Gestational Diabetes Induces Placental Genes for Chronic Stress and Inflammatory Pathways

The protocol was approved by the institutional review board of Case Western Reserve University. Volunteers gave informed written consent in accordance with the MetroHealth Medical Center guidelines. GDM was defined as an abnormal glucose tolerance during the third trimester according to the criteria defined by Carpenter and Coustan (9). All GDM subjects required chronic insulin therapy for glucose control. Maternal and cord blood samples were obtained at delivery. Neonatal anthropometric measurements were performed within 48 h of delivery. Neonatal body composition was estimated using Total Body Electrical Conductivity (EM-Scan HP-2 TOBEC, Springfield, IL).

Plasma glucose was measured by the glucose oxidase method with a glucose analyser (Yellow Springs Instrument, Yellow Springs, OH). Plasma insulin was assayed by radioimmunoassay as described (1). We estimated insulin sensitivity using a prediction model based on a significant correlation between the 1-h glucose screen and insulin sensitivity measured with the hyperinsulinemic-euglycemic clamp (2).

Placental biopsies (∼1 cm³) were randomly obtained from six intact cotyledons after dissecting out the basal and the chorial plates and snap-freezing them in liquid nitrogen. Total RNA was prepared from whole-villous tissue using CsCl gradient (10). RNA samples were electrophoresed to verify integrity, pooled, and reversed transcribed using Superscript first-strand synthesis (Invitrogen, Carlsbad, CA). This pooling strategy was used to minimize variations in structural content of the biopsies due to placental heterogeneity. cDNA served as a template to generate biotinylated cRNA by in vitro transcription (ENZO kit; Affymetrix). The quality of each fragmented cRNA evaluated with test microarrays (Test-3array; Affymetrix) was considered satisfactory when bioC, bioD, and cre were present and the 3′/5′ ratio of the polyA control subjects was <3. The 3′/5′ ratios for β-actin and GAPDH were 1.4 ± 0.2 and 1.2 ± 0.2, respectively. Fragmented cRNAs were spotted onto eight human U133 Affymetrix microarrays. Hybridization was performed according to the manufacturer’s instructions. Signal scanning and analysis were performed with Affymetrix equipment (Fluidics station, HPgene array scanner, and MAS 5.0 microarray suite).

To correct for hybridization efficiency, results were scaled to an average signal intensity of 1500. A serial four-step analysis was completed to select the significantly modified transcripts while minimizing false-positive genes. The first step excluded all probe sets with signal below the probe pair threshold (nc). Average background (67.8 ± 0.80) and scaled noise (3.7 ± 0.3) were calculated for each array and entered in the subsequent analysis. 1) Genes showing an absolute call of present (P-calls) according to MAS 5 algorithm. The average percentage of P-calls was 39.1 ± 2.8. 2) Genes showing a difference call of increased “I” or decreased “D.” 3) Genes with a difference in signal detection of at least 4.5 times the average background minus the scaled noise. The genes having satisfied these criteria were included in the fourth level of selection based on a fold change ≥2 or ≤−2 and consistent in at least two comparisons (Fig. 1). Functional clustering of the up- and downregulated genes was based on public databases according to the biological functions of their putative encoded proteins.

RT-PCR analysis was performed using a fluorescence temperature cycler (Lightcycler; Roche Molecular Diagnosis, Indianapolis, IN). Specific primers were designed within the 3′ coding region of the genes (sequences available upon request). Real-time reactions were carried out in duplicate, and amplicons were analyzed by generating melting curves with continuous measurement of fluorescence. The PCR products were separated on 1.5% agarose gel. Results were calculated as relative differences in target Ct values normalized to β-actin.

All data are presented as mean ± SE. Significance for statistical differences was calculated using a unpaired Student’s t test.

