Advances in MICA Genotyping: Characterization of 406 Novel Alleles and their Frequencies in Multiple Populations

Viviane Albrecht¹Christin Paech¹Kathrin Putke¹Gerhard Schöfl¹Jürgen Sauter²Alexander H. Schmidt^1,2Vinzenz Lange¹Anja Klussmeier^1*

• ¹DKMS Life Science Lab, Dresden, Germany
• ²DKMS Group, Tübingen, Germany

In 2020, we reported MICA allele frequencies from a cohort of over one million German individuals. This study identified MICA*008 (42%), MICA*002 (12%), and MICA*009 (9%) as the most common MICA alleles at protein resolution. Additionally, we discovered novel alleles with a cumulative frequency of 0.3%. To reduce this fraction of unnamed sequences, we aimed to fully characterize the most frequent novel alleles using both long-and short-read sequencing. As a result, we submitted 603 sequences to the IPD-IMGT/HLA Database: 406 novel alleles and 197 sequence extensions and confirmations. Among the novel alleles, 199 encoded for distinct novel MICA proteins. Following the inclusion of these sequences into the IPD-IMGT/HLA Database, we genotyped 93,814 individuals from an independent cohort. In the German subset (n=48,618), our previous findings on MICA allele frequencies were confirmed. As anticipated, the cumulative frequency of novel alleles decreased significantly from 0.3% to 0.03%, reflecting the expanded reference database. The most frequent of the previously novel alleles were MICA*107N (0.02%), MICA*141 (0.01%), MICA*119 (0.01%), MICA*089 (0.01%), and MICA*247 (0.01%). While allele frequencies in other European and the South African White population were similar to those in Germany, greater variation was observed in the South African Black, non-indigenous Chilean, and Turkish populations. Notably, some of the novel alleles appeared to be population-specific; for example, MICA*258 was exclusively identified in samples from the Black or Coloured populations of South Africa. In conclusion, the extensive characterization of novel MICA alleles has substantially reduced the fraction of unknown sequences in MICA donor genotyping, which will support future biomedical and population genetic studies.