Defective IGF2 and IGF1R protein production in embryonic pancreas precedes beta cell mass anomaly in the Goto-Kakizaki rat model of type 2 diabetes

The Parasite-Derived Peptide, FhHDM-1, Selectively Modulates miRNA Expression in β-Cells to Prevent Apoptotic Pathways Induced by Proinflammatory Cytokines

We have previously identified a parasite-derived peptide, FhHDM-1, that prevented the progression of diabetes in nonobese diabetic (NOD) mice. Disease prevention was mediated by the activation of the PI3K/Akt pathway to promote β-cell survival and metabolism without inducing proliferation. To determine the molecular mechanisms driving the antidiabetogenic effects of FhHDM-1, miRNA:mRNA interactions and in silico predictions of the gene networks were characterised in β-cells, which were exposed to the proinflammatory cytokines that mediate β-cell destruction in Type 1 diabetes (T1D), in the presence and absence of FhHDM-1. The predicted gene targets of miRNAs differentially regulated by FhHDM-1 mapped to the biological pathways that regulate β-cell biology. Six miRNAs were identified as important nodes in the regulation of PI3K/Akt signaling. Additionally, IGF-2 was identified as a miRNA gene target that mediated the beneficial effects of FhHDM-1 on β-cells. The findings provide a putative mechanism by which FhHDM-1 positively impacts β-cells to permanently prevent diabetes. As β-cell death/dysfunction underlies diabetes development, FhHDM-1 opens new therapeutic avenues.

Diabetic retinopathy: a comprehensive update on in vivo, in vitro and ex vivo experimental models

Diabetic retinopathy (DR), one of the leading causes of visual impairment and blindness worldwide, is one of the major microvascular complications in diabetes mellitus (DM). Globally, DR prevalence among DM patients is 25%, and 6% have vision-threatening problems among them. With the higher incidence of DM globally, more DR cases are expected to be seen in the future. In order to comprehend the pathophysiological mechanism of DR in humans and discover potential novel substances for the treatment of DR, investigations are typically conducted using various experimental models. Among the experimental models, in vivo models have contributed significantly to understanding DR pathogenesis. There are several types of in vivo models for DR research, which include chemical-induced, surgical-induced, diet-induced, and genetic models. Similarly, for the in vitro models, there are several cell types that are utilised in DR research, such as retinal endothelial cells, Müller cells, and glial cells. With the advancement of DR research, it is essential to have a comprehensive update on the various experimental models utilised to mimic DR environment. This review provides the update on the in vitro, in vivo, and ex vivo models used in DR research, focusing on their features, advantages, and limitations.

Hormonal Determinants of Growth and Weight Gain in the Human Fetus and Preterm Infant

The factors controlling linear growth and weight gain in the human fetus and newborn infant are poorly understood. We review here the changes in linear growth, weight gain, lean body mass, and fat mass during mid- and late gestation and the early postnatal period in the context of changes in the secretion and action of maternal, placental, fetal, and neonatal hormones, growth factors, and adipocytokines. We assess the effects of hormonal determinants on placental nutrient delivery and the impact of preterm delivery on hormone expression and postnatal growth and metabolic function. We then discuss the effects of various maternal disorders and nutritional and pharmacologic interventions on fetal and perinatal hormone and growth factor production, growth, and fat deposition and consider important unresolved questions in the field.

Discovering genetic linkage between periodontitis and type 1 diabetes: A bioinformatics study

Background: Relationship between periodontitis (PD) and type 1 diabetes (T1D) has been reported, but the detailed pathogenesis requires further elucidation. This study aimed to reveal the genetic linkage between PD and T1D through bioinformatics analysis, thereby providing novel insights into scientific research and clinical treatment of the two diseases.

Methods: PD-related datasets (GSE10334, GSE16134, GSE23586) and T1D-related datasets(GSE162689)were downloaded from NCBI Gene Expression Omnibus (GEO). Following batch correction and merging of PD-related datasets as one cohort, differential expression analysis was performed (adjusted p-value <0.05 and ∣log2  fold change| > 0.5), and common differentially expressed genes (DEGs) between PD and T1D were extracted. Functional enrichment analysis was conducted via Metascape website. The protein-protein interaction (PPI) network of common DEGs was generated in The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. Hub genes were selected by Cytoscape software and validated by receiver operating characteristic (ROC) curve analysis.

Results: 59 common DEGs of PD and T1D were identified. Among these DEGs, 23 genes were commonly upregulated, and 36 genes were commonly downregulated in both PD- and T1D-related cohorts. Functional enrichment analysis indicated that common DEGs were mainly enriched in tube morphogenesis, supramolecular fiber organization, 9 + 0 non-motile cilium, plasma membrane bounded cell projection assembly, glomerulus development, enzyme-linked receptor protein signaling pathway, endochondral bone morphogenesis, positive regulation of kinase activity, cell projection membrane and regulation of lipid metabolic process. After PPI construction and modules selection, 6 hub genes (CD34, EGR1, BBS7, FMOD, IGF2, TXN) were screened out and expected to be critical in linking PD and T1D. ROC analysis showed that the AUC values of hub genes were all greater than 70% in PD-related cohort and greater than 60% in T1D-related datasets.

Conclusion: Shared molecular mechanisms between PD and T1D were revealed in this study, and 6 hub genes were identified as potential targets in treating PD and T1D.

Intrauterine exposure of mice to arsenite induces abnormal and transgenerational glycometabolism

The adverse, transgenerational effects on health caused by environmental pollutants are receiving increasing attention. For humans and mice, inorganic arsenic (iAs), a widespread environmental contaminant, is associated with diabetic phenotypes. However, the transgenerational effects of arsenite-induced changes in glucose metabolism in mice have not been fully investigated. In the present study, F0 pregnant mice were exposed to arsenite via drinking water (0, 0.5, 5, or 50 ppm NaAsO₂) from gestational day 0 (GD0) until parturition. We examined the effects of arsenite exposure on the metabolic phenotypes and the levels of proteins and genes related to glucose metabolism of dams and their offspring (F1∼F4). Arsenite exposure altered the glucose tolerance of offspring. Notably, glucose transporter-2 (GLUT2) and insulin receptor substrate-1 (IRS1), which are related to the maintenance of glucose homeostasis, were also changed. The homeostasis assessment-insulin resistance (HOMA-IR), an indicator of insulin resistance, was higher in the offspring from the F0 female mice exposed to arsenite. Furthermore, imprinted genes, insulin-like growth factor 2 (IGF2) and potassium voltage-gated channel subfamily Q member 1 (KCNQ1), related to glycometabolism across multiple generations, were lower in the offspring. In sum, arsenite exposure during pregnancy transgenerationally affects glucose metabolism, which is related to altered levels of IGF2 and KCNQ1.

Vesiculin derived from IGF-II drives increased islet cell mass in a mouse model of pre-diabetes

Pancreatic islet-cell function and volume are both key determinants of the maintenance of metabolic health. Insulin resistance and islet-cell dysfunction often occur in the earlier stages of type 2 diabetes (T2D) progression. The ability of the islet cells to respond to insulin resistance by increasing hormone output accompanied by increased islet-cell volume is key to maintaining blood glucose control and preventing further disease progression. Eventual β-cell loss is the main driver of full-blown T2D and insulin-dependency. Researchers are targeting T2D with approaches that include those aimed at enhancing the function of the patient's existing β-cell population, or replacing islet β-cells. Another approach is to look for agents that enhance the natural capacity of the β-cell population to expand. Here we aimed to study the effects of a new putative β-cell growth factor on a mouse model of pre-diabetes. We asked whether: 1) 4-week's treatment with vesiculin, a two-chain peptide derived by processing from IGF-II, had any measurable effect on pre-diabetic mice vs vehicle; and 2) whether the effects were the same in non-diabetic littermate controls. Although treatment with vesiculin did not alter blood glucose levels over this time period, there was a doubling of the Proliferating Cell Nuclear Antigen (PCNA) detectable in the islets of treated pre-diabetic but not control mice and this was accompanied by increased insulin- and glucagon-positive stained areas in the pancreatic islets.

H19: A vital long noncoding RNA in the treatment of diabetes and diabetic complications

BACKGROUND

Increasing academic efforts have been made to explore the correlation of long noncoding RNAs (lncRNAs) with human diseases, particularly metabolic diseases like diabetes mellitus. Taking lncRNA H19 as an example, this review intends to reveal the functions and mechanism of lncRNA H19 in diabetes mellitus and diabetic complications.

METHODS

The research results associated with lncRNA H19 and diabetes mellitus are collected and summarized on PubMed.

CONCLUSION

LncRNA H19 is a potential instructive marker for the treatment of diabetes mellitus and diabetic complications.

Transient antibiotic-induced changes in the neonatal swine intestinal microbiota impact islet expression profiles reducing subsequent function

Neonatal antibiotics administered to human infants initiate gut microbiota dysbiosis that may have long-term effects on body weight and metabolism. We examined antibiotic-induced adaptations in pancreatic islets of the piglet, a well-accepted model of human infant microbiota and pancreas development. Neonatal piglets randomized to amoxicillin [30 mg/kg body wt/day; n = 7, antibiotic (ANTI)] or placebo [vehicle control; n = 7, control (CON)] from postnatal day (PND)0-13 were euthanized at PND7, 14, and 49. The metabolic phenotype along with functional, immunohistological, and transcriptional phenotypes of the pancreatic islets were studied. The gut microbiome was characterized by 16S rRNA gene sequencing, and microbial metabolites and microbiome-sensitive host molecules were measured. Compared with CON, ANTI PND7 piglets had elevated transcripts of genes involved in glucagon-like peptide 1 ((GLP-1) synthesis or signaling in islets (P < 0.05) coinciding with higher plasma GLP-1 (P = 0.11), along with increased tumor necrosis factor α (Tnf) (P < 0.05) and protegrin 1 (Npg1) (P < 0.05). Antibiotic-induced relative increases in Escherichia, Coprococcus, Ruminococcus, Dehalobacterium, and Oscillospira of the ileal microbiome at PND7 normalized after antibiotic withdrawal. In ANTI islets at PND14, the expression of key regulators pancreatic and duodenal homeobox 1 (Pdx1), insulin-like growth factor-2 (Igf2), and transcription factor 7-like 2 (Tcf7l2) was downregulated, preceding a 40% reduction of β-cell area (P < 0.01) and islet insulin content at PND49 (P < 0.05). At PND49, a twofold elevated plasma insulin concentration (P = 0.07) was observed in ANTI compared with CON. We conclude that antibiotic treatment of neonatal piglets elicited gut microbial changes accompanied by phasic alterations in key regulatory genes in pancreatic islets at PND7 and 14. By PND49, reduced β-cell area and islet insulin content were accompanied by elevated nonfasted insulin despite normoglycemia, indicative of islet stress.

