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Despite recent efforts to increase diversity in genome-wide association studies (GWASs), most loci currently associated with kidney function are still limited to European ancestry due to the underlying sample selection bias in available GWASs. We set out to identify susceptibility loci associated with estimated glomerular filtration rate (eGFRcrea) in 80027 individuals of African-ancestry from the UK Biobank (UKBB), Million Veteran Program (MVP), and Chronic Kidney Disease genetics (CKDGen) consortia. We identified 8 lead loci, 7 of which were previously associated with eGFR in other populations. We identified one novel variant, rs77408001 which is an intronic variant mapped to the ELN gene. We validated seven previously reported loci at GATM-SPATA5L1 and AGPAT3. Fine-mapping analysis identified variants rs77121243 and rs201602445 as having a 99.9% posterior probability of being causal. Our results warrant designing bigger studies within individuals of African ancestry to gain new insights into the pathogenesis of Chronic Kidney Disease (CKD) and identify genomic variants unique to this ancestry that may influence renal function and disease.

Background: According to observational studies, two polymorphisms in the apolipoprotein L1 (APOL1) gene have been linked to an increased risk of chronic kidney disease (CKD) in Africans. One polymorphism involves the substitution of two amino-acid residues (S342G and I384M; known as G1), while the other involves the deletion of two amino-acid residues in a row (N388 and Y389; termed G2). Despite the strong link between APOL1 polymorphisms and kidney disease, the molecular mechanisms via which these APOL1 mutations influence the onset and progression of CKD remain unknown. Methods: To predict the active site and allosteric site on the APOL1 protein, we used the Computed Atlas of Surface Topography of Proteins (CASTp) and the Protein Allosteric Sites Server (PASSer). Using an extended molecular dynamics simulation, we investigated the characteristic structural perturbations in the 3D structures of APOL1 variants. Results: According to CASTp’s active site characterization, the topmost predicted site had a surface area of 964.892 Å2 and a pocket volume of 900.792 Å3. For the top three allosteric pockets, the allostery probability was 52.44%, 46.30%, and 38.50%, respectively. The systems reached equilibrium in about 125 ns. From 0–100 ns, there was also significant structural instability. When compared to G1 and G2, the wildtype protein (G0) had overall high stability throughout the simulation. The root-mean-square fluctuation (RMSF) of wildtype and variant protein backbone Cα fluctuations revealed that the Cα of the variants had a large structural fluctuation when compared to the wildtype. Conclusion: Using a combination of different computational techniques, we identified binding sites within the APOL1 protein that could be an attractive site for potential inhibitors of APOL1. Furthermore, the G1 and G2 mutations reduced the structural stability of APOL1.

BACKGROUND: Observational studies have investigated the effect of serum lipids on kidney function, but these findings are limited by confounding, reverse causation and have reported conflicting results. Mendelian randomization (MR) studies address this confounding problem. However, they have been conducted mostly in European ancestry individuals. We, therefore, set out to investigate the effect of lipid traits on the estimated glomerular filtration rate (eGFR) based on serum creatinine in individuals of African ancestry. METHODS: We used the two-sample and multivariable Mendelian randomization (MVMR) approaches; in which instrument variables (IV's) for the predictor (lipid traits) were derived from summary-level data of a meta-analyzed African lipid GWAS (MALG, n = 24,215) from the African Partnership for Chronic Disease Research (APCDR) (n = 13,612) & the Africa Wits-IN-DEPTH partnership for Genomics studies (AWI-Gen) dataset (n = 10,603). The outcome IV's were computed from the eGFR summary-level data of African-ancestry individuals within the Million Veteran Program (n = 57,336). A random-effects inverse variance method was used in our primary analysis, and pleiotropy was adjusted for using robust and penalized sensitivity testing. The lipid predictors for the MVMR were high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and triglycerides (TG). FINDINGS: We found a significant causal association between genetically predicted low-density lipoprotein (LDL) cholesterol and eGFR in African ancestry individuals β = 1.1 (95% CI [0.411–1.788]; p = 0.002). Similarly, total cholesterol (TC) showed a significant causal effect on eGFR β = 1.619 (95% CI [0.412–2.826]; p = 0.009). However, the IVW estimate showed that genetically predicted HDL-C β = −0.164, (95% CI = [−1.329 to 1.00]; p = 0.782), and TG β = −0.934 (CI = [−2.815 to 0.947]; p = 0.33) were not significantly causally associated with the risk of eGFR. In the multivariable analysis inverse-variance weighted (MVIVW) method, there was evidence for a causal association between LDL and eGFR β = 1.228 (CI = [0.477–1.979]; p = 0.001). A significant causal effect of Triglycerides (TG) on eGFR in the MVIVW analysis β = −1.3 ([−2.533 to −0.067]; p = 0.039) was observed as well. All the causal estimates reported reflect a unit change in the outcome per a 1 SD increase in the exposure. HDL showed no evidence of a significant causal association with eGFR in the MVIVW method (β = −0.117 (95% CI [−1.252 to 0.018]; p = 0.840)). We found no evidence of a reverse causal impact of eGFR on serum lipids. All our sensitivity analyses indicated no strong evidence of pleiotropy or heterogeneity between our instrumental variables for both the forward and reverse MR analysis. INTERPRETATION: In this African ancestry population, genetically predicted higher LDL-C and TC are causally associated with higher eGFR levels, which may suggest that the relationship between LDL, TC and kidney function may be U-shaped. And as such, lowering LDL_C does not necessarily improve risk of kidney disease. This may also imply the reason why LDL_C is seen to be a poorer predictor of kidney function compared to HDL. In addition, this further supports that more work is warranted to confirm the potential association between lipid traits and risk of kidney disease in individuals of African Ancestry. FUNDING: 10.13039/100004440Wellcome (220740/Z/20/Z).

