Institution: Makerere University

Project Affiliation: BRecA

Abstract

Host response to the human immune deficiency virus (HIV) involves both the innate and adaptive immune systems. As part of the innate immune system, the killer cell immunoglobulin-like receptors (KIRs) found on natural killer cells and some T-lymphocytes are genetically diverse and play key functions in the host response against viral pathogens. In the last decade, there has been substantial growth in sequencing technologies and bioinformatics capacity to understand human host genetics, including KIR. However, there is inadequate evidence on how the KIR diversity informs the perspectives on HIV disease states in understudied African settings. We conducted a narrative review of published literature from PUBMED, CINAHL, and EMBASE databases with a particular emphasis on KIR studies from Africa. We found that only 32 KIR-focused studies had been conducted across the African continent with 83.3 % of them based on gene content while the rest of the studies combined gene content and allele level analyses. Allele and haplotype frequencies varied between populations with high diversity noted in studies from Ghana, Uganda and Tanzania. The KIR2DL5 gene was associated with HIV infection acquisition. KIR3DL1/S1 genes were associated with slow HIV disease progression to AIDS among African-Americans and European American PLWH although studies from Africa were lacking. Only three studies utilized next-generation sequencing techniques and bioinformatics tools to study KIR from African samples. We conclude that our current knowledge of KIR diversity and its relevance to HIV phenotypes in Africa remains limited in comparison to the size and genetic diversity of the continent. There is an opportunity to utilize the available and novel techniques in bioinformatics and KIR genomics research technologies to fill knowledge gaps and guide future immunogenetics research in HIV populations.
Keywords: Killer cell immunoglobulin-like receptors (KIR), diversity, Human immune deficiency virus (HIV), bioinformatics.

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