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BackgroundA T cell positive and B cell negative (T+B-) flow cytometry crossmatch (FCXM) result remains a conundrum since HLA-class I antigens are expressed on both T and B cells. We investigated the frequency, HLA specificity of the antibodies and mechanisms for the T+B- FCXM result.MethodsWe analyzed 3073 clinical FCXM tests performed in an American Society of Histocompatibility and Immunogenetics accredited histocompatibility laboratory. The sera associated with the T+B- FCXM were also tested for donor HLA IgG antibodies using LABScreen™ single antigen assays.ResultsAmong the 3073 FCXM tests, 1963 were T-B-, 811 were T-B+, 274 were T+B+, and 25 were T+B-. IgG antibodies directed at donor HLA-A, B, or Cw locus determined antigens (DSA) were identified in all 25 sera and the summed mean fluorescence intensity (MFI) of DSA ranged from 212 to 53,187. Correlational analyses identified a significant association between the summed MFI of class I DSA, and the median channel fluorescence (MCF) of T cells treated with the recipient serum (Spearman rank correlation, rs=0.34, P=0.05) but not with the MCF of B cells (rs=0.23, P=0.24). We identified that differential binding of anti-HLA antibodies to T cells and B cells and the B cell channel shift threshold used to classify a B cell FCXM are potential contributors to a T+B- FCXM result.ConclusionsOur analysis of 3073 FCXM, in addition to demonstrating that HLA antibodies directed at HLA-A, B or Cw locus are associated with a T+B- result, identified mechanisms for the surprising T+B- FCXM result.

Aim Emerging data suggest that DSA development is a frequent complication post BKV replication, and most DSA are directed against donor HLA-DQ. In the current investigation, we quantified DQ epitope mismatches between the recipient and donor in individuals with BKVN diagnosis and investigated the association between DQ epitope load and development of DSA. Methods In this pilot study, using the most probable 4-digit HLA typings, we investigated epitope mismatches in individuals who developed DSA post BKVN diagnosis compared to those who did not and correlated them to DSA development and graft dysfunction defined as an increase in serum creatinine by > 0.5 mg/dL at 12 months post-BKVN diagnosis. We had SSOP based intermediate HLA typing available for recipients and donors in 13 recipients who developed BKVN confirmed by renal allograft biopsy. Of the 13 recipients, 2 were excluded: 1 for early graft loss and 1 who had zero DQ mismatches. None of the 11 recipients with BKVN diagnosis had a positive XM or DSA at time of transplantation. Results Time from kidney transplantation to BKVN diagnosis was 8.5 ± 5.1 months. Serum creatinine at time of diagnosis was 1.78 ± 0.56. Of the 11 with BKVN, 36% developed de novo DSA. All DSAs were directed against DQ mismatches. Time from BKVN diagnosis to DSA development was 5.5 ± 2.3 months. Table below lists the epitope mismatch number at each locus. Of the 4 patients with de novo DSA, 75% experienced graft dysfunction during the 12 months post BKVN and of the 7 patients without de novo DSA, 29% experienced graft dysfunction by 12 months. Our data demonstrated that the most frequent DQ epitope mismatches in those with de novo DSA were 52PL3, 45EV, 52PQ2, and 52PR. Conclusions In our pilot study, the epitope load was not different between BKVN patients who developed or did not develop de novo DSA. The most frequent target of de novo antibodies were DQ locus mismatched epitopes. Knowledge of epitope targets of de novo DSA in patients with BKVN may facilitate targeted therapies and improve kidney allograft outcomes. Download : Download high-res image (148KB) Download : Download full-size image

Aim Luminex Single Antigen bead assay (LSAB) derived mean fluorescence intensity (MFI) values of anti-HLA antibodies directed at the potential donor’s HLA are the primary parameter used in the virtual crossmatch to predict physical crossmatch (XM) outcome. We aimed to develop statistically validated LSAB MFI cutpoints for predicting CDC XM and FCXM results. Methods We leveraged the ASHI proficiency testing (PT) 80% consensus results of 7156 T FCXM, 6758 B FCXM, 2917 T CDC XM and 2233 B CDC XM as the reference results to investigate whether LSAB MFI of IgG anti-HLA antibodies predict validated physical XM results. LSAB MFI was determined in our laboratory using One Lambda Single Antigen HLA Class I and Class II beads. The 80% consensus results are from 8 consecutive challenges during 2013 to 2016, and 107 laboratories across USA tested sera and HLA typed cells distributed by ASHI, and reported the results to ASHI for assessment of the laboratory’s proficiency. Data analysis included: summing of MFI of IgG antibodies directed at HLA-A, B and C for investigating their association with T FCXM and T CDC XM results; summing of MFI of antibodies directed at HLA-A, B, C, DR, DQ and DP for investigating their association with B FCXM and B CDC XM results; assigning alternate ASHI challenges to the Discovery set and the Validation set; investigating the association between LSAB MFI and physical XM results by logistic regression analysis corrected for overdispersion; and identification of LSAB MFI cutpoint for maximizing the sum of sensitivity and specificity. LSAB MFI cutpoints derived from the Discovery set to predict FCXM and CDC XM results were investigated in an independent validation set. Results Table 1 demonstrates that LSAB MFI cutpoints from the Discovery set predicts XM outcomes in the Validation set (ROC AUC range from 0.974 to 0.999). Conclusions We have developed and validated LSAB MFI cutpoints for use in the virtual crossmatch to accurately predict physical T FCXM, B FCXM, T CDC XM and B CDC XM results.

