Because of the presence of confounding antigens, the assignment of HLA antibody specificity is difficult in highly sensitized patients, and the definition of an acceptable HLA mismatch requires a significant workload per patient. We describe a new ELISA method, monoLISA, for detection of immunoglobulin (Ig)G HLA antibody using single recombinant HLA class I monomers bound to microtiter plates.
HLA-A2 and -B8 monomers were synthesized and used as screening targets for 85 sera from renal patients. The sera contained various IgG and IgM HLA-specific antibodies, including anti-A2 and anti-B8,defined in a conventional complement-dependent cytotoxicity test (CDC). Investigations were performed to determine possible effects on antibody binding of differential monomer peptide presentation as well as lack of glycosylation.
A good correlation was found between CDC-defined specificities and the reactivity observed with HLA monomers. MonoLISA attained means of 100% sensitivity and 92.5% specificity compared with CDC. Neither the presence of different peptides, nor the absence of glycosylation of the monomer affected the ability of monoLISA to detect antibody.
This study demonstrates that the monoLISA method for HLA antibody detection is valid. Because this has the potential to reduce the work involved in screening sensitized patients awaiting transplantation for HLA antibodies, resources aimed at increasing the number of constructed monomers would be well targeted.
Transplant Immunology, Oxford Transplant Centre and Nuffield Dept. of Surgery, Oxford, OX3 7LJ; SE & SW Thames Regional Tissue Typing, Guy’s Hospital, London; Institute of Molecular Medicine, Oxford, OX3 9DU UK
1 Transplant Immunology.
2 SE & SW Thames Regional Tissue Typing.
3 Institute of Molecular Medicine, Oxford, OX3 9DU UK.
4 Graham Ogg is the recipient of MRC Clinician Scientist Fellowship.
Received 1 November 1999.
Accepted 28 January 2000.
5 Address correspondence to: Martin Barnardo, Transplant Immunology, Oxford Transplant Centre, Churchill Hospital, Oxford, OX3 7LJ. E-mail: email@example.com.