Autocrine IGF2 programmes β-cell plasticity under conditions of increased metabolic demand

When exposed to nutrient excess and insulin resistance, pancreatic β-cells undergo adaptive changes in order to maintain glucose homeostasis. The role that growth control genes, highly expressed in early pancreas development, might exert in programming β-cell plasticity in later life is a poorly studied area. The imprinted Igf2 (insulin-like growth factor 2) gene is highly transcribed during early life and has been identified in recent genome-wide association studies as a type 2 diabetes susceptibility gene in humans. Hence, here we investigate the long-term phenotypic metabolic consequences of conditional Igf2 deletion in pancreatic β-cells (Igf2βKO) in mice. We show that autocrine actions of IGF2 are not critical for β-cell development, or for the early post-natal wave of β-cell remodelling. Additionally, adult Igf2βKO mice maintain glucose homeostasis when fed a chow diet. However, pregnant Igf2βKO females become hyperglycemic and hyperinsulinemic, and their conceptuses exhibit hyperinsulinemia and placentomegalia. Insulin resistance induced by congenital leptin deficiency also renders Igf2βKO females more hyperglycaemic compared to leptin-deficient controls. Upon high-fat diet feeding, Igf2βKO females are less susceptible to develop insulin resistance. Based on these findings, we conclude that in female mice, autocrine actions of β-cell IGF2 during early development determine their adaptive capacity in adult life.

Plastics derived endocrine-disrupting compounds and their effects on early development

Despite the fact that the estrogenic effects of bisphenols were first described 80 years ago, recent data about its potential negative impact on birth outcome parameters raises a strong rationale to investigate further. The adverse health effects of plastics recommend to measure the impacts of endocrine-disrupting compounds (EDCs) such as bisphenols (BPA, BPS, BPF), bis(2-ethylhexyl) phthalate, and dibutyl phthalate (DBP) in human health. Exposure to these compounds in utero may program the diseases of the testis, prostate, kidney and abnormalities in the immune system, and cause tumors, uterine hemorrhage during pregnancy and polycystic ovary. These compounds also control the processes of epigenetic transgenerational inheritance of adult-onset diseases by modulating DNA methylation and epimutations in reproductive cells. The early developmental stage is the most susceptible window for developmental and genomic programming. The critical stages of the events for a normal human birth lie between the many transitions occurring between spermatogenesis, egg fertilization and the fully formed fetus. As the cells begin to grow and differentiate, there are critical balances of hormones, and protein synthesis. Data are emerging on how these plastic-derived compounds affect embryogenesis, placentation and feto-placental development since pregnant women and unborn fetuses are often exposed to these factors during preconception and throughout gestation. Impaired early development that ultimately influences fetal outcomes is at the center of many developmental disorders and contributes an independent risk factor for adult chronic diseases. This review will summarize the current status on the impact of exposure to plastic derived EDCs on the growth, gene expression, epigenetic and angiogenic activities of the early fetal development process and their possible effects on birth outcomes.

Epigenetic modifications associated with in utero exposure to endocrine disrupting chemicals BPA, DDT and Pb

Endocrine disrupting chemicals (EDCs) are xenobiotics which adversely modify the hormone system. The endocrine system is most vulnerable to assaults by endocrine disruptors during the prenatal and early development window, and effects may persist into adulthood and across generations. The prenatal stage is a period of vulnerability to environmental chemicals because the epigenome is usually reprogrammed during this period. Bisphenol A (BPA), lead (Pb), and dichlorodiphenyltrichloroethane (DDT) were chosen for critical review because they have become serious public health concerns globally, especially in Africa where they are widely used without any regulation. In this review, we introduce EDCs and describe the various modes of action of EDCs and the importance of the prenatal and developmental windows to EDC exposure. We give a brief overview of epigenetics and describe the various epigenetic mechanisms: DNA methylation, histone modifications and non-coding RNAs, and how each of them affects gene expression. We then summarize findings from previous studies on the effects of prenatal exposure to the endocrine disruptors BPA, Pb and DDT on each of the previously described epigenetic mechanisms. We also discuss how the epigenetic alterations caused by these EDCs may be related to disease processes.

Maternally expressed gene 3 in metabolic programming

Maternally Expressed Gene 3 (MEG3) is a long noncoding RNA (lncRNA) that coordinates a diverse array of cellular processes requiring epigenetic regulation of genes and interactions with key signaling proteins and by acting as a competitive endogenous (ce)RNA. Epigenetic modifications driven by in utero nutrition affect MEG3 expression and its role in the development of multiple metabolic disorders. This review examines how epigenetic modification of MEG3 expression can confer adaptedness to different metabolic environments. To this end, we discuss how nutritional status that leads to an increase of MEG3 expression can protect against cancer and metabolic dysfunctions, while interventions that promote MEG3 downregulation minimize the pleiotropic costs associated with its expression. Lastly, we identify research directions that would further shed light on the role of MEG3 in metabolic regulation and in functional imprinted gene networks. This article is part of a Special Issue entitled: ncRNA in control of gene expression edited by Kotb Abdelmohsen.

Epidemiological Investigation of Type 2 Diabetes and Alzheimer's Disease in a Pakistani Population

The epidemic of type 2 diabetes mellitus (T2DM) and the possibility of it contributing to the risk of Alzheimer's disease (AD) have become important health concerns worldwide and in Pakistan, where the co-occurrence of T2DM and AD is becoming more frequent. To gain insights on this phenomenon, a cross-sectional study was initiated. We recruited and interviewed 820 research participants from four cities in Pakistan: 250 controls, 450 T2DM, 100 AD, and 20 with both diseases. Significant differences between groups were observed for age (p < 0.0001), urban vs. rural locality (p = 0.0472) and residing near industrial areas. The average HbA1c (%) level was 10.68 ± 2.34 in the T2DM group, and females had a lower level than males (p = 0.003). In the AD group, significant relationships existed between education and family history. Overall, the results suggest that T2DM and AD were associated with both socio-demographic and environmental factors in Pakistani participants. Detailed molecular investigations are underway in our laboratory to decipher the differential genetic pathways of the two diseases to address their increasing prevalence in this developing nation.

ZBED6 negatively regulates insulin production, neuronal differentiation, and cell aggregation in MIN6 cells

Zinc finger BED domain containing protein 6 ( Zbed6) has evolved from a domesticated DNA transposon and encodes a transcription factor unique to placental mammals. The aim of the present study was to investigate further the role of ZBED6 in insulin-producing cells, using mouse MIN6 cells, and to evaluate the effects of Zbed6 knockdown on basal β-cell functions, such as morphology, transcriptional regulation, insulin content, and release. Zbed6-silenced cells and controls were characterized with a range of methods, including RNA sequencing, chromatin immunoprecipitation sequencing, insulin content and release, subplasma membrane Ca²⁺ measurements, cAMP determination, and morphologic studies. More than 700 genes showed differential expression in response to Zbed6 knockdown, which was paralleled by increased capacity to generate cAMP, as well as by augmented subplasmalemmal calcium concentration and insulin secretion in response to glucose stimulation. We identified >4000 putative ZBED6-binding sites in the MIN6 genome, with an enrichment of ZBED6 sites at upregulated genes, such as the β-cell transcription factors v-maf musculoaponeurotic fibrosarcoma oncogene homolog A and Nk6 homeobox 1. We also observed altered morphology/growth patterns, as indicated by increased cell clustering, and in the appearance of axon-like Neurofilament, medium polypeptide and tubulin β 3, class III-positive protrusions. We conclude that ZBED6 acts as a transcriptional regulator in MIN6 cells and that its activity suppresses insulin production, cell aggregation, and neuronal-like differentiation.-Wang, X., Jiang, L., Wallerman, O., Younis, S., Yu, Q., Klaesson, A., Tengholm, A., Welsh, N., Andersson, L. ZBED6 negatively regulates insulin production, neuronal differentiation, and cell aggregation in MIN6 cells.

Insulin and IGF-1 receptor autocrine loops are not required for Exendin-4 induced changes to pancreatic β-cell bioenergetic parameters and metabolism in BRIN-BD11 cells

Pharmacological long lasting Glucagon-like peptide-1 (GLP-1) analogues, such as Exendin-4, have become widely used diabetes therapies. Chronic GLP-1R stimulation has been linked to β-cell protection and these pro-survival actions of GLP-1 are dependent on the activation of the mammalian target of rapamycin (mTOR) leading to accumulation of Hypoxia inducible factor 1 alpha (HIF-1α). Recent studies from our lab indicate that prolonged GLP-1R stimulation promotes metabolic reprograming of β-cells towards a highly glycolytic phenotype and activation of the mTOR/HIF-1α pathway was required for this action. We hypothesised that GLP-1 induced metabolic changes depend on the activation of mTOR and HIF-1α, in a cascade that occurs after triggering of a potential Insulin-like growth factor 1 receptor (IGF-1R) or the Insulin receptor (IR) autocrine loops. Loss of function of these receptors, through the use of small interfering RNA, or neutralizing antibodies directed towards their products, was undertaken in conjunction with functional assays. Neither of these strategies mitigated the effect of GLP-1 on glucose uptake, protein expression or bioenergetic flux. Our data indicates that activation of IGF-1R and/or the IR autocrine loops resulting in β-cell protection and function, involve mechanisms independent to the enhanced metabolic effects resulting from sustained GLP-1R activation.

IGF2 stimulates fetal growth in a sex- and organ-dependent manner

BackgroundInsulin-like growth factor 2 (IGF2) is a key determinant of fetal growth, and the altered expression of IGF2 is implicated in fetal growth disorders and maternal metabolic derangements including gestational diabetes. Here we studied how increased levels of IGF2 in late pregnancy affect fetal growth.MethodsWe employed a rat model of repeated intrafetal IGF2 administration in late pregnancy, i.e., during GD19-GD21, and measured the consequences on fetal organ weight and expression of insulin/IGF-axis components.ResultsIGF2 treatment tended to increase fetal weight, but only weight increase of the fetal stomach reached significance (+33±9%; P<0.01). Sex-dependent data analysis revealed a sexual dimorphism of IGF2 action. In male fetuses, IGF2 administration significantly increased fetal weight (+13±3%; P<0.05) and weight of fetal stomach (+42±10%; P<0.01), intestine (+26±5%; P<0.05), liver (+13±4%; P<0.05), and pancreas (+25±8%; P<0.05). Weights of heart, lungs, and kidneys were unchanged. In female fetuses, IGF2 increased only stomach weight (+26±9%; P<0.05). Furthermore, gene expression of insulin/IGF axis in the heart, lungs, liver, and stomach was more sensitive toward IGF2 treatment in male than in female fetuses.ConclusionData suggest that elevated circulating IGF2 in late pregnancy predominantly stimulates organ growth of the digestive system, and male fetuses are more susceptible toward the IGF2 effects than female fetuses.

