Transcriptomic Analysis Reveals Novel Mechanisms Mediating Islet Dysfunction in the Intrauterine Growth–Restricted Rat

Transcriptomic Analysis Reveals Novel Mechanisms Mediating Islet Dysfunction in the Intrauterine... Abstract Intrauterine growth restriction (IUGR) increases the risk of type 2 diabetes developing in adulthood. In previous studies that used bilateral uterine artery ligation in a rat model of IUGR, age-associated decline in glucose homeostasis and islet function was revealed. To elucidate mechanisms contributing to IUGR pathogenesis, the islet transcriptome was sequenced from 2-week-old rats, when in vivo glucose tolerance is mildly impaired, and at 10 weeks of age, when rats are hyperglycemic and have reduced β-cell mass. RNA sequencing and functional annotation with Ingenuity Pathway Analysis revealed temporal changes in IUGR islets. For instance, gene expression involving amino acid metabolism was significantly reduced primarily at 2 weeks of age, but ion channel expression, specifically that involved in cell-volume regulation, was more disrupted in adult IUGR islets. Additionally, we observed alterations in the microenvironment of IUGR islets with extracellular matrix genes being significantly increased at 2 weeks of age and significantly decreased at 10 weeks. Specifically, hyaluronan synthase 2 expression and hyaluronan staining were increased in IUGR islets at 2 weeks of age (P < 0.05). Mesenchymal stromal cell–derived factors that have been shown to preserve islet allograft function, such as Anxa1, Cxcl12, and others, also were increased at 2 weeks and decreased in adult islets. Finally, comparisons of differentially expressed genes with those of type 2 diabetic human islets support a role for these pathways in human patients with diabetes. Together, these data point to new mechanisms in the pathogenesis of IUGR-mediated islet dysfunction in type 2 diabetes. Human and animal studies have shown that uteroplacental insufficiency is associated with intrauterine growth restriction (IUGR) and development of metabolic sequelae such as obesity and type 2 diabetes in adulthood (1–4). To better understand mechanisms by which IUGR results in the development of diabetes, we have used bilateral uterine artery ligation, in which blood supply to developing rat fetuses is decreased, resulting in fetal growth restriction and decreased birth weight (5, 6). β-cell dysfunction, immune cell infiltration in the pancreas, and islet capillary rarefaction are observed even before delivery in the IUGR rat (6–8). At 2 weeks of age, IUGR pups exhibit impaired insulin secretion that is due, in part, to mitochondrial dysfunction and inflammation in the islet (7–10). Glucose homeostasis progressively worsens with age such that, at 10 weeks, IUGR rats begin to display fasting hyperinsulinemia, mild reductions in β-cell mass, and diminished glucose-stimulated insulin secretion (GSIS) and leucine-stimulated insulin secretion (6–8, 11). Early postnatal interventions, with the GLP-1 analog, exendin-4, or immunological IL-4 neutralization, rescue low-birth-weight pups from later-life diabetes (7, 9, 10, 12, 13). Normalization of endocrine pancreas maturation and function by these two seemingly disparate postnatal interventions suggests diverse mechanisms engender β-cell dysfunction in IUGR rats. Transcriptome sequencing is an effective tool for uncovering unknown mechanisms of islet dysfunction. In a sheep model of hyperthermia-induced IUGR, RNA sequencing (RNAseq) of fetal islets identified more than 1000 differentially expressed genes, many representing newly identified genes in pathways known to be disrupted in IUGR animals (14). However, when sequencing the fetal islet transcriptome, it is impossible to ascertain which changes will persist after the islet’s postnatal remodeling, and makes it more difficult to distinguish detrimental changes in gene expression and those that may be compensatory. To this point, islet transcriptomic analysis performed in Goto-Kakizaki diabetic rats at five time points throughout glucose metabolic dysfunction showed that gene expression patterns differ temporally, as do the biological pathways they represent (15). However, because the Goto-Kakizaki rat represents a polygenic model of diabetes (16) with pathological end points such as islet fibrosis (17) that do not manifest in IUGR-mediated islet pathology, the study provides limited relevance to our surgical model of IUGR and subsequent islet dysfunction. In the current study, by sequencing the transcriptome at 2 and 10 weeks of age, we elucidate mechanisms that mediated islet dysfunction in our IUGR model. Finally, we show clinical relevance by comparing genes previously identified as differentially expressed in diabetic human islets with those in IUGR islets and identify common genes and shared pathways. Materials and Methods Animal model The animals and procedures used in this study were approved by the Animal Care Committee of The Children’s Hospital of Philadelphia and the Perelman School of Medicine at the University of Pennsylvania. Our animal model has been described previously (6). Briefly, at embryonic day 18.5, pregnant Sprague Dawley rats were anesthetized with isoflurane and bilateral uterine artery ligation was performed (6). A sham operation was performed in control rats. On the day of delivery, pups were weighed to confirm IUGR and litters were culled to eight to equilibrate postnatal nutrient availability. Dams and offspring were given ad libitum access to water and standard rodent chow. At 2 weeks and 10 weeks of age, pancreata were excised under ketamine and xylazine anesthesia, followed by islet isolation. Islets were pooled from both sexes at 2 weeks of age because previous phenotypic studies at this age were conducted in pooled samples from both sexes (8). Only male rats were studied at 10 weeks of age, because previous studies have shown the diabetic phenotype in adulthood is male-sex specific (8). Islet isolation Two pancreata per litter were pooled for each 2-week sample (three litters were studied); 10-week pancreata were not pooled, and pancreata from three different litters were used. Pancreatic islets were isolated as previously described (8). Briefly, pancreata were digested via ductal perfusion with 10 mg/mL Collagenase P (Roche) in Hanks balanced salt solution supplemented with 4 mM NaCO3 and 1% bovine serum albumin. After ductal perfusion, excised pancreata were digested for 15 minutes at 37°C. Tissue was then washed in cold, supplemented Hanks balanced salt solution without collagenase. Islets were isolated by histopaque gradient centrifugation and washed. Total RNA isolation and RNAseq library preparation Total RNA was extracted from freshly isolated islets using TRIzol Reagent (Invitrogen) and then the Qiagen RNeasy Mini kit following manufacturer’s instructions. RNA (1 µg) from samples with RNA integrity numbers between 7 and 9.2 were used to generate complementary DNA. RNAseq libraries were made using the Illumina TruSeq Stranded Total RNA LT Sample Prep Kit with Ribo-Zero Gold. RNAseq and gene expression analysis RNAseq libraries were single-end sequenced to 100 bp on an Illumina hiSeq2000 system. All the RNAseq data were mapped using the Tophat package against the rat genome (version rn5). Differential analysis was done using edgeR package (Bioconductor). Differentially regulated genes were identified using a Q-value cutoff of 0.05. Hierarchical clustering analysis was performed using the gene expression values from all conditions and replicates for previously selected differential genes. Specifically, we used Ward’s criterion for genes with 1 − (correlation coefficient) as a distance measure. Clustering heatmaps were constructed using a z-score that was scaled across samples for each gene. Functional analysis was conducted using Ingenuity Pathway Analysis (IPA; Qiagen, Redwood City, CA). Uploaded data sets contained gene identifiers, fold changes, counts per million and Q-values. Significance filtering was used to increase the focus and specificity of analysis. Core analysis was performed only on genes having a fold change ≥1.5, counts per million ≥4, and Q-value < 0.05. The data discussed in this publication have been deposited in the National Center for Biotechnology Information Gene Expression Omnibus (18) and are accessible through GEO Series accession number GSE104017 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE104017). Quantitative polymerase chain reaction Quantitative polymerase chain reaction (qPCR) was performed on biological replicates to verify changes in select genes in islets from three to eight animals, each from a different litter and from a different cohort than that of the animals used for RNAseq. Reverse transcription was performed using iScript cDNA Synthesis Kit (BioRad). QuantStudio 7 Flex Real-Time PCR System (Thermo Fisher Scientific, Waltham, MA) was used for qPCR. The following Taqman Gene Expression Assays (Applied Biosystems) were used: Emilin3 (Rn01750280), Matn4 (Rn01423881), Bcat2 (Rn00574455), Gatm (Rn00578954), Kcnq1 (Rn00583376), Ano1 (Rn01474520), Aqp8 (Rn00569732), Trpa1 (Rn01473803), and Cltc (Rn00693501). Cltc gene expression was used as the endogenous control. Relative fold change was calculated using the ΔCT method. Histochemistry Excised pancreata were fixed using formalin-free zinc fixative (BD Pharmigen) for 48 hours. Tissues were embedded in paraffin and sectioned. Slides were stained with biotinylated hyaluronic acid (HA) binding protein (EMD Millipore). Staining was performed as previously described (16). Slides were incubated with 5 μg/mL biotinylated HA binding protein in 0.1% bovine serum albumin in phosphate-buffered saline overnight at 4°C in a humidified chamber. Vectastain ABC reagent was applied for 1 hour at room temperature. Slides were rinsed and stained using 3,3'-diaminobenzidine and Chromogen (Dako), and counterstained with hematoxylin (Azer Scientific). To quantify staining, slides were digitally scanned at ×40 magnification on an Aperio Scanscope CS-O (brightfield; Leica Biosystems), and analyzed by ImageScope version 12.2.2.5015 (Leica Biosystems) using Aperio-Color Deconvolution version 9.1 algorithm. Islets were identified, and the area of HA staining was calculated within the intraislet and peri-islet regions by multiplying percent positive staining of HA within these regions with total stained area and the product was normalized to the total analysis area. Peri-islet region was defined as the region around the islets at approximately 5 μm from the outer edge of the islet, as described previously (19). Results IUGR altered the islet transcriptome at 2 weeks and 10 weeks of age Next-generation sequencing of pancreatic islets isolated from IUGR and control rats detected 26,312 and 27,703 gene transcripts at 2 weeks and 10 weeks, respectively (Supplemental Table 1). Differential gene expression was observed for 793 genes (n = 220 increased, n = 573 decreased) and 2184 genes (n = 524 increased, n = 1660 decreased) at 2 and 10 weeks, respectively (Fig. 1). Recent RNAseq from fetal IUGR sheep islets revealed a similar number of differentially expressed genes and a similar proportion of those increased to those decreased (14). Previous studies by us and other laboratories have shown that differentially expressed genes correlate with fold change determined via qPCR (14, 20). Therefore, we confirmed by qPCR gene expression of only eight genes (Emilin3, Matn4, Bcat2, Gatm, Kcnq1, Ano1, Aqp8, and Trpa1) that were differentially expressed at both time points examined. Fold changes from qPCR were consistent with fold change in our RNAseq data set (Supplemental Fig. 1). Figure 1. View largeDownload slide RNA sequencing revealed differential gene expression in IUGR rat islets compared with that in controls at 2 and 10 weeks of age. (A) A heat map of genes differentially expressed between groups (n = 3 per group). Differential gene expression was defined as −1.5 ≤ fold change ≥ 1.5, counts per million ≥ 4, and Q ≤ 0.05. (B) A Venn diagram illustrating overlap of differentially expressed genes between IUGR and control islets based on fold change at 2 and 10 weeks of age. Figure 1. View largeDownload slide RNA sequencing revealed differential gene expression in IUGR rat islets compared with that in controls at 2 and 10 weeks of age. (A) A heat map of genes differentially expressed between groups (n = 3 per group). Differential gene expression was defined as −1.5 ≤ fold change ≥ 1.5, counts per million ≥ 4, and Q ≤ 0.05. (B) A Venn diagram illustrating overlap of differentially expressed genes between IUGR and control islets based on fold change at 2 and 10 weeks of age. To identify pathways disrupted by IUGR at 2 and 10 weeks of age, IPA was used for functional annotation of differentially expressed genes. Multiple pathways were altered in IUGR rats at both ages, including downregulation of pathways involving glucose use and mitochondrial respiration, and upregulation of inflammation and insulin resistance (Table 1), which are supported by previous functional studies in IUGR rats (6, 8, 11). Additionally, we identified disruption of unanticipated pathways that may contribute to IUGR islet pathogenesis (Table 1). In the following subsections, these pathways and their possible contribution to the temporal progression of IUGR islet dysfunction are discussed. Table 1. Ingenuity Pathway Analysis of Differentially Expressed Genes   Islets at 2 Weeks    Islets at 10 Weeks  Category  P Value  Activation Z-Score  Category  P Value  Activation Z-Score  Canonical pathways  Canonical pathways   Fibrosis/stellate cell activation  6.24E-05  —   Fibrosis/stellate cell activation  2.84E-20  —   Gap junction signaling  9.33E-03  —   Integrin signaling  3.80E-06  −5.568   Type 2 diabetes mellitus signaling  1.04E-02  1.890   PAK signaling  3.95E-05  −3.900   Tight junction signaling  1.58E-02  —   Regulation of the EMT pathway  6.46E-05  —   Acute phase response  1.71E-02  1.897   Tight junction signaling  1.66E-03  —   ILK signaling  1.51E-02  1.897   Paxillin signaling  1.82E-03  −3.32   cAMP-mediated signaling  4.24E-02  −2.111   HIPPO signaling  2.00E-03  0.00   Leukocyte extravasation signaling  4.65E-02  1.890   Gap junction signaling  2.63E-03  —         Epithelial adherens junction signaling  1.07E-02  —         FAK signaling  1.35E-02  —         ILK signaling  2.24E-02  −3.71  Upstream regulators  Upstream regulators   Activated     Activated      TGF-β1  9.30E-20  4.557    α-Catenin  2.45E-36  7.566    IL-1β  1.02E-07  4.157    COL18A1  2.42E-13  5.502    TNF  5.29E-12  3.026    CD3  9.95E-04  4.732    AGT  3.64E-03  2.331    TRIM24  9.03E-07  4.558    F2  4.65E-09  2.306    SMAD7  2.86E-11  4.394    IL-4  3.71E-08  1.396         Inhibited   Inhibited    α-Catenin  1.62E-04  −3.422    VEGF  1.06E-26  −7.890    UCP1  