogenic donor-specific antibodies. However, because of limitations of transplant registries, this cannot be directly confirmed with registry-based analyses.

Methods

We evaluated patients in the Scientific Registry of Transplant Recipients who were relisted after renal graft failure with new, unacceptable antigens corresponding to the HLA typing of their previous donor (UA-PD) as a proxy for donor-specific antibodies. Linear regression was applied to estimate the effects of HLA mismatches on UA-PD and the effects of UA-PD on calculated panel reactive antibody (cPRA) values for 4867 kidney recipients from 2010 to 2021.

Results

Each additional HLA-DQ mismatch increased the probability of UA-PD by 25.2% among deceased donor transplant recipients and by 28.9% among living donor transplant recipients, significantly more than all other HLA loci (P<0.05). HLA-DQ UA-PD increased cPRA by 29.0% in living donor transplant recipients and by 23.5% in deceased donor transplant recipients, significantly more than all loci except for HLA-A in deceased donor transplant recipients (23.1%). African American deceased donor transplant recipients were significantly more likely than Hispanic and White recipients to develop HLA-DQ UA-PD; among living donor transplant recipients, African American or Hispanic recipients were significantly more likely to do so compared with White recipients. Models evaluating interactions between HLA-DR/DQ mismatches revealed largely independent effects of HLA-DQ mismatches on HLA-DQ UA-PD.

Conclusions

HLA-DQ mismatches had the strongest associations with UA-PD, an effect that was greatest in African American and Hispanic recipients. cPRA increases with HLA-DQ UA-PD were equivalent or larger than any other HLA locus. This suggests a need to consider the effects of HLA-DQ in kidney allocation.

Kidney transplantation is the most definitive treatment for ESKD and confers improved longevity and quality of life compared with dialysis.¹^,² Although current US trends have shown improvements in graft survival, more than 20% of deceased donor and 10% of living donor kidneys still fail by 5 years.³

Antibody-mediated rejection (ABMR) is the leading cause of graft loss after kidney transplantation.⁴ Correspondingly, donor-specific antibodies (DSAs) produced by recipients against mismatched human leukocyte antigens (HLAs) are highly predictive of graft failure.⁵^–⁷ Although single-center studies have demonstrated that donor HLA-DQ antigens stimulate the most common and pathogenic DSAs,⁸^–¹¹ HLA-DQ matching is not yet considered in many kidney-matching algorithms, including the US Kidney Allocation System.¹²

Registry-based analyses of HLA-DQ matching and kidney transplant outcomes have shown variable results. Early studies found no associations between serologic DQ mismatches and graft outcomes.¹³^,¹⁴ Subsequent analyses demonstrated effects of HLA-DQ mismatches on rejection episodes and biopsy-proven ABMR¹⁵ and on graft loss in living donor recipients and deceased donor recipients with cold ischemic times ≤17 hours.¹⁶ These registry-based studies have several key limitations. Inclusion of records before 2010 risks bias due to higher rates of missing HLA-DQ data and heterogeneous HLA typing methods. The Scientific Registry of Transplant Recipients (SRTR) includes HLA typing only at low resolution with serologic-equivalent (1-field) typing, as opposed to modern high-resolution allele-level (2-field) typing. This prevents rigorous analysis of HLA mismatches as donor/recipient types that appear matched with 1-field coding may truly be mismatched at the allelic level.¹⁷^,¹⁸ Finally, the SRTR does not record DSAs or ABMR, preventing direct study of DQ DSAs and transplant outcomes.

Given these limitations, we conceived a novel analysis of SRTR data to assess the effects of HLA-DQ mismatches in kidney transplantation. We identified patients who were relisted after a failed first transplant and used the incidence of new unacceptable antigens corresponding to the HLA typing of their previous donor (UA-PD) as a proxy for DSAs. Unacceptable antigens refer to potential donor antigens analogous to a candidate’s existing HLA antibodies and are designated when a candidate is initially listed or relisted and then periodically until transplantation. We propose that the presence of antibodies to the previous donor’s antigens at the time of relisting is consistent with those antibodies having played a role in graft failure. We apply these principles to evaluate whether HLA-DQ mismatches have a differential effect on the development of UA-PD and recipient sensitization compared with other HLA loci.

Methods

Institutional Review Board

This study was classified as being institutional review board exempt by the institutional review board at Northwestern University before data collection and analysis.

Study Population

This study used data from the SRTR. The SRTR data system includes data on all donors, waitlist candidates, and transplant recipients in the United States, submitted by the members of the Organ Procurement and Transplantation Network. The Health Resources and Services Administration, US Department of Health and Human Services provides oversight to the activities of the Organ Procurement and Transplantation Network and SRTR contractors.

Adult (≥18 years) patients in the SRTR who received an initial single deceased or living donor kidney transplant between January 1, 2010 and March 2, 2021 were eligible for inclusion in the study if they were relisted after allograft failure. We limited inclusion to patients with complete donor/recipient HLA typing and recipient unacceptable antigen data. Subjects were excluded if they had broad HLA antigen typing listed to ensure all matching was assessed at the split (private antigen) level, if they had received other transplanted organs, or if they had experienced graft loss within 30 days after transplantation. We further excluded patients who were preemptively listed for retransplantation to minimize the potential confounding effects of continuing full-dose immunosuppression.

Data Collection

Data collected on kidney donors included antigen-level HLA-A/B/C/DR/DQ typing. Data collected on recipients included age, sex, race and ethnicity, body mass index, education level, insurance status, cause of ESKD, time on dialysis pretransplant, dates of graft failure and relisting, antigen-level HLA-A/B/C/DR/DQ typing, HLA-A/B/C/DR/DQ unacceptable antigen data, and pre/post-transplant cPRA.

Outcomes

The primary outcomes of the study were (1) the probability of relisting after graft failure with a new UA-PD given a mismatch at an HLA locus; and (2) the change in cPRA from the pretransplant value to the maximal value recorded after graft failure given development of a new UA-PD at an HLA locus. Primary outcomes were stratified by living or deceased donor status of the initial transplant kidney and by recipient race and ethnicity. Secondary analyses evaluated the interactions between the effects of HLA-DR and HLA-DQ on the primary outcomes.

Statistical Analyses

Baseline demographics were expressed as percentages or medians with interquartile ranges. t tests and one-way ANOVAs were applied to determine statistical significance of differences in characteristics between groups.

