Angelo J. Canty

A Genome-Wide Association Study Identifies a Novel Major Locus for Glycemic Control in Type 1 Diabetes, as Measured by Both A1C and Glucose

OBJECTIVE Glycemia is a major risk factor for the development of long-term complications in type 1 diabetes; however, no specific genetic loci have been identified for glycemic control in individuals with type 1 diabetes. To identify such loci in type 1 diabetes, we analyzed longitudinal repeated measures of A1C from the Diabetes Control and Complications Trial. RESEARCH DESIGN AND METHODS We performed a genome-wide association study using the mean of quarterly A1C values measured over 6.5 years, separately in the conventional (n = 667) and intensive (n = 637) treatment groups of the DCCT. At loci of interest, linear mixed models were used to take advantage of all the repeated measures. We then assessed the association of these loci with capillary glucose and repeated measures of multiple complications of diabetes. RESULTS We identified a major locus for A1C levels in the conventional treatment group near SORCS1 (10q25.1, P = 7 × 10−10), which was also associated with mean glucose (P = 2 × 10−5). This was confirmed using A1C in the intensive treatment group (P = 0.01). Other loci achieved evidence close to genome-wide significance: 14q32.13 (GSC) and 9p22 (BNC2) in the combined treatment groups and 15q21.3 (WDR72) in the intensive group. Further, these loci gave evidence for association with diabetic complications, specifically SORCS1 with hypoglycemia and BNC2 with renal and retinal complications. We replicated the SORCS1 association in Genetics of Diabetes in Kidneys (GoKinD) study control subjects (P = 0.01) and the BNC2 association with A1C in nondiabetic individuals. CONCLUSIONS A major locus for A1C and glucose in individuals with diabetes is near SORCS1. This may influence the design and analysis of genetic studies attempting to identify risk factors for long-term diabetic complications.

Application of Bernstein Polynomials for smooth estimation of a distribution and density function

The empirical distribution function is known to have optimum properties as an estimator of the underlying distribution function. However, it may not be appropriate for estimating continuous distributions because of its jump discontinuities. In this paper, we consider the application of Bernstein polynomials for approximating a bounded and continuous function and show that it can be naturally adapted for smooth estimation of a distribution function concentrated on the interval [0,1] by a continuous approximation of the empirical distribution function. The smoothness of the approximating polynomial is further used in deriving a smooth estimator of the corresponding density. The asymptotic properties of the resulting estimators are investigated. Specifically, we obtain strong consistency and asymptotic normality under appropriate choice of the degree of the polynomial. The case of distributions with other compact and non-compact support can be dealt through transformations. Thus, this paper gives a general method for non-parametric density estimation as an alternative to the current estimators. A small numerical investigation shows that the estimator proposed here may be preferable to the popular kernel-density estimator.

Lunatic Fringe-mediated Notch signaling is required for lung alveogenesis

Distal lung development occurs through coordinated induction of myofibroblasts, epithelial cells, and capillaries. Lunatic Fringe (Lfng) is a beta(1-3) N-acetylglucosamine transferase that modifies Notch receptors to facilitate their activation by Delta-like (Dll1/4) ligands. Lfng is expressed in the distal lung during saccular development, and deletion of this gene impairs myofibroblast differentiation and alveogenesis in this context. A similar defect was observed in Notch2(beta-geo/+)Notch3(beta-geo/beta-geo) compound mutant mice but not in Notch2(beta-geo/+) or Notch3(beta-geo/beta-geo) single mutants. Finally, to directly test for the role of Notch signaling in myofibroblast differentiation in vivo, we used ROSA26-rtTA(/+);tetO-CRE(/+);RBPJkappa(flox/flox) inducible mutant mice to show that disruption of canonical Notch signaling during late embryonic development prevents induction of smooth muscle actin in mesenchymal cells of the distal lung. In sum, these results demonstrate that Lfng functions to enhance Notch signaling in myofibroblast precursor cells and thereby to coordinate differentiation and mobilization of myofibroblasts required for alveolar septation.

