Aim The OPTN recently implemented a new process wherein renal transplant candidates with cPRA values of 99% and 100% are given regional and national priority, respectively, for deceased donor (DD) ...kidneys. While the majority of these highly sensitized patients have HLA-DP antibodies, allocation offers frequently occur without donor HLA-DP typing. Furthermore, information regarding the frequency and distribution of HLA-DP antigens is not readily available. Herein we report the frequency and distribution of HLA-DP antigens in 1168 DDs typed over the past three years. Methods HLA-DPB1* typing was performed by SSO, SSP (One Lambda, Thermal-Fisher) or RT-PCR (Linkage Biosciences). Results Donors were 58.9% white, 32.4% black, 7.3% Hispanic and 1.4% API. As shown below, the frequency and distribution of HLA-DPB1 antigens varied significantly by race. For example, HLA-DPB1*04:01 is seen in 64.6% of whites and 16.2% of blacks while HLA-DPB1*01:01 is in 53.4% of black donors and only 9.1% of whites. Some HLA-DPB1* alleles appear racially restricted; e.g., HLA-DPB1*10:01 was observed in white and Hispanic but not black donors, while HLA-DPB1*85:01 was seen only in black donors. Multiple HLA-DPB1* alleles with a frequency of ⩾1% are not represented on any single antigen bead (SAB) products used to detect HLA antibodies. In contrast, SAB manufacturers allotted up to three beads for HLA-DPB1* 28:01, an allele not observed in any of the 1168 donors in this study. Conclusions OPO laboratories do not yet uniformly perform HLA-DP typing of deceased donors. In the absence of HLA-DP typing information, frequency tables as presented here can aid in the decision process of whether to accept/reject offers for patients with HLA-DPB1* antibodies. Hopefully, these data will stimulate bead manufacturers to provide SAB targets that more accurately reflect donor antigen distribution.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Aim “Interfering factors” mask the presence of HLA antibodies detected in solid phase assays, especially in highly sensitized patients. In this study, we evaluated the effect of EDTA on HLA antibody ...detection using sera from 20 wait list patients (each with a cPRA of > 80%). Methods Briefly, 5ul of a 6% solution of EDTA was added to 95ul of patient sera. Paired samples (untreated vs EDTA treated) were then tested on FlowPRA® and LABScreen® Single Antigen Beads (SAB) for class I and II HLA reactivity. Results Among 20 patient sera tested by SABs (untreated or EDTA treated), HLA antibody profiles were identical in 7/20 paired samples and significantly different in 13. In 4/13 samples, antibody specificities detected at moderate levels (2000-7000 MFI) without EDTA increased to >19,000 MFI with EDTA treatment. In 9/13 sera, antibody specificities not detectable in untreated sera (0 MFI) presented with MFI values ranging from 18,000-25,000 following treatment with EDTA. When one such serum was crossmatched with informative HLA-A2 positive target cells (i.e., no other unacceptable antigens expressed), T and B cell crossmatches were strongly positive (>300,000 MESFs) with EDTA treated or untreated sera. Surprisingly, all sera, with or without EDTA treatment, had identical staining patterns by FlowPRA®. Conclusions These findings demonstrate that EDTA sensitive interfering factors can mask the detection of HLA antibodies that result in strongly positive crossmatches. While the untreated serum reported here was unequivocally vXM negative with the selected HLA-A2 positive target cells, the actual crossmatch against these cells was strongly positive. Interestingly, the FlowPRA® assay does not appear to be affected by these factors. As the transplant community embraces virtual crossmatching in lieu of physical crossmatching, sera from highly sensitized patients should be treated with EDTA (or other such approaches) to unmask HLA antibodies not detectable by SABs due to “interfering factors.”
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
4.
68-P McRacken, Tracy T; Spraggins, Cynthia M; Gebel, Howard M ...
Human immunology,
10/2012, Volume:
73
Journal Article
Peer reviewed
Aim Requests for Post transplant monitoring of solid organ transplant recipients is on the increase. Methods for monitoring must be robust and capable of detecting all potential DSAs. One renal and ...one cardiac recipient, transplanted in 2005 and 2008 respectively, were tested for DSA. Both patients were devoid of HLA Class II antibody at the time of transplant. Methods Post transplant DSA assessments were performed on both patients using LabScreen single antigen bead assays (One Lambda, Inc). Testing for both patients was “for cause”. Interestingly, both patients presented with de novo Class II antibodies. No obvious DSAs were identified for one patient and the second patient showed a possible DSA (only 2 of 5 DQ7 beads positive). Recent studies with pre-transplant sera have demonstrated that IgG DSA may be masked by “interfering factors” such as C1q and/or IgM. Hence, we investigated this possibility. Results Repeat testing of heat-inactivated serum from both patients revealed de novo DSA (DQB1∗ 03:01) with MFI values of approx. 15,000 - 20,000. For patient 1, all DQ7 beads became strongly positive. For patient 2, all 5 DQ7 beads were now strongly positive. Interestingly, the non-DSA Class II specificities were still detectable and at similar MFI levels (12,000-21,000) compared to the untreated sample. In supplemental studies, we diluted untreated patient serum (1:10) which also led to the unmasking of DQB1∗ 03:01 antibody. Conclusions Collectively, this study demonstrates that “interfering factors” can also mask the detection of donor specific antibodies during post-transplant monitoring. There are numerous times when patients present with symptoms suspicious of antibody mediated rejection but have no detectable DSA although some patients may display 3rd party HLA specificities. We suggest that sera from such patients be routinely treated to eliminate potential interfering factors that can mask the identification of DSA.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Requests for Post transplant monitoring of solid organ transplant recipients is on the increase. Methods for monitoring must be robust and capable of detecting all potential DSAs. One renal and one ...cardiac recipient, transplanted in 2005 and 2008 respectively, were tested for DSA. Both patients were devoid of HLA Class II antibody at the time of transplant.