To establish the relationship between HLA mismatches and UA-PD, a multiple linear regression model was created. This model assessed the effect of mismatches at an HLA locus (0–2) on relisting with new UA-PD at that locus, controlling for mismatches at all other HLA loci. The model was applied to the cohort overall and stratified by recipient race and ethnicity classifications. A second regression model was estimated to test for statistical significance of differences between the effect of DQ mismatches on DQ UA-PD versus the effects of other HLA mismatches on corresponding UA-PD. A third regression model assessed for statistical significance of differences in the probabilities of DQ UA-PD between recipients of different race and ethnicity groups.

To determine the effects of HLA-DQ mismatches on recipient sensitization, linear regression was again applied. The outcome was the increase in cPRA from the final pretransplant value to the maximal value recorded after relisting. Independent variables were the presence of a new UA-PD at each HLA locus. To eliminate potential confounders of sensitization, this model controlled for the effects of unacceptable antigens at each locus not being assessed, HLA mismatches (0–2), pretransplantation cPRA, time between graft failure and relisting, and time between relisting and final follow-up. Results were calculated for the cohort overall and stratified by pretransplantation cPRA (0%, 1%–50%, 51%–100%) and recipient race and ethnicity classifications. A second regression model was applied to assess for statistical significance of the differences in cPRA increases for each HLA locus compared with HLA-DQ. A third regression model assessed the statistical significance of differences in cPRA increases with a new HLA-DQ UA-PD between subjects of different race and ethnicity groups.

To evaluate the interactions between the effects of HLA-DR and HLA-DQ in these analyses, the regression models were augmented to include HLA-DR/DQ interaction terms. In the models assessing the effects of HLA mismatches on relisting with new UA-PD, the interaction term estimates how the change in probability of UA-PD with an additional HLA-DQ mismatch differs between cases without an HLA-DR mismatch and cases with an HLA-DR mismatch. In the models evaluating cPRA changes with new UA-PD, the interaction term estimates how the change in cPRA with an additional HLA-DQ UA-PD differs between cases without an HLA-DR UA-PD and cases with an HLA-DR UA-PD.

P<0.05 was considered statistically significant throughout the study. Calculations were performed in Stata version 17 (StataCorp, College Station, TX).

Results

Study Population

A total of 34,891 patients experienced graft failure during the study period, of whom 28,553 (81.8%) were not relisted (Figure 1). Of the 6338 (18.2%) patients relisted, 4867 (76.8%) were included: 3443 deceased donor recipients (70.7% of included patients) and 1424 living donor recipients (29.3% of included patients).

Baseline Characteristics

Demographics and characteristics related to sensitization are stratified by failed deceased versus living donor kidney and the presence/absence of new DQ UA-PD in Table 1. Characteristics are further stratified by recipient race and ethnicity in Supplemental Table 1.

Table 1.

Demographics and characteristics related to sensitization stratified by deceased versus living donor category of the initial failed graft and the presence or absence of a new HLA-DQ unacceptable antigen corresponding to prior donor typing (UA-PD)

Characteristics	Failed Deceased Donor Kidney		Failed Living Donor Kidney
Characteristics	New HLA-DQ UA-PD (n=1445)	No New HLA-DQ UA-PD (n=1998)	New HLA-DQ UA-PD (n=593)	No New HLA-DQ UA-PD (n=831)
Age (yr), median (IQR)	48 (35–59)^a	52 (40–62)^a	40 (30–52)^a	44 (32–56)^a
Male, n (%)	870 (60.2)	1155 (57.8)	354 (59.7)	479 (57.6)
Race, n (%)
African American	713 (49.3)^a	857 (42.9)^a	143 (24.1)^a	150 (18.1)^a
Asian/Pacific Islander	85 (5.9)	134 (6.7)	26 (4.4)	26 (3.1)
Hispanic	210 (14.5)	291 (14.6)	94 (15.9)	123 (14.8)
White	425 (29.4)^a	693 (34.7)^a	323 (54.5)^a	523 (62.9)^a
Other	12 (0.83)	23 (1.2)	7 (1.9)	9 (1.1)
Cause of ESKD, n (%)
GN	421 (29.1)	565 (28.3)	273 (46.0)^a	320 (38.5)^a
Diabetes	252 (17.4)^a	418 (20.9)^a	54 (9.1)^a	124 (14.9)^a
Hypertension	380 (26.3)^a	454 (22.7)^a	90 (15.2)	120 (14.4)
PKD	88 (6.1)^a	170 (8.5)^a	54 (9.1)	80 (9.6)
Other	304 (21.0)	391 (19.6)	122 (20.6)	187 (22.5)
Days on dialysis pretransplant, median (IQR)	1514 (889–2174)	1468 (856–2244)	520 (302–933)	475 (281–918)
Days between graft failure/relisting, median (IQR)	1261 (405–1980)^a	620.5 (113–1597)^a	1569 (881–2269)^a	1246 (246–2112)^a
Pretransplant cPRA, n (%)
0%	948 (65.6)^a	1224 (61.3)^a	413 (69.7)^a	623 (75.0)^a
0.1%–50%	296 (20.5)	415 (20.8)	125 (21.1)^a	148 (17.8)^a
50.1%–80%	84 (5.8)	143 (7.2)	29 (4.9)	31 (3.7)
80.1%–98.0%	96 (6.6)	159 (8.0)	23 (3.9)	20 (2.4)
>98.1%	21 (1.5)^a	56 (2.8)^a	3 (0.51)	9 (1.1)
Peak post-graft loss cPRA, n (%)
0%	12 (0.83)^a	721 (36.1)^a	6 (1.0)^a	357 (43.0)^a
0.1%–50%	52 (3.6)^a	289 (14.5)^a	29 (4.9)^a	146 (17.6)^a
50.1%–80%	143 (9.9)	199 (10.0)	80 (13.5)	96 (11.6)
80.1%–98.0%	361 (25.0)^a	255 (12.8)^a	180 (30.4)^a	104 (12.5)^a
>98.1%	877 (60.7)^a	534 (26.7)^a	298 (50.4)^a	128 (15.4)^a

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IQR, interquartile range; PKD, polycystic kidney disease.

Statistically significant differences between groups (P<0.05).

Probabilities of New Unacceptable Antigens Corresponding to Previous Donor Typing

Figure 2 depicts the probabilities that recipients would return to the waitlist after graft failure with new UA-PD (0%–100%). Each additional HLA-DQ mismatch increased the probability of relisting with an HLA-DQ UA-PD by 25.2% in deceased donor recipients and 28.9% in living donor recipients. This probability was significantly greater than with mismatches at all other HLA loci (P<0.05).

