HLA Profiles of Patients With Chronic Kidney Disease in Central South Africa

The human leucocyte antigen (HLA) complex has been associated with the susceptibility of several hundred human diseases, increasingly so with kidney disease. HLA data are under-represented in South Africa, and thus, their contribution to disease characterisation remains poorly understood. Therefore, there is a need for HLA typing studies among high-risk disease populations in our region.

We recruited a total of 100 participants with biopsy-proven chronic kidney disease (CKD) attending a nephrology clinic in central South Africa. Exploratory analyses of demographic, clinical and serological characteristics were performed. High-resolution HLA typing was conducted using DNA microarray technology.

Among 100 participants, a large proportion had early-stage CKD based on glomerular filtration rate (GFR) category (CKD stage 1 and 2: 64%), yet many were classified as being at high or very high risk of disease progression to end-stage kidney disease (ESKD) according to the 'Kidney Disease: Improving Global Outcomes' (KDIGO) criteria. This risk was predominantly driven by severely increased proteinuria (proteinuria category A3: 41.8%) rather than reduced estimated GFR (eGFR). Hypertension was the most common comorbidity/complication, and roughly a fifth of the cohort were HIV positive. The most prevalent autoimmune serology was antinuclear antibody (ANA) positivity, occurring in the context of a high frequency of lupus nephritis (LN) in this cohort. We observed the following recurring set of HLA alleles in this CKD cohort, alongside specific clinical and/or serological features: HLA-A∗23:01; HLA-A∗68:02; HLA-B∗15:10; HLA-B∗44:03; HLA-DRB1∗03:01; HLADQB1∗02:01; HLA-DQB1∗02:02 and/or HLA-DPB1∗04:01.

Our findings suggest that specific HLA alleles may be associated with CKD susceptibility and/or the increased risk of disease progression in this regional cohort, warranting further investigation into specific CKD-related immunological and molecular mechanisms to establish causality in larger studies. Furthermore, by increasing our global representation in population-specific reference panels, we can improve our understanding of South Africa's extensive genetic diversity.