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Search: WFRF:(Aalund M)

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1.
  • Bergholdt, R, et al. (author)
  • Transcriptional profiling of type 1 diabetes genes on chromosome 21 in a rat beta-cell line and human pancreatic islets
  • 2007
  • In: Genes and Immunity. - : Springer Science and Business Media LLC. - 1476-5470 .- 1466-4879. ; 8:3, s. 232-238
  • Journal article (peer-reviewed)abstract
    • We recently finemapped a type 1 diabetes (T1D)-linked region on chromosome 21, indicating that one or more T1D-linked genes exist in this region with 33 annotated genes. In the current study, we have taken a novel approach using transcriptional profiling in predicting and prioritizing the most likely candidate genes influencing beta-cell function in this region. Two array-based approaches were used, a rat insulinoma cell line (INS-1 alpha beta) overexpressing pancreatic duodenum homeobox 1 (pdx-1) and treated with interleukin 1 beta (IL-1 beta) as well as human pancreatic islets stimulated with a mixture of cytokines. Several candidate genes with likely functional significance in T1D were identified. Genes showing differential expression in the two approaches were highly similar, supporting the role of these specific gene products in cytokine-induced beta-cell damage. These were genes involved in cytokine signaling, oxidative phosphorylation, defense responses and apoptosis. The analyses, furthermore, revealed several transcription factor binding sites shared by the differentially expressed genes and by genes demonstrating highly similar expression profiles with these genes. Comparable findings in the rat beta-cell line and human islets support the validity of the methods used and support this as a valuable approach for gene mapping and identification of genes with potential functional significance in T1D, within a region of linkage.
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2.
  • Bergholdt, Regine, et al. (author)
  • Integrative analysis for finding genes and networks involved in diabetes and other complex diseases
  • 2007
  • In: Genome Biology. - : Springer Science and Business Media LLC. - 1474-7596 .- 1465-6906. ; 8:11
  • Journal article (peer-reviewed)abstract
    • We have developed an integrative analysis method combining genetic interactions, identified using type l 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.
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  • Result 1-4 of 4

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