Letter to the Editor

Ann Lab Med 2023; 43(2): 214-216

Published online March 1, 2023

Copyright © Korean Society for Laboratory Medicine.

Establishment of Reference Values for Non-HLA Antibodies in Patients With End-stage Renal Disease

Kyung-Hwa Shin, M.D., Ph.D.1,2 , Hyun Ji Lee, M.D., Ph.D.1,3 , Il Young Kim, M.D., Ph.D.4 , Byung Hyun Choi, M.D.5 , and Hyung-Hoi Kim, M.D., Ph.D.2,6

1Department of Laboratory Medicine, Pusan National University School of Medicine, Yangsan, Korea; 2Biomedical Research Institute, Pusan National University Hospital, Busan, Korea; 3Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Korea; 4Department of Internal Medicine, Pusan National University Yangsan Hospital, Yangsan, Korea; 5Department of Surgery, Pusan National University Yangsan Hospital, Yangsan, Korea; 6BioMedical Informatics Unit, Pusan National University School of Medicine, Yangsan, Korea

Correspondence to: Hyun Ji Lee, M.D., Ph.D.
Department of Laboratory Medicine, Pusan National University School of Medicine and Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, 20 Geumo-ro, Yangsan 50612, Korea
Tel: +82-55-360-1875, Fax: +82-55-360-1880, E-mail:

Received: July 7, 2022; Revised: August 17, 2022; Accepted: September 15, 2022

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Dear Editor,

Non-HLA expression varies with anatomic location and vessel type. Extensive kidney cell damage and apoptosis in patients with end-stage renal disease (ESRD) trigger the release of intracellular proteins that are inaccessible to antibodies. This reaction boosts autoantibody formation to eliminate these antigens from the circulation [1]. Thus, non-HLA antibody levels may differ between patients with ESRD and healthy individuals. We aimed to establish reference values for patients with ESRD and investigate the factors affecting their non-HLA antibody levels.

This retrospective observational study included non-transplant patients with ESRD aged ≥18 years from January 2015 to July 2020. The institutional review board (IRB) of Pusan National University Yangsan Hospital (Yangsan, Korea) approved the study (05-2021-248). All samples were obtained from the Biobank with informed consent under IRB-approved protocols. We used the single-antigen bead-based LABScreen assay (One Lambda, Canoga Park, CA, USA) following the manufacturer’s instructions to determine non-HLA antibody levels. To define positive and negative reactions, we used the manufacturer’s reference values, which were calculated using the median of the trimmed mean fluorescence output data plus twice the standard deviation in 95% of the 125 non-transplant patients. We calculated reference values using the same method and our study data. Statistical analyses were performed using the MedCalc Statistical Software version 18.11.3 (MedCalc, Ostend, Belgium). Statistical significance was set at P<0.05.

In the 241 patients, the antibody positivity rates based on the manufacturer’s and our reference values ranged 0.4%–97.1% and 10.3%–14.9%, respectively (Table 1). More than 50% of the patients tested positive for interferon gamma (IFNG), protein kinase C (PRKCH), regenerating islet-derived protein 3 alpha (REG3A), and vimentin (VM) antibodies based on the manufacturer’s reference values. The positivity rates of 22 antibodies calculated based on the manufacturer’s and our reference values differed significantly (Table 1).

Table 1 . Positivity rates for 32 non-HLA antibodies based on the manufacturer’s reference values (95%) and those established in the present study (N=241)

Antibody targetManufacturerCurrent studyP

Reference values (MFI)N of positive cases (%)Reference values (MFI)N of positive cases (%)
AGRIN50413 (5.3)30832 (13.3)0.004
AGT1,64150 (20.7)2,41530 (12.4)0.020
ARHGDIB3,91812 (5.0)1,89726 (10.8)0.027
AURKA4,89215 (6.2)3,36033 (13.6)0.009
CD361,59111 (4.5)56927 (11.2)0.010
CHAF1B11,7226 (2.5)6,32430 (12.4)< 0.001
CSCL957529 (12.0)56331 (12.8)0.890
CXCL1028573 (30.3)43328 (11.6)< 0.001
CXCL1130996 (39.8)57428 (11.6)< 0.001
EIF2A6,9017 (2.9)3,24936 (14.9)< 0.001
ENO4,21850 (20.7)5,34135 (14.5)0.094
FLRT68878 (32.4)1,22529 (12.0)< 0.001
GAPDH50875 (31.1)1,34527 (11.2)< 0.001
GDNF1,00414 (5.8)73331 (12.8)0.012
GSTT16,13629 (12.0)5,02536 (14.9)0.424
HNRNPK845102 (42.3)1,57825 (10.3)< 0.001
IFIH13,87028 (11.6)3,42833 (13.6)0.584
IFNG498128 (53.1)1,09027 (11.2)< 0.001
LG34,15410 (4.1)1,90031 (12.8)0.001
LMNA6,63312 (5.0)4,11131 (12.8)0.002
LMNB2,06524 (10.0)1,80428 (11.6)0.660
Myosin9,3415 (2.1)6,61928 (11.6)< 0.001
PECR4,12042 (17.4)4,74334 (14.1)0.382
PLA2R19524 (10.0)18028 (11.6)0.660
PPIA3,29239 (16.2)3,65734 (14.1)0.612
PRKCH1,048151 (62.6)3,66327 (11.2)< 0.001
PRKCZ9,10430 (12.4)9,33427 (11.2)0.778
PTPRN3,04226 (10.8)2,64834 (14.1)0.334
REG3A86234 (97.1)67627 (11.2)< 0.001
TNFA5,3311 (0.4)93228 (11.6)< 0.001
TUBA1B1,98717 (7.0)1,31828 (11.6)< 0.001
VM820125 (51.9)3,09230 (12.4)< 0.001

