Publications by authors named "Mogens Aalund"

3 Publications

  • Page 1 of 1

Divalent metal transporter 1 regulates iron-mediated ROS and pancreatic β cell fate in response to cytokines.

Cell Metab 2012 Oct 20;16(4):449-61. Epub 2012 Sep 20.

Center for Medical Research Methodology, Department of Biomedical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark.

Reactive oxygen species (ROS) contribute to target-cell damage in inflammatory and iron-overload diseases. Little is known about iron transport regulation during inflammatory attack. Through a combination of in vitro and in vivo studies, we show that the proinflammatory cytokine IL-1β induces divalent metal transporter 1 (DMT1) expression correlating with increased β cell iron content and ROS production. Iron chelation and siRNA and genetic knockdown of DMT1 expression reduce cytokine-induced ROS formation and cell death. Glucose-stimulated insulin secretion in the absence of cytokines in Dmt1 knockout islets is defective, highlighting a physiological role of iron and ROS in the regulation of insulin secretion. Dmt1 knockout mice are protected against multiple low-dose streptozotocin and high-fat diet-induced glucose intolerance, models of type 1 and type 2 diabetes, respectively. Thus, β cells become prone to ROS-mediated inflammatory damage via aberrant cellular iron metabolism, a finding with potential general cellular implications.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cmet.2012.09.001DOI Listing
October 2012

Integrative analysis for finding genes and networks involved in diabetes and other complex diseases.

Genome Biol 2007 ;8(11):R253

Steno Diabetes Center, Niels Steensensvej 2, DK-2820 Gentofte, Denmark.

We have developed an integrative analysis method combining genetic interactions, identified using type 1 diabetes genome scan data, and a high-confidence human protein interaction network. Resulting networks were ranked by the significance of the enrichment of proteins from interacting regions. We identified a number of new protein network modules and novel candidate genes/proteins for type 1 diabetes. We propose this type of integrative analysis as a general method for the elucidation of genes and networks involved in diabetes and other complex diseases.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/gb-2007-8-11-r253DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2258178PMC
August 2008

Novel analytical methods applied to type 1 diabetes genome-scan data.

Am J Hum Genet 2004 Apr 11;74(4):647-60. Epub 2004 Mar 11.

Steno Diabetes Center, Gentofte, Denmark.

Complex traits like type 1 diabetes mellitus (T1DM) are generally taken to be under the influence of multiple genes interacting with each other to confer disease susceptibility and/or protection. Although novel methods are being developed, analyses of whole-genome scans are most often performed with multipoint methods that work under the assumption that multiple trait loci are unrelated to each other; that is, most models specify the effect of only one locus at a time. We have applied a novel approach, which includes decision-tree construction and artificial neural networks, to the analysis of T1DM genome-scan data. We demonstrate that this approach (1) allows identification of all major susceptibility loci identified by nonparametric linkage analysis, (2) identifies a number of novel regions as well as combinations of markers with predictive value for T1DM, and (3) may be useful in characterizing markers in linkage disequilibrium with protective-gene variants. Furthermore, the approach outlined here permits combined analyses of genetic-marker data and information on environmental and clinical covariates.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1086/383095DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1181942PMC
April 2004
-->