Insulin expressing hepatocytes not destroyed in transgenic NOD mice

BACKGROUND: The liver has been suggested as a suitable target organ for gene therapy of Type 1 diabetes. However, the fundamental issue whether insulin-secreting hepatocytes in vivo will be destroyed by the autoimmune processes that kill pancreatic β cells has not been fully addressed. It is possible that the insulin secreting liver cells will be destroyed by the immune system because hepatocytes express major histocompatibility complex (MHC) class I molecules and exhibit constitutive Fas expression; moreover the liver has antigen presenting activity. Together with previous reports that proinsulin is a possible autoantigen in the development of Type 1 diabetes, the autoimmune destruction of insulin producing liver cells is a distinct possibility. METHODS: To address this question, transgenic Non-Obese Diabetic (NOD) mice which express insulin in the liver were made using the Phosphoenolpyruvate Carboxykinase (PEPCK) promoter to drive the mouse insulin I gene (Ins). RESULTS: The liver cells were found to possess preproinsulin mRNA, translate (pro)insulin in vivo and release it when exposed to 100 nmol/l glucagon in vitro. The amount of insulin produced was however significantly lower than that produced by the pancreas. The transgenic PEPCK-Ins NOD mice became diabetic at 20–25 weeks of age, with blood glucose levels of 24.1 ± 1.7 mmol/l. Haematoxylin and eosin staining of liver sections from these transgenic NOD PEPCK-Ins mice revealed the absence of an infiltrate of immune cells, a feature that characterised the pancreatic islets of these mice. CONCLUSIONS: These data show that hepatocytes induced to produce (pro)insulin in NOD mice are not destroyed by an ongoing autoimmune response; furthermore the expression of (pro)insulin in hepatocytes is insufficient to prevent development of diabetes in NOD mice. These results support the use of liver cells as a potential therapy for type 1 diabetes. However it is possible that a certain threshold level of (pro)insulin production might have to be reached to trigger the autoimmune response

Different genetic mechanisms mediate spontaneous versus UVR-induced malignant melanoma

Genetic variation conferring resistance and susceptibility to carcinogen-induced tumorigenesis is frequently studied in mice. We have now turned this idea to melanoma using the collaborative cross (CC), a resource of mouse strains designed to discover genes for complex diseases. We studied melanoma-prone transgenic progeny across seventy CC genetic backgrounds. We mapped a strong quantitative trait locus for rapid onset spontaneous melanoma onset to Prkdc, a gene involved in detection and repair of DNA damage. In contrast, rapid onset UVR-induced melanoma was linked to the ribosomal subunit gene Rrp15. Ribosome biogenesis was upregulated in skin shortly after UVR exposure. Mechanistically, variation in the ‘usual suspects’ by which UVR may exacerbate melanoma, defective DNA repair, melanocyte proliferation, or inflammatory cell infiltration, did not explain melanoma susceptibility or resistance across the CC. Instead, events occurring soon after exposure, such as dysregulation of ribosome function, which alters many aspects of cellular metabolism, may be important

The Rising Incidence of Type 1 Diabetes Is Accounted for by Cases With Lower-Risk Human Leukocyte Antigen Genotypes

OBJECTIVE—The rising incidence of type 1 diabetes has been attributed to environment, implying a lesser role for genetic susceptibility. However, the rise could be accounted for by either more cases with classic high-risk genes or by cases with other risk genes. Separately, for any degree of genetic susceptibility, age at presentation may decrease in a permissive environment. To examine these possibilities, human leukocyte antigen (HLA) class II DRB1 genes known to confer risk for type 1 diabetes were analyzed in relation to year of birth and age at diagnosis over the last five decades

Tests for Genetic Interactions in Type 1 Diabetes: Linkage and Stratification Analyses of 4,422 Affected Sib-Pairs

OBJECTIVE - Interactions between genetic and environmental factors lead to immune dysregulation causing type 1 diabetes and other autoimmune disorders. Recently, many common genetic variants have been associated with type 1 diabetes risk, but each has modest individual effects. Familial clustering of type 1 diabetes has not been explained fully and could arise from many factors, including undetected genetic variation and gene interactions. RESEARCH DESIGN AND METHODS - To address this issue, the Type 1 Diabetes Genetics Consortium recruited 3,892 families, including 4,422 affected sib-pairs. After genotyping 6,090 markers, linkage analyses of these families were performed, using a novel method and taking into account factors such as genotype at known susceptibility loci. RESULTS - Evidence for linkage was robust at the HLA and INS loci, with logarithm of odds (LOD) scores of 398.6 and 5.5, respectively. There was suggestive support for five other loci. Stratification by other risk factors (including HLA and age at diagnosis) identified one convincing region on chromosome 6q14 showing linkage in male subjects (corrected LOD = 4.49; replication P = 0.0002), a locus on chromosome 19q in HLA identical siblings (replication P = 0.006), and four other suggestive loci. CONCLUSIONS - This is the largest linkage study reported for any disease. Our data indicate there are no major type 1 diabetes subtypes definable by linkage analyses; susceptibility is caused by actions of HLA and an apparently random selection from a large number of modest-effect loci; and apart from HLA and INS, there is no important susceptibility factor discoverable by linkage methods

Genetic characterization of early renal changes in a novel mouse model of diabetic kidney disease

Genetic factors influence susceptibility to diabetic kidney disease. Here we mapped genes mediating renal hypertrophic changes in response to diabetes. A survey of 15 mouse strains identified variation in diabetic kidney hypertrophy. Strains with greater (FVB/N(FVB)) and lesser (C57BL/6 (B6)) responses were crossed and diabetic F2 progeny were characterized. Kidney weights of diabetic F2 mice were broadly distributed. Quantitative trait locus analyses revealed diabetic mice with kidney weights in the upper quartile shared alleles on chromosomes (chr) 6 and 12; these loci were designated as Diabetic kidney hypertrophy (Dkh)-1 and -2. To confirm these loci, reciprocal congenic mice were generated with defined FVB chromosome segments on the B6 strain background (B6.Dkh1/2f) or vice versa (FVB.Dkh1/2b). Diabetic mice of the B6.Dkh1/2f congenic strain developed diabetic kidney hypertrophy, while the reciprocal FVB.Dkh1/2b congenic strain was protected. The chr6 locus contained the candidate gene; Ark1b3, coding aldose reductase; the FVB allele has a missense mutation in this gene. Microarray analysis identified differentially expressed genes between diabetic B6 and FVB mice. Thus, since the two loci identified by quantitative trait locus mapping are syntenic with regions identified for human diabetic kidney disease, the congenic strains we describe provide a valuable new resource to study diabetic kidney disease and test agents that may prevent it

Variable outcomes of human heart attack recapitulated in genetically diverse mice.

Clinical variation in patient responses to myocardial infarction (MI) has been difficult to model in laboratory animals. To assess the genetic basis of variation in outcomes after heart attack, we characterized responses to acute MI in the Collaborative Cross (CC), a multi-parental panel of genetically diverse mouse strains. Striking differences in post-MI functional, morphological, and myocardial scar features were detected across 32 CC founder and recombinant inbred strains. Transcriptomic analyses revealed a plausible link between increased intrinsic cardiac oxidative phosphorylation levels and MI-induced heart failure. The emergence of significant quantitative trait loci for several post-MI traits indicates that utilizing CC strains is a valid approach for gene network discovery in cardiovascular disease, enabling more accurate clinical risk assessment and prediction