Abbreviations: AGRIN, agrin; AGT, angiotensinogen; ARHGDIB, rho GDP dissociation inhibitor 2; AURKA, aurora kinase A-interacting protein; CD36, platelet glycoprotein 4; CHAF1B, chromatin assembly factor 1 subunit B; CXCL10, C-X-C motif chemokine 10; CXCL11, C-X-C motif chemokine 11; CXCL9, C-X-C motif chemokine 9; EIF2A, eukaryotic translation initiation factor 2A; ENO1, α-enolase; FLRT, fibronectin leucine-rich transmembrane protein; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; GDNF, glial cell line-derived neurotrophic factor; GSTT1, glutathione S-transferase theta 1; HNRNPK, heterogeneous nuclear ribonucleoprotein K; IFIH1, interferon-induced helicase C domain-containing protein 1; IFNG, interferon gamma; LG3, basement membrane-specific heparan sulfate proteoglycan core protein; LMNA, prelamin-A/C; LMNB, lamin-B1; myosin, cardiac-type myosin-binding protein C; MFI, median fluorescence intensity; PECR, peroxisomal trans-2-enoyl-CoA reductase; PLA2R, secretory phospholipase A2 receptor; PPIA, peptidyl-prolyl cis-trans isomerase A; PRKCH, protein kinase C eta type; PRKCZ, protein kinase C zeta type; PTPRN, receptor-type tyrosine-protein phosphatase-like N; REG3A, regenerating islet-derived protein 3 alpha; TNFA, tumor necrosis factor alpha; TUBA1B, tubulin alpha 1B chain; VM, vimentin.

All patients had one or more antibodies based on the manufacturer’s reference values; however, 30 patients lacked the antibodies assessed according to our reference values. Moreover, 186 patients had <10 antibodies (including 47 patients with only one antibody), and 25 patients had ≥10 antibodies (including four patients with >20 antibodies) according to our reference values. Only glutathione S-transferase theta 1 (GSTT1) antibody levels were higher in women than in men (1,513.8 [124.4–15,970] median fluorescence intensity (MFI) vs. 816.3 [76.3–12,079.2] MFI). Only GSTT1, IFNG, and secretory phospholipase A2 receptor (PLA2R) antibody levels differed between older (≥50 years) and younger (<50 years) patients. Patients with preformed donor-specific antibodies (DSA) displayed higher chemokine (C-X-C motif) ligand 9 (CXCL9), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and tumor necrosis factor alpha (TNFA) antibody levels than those without preformed DSA (Fig. 1).

Figure 1. Non-HLA antibody levels according to the pre-DSA status. (A) CXCL9, (B) GAPDH, and (C) TNFA levels in patients with and without pre-DSA (median [range]: CXCL9, 197.7 [43.0–4102.7] vs. 135.1 [23.1–3168.2]; GAPDH, 504.6 [72.7–11490.2] vs. 311.6 [27.2–7732.8]; TNFA, 457.6 [159–4629.5] vs. 359.3 [54.7–10403.3]).
Abbreviations: CXCL9, C-X-C motif chemokine 9; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; MFI, median fluorescence intensity; TNFA, tumor necrosis factor alpha; DSA, donor-specific antibodies.

There was no information about the individuals based on whom the manufacturer’s reference values were established. Therefore, we analyzed the distribution of non-HLA antibody levels in non-transplant patients with ESRD for use as reference values for patients undergoing kidney transplantation. Based on reference values, the healthy subjects displayed 3% to 5% positivity rate for non-HLA antibodies [1, 2]. Most previous studies used manufacturers’ reference values [3-5], and non-HLA antibodies are present in 95.2% of hypersensitized patients awaiting kidney transplantation (N=27) [4]. More than one non-HLA antibody has been identified in 13 patients with unexplained positive pre-transplant crossmatch testing results [6]. IFNG, PRKCH, REG3A, and VM antibodies were frequently detected in this study as well as in previous studies [3-5]. All patients had more than one antibody based on the manufacturer’s reference values. The positivity rates differed when using the reference values established for patients with ESRD.

CXCL9 and TNFA are related to T-cell reactivity, whereas CXCL9, a proinflammatory chemokine, is produced in response to IFNG. High pre-transplant CXCL9 levels in kidney transplant recipients can predict acute rejection and 5-year graft survival [7]. Tissue injury, alloimmune injury, and other injury types, including those induced by the use of immunosuppressants, after transplantation can cause the exposure of neo-antigens, which can induce the production of non-HLA antibodies [8], thus affecting prognosis [9] and warranting research on de novo non-HLA antibodies.

The positivity rates of non-HLA antibodies, including IFNG, PRKCH, REG3A, and VM antibodies, were high in patients with ESRD according to the manufacturer’s reference values. We observed differences in certain non-HLA antibody levels according to sex, age, and the presence of DSA. Our findings indicate the need for appropriate reference values for patients with ESRD and revealed the clinical significance of non-HLA antibodies for ESRD patients awaiting transplant by confirming true positivity rates of non-HLA antibodies.

Lee HJ and Kim HH designed the study. Kim IY, Choi BH, Kim IY, and Choi BH were involved in data collection. Lee HJ and Shin KH analyzed the data. Lee HJ and Shin KH wrote the manuscript. All authors reviewed and approved the final version of the manuscript.

This study was supported by a National Research Foundation of Korea Grant funded by the Korean Government (grant No. NRF-2019R1C1C10073788) and a Pusan National University Research Grant, 2021.

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