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Determination of HLA-A, -B, and -DRB1 Allele and Haplotype Frequencies in the Croatian Population Based on a Family Study.

Zorana GrubicMarija MaskalanDanijela SvilicicKatarina Stingl JankovicRenata Zunec
Published in: Archivum immunologiae et therapiae experimentalis (2017)
In the present study, HLA allele and haplotype frequencies among Croatian families were investigated to evaluate valuable information about HLA genotypes and to compare them with data from the Croatian Bone Marrow Donor Registry (CBMDR). A total of 350 families which have been typed for the purpose of HSCT were included. All individuals were tested using PCR-SSO or PCR-SSP methods for HLA-A, -B, and -DRB1 alleles. The HLA-A-B-DRB1 haplotypes were determined by segregation and directly counted. A total of 30 HLA-A, 54 HLA-B, and 38 HLA-DRB1 alleles and 716 different HLA-A-B-DRB1 haplotypes were identified. Of these, the three most frequent alleles at HLA-A, -B, and -DRB1 loci, respectively, were A*02:01 (30.39%), A*11:01 (13.37%), A*24:02 (10.91%); B*51:01 (12.48%), B*18:01 (8.35%), B*08:01 (8.06%); DRB1*03:01 (11.20%), DRB1*01:01 (9.84%), DRB1*16:01 (9.63%). The following HLA alleles were detected only once: A*02:09, A*24:03, A*24:04, A*24:07; B*07:04, B*15:07, B*15:08, B*39:04, B*39:10, B*39:24, B*40:04; DRB1*08:03, DRB1*11:06, DRB1*13:32, DRB1*14:05. Five most frequent haplotypes were: A*01:01-B*08:01-DRB1*03:01 (5.34%), A*02:01-B*18:01-DRB1*11:04 (1.57%), A*02:01-B*27:02-DRB1*16:01 (1.50%), A*02:01-B*27:05-DRB1*01:01 (1.42%) and A*02:01-B*44:02:01G-DRB1*16:01 (1.28%). The haplotype frequencies based on the family study were compared with the frequencies from CBMDR, and similar results were obtained for all except for the HLA-A*26:01-B*38:01-DRB1*04:02 haplotype. A significantly higher frequency (P = 0.0017) of this haplotype was observed among family individuals. Nine haplotypes were unique and data about their frequencies do not exist in current databases. The data obtained in this study could be useful for anthropology, transplantation and disease association studies.
Keyphrases
  • bone marrow
  • healthcare
  • gene expression
  • stem cells
  • electronic health record
  • machine learning
  • social media
  • dna methylation
  • liquid chromatography
  • cell therapy
  • high speed