Probabilities of New Unacceptable Antigens by Recipient Race and Ethnicity

The probabilities of relisting with new UA-PD by recipient race and ethnicity are presented in Figure 3. Analyses include African American, Hispanic, and White recipients only, as we did not have sufficient subjects to include Asian/Pacific Islander recipients or recipients reporting other races/ethnicities. (See Table 1 for the distribution of the cohort by race and ethnicity).

Figure 3, A–C, illustrates results for deceased donor recipients. For African American deceased donor recipients, the probability that DQ mismatches would produce UA-PD (29.3%) was significantly greater than any other HLA locus (P<0.05). For Hispanic recipients, the probability of DQ UA-PD (24.0%) was only significantly different from HLA-C. In White recipients, the probability of DQ UA-PD (21.6%) was significantly greater than HLA-B, -C, and -DR and comparable to HLA-A (22.2%). African American recipients were significantly more likely to be relisted with new DQ UA-PD compared with Hispanic and White recipients (P<0.05). There was no significant difference in the probabilities of DQ UA-PD between Hispanic and White recipients.

Results for living donor recipients are depicted in Figure 3, D–F. For African American living donor recipients, DQ mismatches were associated with the greatest probability of UA-PD (34.1%), significantly more than HLA-C. In Hispanic recipients, the probability of DQ UA-PD (33.0%) was significantly greater than all HLA loci except for HLA-A (26.9%). In White recipients, the probability of DQ UA-PD (27.6%) was significantly greater than all other HLA loci (P<0.05). Both African American and Hispanic living donor recipients were more likely to be relisted with new DQ UA-PD compared with White recipients (P<0.05). There was no significant difference in the probabilities of DQ UA-PD between African American and Hispanic recipients.

HLA Unacceptable Antigens and Increases in cPRA

The fully adjusted analyses assessing cPRA increases with new UA-PD are depicted in Figure 4. Results are presented for deceased and living donor recipients overall and stratified by pretransplantation cPRA. The majority of deceased (63.1%) and living donor recipients (72.8%) were unsensitized before transplantation (cPRA 0%), comprising an important subgroup as the full effect of cPRA changes is most accurately captured in these patients.

In deceased donor recipients (Figure 4, A–D), patients who developed new HLA-DQ UA-PD experienced mean overall cPRA increases of 23.5%, significantly greater than HLA-B, -C, and -DR but not HLA-A (23.1%, Figure 4A). In initially unsensitized deceased donor recipients (Figure 4B), the average cPRA increase with a new DQ UA-PD (27.9%) was significantly greater than HLA-B, -C, and -DR but not HLA-A (28.3%). In living donor recipients (Figure 4, E–H), DQ UA-PD resulted in an average overall cPRA increase of 29.0%, significantly greater than all other HLA loci (P<0.05, Figure 4E). In previously unsensitized living donor recipients, DQ UA-PD had a significantly greater effect on cPRA (33.2%) than every other HLA locus (P<0.05, Figure 4F).

These effects of UA-PD on cPRA were largely independent of other potential contributors to sensitization such as overall HLA mismatches and the time intervals between graft failure, relisting, and final follow-up (Supplemental Table 2).

HLA Unacceptable Antigens and Increases in cPRA by Recipient Race and Ethnicity

The adjusted analyses evaluating cPRA increases with UA-PD are stratified by recipient race and ethnicity in Figure 5 and substratified to evaluate previously unsensitized recipients in Figure 6. As in the cohort overall, the majority of African American, Hispanic, and White deceased donor recipients (61.2%, 64.5%, and 65.7%, respectively) and living donor recipients (67.6%, 76.0%, and 74.2%, respectively) were unsensitized before transplantation.

In initially unsensitized deceased donor recipients (Figure 6, A–C), African American recipients experienced average cPRA increases of 27.5% with a new DQ UA-PD, significantly greater than HLA-B, -C, and -DR but not statistically different from HLA-A (30.6%). For Hispanic recipients, the average increase in cPRA with a new DQ UA-PD (23.9%) was significantly greater than HLA-DR only. In White recipients, the mean cPRA increase with a new DQ UA-PD (29.9%) was significantly greater than all other HLA loci except for HLA-A (25.6%). There were no significant differences in the magnitudes of cPRA increases with DQ UA-PD between race and ethnicity groups either in the cohort overall or in the subgroup of initially unsensitized recipients.

In initially unsensitized living donor recipients (Figure 6, D–F), African American recipients experienced overall mean cPRA increases of 30.4% with a new HLA-DQ UA-PD, significantly greater than all loci except HLA-A (27.6%). The cPRA increases with new DQ UA-PD for Hispanic and White living donor recipients (46.1% and 32.0%, respectively) were greater than the effects of all other HLA loci (P<0.05). As in deceased donor recipients, there were no significant differences in cPRA increases with DQ UA-PD between race and ethnicity groups in either the overall cohort or in previously unsensitized recipients.

Interactions of HLA-DR/DQ on Unacceptable Antigen Probabilities and cPRA Increases

To illustrate the interactions between HLA-DR and -DQ mismatches on the probabilities of UA-PD, we formulated scenarios with example recipients demonstrating how these probabilities change with addition or removal of HLA-DR and/or -DQ mismatches (Supplemental Figure 1). Note that the magnitudes of the coefficients in this model are not directly comparable to those in the initial model without the DR/DQ interaction term (Figure 2). Compared with a deceased donor-recipient initially transplanted with no HLA-DR or -DQ mismatches, a simulated recipient with no HLA-DR mismatches and one HLA-DQ mismatch had a 40.2% (95% confidence interval [CI], 35.0% to 45.5%) probability of developing an HLA-DQ UA-PD and a 9.5% (95% CI, 4.1% to 14.8%) probability of developing an HLA-DR UA-PD (Supplemental Figure 1A). A simulated recipient with an HLA-DR mismatch and an HLA-DQ mismatch comparatively had a 41.5% (95% CI, 36.3% to 46.7%) probability of developing an HLA-DQ UA-PD and a 29.0% (95% CI, 23.7% to 34.2%) probability of developing an HLA-DR UA-PD. An analogous example in living donor recipients is presented in Supplemental Figure 1B. The output of the models upon which these examples are based is included in Supplemental Table 3.

