Stable Patterns of Gene Expression Regulating Carbohydrate Metabolism Determined by Geographic Ancestry

Individuals of African descent in the United States suffer disproportionately from diseases with a metabolic etiology (obesity, metabolic syndrome, and diabetes), and from the pathological consequences of these disorders (hypertension and cardiovascular disease). Using a combination of genetic/genomic and bioinformatics approaches, we identified a large number of genes that were both differentially expressed between American subjects self-identified to be of either African or European ancestry and that also contained single nucleotide polymorphisms that distinguish distantly related ancestral populations. Several of these genes control the metabolism of simple carbohydrates and are direct targets for the SREBP1, a metabolic transcription factor also differentially expressed between our study populations. These data support the concept of stable patterns of gene transcription unique to a geographic ancestral lineage. The coordinated transcriptional adaptation of carbohydrate metabolism to dietary environmental pressures suggests a genetic and transcriptional mechanism for the disproportionate levels of obesity, diabetes, and cardiovascular disease observed in Americans with African ancestry. Keywords: Ancestry-dependent gene expression, functional genomics, personalized medicine, multi-factoral disease, nutrition, diabetes We utilized a “sample x reference” experimental design strategy in which RNA extracted from human peripheral blood mononuclear cells was hybridized to the microarray slide in the presence of labeled Universal Human Reference RNA (UHRR, Stratagene, LaJolla, CA). A total of 161 subjects were used in this analysis. Briefly, five hundred nanograms of total RNA were used for gene expression profiling following reverse transcription and T-7 polymerase-mediated amplification/labeling with Cyanine-5 CTP. Labeled subject cRNA was co-hybridized to Agilent G4112A Whole Human Genome 44K oligonucleotide arrays with equimolar amounts of Cyanine-3 labeled UHRR. Slides were hybridized, washed, and scanned on an Axon 4000b microarray scanner. The data were processed using GenePix Pro 6 software