4.19E-07  −3.051    Il-1β  1.35E-50  −7.651    HNF1A  5.45E-07  −3.033    TGF-β1  1.05E-72  −7.629    PTF1A  8.46E-06  −2.959    IFN-γ  3.85E-40  −7.022    NR5A2  2.61E-13  −2.905    TNF  6.58E-71  −5.860  Diseases and functions, top five by P value  Diseases and functions, top five by P value   Quantity of carbohydrate  1.36E-14  0.011   Cell movement  1.13E-73  −8.646   Metabolism of amino acids  1.53E-14  −1.134   Migration of cells  6.94E-70  −8.519   Migration of cells  1.16E-10  0.764   Angiogenesis  3.54E-63  −6.832   Invasion of cells  2.59E-10  2.093   Proliferation of cells  2.13E-62  −3.502   Cell movement  3.20E-10  0.556   Vasculogenesis  2.53E-62  −6.349   Upregulated   Upregulated    Recruitment of leukocytes  4.68E-07  3.134    Edema  4.42E-18  5.997    Inflammation of pancreas  6.98E-09  2.355    Inflammation of organ  1.60E-18  3.011    Cell spreading  3.11E-04  2.239    Glucose metabolism disorder  1.79E-22  2.862    Adhesion of fibroblasts  1.24E-05  2.132    Insulin resistance  1.82E-12  2.056    Formation of focal adhesions  8.19E-08  2.016    Fibrosis  5.09E-16  1.906    Epithelial mesenchymal transition  8.81E-06  1.567    Peripheral vascular disease  6.32E-17  1.683    Glucose metabolism disorder  9.04E-06  1.554    Infarction  1.94E-13  1.555    Fibrogenesis  9.89E-05  1.428    Apoptosis  1.57E-44  1.133   Downregulated   Downregulated    Assembly of cells  3.25E-05  −2.057    Angiogenesis  3.54E-63  −6.832    Endothelial cell development  6.98E-05  −1.919    Leukocyte migration  1.22E-29  −6.408    Use of d-glucose  7.56E-06  −1.706    Microtubule dynamics  4.68E-20  −5.054    Consumption of oxygen  2.45E-06  −1.601    Cell spreading  3.90E-16  −4.851    Angiogenesis of lesion  2.30E-05  −1.503    Metabolism of carbohydrate  1.89E-15  −4.760    Quantity of secretory structure  3.98E-04  −1.333    Adhesion of epithelial cells  4.08E-12  −3.658    Quantity of insulin in blood  8.14E-09  −1.235    Organization of actin cytoskeleton  3.33E-15  −3.296    Islets at 2 Weeks    Islets at 10 Weeks  Category  P Value  Activation Z-Score  Category  P Value  Activation Z-Score  Canonical pathways  Canonical pathways   Fibrosis/stellate cell activation  6.24E-05  —   Fibrosis/stellate cell activation  2.84E-20  —   Gap junction signaling  9.33E-03  —   Integrin signaling  3.80E-06  −5.568   Type 2 diabetes mellitus signaling  1.04E-02  1.890   PAK signaling  3.95E-05  −3.900   Tight junction signaling  1.58E-02  —   Regulation of the EMT pathway  6.46E-05  —   Acute phase response  1.71E-02  1.897   Tight junction signaling  1.66E-03  —   ILK signaling  1.51E-02  1.897   Paxillin signaling  1.82E-03  −3.32   cAMP-mediated signaling  4.24E-02  −2.111   HIPPO signaling  2.00E-03  0.00   Leukocyte extravasation signaling  4.65E-02  1.890   Gap junction signaling  2.63E-03  —         Epithelial adherens junction signaling  1.07E-02  —         FAK signaling  1.35E-02  —         ILK signaling  2.24E-02  −3.71  Upstream regulators  Upstream regulators   Activated     Activated      TGF-β1  9.30E-20  4.557    α-Catenin  2.45E-36  7.566    IL-1β  1.02E-07  4.157    COL18A1  2.42E-13  5.502    TNF  5.29E-12  3.026    CD3  9.95E-04  4.732    AGT  3.64E-03  2.331    TRIM24  9.03E-07  4.558    F2  4.65E-09  2.306    SMAD7  2.86E-11  4.394    IL-4  3.71E-08  1.396         Inhibited   Inhibited    α-Catenin  1.62E-04  −3.422    VEGF  1.06E-26  −7.890    UCP1  4.19E-07  −3.051    Il-1β  1.35E-50  −7.651    HNF1A  5.45E-07  −3.033    TGF-β1  1.05E-72  −7.629    PTF1A  8.46E-06  −2.959    IFN-γ  3.85E-40  −7.022    NR5A2  2.61E-13  −2.905    TNF  6.58E-71  −5.860  Diseases and functions, top five by P value  Diseases and functions, top five by P value   Quantity of carbohydrate  1.36E-14  0.011   Cell movement  1.13E-73  −8.646   Metabolism of amino acids  1.53E-14  −1.134   Migration of cells  6.94E-70  −8.519   Migration of cells  1.16E-10  0.764   Angiogenesis  3.54E-63  −6.832   Invasion of cells  2.59E-10  2.093   Proliferation of cells  2.13E-62  −3.502   Cell movement  3.20E-10  0.556   Vasculogenesis  2.53E-62  −6.349   Upregulated   Upregulated    Recruitment of leukocytes  4.68E-07  3.134    Edema  4.42E-18  5.997    Inflammation of pancreas  6.98E-09  2.355    Inflammation of organ  1.60E-18  3.011    Cell spreading  3.11E-04  2.239    Glucose metabolism disorder  1.79E-22  2.862    Adhesion of fibroblasts  1.24E-05  2.132    Insulin resistance  1.82E-12  2.056    Formation of focal adhesions  8.19E-08  2.016    Fibrosis  5.09E-16  1.906    Epithelial mesenchymal transition  8.81E-06  1.567    Peripheral vascular disease  6.32E-17  1.683    Glucose metabolism disorder  9.04E-06  1.554    Infarction  1.94E-13  1.555    Fibrogenesis  9.89E-05  1.428    Apoptosis  1.57E-44  1.133   Downregulated   Downregulated    Assembly of cells  3.25E-05  −2.057    Angiogenesis  3.54E-63  −6.832    Endothelial cell development  6.98E-05  −1.919    Leukocyte migration  1.22E-29  −6.408    Use of d-glucose  7.56E-06  −1.706    Microtubule dynamics  4.68E-20  −5.054    Consumption of oxygen  2.45E-06  −1.601    Cell spreading  3.90E-16  −4.851    Angiogenesis of lesion  2.30E-05  −1.503    Metabolism of carbohydrate  1.89E-15  −4.760    Quantity of secretory structure  3.98E-04  −1.333    Adhesion of epithelial cells  4.08E-12  −3.658    Quantity of insulin in blood  8.14E-09  −1.235    Organization of actin cytoskeleton  3.33E-15  −3.296  Abbreviation: —, IPA did not generate an activation z score. View Large Effects of IUGR on the islet microenvironment in 2- and 10-week-old rats IUGR alters extracellular matrix and cytoskeleton organization The islet extracellular matrix (ECM) plays a vital role in cell survival, proliferation, and function (21–23). We observed multiple differentially expressed ECM genes, including those encoding collagens, laminins, fibulins, and tenascins, as well as lysyl oxidase–like enzymes that are responsible for cross-linking collagen and subsequent stiffening of the ECM (24, 25)(Fig. 2). Figure 2. View largeDownload slide Differential gene expression modulating the islet microenvironment. (A) A heat map of differentially expressed ECM genes. (B) A heat map of differentially expressed plasma membrane–associated genes involved in cellular attachment. Also included are plasma membrane–associated genes that modulate the external environment, such as Has1 and Has2 genes that mediate outside-in signal transduction, including Cav1 and Tjp3. Genes are listed in ascending order according to fold change relative to control at 2 weeks of age and then by 10 weeks of age. *Gene was differentially expressed in IUGR islets at 2 weeks of age; #gene was differentially expressed in IUGR islets at 10 weeks of age. Figure 2. View largeDownload slide Differential gene expression modulating the islet microenvironment. (A) A heat map of differentially expressed ECM genes. (B) A heat map of differentially expressed plasma membrane–associated genes involved in cellular attachment. Also included are plasma membrane–associated genes that modulate the external environment, such as Has1 and Has2 genes that mediate outside-in signal transduction, including Cav1 and Tjp3. Genes are listed in ascending order according to fold change relative to control at 2 weeks of age and then by 10 weeks of age. *Gene was differentially expressed in IUGR islets at 2 weeks of age; #gene was differentially expressed in IUGR islets at 10 weeks of age. HA is an ECM component present in mouse and human islet ECM, and recent studies suggest HA may be a novel inflammatory mediator of islet pathology in type 1 and 2 diabetes (26). In 2-week-old IUGR islets, gene expression of hyaluronan-synthesizing enzyme, Has2, was significantly increased (Fig. 2). To determine whether changes in Has2 gene expression correlated with HA levels, 2-week-old control and IUGR pancreata were histochemically stained for HA (Fig. 3). Peri-islet HA staining was increased in IUGR islets from 2-week old animals, whereas intraislet HA staining was decreased, the latter being reflective of diminished capillary density observed in previous studies (8, 9). Figure 3. View largeDownload slide Islets of 2-week-old IUGR rats exhibit increased HA protein staining. (A) ×200 Magnification of control and IUGR pancreas stained with biotinylated-HA binding protein (EMD Millipore) with hematoxylin counterstain. (B) Quantification of HA-positive area. One section from five animals was analyzed. The HA-positive area was taken as the percentage of the total analysis area of the region. *P < 0.05 (t test). Figure 3. View largeDownload slide Islets of 2-week-old IUGR rats exhibit increased HA protein staining. (A) ×200 Magnification of control and IUGR pancreas stained with biotinylated-HA binding protein (EMD Millipore) with hematoxylin counterstain. (B) Quantification of HA-positive area. One section from five animals was analyzed. The HA-positive area was taken as the percentage of the total analysis area of the region. *P < 0.05 (t test). Integrins and syndecans are transmembrane proteins that adhere to the ECM and transduce signals intracellularly through interactions with the cytoskeleton and associated second messengers. In the islet, they enhance insulin secretion and β-cell survival (27–30). Interestingly, expression of integrin β subunit 3 and syndecan 4, was increased in 2-week-old IUGR islets (Fig. 2). Moreover, IPA predicted upregulation of integrin-linked kinase (ILK) signaling (Table 1). Additionally, pathways regulating cell spreading and formation of focal adhesions were upregulated in IUGR islets at 2 weeks (Table 1), indicating increased cellular anchoring and cytoskeletal modulation. In contrast to increased interactions between cells and ECM, we observed transcriptomic evidence at 2 weeks of age for a reduction of cell-to-cell contact. Genes regulating tight junctions (i.e., Tjp3, Ocln, and Cldn10) and gap junctions (i.e., Gjb2 and Gjb1) were decreased at this age (Fig. 2). Taken together, these data suggest that modulation of the microenvironment occurs early in the IUGR islet and may represent a fundamental process underlying the abnormal phenotype. At 10 weeks of age, these early-life ECM changes appear to reverse, such that expression of 53 of 56 differentially expressed ECM genes was decreased, indicating extensive remodeling of the islet extracellular matrix. The effect of interactions between cells and the ECM on insulin secretion is mediated via cytoskeleton remodeling at focal adhesions and involves paxillin, ILK, PAK, and FAK signaling pathways (27–29, 31). IPA predicted downregulation of most of these signaling pathways (Table 1). Similarly, pathways regulating cell spreading, organization of the actin cytoskeleton, and microtubule dynamics were downregulated in IUGR islets at 10 weeks (Table 1). Furthermore, genes regulating cell-to-cell contact such as tight junctions and gap junctions were persistently decreased in IUGR islets (Fig. 2). Additional genes involved in cell-to-cell contact such as cadherins, cell adhesion molecules, and ephrins and their Ephs receptors, few of which were increased at 2 weeks of age, were observed to be downregulated in islets of 10-week-old IUGR rats. Thus, the array of molecules that facilitate cell adhesion to either the ECM or other cells was downregulated primarily in the adult IUGR islet, indicating progressive disconnectivity. Indeed, at 10 weeks, IPA identified enrichment of genes related to the downregulation of adhesion of epithelial cells (Table 1). Physically disconnected β-cells exhibit increased basal insulin secretion and attenuated glucose-stimulated insulin secretion, both of which we have observed previously in IUGR rats in vivo (32, 33). Mesenchymal stromal cell factors contribute to the IUGR islet phenotype Previous studies have identified mesenchymal stromal cell (MSC)–associated genes and proteins conferring islet-regenerative potential, mitigating inflammation, and preserving GSIS (34, 35). Those genes that were differentially expressed in IUGR islets are shown in Table 2. Interestingly, nine of 10 differentially expressed genes associated with MSC islet–regenerative potential were upregulated at 2 weeks of age (Table 2). ILK signaling in MSCs mediates their beneficial effects on islets and was predicted by IPA to be significantly increased at 2 weeks in IUGR islets (Table 1). Table 2. Genes Associated With Mesenchymal Stromal Cell Islet Regenerative Capacity Gene  At 2 Weeks  At 10 Weeks  Fold Change  Q Value  Fold Change  Q Value  Anxa1  1.83  0.0387  −2.45  9.93E-05  Cxcl12  —  —  −1.93  0.0062  Col3a1  —  —  −4.05  6.61E-06  Nr1h4  —  —  1.80  0.0014  Crip1  1.97  0.0033  —  —  Dtx4  —  —  −1.93  0.0177  Peg3  —  —  1.70  0.0276  Htra1  1.58  0.0462  −1.86  6.89E-04  Npas2  −2.01  0.0010  —  —  Plec  —  —  −1.72  0.0071  Cd248  —  —  −3.05  1.39E-04  Fbn1  —  —  −3.13  9.48E-07  Fabp5  1.83  0.0446  −2.93  6.81E-06  Capg  —  —  −2.82  6.50E-05  Inf2  —  —  −3.01  5.75E-04  Gstp1  —  —  −2.85  1.61E-11  Fhl1  —  —  −2.65  7.84E-10  Cotl1  1.54  0.0159  —  —  Hbb  —  —  −2.73  0.0018  Nrp2  —  —  −1.58  0.0400  Zyx  —  —  −2.54  1.90E-06  Plin3  —  —  −2.04  5.73E-06  Lats2  1.55  0.0459  —  —  Flnc  1.63  0.0290  −4.47  3.90E-16  Lpp  —  —  −1.79  4.61E-04  Sox17  —  —  −2.70  9.99E-06  Mxra8  —  —  −2.42  1.40E-07  Bag3  —  —  −2.77  2.14E-04  Ehd4  —  —  −1.92  9.42E-06  Fstl1  1.74  0.0084  −1.62  0.0132  Nr1d1  —  —  −1.63  0.0055  Bphl  —  —  1.79  0.0071  Vasn  —  —  −2.95  1.21E-10  Hspb1  —  —  −3.24  4.56E-06  Cyr61  —  —  −2.29  3.80E-05  Xdh  —  —  −5.59  2.91E-14  Thy1  2.14  0.0016  —  —  Gene  At 2 Weeks  At 10 Weeks  Fold Change  Q Value  Fold Change  Q Value  Anxa1  1.83  0.0387  −2.45  9.93E-05  Cxcl12  —  —  −1.93  0.0062  Col3a1  —  —  −4.05  6.61E-06  Nr1h4  —  —  1.80  0.0014  Crip1  1.97  0.0033  —  —  Dtx4  —  —  −1.93  0.0177  Peg3  —  —  1.70  0.0276  Htra1  1.58  0.0462  −1.86  6.89E-04  Npas2  −2.01  0.0010  —  —  Plec  —  —  −1.72  0.0071  Cd248  —  —  −3.05  1.39E-04  Fbn1  —  —  −3.13  9.48E-07  Fabp5  1.83  0.0446  −2.93  6.81E-06  Capg  —  —  −2.82  6.50E-05  Inf2  —  —  −3.01  5.75E-04  Gstp1  —  —  −2.85  1.61E-11  Fhl1  —  —  −2.65  7.84E-10  Cotl1  1.54  0.0159  —  —  Hbb  —  —  −2.73  0.0018  Nrp2  —  —  −1.58  0.0400  Zyx  —  —  −2.54  1.90E-06  Plin3  —  —  −2.04  5.73E-06  Lats2  1.55  0.0459  —  —  Flnc  1.63  0.0290  −4.47  3.90E-16  Lpp  —  —  −1.79  4.61E-04  Sox17  —  —  −2.70  9.99E-06  Mxra8  —  —  −2.42  1.40E-07  Bag3  —  —  −2.77  2.14E-04  Ehd4  —  —  −1.92  9.42E-06  Fstl1  1.74  0.0084  −1.62  0.0132  Nr1d1  —  —  −1.63  0.0055  Bphl  —  —  1.79  0.0071  Vasn  —  —  −2.95  1.21E-10  Hspb1  —  —  −3.24  4.56E-06  Cyr61  —  —  −2.29  3.80E-05  Xdh  —  —  −5.59  2.91E-14  Thy1  2.14  0.0016  —  —  Abbreviation: —, the gene was not differentially expressed at the indicated time point. View Large This trend reversed by 10 weeks