Early alterations of the immune transcriptome in cultured progenitor cells from obese African-American women

Abstract

Progenitor cells (PCs) are key components of vasculogenic remodeling and hematopoietic development. Decreases in the number and function of angiogenic progenitors have been observed in coronary artery disease, hypertension, and diabetic vasculopathy. Several recent studies have also demonstrated a close relationship between increased visceral fat and cardiovascular disease, implying an association between obesity and vascular dysfunction. However, very little is known about the role of PCs in obesity. We generated whole genome expression profiles of cultured PCs from 18 obese and 6 lean African-American women on Agilent microarrays and analyzed the data through bioinformatic pathway analysis using multiple databases and analytic tools. False-discovery rates (FDR) were calculated to assess statistical significance while controlling for multiple testing. We identified 1,145 upregulated and 2,257 downregulated genes associated with obesity (1.5-fold or greater absolute fold-change). Pathway analysis further identified a statistically significant downregulation of immune-response pathways in the obese subjects, including T-cell receptor signaling, natural killer cell signaling, and chemokine-signaling pathways (FDR <5%). Chemokine gene-expression patterns were consistent with an angiogenic-angiostatic imbalance and a downregulation of CXCR3 receptor-mediated signaling in the PCs from obese subjects. Overall, these findings reveal a novel transcriptional signature in cultured PCs from obese African-American women and further suggest that obesity-associated immune-compromise may originate much earlier in cellular development than currently appreciated. Clinically, this may translate into a lengthier period of immune dysregulation in obese subjects exposing them to greater risks of infection and other morbidities.

Figure 1

Extracellular matrix and cell-type specific marker gene expression in cultured progenitor cells from obese and lean subjects. Gene-expression signals (log base 2) of extracellular matrix markers and cell-type markers in progenitor cells from 13 obese (black bars) and 6 lean (white bars) subjects. All gene-expression signals were obtained from Agilent microarrays with the exception of CD14, CD34, and KDR which were assessed by quantitative PCR.

Figure 2

Pathway analyses by gene set enrichment (GSEA). (a) MA plots of log intensity averages (x axis; mean gene expression in obese and lean groups) vs. log ratios (y axis; mean differences between obese and lean log signals). Genes in gray are all genes from the Agilent microarray that were considered for analysis after filtering. Genes shown as crosses belong to the top obese-downregulated pathway (T-cell receptor signaling) and genes shown as open circles constitute the top obese-upregulated pathway (olfactory signal transduction). The regression line of best fit passes through zero on the y axis. (b) Concordance-significance plot quantifying the significance of the overlap among the GSEA selected pathways in comparison to randomly selected pathways. Negative of the log P values are plotted on the×axis and concordance measures, along with their confidence intervals, are plotted on the y axis. Pairwise concordance of gene lists from Kyoto Encyclopedia of Genes and Genomes (KEGG), Biocarta, and Custom are as indicated. Comparisons of selected gene lists with randomly selected gene lists are indicated by the “Random” identifier. Concordance values close to zero indicate no concordance among gene lists.

Figure 3

Pathway enrichment by Ingenuity Pathway analysis (IPA). Identification of top 10 obese-downregulated canonical pathways identified by IPA. Pathway names are indicated on the×axis and the statistical significance of gene-set over-representation is indicated on the y axis (–log base 10 scale). The numbers at the top of each bar is a ratio of the number of genes in each pathway present in the obese downregulated dataset to the total number of genes representing that pathway in the IPA knowledge base.

Figure 4

Chemokine gene expression in obese and lean subjects. Differential expression of chemokines is quantified by the fold-change in gene-expression signals in obese compared to lean subjects (from microarray). Chemokines are classified as described in the text. The symbols indicate the level of statistical significance for differential expression (^$P < 0.05; ^#P < 0.01; *P < 0.005). The fold-change axis (y axis) is truncated to accommodate a large range of fold-change values.

Figure 5

Schematic of the obese-derived progenitor cell transcriptome. A summary of the results observed in the present study indicates a net downregulation of the immune response pathways and upregulation of selected proinflammatory cytokines and genes related to a spectrum of cardiovascular disorders in the obese-derived progenitor cells (PCs). Additionally, chemokine gene expression suggests an angiostatic–angiogenic imbalance resulting in a net proangiogenic milieu in the cells. Immune compromise may be responsible for increased infections and cancers whereas the proinflammatory, net angiogenic and higher cardiovascular disk (CVD) risk gene expression may lead to cardiovascular dysfunction in the obese. In the figure, the thickness of the rectangles is qualitatively proportional to the strength of the statistical significance of the findings.