A total of 16 women with either normal glucose tolerance (control subjects) or GDM, who were recruited for the study, were matched for BMI and gestational age (Table 1). Insulin resistance was documented by a higher 1-h postchallenge blood and lower predicted insulin sensitivity compared with control subjects. This was observed despite satisfactory glycemic control with normal HbA_1c (5.4 vs. 5.1%) and normal fasting blood glucose (90.7 ± 11 vs. 86.5 ± 4.5 mg/dl). Higher plasma insulin levels in the GDM women reflect chronic exogenous insulin therapy. Plasma leptin and TNF-α levels were higher in women with GDM. Birth weights were similar in the two groups; however, placental weights were increased with GDM (585 ± 64 vs. 434 ± 20 g, P < 0.001), and neonates of GDM mothers were fatter based on percent fat mass (15.1 ± 1.2 vs. 12.6 ± 1.3, P < 0.001) and ponderal index (2.9 ± 0.2 vs. 2.7 ± 0.1 g/cm³, P < 0.001). Plasma insulin levels were higher in neonates of GDM mothers (33.3 ± 9.6 vs. 12.5 ± 1.6 μU/ml, P < 0.01).

To characterize gene targets that determine altered placental functions, the global pattern of gene expression was analyzed in placenta from matched control subjects and GDM pregnancies. Of 22,823 gene sequences surveyed, 8,627 ± 172 were present in control subjects and 9,378 ± 165 in GDM, representing placental transcriptome. The consecutive screening filters that we applied allowed us to narrow these numbers to 2,682 genes eligible for analysis. The average fold change value was then calculated for all pairwise comparisons, resulting in the final selection of 435 genes significantly modified in GDM.

The genes included in the final selection represented 2.0% of the total gene sequences analyzed and 5.6% of the placental transcriptome. The 435 genes identified as significantly modified refer to genes whose transcriptional pattern was altered in GDM with 254 upregulated and 181 downregulated genes. Functional clustering of the 435 genes followed by quantitative ranking identified six major subgroups of genes (Fig. 2). They included genes associated with 1) stress-activated and inflammatory responses (n = 79), 2) endothelial structure and differentiation (n = 41), 3) substrate metabolism (n = 39), 4) transport and trafficking (n = 34), 5) translation (n = 33), and 6) signal transduction (n = 23). Genes related to inflammatory responses represented the largest cluster, accounting for up to 18% of the modified genes. Additional single clusters, each accounting for <5% of the modified genes, were those associated with transcription and early genes (n = 17), immunity and cell surface antigens (n = 19), hormones (n = 15), growth factors (n = 13), cell growth and maintenance (n = 9), and mitochondrial (n = 7). They represented 19% of the modified genes (Fig. 2, other clusters). The 103 genes with unknown functions were listed under nonclassified genes. The list of the two main clusters is given in Table 2, and the complete listing of the 435 significantly modified genes is available at http://www.ncbi.nlm.nih.gov/geo (accession no. GPL130). Modifications observed with microarrays were validated by real-time PCR analysis of the same RNA samples (Fig. 3). We analyzed mRNA expression for 22 genes of interest and were able to confirm 21 modifications with either increased or decreased expression (Fig. 3).

Expression profiling of the placenta revealed that genes regulating inflammatory responses and endothelial reorganization represent the two main functional clusters altered in GDM. With a total of 110 genes, they account for one-third of the modified genes, reflecting a state of chronic inflammation with signs of major vascular dysfunction. This is further supported by the findings that most of the genes were upregulated (75 of 110), as compared with a balanced ratio observed in the other gene categories.

The diabetic placentas analyzed in this study were obtained from women with marked glucose intolerance and insulin resistance (Table 1). Growing evidence in the literature suggests that insulin resistance is the result of an inflammatory milieu. Plasma levels of several markers of inflammation, C-reactive protein, lipopolysaccharide (LPS), interleukin (IL)-6, TNF-α, and leptin are elevated in individuals with obesity and type 2 diabetes (11–14). TNF-α has been recognized as the most prominent factor contributing to insulin resistance in obesity and diabetes (15–19). The changes in placental gene expression that we report herein further support our hypothesis that a panel of proinflammatory cytokines and cellular mediators act in concert with TNF-α to either relay or potentiate its action.

