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Variations in lipid levels are attributed partly to genetic factors. Genome-wide association studies (GWASs) mainly performed in European, African American and Asian cohorts have identified variants associated with LDL-C, HDL-C, total cholesterol (TC) and triglycerides (TG), but few studies have been performed in sub-Saharan Africans. This study evaluated the effect of single nucleotide variants (SNVs) in eight candidate loci ( ABCA1 ,  LCAT ,  LPL ,  PON1 ,  CETP ,  PCSK9 ,  MVK , and  MMAB ) on lipid levels among 1855 Ghanaian adults. All lipid levels were measured directly using an automated analyser. DNA was extracted and genotyped using the H3Africa SNV array. Linear regression models were used to test the association between SNVs and log-transformed lipid levels, adjusting for sex, age and waist circumference. In addition Bonferroni correction was performed to account for multiple testing. Several variants of  CETP ,  LCAT ,  PCSK9 , and  PON1  (MAF > 0.05) were associated with HDL-C, LDL-C and TC levels at  p  < 0.05. The lead variants for association with HDL-C were rs17231520 in  CETP  (β = 0.139,  p  < 0.0001) and rs1109166 in  LCAT  (β = −0.044,  p  = 0.028). Lower LDL-C levels were associated with an intronic variant in  PCSK9  (rs11806638 [β = −0.055,  p  = 0.027]) and increased TC was associated with a variant in  PON1  (rs854558 [β = 0.040,  p  = 0.020]).  In silico  functional analyses indicated that these variants likely influence gene function through their effect on gene transcription. We replicated a strong association between  CETP  variants and HDL-C and between  PCSK9  variant and LDL-C in West Africans, with two potentially functional variants and identified three novel variants in linkage disequilibrium in  PON1  which were associated with increasing TC levels in Ghanaians.

frontiers in genetics

Candidate Gene Analysis Reveals Strong Association of CETP Variants With High Density Lipoprotein Cholesterol and PCSK9 Variants With Low Density Lipoprotein Cholesterol in Ghanaian Adults: An AWI-Gen Sub-Study