Comparison of Goto-Kakizaki rats and high fat diet-induced obese rats: Are they reliable models to study Type 2 Diabetes mellitus?

Type 2 Diabetes mellitus (T2DM) is an evident growing disease that affects different cultures throughout the world. T2DM occurs under the influence of three main factors: the genetic background, environmental and behavioral components. Obesity is strongly associated to the development of T2DM in the occident, while in the orient most of the diabetic patients are considered lean. Genetics may be a key factor in the development of T2DM in societies where obesity is not a recurrent public health problem. Herein, two different models of rats were used to understand their differences and reliability as experimental models to study the pathophysiology of T2DM, in two different approaches: the genetic (GK rats) and the environmental (HFD-induced obese rats) influences. GK rats were resistant to weight gain even though food/energy consumption (relative to body weight) was higher in this group. HFD, on the other hand, induced obesity in Wistar rats. White adipose tissue (WAT) expansion in this group was accompanied by immune cells infiltration, inflammation and insulin resistance. GK rats also presented WAT inflammation and insulin resistance; however, no immune cells infiltration was observed in the WAT of this group. Liver of HFD group presented fat accumulation without differences in inflammatory cytokines content, while liver of GK rats didn't present fat accumulation, but showed an increase of IL-6 and IL-10 content and glycogen. Also, GK rats showed increased plasma GOT and GPT. Soleus muscle of HFD presented normal insulin signaling, contrary to GK rats, which presented higher content of basal phosphorylation of GSK-3β. Our results demonstrated that HFD developed a mild insulin resistance in Wistar rats, but was not sufficient to develop T2DM. In contrast, GK rats presented all the typical hallmarks of T2DM, such as insulin resistance, defective insulin production, fasting hyperglycemia/hyperinsulinemia and lipid plasma alteration. Thus, on the given time point of this study, we may conclude that only GK rats shown to be a reliable model to study T2DM.

Transgenerational pancreatic impairment with Igf2/H19 epigenetic alteration induced by p,p'-DDE exposure in early life

The hypothesis of fetal origins indicates that exposures in early development could induce epigenetic modifications in the male germ-line, affecting the susceptibility of adult-onset disease for generations. p,p'-DDE, the primary metabolite of persistent organochlorine pesticide DDT, is highly correlated with impaired glucose tolerance (IGT) and a strong contributing factor to type 2 diabetes. In our previous study, ancestral p,p'-DDE exposure could induce transgenerational impaired male fertility with sperm Igf2 hypomethylation. It is still unknown whether this germline epigenetic defect would affect the somatic tissue endocrine pancreas. Gestating F0 generation females were exposed to p,p'-DDE from gestation day 8 to 15. The F1 male offspring were mated with female to produce F2 progeny. F3 generation was obtained by intercrossing the control and treated male and female of F2 generation and divided as C♂-C♀, DDE♂-DDE♀, DDE♂-C♀ and C♂-DDE♀. Results indicated that F1 offspring in p,p'-DDE group exhibited impaired glucose tolerance (IGT), abnormal insulin secretion, β-cell dysfunction and altered Igf2 and H19 expression induced by Igf2/H19 hypomethylation, which could be transferred to the F3 offspring through the male germ line. IGT and abnormal insulin secretion were more obvious in males than those in females. Ancestral p,p'-DDE exposure could induce transgenerational pancreatic impairment with Igf2/H19 epigenetic defect.

Pancreatic impairment and Igf2 hypermethylation induced by developmental exposure to bisphenol A can be counteracted by maternal folate supplementation

Increasing evidence indicates that bisphenol A (BPA), a widely manufactured environmental pollutant, can induce changes in DNA methylation paatterns, which is a potential mechanism linking this environmental exposure to disease development. We investigated the influence of developmental exposure to BPA on pancreatic DNA methylation patterns and whether maternal folate supplementation can modify the epigenetic status and pancreatic impairment induced by BPA. Our results showed that maternal dietary folate supplementation in rats exposed to BPA counteracted the observed BPA-induced pancreatic impairments in the offspring, which included disrupted insulin secretion and glucose intolerance, and impaired morphology and ultrastructure of β cells. Moreover, these pancreatic dysfunctions were shown to be associated with low expression and DNA hypermethylation of insulin-like growth factor-2 (Igf2) in islets induced by exposure to BPA during the developmental period. Importantly, maternal dietary folate supplementation was demonstrated to negate this Igf2 DNA hypermethylation in the offspring, which was consistent with the upregulation of Igf2 expression. Overall, our results suggest that early developmental exposure to BPA alters the DNA methylation of Igf2, that these altered methylation patterns are associated with impaired β-cell function in the offspring and that these effects can be counteracted by maternal folate supplementation. Copyright © 2017 John Wiley & Sons, Ltd.

The association of soluble IGF2R and IGF2R gene polymorphism with type 2 diabetes

The aim of this study is to investigate the insulin-like growth factor type 2 (IGF2R) gene and circulating soluble IGF2R in relation to type 2 diabetes (T2DM). Six hundred fifty-four subjects without history of diabetes were screened for diabetes by oral glucose tolerance test. In addition, 145 subjects with known diabetes were recruited from a local diabetes clinic. Circulating IGF2R levels were measured by ELISA method; plasma glucose was measured by colorimetric method; insulin levels were determined by chemiluminescent method; IGF2R gene rs416572 was genotyped using real-time PCR. The distributions of IGF2R genotypes were 69.2% CC, 27.8% CT, and 3.0% TT. The C allele was more commonly found in diabetes subjects, with a significant difference (P < 0.01). In the presence of the T allele, circulating IGF2R levels were significantly lower (P < 0.05). There was no significant difference in other potential confounders including age, sex, and BMI. Only circulating IGF2R, age, and BMI were independently associated with the degree of insulin resistance, as assessed by the HOMA model. It was found that age, sex, and BMI were associated with beta cell function. In conclusion, IGF2R gene polymorphism and circulating IGF2R are associated with T2DM.

Prenatal xenobiotic exposure and intrauterine hypothalamus-pituitary-adrenal axis programming alteration

The hypothalamic-pituitary-adrenal (HPA) axis is one of the most important neuroendocrine axes and plays an important role in stress defense responses before and after birth. Prenatal exposure to xenobiotics, including environmental toxins (such as smoke, sulfur dioxide and carbon monoxide), drugs (such as synthetic glucocorticoids), and foods and beverage categories (such as ethanol and caffeine), affects fetal development indirectly by changing the maternal status or damaging the placenta. Certain xenobiotics (such as caffeine, ethanol and dexamethasone) may also affect the fetus directly by crossing the placenta into the fetus due to their lipophilic properties and lower molecular weights. All of these factors probably result in intrauterine programming alteration of the HPA axis, which showed a low basal activity but hypersensitivity to chronic stress. These alterations will, therefore, increase the susceptibility to adult neuropsychiatric (such as depression and schizophrenia) and metabolic diseases (such as hypertension, diabetes and non-alcoholic fatty liver disease). The "over-exposure of fetuses to maternal glucocorticoids" may be the main initiation factor by which the fetal HPA axis programming is altered. Meantime, xenobiotics can directly induce abnormal epigenetic modifications and expression on the important fetal genes (such as hippocampal glucocorticoid receptor, adrenal steroidogenic acute regulatory protein, et al) or damage by in situ oxidative metabolism of fetal adrenals, which may also be contributed to the programming alteration of fetal HPA axis.

Effects of genetics and in utero diet on murine pancreatic development

Intrauterine (IU) malnutrition could alter pancreatic development. In this study, we describe the effects of high-fat diet (HFD) during pregnancy on fetal growth and pancreatic morphology in an 'at risk' animal model of metabolic disease, the glucose transporter 4 (GLUT4) heterozygous mouse (G4+/-). WT female mice mated with G4+/- males were fed HFD or control diet (CD) for 2 weeks before mating and throughout pregnancy. At embryonic day 18.5, fetuses were killed and pancreata isolated for analysis of morphology and expression of genes involved in insulin (INS) cell development, proliferation, apoptosis, glucose transport and function. Compared with WT CD, WT HFD fetal pancreata had a 2.4-fold increase in the number of glucagon (GLU) cells (P=0.023). HFD also increased GLU cell size by 18% in WT pancreata compared with WT CD. Compared with WT CD, G4+/- CD had an increased number of INS cells and decreased INS and GLU cell size. Compared with G4+/- CD, G4+/- HFD fetuses had increased pancreatic gene expression of Igf2, a mitogen and inhibitor of apoptosis. The expression of genes involved in proliferation, apoptosis, glucose transport, and INS secretion was not altered in WT HFD compared with G4+/- HFD pancreata. In contrast to WT HFD pancreata, HFD exposure did not alter pancreatic islet morphology in fetuses with GLUT4 haploinsufficiency; this may be mediated in part by increased Igf2 expression. Thus, interactions between IU diet and fetal genetics may play a critical role in the developmental origins of health and disease.