Generation and analysis of a mouse intestinal metatranscriptome through Illumina based RNA-sequencing

With the advent of high through-put sequencing (HTS), the emerging science of metagenomics is transforming our understanding of the relationships of microbial communities with their environments. While metagenomics aims to catalogue the genes present in a sample through assessing which genes are actively expressed, metatranscriptomics can provide a mechanistic understanding of community inter-relationships. To achieve these goals, several challenges need to be addressed from sample preparation to sequence processing, statistical analysis and functional annotation. Here we use an inbred non-obese diabetic (NOD) mouse model in which germ-free animals were colonized with a defined mixture of eight commensal bacteria, to explore methods of RNA extraction and to develop a pipeline for the generation and analysis of metatranscriptomic data. Applying the Illumina HTS platform, we sequenced 12 NOD cecal samples prepared using multiple RNA-extraction protocols. The absence of a complete set of reference genomes necessitated a peptide-based search strategy. Up to 16% of sequence reads could be matched to a known bacterial gene. Phylogenetic analysis of the mapped ORFs revealed a distribution consistent with ribosomal RNA, the majority from Bacteroides or Clostridium species. To place these HTS data within a systems context, we mapped the relative abundance of corresponding Escherichia coli homologs onto metabolic and protein-protein interaction networks. These maps identified bacterial processes with components that were well-represented in the datasets. In summary this study highlights the potential of exploiting the economy of HTS platforms for metatranscriptomics.

Resampling-based variance estimation for labour force surveys

Reference STAT-ARTICLE-1999-002View record in Web of Science Record created on 2006-04-21, modified on 2017-05-12

Sex-Specific Effect of Insulin-Dependent Diabetes 4 on Regulation of Diabetes Pathogenesis in the Nonobese Diabetic Mouse

Many human autoimmune diseases are more frequent in females than males, and their clinical severity is affected by sex hormone levels. A strong female bias is also observed in the NOD mouse model of type I diabetes (T1D). In both NOD mice and humans, T1D displays complex polygenic inheritance and T cell-mediated autoimmune pathogenesis. The identities of many of the insulin-dependent diabetes (Idd) loci, their influence on specific stages of autoimmune pathogenesis, and sex-specific effects of Idd loci in the NOD model are not well understood. To address these questions, we analyzed cyclophosphamide-accelerated T1D (CY-T1D) that causes disease with high and similar frequencies in male and female NOD mice, but not in diabetes-resistant animals, including the nonobese diabetes-resistant (NOR) strain. In this study we show by genetic linkage analysis of (NOD × NOR) × NOD backcross mice that progression to severe islet inflammation after CY treatment was controlled by the Idd4 and Idd9 loci. Congenic strains on both the NOD and NOR backgrounds confirmed the roles of Idd4 and Idd9 in CY-T1D susceptibility and revealed the contribution of a third locus, Idd5. Importantly, we show that the three loci acted at distinct stages of islet inflammation and disease progression. Among these three loci, Idd4 alleles alone displayed striking sex-specific behavior in CY-accelerated disease. Additional studies will be required to address the question of whether a sex-specific effect of Idd4, observed in this study, is also present in the spontaneous model of the disease with striking female bias.

Molecular Genetic Analysis of the Idd4 Locus Implicates the IFN Response in Type 1 Diabetes Susceptibility in Nonobese Diabetic Mice

High-resolution mapping and identification of the genes responsible for type 1 diabetes (T1D) has proved difficult because of the multigenic etiology and low penetrance of the disease phenotype in linkage studies. Mouse congenic strains have been useful in refining Idd susceptibility loci in the NOD mouse model and providing a framework for identification of genes underlying complex autoimmune syndromes. Previously, we used NOD and a nonobese diabetes-resistant strain to map the susceptibility to T1D to the Idd4 locus on chromosome 11. Here, we report high-resolution mapping of this locus to 1.4 megabases. The NOD Idd4 locus was fully sequenced, permitting a detailed comparison with C57BL/6 and DBA/2J strains, the progenitors of T1D resistance alleles found in the nonobese diabetes-resistant strain. Gene expression arrays and quantitative real-time PCR were used to prioritize Idd4 candidate genes by comparing macrophages/dendritic cells from congenic strains where allelic variation was confined to the Idd4 interval. The differentially expressed genes either were mapped to Idd4 or were components of the IFN response pathway regulated in trans by Idd4. Reflecting central roles of Idd4 genes in Ag presentation, arachidonic acid metabolism and inflammation, phagocytosis, and lymphocyte trafficking, our combined analyses identified Alox15, Alox12e, Psmb6, Pld2, and Cxcl16 as excellent candidate genes for the effects of the Idd4 locus.