Aim Interfering factors in sera may confound crossmatch (XM) results. Heat inactivation (HI), DTT and dialysis treatment of sera have been utilized to minimize these confounders. We investigated the impact of HI on donor T cell complement dependent cytotoxicity (CDC) XM (T Cell AHG XM) and donor B cell CDC XM (B Cell NIH XM). Methods We queried our electronic database for all donor CDC T cell and B cell XM performed during 2011–2017 in which potential kidney transplant recipient’s serum was tested in parallel with or without HI and using potential donor’s T cells and B cells as target cells. Results A total of 6295 living donor XMs and 15880 deceased donor XMs performed in our laboratory were reviewed. Table 1 shows the impact of HI on the 22175 consecutive XM results. 394 of the 6295 living donor T Cell AHG XMs were positive using neat sera and 303 were positive following HI at 63C for 6 min, a 23% conversion from positive to negative results. 698 of the 15880 deceased donor T Cell AHG XMs were positive using neat sera and 540 XMs were positive following HI, a 23% reduction. 1372 of the 6295 living donor B Cell NIH XMs were positive using neat sera and 539 were positive following HI, a 61% reduction. 3015 of the 15880 deceased donor B Cell NIH XMs were positive using neat sera and 842 XMs were positive following HI, a 72% reduction from a positive result to negative result. Conclusions A substantial percentage of XMs are converted from a positive CDC result to negative result and such conversion is more frequent with B cell XM compared to T cell XM. Transplant centers seldom transplant across a positive T cell CDC XM even when HI converts a positive result to a negative result. On the other hand, it is not uncommon to proceed with a kidney transplant when HI converts a positive B cell CDC to a negative CDC provided there are no other immune contraindications. There is an urgent need to establish the clinical significance of XMs converted from a positive to a negative result by heat inactivation.

Aim Luminex Single Antigen bead assays (LSAB) are robust for detecting and identifying IgG anti-HLA antibodies, and the LSAB mean fluorescence intensity (MFI) is currently used to list unacceptable antigens and to predict physical crossmatch (XM) results. Concerns exist regarding the use of MFI as the criterion because MFI thresholds for accurately predicting physical XM results are far from established. We aimed to address this unmet need. Methods We leveraged the XM results from ASHI Proficiency Testing (PTs) to investigate whether LSAB MFI cutpoints are predictive of physical XM results. ASHI graded (⩾80% consensus) XM results from 8 consecutive ASHI PTs in which up to 30 labs tested 40 sera and 16 cells distributed by ASHI were used to examine whether LSAB MFI data we generated in the same PTs predict physical XM results. Cumulative MFIs of DSA directed at HLA-A, B, and C were tested for their ability to predict T cell Flow XM and T cell AHG XM results; cumulative MFIs of DSA directed at HLA-A, B, C, DRB1, DRB3/4/5, DQB and DP were tested for their ability to predict B cell Flow XM and B cell CDC XM results. Results Our data analysis identified that cumulative MFI of DSA less than 6000 directed at HLA-class I antigens predicted T cell Flow XM results with a 100% negative predictive value (NPV) and MFI > 7000 predicted T cell Flow XM results with a 100% positive predictive value (PPV) (Chi-Square for trend, X 2 = 70, df = 1, P 8000 predicted B Flow XM result with a 100% PPV (X 2 ; =; 67, df = 1, P Download high-res image (343KB) Download full-size image Conclusions Our data demonstrating the feasibility of developing LSAB MFI cutpoints for the accurate prediction of T cell Flow XM, B cell Flow XM, T cell AHG XM, and B cell CDC XM results advance a strategy for the interpretation of virtual crossmatches and the prediction of physical XM results.