Meta-analysis of genome-wide association studies in African Americans provides insights into the genetic architecture of type 2 diabetes

Type 2 diabetes (T2D) is more prevalent in African Americans than in Europeans. However, little is known about the genetic risk in African Americans despite the recent identification of more than 70 T2D loci primarily by genome-wide association studies (GWAS) in individuals of European ancestry. In order to investigate the genetic architecture of T2D in African Americans, the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium examined 17 GWAS on T2D comprising 8,284 cases and 15,543 controls in African Americans in stage 1 analysis. Single nucleotide polymorphisms (SNPs) association analysis was conducted in each study under the additive model after adjustment for age, sex, study site, and principal components. Meta-analysis of approximately 2.6 million genotyped and imputed SNPs in all studies was conducted using an inverse variance-weighted fixed effect model. Replications were performed to follow up 21 loci in up to 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry. We identified three known loci (TCF7L2, HMGA2 and KCNQ1) and two novel loci (HLA-B and INS-IGF2) at genome-wide significance (4.15 × 10(-94) Collapse

Key Words Collapse

MESH Headings

• Black or African American/genetics
• Diabetes Mellitus, Type 2/genetics
• Diabetes Mellitus, Type 2/pathology
• Genome-Wide Association Study
• HLA-B27 Antigen/genetics
• HMGA2 Protein/genetics
• Humans
• KCNQ1 Potassium Channel/genetics
• Mutant Chimeric Proteins/genetics
• Polymorphism, Single Nucleotide
• Transcription Factor 7-Like 2 Protein/genetics

Collapse

Grants

• R01 DK078616 NIDDK NIH HHS
• HHSN268201100012C NHLBI NIH HHS
• UL1RR025005 NCRR NIH HHS
• N02-HL-6-4278 NHLBI NIH HHS
• R01 HL071025 NHLBI NIH HHS
• R01-HL-088215 NHLBI NIH HHS
• UL1 RR033176 NCRR NIH HHS
• U01 HG007417 NHGRI NIH HHS
• U01-HG-004610 NHGRI NIH HHS
• U01DK057303 NIDDK NIH HHS
• R01 HL103612 NHLBI NIH HHS
• HHSN268201100009I NHLBI NIH HHS
• UL1 TR000445 NCATS NIH HHS
• U01 DK057304 NIDDK NIH HHS
• 32105-6 PHS HHS
• N01-HC-45205 NHLBI NIH HHS
• UL1RR033176 NCRR NIH HHS
• UL1TR000124 NCATS NIH HHS
• Z01-AG000513 NIA NIH HHS
• Z01 AG000513 Intramural NIH HHS
• M01-RR-01346 NCRR NIH HHS
• N01HC45204 NHLBI NIH HHS
• R01 HL061210 NHLBI NIH HHS
• N01-HC-05187 NHLBI NIH HHS
• R01-HL-071252 NHLBI NIH HHS
• HL59684 NHLBI NIH HHS
• R01 HL56266 NHLBI NIH HHS
• R01 HL120393 NHLBI NIH HHS
• R01 HL087698 NHLBI NIH HHS
• R01 HL046380 NHLBI NIH HHS
• S06GM008016-380111 NIGMS NIH HHS
• R01 HL071251 NHLBI NIH HHS
• U01DK57304 NIDDK NIH HHS
• R01 DK070941 NIDDK NIH HHS
• R01-HL-071258 NHLBI NIH HHS
• UL1 TR000150 NCATS NIH HHS
• UL1RR025741 NCRR NIH HHS
• G12 MD007597 NIMHD NIH HHS
• HHSC268200782096C PHS HHS
• R01HL59367 NHLBI NIH HHS
• HHSN268201100010C NHLBI NIH HHS
• U01 DK057298 NIDDK NIH HHS
• R01 HL071259 NHLBI NIH HHS
• UL1 RR025005 NCRR NIH HHS
• UL1-RR-025005 NCRR NIH HHS
• HL071025-01A1 NHLBI NIH HHS
• HL47902 NHLBI NIH HHS
• HHSN268201100008C NHLBI NIH HHS
• U01 HL080295 NHLBI NIH HHS
• N01 AG062101 NIA NIH HHS
• S06GM008016-320107 NIGMS NIH HHS
• HL060894 NHLBI NIH HHS
• N01-HC-48047 NHLBI NIH HHS
• R01-DK-8925601 NIDDK NIH HHS
• U01 DK057295 NIDDK NIH HHS
• HHSN268201100005G NHLBI NIH HHS
• R01 HL071252 NHLBI NIH HHS
• N01HC48049 NHLBI NIH HHS
• Z01 HG200362 Intramural NIH HHS
• HL085251 NHLBI NIH HHS
• Z01HG200362 NHGRI NIH HHS
• M01RR00080 NCRR NIH HHS
• NHGRI T32-HG002536 PHS HHS
• HHSN268201100008I NHLBI NIH HHS
• N01HC45205 NHLBI NIH HHS
• HL047890 NHLBI NIH HHS
• R01 HL087660 NHLBI NIH HHS
• R01CA92447 NCI NIH HHS
• U01 DK057300 NIDDK NIH HHS
• R01 HL059367 NHLBI NIH HHS
• HHSN268201100007C NHLBI NIH HHS
• HL62985 NHLBI NIH HHS
• HL105756 NHLBI NIH HHS
• P30 CA68485 NCI NIH HHS
• HHSN268200800007C NHLBI NIH HHS
• R01-HL-071250 NHLBI NIH HHS
• MC_UU_12015/1 Medical Research Council
• HS08365 AHRQ HHS
• NIH HL 46380 NHLBI NIH HHS
• N01HC95169 NHLBI NIH HHS
• N01AG62101 NIA NIH HHS
• HL061210 NHLBI NIH HHS
• R01 HL085251 NHLBI NIH HHS
• 32118 PHS HHS
• UL1-RR-024156 NCRR NIH HHS
• U01 HL120393 NHLBI NIH HHS
• R01 CA092447 NCI NIH HHS
• 42107-26 PHS HHS
• 32115 PHS HHS
• HHSN268201100011I NHLBI NIH HHS
• P30 DK079637 NIDDK NIH HHS
• HHSN268201100011C NHLBI NIH HHS
• R01 HL086694 NHLBI NIH HHS
• U01 HG004603 NHGRI NIH HHS
• UL1 RR024156 NCRR NIH HHS
• HL047887 NHLBI NIH HHS
• DP3 DK094311 NIDDK NIH HHS
• N01-HC-45204 NHLBI NIH HHS
• R01 HL071250 NHLBI NIH HHS
• T32 HG002536 NHGRI NIH HHS
• U01 DK057303 NIDDK NIH HHS
• N01-HC-95159 NHLBI NIH HHS
• HHSN268201300048C NHLBI NIH HHS
• 1R01AG032098-01A1 NIA NIH HHS
• UL1 RR025741 NCRR NIH HHS
• R01 HL087652 NHLBI NIH HHS
• N01-HC-95095 NHLBI NIH HHS
• M01-RR000052 NCRR NIH HHS
• HL087652 NHLBI NIH HHS
• U01HG004609 NHGRI NIH HHS
• UL1 TR000124 NCATS NIH HHS
• N01 AG062106 NIA NIH HHS
• HL58625-01A1 NHLBI NIH HHS
• HHSN268200625226C PHS HHS
• U01 HG004402 NHGRI NIH HHS
• R01-HL-071251 NHLBI NIH HHS
• N01HC55222 NHLBI NIH HHS
• R01 DK075681 NIDDK NIH HHS
• HL120393 NHLBI NIH HHS
• N01HC85086 NHLBI NIH HHS
• N02HL64278 NHLBI NIH HHS
• M01-RR-000080 NCRR NIH HHS
• R01 HL060944 NHLBI NIH HHS
• 32100-2 PHS HHS
• 24152 PHS HHS
• 32119 PHS HHS
• U01HG004402 NHGRI NIH HHS
• U01 DK057249 NIDDK NIH HHS
• R01 AG032098 NIA NIH HHS
• N01-HC-48050 NHLBI NIH HHS
• R01 HL105756 NHLBI NIH HHS
• U01 HG004609 NHGRI NIH HHS
• M01-RR-00425 NCRR NIH HHS
• U01 HG004599 NHGRI NIH HHS
• U01 HL047902 NHLBI NIH HHS
• HHSN268201100006C NHLBI NIH HHS
• HHSN268201300049C NHLBI NIH HHS
• N01-HC-45134 NHLBI NIH HHS
• R01 DK066358 NIDDK NIH HHS
• 42129-32 PHS HHS
• M01-RR-00827-29 NCRR NIH HHS
• P30 DK063491 NIDDK NIH HHS
• R01 HL071051 NHLBI NIH HHS
• K99 DK081350 NIDDK NIH HHS
• RC1 HL100185 NHLBI NIH HHS
• P20 MD006899 NIMHD NIH HHS
• R01-HL-071259 NHLBI NIH HHS
• R01 HL062985 NHLBI NIH HHS
• N01HC95095 NHLBI NIH HHS
• R01HL087641 NHLBI NIH HHS
• HHSN268201200036C NHLBI NIH HHS
• R01 DK084350 NIDDK NIH HHS
• N01-HC-95169 NHLBI NIH HHS
• HL087660 NHLBI NIH HHS
• HHSN268201100005I NHLBI NIH HHS
• RC1 HL100245 NHLBI NIH HHS
• N01 AG062103 NIA NIH HHS
• U01 NS041588 NINDS NIH HHS
• U01DK057298 NIDDK NIH HHS
• R01-HL-071205 NHLBI NIH HHS
• HL047889 NHLBI NIH HHS
• M01 RR000052 NCRR NIH HHS
• N01-HC-48049 NHLBI NIH HHS
• HL060944 NHLBI NIH HHS
• N01HC95159 NHLBI NIH HHS
• U01DK057300 NIDDK NIH HHS
• NR0224103 NINR NIH HHS
• N01 HC045134 NHLBI NIH HHS
• HHSN268201300047C NHLBI NIH HHS
• R01-HL-087700 NHLBI NIH HHS
• HHSN268201300050C NHLBI NIH HHS
• 32108-9 PHS HHS
• N01HC65226 NHLBI NIH HHS
• R01-DK-075681 NIDDK NIH HHS
• U01 HL072518 NHLBI NIH HHS
• U01 DK078616 NIDDK NIH HHS
• 098395 Wellcome Trust
• HL087698 NHLBI NIH HHS
• R01 HL080295 NHLBI NIH HHS
• U01 DK057329 NIDDK NIH HHS
• MC_PC_U127592696 Medical Research Council
• P30 CA068485 NCI NIH HHS
• HHSN268200782096C NHLBI NIH HHS
• R01 HL088215 NHLBI NIH HHS
• M01 RR010284 NCRR NIH HHS
• M01 RR000425 NCRR NIH HHS
• M01-RR-07122 NCRR NIH HHS
• M01 RR007122 NCRR NIH HHS
• U01DK57292 NIDDK NIH HHS
• R01 HL059684 NHLBI NIH HHS
• HL100245 NHLBI NIH HHS
• M01 RR07122 NCRR NIH HHS
• N01HC48050 NHLBI NIH HHS
• N01HC85082 NHLBI NIH HHS
• N01HC05187 NHLBI NIH HHS
• U01 HG006378 NHGRI NIH HHS
• N01HC48047 NHLBI NIH HHS
• N01HC85083 NHLBI NIH HHS
• HHSN268201100005C NHLBI NIH HHS
• R01 HL071205 NHLBI NIH HHS
• DK063491 NIDDK NIH HHS
• HHSN268201100009C NHLBI NIH HHS
• U01DK57329 NIDDK NIH HHS
• R01 DK053591 NIDDK NIH HHS
• M01 RR000997 NCRR NIH HHS
• UL1 TR001120 NCATS NIH HHS
• HHSN268201100007I NHLBI NIH HHS
• Wellcome Trust
• HHSN268201300046C NHLBI NIH HHS
• N01-HC-95100 NHLBI NIH HHS
• N01AG62103 NIA NIH HHS
• U01 HG004610 NHGRI NIH HHS
• U01DK070657 NIDDK NIH HHS
• R01-HL-071051 NHLBI NIH HHS
• HL080295 NHLBI NIH HHS
• R01 HS008365 AHRQ HHS
• N01AG62106 NIA NIH HHS
• U01-HG-004608 NHGRI NIH HHS
• N01-WH-22110 WHI NIH HHS
• 32122 PHS HHS
• U01DK057249 NIDDK NIH HHS
• U01 DK057292 NIDDK NIH HHS
• N01CO12400 NCI NIH HHS
• N01HC85079 NHLBI NIH HHS
• N02-HL-64278 NHLBI NIH HHS
• R01 HL060894 NHLBI NIH HHS
• R01 AG023629 NIA NIH HHS
• HL100185 NHLBI NIH HHS
• R01 HL087641 NHLBI NIH HHS
• 2M01RR010284 NCRR NIH HHS
• 44221 PHS HHS
• HL103612 NHLBI NIH HHS
• M01 RR000827 NCRR NIH HHS
• M01 RR000080 NCRR NIH HHS
• R01 HL087700 NHLBI NIH HHS
• N01HC85080 NHLBI NIH HHS
• 32111-13 PHS HHS
• AG023629 NIA NIH HHS
• R01 HL071258 NHLBI NIH HHS
• U01 HG004608 NHGRI NIH HHS
• R56 AG023629 NIA NIH HHS
• M01-RR-00997 NCRR NIH HHS
• N01WH22110 WHI NIH HHS
• N01-CO-12400 NCI NIH HHS
• U01 DK070657 NIDDK NIH HHS
• U01DK57295 NIDDK NIH HHS
• N01HC48048 NHLBI NIH HHS
• M01 RR001346 NCRR NIH HHS
• N01-HC-65226 NHLBI NIH HHS
• U01HL72518 NHLBI NIH HHS
• U01-HG-04599 NHGRI NIH HHS
• N01HC85081 NHLBI NIH HHS
• R01HL086694 NHLBI NIH HHS