Similar scenarios demonstrating how overall cPRA increases vary with addition or removal of HLA-DR and/or -DQ UA-PD at relisting are presented in Supplemental Figures 2 and 3. These depict hypothetical deceased (Supplemental Figure 2) and living donor recipients (Supplemental Figure 3) with pretransplant cPRA of 0% (Supplemental Figures 2A and 3A) or 1%–50% (Supplemental Figures 2B and 3B). Changes in cPRA are relative to a recipient who did not develop DR or DQ UA-PD. The output of the models upon which these scenarios are based is included in Supplemental Table 4. As in Supplemental Figure 1, note that the magnitudes of the coefficients in these models are not directly comparable to those in the initial model without the DR/DQ interaction term (Figure 4), and that the additive effect of DR and DQ UA-PD can be slightly lower than the individual effects due to the negative interaction term and the uncertainty of each of the estimates.

Discussion

We present a novel method utilizing SRTR data to quantify the differential effects of HLA mismatches on generation of DSAs (determined on the basis of the appearance of new UA-PD at relisting) and on the likelihood of receiving an antibody-compatible deceased donor kidney after graft loss (measured as increase in cPRA). We demonstrate that HLA-DQ mismatches are associated with the highest probability of new UA-PD after graft failure, an effect that disproportionately affects African American and Hispanic recipients compared with White recipients. We show that UA-PD at distinct HLA loci have differential effects on cPRA and that HLA-DQ has an effect greater than or equal to any other HLA locus. Although this method does not prove causality, these findings are consistent with the broader literature, based largely on single-center studies using single antigen bead assays, which has shown that HLA-DQ DSAs are the most common alloantibodies that develop after kidney transplantation and are strongly associated with ABMR and graft loss.⁹^,¹⁰^,¹⁹

The patients in our study who were relisted with new UA-PD after allograft failure, should by definition have developed de novo DSAs. Other explanations, such as reactivation of quiescent immune responses, cannot entirely be ruled out, but are less likely given that 66% of the cohort had a pretransplantation cPRA of 0%. Also possible is that these antibodies developed after graft failure as a result of decreases in immunosuppression; a recent prospective multicenter study demonstrated moderate cPRA increases in recipients observed for a median of 1.5 years after kidney transplant failure.²⁰ We could not directly control for immunosuppression changes after graft loss as the SRTR does not record these data; however, our models did not show effects of time elapsed between graft failure, relisting, and final follow-up on overall sensitization, as would likely be expected if this were the primary driving factor behind the effects observed in this study¹⁰ (Supplemental Table 2).

Our analyses found that each HLA-DQ mismatch increased the probability of DQ UA-PD by 25.2% in deceased donor recipients and 28.9% in living donor recipients, an effect significantly greater than all other HLA loci (Figure 2). This suggests that HLA-DQ mismatches have the greatest effect of any HLA locus on graft loss in our cohort, although a causal relationship cannot be definitively proven within limitations of registry data. The significantly smaller probability of HLA-DR UA-PD after DR-mismatched transplantation is a notable finding given the longstanding assumption that, due to high linkage disequilibrium between HLA-DR and -DQ, matching at DR implicitly results in DQ matching, rendering explicit DQ matching unnecessary.²¹ Our analysis of the interactions between DR and DQ mismatches (Supplemental Figure 1) goes further in supporting the independent relationship of HLA-DQ mismatches and DQ UA-PD. In these models, the effect of adding an additional DR mismatch to an existing DQ mismatch resulted in only a small absolute increase in the probability of DQ UA-PD proportional to the uncertainty of the estimates.

Overall, HLA-DQ UA-PD were associated with cPRA increases equal to or greater than with UA-PD at any other HLA locus (Figure 4). These effects were largely driven by patients who were unsensitized (cPRA 0%) before transplantation, who comprised 63.1% of deceased donor recipients and 72.8% of living donor recipients. In unsensitized recipients and recipients overall (Figure 4, A, B, E, and F), UA-PD at HLA-A in deceased donor recipients produced the only cPRA increases not statistically distinguishable from those of HLA-DQ, effects conceivably attributable to the high population frequency of HLA-A2, which is present in close to half (48%) of US donors.²² Effects of HLA-DQ UA-PD relative to other UA-PD in previously sensitized recipients (cPRA 1–50, 51%–100%, Figure 4, C, D, G, and H) were less consistent, likely due to smaller sample sizes, although notably no effects were significantly greater than those of HLA-DQ. A potential contributor to these observations is that there are only seven DQ serologic specificities, the fewest of any HLA locus,²³ meaning that individuals with preexisting HLA-DQ unacceptable antigens may have proportionally fewer DQ antigens remaining to become unacceptable.

We analyzed the interaction between the effects of HLA-DR and HLA-DQ UA-PD on cPRA increases and demonstrated that the addition of a DR UA-PD to an existing DQ UA-PD resulted in only small changes in overall cPRA proportional to the uncertainty of the estimates (Supplemental Figures 2 and 3). This finding further supports the independent relationship of HLA-DQ UA-PD with recipient sensitization after graft loss. The summation of this observation with the overall findings of our study is that HLA-DQ UA-PD disqualify patients relisted for transplantation from a share of the US donor pool equal to or greater than UA-PD at any other HLA locus. This has implications in deceased donor kidney allocation, particularly in transplantation of younger patients with life expectancy greater than that of their allograft.

Racial and ethnic minority recipients, especially African American recipients, are more likely to receive HLA-mismatched kidneys,²⁴^,²⁵ to experience graft failure,²⁴ and to return to the waitlist highly sensitized.¹⁹^,²⁶ In this work, HLA-DQ mismatches were associated with significantly higher probabilities of UA-PD in African American deceased donor recipients compared with Hispanic and White recipients and for African American and Hispanic living donor recipients compared with White recipients (Figure 3). Although African American and Hispanic recipients in our cohort were more highly sensitized than White recipients after returning to the waitlist (Supplemental Table 1), we did not find any significant differences in cPRA increases with new DQ UA-PD between race and ethnicity groups (Figures 5 and 6). Overall, these results are important in the context of kidney allocation, in which the paradigm has been to de-emphasize HLA matching to increase access for underserved groups.²⁷^,²⁸ Our findings suggest that this strategy may expose recipients to unintended risks of developing DSAs and graft loss.