IL-1 and TNF-α induce synergistic pleiotropic responses that profoundly affect production of extracellular matrix (ECM) proteins. Increased expression of fibronectin, laminin β-1, and metalloproteinases may induce a fibrotic response and disrupt the structural integrity of placental endothelial cells as in other cell types (20–22). Increase in metalloproteinases may also influence angiogenesis by degrading matrix molecules, loosening the cellular network, and releasing growth factors sequestered in the ECM (23). Several other modified genes are directly modulated by IL-1 and TNF-α. For example, TNF-induced CG12 accompanies inflammatory reactions in atherosclerotic regions (24), and acute-phase reactants, such as LPS, pentaxin-related gene (PTX-3), calgranulin, and thrombospondin, are key components of impaired vascular function (25–28). The increased expression of IL-8 receptor, IL-1 receptor, and the short form of leptin receptor points to an activation of the signaling pathways recruited by these cytokines. The activation of leptin gene expression in diabetic placenta is in keeping with its transcriptional regulation (29). The role of placental leptin has raised several hypotheses regarding its autocrine action within the placenta without reaching definite conclusions (30). The increase in short leptin receptor supports the view that this isoform transduces proinflammatory responses in the placenta.

Besides the metabolic control of adipose tissue homeostasis, leptin elicits inflammatory, immunological, and vascular responses (31,32). Administration of IL-6, LPS, and TNF-α to mice increases leptin production, suggesting that they induce concurrent effects in addition to the development of inflammation (33). The coordinated action of ILs, TNF-α, and leptin on placental genes may explain part of a fibrotic response via disruption of extracellular matrix components and vascular architecture (Fig. 4). These transcriptional changes are in line with the modifications of placental morphology and composition documented in diabetes with increased parenchymal tissue cellularity, alterations of surface expression of junctional proteins, and enhanced feto-placental angiogenesis (34–36). The downstream effectors of TNF-α, ILs, and leptin activate p38 MAPK and JNK, which belong to the family of SAPK stress kinases abnormally activated in obesity and insulin resistance (37,38). MAPK and JNK/SAPK pathways cooperate to phosphorylate ras GTPases of the rho family, such as mig-6, a molecular adaptor triggering cellular hypertrophy in diabetic nephropathy (39,40). The upregulation of placental mig-6 expression, makes this gene a particularly attractive candidate as a mediator of placental overgrowth of diabetes.

The array of genes activated by TNF-α, leptin, and ILs also include several transcription factors, GATA, CREB-binding protein, CEBP-α, and AP-1, all of which are involved in the regulation of inflammatory processes (41). Upon activation, they are able to turn on genes involved in signal transduction related to stress and chronic inflammation (Fig. 5). Modifications of the expression of genes assigned to other functional clusters, signal transduction, growth factors, and cytoskeleton reorganization are also likely to contribute to global placental dysfunction. This may be particularly relevant for genes encoding mediators of the insulin signaling cascade, such as the insulin receptor itself, p 110 phosphatidylinositol-kinase, several small G proteins of the ras, rab, and rho families possibly recruited as a result of high insulin levels in maternal and fetal blood.

The best representation of subclasses of genes involved in inflammatory pathways represents the first characterization of an inflammatory response induced through a chronic diabetic insult. No such responses were reported in skeletal muscle of type 2 diabetic patients (42,43), and changes in diabetic mice were related to substrate and energy metabolism (44). These differences could result from cell type specificities or from a greater insulin resistance, as demonstrated by the need for insulin therapy to achieve adequate glucose control in GDM patients. Glucose intolerance and hyperinsulinemia are significant before conception in women who go on to develop GDM (45). A causal role of hyperglycemia has been suggested in the immune activation of diabetes (46). Therefore, the early onset of insulin resistance may initiate an endocrine feedback between mother and placenta with enhanced susceptibility to cytokine that culminate in the inflammation milieu that we describe.

This study provides the first molecular basis linking GDM to modifications of placental transcriptome. It suggests a postreceptor convergence of multiple signal transduction pathways mediated through TNF-α, IL-1, and leptin. Therefore, the fetus of diabetic mothers develops in an inflammatory milieu. We speculate that changes in expression of specific placental genes may be a leading cause to adverse fetal programming.

T.R. is a recipient of a fetal diagnosis fellowship, University of Milan, Italy. This study is supported by grants from the National Institutes of Health (RO-1 HD22965 to P.C.) and Alfediam Roche Pharma (to S.H.-D.M).

We thank Patrick Leahy and the staff of the Gene Array facility at Case Western Reserve University for advice and excellent technical support.