in IUGR islets and expression of 29 of 32 differentially expressed genes associated with MSC regenerative capacity was significantly decreased (Table 2). Of particular interest is our finding that Cxcl12 expression was significantly decreased. Cxcl12 encodes stromal cell–derived factor 1 (SDF-1), which is chemotactic for MSCs and has a role in immune modulation (36). SDF-1 is a ligand for CXCR4, and IPA identified significant downregulation of CXCR4 signaling at 10 weeks of age (Table 1). Taken together, these data suggest that IUGR induced a compensatory increase in expression of genes regulating MSC regenerative capacity at 2 weeks, but by 10 weeks, this process was markedly decreased, which may contribute to the progressive loss of islet function in the IUGR rat. Effects of IUGR on islet nutrient metabolism and ion transport in 2- and 10-week-old rats In previous studies, we have shown that glucose-stimulated insulin secretion is markedly impaired in IUGR islets (6–8). Although we previously have shown that abnormal mitochondria function plays a fundamental role in this process (11), it is likely that other metabolic pathways may be disrupted and contribute to impaired insulin secretion. Amino acid metabolism is altered in IUGR islets IPA functional analysis identified amino acid (AA) degradation as among the most important canonical pathways differentially regulated by IUGR at 2 weeks of age (Fig. 4). These pathways included genes involved in metabolism of branched chain AAs (i.e., valine, leucine, isoleucine) and alanine, glycine, methionine, and threonine (Fig. 4). All but one of the genes associated with these pathways were downregulated (Table 3). The one gene exhibiting increased expression was cysteine dioxygenase 1, which converts cysteine and oxygen to cysteine sulfinate (37). Figure 4. View largeDownload slide Ingenuity Pathway Analysis (Qiagen, Hilden, Germany) identifies gene enrichment involving AA degradation in 2-week-old IUGR islets. Green indicates decreased gene expression in IUGR islets compared with controls. Red indicates increased expression. NaN, not a number. Figure 4. View largeDownload slide Ingenuity Pathway Analysis (Qiagen, Hilden, Germany) identifies gene enrichment involving AA degradation in 2-week-old IUGR islets. Green indicates decreased gene expression in IUGR islets compared with controls. Red indicates increased expression. NaN, not a number. Table 3. Differentially Expressed Genes Involved in Amino Acid Metabolism and Transport   Islets at 2 Weeks  Islets at 10 Weeks    Gene  Fold Change  Q Value  Fold Change  Q Value  AA Metabolized  AA metabolism             Mccc1  −2.05  9.60E-03  —  —  Leu   Mccc2  −2.07  1.74E-03  —  —  Leu   Acat1  −2.03  0.0138  —  —  Ile   Bcat2  −2.12  0.0130  −2.58  1.74E-04  Leu, Ile, Val   Acadsb  −2.19  4.99E-04  —  —  Ile, Val   Acad8  −2.43  1.46E-03  −1.74  0.0498  Ile, Val   Ehhadh  −2.38  0.0162  —  —  Ile, Val   Bckdha  −1.83  0.0247  −2.53  1.42E-05  Val   Bckdhb  −2.15  0.0193  −2.10  9.59E-03  Val   Aldh6a1  −1.75  0.0286  −1.66  0.0259  Val   Tdh  −5.82  2.42E-03  −3.67  2.05E-02  Thr   Gcat  −3.92  5.49E-05  −2.93  5.71E-04  Thr   Gpt  −2.00  0.0226  −2.19  2.82E-03  Ala   Gpt2  −2.62  2.83E-04  −1.88  0.0167  Ala   Gamt  −3.52  5.38E-04  −6.83  1.25E-09  Gly   Gatm  −3.81  5.55E-03  −25.68  1.10E-14  Gly   Cdo1  2.13  9.36E-04  —  —  Met   Mtr  −1.79  1.22E-04  —  —  Met   Cbs  −5.12  8.06E-05  −30.18  2.47E-18  Met   Ahcy  −3.42  6.29E-08  −2.41  3.06E-05  Met   Pcca  −2.12  2.78E-03  —  —  Met   Cth  −4.81  3.06E-04  −39.13  5.09E-19  Met   Bhmt  −3.56  3.04E-04  —  —  Met   Gls2  −3.09  8.41E-03  −11.31  1.07E-11  Gln   Gad1  —  —  1.74  4.53E-03  Glu  AA transporter             Slc1a3  —  —  −4.39  3.60E-12  High affinity Glu transporter   Slc1a5  —  —  −1.90  6.67E-03  Neutral AA transporter   Slc3a1  —  —  1.83  5.39E-04  Cystine, dibasic and neutral   Slc6a9  —  —  −4.65  2.79E-11  Gly transporter   Slc6a20  −3.07  1.11E-03  −8.89  1.01E-11  Pro transporter   Slc7a1  −1.73  0.0216  −1.78  5.59E-03  Cationic Y+ system   Slc7a7  −1.76  0.0345  −2.96  5.87E-07  Cationic Y+ system   Slc7a8  −1.97  7.10E-04  —  —  Cationic Y+ system   Slc7a11  −4.66  2.92E-04  −3.42  1.63E-03  Cationic Y+ system   Slc38a2  —  —  −1.50  0.0173  Neutral system A   Slc38a3  −4.18  1.03E-04  −4.15  1.53E-05  Gln, Asn, and His transporter   Slc38a4  —  —  1.64  4.15E-03  Cationic and neutral transporter    Islets at 2 Weeks  Islets at 10 Weeks    Gene  Fold Change  Q Value  Fold Change  Q Value  AA Metabolized  AA metabolism             Mccc1  −2.05  9.60E-03  —  —  Leu   Mccc2  −2.07  1.74E-03  —  —  Leu   Acat1  −2.03  0.0138  —  —  Ile   Bcat2  −2.12  0.0130  −2.58  1.74E-04  Leu, Ile, Val   Acadsb  −2.19  4.99E-04  —  —  Ile, Val   Acad8  −2.43  1.46E-03  −1.74  0.0498  Ile, Val   Ehhadh  −2.38  0.0162  —  —  Ile, Val   Bckdha  −1.83  0.0247  −2.53  1.42E-05  Val   Bckdhb  −2.15  0.0193  −2.10  9.59E-03  Val   Aldh6a1  −1.75  0.0286  −1.66  0.0259  Val   Tdh  −5.82  2.42E-03  −3.67  2.05E-02  Thr   Gcat  −3.92  5.49E-05  −2.93  5.71E-04  Thr   Gpt  −2.00  0.0226  −2.19  2.82E-03  Ala   Gpt2  −2.62  2.83E-04  −1.88  0.0167  Ala   Gamt  −3.52  5.38E-04  −6.83  1.25E-09  Gly   Gatm  −3.81  5.55E-03  −25.68  1.10E-14  Gly   Cdo1  2.13  9.36E-04  —  —  Met   Mtr  −1.79  1.22E-04  —  —  Met   Cbs  −5.12  8.06E-05  −30.18  2.47E-18  Met   Ahcy  −3.42  6.29E-08  −2.41  3.06E-05  Met   Pcca  −2.12  2.78E-03  —  —  Met   Cth  −4.81  3.06E-04  −39.13  5.09E-19  Met   Bhmt  −3.56  3.04E-04  —  —  Met   Gls2  −3.09  8.41E-03  −11.31  1.07E-11  Gln   Gad1  —  —  1.74  4.53E-03  Glu  AA transporter             Slc1a3  —  —  −4.39  3.60E-12  High affinity Glu transporter   Slc1a5  —  —  −1.90  6.67E-03  Neutral AA transporter   Slc3a1  —  —  1.83  5.39E-04  Cystine, dibasic and neutral   Slc6a9  —  —  −4.65  2.79E-11  Gly transporter   Slc6a20  −3.07  1.11E-03  −8.89  1.01E-11  Pro transporter   Slc7a1  −1.73  0.0216  −1.78  5.59E-03  Cationic Y+ system   Slc7a7  −1.76  0.0345  −2.96  5.87E-07  Cationic Y+ system   Slc7a8  −1.97  7.10E-04  —  —  Cationic Y+ system   Slc7a11  −4.66  2.92E-04  −3.42  1.63E-03  Cationic Y+ system   Slc38a2  —  —  −1.50  0.0173  Neutral system A   Slc38a3  −4.18  1.03E-04  −4.15  1.53E-05  Gln, Asn, and His transporter   Slc38a4  —  —  1.64  4.15E-03  Cationic and neutral transporter  Abbreviations: —, the gene was not differentially expressed at the indicated time point; cAMP, cyclic adenosine monophosphate. View Large Because AA metabolism depends on the transport-mediated availability of AAs, we investigated whether gene expression of AA transporters was also differentially expressed in IUGR islets. Consistent with decreased expression of genes involved in AA degradation, we observed downregulation of genes involved in AA transport in islets of 2-week-old IUGR rats (Table 3). Two-week-old IUGR islets exhibited a greater than fourfold reduction in Slc7a11 and Slc38a3 expression than those from control rats. Slc7a11 encodes a cystine/glutamate antiporter that plays a role in intracellular antioxidant defense and extracellular glutamate signaling (38). Slc38a3 encodes glutamine, Na+, and the H+ transporter SN1, and may have roles in nutrient sensing and β-cell function (39–41). In IUGR islets from rats at 10 weeks of age, expression of genes regulating degradation of threonine, glycine, and alanine metabolism pathways remained decreased (Table 3). Fewer genes involved in branched chain AA degradation were differentially expressed, but messenger RNA levels of the initial metabolizing enzyme, Bcat2, were lower than at 2 weeks. Expression of the AA transporters Slc7a11 and Slc38a3 continued to be decreased at 10 weeks of age in addition to that of several others, including glycine transporter Slc6a9 and intracellular glutamate transporter Slc1a3 (Table 3). Thus, we observed reduced expression of genes involved in AA metabolism and trans-cellular transport, which, together, could have deleterious effects on insulin secretion and β-cell proliferation. Genes regulating movement of water and ions are dysregulated in IUGR islets Because regulated movement of ions across the cellular membrane is responsible for changes in membrane potential and the subsequent mobilization of Ca+2 required for insulin secretion, we investigated whether genes encoding ion channels were differentially expressed in IUGR islets. Expression of several genes involved in ion transport was altered, but primarily in 10-week-old IUGR animals (Table 4). Chloride and water transport are intimately involved in cell-volume regulation. Gene expression of chloride channels Ano1, Cftr, and Slc26a8, and water transporters Aqp8 and Aqp12a were significantly downregulated in IUGR islets at 2 weeks of age (Table 4). Decreased expression of Ano1, Aqp8, and Aqp12a persisted into adulthood and was exacerbated such that aquaporins were decreased more than 30-fold in 10-week-old IUGR islets compared with those of control rats (Table 4). Moreover, volume-regulated chloride (Lrrc8c and Slc12a4) and potassium (Kcnk5) channels were decreased in adult IUGR islets (Table 4). Potassium channel KCNQ1 is known to be voltage gated, but it is also responsive to changes in cell volume (42). Therefore, it is unsurprising that, at both ages, Kcnq1 expression levels were decreased in IUGR islets. KCNQ1 auxiliary components Kcne1 and Kcne4, however, were downregulated only at 10 weeks of age (Table 4). In contrast, gene expression of potassium channels that are not sensitive to changes in volume was increased at 10 weeks of age (Table 4). Considering IPA identified pathways associated with edema (Table 1), the selective reduction in gene expression of ion channels regulating cell volume or being regulated by cell volume may indicate a possible compensatory mechanism to protect β-cells from pathological cell swelling. Table 4. Differential Gene Expression Related to Ion and Water Transport     Transport    Gene Expression a  Gene  Alternate Name  Inward  Outward  Regulation  At 2 Weeks  At 10 Weeks  Kcnj11  Kir6.2    K+  ATP  —  ↑  Kcnk16  TALK1    K+  pH  —  ↑  Kcnma1  BK    K+  Ca+2, voltage  —  ↑  Kcnn3  SK3    K+  Ca+2  —  ↑  Kcnq1  KVLQT1    K+  Voltage  ↓↓  ↓↓↓  Kcne1  ISK  Slows KCNQ1 activation  ↓↓↓  ↓↓↓↓  Kcne4    Inhibits KCNQ1 current  —  ↓↓  Kcna2  Kv1.2    K+  Voltage  ↓↓  —  Kcna4  Kv1.4    K+  Voltage  ↑  ↑↑  Kcnb2  Kv2.2    K+  Voltage  —  ↑  Kcnk5  TASK2    K+  Volume, pH  —  ↓↓  Ano1  Tmem16    Cl-  Ca+2  ↓  ↓↓  Cftr      Cl-  ATP  ↓↓  —  Slc26a8  Tat1  Cl−  HCO3−, SO4−2    ↓↓  —  Slc12a2  NKCC1  Cl−, Na+, K+      —  ↓  Slc12a8    Cl−, Na+, K+      ↓  —  Slc12a4  KCC1    Cl−, Na+  Volume  —  ↓  Lrrc8c      Cl−  Volume  —  ↓↓  Clcn5    Cl−  H+  Voltage  —  ↑  Clic4  MTCLIC  Cl−      ↑  ↓  Scn3a  Nav1.3  Na+    Voltage  —  ↑  Scn3b    Na+    Voltage  —  ↑  Trpm4    Na+    Ca+2  —  ↓↓  Trpm5    Na+    Ca+2  —  ↑  Slc8a1  NCX1  Na+  Ca+2  Ca+2  —  ↑  Slc8a3  NCX3  Na+  Ca+2    —  ↑↑  Slc24a3  NCKX3  Na+  Ca+2, K+    —  ↓  Ryr2    Ca+2    Ca+2  —  ↑  Micu3      Ca+2    —  ↑  Trpm3    Ca+2    Sphingosine  —  ↑  Trpa1    Ca+2    Cold  ↑↑  ↑↑  Trpc1    Ca+2      —  ↑  Trpc5    Ca+2    Ca+2  —  ↑  Trpc6    Ca+2, Na+    DAG  —  ↓↓  Itpr2    Ca+2    IP3  —  ↓  Itpr3    Ca+2    IP3  ↓  ↓  Piezo1    Cation channel  Mechanically  —  ↓↓  Aqp1    Water channel    —  ↓↓↓  Aqp8    Water channel    ↓↓↓  ↓↓↓↓  Aqp12a    Water channel    ↓↓  ↓↓↓↓      Transport    Gene Expression a  Gene  Alternate Name  Inward  Outward  Regulation  At 2 Weeks  At 10 Weeks  Kcnj11  Kir6.2    K+  ATP  —  ↑  Kcnk16  TALK1    K+  pH  —  ↑  Kcnma1  BK    K+  Ca+2, voltage  —  ↑  Kcnn3  SK3    K+  Ca+2  —  ↑  Kcnq1  KVLQT1    K+  Voltage  ↓↓  ↓↓↓  Kcne1  ISK  Slows KCNQ1 activation  ↓↓↓  ↓↓↓↓  Kcne4    Inhibits KCNQ1 current  —  ↓↓  Kcna2  Kv1.2    K+  Voltage  ↓↓  —  Kcna4  Kv1.4    K+  Voltage  ↑  ↑↑  Kcnb2  Kv2.2    K+  Voltage  —  ↑  Kcnk5  TASK2    K+  Volume, pH  —  ↓↓  Ano1  Tmem16    Cl-  Ca+2  ↓  ↓↓  Cftr      Cl-  ATP  ↓↓  —  Slc26a8  Tat1  Cl−  HCO3−, SO4−2    ↓↓  —  Slc12a2  NKCC1  Cl−, Na+, K+      —  ↓  Slc12a8    Cl−, Na+, K+      ↓  —  Slc12a4  KCC1    Cl−, Na+  Volume  —  ↓  Lrrc8c      Cl−  Volume  —  ↓↓  Clcn5    Cl−  H+  Voltage  —  ↑  Clic4  MTCLIC  Cl−      ↑  ↓  Scn3a  Nav1.3  Na+    Voltage  —  ↑  Scn3b    Na+    Voltage  —  ↑  Trpm4    Na+    Ca+2  —  ↓↓  Trpm5    Na+    Ca+2  —  ↑  Slc8a1  NCX1  Na+  Ca+2  Ca+2  —  ↑  Slc8a3  NCX3  Na+  Ca+2    —  ↑↑  Slc24a3  NCKX3  Na+  Ca+2, K+    —  ↓  Ryr2    Ca+2    Ca+2  —  ↑  Micu3      Ca+2    —  ↑  Trpm3    Ca+2    Sphingosine  —  ↑  Trpa1    Ca+2    Cold  ↑↑  ↑↑  Trpc1    Ca+2      —  ↑  Trpc5    Ca+2    Ca+2  —  ↑  Trpc6    Ca+2, Na+    DAG  —  ↓↓  Itpr2    Ca+2    IP3  —  ↓  Itpr3    Ca+2    IP3  ↓  ↓  Piezo1    Cation channel  Mechanically  —  ↓↓  Aqp1    Water channel    —  ↓↓↓  Aqp8    Water channel    ↓↓↓  ↓↓↓↓  Aqp12a    Water channel    ↓↓  ↓↓↓↓  Abbreviation: —, the gene was not differentially expressed at the indicated time point. a One arrow: 1.5 ≤ fold change (FC) ≤ 2; two arrows: 2 < FC ≤ 5; three arrows: 5 < FC ≤ 10; four arrows: FC > 10. View Large Recent studies show GLP-1’s phospholipase C–dependent incretin effect is mediated by TRPM4 and TRPM5 sodium channel activity and subsequent Ca+2 mobilization from the endoplasmic reticulum (43). IUGR islets at 10 weeks of age exhibited differential gene expression of ion channels regulating this phospholipase C –dependent potentiation of insulin secretion (Table 4). Specifically, Trpm5 expression was increased, whereas gene expression of Trpm4, Itpr2, and Itpr3 was decreased (Table 4). Taken together, we observed differential gene expression of ion transporters that influence β-cell function. Many of these changes were exacerbated with age and were concordant with age-associated functional decline in IUGR islets. Islets from IUGR rats and human patients with type 2 diabetes share common pathways and genes To assess relevancy of pathogenic mechanisms in our model of IUGR-mediated islet dysfunction to mechanisms impairing islet function in human patients with diabetes, a master list of 1945 gene transcripts correlating with impaired GSIS and/or elevated hemoglobin A1c in patients with diabetes (Fig. 5A) (44–46) was compiled. IPA-generated pathways and genes from the diabetes-associated master list were compared with those from IUGR islets, using the Venny2.0 interactive Venn diagram generator (47). Pathways shared between dysfunctional islets of IUGR rats and human patients with diabetes are listed in Supplemental Table 2. Pathways shared between IUGR islets at both ages and in human patients with diabetes include the unfolded protein response, cyclic adenosine monophosphate (cAMP)–mediated signaling, microtubule dynamics, organization of cytoskeleton, glucose tolerance, fibrogenesis, and cell proliferation of fibroblasts. The only pathway that overlapped between 