Our race and ethnicity findings come with caveats as illustrated by the demographic breakdown of the cohort (Supplemental Table 1). After graft failure, African American and Hispanic deceased donor recipients waited an average of 456 and 243 additional days before relisting, respectively, compared with White recipients. Medicaid insurance rates, a factor we have previously shown trends with poor health indicators,²⁹ were comparable between African American and White recipients, however, the share of Hispanic recipients with Medicaid insurance was 11.0% higher than White recipients. Although we controlled for several potential contributors to sensitization in our models, some of which were relatively well-balanced between race and ethnicity groups (i.e., pretransplantation cPRA), the potential existence of unidentified differences in care and socioeconomic factors necessitates a degree of caution in interpretation of our results.

Of the strengths of this work, we made conservative judgements to only include patients from the era of mandated molecular HLA typing, with no missing HLA data, who were transplanted in a time period with use of consistent immunosuppressive therapies.³⁰ Despite this, our novel method enabled an analysis one to two orders of magnitude larger than previous single-center studies of HLA-DQ mismatches and DSAs.

Study limitations include its retrospective design and use of registry data, in which potential confounders may not be recorded. Our analyses were reliant on low-resolution, serologic-equivalent HLA typing, in which multiple common HLA alleles are indistinguishable within antigenic groups. One hypothesis underlying this work is that certain donor-recipient HLA mismatches are likely more immunogenic than others⁷; however, we considered a mismatch-level analysis performed with antigen-level typing likely to implicate entire antigenic groups without identifying true culprit allelic mismatches. Subsequent studies using high-resolution typing should investigate the differential immunogenicity of HLA mismatches and their implications on transplantation equity given allelic distributions across donor and recipient races/ethnicities. Additionally, the resolution of our HLA data did not allow us to specifically delineate or account for cPRA increases attributable to cross-reactive antigens. Our study focuses on individuals relisted for transplant, who may not be representative of all recipients experiencing graft loss. Our race and ethnicity analyses use SRTR classifications which are based on patient self-declaration and do not distinguish between concepts of race and ethnicity.³¹ Therefore, overlap may exist between patients classified as Hispanic versus African American and White.

Conclusions

This is the first study applying registry data to evaluate the effect of HLA mismatches on generation of DSAs and recipient sensitization after renal graft failure. HLA-DQ mismatches have the highest probability of producing unacceptable antigens corresponding to previous donor typing after graft loss and these DQ UA-PD result in cPRA increases greater than or equal to any other HLA locus. The association between DQ mismatches and UA-PD is most pronounced in African American and Hispanic recipients compared with White recipients. These findings expand the existing literature demonstrating that HLA-DQ alloantibodies are the most pathogenic and suggest a need to consider the effects of HLA-DQ in kidney allocation.

Disclosures

D. Isaacson reports consultancy fees from L&E Research. V. Kosmoliaptsis reports patents or royalties from University of Cambridge. J.D. Schold reports both consultancy fees and honoraria from eGenesis, NephroSant, and Sanofi; reports research funding from OneLegacy Foundation; has an advisory or leadership role with Bristol Myers Squibb (Data Safety Monitoring Board member) and Lifebanc (an organ procurement organization, Board of Directors); and is on the speakers bureau for Sanofi. A.R. Tambur reports consultancy fees from Sanofi; reports honoraria from Thermo Fisher/One Lambda; and has an advisory or leadership role with Sanofi. All remaining authors have nothing to disclose.

Funding

This work was supported in part by a generous contribution from The Paul I. Terasaki Memorial Research Fund. V. Kosmoliaptsis acknowledges funding from a National Institute for Health Research fellowship (PDF-2016-09-065). A.R. Tambur and V. Kosmoliaptsis are Paul I. Terasaki Scholars.

Supplementary Material

Supplemental Data

ASN.2022030296SupplementaryData.pdf^{(1.2MB, pdf)}

Acknowledgments

The data reported here have been supplied by the Hennepin Healthcare Research Institute as the contractor for the SRTR. The interpretation and reporting of these data are the responsibility of the authors and in no way should be seen as an official policy of or interpretation by the SRTR or the US Government.

Footnotes

Published online ahead of print. Publication date available at www.jasn.org.

Author Contributions

D. Isaacson, M.W. Gmeiner, V. Kosmoliaptsis, and A.R. Tambur were responsible for project administration and resources; D. Isaacson and M.W. Gmeiner were responsible for software; D. Isaacson, J.D. Schold, M.W. Gmeiner, V. Kosmoliaptsis, and A.R. Tambur were responsible for supervision; D. Isaacson, V. Kosmoliaptsis, J.D. Schold, and A.R. Tambur were responsible for visualization; V. Kosmoliaptsis and A.R. Tambur were responsible for funding acquisition; and all authors conceptualized the study, were responsible for data curation, formal analysis, investigation, and methodology, wrote the original draft, and reviewed and edited the manuscript.

Data Sharing Statement

The data that support the findings of this study are available from the SRTR but restrictions apply to the availability of these data, which were used under license for this study, and so are not publicly available. Data are, however, available from the authors upon reasonable request and with permission of the SRTR.

Supplemental Material

This article contains the following supplemental material online at http://jasn.asnjournals.org/lookup/suppl/doi:10.1681/ASN.2022030296/-/DCSupplemental.

Supplemental Table 1. Demographics and relevant characteristics stratified by deceased versus living donor category of the initial failed graft and recipient race and ethnicity.

Supplemental Table 2. Regression analysis to determine the relationship between UA-PD at each HLA locus and changes in cPRA after relisting (Figure 4), stratified by failed (A) deceased and (B) living donor kidney and by pretransplantation cPRA (0%, 1%–50%, 51%–100%).

Supplemental Table 3. Regression analyses to determine the effects of HLA mismatches (0–2) on the probabilities of UA-PD (0–1.000), augmented to evaluate the interactions between the effects of HLA-DR and HLA-DQ. The interaction term “DR & DQ Interaction” estimates the change in probability of an UA-PD with each additional HLA-DR mismatch in the presence of an HLA-DQ mismatch, or with each additional HLA-DQ mismatch in the presence of an HLA-DR mismatch.

Supplemental Table 4. Regression analyses to determine the effects of new UA-PD on cPRA increases (0–1.000) after failed transplant and relisting, augmented to evaluate the interaction between the effects of HLA-DR and HLA-DQ. The interaction term “DR & DQ Interaction” estimates the change in cPRA given an additional HLA-DR UA-PD in the presence of an HLA-DQ UA-PD.

Supplemental Figure 1. Scenarios applying regression analyses from Supplemental Table 3 to demonstrate interactions between the effects of HLA-DR and HLA-DQ mismatches (MM) on the probabilities of being relisted with new HLA-DR and HLA-DQ UA-PD, compared to recipients with no HLA-DR or DQ mismatches (0%–100%).