Post transplant DSA assessments were performed on both patients using LabScreen single antigen bead assays (One Lambda, Inc). Testing for both patients was “for cause”. Interestingly, both patients presented with de novo Class II antibodies. No obvious DSAs were identified for one patient and the second patient showed a possible DSA (only 2 of 5 DQ7 beads positive). Recent studies with pre-transplant sera have demonstrated that IgG DSA may be masked by “interfering factors” such as C1q and/or IgM. Hence, we investigated this possibility.
Repeat testing of heat-inactivated serum from both patients revealed de novo DSA (DQB1∗03:01) with MFI values of approx. 15,000 - 20,000. For patient 1, all DQ7 beads became strongly positive. For patient 2, all 5 DQ7 beads were now strongly positive. Interestingly, the non-DSA Class II specificities were still detectable and at similar MFI levels (12,000-21,000) compared to the untreated sample. In supplemental studies, we diluted untreated patient serum (1:10) which also led to the unmasking of DQB1∗03:01 antibody.
Collectively, this study demonstrates that “interfering factors” can also mask the detection of donor specific antibodies during post-transplant monitoring. There are numerous times when patients present with symptoms suspicious of antibody mediated rejection but have no detectable DSA although some patients may display 3rd party HLA specificities. We suggest that sera from such patients be routinely treated to eliminate potential interfering factors that can mask the identification of DSA.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
“Interfering factors” mask the presence of HLA antibodies detected in solid phase assays, especially in highly sensitized patients. In this study, we evaluated the effect of EDTA on HLA antibody ...detection using sera from 20 wait list patients (each with a cPRA of >80%).
Briefly, 5ul of a 6% solution of EDTA was added to 95ul of patient sera. Paired samples (untreated vs EDTA treated) were then tested on FlowPRA® and LABScreen® Single Antigen Beads (SAB) for class I and II HLA reactivity.
Among 20 patient sera tested by SABs (untreated or EDTA treated), HLA antibody profiles were identical in 7/20 paired samples and significantly different in 13. In 4/13 samples, antibody specificities detected at moderate levels (2000-7000 MFI) without EDTA increased to >19,000 MFI with EDTA treatment. In 9/13 sera, antibody specificities not detectable in untreated sera (0 MFI) presented with MFI values ranging from 18,000-25,000 following treatment with EDTA. When one such serum was crossmatched with informative HLA-A2 positive target cells (i.e., no other unacceptable antigens expressed), T and B cell crossmatches were strongly positive (>300,000 MESFs) with EDTA treated or untreated sera. Surprisingly, all sera, with or without EDTA treatment, had identical staining patterns by FlowPRA®.
These findings demonstrate that EDTA sensitive interfering factors can mask the detection of HLA antibodies that result in strongly positive crossmatches. While the untreated serum reported here was unequivocally vXM negative with the selected HLA-A2 positive target cells, the actual crossmatch against these cells was strongly positive. Interestingly, the FlowPRA® assay does not appear to be affected by these factors. As the transplant community embraces virtual crossmatching in lieu of physical crossmatching, sera from highly sensitized patients should be treated with EDTA (or other such approaches) to unmask HLA antibodies not detectable by SABs due to “interfering factors.”
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
The presence of HLA antibodies in highly sensitized heart transplant candidates is a barrier that can prevent these individuals from receiving a lifesaving transplant. In an effort to downregulate ...their HLA antibodies, many candidates are treated with high-dose intravenous immunoglobulin. While this therapeutic approach to downregulation is successful in some subjects, others show no response. In this study, we attempted to identify factors associated with the successful downregulation of HLA antibodies in highly sensitized candidates eligible for heart transplantation.
Fifteen heart transplant candidates (ages 25–66) in this retrospective chart review had calculated panel reactive antibody (cPRA) levels ranging from 41 to 100%. In an effort to downregulate HLA antibodies, all subjects received monthly IVIG (2g/kg; number of doses ranged from 2 to 25). Data evaluated included gender, age, race, BMI, ventricular assist device (VAD) type, desensitization regimen, PRA levels, antibodies present prior to and after IVIG, as well as history of blood transfusions, pregnancies, and previous transplants. Patients were considered responders to IVIG therapy if their original cPRA level decreased by ⩾50%, and non-responders if the decrease in cPRA was <50%.
Patients included in this study had all received a VAD with a mean cPRA of 79.6 prior to IVIG treatment. IVIG efficacy was demonstrated by lower cPRA values (p<0.001) and specific HLA antibodies (p=0.005) in the responder group. Compared with the non-responder group, responders were more likely to be male (p=0.036) and females without previous pregnancies (p=0.036). Trends towards responsivenss were also seen with white race (0.106) and greater number of IVIG doses (p=0.085). Display omitted
IVIG is an appropriate treatment for highly sensitized patients eligible for heart transplant with patient-specific characteristics including male gender and pregnancy status, making certain patients more responsive to therapy than others.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
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