The Uganda Genome Resource (UGR) is a well characterised genomic database, with a range of phenotypic communicable and non-communicable diseases and risk factors generated from the Uganda General Population Cohort (GPC) - a population-based open cohort study established in 1989 by the Medical Research Council (MRC) UK in collaboration with the Uganda Virus Research Institute (UVRI).In 2011, UGR was launched with genotype data on ∼5000 and whole genome sequence data on ∼2000 Ugandan individuals from 9 ethno-linguistic groups. Leveraging other available platforms at the MRC Uganda such as Biorepository centre for sample storage, Clinical Diagnostic Laboratory Service (CDLS) for sample diagnostic testing, sequencing platform for DNA extraction, Uganda Medical informatics Unit (UMIC) for large-scale data analysis, GPC for additional sample collection, UGR is strategically poised to expand and generate scientific discoveries.Here, we describe UGR and highlight the important genetic findings thus far including how UGR is providing opportunities to: (1) discover novel disease susceptibility genetic loci; (2) refine association signals at new and existing loci; (3) develop and test Polygenic Risk Score (PRS) to determine individual’s disease risk; 4) assess how some risk factors including infectious diseases are causally related to non-communicable diseases (NCDs) in Africa; (5) develop research capacity for genomics in Africa; and (6) enhance African participation in the global genomics research arena. Leveraging established research infrastructure, expertise, local genomic leadership, global collaboration and strategic funding, we anticipate that UGR can develop further to a comparable level of European and Asian large-scale genomic initiatives.

Polygenic risk scores (PRS) can enhance risk stratification and are useful for precision medicine interventions. Here we show that African American Genome-wide Association Study (GWAS) derived PRS enhance prediction of lipid traits in Sub-Saharan Africans. Our PRS prediction varied greatly between South African Zulus (LDL-C, R2 = 8.49%) and Ugandans (LDL-C, R2= 0.043%), potentially attributable to environmental factors. Moreover, the PRS shown here had a higher discriminatory ability (AUC = 74.6%) than conventional risk factors (AUC= 67.8%) to identify extreme phenotypes. This work highlights the utility of PRS derived from relevant ethnic groups for identifying high-risk cases missed by conventional clinical factors.

Evaluation of antigen-specific T-cell responses to viral antigens is frequently performed on IFN-γ secreting cells. However, T-cells are capable of producing many more functions than just IFN-γ, some of which, like Perforin, are associated with immune protection in HIV-1 disease elite controllers. We evaluated the extent of missed T-cell functions when IFN-γ secretion is used as a surrogate marker for further evaluation of T-cell functions. Intracellular cytokine staining assay and flow cytometry were used to assess peripheral blood mononuclear cells (PBMCs) from 31 HIV-infected ART-naive individuals for the extent to which gated CD4+ and CD8+ IFN-γ producing and non-producing T-cells also secreted IL-2, Perforin, and TNF-α functions. Similarly, the extent of missed virus-specific responses in IFN-γ ELISpot assay negative T-cells from 5 HIV-1 uninfected individuals was evaluated. Cells from HIV-infected individuals were stimulated with pooled consensus group M (Con M) peptides; and those from healthy individuals were stimulated with pooled adenovirus (Ad) peptides. Overall, frequencies of virus-specific IFN-γ secreting CD4+ and CD8+ cells were low. Proportions of IFN-γ negative CD4+ expressing IL-2, Perforin, or TNF-α to Con M were significantly higher (5 of 7 functional profiles) than the corresponding IFN-γ positive CD4+ (0 of 7) T-cell phenotype, p = 0.02; Fisher's Exact test. Likewise, proportions of CD8+ T-cells expressing other functions were significantly higher in 4 of the 7 IFN-γ negative CD8+ T-cells. Notably, newly stimulated Perforin, identified as Perforin co-expression with IL-2 or TNF-α, was significantly higher in IFN-γ negative CD8+ T-cell than in the positive CD8+ T-cells. Using SEB, lower responses in IFN-γ positive cells were most associated with CD4+ than CD8+ T-cells. These findings suggest that studies evaluating immunogenicity in response to HIV and Adenovirus viral antigens should not only evaluate T-cell responsiveness among IFN-γ producing cells but also among those T-cells that do not express IFN-γ.