Supplemental Figure 2. Scenarios applying regression analyses from Supplemental Table 4 to demonstrate interactions between the effects of HLA-DR and HLA-DQ UA-PD on cPRA increases (0%–100%) in prior deceased donor recipients with pretransplant cPRA of 0% (A) or 1%–50% (B), compared to recipients relisted with no HLA-DR or DQ UA-PD.

Supplementa l Figure 3. Scenarios applying regression analyses from Supplemental Table 4 to demonstrate interactions between the effects of HLA-DR and HLA-DQ UA-PD on cPRA increases (0%–100%) in prior living donor recipients with pretransplant cPRA of 0% (A) or 1%–50% (B), compared to recipients relisted with no HLA-DR or DQ UA-PD.

References

1.Schold JD, Buccini LD, Goldfarb DA, Flechner SM, Poggio ED, Sehgal AR: Association between kidney transplant center performance and the survival benefit of transplantation versus dialysis. Clin J Am Soc Nephrol 9: 1773–1780, 2014 [DOI] [PMC free article] [PubMed] [Google Scholar]
2.Rana A, Gruessner A, Agopian VG, Khalpey Z, Riaz IB, Kaplan B, et al. : Survival benefit of solid-organ transplant in the United States. JAMA Surg 150: 252–259, 2015 [DOI] [PubMed] [Google Scholar]
3.Hart A, Lentine KL, Smith JM, Miller JM, Skeans MA, Prentice M, et al. : OPTN/SRTR 2019 Annual Data Report: Kidney. Am J Transplant 21[Suppl 2]: 21–137, 2021 [DOI] [PubMed] [Google Scholar]
4.Zhang R: Donor-specific antibodies in kidney transplant recipients. Clin J Am Soc Nephrol 13: 182–192, 2018 [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Lee PC, Zhu L, Terasaki PI, Everly MJ: HLA-specific antibodies developed in the first year posttransplant are predictive of chronic rejection and renal graft loss. Transplantation 88: 568–574, 2009 [DOI] [PubMed] [Google Scholar]
6.Zhu L, Lee PC, Everly MJ, Terasaki PI: Detailed examination of HLA antibody development on renal allograft failure and function. Clin Transpl: 171–187, 2008 [PubMed] [Google Scholar]
7.Tambur AR, McDowell H, Hod-Dvorai R, Abundis MAC, Pinelli DF: The quest to decipher HLA immunogenicity: Telling friend from foe. Am J Transplant 19: 2910–2925, 2019 [DOI] [PubMed] [Google Scholar]
8.Tambur AR: Human leukocyte antigen matching in organ transplantation: What we know and how can we make it better (revisiting the past, improving the future). Curr Opin Organ Transplant 23: 470–476, 2018 [DOI] [PubMed] [Google Scholar]
9.Tambur AR: HLA-DQ antibodies: Are they real? Are they relevant? Why so many? Curr Opin Organ Transplant 21: 441–446, 2016 [DOI] [PubMed] [Google Scholar]
10.Kosmoliaptsis V, Gjorgjimajkoska O, Sharples LD, Chaudhry AN, Chatzizacharias N, Peacock S, et al. : Impact of donor mismatches at individual HLA-A, -B, -C, -DR, and -DQ loci on the development of HLA-specific antibodies in patients listed for repeat renal transplantation. Kidney Int 86: 1039–1048, 2014 [DOI] [PubMed] [Google Scholar]
11.Everly MJ, Rebellato LM, Haisch CE, Ozawa M, Parker K, Briley KP, et al. : Incidence and impact of de novo donor-specific alloantibody in primary renal allografts. Transplantation 95: 410–417, 2013 [DOI] [PubMed] [Google Scholar]
12.Organ Procurement and Transplantation Network : Kidney allocation system (KAS). Available at https://optn.transplant.hrsa.gov/learn/professional-education/kidney-allocation-system/. Accessed February 12, 2022
13.Freedman BI, Thacker LR, Heise ER, Adams PL: HLA-DQ matching in cadaveric renal transplantation. Clin Transplant 11: 480–484, 1997 [PubMed] [Google Scholar]
14.Sasaki N, Idica A: The HLA-matching effect in different cohorts of kidney transplant recipients: 10 years later. Clin Transpl: 261–282, 2010 [PubMed] [Google Scholar]
15.Lim WH, Chapman JR, Coates PT, Lewis JR, Russ GR, Watson N, et al. : HLA-DQ mismatches and rejection in kidney transplant recipients. Clin J Am Soc Nephrol 11: 875–883, 2016 [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Leeaphorn N, Pena JRA, Thamcharoen N, Khankin EV, Pavlakis M, Cardarelli F: HLA-DQ mismatching and kidney transplant outcomes. Clin J Am Soc Nephrol 13: 763–771, 2018 [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Engen RM, Jedraszko AM, Conciatori MA, Tambur AR: Substituting imputation of HLA antigens for high-resolution HLA typing: Evaluation of a multiethnic population and implications for clinical decision making in transplantation. Am J Transplant 21: 344–352, 2021 [DOI] [PubMed] [Google Scholar]
18.Flomenberg N, Baxter-Lowe LA, Confer D, Fernandez-Vina M, Filipovich A, Horowitz M, et al. : Impact of HLA class I and class II high-resolution matching on outcomes of unrelated donor bone marrow transplantation: HLA-C mismatching is associated with a strong adverse effect on transplantation outcome. Blood 104: 1923–1930, 2004 [DOI] [PubMed] [Google Scholar]
19.Tambur AR, Kosmoliaptsis V, Claas FHJ, Mannon RB, Nickerson P, Naesens M: Significance of HLA-DQ in kidney transplantation: Time to reevaluate human leukocyte antigen-matching priorities to improve transplant outcomes? An expert review and recommendations. Kidney Int 100: 1012–1022, 2021 [DOI] [PubMed] [Google Scholar]
20.Knoll G, Campbell P, Chassé M, Fergusson D, Ramsay T, Karnabi P, et al. : Immunosuppressant medication use in patients with kidney allograft failure: A prospective multicenter Canadian cohort study. J Am Soc Nephrol 33: 1182–1192, 2022 [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Süsal C, Zeier M: Is there a need for additional DQ matching? Clin J Am Soc Nephrol 13: 683–684, 2018 [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Montgomery RA, Tatapudi VS, Leffell MS, Zachary AA: HLA in transplantation. Nat Rev Nephrol 14: 558–570, 2018 [DOI] [PubMed] [Google Scholar]
23.Tambur AR, Leventhal JR, Walsh RC, Zitzner JR, Friedewald JJ: HLA-DQ barrier: Effects on cPRA calculations. Transplantation 96: 1065–1072, 2013 [DOI] [PubMed] [Google Scholar]
24.Taber DJ, Gebregziabher M, Hunt KJ, Srinivas T, Chavin KD, Baliga PK, et al. : Twenty years of evolving trends in racial disparities for adult kidney transplant recipients. Kidney Int 90: 878–887, 2016 [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Harding K, Mersha TB, Pham PT, Waterman AD, Webb FA, Vassalotti JA, et al. : Health disparities in kidney transplantation for African Americans. Am J Nephrol 46: 165–175, 2017 [DOI] [PMC free article] [PubMed] [Google Scholar]
26.Meier-Kriesche HU, Scornik JC, Susskind B, Rehman S, Schold JD: A lifetime versus a graft life approach redefines the importance of HLA matching in kidney transplant patients. Transplantation 88: 23–29, 2009 [DOI] [PubMed] [Google Scholar]
27.Roberts JP, Wolfe RA, Bragg-Gresham JL, Rush SH, Wynn JJ, Distant DA, et al. : Effect of changing the priority for HLA matching on the rates and outcomes of kidney transplantation in minority groups. N Engl J Med 350: 545–551, 2004 [DOI] [PubMed] [Google Scholar]
28.Hall EC, Massie AB, James NT, Garonzik Wang JM, Montgomery RA, Berger JC, et al. : Effect of eliminating priority points for HLA-B matching on racial disparities in kidney transplant rates. Am J Kidney Dis 58: 813–816, 2011 [DOI] [PubMed] [Google Scholar]
29.Schold JD, Buccini LD, Kattan MW, Goldfarb DA, Flechner SM, Srinivas TR, et al. : The association of community health indicators with outcomes for kidney transplant recipients in the United States. Arch Surg 147: 520–526, 2012 [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Lim MA, Kohli J, Bloom RD: Immunosuppression for kidney transplantation: Where are we now and where are we going? Transplant Rev (Orlando) 31: 10–17, 2017 [DOI] [PubMed] [Google Scholar]
31.Scientific Registry of Transplant Recipients : Technical methods for the program-specific reports: Appendix A: Definitions of candidate, recipient and donor characteristics. Available at: https://www.srtr.org/about-the-data/technical-methods-for-the-program-specific-reports/. Accessed December 21, 2021