2-week-old IUGR islets and human diabetic islets was proliferation of endocrine cells and, indeed, previous studies have shown diminished β-cell replication in IUGR islets compared with controls (7, 48). Overlapping exclusively with IUGR islets at 10 weeks of age were signaling pathways related to epithelial adherens junctions HIPPO, HGF, and CXCR4, as well as pathology associated with amyloidosis. Together, these shared pathways support a role for modulation of the islet microenvironment, physical connectivity, and the participation of stromal cells in the pathogenesis of human type 2 diabetes and in our IUGR model. Figure 5. View largeDownload slide Venn diagrams illustrating (A) number of genes associated with islet dysfunction from humans with diabetes from three published reports (44–46) and (B) overlap between genes differentially expressed in IUGR islets and human diabetic islets. T2D, type 2 diabetes. Figure 5. View largeDownload slide Venn diagrams illustrating (A) number of genes associated with islet dysfunction from humans with diabetes from three published reports (44–46) and (B) overlap between genes differentially expressed in IUGR islets and human diabetic islets. T2D, type 2 diabetes. Despite appreciable pathway overlap between dysfunctional islets from IUGR rats and humans, individual genes within pathways could differ considerably; therefore, the genes themselves were also compared. In IUGR islets, 76 and 237 genes at 2 and 10 weeks, respectively, were found to overlap with the master list of diabetes-associated genes. A total of 41 genes were common among all groups (Fig. 5B; Supplemental Table 3). Unsurprisingly, the 41 genes were enriched in endoplasmic reticulum stress response [i.e., Eif2ak3 (PERK), Sel1l, and Xbp1] and cAMP-mediated signaling (i.e., Akap2, Camk1d, Pde8b, and Smpdl3a). Ten genes overlapped with the master list of diabetes-associated genes in human islets and genes differentially expressed in IUGR islets from rats at embryonic day 19.5 [previously published microarray data (8)], and 2 and 10 weeks of age. Expression of Pde8b, Edaradd, Ptf1a, Slc16a7, Rab27b, Mgat4a, Cmtm8, Tmed6, Kcnq1, and Sel1l was increased in fetal IUGR islets and decreased at 2 and 10 weeks of age. These changes indicate that decreased expression of these genes may engender islet dysfunction in IUGR rats and also contribute to human type 2 diabetes islet dysfunction. Discussion In this study, we identified mechanisms involved in the pathogenesis of IUGR islet dysfunction. These results support findings of our previous phenotypic studies and reveal pathways contributing to islet dysfunction in IUGR rats. Importantly, many of these genes and pathways overlap with those already identified in human type 2 diabetic islets. A key finding of our study was the observation that multiple genes regulating fibrosis in IUGR islets at 2 weeks of age were differentially expressed, suggesting fibrogenesis participates fundamentally in the initiation of the abnormal islet phenotype in diabetes. Fibrogenesis induces immune-cell trafficking and remodeling of the ECM in the islet (49–51). Indeed, IPA showed stellate-cell activation and fibrosis to be among the most enriched pathways in 2- and 10-week-old IUGR islets, and fibrogenesis was also identified as a dysregulated pathway in human diabetic islets. Activated stellate cells influence T-cell differentiation and activation toward a Th2 response (52), which is consistent with our previous IUGR studies showing elevated levels of Th2 cytokine IL-4 (8). Another important finding was the extensive changes in expression of genes related to modulation of the islet microenvironment and cellular communication with the ECM. Many differentially expressed genes encode components of the ECM that serve structural and instructive roles influencing cell migration, proliferation, insulin gene transcription, and nutrient-stimulated insulin secretion (53–55). Laminins and collagen types 1 and 3 through 6, which are secreted by cells of the vasculature and known to help maintain proper islet function (56–58), are decreased in IUGR islets by age 10 weeks. Moreover, the reduction in vasculature-derived laminins and collagens is consistent with the progressive loss of capillary density observed in IUGR islets (8). The effect of these extracellular components on islet function is mediated primarily through their interaction with integrins (54, 58, 59) whose gene expression was also decreased in IUGR islets at 10 weeks of age. These changes were not as robust at 2 weeks of age, suggesting there is a progressive loss of interactions between cells and the ECM that are integral to islet function, thereby contributing to progressive IUGR-mediated islet dysfunction. Another important component of the ECM, HA, is increased in response to tissue injury and proinflammatory cytokines (60–62). We observed increased gene expression of the HA-synthesizing protein Has2 and increased peri-islet HA staining in IUGR islets. This early increase in HA levels is consistent with changes observed in islets from human patients and from rodents with type 1 diabetes (26, 49). Moreover, studies have shown HA accumulates in lymphedematous fibrotic tissue. Interestingly, islet lymphatic vessels are localized to the islet and exocrine interface, where increased HA staining was observed (63). HA and CXCL12 are chemotactic for MSCs via interactions with CD44 and CXCR4/7, respectively (64, 65). Expression of the genes encoding these proteins was increased at age 2 weeks but decreased at age 10 weeks in IUGR islets, pointing to modulation of ligands and receptors mediating MSC migration. MSCs possess regenerative capabilities in islet grafts (34, 35, 66, 67), and genes associated with this beneficial effect mirror the pattern of genes regulating their chemotaxis; that is, their expression was increased in IUGR islets at 2 weeks of age but decreased at 10 weeks of age. Although CXCR4 and CXCR7 mediate migration and confer CXCL12’s beneficial effects, CXCR7 has an added function in regard to MSC proliferation and viability that is absent with CXCR4 (65, 68, 69). Interestingly, Cxcr7, but not Cxcr4, was differentially expressed in IUGR islets, suggesting that MSC migration, proliferation, and viability are altered in IUGR islets. The MSC-associated genes identified as conferring benefits to islets are not exclusively expressed by MSCs (70–72); thus, the changes in gene expression could be attributed to other islet cell types such as fibroblasts and microvascular-associated pericytes (73). MSC ILK signaling may be necessary to confer MSCs’ beneficial effects, and ILK signaling in islet endocrine cells is required for normal intraislet vascularization and insulin secretion (74). Therefore, attenuated ILK signaling in either MSCs or endocrine cells would impair islet function, but because the islet is a mixed-cell population, we were unable to delineate the cell type displaying attenuated ILK signaling and, subsequently, the specific mechanism involved. Regardless of origin, SDF-1 (Cxcl12), ANXA1, and ILK signaling have been shown to confer restorative properties to islets (75, 76), and their expression levels were modulated by IUGR. That gene expression associated with MSCs’ regenerative capacity was increased at 2 weeks and decreased at 10 weeks of age elucidates another mechanism of age-associated disease progression. A surprising finding of this study was gene-expression changes in IUGR islets related to the progressive loss of islet cell-to-cell interactions that are critical to maintaining structural integrity and cellular communication. These intercellular connections allow heterogenic β-cell populations within the normal islet to coordinate secretory responses to glucose such that loss of these connections result in augmented basal insulin secretion and attenuated GSIS (77–81). These aberrant insulin secretory responses associated with β-cell disconnectivity are observed in IUGR islets (8, 82). Indeed, findings of this and other studies indicate dysfunctional islets are more homogenous in their transcriptomes than are normal islets (14), which may be reflective of the diminished cell-to-cell communication that affords physiological and transcriptomic β-cell diversity. The regulated transport of ions across the plasma membrane is indispensable for GSIS. Few ion channel genes were differentially expressed in IUGR islets at 2 weeks of age, but those altered were primarily associated with anion transport (i.e., Ano1, Cftr, and Slc26a8) and Kcnq1 potassium transport. Previous studies showed these anion transporters coprecipitate and interact with one another to mediate cAMP responses (83–85). Their decreased expression at 2 weeks of age may contribute to the decreased cAMP-mediated signaling predicted by IPA and to the GSIS impairment observed in IUGR islets at this age (6, 8). Many more genes encoding ion channels were differentially expressed in IUGR islets at 10 weeks of age, including downregulation of transporters involved in cell-volume regulation including chloride channels, volume-regulated ion channels, and aquaporins. Intracellular chloride concentrations are kept above equilibrium by NKCC1 (86–88), whose gene expression was decreased in IUGR islets at 10 weeks of age. Decreased intracellular chloride concentration can diminish GSIS (86, 89, 90). Glycolytic intermediates increase intracellular osmolarity, leading to water influx, subsequent cell-volume increase, and activation of volume-regulated anion channels (90). The latter event causes a depolarizing current that complements the current generated by closure of the adenosine triphosphate–sensitive potassium (KATP) channel; together, these two currents facilitate first-phase insulin secretion (90, 91). It is this first-phase insulin secretory response that is most prominently impaired in IUGR islets (6). Interestingly, Kcnj11, which encodes the pore-forming subunit of the KATP channel, is increased in IUGR islets at 10 weeks of age, suggesting modulation of volume-regulated currents contributes more to IUGR islet dysfunction than previously recognized. In addition to Kcnj11, expression of genes regulating Ca+2-dependent or voltage-gated potassium channels, which contribute to membrane repolarization, is increased in IUGR islets. However the volume-sensitive, voltage-gated potassium channel encoded by Kcnq1 was decreased. It may be that increased, voltage-gated potassium channel expression was compensating for the reduction in Kcnq1 expression, suggesting that diminished volume regulation supersedes other changes in ion channel expression. Thus, differentially expressed ion channels highlight the importance of cell-volume regulation and anion mobilization in insulin secretion. These channels and transporters were differentially expressed at 2 weeks of age, but dysregulated expression was more pronounced in IUGR islets at 10 weeks of age, consistent with the progression of the IUGR islet phenotype. Dysregulated AA degradation in IUGR islets was an unexpected finding and, in contrast to most other pathways that were more disrupted at 10 weeks, was far more pronounced at 2 weeks of age. AA degradation occurs primarily in mitochondria, because the products of their breakdown are tricarboxylic acid cycle intermediates. Therefore, decreased AA degradation may lead to a decreased pool of tricarboxylic acid cycle intermediates. This has direct relevance to the IUGR islet phenotype because mitochondrial function is significantly impaired (11). AA metabolism depends on AA transport-mediated availability and AA transporters were differentially expressed at both ages in IUGR islets. Without quantification of AAs and their metabolites, we cannot expound on how these changes might affect islet physiology, but the importance of AAs in IUGR islet pathogenesis is evidenced by normalization of islet vascularity and function with AA supplementation (92). Of importance was our finding that many pathways identified in IUGR islets were also disrupted in islets from humans with type 2 diabetes, including those regulating cell adherence and their associated signaling pathways that modulate the cytoskeleton. These same pathways were also dysregulated in fetal islets in a sheep model of hyperthermia-induced IUGR, pointing to the pathways’ importance in the pathogenesis of islet dysfunction in diabetes (14). Interestingly, amyloidosis was another enriched pathway in 10-week-old IUGR islets and humans, indicating that although amyloid deposition does not occur in rodent models of diabetes (93), the underlying mechanism contributing to this defect also occurs in IUGR rats. Although IUGR is one of many factors contributing to type 2 diabetes risk, the overlap of pathways associated with islet dysfunction in IUGR rats and in humans strongly suggests that the diverse etiologies of type 2 diabetes converge mechanistically to disrupt islet function. In summary, we identified mechanisms contributing to IUGR-induced islet dysfunction. Moreover, temporal changes in gene expression were evident in our islet transcriptome analysis, with juvenile and adult IUGR islets displaying different patterns, underscoring the advantage of performing analyses at time points before the development of diabetes and during the progression of the disease. By doing so, we were able to uncover mechanisms by which islet dysfunction becomes exacerbated with age in IUGR animals. Last, comparing differentially expressed genes in our IUGR islets with those of human patients with diabetes supports a role for these mechanisms in islet dysfunction in type 2 diabetes. Additional studies are needed to corroborate these findings and determine specifically the effect alterations in these pathways have on IUGR-mediated islet abnormalities. Abbreviations: AA amino acid cAMP cyclic adenosine monophosphate ECM extracellular matrix GSIS glucose-stimulated insulin secretion HA hyaluronic acid Has2 hyaluronan-synthesizing enzyme ILK integrin-linked kinase IPA Ingenuity Pathway Analysis IUGR intrauterine growth restriction KATP adenosine triphosphate–sensitive potassium MSC mesenchymal stromal cell qPCR quantitative polymerase chain reaction RNAseq RNA sequencing SDF-1 stromal cell–derived factor 1. Acknowledgments Financial Support: The experiments performed in this study were funded by National Institutes of Health, Eunice Kennedy Shriver National Institute of Child Health and Human Development Grant T32HD60556 and National Institute of Diabetes and Digestive and Kidney Diseases Grant R01DK55704 (to R.A.S.). 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Google Scholar CrossRef Search ADS PubMed  Copyright © 2018 Endocrine Society http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Endocrinology Oxford University Press

Transcriptomic Analysis Reveals Novel Mechanisms Mediating Islet Dysfunction in the Intrauterine Growth–Restricted Rat