Collapse

Affiliation(s)

Maggie C. Y. Ng Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Daniel Shriner Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
Brian H. Chen Program on Genomics and Nutrition, School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America Center for Metabolic Disease Prevention, School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America
Jiang Li Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Wei-Min Chen Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, United States of America
Xiuqing Guo Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
Jiankang Liu Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
Suzette J. Bielinski Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America
Lisa R. Yanek The GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
Michael A. Nalls Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
Mary E. Comeau Center for Public Health Genomics, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Laura J. Rasmussen-Torvik Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
Richard A. Jensen Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America Department of Medicine, University of Washington, Seattle, Washington, United States of America
Daniel S. Evans San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, California, United States of America
Yan V. Sun Department of Epidemiology and Biomedical Informatics, Emory University, Atlanta, Georgia, United States of America
Ping An Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri, United States of America
Sanjay R. Patel Division of Sleep Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
Yingchang Lu The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
Jirong Long Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
Loren L. Armstrong Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
Lynne Wagenknecht Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Lingyao Yang Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Beverly M. Snively Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Nicholette D. Palmer Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Poorva Mudgal Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Carl D. Langefeld Center for Public Health Genomics, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Keith L. Keene Department of Biology, Center for Health Disparities, East Carolina University, Greenville, North Carolina, United States of America
Barry I. Freedman Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Josyf C. Mychaleckyj Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, United States of America
Uma Nayak Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, United States of America
Leslie J. Raffel Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
Mark O. Goodarzi Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
Y-D Ida Chen Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
Herman A. Taylor Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America Jackson State University, Tougaloo College, Jackson, Mississippi, United States of America
Adolfo Correa Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
Mario Sims Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
David Couper Collaborative Studies Coordinating Center, Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
James S. Pankow Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota, United States of America
Eric Boerwinkle Human Genetics Center, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
Adebowale Adeyemo Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
Ayo Doumatey Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
Guanjie Chen Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
Rasika A. Mathias The GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America Division of Allergy and Clinical Immunology, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
Dhananjay Vaidya The GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
Andrew B. Singleton Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
Alan B. Zonderman Laboratory of Personality and Cognition, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, United States of America
Robert P. Igo Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
John R. Sedor Department of Medicine, Case Western Reserve University, MetroHealth System campus, Cleveland, Ohio, United States of America Department of Physiology and Biophysics, Case Western Reserve University, Cleveland, Ohio, United States of America
the FIND Consortium
Edmond K. Kabagambe Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
David S. Siscovick Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America Department of Medicine, University of Washington, Seattle, Washington, United States of America Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
Barbara McKnight Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
Kenneth Rice Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
Yongmei Liu Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Wen-Chi Hsueh Department of Medicine, University of California, San Francisco, California, United States of America
Wei Zhao Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
Lawrence F. Bielak Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
Aldi Kraja Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri, United States of America
Michael A. Province Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri, United States of America
Erwin P. Bottinger The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
Omri Gottesman The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
Qiuyin Cai Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
Wei Zheng Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
William J. Blot Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee; International Epidemiology Institute, Rockville, Maryland, United States of America
William L. Lowe Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
Jennifer A. Pacheco Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
Dana C. Crawford Center for Human Genetics Research and Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee, United States of America
the eMERGE Consortium
the DIAGRAM Consortium
Elin Grundberg Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
the MuTHER Consortium
Stephen S. Rich Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
M. Geoffrey Hayes Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
Xiao-Ou Shu Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
Ruth J. F. Loos The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
Ingrid B. Borecki Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri, United States of America
Patricia A. Peyser Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
Steven R. Cummings San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, California, United States of America
Bruce M. Psaty Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America Department of Medicine, University of Washington, Seattle, Washington, United States of America Department of Epidemiology, University of Washington, Seattle, Washington, United States of America Department of Health Services, University of Washington, Seattle, Washington, United States of America
Myriam Fornage Human Genetics Center, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
Sudha K. Iyengar Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
Michele K. Evans Health Disparities Unit, National Institute on Aging, National Institutes of Health, Baltimore Maryland, United States of America
Diane M. Becker The GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
W. H. Linda Kao Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
James G. Wilson Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
Jerome I. Rotter Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
Michèle M. Sale Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America Department of Medicine, University of Virginia, Charlottesville, Virginia, United States of America Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, United States of America
Simin Liu Program on Genomics and Nutrition, School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America Department of Epidemiology, University of California Los Angeles, Los Angeles, California, United States of America Departments of Epidemiology and Medicine, Brown University, Providence, Rhode Island, United States of America
Charles N. Rotimi Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
Donald W. Bowden Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
for the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium

Collapse

Maternal diabetes, programming of beta-cell disorders and intergenerational risk of type 2 diabetes

A substantial body of evidence suggests that an abnormal intra-uterine milieu elicited by maternal metabolic disturbances as diverse as malnutrition, placental insufficiency, diabetes and obesity may be able to programme susceptibility of the foetus to later develop chronic degenerative diseases such as obesity, hypertension, cardiovascular diseases and type 2 diabetes (T2D). As insulin-producing cells have been placed centre stage in the development of T2D, this review examines developmental programming of the beta-cell mass (BCM) in various rodent models of maternal protein restriction, calorie restriction, overnutrition and diabetes. The main message is that whatever the initial maternal insult (F0 generation) and whether alone or in combination, it gives rise to the same programmed BCM outcome in the daughter generation (F1). The altered BCM phenotype in F1 females prohibits normal BCM adaptation during pregnancy and, thus, diabetes (gestational diabetes) ensues. This gestational diabetes is then passed from one generation (F1) to the next (F2, F3 and so on). This review highlights a number of studies that have identified epigenetic mechanisms that may contribute to altered BCM development and beta-cell failure, as observed in diabetes. In addition to their role in instilling the programmed defect, these non-genomic mechanisms may also be involved in its intergenerational transmission.

Defective prolactin signaling impairs pancreatic β-cell development during the perinatal period

Prolactin (PRL) and placental lactogens stimulate β-cell replication and insulin production in pancreatic islets and insulinoma cells through binding to the PRL receptor (PRLR). However, the contribution of PRLR signaling to β-cell ontogeny and function in perinatal life and the effects of the lactogens on adaptive islet growth are poorly understood. We provide evidence that expansion of β-cell mass during both embryogenesis and the postnatal period is impaired in the PRLR(-/-) mouse model. PRLR(-/-) newborns display a 30% reduction of β-cell mass, consistent with reduced proliferation index at E18.5. PRL stimulates leucine incorporation and S6 kinase phosphorylation in INS-1 cells, supporting a role for β-cell mTOR signaling in PRL action. Interestingly, a defect in the development of acini is also observed in absence of PRLR signaling, with a sharp decline in cellular size in both endocrine and exocrine compartments. Of note, a decrease in levels of IGF-II, a PRL target, in the Goto-Kakizaki (GK) rat, a spontaneous model of type 2 diabetes, is associated with a lack of PRL-mediated β-cell proliferation in embryonic pancreatic buds. Reduced pancreatic IGF-II expression in both rat and mouse models suggests that this factor may constitute a molecular link between PRL signaling and cell ontogenesis. Together, these results provide evidence that PRL signaling is essential for pancreas ontogenesis during the critical perinatal window responsible for establishing functional β-cell reserve.

Transcription factor ZBED6 affects gene expression, proliferation, and cell death in pancreatic beta cells

We have investigated whether the recently discovered transcription factor, zinc finger BED domain-containing protein 6 (ZBED6), is expressed in insulin-producing cells and, if so, to what extent it affects beta cell function. ZBED6 was translated from a ZC3H11A transcript in which the ZBED6-containing intron was retained. ZBED6 was present in mouse βTC-6 cells and human islets as a double nuclear band at 115/120 kDa and as a single cytoplasmic band at 95-100 kDa, which lacked N-terminal nuclear localization signals. We propose that ZBED6 supports proliferation and survival of beta cells, possibly at the expense of specialized beta cell function-i.e., insulin production-because (i) the nuclear ZBED6 were the predominant forms in rapidly proliferating βTC-6 cells, but not in human islet cells; (ii) down-regulation of ZBED6 in βTC-6 cells resulted in altered morphology, decreased proliferation, a partial S/G2 cell-cycle arrest, increased expression of beta cell-specific genes, and higher rates of apoptosis; (iii) silencing of ZBED6 in the human PANC-1 duct cell line reduced proliferation rates; and (iv) ZBED6 binding was preferentially to genes that control transcription, macromolecule biosynthesis, and apoptosis. Furthermore, it is possible that beta cells, by switching from full length to a truncated form of ZBED6, can decide the subcellular localization of ZBED6, thereby achieving differential ZBED6-mediated transcriptional regulation.

