Abstract
Abstract Introduction There is an unmet need for prognostic biomarkers for alloimmune risk stratification to guide personalised recipient care kidney transplantation. Methods We used three molecular Mismatch (molMM) algorithms - Amino-Acid-Mismatch-Score (AAMS), Electrostatic-Mismatch-Score (EMS3D) and NetMHCIIpan in a dataset of patients receiving standardised donor lymphocyte injections to predict de-novo donor-specific-antibody (dnDSA) at the individual HLA level (n=665). Risk thresholds were derived for HLA-DR/DQ mismatch and algorithms combined. External validation was performed in two extensively-phenotyped kidney transplant cohorts (Manitoba, n=856, Denver n=404) and in the NHSBT kidney transplant registry (2000–2020, n=27,028). Results External validation (Manitoba cohort, 10-year follow-up) showed all algorithms predicted dnDSA development using experimentally derived HLA-DR/DQ molMM risk thresholds (HLA-DQ AUC: 0.78-0.80; HLA-DR AUC:0.76-0.81). AAMS and EMS3D had improved risk stratification (low-medium-high risk groups for HLA-DR+DQ dnDSA) vs NetMHCIIpan (p=NS). A combined AAMS+EMS3D molMM algorithm further improved discrimination and identified a large patient cohort (15.4% patients) at very-low risk of Class-II dnDSA (1.3% at 10 years). Multivariate analysis confirmed correlation with primary alloimmune events (dnDSA p<0.001, TCMR p<0.001, ABMR p=0.0049) and all-cause graft loss (p=0.0038). Further external validation of the combined molMM algorithm in an ethnically diverse cohort (Denver) confirmed the dnDSA risk association (p<0.0001), and in the UK registry cohort confirmed significant association with all-cause graft loss (p<0.001). Conclusion We developed and validated a novel molMM algorithm, incorporating information from HLA amino-acid sequence and tertiary structurebthat may be used as a prognostic biomarker of primary alloimmunity risk and to enrich prospective clinical trials in kidney transplantation.
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