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Oxford University Press
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Copyright © 2018 Endocrine Society
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0013-7227
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1945-7170
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10.1210/en.2017-00888
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Abstract

Abstract Intrauterine growth restriction (IUGR) increases the risk of type 2 diabetes developing in adulthood. In previous studies that used bilateral uterine artery ligation in a rat model of IUGR, age-associated decline in glucose homeostasis and islet function was revealed. To elucidate mechanisms contributing to IUGR pathogenesis, the islet transcriptome was sequenced from 2-week-old rats, when in vivo glucose tolerance is mildly impaired, and at 10 weeks of age, when rats are hyperglycemic and have reduced β-cell mass. RNA sequencing and functional annotation with Ingenuity Pathway Analysis revealed temporal changes in IUGR islets. For instance, gene expression involving amino acid metabolism was significantly reduced primarily at 2 weeks of age, but ion channel expression, specifically that involved in cell-volume regulation, was more disrupted in adult IUGR islets. Additionally, we observed alterations in the microenvironment of IUGR islets with extracellular matrix genes being significantly increased at 2 weeks of age and significantly decreased at 10 weeks. Specifically, hyaluronan synthase 2 expression and hyaluronan staining were increased in IUGR islets at 2 weeks of age (P < 0.05). Mesenchymal stromal cell–derived factors that have been shown to preserve islet allograft function, such as Anxa1, Cxcl12, and others, also were increased at 2 weeks and decreased in adult islets. Finally, comparisons of differentially expressed genes with those of type 2 diabetic human islets support a role for these pathways in human patients with diabetes. Together, these data point to new mechanisms in the pathogenesis of IUGR-mediated islet dysfunction in type 2 diabetes. Human and animal studies have shown that uteroplacental insufficiency is associated with intrauterine growth restriction (IUGR) and development of metabolic sequelae such as obesity and type 2 diabetes in adulthood (1–4). To better understand mechanisms by which IUGR results in the development of diabetes, we have used bilateral uterine artery ligation, in which blood supply to developing rat fetuses is decreased, resulting in fetal growth restriction and decreased birth weight (5, 6). β-cell dysfunction, immune cell infiltration in the pancreas, and islet capillary rarefaction are observed even before delivery in the IUGR rat (6–8). At 2 weeks of age, IUGR pups exhibit impaired insulin secretion that is due, in part, to mitochondrial dysfunction and inflammation in the islet (7–10). Glucose homeostasis progressively worsens with age such that, at 10 weeks, IUGR rats begin to display fasting hyperinsulinemia, mild reductions in β-cell mass, and diminished glucose-stimulated insulin secretion (GSIS) and leucine-stimulated insulin secretion (6–8, 11). Early postnatal interventions, with the GLP-1 analog, exendin-4, or immunological IL-4 neutralization, rescue low-birth-weight pups from later-life diabetes (7, 9, 10, 12, 13). Normalization of endocrine pancreas maturation and function by these two seemingly disparate postnatal interventions suggests diverse mechanisms engender β-cell dysfunction in IUGR rats. Transcriptome sequencing is an effective tool for uncovering unknown mechanisms of islet dysfunction. In a sheep model of hyperthermia-induced IUGR, RNA sequencing (RNAseq) of fetal islets identified more than 1000 differentially expressed genes, many representing newly identified genes in pathways known to be disrupted in IUGR animals (14). However, when sequencing the fetal islet transcriptome, it is impossible to ascertain which changes will persist after the islet’s postnatal remodeling, and makes it more difficult to distinguish detrimental changes in gene expression and those that may be compensatory. To this point, islet transcriptomic analysis performed in Goto-Kakizaki diabetic rats at five time points throughout glucose metabolic dysfunction showed that gene expression patterns differ temporally, as do the biological pathways they represent (15). However, because the Goto-Kakizaki rat represents a polygenic model of diabetes (16) with pathological end points such as islet fibrosis (17) that do not manifest in IUGR-mediated islet pathology, the study provides limited relevance to our surgical model of IUGR and subsequent islet dysfunction. In the current study, by sequencing the transcriptome at 2 and 10 weeks of age, we elucidate mechanisms that mediated islet dysfunction in our IUGR model. Finally, we show clinical relevance by comparing genes previously identified as differentially expressed in diabetic human islets with those in IUGR islets and identify common genes and shared pathways. Materials and Methods Animal model The animals and procedures used in this study were approved by the Animal Care Committee of The Children’s Hospital of Philadelphia and the Perelman School of Medicine at the University of Pennsylvania. Our animal model has been described previously (6). Briefly, at embryonic day 18.5, pregnant Sprague Dawley rats were anesthetized with isoflurane and bilateral uterine artery ligation was performed (6). A sham operation was performed in control rats. On the day of delivery, pups were weighed to confirm IUGR and litters were culled to eight to equilibrate postnatal nutrient availability. Dams and offspring were given ad libitum access to water and standard rodent chow. At 2 weeks and 10 weeks of age, pancreata were excised under ketamine and xylazine anesthesia, followed by islet isolation. Islets were pooled from both sexes at 2 weeks of age because previous phenotypic studies at this age were conducted in pooled samples from both sexes (8). Only male rats were studied at 10 weeks of age, because previous studies have shown the diabetic phenotype in adulthood is male-sex specific (8). Islet isolation Two pancreata per litter were pooled for each 2-week sample (three litters were studied); 10-week pancreata were not pooled, and pancreata from three different litters were used. Pancreatic islets were isolated as previously described (8). Briefly, pancreata were digested via ductal perfusion with 10 mg/mL Collagenase P (Roche) in Hanks balanced salt solution supplemented with 4 mM NaCO3 and 1% bovine serum albumin. After ductal perfusion, excised pancreata were digested for 15 minutes at 37°C. Tissue was then washed in cold, supplemented Hanks balanced salt solution without collagenase. Islets were isolated by histopaque gradient centrifugation and washed. Total RNA isolation and RNAseq library preparation Total RNA was extracted from freshly isolated islets using TRIzol Reagent (Invitrogen) and then the Qiagen RNeasy Mini kit following manufacturer’s instructions. RNA (1 µg) from samples with RNA integrity numbers between 7 and 9.2 were used to generate complementary DNA. RNAseq libraries were made using the Illumina TruSeq Stranded Total RNA LT Sample Prep Kit with Ribo-Zero Gold. RNAseq and gene expression analysis RNAseq libraries were single-end sequenced to 100 bp on an Illumina hiSeq2000 system. All the RNAseq data were mapped using the Tophat package against the rat genome (version rn5). Differential analysis was done using edgeR package (Bioconductor). Differentially regulated genes were identified using a Q-value cutoff of 0.05. Hierarchical clustering analysis was performed using the gene expression values from all conditions and replicates for previously selected differential genes. Specifically, we used Ward’s criterion for genes with 1 − (correlation coefficient) as a distance measure. Clustering heatmaps were constructed using a z-score that was scaled across samples for each gene. Functional analysis was conducted using Ingenuity Pathway Analysis (IPA; Qiagen, Redwood City, CA). Uploaded data sets contained gene identifiers, fold changes, counts per million and Q-values. Significance filtering was used to increase the focus and specificity of analysis. Core analysis was performed only on genes having a fold change ≥1.5, counts per million ≥4, and Q-value < 0.05. The data discussed in this publication have been deposited in the National Center for Biotechnology Information Gene Expression Omnibus (18) and are accessible through GEO Series accession number GSE104017 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE104017). Quantitative polymerase chain reaction Quantitative polymerase chain reaction (qPCR) was performed on biological replicates to verify changes in select genes in islets from three to eight animals, each from a different litter and from a different cohort than that of the animals used for RNAseq. Reverse transcription was performed using iScript cDNA Synthesis Kit (BioRad). QuantStudio 7 Flex Real-Time PCR System (Thermo Fisher Scientific, Waltham, MA) was used for qPCR. The following Taqman Gene Expression Assays (Applied Biosystems) were used: Emilin3 (Rn01750280), Matn4 (Rn01423881), Bcat2 (Rn00574455), Gatm (Rn00578954), Kcnq1 (Rn00583376), Ano1 (Rn01474520), Aqp8 (Rn00569732), Trpa1 (Rn01473803), and Cltc (Rn00693501). Cltc gene expression was used as the endogenous control. Relative fold change was calculated using the ΔCT method. Histochemistry Excised pancreata were fixed using formalin-free zinc fixative (BD Pharmigen) for 48 hours. Tissues were embedded in paraffin and sectioned. Slides were stained with biotinylated hyaluronic acid (HA) binding protein (EMD Millipore). Staining was performed as previously described (16). Slides were incubated with 5 μg/mL biotinylated HA binding protein in 0.1% bovine serum albumin in phosphate-buffered saline overnight at 4°C in a humidified chamber. Vectastain ABC reagent was applied for 1 hour at room temperature. Slides were rinsed and stained using 3,3'-diaminobenzidine and Chromogen (Dako), and counterstained with hematoxylin (Azer Scientific). To quantify staining, slides were digitally scanned at ×40 magnification on an Aperio Scanscope CS-O (brightfield; Leica Biosystems), and analyzed by ImageScope version 12.2.2.5015 (Leica Biosystems) using Aperio-Color Deconvolution version 9.1 algorithm. Islets were identified, and the area of HA staining was calculated within the intraislet and peri-islet regions by multiplying percent positive staining of HA within these regions with total stained area and the product was normalized to the total analysis area. Peri-islet region was defined as the region around the islets at approximately 5 μm from the outer edge of the islet, as described previously (19). Results IUGR altered the islet transcriptome at 2 weeks and 10 weeks of age Next-generation sequencing of pancreatic islets isolated from IUGR and control rats detected 26,312 and 27,703 gene transcripts at 2 weeks and 10 weeks, respectively (Supplemental Table 1). Differential gene expression was observed for 793 genes (n = 220 increased, n = 573 decreased) and 2184 genes (n = 524 increased, n = 1660 decreased) at 2 and 10 weeks, respectively (Fig. 1). Recent RNAseq from fetal IUGR sheep islets revealed a similar number of differentially expressed genes and a similar proportion of those increased to those decreased (14). Previous studies by us and other laboratories have shown that differentially expressed genes correlate with fold change determined via qPCR (14, 20). Therefore, we confirmed by qPCR gene expression of only eight genes (Emilin3, Matn4, Bcat2, Gatm, Kcnq1, Ano1, Aqp8, and Trpa1) that were differentially expressed at both time points examined. Fold changes from qPCR were consistent with fold change in our RNAseq data set (Supplemental Fig. 1). Figure 1. View largeDownload slide RNA sequencing revealed differential gene expression in IUGR rat islets compared with that in controls at 2 and 10 weeks of age. (A) A heat map of genes differentially expressed between groups (n = 3 per group). Differential gene expression was defined as −1.5 ≤ fold change ≥ 1.5, counts per million ≥ 4, and Q ≤ 0.05. (B) A Venn diagram illustrating overlap of differentially expressed genes between IUGR and control islets based on fold change at 2 and 10 weeks of age. Figure 1. View largeDownload slide RNA sequencing revealed differential gene expression in IUGR rat islets compared with that in controls at 2 and 10 weeks of age. (A) A heat map of genes differentially expressed between groups (n = 3 per group). Differential gene expression was defined as −1.5 ≤ fold change ≥ 1.5, counts per million ≥ 4, and Q ≤ 0.05. (B) A Venn diagram illustrating overlap of differentially expressed genes between IUGR and control islets based on fold change at 2 and 10 weeks of age. To identify pathways disrupted by IUGR at 2 and 10 weeks of age, IPA was used for functional annotation of differentially expressed genes. Multiple pathways were altered in IUGR rats at both ages, including downregulation of pathways involving glucose use and mitochondrial respiration, and upregulation of inflammation and insulin resistance (Table 1), which are supported by previous functional studies in IUGR rats (6, 8, 11). Additionally, we identified disruption of unanticipated pathways that may contribute to IUGR islet pathogenesis (Table 1). In the following subsections, these pathways and their possible contribution to the temporal progression of IUGR islet dysfunction are discussed. Table 1. Ingenuity Pathway Analysis of Differentially Expressed Genes   Islets at 2 Weeks    Islets at 10 Weeks  Category  P Value  Activation Z-Score  Category  P Value  Activation Z-Score  Canonical pathways  Canonical pathways   Fibrosis/stellate cell activation  6.24E-05  —   Fibrosis/stellate cell activation  2.84E-20  —   Gap junction signaling  9.33E-03  —   Integrin signaling  3.80E-06  −5.568   Type 2 diabetes mellitus signaling  1.04E-02  1.890   PAK signaling  3.95E-05  −3.900   Tight junction signaling  1.58E-02  —   Regulation of the EMT pathway  6.46E-05  —   Acute phase response  1.71E-02  1.897   Tight junction signaling  1.66E-03  —   ILK signaling  1.51E-02  1.897   Paxillin signaling  1.82E-03  −3.32   cAMP-mediated signaling  4.24E-02  −2.111   HIPPO signaling  2.00E-03  0.00   Leukocyte extravasation signaling  4.65E-02  1.890   Gap junction signaling  2.63E-03  —         Epithelial adherens junction signaling  1.07E-02  —         FAK signaling  1.35E-02  —         ILK signaling  2.24E-02  −3.71  Upstream regulators  Upstream regulators   Activated     Activated      TGF-β1  9.30E-20  4.557    α-Catenin  2.45E-36  7.566    IL-1β  1.02E-07  4.157    COL18A1  2.42E-13  5.502    TNF  5.29E-12  