The capacity evaluation and utilization strategy of the platelet donor database with known HLA/HPA genotype in Shaanxi / 中国输血杂志

ABSTRACT

【Objective】 To evaluate the appropriate optimal capacity and matching probability of the platelet donor database with known HLA/HPA genotype in Shaanxi aera, and provide data support for subsequent construction, maintenance and application of the local platelet donor database. 【Methods】 A total of 11 755 individuals from the Shaanxi Branch of China Marrow Donor Program, 401 and 249 unrelated random platelet donors in Shaanxi aera were enrolled to the population study of HLA-A, -B polymorphisms, HPA genotyping and CD36 antigen expression, respectively. The frequencies of HLA-A, -B alleles, HPA alleles and haplotypes were calculated with Arlequin 3. 5. 2. 2 software; matching probability and capacity evaluation of platelet donor database was conducted according to the phenotypic frequencies. 【Results】 The population genetic and phenotypic polymorphisms data of HLA-A, -B and HPA1-6, 10, 15, 21 in Shaanxi aera were obtained. The frequency of CD36 type Ⅰ or Ⅱ deficiency was 0.40%(1/249). According to the subsequent calculating and deriving, with a database size of 194 donors, the patient having approximate 95% probability could achieve matching of HPA1-6, 10, 15, 21 genotype. With a database size of 1500 donors, there is a 95% probability of matching at least one donor with HLA-A-B phenotype frequency >0.002 or haplotype frequency >0.001; meanwhile, the probability of matching a cross-reactive group donor should be 44.95%-97.57%. Based on database size of 8 856 and 15 033, the probabilities of matching HLA-A, -B phenotype were about 80% and 90%, respectively. 【Conclusion】 The differences in the distribution of HLA/HPA polymorphism in different regions make the establishment mode and optimal capacity of platelet donor database different. It is necessary to apply a variety of platelet matching transfusion strategies to expand the range of donor selection, thereby effectively reducing the database construction cost and resource requirements.