1. Identification of Novel Potential Type 2 Diabetes Genes Mediating β-Cell Loss and Hyperglycemia Using Positional Cloning
- Author
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Heja Aga, Nicole Hallahan, Pascal Gottmann, Markus Jaehnert, Sophie Osburg, Gunnar Schulze, Anne Kamitz, Danny Arends, Gudrun Brockmann, Tanja Schallschmidt, Sandra Lebek, Alexandra Chadt, Hadi Al-Hasani, Hans-Georg Joost, Annette Schürmann, and Heike Vogel
- Subjects
type 2 diabetes ,β-cell loss ,insulin ,positional cloning ,transcriptomics ,haplotype ,Genetics ,QH426-470 - Abstract
Type 2 diabetes (T2D) is a complex metabolic disease regulated by an interaction of genetic predisposition and environmental factors. To understand the genetic contribution in the development of diabetes, mice varying in their disease susceptibility were crossed with the obese and diabetes-prone New Zealand obese (NZO) mouse. Subsequent whole-genome sequence scans revealed one major quantitative trait loci (QTL), Nidd/DBA on chromosome 4, linked to elevated blood glucose and reduced plasma insulin and low levels of pancreatic insulin. Phenotypical characterization of congenic mice carrying 13.6 Mbp of the critical fragment of DBA mice displayed severe hyperglycemia and impaired glucose clearance at week 10, decreased glucose response in week 13, and loss of β-cells and pancreatic insulin in week 16. To identify the responsible gene variant(s), further congenic mice were generated and phenotyped, which resulted in a fragment of 3.3 Mbp that was sufficient to induce hyperglycemia. By combining transcriptome analysis and haplotype mapping, the number of putative responsible variant(s) was narrowed from initial 284 to 18 genes, including gene models and non-coding RNAs. Consideration of haplotype blocks reduced the number of candidate genes to four (Kti12, Osbpl9, Ttc39a, and Calr4) as potential T2D candidates as they display a differential expression in pancreatic islets and/or sequence variation. In conclusion, the integration of comparative analysis of multiple inbred populations such as haplotype mapping, transcriptomics, and sequence data substantially improved the mapping resolution of the diabetes QTL Nidd/DBA. Future studies are necessary to understand the exact role of the different candidates in β-cell function and their contribution in maintaining glycemic control.
- Published
- 2020
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