Assessing HLA imputation accuracy in a West African population

Area of Science:

• Genetics
• Immunogenetics
• Population Genetics

Background:

• The Human Leukocyte Antigen (HLA) region is critical in autoimmune and infectious diseases but challenging to impute due to high polymorphism.
• West African populations exhibit significant genetic diversity and are underrepresented in genomic studies, necessitating evaluation of HLA imputation accuracy in this demographic.

Approach:

• Assessed HLA imputation accuracy using Gambian Genome Variation Project (GGVP) Whole Genome Sequence datasets.
• Evaluated two genotyping arrays (Illumina Omni 2.5, H3Africa) and tested multiple imputation panels (1000 Genomes, H3Africa, HLA Multi-ethnic) and tools (HIBAG, SNP2HLA, CookHLA, Minimac4).
• Utilized concordance rate as the primary metric for assessing imputation accuracy of HLA-A, HLA-B, and HLA-C alleles.

Key Points:

• The HIBAG tool demonstrated the highest overall concordance rate (0.84).
• The H3Africa reference panel yielded the best performance (0.62 concordance rate).
• Minimac4 improved HLA-B imputation accuracy (0.75) compared to other tools, while genotyping array type had minimal impact on imputation accuracy in West Africans.

Conclusions:

• Employing a larger, population-specific reference panel, such as the H3Africa dataset, is key to enhancing HLA imputation accuracy.
• The HIBAG imputation tool is recommended for improving HLA imputation accuracy in West African populations.
• These findings are vital for future genetic association studies of diseases in underrepresented African populations.