ETD Collection

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    Variants in four genes associated with lipid levels: a study in African populations
    (2018) Hayat, Mahtaab
    Non-communicable diseases, including cardiovascular disease (CVD), are on the rise in African populations. High serum LDL cholesterol (LDL-C) levels is a risk factor for CVD, but the contribution of high LDL-C levels to CVD in African populations remains poorly understood. Genetic variation in the LDLR, APOB, PCSK9 and LDLRAP1 genes is known to be associated with alteration in LDL-C levels in many populations. This study aims to examine whether genetic variants in these four genes are associated with differing LDL-C levels in African populations, considering LDL-C as a polygenic trait. Publicly available African whole genome sequence data were interrogated, and variants were selected for genotyping using functional predictive bioinformatics tools. Participants (n=1000) from the AWI-Gen study were selected using a case-control study design based on clinical cut-offs of LDL-C levels (500 with LDL-C>3.5 mmol/l, 500 with LDL-C<1.1 mmol/l). Genotyping was carried out on 19 selected SNPs chosen from across the four genes. Logistic regression analysis revealed that, after adjusting for sex, fasting glucose levels, BMI and geographic region, the minor alleles at two SNPs remained significantly associated (p<0.05) with low LDL-C levels - LDLRAP1 rs12071264, c.533-22A>G (OR 0.5866, p<0.01) and APOB rs6752026, c.433G>A (OR 0.6898, p=0.04). The minor alleles G and A, were associated with lower LDL-C levels, suggesting gain of function effects. The variant alleles at both loci are extremely rare in European populations (MAF<0.001) and this may explain why they have not previously been reported in LDL-C association studies. Since African populations, in general, have reduced LDL-C levels these variants could be African-specific LDL-C associated variants and may suggest a unique gene-environment interaction. Using a limited number of potentially functional variants in African populations and after extensive adjustment for potential covariates, significant associations were detected with variants in two of the four genes studied.