| 1. |
- Gylvin, T., et al.
(författare)
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Functional SOCS1 polymorphisms are associated with variation in obesity in whites
- 2009
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Ingår i: Diabetes, Obesity and Metabolism. - : Wiley. - 1462-8902 .- 1463-1326. ; 11:3, s. 196-203
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Tidskriftsartikel (refereegranskat)abstract
- The suppressor of cytokine signalling 1 (SOCS1) is a natural inhibitor of cytokine and insulin signalling pathways and may also play a role in obesity. In addition, SOCS1 is considered a candidate gene in the pathogenesis of both type 1 diabetes (T1D) and type 2 diabetes (T2D). The objective was to perform mutation analysis of SOCS1 and to test the identified variations for association to T2D-related quantitative traits, T2D or T1D. Mutation scanning was performed by direct sequencing in 27 white Danish subjects. Genotyping was carried out by TaqMan allelic discrimination. A total of more than 8100 individuals were genotyped. Eight variations were identified in the 5' untranslated region (UTR) region. Two of these had allele frequencies below 1% and were not further examined. The six other variants were analysed in groups of T1D families (n = 1461 subjects) and T2D patients (n = 1430), glucose tolerant first-degree relatives of T2D patients (n = 212) and normal glucose tolerant (NGT) subjects. The rs33977706 polymorphism (-820G > T) was associated with a lower body mass index (BMI) (p = 0.004). In a second study (n = 4625 NGT subjects), significant associations of both the rs33977706 and the rs243330 (-1656G > A) variants to obesity were found (p = 0.047 and p = 0.015) respectively. The rs33977706 affected both binding of a nuclear protein to and the transcriptional activity of the SOCS1 promoter, indicating a relationship between this polymorphism and gene regulation. This study demonstrates that functional variations in the SOCS1 promoter may associate with alterations in BMI in the general white population.
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| 2. |
- Brorsson, C., et al.
(författare)
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Identification of T1D susceptibility genes within the MHC region by combining protein interaction networks and SNP genotyping data
- 2009
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Ingår i: Diabetes, Obesity and Metabolism. - : Wiley. - 1462-8902 .- 1463-1326. ; 11:S1, s. 60-66
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Tidskriftsartikel (refereegranskat)abstract
- To develop novel methods for identifying new genes that contribute to the risk of developing type 1 diabetes within the Major Histocompatibility Complex (MHC) region on chromosome 6, independently of the known linkage disequilibrium (LD) between human leucocyte antigen (HLA)-DRB1, -DQA1, -DQB1 genes. We have developed a novel method that combines single nucleotide polymorphism (SNP) genotyping data with protein-protein interaction (ppi) networks to identify disease-associated network modules enriched for proteins encoded from the MHC region. Approximately 2500 SNPs located in the 4 Mb MHC region were analysed in 1000 affected offspring trios generated by the Type 1 Diabetes Genetics Consortium (T1DGC). The most associated SNP in each gene was chosen and genes were mapped to ppi networks for identification of interaction partners. The association testing and resulting interacting protein modules were statistically evaluated using permutation. A total of 151 genes could be mapped to nodes within the protein interaction network and their interaction partners were identified. Five protein interaction modules reached statistical significance using this approach. The identified proteins are well known in the pathogenesis of T1D, but the modules also contain additional candidates that have been implicated in beta-cell development and diabetic complications. The extensive LD within the MHC region makes it important to develop new methods for analysing genotyping data for identification of additional risk genes for T1D. Combining genetic data with knowledge about functional pathways provides new insight into mechanisms underlying T1D.
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| 3. |
- Luheshi, Leila M, et al.
(författare)
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Systematic in vivo analysis of the intrinsic determinants of amyloid Beta pathogenicity.
- 2007
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Ingår i: PLoS biology. - : Public Library of Science (PLoS). - 1545-7885. ; 5:11, s. e290-
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Tidskriftsartikel (refereegranskat)abstract
- Protein aggregation into amyloid fibrils and protofibrillar aggregates is associated with a number of the most common neurodegenerative diseases. We have established, using a computational approach, that knowledge of the primary sequences of proteins is sufficient to predict their in vitro aggregation propensities. Here we demonstrate, using rational mutagenesis of the Abeta42 peptide based on such computational predictions of aggregation propensity, the existence of a strong correlation between the propensity of Abeta42 to form protofibrils and its effect on neuronal dysfunction and degeneration in a Drosophila model of Alzheimer disease. Our findings provide a quantitative description of the molecular basis for the pathogenicity of Abeta and link directly and systematically the intrinsic properties of biomolecules, predicted in silico and confirmed in vitro, to pathogenic events taking place in a living organism.
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