A euglycaemic/non-diabetic perinatal environment does not alleviate early beta cell maldevelopment and type 2 diabetes risk in the GK/Par rat model

AIMS/HYPOTHESIS

We used the GK/Par rat, a spontaneous model of type 2 diabetes with early defective beta cell neogenesis, to determine whether the development of GK/Par offspring in a non-diabetic intrauterine/postnatal environment would prevent the alteration of fetal beta cell mass (BCM) and ultimately decrease the risk of diabetes later in adult life.

METHODS

We used an embryo-transfer approach, with fertilised GK/Par ovocytes (oGK) being transferred into pregnant Wistar (W) or GK/Par females (pW and pGK). Offspring were phenotyped at fetal age E18.5 and at 10 weeks of age, for BCM, expression of genes of pancreatic progenitor cell regulators (Igf2, Igf1r, Sox9, Pdx1 and Ngn3), glucose tolerance and insulin secretion.

RESULTS

(1) Alterations in neogenesis markers/regulators and BCM were as severe in the oGK/pW E18.5 fetuses as in the oGK/pGK group. (2) Adult offspring from oGK transfers into GK (oGK/pGK/sGK) had the expected diabetic phenotype compared with unmanipulated GK rats. (3) Adult offspring from oGK reared in pW mothers and milked by GK foster mothers had reduced BCM, basal hyperglycaemia, glucose intolerance and low insulin, to an extent similar to that of oGK/pGK/sGK offspring. (4) In adult offspring from oGK transferred into pW mothers and milked by their W mothers (oGK/pW/sW), the phenotype was similar to that in oGK/pGK/sGK or oGK/pW/sGK offspring.

CONCLUSIONS/INTERPRETATION

These data support the conclusion that early BCM alteration and subsequent diabetes risk in the GK/Par model are not removed despite normalisation of the prenatal and postnatal environments, either isolated or combined.

The rs11705701 G>A polymorphism of IGF2BP2 is associated with IGF2BP2 mRNA and protein levels in the visceral adipose tissue - a link to type 2 diabetes susceptibility

BACKGROUND

Insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) regulates translation of IGF2, a growth factor that plays a key role in controlling fetal growth and organogenesis including adipogenesis and pancreatic development. In Caucasians, the rs4402960 G>T polymorphism of IGF2BP2 has been shown to predispose to type 2 diabetes (T2D) in multiple populations. In this study, we tested whether rs4402960 G>T and rs11705701 G>A contribute to the development of T2D in a Russian population.

METHODS

Both markers were genotyped in Russian diabetic (n = 1,470) and non-diabetic patients (n = 1,447) using a Taqman allele discrimination assay. The odds ratio (OR) for the risk of developing T2D was calculated using logistic regression assuming an additive genetic model adjusted for age, sex, HbA1c, hypertension, obesity, and body mass index (BMI). Multivariate linear regression analyses were used to test genotype-phenotype correlations, and adjusted for age, sex, hypertension, obesity, and BMI. Expression of IGF2BP2 in the visceral adipose tissue was quantified using real-time PCR. The content of IGF2BP2 protein and both its isoforms (p58 and p66) in the adipose tissue was measured using Western blot analysis.

RESULTS

There was no significant association between rs4402960 and T2D. Whereas, allele A of rs11705701 was associated with higher T2D risk (OR = 1.19, p < 0.001). Diabetic and non-diabetic carriers of genotype TT (rs4402960) had significantly increased HOMA-IR (p = 0.033 and p = 0.031, respectively). Non-diabetic patients homozygous for AA (rs11705701) had higher HOMA-IR (p = 0.04), lower HOMA-β (p = 0.012), and reduced 2-h insulin levels (p = 0.016). Non-obese individuals (diabetic and non-diabetic) homozygous for either AA (rs11705701) or TT (rs4402960) had higher levels of IGF2BP2 mRNA in the adipose tissue than other IGF2BP2 variants. Also, allele A of rs11705701 was associated with reduced amounts of the short isoform (p58) and increased levels of the long isoform (p66) of the IGF2BP2 protein in adipose tissue of non-obese diabetic and non-diabetic subjects.

CONCLUSIONS

IGF2BP2 genetic variants contribute to insulin resistance in Russian T2D patients. The short protein isoform p58 of IGF2BP2 is likely to play an anti-diabetogenic role in non-obese individuals.

Re-expression of IGF-II is important for beta cell regeneration in adult mice

Background

The key factors which support re-expansion of beta cell numbers after injury are largely unknown. Insulin-like growth factor II (IGF-II) plays a critical role in supporting cell division and differentiation during ontogeny but its role in the adult is not known. In this study we investigated the effect of IGF-II on beta cell regeneration.

Methodology/Principal Findings

We employed an in vivo model of ‘switchable’ c-Myc-induced beta cell ablation, pIns-c-MycER^TAM, in which 90% of beta cells are lost following 11 days of c-Myc (Myc) activation in vivo. Importantly, such ablation is normally followed by beta cell regeneration once Myc is deactivated, enabling functional studies of beta cell regeneration in vivo. IGF-II was shown to be re-expressed in the adult pancreas of pIns-c-MycER^TAM/IGF-II^+/+ (MIG) mice, following beta cell injury. As expected in the presence of IGF-II beta cell mass and numbers recover rapidly after ablation. In contrast, in pIns-c-MycER^TAM/IGF-II^+/− (MIGKO) mice, which express no IGF-II, recovery of beta cell mass and numbers were delayed and impaired. Despite failure of beta cell number increase, MIGKO mice recovered from hyperglycaemia, although this was delayed.

Conclusions/Significance

Our results demonstrate that beta cell regeneration in adult mice depends on re-expression of IGF-II, and supports the utility of using such ablation-recovery models for identifying other potential factors critical for underpinning successful beta cell regeneration in vivo. The potential therapeutic benefits of manipulating the IGF-II signaling systems merit further exploration.

Fine-mapping diabetes-related traits, including insulin resistance, in heterogeneous stock rats

Type 2 diabetes (T2D) is a disease of relative insulin deficiency resulting from both insulin resistance and beta cell failure. We have previously used heterogeneous stock (HS) rats to fine-map a locus for glucose tolerance. We show here that glucose intolerance in the founder strains of the HS colony is mediated by different mechanisms: insulin resistance in WKY and an insulin secretion defect in ACI, and we demonstrate a high degree of variability for measures of insulin resistance and insulin secretion in HS rats. As such, our goal was to use HS rats to fine-map several diabetes-related traits within a region on rat chromosome 1. We measured blood glucose and plasma insulin levels after a glucose tolerance test in 782 male HS rats. Using 97 SSLP markers, we genotyped a 68 Mb region on rat chromosome 1 previously implicated in glucose and insulin regulation. We used linkage disequilibrium mapping by mixed model regression with inferred descent to identify a region from 198.85 to 205.9 that contains one or more quantitative trait loci (QTL) for fasting insulin and a measure of insulin resistance, the quantitative insulin sensitivity check index. This region also encompasses loci identified for fasting glucose and Insulin_AUC (area under the curve). A separate <3 Mb QTL was identified for body weight. Using a novel penalized regression method we then estimated effects of alternative haplotype pairings under each locus. These studies highlight the utility of HS rats for fine-mapping genetic loci involved in the underlying causes of T2D.

Transgenerational glucose intolerance with Igf2/H19 epigenetic alterations in mouse islet induced by intrauterine hyperglycemia

Gestational diabetes mellitus (GDM) has been shown to be associated with high risk of diabetes in offspring. However, the mechanisms involved and the possibilities of transgenerational transmission are still unclear. We intercrossed male and female adult control and first-generation offspring of GDM (F1-GDM) mice to obtain the second-generation (F2) offspring in four groups: C♂-C♀, C♂-GDM♀, GDM♂-C♀, and GDM♂-GDM♀. We found that birth weight significantly increased in F2 offspring through the paternal line with impaired glucose tolerance (IGT). Regardless of birth from F1-GDM with or without IGT, high risk of IGT appeared as early as 3 weeks in F2 offspring and progressed through both parental lineages, especial the paternal line. IGT in male offspring was more obvious than that in females, with parental characteristics and sex-specific transmission. In both F1 and F2 offspring of GDM, the expression of imprinted genes Igf2 and H19 was downregulated in pancreatic islets, caused by abnormal methylation status of the differentially methylated region, which may be one of the mechanisms for impaired islet ultrastructure and function. Furthermore, altered Igf2 and H19 gene expression was found in sperm of adult F1-GDM, regardless of the presence of IGT, indicating that changes of epigenetics in germ cells contributed to transgenerational transmission.

The GK rat: a prototype for the study of non-overweight type 2 diabetes

Type 2 diabetes mellitus (T2D) arises when the endocrine pancreas fails to secrete sufficient insulin to cope with the metabolic demand because of β-cell secretory dysfunction and/or decreased β-cell mass. Defining the nature of the pancreatic islet defects present in T2D has been difficult, in part because human islets are inaccessible for direct study. This review is aimed to illustrate to what extent the Goto Kakizaki rat, one of the best characterized animal models of spontaneous T2D, has proved to be a valuable tool offering sufficient commonalities to study this aspect. A comprehensive compendium of the multiple functional GK abnormalities so far identified is proposed in this perspective, together with their time-course and interactions. A special focus is given toward the pathogenesis of defective β-cell number and function in the GK model. It is proposed that the development of T2D in the GK model results from the complex interaction of multiple events: (1) several susceptibility loci containing genes responsible for some diabetic traits; (2) gestational metabolic impairment inducing an epigenetic programming of the offspring pancreas and the major insulin target tissues; and (3) environmentally induced loss of β-cell differentiation due to chronic exposure to hyperglycemia/hyperlipidemia, inflammation, and oxidative stress.

Early-life origins of type 2 diabetes: fetal programming of the beta-cell mass

A substantial body of evidence suggests that an abnormal intrauterine milieu elicited by maternal metabolic disturbances as diverse as undernutrition, placental insufficiency, diabetes or obesity, may program susceptibility in the fetus to later develop chronic degenerative diseases, such as obesity, hypertension, cardiovascular diseases and diabetes. This paper examines the developmental programming of glucose intolerance/diabetes by disturbed intrauterine metabolic condition experimentally obtained in various rodent models of maternal protein restriction, caloric restriction, overnutrition or diabetes, with a focus on the alteration of the developing beta-cell mass. In most of the cases, whatever the type of initial maternal metabolic stress, the beta-cell adaptive growth which normally occurs during gestation, does not take place in the pregnant offspring and this results in the development of gestational diabetes. Therefore gestational diabetes turns to be the ultimate insult targeting the offspring beta-cell mass and propagates diabetes risk to the next generation again. The aetiology and the transmission of spontaneous diabetes as encountered in the GK/Par rat model of type 2 diabetes, are discussed in such a perspective. This review also discusses the non-genomic mechanisms involved in the installation of the programmed effect as well as in its intergenerational transmission.