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental Data

ASN.2022030296SupplementaryData.pdf^{(1.2MB, pdf)}

[B1] 1.Schold JD, Buccini LD, Goldfarb DA, Flechner SM, Poggio ED, Sehgal AR: Association between kidney transplant center performance and the survival benefit of transplantation versus dialysis. Clin J Am Soc Nephrol 9: 1773–1780, 2014 [DOI] [PMC free article] [PubMed] [Google Scholar]

[B2] 2.Rana A, Gruessner A, Agopian VG, Khalpey Z, Riaz IB, Kaplan B, et al. : Survival benefit of solid-organ transplant in the United States. JAMA Surg 150: 252–259, 2015 [DOI] [PubMed] [Google Scholar]

[B3] 3.Hart A, Lentine KL, Smith JM, Miller JM, Skeans MA, Prentice M, et al. : OPTN/SRTR 2019 Annual Data Report: Kidney. Am J Transplant 21[Suppl 2]: 21–137, 2021 [DOI] [PubMed] [Google Scholar]

[B4] 4.Zhang R: Donor-specific antibodies in kidney transplant recipients. Clin J Am Soc Nephrol 13: 182–192, 2018 [DOI] [PMC free article] [PubMed] [Google Scholar]

[B5] 5.Lee PC, Zhu L, Terasaki PI, Everly MJ: HLA-specific antibodies developed in the first year posttransplant are predictive of chronic rejection and renal graft loss. Transplantation 88: 568–574, 2009 [DOI] [PubMed] [Google Scholar]

[B6] 6.Zhu L, Lee PC, Everly MJ, Terasaki PI: Detailed examination of HLA antibody development on renal allograft failure and function. Clin Transpl: 171–187, 2008 [PubMed] [Google Scholar]

[B7] 7.Tambur AR, McDowell H, Hod-Dvorai R, Abundis MAC, Pinelli DF: The quest to decipher HLA immunogenicity: Telling friend from foe. Am J Transplant 19: 2910–2925, 2019 [DOI] [PubMed] [Google Scholar]

[B8] 8.Tambur AR: Human leukocyte antigen matching in organ transplantation: What we know and how can we make it better (revisiting the past, improving the future). Curr Opin Organ Transplant 23: 470–476, 2018 [DOI] [PubMed] [Google Scholar]

[B9] 9.Tambur AR: HLA-DQ antibodies: Are they real? Are they relevant? Why so many? Curr Opin Organ Transplant 21: 441–446, 2016 [DOI] [PubMed] [Google Scholar]

[B10] 10.Kosmoliaptsis V, Gjorgjimajkoska O, Sharples LD, Chaudhry AN, Chatzizacharias N, Peacock S, et al. : Impact of donor mismatches at individual HLA-A, -B, -C, -DR, and -DQ loci on the development of HLA-specific antibodies in patients listed for repeat renal transplantation. Kidney Int 86: 1039–1048, 2014 [DOI] [PubMed] [Google Scholar]

[B11] 11.Everly MJ, Rebellato LM, Haisch CE, Ozawa M, Parker K, Briley KP, et al. : Incidence and impact of de novo donor-specific alloantibody in primary renal allografts. Transplantation 95: 410–417, 2013 [DOI] [PubMed] [Google Scholar]

[B12] 12.Organ Procurement and Transplantation Network : Kidney allocation system (KAS). Available at https://optn.transplant.hrsa.gov/learn/professional-education/kidney-allocation-system/. Accessed February 12, 2022

[B13] 13.Freedman BI, Thacker LR, Heise ER, Adams PL: HLA-DQ matching in cadaveric renal transplantation. Clin Transplant 11: 480–484, 1997 [PubMed] [Google Scholar]

[B14] 14.Sasaki N, Idica A: The HLA-matching effect in different cohorts of kidney transplant recipients: 10 years later. Clin Transpl: 261–282, 2010 [PubMed] [Google Scholar]