3.026    CD3  9.95E-04  4.732    AGT  3.64E-03  2.331    TRIM24  9.03E-07  4.558    F2  4.65E-09  2.306    SMAD7  2.86E-11  4.394    IL-4  3.71E-08  1.396         Inhibited   Inhibited    α-Catenin  1.62E-04  −3.422    VEGF  1.06E-26  −7.890    UCP1  4.19E-07  −3.051    Il-1β  1.35E-50  −7.651    HNF1A  5.45E-07  −3.033    TGF-β1  1.05E-72  −7.629    PTF1A  8.46E-06  −2.959    IFN-γ  3.85E-40  −7.022    NR5A2  2.61E-13  −2.905    TNF  6.58E-71  −5.860  Diseases and functions, top five by P value  Diseases and functions, top five by P value   Quantity of carbohydrate  1.36E-14  0.011   Cell movement  1.13E-73  −8.646   Metabolism of amino acids  1.53E-14  −1.134   Migration of cells  6.94E-70  −8.519   Migration of cells  1.16E-10  0.764   Angiogenesis  3.54E-63  −6.832   Invasion of cells  2.59E-10  2.093   Proliferation of cells  2.13E-62  −3.502   Cell movement  3.20E-10  0.556   Vasculogenesis  2.53E-62  −6.349   Upregulated   Upregulated    Recruitment of leukocytes  4.68E-07  3.134    Edema  4.42E-18  5.997    Inflammation of pancreas  6.98E-09  2.355    Inflammation of organ  1.60E-18  3.011    Cell spreading  3.11E-04  2.239    Glucose metabolism disorder  1.79E-22  2.862    Adhesion of fibroblasts  1.24E-05  2.132    Insulin resistance  1.82E-12  2.056    Formation of focal adhesions  8.19E-08  2.016    Fibrosis  5.09E-16  1.906    Epithelial mesenchymal transition  8.81E-06  1.567    Peripheral vascular disease  6.32E-17  1.683    Glucose metabolism disorder  9.04E-06  1.554    Infarction  1.94E-13  1.555    Fibrogenesis  9.89E-05  1.428    Apoptosis  1.57E-44  1.133   Downregulated   Downregulated    Assembly of cells  3.25E-05  −2.057    Angiogenesis  3.54E-63  −6.832    Endothelial cell development  6.98E-05  −1.919    Leukocyte migration  1.22E-29  −6.408    Use of d-glucose  7.56E-06  −1.706    Microtubule dynamics  4.68E-20  −5.054    Consumption of oxygen  2.45E-06  −1.601    Cell spreading  3.90E-16  −4.851    Angiogenesis of lesion  2.30E-05  −1.503    Metabolism of carbohydrate  1.89E-15  −4.760    Quantity of secretory structure  3.98E-04  −1.333    Adhesion of epithelial cells  4.08E-12  −3.658    Quantity of insulin in blood  8.14E-09  −1.235    Organization of actin cytoskeleton  3.33E-15  −3.296    Islets at 2 Weeks    Islets at 10 Weeks  Category  P Value  Activation Z-Score  Category  P Value  Activation Z-Score  Canonical pathways  Canonical pathways   Fibrosis/stellate cell activation  6.24E-05  —   Fibrosis/stellate cell activation  2.84E-20  —   Gap junction signaling  9.33E-03  —   Integrin signaling  3.80E-06  −5.568   Type 2 diabetes mellitus signaling  1.04E-02  1.890   PAK signaling  3.95E-05  −3.900   Tight junction signaling  1.58E-02  —   Regulation of the EMT pathway  6.46E-05  —   Acute phase response  1.71E-02  1.897   Tight junction signaling  1.66E-03  —   ILK signaling  1.51E-02  1.897   Paxillin signaling  1.82E-03  −3.32   cAMP-mediated signaling  4.24E-02  −2.111   HIPPO signaling  2.00E-03  0.00   Leukocyte extravasation signaling  4.65E-02  1.890   Gap junction signaling  2.63E-03  —         Epithelial adherens junction signaling  1.07E-02  —         FAK signaling  1.35E-02  —         ILK signaling  2.24E-02  −3.71  Upstream regulators  Upstream regulators   Activated     Activated      TGF-β1  9.30E-20  4.557    α-Catenin  2.45E-36  7.566    IL-1β  1.02E-07  4.157    COL18A1  2.42E-13  5.502    TNF  5.29E-12  3.026    CD3  9.95E-04  4.732    AGT  3.64E-03  2.331    TRIM24  9.03E-07  4.558    F2  4.65E-09  2.306    SMAD7  2.86E-11  4.394    IL-4  3.71E-08  1.396         Inhibited   Inhibited    α-Catenin  1.62E-04  −3.422    VEGF  1.06E-26  −7.890    UCP1  4.19E-07  −3.051    Il-1β  1.35E-50  −7.651    HNF1A  5.45E-07  −3.033    TGF-β1  1.05E-72  −7.629    PTF1A  8.46E-06  −2.959    IFN-γ  3.85E-40  −7.022    NR5A2  2.61E-13  −2.905    TNF  6.58E-71  −5.860  Diseases and functions, top five by P value  Diseases and functions, top five by P value   Quantity of carbohydrate  1.36E-14  0.011   Cell movement  1.13E-73  −8.646   Metabolism of amino acids  1.53E-14  −1.134   Migration of cells  6.94E-70  −8.519   Migration of cells  1.16E-10  0.764   Angiogenesis  3.54E-63  −6.832   Invasion of cells  2.59E-10  2.093   Proliferation of cells  2.13E-62  −3.502   Cell movement  3.20E-10  0.556   Vasculogenesis  2.53E-62  −6.349   Upregulated   Upregulated    Recruitment of leukocytes  4.68E-07  3.134    Edema  4.42E-18  5.997    Inflammation of pancreas  6.98E-09  2.355    Inflammation of organ  1.60E-18  3.011    Cell spreading  3.11E-04  2.239    Glucose metabolism disorder  1.79E-22  2.862    Adhesion of fibroblasts  1.24E-05  2.132    Insulin resistance  1.82E-12  2.056    Formation of focal adhesions  8.19E-08  2.016    Fibrosis  5.09E-16  1.906    Epithelial mesenchymal transition  8.81E-06  1.567    Peripheral vascular disease  6.32E-17  1.683    Glucose metabolism disorder  9.04E-06  1.554    Infarction  1.94E-13  1.555    Fibrogenesis  9.89E-05  1.428    Apoptosis  1.57E-44  1.133   Downregulated   Downregulated    Assembly of cells  3.25E-05  −2.057    Angiogenesis  3.54E-63  −6.832    Endothelial cell development  6.98E-05  −1.919    Leukocyte migration  1.22E-29  −6.408    Use of d-glucose  7.56E-06  −1.706    Microtubule dynamics  4.68E-20  −5.054    Consumption of oxygen  2.45E-06  −1.601    Cell spreading  3.90E-16  −4.851    Angiogenesis of lesion  2.30E-05  −1.503    Metabolism of carbohydrate  1.89E-15  −4.760    Quantity of secretory structure  3.98E-04  −1.333    Adhesion of epithelial cells  4.08E-12  −3.658    Quantity of insulin in blood  8.14E-09  −1.235    Organization of actin cytoskeleton  3.33E-15  −3.296  Abbreviation: —, IPA did not generate an activation z score. View Large Effects of IUGR on the islet microenvironment in 2- and 10-week-old rats IUGR alters extracellular matrix and cytoskeleton organization The islet extracellular matrix (ECM) plays a vital role in cell survival, proliferation, and function (21–23). We observed multiple differentially expressed ECM genes, including those encoding collagens, laminins, fibulins, and tenascins, as well as lysyl oxidase–like enzymes that are responsible for cross-linking collagen and subsequent stiffening of the ECM (24, 25)(Fig. 2). Figure 2. View largeDownload slide Differential gene expression modulating the islet microenvironment. (A) A heat map of differentially expressed ECM genes. (B) A heat map of differentially expressed plasma membrane–associated genes involved in cellular attachment. Also included are plasma membrane–associated genes that modulate the external environment, such as Has1 and Has2 genes that mediate outside-in signal transduction, including Cav1 and Tjp3. Genes are listed in ascending order according to fold change relative to control at 2 weeks of age and then by 10 weeks of age. *Gene was differentially expressed in IUGR islets at 2 weeks of age; #gene was differentially expressed in IUGR islets at 10 weeks of age. Figure 2. View largeDownload slide Differential gene expression modulating the islet microenvironment. (A) A heat map of differentially expressed ECM genes. (B) A heat map of differentially expressed plasma membrane–associated genes involved in cellular attachment. Also included are plasma membrane–associated genes that modulate the external environment, such as Has1 and Has2 genes that mediate outside-in signal transduction, including Cav1 and Tjp3. Genes are listed in ascending order according to fold change relative to control at 2 weeks of age and then by 10 weeks of age. *Gene was differentially expressed in IUGR islets at 2 weeks of age; #gene was differentially expressed in IUGR islets at 10 weeks of age. HA is an ECM component present in mouse and human islet ECM, and recent studies suggest HA may be a novel inflammatory mediator of islet pathology in type 1 and 2 diabetes (26). In 2-week-old IUGR islets, gene expression of hyaluronan-synthesizing enzyme, Has2, was significantly increased (Fig. 2). To determine whether changes in Has2 gene expression correlated with HA levels, 2-week-old control and IUGR pancreata were histochemically stained for HA (Fig. 3). Peri-islet HA staining was increased in IUGR islets from 2-week old animals, whereas intraislet HA staining was decreased, the latter being reflective of diminished capillary density observed in previous studies (8, 9). Figure 3. View largeDownload slide Islets of 2-week-old IUGR rats exhibit increased HA protein staining. (A) ×200 Magnification of control and IUGR pancreas stained with biotinylated-HA binding protein (EMD Millipore) with hematoxylin counterstain. (B) Quantification of HA-positive area. One section from five animals was analyzed. The HA-positive area was taken as the percentage of the total analysis area of the region. *P < 0.05 (t test). Figure 3. View largeDownload slide Islets of 2-week-old IUGR rats exhibit increased HA protein staining. (A) ×200 Magnification of control and IUGR pancreas stained with biotinylated-HA binding protein (EMD Millipore) with hematoxylin counterstain. (B) Quantification of HA-positive area. One section from five animals was analyzed. The HA-positive area was taken as the percentage of the total analysis area of the region. *P < 0.05 (t test). Integrins and syndecans are transmembrane proteins that adhere to the ECM and transduce signals intracellularly through interactions with the cytoskeleton and associated second messengers. In the islet, they enhance insulin secretion and β-cell survival (27–30). Interestingly, expression of integrin β subunit 3 and syndecan 4, was increased in 2-week-old IUGR islets (Fig. 2). Moreover, IPA predicted upregulation of integrin-linked kinase (ILK) signaling (Table 1). Additionally, pathways regulating cell spreading and formation of focal adhesions were upregulated in IUGR islets at 2 weeks (Table 1), indicating increased cellular anchoring and cytoskeletal modulation. In contrast to increased interactions between cells and ECM, we observed transcriptomic evidence at 2 weeks of age for a reduction of cell-to-cell contact. Genes regulating tight junctions (i.e., Tjp3, Ocln, and Cldn10) and gap junctions (i.e., Gjb2 and Gjb1) were decreased at this age (Fig. 2). Taken together, these data suggest that modulation of the microenvironment occurs early in the IUGR islet and may represent a fundamental process underlying the abnormal phenotype. At 10 weeks of age, these early-life ECM changes appear to reverse, such that expression of 53 of 56 differentially expressed ECM genes was decreased, indicating extensive remodeling of the islet extracellular matrix. The effect of interactions between cells and the ECM on insulin secretion is mediated via cytoskeleton remodeling at focal adhesions and involves paxillin, ILK, PAK, and FAK signaling pathways (27–29, 31). IPA predicted downregulation of most of these signaling pathways (Table 1). Similarly, pathways regulating cell spreading, organization of the actin cytoskeleton, and microtubule dynamics were downregulated in IUGR islets at 10 weeks (Table 1). Furthermore, genes regulating cell-to-cell contact such as tight junctions and gap junctions were persistently decreased in IUGR islets (Fig. 2). Additional genes involved in cell-to-cell contact such as cadherins, cell adhesion molecules, and ephrins and their Ephs receptors, few of which were increased at 2 weeks of age, were observed to be downregulated in islets of 10-week-old IUGR rats. Thus, the array of molecules that facilitate cell adhesion to either the ECM or other cells was downregulated primarily in the adult IUGR islet, indicating progressive disconnectivity. Indeed, at 10 weeks, IPA identified enrichment of genes related to the downregulation of adhesion of epithelial cells (Table 1). Physically disconnected β-cells exhibit increased basal insulin secretion and attenuated glucose-stimulated insulin secretion, both of which we have observed previously in IUGR rats in vivo (32, 33). Mesenchymal stromal cell factors contribute to the IUGR islet phenotype Previous studies have identified mesenchymal stromal cell (MSC)–associated genes and proteins conferring islet-regenerative potential, mitigating inflammation, and preserving GSIS (34, 35). Those genes that were differentially expressed in IUGR islets are shown in Table 2. Interestingly, nine of 10 differentially expressed genes associated with MSC islet–regenerative potential were upregulated at 2 weeks of age (Table 2). ILK signaling in MSCs mediates their beneficial effects on islets and was predicted by IPA to be significantly increased at 2 weeks in IUGR islets (Table 1). Table 2. Genes Associated With Mesenchymal Stromal Cell Islet Regenerative Capacity Gene  At 2 Weeks  At 10 Weeks  Fold Change  Q Value  Fold Change  Q Value  Anxa1  1.83  0.0387  −2.45  9.93E-05  Cxcl12  —  —  −1.93  0.0062  Col3a1  —  —  −4.05  6.61E-06  Nr1h4  —  —  1.80  0.0014  Crip1  1.97  0.0033  —  —  Dtx4  —  —  −1.93  0.0177  Peg3  —  —  1.70  0.0276  Htra1  1.58  0.0462  −1.86  6.89E-04  Npas2  −2.01  0.0010  —  —  Plec  —  —  −1.72  0.0071  Cd248  —  —  −3.05  1.39E-04  Fbn1  —  —  −3.13  9.48E-07  Fabp5  1.83  0.0446  −2.93  6.81E-06  Capg  —  —  −2.82  6.50E-05  Inf2  —  —  −3.01  5.75E-04  Gstp1  —  —  −2.85  1.61E-11  Fhl1  —  —  −2.65  7.84E-10  Cotl1  1.54  0.0159  —  —  Hbb  —  —  −2.73  0.0018  Nrp2  —  —  −1.58  0.0400  Zyx  —  —  −2.54  1.90E-06  Plin3  —  —  −2.04  5.73E-06  Lats2  1.55  0.0459  —  —  Flnc  1.63  0.0290  −4.47  3.90E-16  Lpp  —  —  −1.79  4.61E-04  Sox17  —  —  −2.70  9.99E-06  Mxra8  —  —  −2.42  1.40E-07  Bag3  —  —  −2.77  2.14E-04  Ehd4  —  —  −1.92  9.42E-06  Fstl1  1.74  0.0084  −1.62  0.0132  Nr1d1  —  —  −1.63  0.0055  Bphl  —  —  1.79  0.0071  Vasn  —  —  −2.95  1.21E-10  Hspb1  —  —  −3.24  4.56E-06  Cyr61  —  —  −2.29  3.80E-05  Xdh  —  —  −5.59  2.91E-14  Thy1  2.14  0.0016  —  —  Gene  At 2 Weeks  At 10 Weeks  Fold Change  Q Value  Fold Change  Q Value  Anxa1  1.83  0.0387  −2.45  9.93E-05  Cxcl12  —  —  −1.93  0.0062  Col3a1  —  —  −4.05  6.61E-06  Nr1h4  —  —  1.80  0.0014  Crip1  1.97  0.0033  —  —  Dtx4  —  —  −1.93  0.0177  Peg3  —  —  1.70  0.0276  Htra1  1.58  0.0462  −1.86  6.89E-04  Npas2  −2.01  0.0010  —  —  Plec  —  —  −1.72  0.0071  Cd248  —  —  −3.05  1.39E-04  Fbn1  —  —  −3.13  9.48E-07  Fabp5  1.83  0.0446  −2.93  6.81E-06  Capg  —  —  −2.82  6.50E-05  Inf2  —  —  −3.01  5.75E-04  Gstp1  —  —  −2.85  1.61E-11  Fhl1  —  —  −2.65  7.84E-10  Cotl1  1.54  0.0159  —  —  Hbb  —  —  −2.73  0.0018  Nrp2  —  —  −1.58  0.0400  Zyx  —  —  −2.54  1.90E-06  Plin3  —  —  −2.04  5.73E-06  Lats2  1.55  0.0459  —  —  Flnc  1.63  0.0290  −4.47  3.90E-16  Lpp  —  —  −1.79  4.61E-04  Sox17  —  —  −2.70  9.99E-06  Mxra8  —  —  −2.42  1.40E-07  Bag3  —  —  −2.77  2.14E-04  Ehd4  —  —  −1.92  9.42E-06  Fstl1  1.74  0.0084  −1.62  0.0132  Nr1d1  —  —  −1.63  0.0055  Bphl  —  —  1.79  0.0071  Vasn  —  —  −2.95  