Hypercholesterolaemia, signs of islet microangiopathy and altered angiogenesis precede onset of type 2 diabetes in the Goto-Kakizaki (GK) rat

AIMS/HYPOTHESIS

The adult non-obese Goto-Kakizaki (GK) rat model of type 2 diabetes, particularly females, carries in addition to hyperglycaemia a genetic predisposition towards dyslipidaemia, including hypercholesterolaemia. As cholesterol-induced atherosclerosis may be programmed in utero, we looked for signs of perinatal lipid alterations and islet microangiopathy. We hypothesise that such alterations contribute towards defective pancreas/islet vascularisation that might, in turn, lead to decreased beta cell mass. Accordingly, we also evaluated islet inflammation and endothelial activation in both prediabetic and diabetic animals.

METHODS

Blood, liver and pancreas were collected from embryonic day (E)21 fetuses, 7-day-old prediabetic neonates and 2.5-month-old diabetic GK rats and Wistar controls for analysis/quantification of: (1) systemic variables, particularly lipids; (2) cholesterol-linked hepatic enzyme mRNA expression and/or activity; (3) pancreas (fetuses) or collagenase-isolated islet (neonates/adults) gene expression using Oligo GEArray microarrays targeted at rat endothelium, cardiovascular disease biomarkers and angiogenesis, and/or RT-PCR; and (4) pancreas endothelial immunochemistry: nestin (fetuses) or von Willebrand factor (neonates).

RESULTS

Systemic and hepatic cholesterol anomalies already exist in GK fetuses and neonates. Hyperglycaemic GK fetuses exhibit a similar percentage decrease in total pancreas and islet vascularisation and beta cell mass. Normoglycaemic GK neonates show systemic inflammation, signs of islet pre-microangiopathy, disturbed angiogenesis, collapsed vascularisation and altered pancreas development. Concomitantly, GK neonates exhibit elevated defence mechanisms.

CONCLUSIONS/INTERPRETATION

These data suggest an autoinflammatory disease, triggered by in utero programming of cholesterol-induced islet microangiopathy interacting with chronic hyperglycaemia in GK rats. During the perinatal period, GK rats show also a marked deficient islet vascularisation in conjunction with decreased beta cell mass.

Insulin-like growth factor 2 enhances insulinogenic differentiation of human eyelid adipose stem cells via the insulin receptor

OBJECTIVES

Previously, we have isolated stem cells (HEAC) from human eyelid adipose tissue and functionally differentiated them into insulin-secreting cells. In the present study, we examined whether insulin family members might influence insulinogenic differentiation of HEAC.

MATERIALS AND METHODS

Following culture in differentiation media containing insulin family member or not, cells were examined for gene expression, protein expression and, particularly, insulin and C-peptide secretion, in response to high glucose challenge. Using antibodies against the specific receptor, target receptor mediating effect of the insulin family member was investigated.

RESULTS

Insulin treatment during culture had little effect on either insulin or C-peptide secretion from HEAC, against high glucose challenge after culture. However, insulin-like growth factor (IGF) 1 treatment decreased both secretions, and interestingly, IGF2 greatly increased the secretions. HEAC treated with IGF2 had strong expression of Pdx1, Isl1, Pax6 and PC1/3 genes, and distinct staining after insulin and C-peptide antibodies, and dithizone. IGF2-enhanced insulinogenic differentiation was totally blocked by antibody against insulin receptor (IR), but not by anti-IGF1 receptor (IGF1R). Differentiated HEAC expressed both IR and IGF1R genes, whereas they expressed neither IGF2 nor IGF2R genes.

CONCLUSIONS

From these results, it is suggested that IGF1 might inhibit insulinogenic differentiation of HEAC, whereas IGF2 enhances differentiation, and that enhancement of IGF2 appeared to be mediated via IR.

Rapamycin suppresses the expansion and differentiation of porcine neonatal pancreas cell clusters

BACKGROUND

The role of rapamycin in pancreas stem cells remains to be clearly elucidated. Herein, we evaluated the effects of rapamycin on porcine neonatal pancreas cell clusters (NPCCs), which primarily comprised pancreatic precursors, and attempted to find an intracellular mechanism about the harmful effects of rapamycin.

METHODS

Porcine NPCCs were treated with rapamycin in a monolayer, and the apoptosis and proliferation were determined via caspase-3 assay and H-thymidine uptake analysis. The expression of transcription factors was assessed via reverse-transcriptase polymerase chain reaction and Western blotting. For the in vivo study, the porcine NPCCs were transplanted into the kidney subcapsules of normal nude mice and treated with rapamycin.

RESULTS

Rapamycin treatment significantly reduced the number of β cells, glucose-stimulated insulin secretion, and the insulin contents in the monolayer-cultured porcine NPCCs. Furthermore, rapamycin treatment increased the apoptosis and inhibited the proliferation of β cells in the culture dishes. The expressions of the insulin, pancreatic and duodenal homeobox-1, and NeuroD/Beta2 genes were down-regulated via rapamycin treatment. The expression of insulin-like growth factor-II was significantly down-regulated, but the expression of Foxo1 was simultaneously inversely increased, and the translocation of Foxo1 from the cytoplasm to the nucleus was induced by rapamycin treatment. Moreover, rapamycin treatment induced a marked reduction in the relative volume and absolute mass of β cells in the porcine NPCCs grafts at 8 weeks after transplantation in the normal nude mice.

CONCLUSIONS

Here, we demonstrate that rapamycin treatment suppresses the expansion and differentiation of porcine NPCCs, and the alteration of Foxo1 and insulin-like growth factor-II gene expression might be the crucial factors.

Animal models in diabetes and pregnancy

The worldwide increase in the incidence of diabetes, the increase in type 2 diabetes in women at reproductive ages, and the cross-generation of the intrauterine programming of type 2 diabetes are the bases for the growing interest in the use of experimental diabetic models in order to gain insight into the mechanisms of induction of developmental alterations in maternal diabetes. In this scenario, experimental models that present the most common features of diabetes in pregnancy are highly required. Several important aspects of human diabetic pregnancies such as the increased rates of spontaneous abortions, malformations, fetoplacental impairments, and offspring diseases in later life can be approached by using the appropriate animal models. The purpose of this review is to give a practical and critical guide into the most frequently used experimental models in diabetes and pregnancy, discuss their advantages and limitations, and describe the aspects of diabetes and pregnancy for which these models are thought to be adequate. This review provides a comprehensive view and an extensive analysis of the different models and phenotypes addressed in diabetic animals throughout pregnancy. The review includes an analysis of the surgical, chemical-induced, and genetic experimental models of diabetes and an evaluation of their use to analyze early pregnancy defects, induction of congenital malformations, placental and fetal alterations, and the intrauterine programming of metabolic diseases in the offspring's later life.

Glial cell line-derived neurotrophic factor enhances neurogenin3 gene expression and beta-cell proliferation in the developing mouse pancreas

Glial cell line-derived neurotrophic factor (GDNF) is a factor produced by glial cells that is required for the development of the enteric nervous system. In transgenic mice that overexpress GDNF in the pancreas, GDNF has been shown to enhance beta-cell mass and improve glucose control, but the transcriptional and cellular processes involved are not known. In this study we examined the influence of GDNF on the expression of neurogenin3 (Ngn3) and other transcription factors implicated in early beta-cell development, as well as on beta-cell proliferation during embryonic and early postnatal mouse pancreas development. Embryonic day 15.5 (E15.5) mouse pancreatic tissue when exposed to GDNF for 24 h showed higher Ngn3, pancreatic and duodenal homeobox gene 1 (Pdx1), neuroD1/beta(2), paired homeobox gene 4 (Pax4), and insulin mRNA expression than tissue exposed to vehicle only. Transgenic expression of GDNF in mouse pancreata was associated with increased numbers of Ngn3-expressing pancreatic cells and higher beta-cell mass at embryonic day 18 (E18), as well as higher beta-cell proliferation and Pdx1 expression in beta-cells at E18 and postnatal day 1. In the HIT-T15 beta-cell line, GDNF enhanced the expression of Pax6. This response was, however, blocked in the presence of Pdx1 small interfering RNA (siRNA). Chromatin immunoprecipitation studies using the HIT-T15 beta-cell line demonstrated that GDNF can influence Pdx1 gene expression by enhancing the binding of Sox9 and neuroD1/beta(2) to the Pdx1 promoter. Our data provide evidence of a mechanism by which GDNF influences beta-cell development. GDNF could be a potential therapeutic target for the treatment and prevention of diabetes.

Insulin-like growth factor-I regulation of immune function: a potential therapeutic target in autoimmune diseases?

This topically limited review explores the relationship between the immune system and insulin-like growth factors (IGF-I and IGF-II) and the proteins through which they act, including IGF-I receptor (IGF-IR) and the IGF-I binding proteins. The IGF/IGF-IR pathway plays important and diverse roles in tissue development and function. It regulates cell cycle progression, apoptosis, and the translation of proteins. Many of the consequences ascribed to IGF-IR activation result from its association with several accessory proteins that are either identical or closely related to those involved in insulin receptor signaling. Relatively recent awareness that IGF-I and IGF-IR regulate immune function has cast this pathway in an unexpected light; it may represent an important switch governing the quality and amplitude of immune responses. IGF-I/IGF-IR signaling may also participate in the pathogenesis of autoimmune diseases, although its relationship with these processes seems complex and relatively unexplored. On the one hand, IGF-I seems to protect experimental animals from developing insulin-deficient diabetes mellitus. In contrast, activating antibodies directed at IGF-IR have been detected in patients with Graves' disease, where the receptor is overexpressed by multiple cell types. The frequency of IGF-IR+ B and T cells is substantially increased in patients with that disease. Potential involvement of IGF-I and IGF-IR in the pathogenesis of autoimmune diseases suggests that this pathway might constitute an attractive therapeutic target. IGF-IR has been targeted in efforts directed toward drug development for cancer, employing both small-molecule and monoclonal antibody approaches. These have been generally well-tolerated. Recognizing the broader role of IGF-IR in regulating both normal and pathological immune responses may offer important opportunities for therapeutic intervention in several allied diseases that have proven particularly difficult to treat.

