Investigation of MHC gamma block C4A and C4B polymorphisms in unrelated hematopoietic stem cell transplantation

Abstract

Background Immunological life-threatening complications frequently occur in post-hematopoietic stem cell transplantation (HSCT), despite matching recipient and donor (R/D) pairs for classical human leukocyte antigens (HLA). Studies have shown that R/D non-HLA disparities within the major histocompatibility complex (MHC) are associated with adverse effects post-HSCT. Methods We investigated the impact of mismatches of single-nucleotide polymorphisms (SNPs) in C4A / C4B genes, for showing the highest diversity in the MHC gamma block, on 238 patients who underwent HLA 10/10 unrelated donor (URD) HSCT. The endpoints were acute graft-versus-host disease (aGVHD), chronic graft-versus-host disease (cGVHD) and mortality. One hundred and twenty-nine R/D pairs had 23 C4-SNPs typed by PCR-SSP (Gamma-Type™v.1.0), and 109 R/D pairs had these 23 SNPs identified by next-generation sequencing (NGS) using the Illumina platform. Results The percentage of patients who received HSC from HLA 10/10 donors with 1–7 mismatches was 42.9%. The R/D pairs were considered C4 mismatched when bearing at least one disparity. These mismatches were not found to be risk factors for aGVHD, cGVHD or mortality after unrelated HSCT when SNPs were analyzed together (matched or mm ≥ 1), independently or according to the percentage of incompatibilities (full match for 23 SNPs; 1–3 mm and >3 mm). An exception was the association between 1–3 mismatches at the composite of SNPs C13193/T14952/T19588 with the development of aGVHD (P = 0.012) and with grades III-IV of this disease (P = 0.004). Conclusion Our data are not consistent with the hypothesis that disparities in C4A / C4B SNPs increase the risks of post-HSCT adverse effects for the endpoints investigated in this study.

HLA gamma block matching in unrelated hematopoietic stem cell transplantation and the development of graft versus host disease

“…On the other hand, Askar et al conducted a study of 714 patients that were HLA matched and did not report any significant association between GB SNP nor C4 SNP mismatches with HSCT outcomes 10 . In 2020, another group found no significant correlation between the occurrence of GvHD and C4 mismatches, although those results were not in accordance with their research of the same subject conducted in 2014 16 . Considering that all patient-donor pairs in our study group were unrelated, mismatches within the MHC Gamma region were expected.…”

Widespread non‐coding polymorphism in HLA class II genes of International HLA and Immunogenetics Workshop cell lines

“…There is potential for additional genes within the MHC, such as those residing in the gamma block, to be investigated for their polymorphisms. This is currently largely performed by SNP mapping and although their clinical impact is not yet clear, [53][54][55] they provide interesting targets for future study, in a further step towards full haplotype characterization.…”

BSHI guideline: HLA matching and donor selection for haematopoietic progenitor cell transplantation

“…HLA class I and II genes are separated by the MHC class III region, also described as the gamma block, which contains genes encoding immune regulatory proteins including the complement components Bf, C2 and C4. Comparison of SNPs within the complement C4A and C4B genes did not identify any association between SNP mismatching and transplant outcome (Clancy et al., 2019; Getz et al., 2020). Similarly, no significant associations between gamma block mismatching and unrelated donor HPCT outcomes were observed in a large retrospective cohort from the CIBMTR (Askar et al., 2019), nor in multivariate analysis of a single‐centre cohort (Maskalan et al., 2020).…”

“…The EBMT consensus recommendations (Ciurea et al, 2020) concluded that NIMA-mismatched siblings may be preferred over (Clancy et al, 2019;Getz et al, 2020). Similarly, no significant associations between gamma block mismatching and unrelated donor HPCT outcomes were observed in a large retrospective cohort from the CIBMTR (Askar et al, 2019), nor in multivariate analysis of a single-centre cohort (Maskalan et al, 2020).…”