Ann Lab Med.  2021 Mar;41(2):190-197. 10.3343/alm.2021.41.2.190.

Prediction of HLA-DQ in Deceased Donors and its Clinical Significance in Kidney Transplantation

• Kim SK
• Yang JJ
• Hwang SH
• Sung H
• Shin S
• Ko SY
• Oh HB

• KMID: 2512665
• DOI: http://doi.org/10.3343/alm.2021.41.2.190

Abstract

Background
HLA-DQ typing in deceased donors is not mandatory in Korea. Therefore, when patients develop DQ antibodies after kidney transplantation (KT) from deceased donor, it is impossible to determine whether they are donor-specific antibodies (DSA). We developed DQ prediction programs for the HLA gene and evaluated their clinical utility.
Methods
Two HLA-DQ prediction programs were developed: one based on Lewontin’s linkage disequilibrium (LD) and haplotype frequency and the other on an artificial neural network (ANN). Low-resolution HLA-A, -B, -DR, and -DQ typing data of 5,603 Korean patients were analyzed in terms of haplotype frequency and used to develop an ANN DQ prediction program. Predicted DQ (pDQ) genotype accuracy was analyzed using the typed DQ data of 403 patients. pDQ DSA agreement, sensitivity, specificity, and false-negative rate was evaluated using 1,970 single-antigen bead assays performed on 885 KT recipients. The clinical significance of DQ and pDQ DSA was evaluated in 411 KT recipients.
Results
pDQ genotype accuracies were 75.4% (LD algorithm) and 75.7% (ANN). When the second most likely pDQ (LD algorithm) was also considered, the genotype accuracy increased to 92.6%. pDQ DSA (LD algorithm) agreement, sensitivity, specificity, and falsenegative rate were 97.5%, 97.3%, 98.6%, and 2.4%, respectively. The antibody-mediated rejection treatment frequency was significantly higher in DQ or pDQ DSA-positive patients than in DQ or pDQ DSA-negative patients (P < 0.001).
Conclusions
Our DQ prediction programs showed good accuracy and could aid DQ DSA detection in patients who had undergone deceased donor KT without donor HLA-DQ typing.

Keyword

Artificial neural network; Donor-specific antibody; HLA-DQ; Kidney transplantation; Linkage disequilibrium

Figure

• 

  Fig. 1 Patient and data selection flowchart. (A) HLA-DQ prediction program development and evaluation. (B) Evaluation of pDQ DSA agreement, sensitivity, and specificity. (C) Evaluation of DQ and pDQ DSA clinical significance. Abbreviations: ANN, artificial neural network; DSA, donor specific antibody; KT, kidney transplantation; LD, linkage disequilibrium; pDQ, predicted DQ; SAB, single-antigen bead.

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