1.21E-10  Hspb1  —  —  −3.24  4.56E-06  Cyr61  —  —  −2.29  3.80E-05  Xdh  —  —  −5.59  2.91E-14  Thy1  2.14  0.0016  —  —  Abbreviation: —, the gene was not differentially expressed at the indicated time point. View Large This trend reversed by 10 weeks in IUGR islets and expression of 29 of 32 differentially expressed genes associated with MSC regenerative capacity was significantly decreased (Table 2). Of particular interest is our finding that Cxcl12 expression was significantly decreased. Cxcl12 encodes stromal cell–derived factor 1 (SDF-1), which is chemotactic for MSCs and has a role in immune modulation (36). SDF-1 is a ligand for CXCR4, and IPA identified significant downregulation of CXCR4 signaling at 10 weeks of age (Table 1). Taken together, these data suggest that IUGR induced a compensatory increase in expression of genes regulating MSC regenerative capacity at 2 weeks, but by 10 weeks, this process was markedly decreased, which may contribute to the progressive loss of islet function in the IUGR rat. Effects of IUGR on islet nutrient metabolism and ion transport in 2- and 10-week-old rats In previous studies, we have shown that glucose-stimulated insulin secretion is markedly impaired in IUGR islets (6–8). Although we previously have shown that abnormal mitochondria function plays a fundamental role in this process (11), it is likely that other metabolic pathways may be disrupted and contribute to impaired insulin secretion. Amino acid metabolism is altered in IUGR islets IPA functional analysis identified amino acid (AA) degradation as among the most important canonical pathways differentially regulated by IUGR at 2 weeks of age (Fig. 4). These pathways included genes involved in metabolism of branched chain AAs (i.e., valine, leucine, isoleucine) and alanine, glycine, methionine, and threonine (Fig. 4). All but one of the genes associated with these pathways were downregulated (Table 3). The one gene exhibiting increased expression was cysteine dioxygenase 1, which converts cysteine and oxygen to cysteine sulfinate (37). Figure 4. View largeDownload slide Ingenuity Pathway Analysis (Qiagen, Hilden, Germany) identifies gene enrichment involving AA degradation in 2-week-old IUGR islets. Green indicates decreased gene expression in IUGR islets compared with controls. Red indicates increased expression. NaN, not a number. Figure 4. View largeDownload slide Ingenuity Pathway Analysis (Qiagen, Hilden, Germany) identifies gene enrichment involving AA degradation in 2-week-old IUGR islets. Green indicates decreased gene expression in IUGR islets compared with controls. Red indicates increased expression. NaN, not a number. Table 3. Differentially Expressed Genes Involved in Amino Acid Metabolism and Transport   Islets at 2 Weeks  Islets at 10 Weeks    Gene  Fold Change  Q Value  Fold Change  Q Value  AA Metabolized  AA metabolism             Mccc1  −2.05  9.60E-03  —  —  Leu   Mccc2  −2.07  1.74E-03  —  —  Leu   Acat1  −2.03  0.0138  —  —  Ile   Bcat2  −2.12  0.0130  −2.58  1.74E-04  Leu, Ile, Val   Acadsb  −2.19  4.99E-04  —  —  Ile, Val   Acad8  −2.43  1.46E-03  −1.74  0.0498  Ile, Val   Ehhadh  −2.38  0.0162  —  —  Ile, Val   Bckdha  −1.83  0.0247  −2.53  1.42E-05  Val   Bckdhb  −2.15  0.0193  −2.10  9.59E-03  Val   Aldh6a1  −1.75  0.0286  −1.66  0.0259  Val   Tdh  −5.82  2.42E-03  −3.67  2.05E-02  Thr   Gcat  −3.92  5.49E-05  −2.93  5.71E-04  Thr   Gpt  −2.00  0.0226  −2.19  2.82E-03  Ala   Gpt2  −2.62  2.83E-04  −1.88  0.0167  Ala   Gamt  −3.52  5.38E-04  −6.83  1.25E-09  Gly   Gatm  −3.81  5.55E-03  −25.68  1.10E-14  Gly   Cdo1  2.13  9.36E-04  —  —  Met   Mtr  −1.79  1.22E-04  —  —  Met   Cbs  −5.12  8.06E-05  −30.18  2.47E-18  Met   Ahcy  −3.42  6.29E-08  −2.41  3.06E-05  Met   Pcca  −2.12  2.78E-03  —  —  Met   Cth  −4.81  3.06E-04  −39.13  5.09E-19  Met   Bhmt  −3.56  3.04E-04  —  —  Met   Gls2  −3.09  8.41E-03  −11.31  1.07E-11  Gln   Gad1  —  —  1.74  4.53E-03  Glu  AA transporter             Slc1a3  —  —  −4.39  3.60E-12  High affinity Glu transporter   Slc1a5  —  —  −1.90  6.67E-03  Neutral AA transporter   Slc3a1  —  —  1.83  5.39E-04  Cystine, dibasic and neutral   Slc6a9  —  —  −4.65  2.79E-11  Gly transporter   Slc6a20  −3.07  1.11E-03  −8.89  1.01E-11  Pro transporter   Slc7a1  −1.73  0.0216  −1.78  5.59E-03  Cationic Y+ system   Slc7a7  −1.76  0.0345  −2.96  5.87E-07  Cationic Y+ system   Slc7a8  −1.97  7.10E-04  —  —  Cationic Y+ system   Slc7a11  −4.66  2.92E-04  −3.42  1.63E-03  Cationic Y+ system   Slc38a2  —  —  −1.50  0.0173  Neutral system A   Slc38a3  −4.18  1.03E-04  −4.15  1.53E-05  Gln, Asn, and His transporter   Slc38a4  —  —  1.64  4.15E-03  Cationic and neutral transporter    Islets at 2 Weeks  Islets at 10 Weeks    Gene  Fold Change  Q Value  Fold Change  Q Value  AA Metabolized  AA metabolism             Mccc1  −2.05  9.60E-03  —  —  Leu   Mccc2  −2.07  1.74E-03  —  —  Leu   Acat1  −2.03  0.0138  —  —  Ile   Bcat2  −2.12  0.0130  −2.58  1.74E-04  Leu, Ile, Val   Acadsb  −2.19  4.99E-04  —  —  Ile, Val   Acad8  −2.43  1.46E-03  −1.74  0.0498  Ile, Val   Ehhadh  −2.38  0.0162  —  —  Ile, Val   Bckdha  −1.83  0.0247  −2.53  1.42E-05  Val   Bckdhb  −2.15  0.0193  −2.10  9.59E-03  Val   Aldh6a1  −1.75  0.0286  −1.66  0.0259  Val   Tdh  −5.82  2.42E-03  −3.67  2.05E-02  Thr   Gcat  −3.92  5.49E-05  −2.93  5.71E-04  Thr   Gpt  −2.00  0.0226  −2.19  2.82E-03  Ala   Gpt2  −2.62  2.83E-04  −1.88  0.0167  Ala   Gamt  −3.52  5.38E-04  −6.83  1.25E-09  Gly   Gatm  −3.81  5.55E-03  −25.68  1.10E-14  Gly   Cdo1  2.13  9.36E-04  —  —  Met   Mtr  −1.79  1.22E-04  —  —  Met   Cbs  −5.12  8.06E-05  −30.18  2.47E-18  Met   Ahcy  −3.42  6.29E-08  −2.41  3.06E-05  Met   Pcca  −2.12  2.78E-03  —  —  Met   Cth  −4.81  3.06E-04  −39.13  5.09E-19  Met   Bhmt  −3.56  3.04E-04  —  —  Met   Gls2  −3.09  8.41E-03  −11.31  1.07E-11  Gln   Gad1  —  —  1.74  4.53E-03  Glu  AA transporter             Slc1a3  —  —  −4.39  3.60E-12  High affinity Glu transporter   Slc1a5  —  —  −1.90  6.67E-03  Neutral AA transporter   Slc3a1  —  —  1.83  5.39E-04  Cystine, dibasic and neutral   Slc6a9  —  —  −4.65  2.79E-11  Gly transporter   Slc6a20  −3.07  1.11E-03  −8.89  1.01E-11  Pro transporter   Slc7a1  −1.73  0.0216  −1.78  5.59E-03  Cationic Y+ system   Slc7a7  −1.76  0.0345  −2.96  5.87E-07  Cationic Y+ system   Slc7a8  −1.97  7.10E-04  —  —  Cationic Y+ system   Slc7a11  −4.66  2.92E-04  −3.42  1.63E-03  Cationic Y+ system   Slc38a2  —  —  −1.50  0.0173  Neutral system A   Slc38a3  −4.18  1.03E-04  −4.15  1.53E-05  Gln, Asn, and His transporter   Slc38a4  —  —  1.64  4.15E-03  Cationic and neutral transporter  Abbreviations: —, the gene was not differentially expressed at the indicated time point; cAMP, cyclic adenosine monophosphate. View Large Because AA metabolism depends on the transport-mediated availability of AAs, we investigated whether gene expression of AA transporters was also differentially expressed in IUGR islets. Consistent with decreased expression of genes involved in AA degradation, we observed downregulation of genes involved in AA transport in islets of 2-week-old IUGR rats (Table 3). Two-week-old IUGR islets exhibited a greater than fourfold reduction in Slc7a11 and Slc38a3 expression than those from control rats. Slc7a11 encodes a cystine/glutamate antiporter that plays a role in intracellular antioxidant defense and extracellular glutamate signaling (38). Slc38a3 encodes glutamine, Na+, and the H+ transporter SN1, and may have roles in nutrient sensing and β-cell function (39–41). In IUGR islets from rats at 10 weeks of age, expression of genes regulating degradation of threonine, glycine, and alanine metabolism pathways remained decreased (Table 3). Fewer genes involved in branched chain AA degradation were differentially expressed, but messenger RNA levels of the initial metabolizing enzyme, Bcat2, were lower than at 2 weeks. Expression of the AA transporters Slc7a11 and Slc38a3 continued to be decreased at 10 weeks of age in addition to that of several others, including glycine transporter Slc6a9 and intracellular glutamate transporter Slc1a3 (Table 3). Thus, we observed reduced expression of genes involved in AA metabolism and trans-cellular transport, which, together, could have deleterious effects on insulin secretion and β-cell proliferation. Genes regulating movement of water and ions are dysregulated in IUGR islets Because regulated movement of ions across the cellular membrane is responsible for changes in membrane potential and the subsequent mobilization of Ca+2 required for insulin secretion, we investigated whether genes encoding ion channels were differentially expressed in IUGR islets. Expression of several genes involved in ion transport was altered, but primarily in 10-week-old IUGR animals (Table 4). Chloride and water transport are intimately involved in cell-volume regulation. Gene expression of chloride channels Ano1, Cftr, and Slc26a8, and water transporters Aqp8 and Aqp12a were significantly downregulated in IUGR islets at 2 weeks of age (Table 4). Decreased expression of Ano1, Aqp8, and Aqp12a persisted into adulthood and was exacerbated such that aquaporins were decreased more than 30-fold in 10-week-old IUGR islets compared with those of control rats (Table 4). Moreover, volume-regulated chloride (Lrrc8c and Slc12a4) and potassium (Kcnk5) channels were decreased in adult IUGR islets (Table 4). Potassium channel KCNQ1 is known to be voltage gated, but it is also responsive to changes in cell volume (42). Therefore, it is unsurprising that, at both ages, Kcnq1 expression levels were decreased in IUGR islets. KCNQ1 auxiliary components Kcne1 and Kcne4, however, were downregulated only at 10 weeks of age (Table 4). In contrast, gene expression of potassium channels that are not sensitive to changes in volume was increased at 10 weeks of age (Table 4). Considering IPA identified pathways associated with edema (Table 1), the selective reduction in gene expression of ion channels regulating cell volume or being regulated by cell volume may indicate a possible compensatory mechanism to protect β-cells from pathological cell swelling. Table 4. Differential Gene Expression Related to Ion and Water Transport     Transport    Gene Expression a  Gene  Alternate Name  Inward  Outward  Regulation  At 2 Weeks  At 10 Weeks  Kcnj11  Kir6.2    K+  ATP  —  ↑  Kcnk16  TALK1    K+  pH  —  ↑  Kcnma1  BK    K+  Ca+2, voltage  —  ↑  Kcnn3  SK3    K+  Ca+2  —  ↑  Kcnq1  KVLQT1    K+  Voltage  ↓↓  ↓↓↓  Kcne1  ISK  Slows KCNQ1 activation  ↓↓↓  ↓↓↓↓  Kcne4    Inhibits KCNQ1 current  —  ↓↓  Kcna2  Kv1.2    K+  Voltage  ↓↓  —  Kcna4  Kv1.4    K+  Voltage  ↑  ↑↑  Kcnb2  Kv2.2    K+  Voltage  —  ↑  Kcnk5  TASK2    K+  Volume, pH  —  ↓↓  Ano1  Tmem16    Cl-  Ca+2  ↓  ↓↓  Cftr      Cl-  ATP  ↓↓  —  Slc26a8  Tat1  Cl−  HCO3−, SO4−2    ↓↓  —  Slc12a2  NKCC1  Cl−, Na+, K+      —  ↓  Slc12a8    Cl−, Na+, K+      ↓  —  Slc12a4  KCC1    Cl−, Na+  Volume  —  ↓  Lrrc8c      Cl−  Volume  —  ↓↓  Clcn5    Cl−  H+  Voltage  —  ↑  Clic4  MTCLIC  Cl−      ↑  ↓  Scn3a  Nav1.3  Na+    Voltage  —  ↑  Scn3b    Na+    Voltage  —  ↑  Trpm4    Na+    Ca+2  —  ↓↓  Trpm5    Na+    Ca+2  —  ↑  Slc8a1  NCX1  Na+  Ca+2  Ca+2  —  ↑  Slc8a3  NCX3  Na+  Ca+2    —  ↑↑  Slc24a3  NCKX3  Na+  Ca+2, K+    —  ↓  Ryr2    Ca+2    Ca+2  —  ↑  Micu3      Ca+2    —  ↑  Trpm3    Ca+2    Sphingosine  —  ↑  Trpa1    Ca+2    Cold  ↑↑  ↑↑  Trpc1    Ca+2      —  ↑  Trpc5    Ca+2    Ca+2  —  ↑  Trpc6    Ca+2, Na+    DAG  —  ↓↓  Itpr2    Ca+2    IP3  —  ↓  Itpr3    Ca+2    IP3  ↓  ↓  Piezo1    Cation channel  Mechanically  —  ↓↓  Aqp1    Water channel    —  ↓↓↓  Aqp8    Water channel    ↓↓↓  ↓↓↓↓  Aqp12a    Water channel    ↓↓  ↓↓↓↓      Transport    Gene Expression a  Gene  Alternate Name  Inward  Outward  Regulation  At 2 Weeks  At 10 Weeks  Kcnj11  Kir6.2    K+  ATP  —  ↑  Kcnk16  TALK1    K+  pH  —  ↑  Kcnma1  BK    K+  Ca+2, voltage  —  ↑  Kcnn3  SK3    K+  Ca+2  —  ↑  Kcnq1  KVLQT1    K+  Voltage  ↓↓  ↓↓↓  Kcne1  ISK  Slows KCNQ1 activation  ↓↓↓  ↓↓↓↓  Kcne4    Inhibits KCNQ1 current  —  ↓↓  Kcna2  Kv1.2    K+  Voltage  ↓↓  —  Kcna4  Kv1.4    K+  Voltage  ↑  ↑↑  Kcnb2  Kv2.2    K+  Voltage  —  ↑  Kcnk5  TASK2    K+  Volume, pH  —  ↓↓  Ano1  Tmem16    Cl-  Ca+2  ↓  ↓↓  Cftr      Cl-  ATP  ↓↓  —  Slc26a8  Tat1  Cl−  HCO3−, SO4−2    ↓↓  —  Slc12a2  NKCC1  Cl−, Na+, K+      —  ↓  Slc12a8    Cl−, Na+, K+      ↓  —  Slc12a4  KCC1    Cl−, Na+  Volume  —  ↓  Lrrc8c      Cl−  Volume  —  ↓↓  Clcn5    Cl−  H+  Voltage  —  ↑  Clic4  MTCLIC  Cl−      ↑  ↓  Scn3a  Nav1.3  Na+    Voltage  —  ↑  Scn3b    Na+    Voltage  —  ↑  Trpm4    Na+    Ca+2  —  ↓↓  Trpm5    Na+    Ca+2  —  ↑  Slc8a1  NCX1  Na+  Ca+2  Ca+2  —  ↑  Slc8a3  NCX3  Na+  Ca+2    —  ↑↑  Slc24a3  NCKX3  Na+  Ca+2, K+    —  ↓  Ryr2    Ca+2    Ca+2  —  ↑  Micu3      Ca+2    —  ↑  Trpm3    Ca+2    Sphingosine  —  ↑  Trpa1    Ca+2    Cold  ↑↑  ↑↑  Trpc1    Ca+2      —  ↑  Trpc5    Ca+2    Ca+2  —  ↑  Trpc6    Ca+2, Na+    DAG  —  ↓↓  Itpr2    Ca+2    IP3  —  ↓  Itpr3    Ca+2    IP3  ↓  ↓  Piezo1    Cation channel  Mechanically  —  ↓↓  Aqp1    Water channel    —  ↓↓↓  Aqp8    Water channel    ↓↓↓  ↓↓↓↓  Aqp12a    Water channel    ↓↓  ↓↓↓↓  Abbreviation: —, the gene was not differentially expressed at the indicated time point. a One arrow: 1.5 ≤ fold change (FC) ≤ 2; two arrows: 2 < FC ≤ 5; three arrows: 5 < FC ≤ 10; four arrows: FC > 10. View Large Recent studies show GLP-1’s phospholipase C–dependent incretin effect is mediated by TRPM4 and TRPM5 sodium channel activity and subsequent Ca+2 mobilization from the endoplasmic reticulum (43). IUGR islets at 10 weeks of age exhibited differential gene expression of ion channels regulating this phospholipase C –dependent potentiation of insulin secretion (Table 4). Specifically, Trpm5 expression was increased, whereas gene expression of Trpm4, Itpr2, and Itpr3 was decreased (Table 4). Taken together, we observed differential gene expression of ion transporters that influence β-cell function. Many of these changes were exacerbated with age and were concordant with age-associated functional decline in IUGR islets. Islets from IUGR rats and human patients with type 2 diabetes share common pathways and genes To assess relevancy of pathogenic mechanisms in our model of IUGR-mediated islet dysfunction to mechanisms impairing islet function in human patients with diabetes, a master list of 1945 gene transcripts correlating with impaired GSIS and/or elevated hemoglobin A1c in patients with diabetes (Fig. 5A) (44–46) was compiled. IPA-generated pathways and genes from the diabetes-associated master list were compared with those from IUGR islets, using the Venny2.0 interactive Venn diagram generator (47). Pathways shared between dysfunctional islets of IUGR rats and human patients with diabetes are listed in Supplemental Table 2. Pathways shared between IUGR islets at both ages and in human patients with diabetes include