Resolution‐Aware Eight‐Locus HLA Diversity Profiling and Rare Allele Interpretation in an Eastern Chinese Transplant‐Typing Cohort

This is the authors' abstract. We don't add key points for this paper.

HLA diversity profiling is essential for transplant-typing practice, yet its interpretation is complicated by heterogeneous typing resolution and ambiguity in routine clinical datasets. We analysed eight-locus HLA genotyping results from 1388 individuals in an Eastern Chinese transplant-typing cohort (2021-2026) using a resolution-aware two-stage analytical framework-an approach that explicitly distinguishes first-field (allele-group) summaries from strict two-field allele-level analysis. HLA diversity profiling is defined as the systematic characterisation of allele/allele-group frequency distributions, heterozygosity and diversity metrics (Shannon entropy, evenness). Stage 1 summarised assay-derived first-field (allele-group) codes with complete coverage across all loci (2776 allele copies per locus), whereas Stage 2 evaluated strict two-field alleles restricted to loci achieving a > 45% two-field resolution threshold. Observed heterozygosity varied markedly across loci, ranging from 0.484 at HLA-DPA1 to 0.923 at HLA-B. At Stage 1, 43 rare allele-group codes (< 1%) were identified, disproportionately contributed by HLA-DPB1 (51.2%), consistent with resolution- and ambiguity-related inflation of apparent rare categories. At Stage 2, 68 rare two-field alleles (< 1% within locus-specific resolvable subsets) were identified; all were officially assigned and listed in the IPD-IMGT/HLA Database and documented in the Allele Frequency Net Database, with 97.1% having reported Chinese population records. Classification using the Common, Intermediate and Well-Documented (CIWD) catalogue showed that most cohort-defined 'rare' alleles were not globally rare. Together, these findings demonstrate that apparent rare allele burden in transplant-typing cohorts is strongly influenced by typing resolution and ambiguity handling. The resolution-aware framework presented here provides a transparent template for HLA diversity reporting and rare allele interpretation in heterogeneous clinical transplant-typing datasets.