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Diabetologia. 2011 Apr;54(4):783-8. doi: 10.1007/s00125-010-2002-7. Epub 2010 Dec 25.

Replication of genome-wide association studies (GWAS) loci for fasting plasma glucose in African-Americans.

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Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive, MSC 5635, Bethesda, MD 20892, USA.



Chronically elevated blood glucose (hyperglycaemia) is the primary indicator of type 2 diabetes, which has a prevalence that varies considerably by ethnicity in the USA, with African-Americans disproportionately affected. Genome-wide association studies (GWASs) have significantly enhanced our understanding of the genetic basis of diabetes and related traits, including fasting plasma glucose (FPG). However, the majority of GWASs have been conducted in populations of European ancestry. Thus, it is important to conduct replication analyses in populations with non-European ancestry to identify shared loci associated with FPG across populations.


We used data collected from non-diabetic unrelated African-American individuals (n = 927) who participated in the Howard University Family Study to attempt to replicate previously published GWASs of FPG. Of the 29 single nucleotide polymorphisms (SNPs) previously reported, we directly tested 20 in this study. In addition to the direct test, we queried a 500 kb window centred on all 29 reported SNPs for local replication of additional markers in linkage disequilibrium (LD).


Using direct SNP and LD-based comparisons, we replicated multiple SNPs previously associated with FPG and strongly associated with type 2 diabetes in populations with European ancestry. The replicated SNPs included those in or near TCF7L2, SLC30A8, G6PC2, MTNR1B, DGKB-TMEM195 and GCKR. We also replicated additional variants in LD with the reported SNPs in ZMAT4 and adjacent to IRS1.


We identified multiple GWAS variants for FPG in our cohort of African-Americans. Using an LD-based strategy we also identified SNPs not previously reported, demonstrating the utility of using diverse populations for replication analysis.

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