The Idd4 Locus Displays Sex-Specific Epistatic Effects on Type 1 Diabetes Susceptibility in Nonobese Diabetic Mice

The nonobese diabetic (NOD) mouse recapitulates many aspects of the pathogenesis of type 1 diabetes in humans, including inheritance as a complex trait. More than 20 Idd loci have been linked to type 1 diabetes susceptibility in NOD mice. Previously, we used linkage analysis of NOD crossed to the nonobese diabetes-resistant (NOR) strain and NOD congenic strains to map susceptibility to both spontaneous and cyclophosphamide-accelerated type 1 diabetes to the Idd4 locus on chromosome 11 that displayed a sex-specific effect on diabetes susceptibility. Here, we elucidate the complex genetic architecture of Idd4 by analysis of congenic strains on the NOD and NOR backgrounds. We previously refined Idd4.1 to 1.4 Mb and demonstrated an impact of this interval on type 1 interferon pathways in antigen-presenting cells. Here, we identify a second subregion, the 0.92 Mb Idd4.2 locus located telomeric to Idd4.1. Strikingly, Idd4.2 displayed a sex-specific, epistatic interaction with Idd4.1 in NOR.NOD congenic females that was not observed in syngenic males. Idd4.2 contains 29 genes, and promising candidates for the Idd4.2 effect on type 1 diabetes are described. These data demonstrate sex-dependent interaction effects on type 1 diabetes susceptibility and provide a framework for functional analysis of Idd4.2 candidate genes.

Comparison of Bayesian and frequentist approaches in modelling risk of preterm birth near the Sydney Tar Ponds, Nova Scotia, Canada

BackgroundThis study compares the Bayesian and frequentist (non-Bayesian) approaches in the modelling of the association between the risk of preterm birth and maternal proximity to hazardous waste and pollution from the Sydney Tar Pond site in Nova Scotia, Canada.MethodsThe data includes 1604 observed cases of preterm birth out of a total population of 17559 at risk of preterm birth from 144 enumeration districts in the Cape Breton Regional Municipality. Other covariates include the distance from the Tar Pond; the rate of unemployment to population; the proportion of persons who are separated, divorced or widowed; the proportion of persons who have no high school diploma; the proportion of persons living alone; the proportion of single parent families and average income. Bayesian hierarchical Poisson regression, quasi-likelihood Poisson regression and weighted linear regression models were fitted to the data.ResultsThe results of the analyses were compared together with their limitations.ConclusionThe results of the weighted linear regression and the quasi-likelihood Poisson regression agrees with the result from the Bayesian hierarchical modelling which incorporates the spatial effects.

Polymorphism in the Innate Immune Receptor SIRPα Controls CD47 Binding and Autoimmunity in the Nonobese Diabetic Mouse

The signal regulatory protein (SIRP) locus encodes a family of paired receptors that mediate both activating and inhibitory signals and is associated with type 1 diabetes (T1D) risk. The NOD mouse model recapitulates multiple features of human T1D and enables mechanistic analysis of the impact of genetic variations on disease. In this study, we identify Sirpa encoding an inhibitory receptor on myeloid cells as a gene in the insulin-dependent diabetes locus 13.2 (Idd13.2) that drives islet inflammation and T1D. Compared to T1D-resistant strains, the NOD variant of SIRPα displayed greater binding to its ligand CD47, as well as enhanced T cell proliferation and diabetogenic potency. Myeloid cell–restricted expression of a Sirpa transgene accelerated disease in a dose-dependent manner and displayed genetic and functional interaction with the Idd5 locus to potentiate insulitis progression. Our study demonstrates that variations in both SIRPα sequence and expression level modulate T1D immunopathogenesis. Thus, we identify Sirpa as a T1D risk gene and provide insight into the complex mechanisms by which disease-associated variants act in concert to drive defined stages in disease progression.