Aim LSAB mean fluorescence intensity (MFI) is often used to predict physical FCXM results, and LSAB MFI cutpoints are used to list unacceptable antigens. We therefore determined the accuracy of LSAB assay MFI cutpoint used to score the LSAB assay as positive or negative in foretelling FCXM results. Methods One hundred and forty-six pre-transplant sera from 146 patients with end stage renal disease were tested against potential kidney donor’s T cells and B cells using a 3-color flow cytometry clinical protocol; the same 146 sera were tested using LSAB assay and the cumulative MFI directed at donor HLA class I and/or II antigens were determined. A T cell FCXM with a median channel shift (MCS) ≥ 40 with the patients serum vs. negative control serum was classified as a positive test; a B cell FCXM with MCS ≥ 50 with the patients serum vs. negative control serum was classified as a positive test. In the LSAB assay, MFI > 2000 directed at donor HLA antigens was scored as positive DSA. These cutpoints are our laboratory’s cutpoints for both ASHI proficiency testing and for clinical use. Results Statistical analysis demonstrated a significant association between LSAB results and FXCM results (Table 1). LSAB assay results predicted T Cell FCXM results with a sensitivity of 70% and a specificity of 100% (Fischers Exact Test, P 0.0001, Positive Predictive Value (PPV = 100%, Negative Predictive Value (NPV) = 91%). LSAB assay results also predicted B Cell FCXM results with a sensitivity of 86% and a specificity of 72% (Fischers Exact Test, P 0.0001, PPV = 62%, NPV = 91%) (Table 1). In a subset of 31 patients, both donor FCXM and auto FCXM results were available and 17 of 31 donor positive FCXM were also auto B cell FCXM positive (17/17) and auto T cell FCXM positive (1/17). Conclusions LSAB assay results are significantly associated with FCXM results. Auto B cell FCXM and high resolution HLA typing should further refine the relationship between these two high sensitive assays. Download high-res image (138KB) Download full-size image

Background In flow cytometry crossmatches (FCXM), sera from AB blood group male donors with none or minimal anti-HLA IgG antibodies are used as the negative control serum (NCS). As NCS can give higher median channel fluorescence (MCF) on certain donor cells, it is advised to use cells treated with phosphate buffer saline (PBS) as an additional negative control for comparison. Aim We examined whether using PBS or NCS as the negative control and subsequent staining with FITC-goat-anti-human IgG polyclonal antibody (g α IgG pAb; Jackson Immunoresearch Laboratory; Cat# 109-096-098) or FITC-mouse-anti-human IgG monoclonal antibody (m α IgG mAb; BD biosciences; Cat# 555786; Clone: G18-145) impacts FCXM results. Methodology Peripheral blood ( N = 5) and serum ( N = 5) were collected from human subjects. Peripheral blood mononuclear cells (PBMC) were isolated by Ficoll density gradient separation. In 96 well V-bottom plate, 300,000 PBMC were incubated with 30 μl of serum for 20 min at 22 °C, washed and stained with 10 μl each of anti-CD3 PerCP and of anti-CD19 PE, and with either 10 μl (1:100 diluted) of FITC-gαIgG pAb or 60 μl of FITC-mαIgG mAb for 30 min at 4 °C. The cells were washed and flow cytometry was performed using BD FACS Canto II instrument and the data was analyzed using the DiVa software. A channel shift of >40 from the NCS for T cell and a shift of >50 for B cells is considered positive here. Results PBMCs treated with PBS gave positive B cell channel shift when stained with g α IgG pAb, but not when stained with m α IgG mAb ( Fig. 1 ). Unlike m α IgG mAb, the g α IgG pAb seems to bind non-specifically to B cells in the absence of human serum. Conclusion This observation cautions that in a clinical FCXM testing, the non use of NCS can lead to a false positive FCXM result. It is also anticipated that a technical error of not adding patient’s serum to the donor cells can lead to positive B cell crossmatch reporting. Using m α IgG mAb or any other α IgG antibody that does not give non-specific binding to donor cells is recommended for FCXM testing.

