Genome-wide association study identifies African-ancestry specific variants for metabolic syndrome.

The metabolic syndrome (MetS) is a constellation of metabolic disorders that increase the risk of developing several diseases including type 2 diabetes and cardiovascular diseases. Although genome-wide association studies (GWAS) have successfully identified variants associated with individual traits comprising MetS, the genetic basis and pathophysiological mechanisms underlying the clustering of these traits remain unclear. We conducted GWAS of MetS in 1427 Africans from Ghana and Nigeria followed by replication testing and meta-analysis in another continental African sample from Kenya. Further replication testing was performed in an African American sample from the Atherosclerosis Risk in Communities (ARIC) study. We found two African-ancestry specific variants that were significantly associated with MetS: SNP rs73989312[A] near CA10 that conferred increased risk (P=3.86 × 10(-8), OR=6.80) and SNP rs77244975[C] in CTNNA3 that conferred protection against MetS (P=1.63 × 10(-8), OR=0.15). Given the exclusive expression of CA10 in the brain, our CA10 finding strengthens previously reported link between brain function and MetS. We also identified two variants that are not African specific: rs76822696[A] near RALYL associated with increased MetS risk (P=7.37 × 10(-9), OR=1.59) and rs7964157[T] near KSR2 associated with reduced MetS risk (P=4.52 × 10(-8), Pmeta=7.82 × 10(-9), OR=0.53). The KSR2 locus displayed pleiotropic associations with triglyceride and measures of blood pressure. Rare KSR2 mutations have been reported to be associated with early onset obesity and insulin resistance. Finally, we replicated the LPL and CETP loci previously found to be associated with MetS in Europeans. These findings provide novel insights into the genetics of MetS in Africans and demonstrate the utility of conducting trans-ethnic disease gene mapping studies for testing the cosmopolitan significance of GWAS signals of cardio-metabolic traits.

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