Rosiglitazone improves pancreatic mitochondrial function in an animal model of dysglycemia: role of the insulin-like growth factor axis

Thiazolidinediones (TZDs) improve insulin sensitivity and maintain beta cell mass. This study examined whether this effect is attributable to improved mitochondrial function in the pancreas and the potential involvement of the pancreatic insulin-like growth factor (IGF) axis in mediating this effect. Female Wistar rats were given either saline (vehicle) or nicotine (1 mg kg⁻¹ day⁻¹) during pregnancy and lactation. Following weaning, nicotine-exposed offspring were randomized to receive either vehicle or rosiglitazone (3 mg kg⁻¹ day⁻¹) until 26 weeks of age when serum and pancreas tissue were collected. The effect of rosiglitazone on nicotine-induced mitochondrial dysfunction was also examined in vitro. Fetal and neonatal nicotine exposure resulted in structural and functional mitochondrial deficits relative to saline controls. The nicotine-induced mitochondrial defects were attenuated by postnatal rosiglitazone administration. A similar effect was observed in vitro; nicotine (25 ng/ml) inhibited beta cell mitochondrial function and co-treatment with rosiglitazone (1 μM) restored enzyme activity to control levels. Fetal and neonatal nicotine exposure also altered key components of the adult pancreatic IGF axis, an effect that was not prevented by rosiglitazone treatment. Rosiglitazone treatment maintains mitochondrial structure and function in the pancreas of rats that are prone to diabetes, as well as mitochondrial function in beta cell culture. We propose that this may be an important part of the mechanism by which rosiglitazone improves beta cell mass and prevents diabetes in individuals with impaired glucose tolerance and/or impaired fasting glucose. The underlying mechanism through which rosiglitazone targets the mitochondria remains to be determined, but does not appear to involve the IGF axis.

Islet structure and function in the GK rat

Type 2 diabetes mellitus (T2D) arises when the endocrine pancreas fails to secrete sufficient insulin to cope with the metabolic demand because of beta-cell secretory dysfunction and/or decreased beta-cell mass. Defining the nature of the pancreatic islet defects present in T2D has been difficult, in part because human islets are inaccessible for direct study. This review is aimed to illustrate to what extent the Goto-Kakizaki rat, one of the best characterized animal models of spontaneous T2D, has proved to be a valuable tool offering sufficient commonalities to study this aspect. A comprehensive compendium of the multiple functional GK islet abnormalities so far identified is proposed in this perspective. The pathogenesis of defective beta-cell number and function in the GK model is also discussed. It is proposed that the development of T2D in the GK model results from the complex interaction of multiple events: (i) several susceptibility loci containing genes responsible for some diabetic traits (distinct loci encoding impairment of beta-cell metabolism and insulin exocytosis, but no quantitative trait locus for decreased beta-cell mass); (ii) gestational metabolic impairment inducing an epigenetic programming of the offspring pancreas (decreased beta-cell neogenesis and proliferation) transmitted over generations; and (iii) loss of beta-cell differentiation related to chronic exposure to hyperglycaemia/hyperlipidaemia, islet inflammation, islet oxidative stress, islet fibrosis and perturbed islet vasculature.

Undernutrition of the GK rat during gestation improves pancreatic IGF-2 and beta-cell mass in the fetuses

The Goto-Kakizaki (GK) rat is a type 2 diabetes model with a defective beta-cell mass detectable in late fetal development. Diminished IGF-2 production seems to be involved in this effect. Herein, we analyzed the effect of maternal food-restriction on the beta-cell mass of GK fetuses and the involvement of the IGF system, highly responsive to nutritional status in this process. To this end, in undernourished GK fetuses (U-GK), we measured serum GH/IGF levels, beta-cell mass, replication and differentiation, and IGF-1/-2 protein content in liver and pancreas tissue. Pregnant GK females were food restricted (65% restriction) during the last week of gestation. Our results show that maternal malnutrition ameliorates beta-cell mass in U-GK fetuses and a specific pancreatic IGF-2 increase may be instrumental in this effect. Further studies are needed to determine whether maternal undernutrition is sufficient to delay or decrease the risk of the GK rat for developing diabetes.

Islet endothelial activation and oxidative stress gene expression is reduced by IL-1Ra treatment in the type 2 diabetic GK rat

Background

Inflammation followed by fibrosis is a component of islet dysfunction in both rodent and human type 2 diabetes. Because islet inflammation may originate from endothelial cells, we assessed the expression of selected genes involved in endothelial cell activation in islets from a spontaneous model of type 2 diabetes, the Goto-Kakizaki (GK) rat. We also examined islet endotheliuml/oxidative stress (OS)/inflammation-related gene expression, islet vascularization and fibrosis after treatment with the interleukin-1 (IL-1) receptor antagonist (IL-1Ra).

Methodology/Principal Findings

Gene expression was analyzed by quantitative RT-PCR on islets isolated from 10-week-old diabetic GK and control Wistar rats. Furthermore, GK rats were treated s.c twice daily with IL-1Ra (Kineret, Amgen, 100 mg/kg/day) or saline, from 4 weeks of age onwards (onset of diabetes). Four weeks later, islet gene analysis and pancreas immunochemistry were performed. Thirty-two genes were selected encoding molecules involved in endothelial cell activation, particularly fibrinolysis, vascular tone, OS, angiogenesis and also inflammation. All genes except those encoding angiotensinogen and epoxide hydrolase (that were decreased), and 12-lipoxygenase and vascular endothelial growth factor (that showed no change), were significantly up-regulated in GK islets. After IL-1Ra treatment of GK rats in vivo, most selected genes implied in endothelium/OS/immune cells/fibrosis were significantly down-regulated. IL-1Ra also improved islet vascularization, reduced fibrosis and ameliorated glycemia.

Conclusions/Significance

GK rat islets have increased mRNA expression of markers of early islet endothelial cell activation, possibly triggered by several metabolic factors, and also some defense mechanisms. The beneficial effect of IL-1Ra on most islet endothelial/OS/immune cells/fibrosis parameters analyzed highlights a major endothelial-related role for IL-1 in GK islet alterations. Thus, metabolically-altered islet endothelium might affect the β-cell microenvironment and contribute to progressive type 2 diabetic β-cell dysfunction in GK rats. Counteracting islet endothelial cell inflammation might be one way to ameliorate/prevent β-cell dysfunction in type 2 diabetes.

Glucagon-like peptide-1 protects beta-cells against apoptosis by increasing the activity of an IGF-2/IGF-1 receptor autocrine loop

OBJECTIVE

The gluco-incretin hormones glucagon-like peptide (GLP)-1 and gastric inhibitory peptide (GIP) protect beta-cells against cytokine-induced apoptosis. Their action is initiated by binding to specific receptors that activate the cAMP signaling pathway, but the downstream events are not fully elucidated. Here we searched for mechanisms that may underlie this protective effect.

RESEARCH DESIGN AND METHODS

We performed comparative transcriptomic analysis of islets from control and GipR(-/-);Glp-1-R(-/-) mice, which have increased sensitivity to cytokine-induced apoptosis. We found that IGF-1 receptor expression was markedly reduced in the mutant islets. Because the IGF-1 receptor signaling pathway is known for its antiapoptotic effect, we explored the relationship between gluco-incretin action, IGF-1 receptor expression and signaling, and apoptosis.

RESULTS

We found that GLP-1 robustly stimulated IGF-1 receptor expression and Akt phosphorylation and that increased Akt phosphorylation was dependent on IGF-1 but not insulin receptor expression. We demonstrated that GLP-1-induced Akt phosphorylation required active secretion, indicating the presence of an autocrine activation mechanism; we showed that activation of IGF-1 receptor signaling was dependent on the secretion of IGF-2. We demonstrated, both in MIN6 cell line and primary beta-cells, that reducing IGF-1 receptor or IGF-2 expression or neutralizing secreted IGF-2 suppressed GLP-1-induced protection against apoptosis.

CONCLUSIONS

An IGF-2/IGF-1 receptor autocrine loop operates in beta-cells. GLP-1 increases its activity by augmenting IGF-1 receptor expression and by stimulating secretion; this mechanism is required for GLP-1-induced protection against apoptosis. These findings may lead to novel ways of preventing beta-cell loss in the pathogenesis of diabetes.

Alzheimer's disease is type 3 diabetes-evidence reviewed

Alzheimer's disease (AD) has characteristic histopathological, molecular, and biochemical abnormalities, including cell loss; abundant neurofibrillary tangles; dystrophic neurites; amyloid precursor protein, amyloid-beta (APP-Abeta) deposits; increased activation of prodeath genes and signaling pathways; impaired energy metabolism; mitochondrial dysfunction; chronic oxidative stress; and DNA damage. Gaining a better understanding of AD pathogenesis will require a framework that mechanistically interlinks all these phenomena. Currently, there is a rapid growth in the literature pointing toward insulin deficiency and insulin resistance as mediators of AD-type neurodegeneration, but this surge of new information is riddled with conflicting and unresolved concepts regarding the potential contributions of type 2 diabetes mellitus (T2DM), metabolic syndrome, and obesity to AD pathogenesis. Herein, we review the evidence that (1) T2DM causes brain insulin resistance, oxidative stress, and cognitive impairment, but its aggregate effects fall far short of mimicking AD; (2) extensive disturbances in brain insulin and insulin-like growth factor (IGF) signaling mechanisms represent early and progressive abnormalities and could account for the majority of molecular, biochemical, and histopathological lesions in AD; (3) experimental brain diabetes produced by intracerebral administration of streptozotocin shares many features with AD, including cognitive impairment and disturbances in acetylcholine homeostasis; and (4) experimental brain diabetes is treatable with insulin sensitizer agents, i.e., drugs currently used to treat T2DM. We conclude that the term "type 3 diabetes" accurately reflects the fact that AD represents a form of diabetes that selectively involves the brain and has molecular and biochemical features that overlap with both type 1 diabetes mellitus and T2DM.

Defective functional β-cell mass and Type 2 diabetes in the Goto-Kakizaki rat model

Increasing evidence indicates that decreased functional β-cell mass is the hallmark of Type 2 diabetes mellitus. Therefore, the debate focuses on the possible mechanisms responsible for abnormal islet microenvironment, decreased β-cell number, impaired β-cell function and their multifactorial etiologies. The information available on the Goto-Kakizaki/Par rat line, one of the best characterized animal models of spontaneous Type 2 diabetes mellitus, are reviewed in such a perspective. We propose that the defective β-cell mass and function in the Goto-Kakizaki/Par model reflect the complex interactions of multiple pathogenic players, including several independent loci containing genes responsible for some diabetic traits (but not decreased β-cell mass), gestational metabolic impairment inducing an epigenetic programming of the pancreas (decreased β-cell neogenesis), which is transmitted to the next generation, and loss of β-cell differentiation due to chronic exposure to hyperglycemia, inflammatory mediators, oxidative stress and perturbed islet microarchitecture.