[B15] 15.Lim WH, Chapman JR, Coates PT, Lewis JR, Russ GR, Watson N, et al. : HLA-DQ mismatches and rejection in kidney transplant recipients. Clin J Am Soc Nephrol 11: 875–883, 2016 [DOI] [PMC free article] [PubMed] [Google Scholar]

[B16] 16.Leeaphorn N, Pena JRA, Thamcharoen N, Khankin EV, Pavlakis M, Cardarelli F: HLA-DQ mismatching and kidney transplant outcomes. Clin J Am Soc Nephrol 13: 763–771, 2018 [DOI] [PMC free article] [PubMed] [Google Scholar]

[B17] 17.Engen RM, Jedraszko AM, Conciatori MA, Tambur AR: Substituting imputation of HLA antigens for high-resolution HLA typing: Evaluation of a multiethnic population and implications for clinical decision making in transplantation. Am J Transplant 21: 344–352, 2021 [DOI] [PubMed] [Google Scholar]

[B18] 18.Flomenberg N, Baxter-Lowe LA, Confer D, Fernandez-Vina M, Filipovich A, Horowitz M, et al. : Impact of HLA class I and class II high-resolution matching on outcomes of unrelated donor bone marrow transplantation: HLA-C mismatching is associated with a strong adverse effect on transplantation outcome. Blood 104: 1923–1930, 2004 [DOI] [PubMed] [Google Scholar]

[B19] 19.Tambur AR, Kosmoliaptsis V, Claas FHJ, Mannon RB, Nickerson P, Naesens M: Significance of HLA-DQ in kidney transplantation: Time to reevaluate human leukocyte antigen-matching priorities to improve transplant outcomes? An expert review and recommendations. Kidney Int 100: 1012–1022, 2021 [DOI] [PubMed] [Google Scholar]

[B20] 20.Knoll G, Campbell P, Chassé M, Fergusson D, Ramsay T, Karnabi P, et al. : Immunosuppressant medication use in patients with kidney allograft failure: A prospective multicenter Canadian cohort study. J Am Soc Nephrol 33: 1182–1192, 2022 [DOI] [PMC free article] [PubMed] [Google Scholar]

[B21] 21.Süsal C, Zeier M: Is there a need for additional DQ matching? Clin J Am Soc Nephrol 13: 683–684, 2018 [DOI] [PMC free article] [PubMed] [Google Scholar]

[B22] 22.Montgomery RA, Tatapudi VS, Leffell MS, Zachary AA: HLA in transplantation. Nat Rev Nephrol 14: 558–570, 2018 [DOI] [PubMed] [Google Scholar]

[B23] 23.Tambur AR, Leventhal JR, Walsh RC, Zitzner JR, Friedewald JJ: HLA-DQ barrier: Effects on cPRA calculations. Transplantation 96: 1065–1072, 2013 [DOI] [PubMed] [Google Scholar]

[B24] 24.Taber DJ, Gebregziabher M, Hunt KJ, Srinivas T, Chavin KD, Baliga PK, et al. : Twenty years of evolving trends in racial disparities for adult kidney transplant recipients. Kidney Int 90: 878–887, 2016 [DOI] [PMC free article] [PubMed] [Google Scholar]

[B25] 25.Harding K, Mersha TB, Pham PT, Waterman AD, Webb FA, Vassalotti JA, et al. : Health disparities in kidney transplantation for African Americans. Am J Nephrol 46: 165–175, 2017 [DOI] [PMC free article] [PubMed] [Google Scholar]

[B26] 26.Meier-Kriesche HU, Scornik JC, Susskind B, Rehman S, Schold JD: A lifetime versus a graft life approach redefines the importance of HLA matching in kidney transplant patients. Transplantation 88: 23–29, 2009 [DOI] [PubMed] [Google Scholar]

[B27] 27.Roberts JP, Wolfe RA, Bragg-Gresham JL, Rush SH, Wynn JJ, Distant DA, et al. : Effect of changing the priority for HLA matching on the rates and outcomes of kidney transplantation in minority groups. N Engl J Med 350: 545–551, 2004 [DOI] [PubMed] [Google Scholar]

[B28] 28.Hall EC, Massie AB, James NT, Garonzik Wang JM, Montgomery RA, Berger JC, et al. : Effect of eliminating priority points for HLA-B matching on racial disparities in kidney transplant rates. Am J Kidney Dis 58: 813–816, 2011 [DOI] [PubMed] [Google Scholar]

[B29] 29.Schold JD, Buccini LD, Kattan MW, Goldfarb DA, Flechner SM, Srinivas TR, et al. : The association of community health indicators with outcomes for kidney transplant recipients in the United States. Arch Surg 147: 520–526, 2012 [DOI] [PMC free article] [PubMed] [Google Scholar]

[B30] 30.Lim MA, Kohli J, Bloom RD: Immunosuppression for kidney transplantation: Where are we now and where are we going? Transplant Rev (Orlando) 31: 10–17, 2017 [DOI] [PubMed] [Google Scholar]

[B31] 31.Scientific Registry of Transplant Recipients : Technical methods for the program-specific reports: Appendix A: Definitions of candidate, recipient and donor characteristics. Available at: https://www.srtr.org/about-the-data/technical-methods-for-the-program-specific-reports/. Accessed December 21, 2021

PERMALINK

HLA-DQ Mismatches Lead to More Unacceptable Antigens, Greater Sensitization, and Increased Disparities in Repeat Transplant Candidates

Dylan Isaacson

Jesse D Schold

Michael W Gmeiner

Hannah C Copley

Vasilis Kosmoliaptsis

Anat R Tambur

Significance Statement

Visual Abstract

Abstract

Background

Methods

Results

Conclusions

Methods

Institutional Review Board

Study Population

Data Collection

Outcomes

Statistical Analyses

Results

Study Population

Figure 1.

Baseline Characteristics

Table 1.

Probabilities of New Unacceptable Antigens Corresponding to Previous Donor Typing

Figure 2.

Probabilities of New Unacceptable Antigens by Recipient Race and Ethnicity

Figure 3.

HLA Unacceptable Antigens and Increases in cPRA

Figure 4.

HLA Unacceptable Antigens and Increases in cPRA by Recipient Race and Ethnicity

Figure 5.

Figure 6.

Interactions of HLA-DR/DQ on Unacceptable Antigen Probabilities and cPRA Increases

Discussion

Conclusions

Disclosures

Funding

Supplementary Material

Acknowledgments

Footnotes

Author Contributions

Data Sharing Statement

Supplemental Material

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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