the unfolded protein response, cyclic adenosine monophosphate (cAMP)–mediated signaling, microtubule dynamics, organization of cytoskeleton, glucose tolerance, fibrogenesis, and cell proliferation of fibroblasts. The only pathway that overlapped between 2-week-old IUGR islets and human diabetic islets was proliferation of endocrine cells and, indeed, previous studies have shown diminished β-cell replication in IUGR islets compared with controls (7, 48). Overlapping exclusively with IUGR islets at 10 weeks of age were signaling pathways related to epithelial adherens junctions HIPPO, HGF, and CXCR4, as well as pathology associated with amyloidosis. Together, these shared pathways support a role for modulation of the islet microenvironment, physical connectivity, and the participation of stromal cells in the pathogenesis of human type 2 diabetes and in our IUGR model. Figure 5. View largeDownload slide Venn diagrams illustrating (A) number of genes associated with islet dysfunction from humans with diabetes from three published reports (44–46) and (B) overlap between genes differentially expressed in IUGR islets and human diabetic islets. T2D, type 2 diabetes. Figure 5. View largeDownload slide Venn diagrams illustrating (A) number of genes associated with islet dysfunction from humans with diabetes from three published reports (44–46) and (B) overlap between genes differentially expressed in IUGR islets and human diabetic islets. T2D, type 2 diabetes. Despite appreciable pathway overlap between dysfunctional islets from IUGR rats and humans, individual genes within pathways could differ considerably; therefore, the genes themselves were also compared. In IUGR islets, 76 and 237 genes at 2 and 10 weeks, respectively, were found to overlap with the master list of diabetes-associated genes. A total of 41 genes were common among all groups (Fig. 5B; Supplemental Table 3). Unsurprisingly, the 41 genes were enriched in endoplasmic reticulum stress response [i.e., Eif2ak3 (PERK), Sel1l, and Xbp1] and cAMP-mediated signaling (i.e., Akap2, Camk1d, Pde8b, and Smpdl3a). Ten genes overlapped with the master list of diabetes-associated genes in human islets and genes differentially expressed in IUGR islets from rats at embryonic day 19.5 [previously published microarray data (8)], and 2 and 10 weeks of age. Expression of Pde8b, Edaradd, Ptf1a, Slc16a7, Rab27b, Mgat4a, Cmtm8, Tmed6, Kcnq1, and Sel1l was increased in fetal IUGR islets and decreased at 2 and 10 weeks of age. These changes indicate that decreased expression of these genes may engender islet dysfunction in IUGR rats and also contribute to human type 2 diabetes islet dysfunction. Discussion In this study, we identified mechanisms involved in the pathogenesis of IUGR islet dysfunction. These results support findings of our previous phenotypic studies and reveal pathways contributing to islet dysfunction in IUGR rats. Importantly, many of these genes and pathways overlap with those already identified in human type 2 diabetic islets. A key finding of our study was the observation that multiple genes regulating fibrosis in IUGR islets at 2 weeks of age were differentially expressed, suggesting fibrogenesis participates fundamentally in the initiation of the abnormal islet phenotype in diabetes. Fibrogenesis induces immune-cell trafficking and remodeling of the ECM in the islet (49–51). Indeed, IPA showed stellate-cell activation and fibrosis to be among the most enriched pathways in 2- and 10-week-old IUGR islets, and fibrogenesis was also identified as a dysregulated pathway in human diabetic islets. Activated stellate cells influence T-cell differentiation and activation toward a Th2 response (52), which is consistent with our previous IUGR studies showing elevated levels of Th2 cytokine IL-4 (8). Another important finding was the extensive changes in expression of genes related to modulation of the islet microenvironment and cellular communication with the ECM. Many differentially expressed genes encode components of the ECM that serve structural and instructive roles influencing cell migration, proliferation, insulin gene transcription, and nutrient-stimulated insulin secretion (53–55). Laminins and collagen types 1 and 3 through 6, which are secreted by cells of the vasculature and known to help maintain proper islet function (56–58), are decreased in IUGR islets by age 10 weeks. Moreover, the reduction in vasculature-derived laminins and collagens is consistent with the progressive loss of capillary density observed in IUGR islets (8). The effect of these extracellular components on islet function is mediated primarily through their interaction with integrins (54, 58, 59) whose gene expression was also decreased in IUGR islets at 10 weeks of age. These changes were not as robust at 2 weeks of age, suggesting there is a progressive loss of interactions between cells and the ECM that are integral to islet function, thereby contributing to progressive IUGR-mediated islet dysfunction. Another important component of the ECM, HA, is increased in response to tissue injury and proinflammatory cytokines (60–62). We observed increased gene expression of the HA-synthesizing protein Has2 and increased peri-islet HA staining in IUGR islets. This early increase in HA levels is consistent with changes observed in islets from human patients and from rodents with type 1 diabetes (26, 49). Moreover, studies have shown HA accumulates in lymphedematous fibrotic tissue. Interestingly, islet lymphatic vessels are localized to the islet and exocrine interface, where increased HA staining was observed (63). HA and CXCL12 are chemotactic for MSCs via interactions with CD44 and CXCR4/7, respectively (64, 65). Expression of the genes encoding these proteins was increased at age 2 weeks but decreased at age 10 weeks in IUGR islets, pointing to modulation of ligands and receptors mediating MSC migration. MSCs possess regenerative capabilities in islet grafts (34, 35, 66, 67), and genes associated with this beneficial effect mirror the pattern of genes regulating their chemotaxis; that is, their expression was increased in IUGR islets at 2 weeks of age but decreased at 10 weeks of age. Although CXCR4 and CXCR7 mediate migration and confer CXCL12’s beneficial effects, CXCR7 has an added function in regard to MSC proliferation and viability that is absent with CXCR4 (65, 68, 69). Interestingly, Cxcr7, but not Cxcr4, was differentially expressed in IUGR islets, suggesting that MSC migration, proliferation, and viability are altered in IUGR islets. The MSC-associated genes identified as conferring benefits to islets are not exclusively expressed by MSCs (70–72); thus, the changes in gene expression could be attributed to other islet cell types such as fibroblasts and microvascular-associated pericytes (73). MSC ILK signaling may be necessary to confer MSCs’ beneficial effects, and ILK signaling in islet endocrine cells is required for normal intraislet vascularization and insulin secretion (74). Therefore, attenuated ILK signaling in either MSCs or endocrine cells would impair islet function, but because the islet is a mixed-cell population, we were unable to delineate the cell type displaying attenuated ILK signaling and, subsequently, the specific mechanism involved. Regardless of origin, SDF-1 (Cxcl12), ANXA1, and ILK signaling have been shown to confer restorative properties to islets (75, 76), and their expression levels were modulated by IUGR. That gene expression associated with MSCs’ regenerative capacity was increased at 2 weeks and decreased at 10 weeks of age elucidates another mechanism of age-associated disease progression. A surprising finding of this study was gene-expression changes in IUGR islets related to the progressive loss of islet cell-to-cell interactions that are critical to maintaining structural integrity and cellular communication. These intercellular connections allow heterogenic β-cell populations within the normal islet to coordinate secretory responses to glucose such that loss of these connections result in augmented basal insulin secretion and attenuated GSIS (77–81). These aberrant insulin secretory responses associated with β-cell disconnectivity are observed in IUGR islets (8, 82). Indeed, findings of this and other studies indicate dysfunctional islets are more homogenous in their transcriptomes than are normal islets (14), which may be reflective of the diminished cell-to-cell communication that affords physiological and transcriptomic β-cell diversity. The regulated transport of ions across the plasma membrane is indispensable for GSIS. Few ion channel genes were differentially expressed in IUGR islets at 2 weeks of age, but those altered were primarily associated with anion transport (i.e., Ano1, Cftr, and Slc26a8) and Kcnq1 potassium transport. Previous studies showed these anion transporters coprecipitate and interact with one another to mediate cAMP responses (83–85). Their decreased expression at 2 weeks of age may contribute to the decreased cAMP-mediated signaling predicted by IPA and to the GSIS impairment observed in IUGR islets at this age (6, 8). Many more genes encoding ion channels were differentially expressed in IUGR islets at 10 weeks of age, including downregulation of transporters involved in cell-volume regulation including chloride channels, volume-regulated ion channels, and aquaporins. Intracellular chloride concentrations are kept above equilibrium by NKCC1 (86–88), whose gene expression was decreased in IUGR islets at 10 weeks of age. Decreased intracellular chloride concentration can diminish GSIS (86, 89, 90). Glycolytic intermediates increase intracellular osmolarity, leading to water influx, subsequent cell-volume increase, and activation of volume-regulated anion channels (90). The latter event causes a depolarizing current that complements the current generated by closure of the adenosine triphosphate–sensitive potassium (KATP) channel; together, these two currents facilitate first-phase insulin secretion (90, 91). It is this first-phase insulin secretory response that is most prominently impaired in IUGR islets (6). Interestingly, Kcnj11, which encodes the pore-forming subunit of the KATP channel, is increased in IUGR islets at 10 weeks of age, suggesting modulation of volume-regulated currents contributes more to IUGR islet dysfunction than previously recognized. In addition to Kcnj11, expression of genes regulating Ca+2-dependent or voltage-gated potassium channels, which contribute to membrane repolarization, is increased in IUGR islets. However the volume-sensitive, voltage-gated potassium channel encoded by Kcnq1 was decreased. It may be that increased, voltage-gated potassium channel expression was compensating for the reduction in Kcnq1 expression, suggesting that diminished volume regulation supersedes other changes in ion channel expression. Thus, differentially expressed ion channels highlight the importance of cell-volume regulation and anion mobilization in insulin secretion. These channels and transporters were differentially expressed at 2 weeks of age, but dysregulated expression was more pronounced in IUGR islets at 10 weeks of age, consistent with the progression of the IUGR islet phenotype. Dysregulated AA degradation in IUGR islets was an unexpected finding and, in contrast to most other pathways that were more disrupted at 10 weeks, was far more pronounced at 2 weeks of age. AA degradation occurs primarily in mitochondria, because the products of their breakdown are tricarboxylic acid cycle intermediates. Therefore, decreased AA degradation may lead to a decreased pool of tricarboxylic acid cycle intermediates. This has direct relevance to the IUGR islet phenotype because mitochondrial function is significantly impaired (11). AA metabolism depends on AA transport-mediated availability and AA transporters were differentially expressed at both ages in IUGR islets. Without quantification of AAs and their metabolites, we cannot expound on how these changes might affect islet physiology, but the importance of AAs in IUGR islet pathogenesis is evidenced by normalization of islet vascularity and function with AA supplementation (92). Of importance was our finding that many pathways identified in IUGR islets were also disrupted in islets from humans with type 2 diabetes, including those regulating cell adherence and their associated signaling pathways that modulate the cytoskeleton. These same pathways were also dysregulated in fetal islets in a sheep model of hyperthermia-induced IUGR, pointing to the pathways’ importance in the pathogenesis of islet dysfunction in diabetes (14). Interestingly, amyloidosis was another enriched pathway in 10-week-old IUGR islets and humans, indicating that although amyloid deposition does not occur in rodent models of diabetes (93), the underlying mechanism contributing to this defect also occurs in IUGR rats. Although IUGR is one of many factors contributing to type 2 diabetes risk, the overlap of pathways associated with islet dysfunction in IUGR rats and in humans strongly suggests that the diverse etiologies of type 2 diabetes converge mechanistically to disrupt islet function. In summary, we identified mechanisms contributing to IUGR-induced islet dysfunction. Moreover, temporal changes in gene expression were evident in our islet transcriptome analysis, with juvenile and adult IUGR islets displaying different patterns, underscoring the advantage of performing analyses at time points before the development of diabetes and during the progression of the disease. By doing so, we were able to uncover mechanisms by which islet dysfunction becomes exacerbated with age in IUGR animals. Last, comparing differentially expressed genes in our IUGR islets with those of human patients with diabetes supports a role for these mechanisms in islet dysfunction in type 2 diabetes. Additional studies are needed to corroborate these findings and determine specifically the effect alterations in these pathways have on IUGR-mediated islet abnormalities. Abbreviations: AA amino acid cAMP cyclic adenosine monophosphate ECM extracellular matrix GSIS glucose-stimulated insulin secretion HA hyaluronic acid Has2 hyaluronan-synthesizing enzyme ILK integrin-linked kinase IPA Ingenuity Pathway Analysis IUGR intrauterine growth restriction KATP adenosine triphosphate–sensitive potassium MSC mesenchymal stromal cell qPCR quantitative polymerase chain reaction RNAseq RNA sequencing SDF-1 stromal cell–derived factor 1. Acknowledgments Financial Support: The experiments performed in this study were funded by National Institutes of Health, Eunice Kennedy Shriver National Institute of Child Health and Human Development Grant T32HD60556 and National Institute of Diabetes and Digestive and Kidney Diseases Grant R01DK55704 (to R.A.S.). 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