Aim The AbSorber flow cytometry crossmatch (FXM) XM-ONE 3:1 (XM3) test measures binding of IgG and IgM antibodies (ab) in recipient’s serum to donor-T, -B, and -Tie2+ EPC. The XM3 and our laboratory’s Clinical FXM (CFXM) were compared to examine the feasibility of the XM3’s use in clinical settings. Methods Peripheral blood (N=5) and serum (N=5) were collected from human subjects. Tie2+ EPC and lymphocytes were isolated using manufacturer’s instructions. Cells were incubated with either test serum, negative control serum (NCS) or positive control serum (PCS), washed, and stained with a combination of anti-CD3, -CD19, and ab directed at human -IgG, or -IgM. The median channel shift (MCS) from the NCS for T cell, B cell, and EPC FXM for IgG was considered positive if > 40, >100, and >50, respectively. The MCS cut-off for IgM on T cell, B cell, and EPC was considered positive if >80 MCS. The FXM were acquired in a BD FACSCanto II instrument and the data analysis was performed using the DiVa software. Results 1) The XM3 and CFXM for CD3+IgG+ T cells had similar Median Channel Fluorescence (MCF) (271 ± 19 vs. 241 ± 26) and MCS (9 ± 16 vs. 22 ± 19). All crossmatches were negative; 2) The XM3 and CFXM for CD19+IgG+ B cells also had similar MCF (301 ± 40 vs. 273 ± 19) and MCS (114 ± 77 vs. 105 ± 69). Two B cell FXM were positive and the remaining crossmatches were negative by both methods; 3) Three FXM for CD3+IgM+ T cell and CD19+IgM+ B cell by XM3 and CFXM were negative by both methods; and 4) Of five EPC crossmatches performed by XM3, two subjects were positive for IgG and all five subjects were negative for IgM. Conclusions In addition to facilitating the detection of conventional analysis of donor T and B cell specific IgG ab, the XM3 helps identify donor T and B cell specific IgM ab in recipient’s serum. In contrast to anti-HLA ab, donor-EPC specific IgG or IgM ab occur in fewer recipients, but their identification may impact allograft survival. The XM3 identifies EPC specific IgG or IgM ab in human serum.

Aim Luminex based solid phase testing has become the assay of choice for detecting and identifying IgG HLA antibodies (Abs) and has become a key component in virtual crossmatching and a front line test for many transplant centers. Based on the strength (MFI values) of the donor specific HLA Abs, a patient is ruled in or out as the renal graft recipient. We address one of the existing challenges in the clinical use of Luminex platform as the screening tool; specifically, when low or negative HLA DSA by Luminex solid phase assay result is associated with a positive CDC XM result. We investigated whether EDTA treatment of sera unmasks the presence of IgG HLA Abs and provides a more accurate view of anti-HLA repertoire. Methods Representative sera were selected for the evaluation of EDTA treatment: Sera previously characterized to be Negative for anti-HLA; Sera previously characterized to be Positive for anti-HLA; Sera previously characterized to be Negative for anti-HLA by Luminex and positive by CDC, Masked sera. Two aliquots of each serum, untreated & treated with EDTA (5 μl EDTA/95 μl serum), were tested for HLA Abs using One Lambda Class I/II Single Antigen Bead assay. The trimmed mean MFI values were compared between untreated & EDTA treated samples. Results The major findings from our study were: 1) EDTA treatment of known Negative sera did not convert negative to positive results 2) EDTA treatment of known Positive sera did not convert positive to negative results; however some of the positive sera gave higher MFIs after treatment 3) EDTA treatment of sera previously found to be Luminex negative and CDC positive resulted in a substantive increase in the MFIs in the sera with low MFIs. Conclusions Our encouraging results advance the idea that EDTA treatment of serum may help resolve the paradox of low MFI with the donor HLA by the Luminex platform and positive CDC and FCXM results.

Aim The “virtual crossmatch” is advanced as a predictor of HLA reactivity/compatibility between the recipient and the potential donor. HLA laboratories and transplant centers rely on this practice. Antibody detection however is limited by the makeup of the alleles in the test panel and the genetic makeup of the donor pool is endless. A laboratory with limited resources, specimen access or time may need to make an immediate “virtual” call about a donor/recipient pairing with low resolution molecular HLA typing paired with allelic level HLA Antibody information. Knowing that low resolution molecular HLA typing kits are geared towards identifying the most common alleles for each locus, we wanted to survey the actual frequency that these low resolution SSO kits identified the high resolution typing of these loci with a “single pass”. Methods We surveyed the last 7 ASHI high resolutions PT challenges. We compared our initial low resolution typing (and most likely implied high resolution typing) with the graded high resolution typing returned for each of these surveys. We then determined the percentage of matched results between the predicted high resolution typing with the actual high resolution typing at each of the following HLA loci: A, B, C, DRB1, DRB3,4,5 and DQB1. Results Percentage matched, Predicted High Resolution Vs. Actual High resolution typing A locus: 96% matched B locus: 96% matched Cw locus: 91% matched DRB1 locus: 81% matched DRB3, 4, 5 locus: 48% matched DQB1 locus: 89% matched. Conclusions Our survey has resolved that HLA typing based on low resolution SSO kits results in 90% matched HLA typing as ascertained by high resolution HLA-A, B and Cw typing; our study also demonstrates that HLA class II typing by low resolution, especially DRB3,4,5 typing, leaves much to be desired. The advantages and disadvantages unmasked by our study may be of value in informing clinical decisions and associated risks and benefits.