@article{JonasKluthHelmsetal.2022, author = {Jonas, Wenke and Kluth, Oliver and Helms, Anett and Voss, Sarah and Jahnert, Markus and Gottmann, Pascal and Speckmann, Thilo and Knebel, Birgit and Chadt, Alexandra and Al-Hasani, Hadi and Sch{\"u}rmann, Annette and Vogel, Heike}, title = {Identification of novel genes involved in hyperglycemia in mice}, series = {International journal of molecular sciences}, volume = {23}, journal = {International journal of molecular sciences}, number = {6}, publisher = {MDPI}, address = {Basel}, issn = {1661-6596}, doi = {10.3390/ijms23063205}, pages = {13}, year = {2022}, abstract = {Current attempts to prevent and manage type 2 diabetes have been moderately effective, and a better understanding of the molecular roots of this complex disease is important to develop more successful and precise treatment options. Recently, we initiated the collective diabetes cross, where four mouse inbred strains differing in their diabetes susceptibility were crossed with the obese and diabetes-prone NZO strain and identified the quantitative trait loci (QTL) Nidd13/NZO, a genomic region on chromosome 13 that correlates with hyperglycemia in NZO allele carriers compared to B6 controls. Subsequent analysis of the critical region, harboring 644 genes, included expression studies in pancreatic islets of congenic Nidd13/NZO mice, integration of single-cell data from parental NZO and B6 islets as well as haplotype analysis. Finally, of the five genes (Acot12, S100z, Ankrd55, Rnf180, and Iqgap2) within the polymorphic haplotype block that are differently expressed in islets of B6 compared to NZO mice, we identified the calcium-binding protein S100z gene to affect islet cell proliferation as well as apoptosis when overexpressed in MINE cells. In summary, we define S100z as the most striking gene to be causal for the diabetes QTL Nidd13/NZO by affecting beta-cell proliferation and apoptosis. Thus, S100z is an entirely novel diabetes gene regulating islet cell function.}, language = {en} } @article{AgaBarfknechtHallahanGottmannetal.2020, author = {Aga-Barfknecht, Heja and Hallahan, Nicole and Gottmann, Pascal and J{\"a}hnert, Markus and Osburg, Sophie and Schulze, Gunnar and Kamitz, Anne and Arends, Danny and Brockmann, Gudrun and Schallschmidt, Tanja and Lebek, Sandra and Chadt, Alexandra and Al-Hasani, Hadi and Joost, Hans-Georg and Sch{\"u}rmann, Annette and Vogel, Heike}, title = {Identification of novel potential type 2 diabetes genes mediating beta-cell loss and hyperglycemia using positional cloning}, series = {Frontiers in genetics}, volume = {11}, journal = {Frontiers in genetics}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {1664-8021}, doi = {10.3389/fgene.2020.567191}, pages = {11}, year = {2020}, 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/DBAon 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 beta-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, andCalr4) 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 QTLNidd/DBA. Future studies are necessary to understand the exact role of the different candidates in beta-cell function and their contribution in maintaining glycemic control.}, language = {en} } @article{VogelKamitzHallahanetal.2018, author = {Vogel, Heike and Kamitz, Anne and Hallahan, Nicole and Lebek, Sandra and Schallschmidt, Tanja and Jonas, Wenke and J{\"a}hnert, Markus and Gottmann, Pascal and Zellner, Lisa and Kanzleiter, Timo and Damen, Mareike and Altenhofen, Delsi and Burkhardt, Ralph and Renner, Simone and Dahlhoff, Maik and Wolf, Eckhard and M{\"u}ller, Timo Dirk and Bl{\"u}her, Matthias and Joost, Hans-Georg and Chadt, Alexandra and Al-Hasani, Hadi and Sch{\"u}rmann, Annette}, title = {A collective diabetes cross in combination with a computational framework to dissect the genetics of human obesity and Type 2 diabetes}, series = {Human molecular genetics}, volume = {27}, journal = {Human molecular genetics}, number = {17}, publisher = {Oxford Univ. Press}, address = {Oxford}, issn = {0964-6906}, doi = {10.1093/hmg/ddy217}, pages = {3099 -- 3112}, year = {2018}, abstract = {To explore the genetic determinants of obesity and Type 2 diabetes (T2D), the German Center for Diabetes Research (DZD) conducted crossbreedings of the obese and diabetes-prone New Zealand Obese mouse strain with four different lean strains (B6, DBA, C3H, 129P2) that vary in their susceptibility to develop T2D. Genome-wide linkage analyses localized more than 290 quantitative trait loci (QTL) for obesity, 190 QTL for diabetes-related traits and 100 QTL for plasma metabolites in the out-cross populations. A computational framework was developed that allowed to refine critical regions and to nominate a small number of candidate genes by integrating reciprocal haplotype mapping and transcriptome data. The efficiency of the complex procedure was demonstrated for one obesity QTL. The genomic interval of 35 Mb with 502 annotated candidate genes was narrowed down to six candidates. Accordingly, congenic mice retained the obesity phenotype owing to an interval that contains three of the six candidate genes. Among these the phospholipase PLA2G4A exhibited an elevated expression in adipose tissue of obese human subjects and is therefore a critical regulator of the obesity locus. Together, our broad and complex approach demonstrates that combined- and comparative-cross analysis exhibits improved mapping resolution and represents a valid tool for the identification of disease genes.}, language = {en} } @misc{SchwerbelKamitzJaehnertetal.2018, author = {Schwerbel, Kristin and Kamitz, Anne and Jaehnert, Markus and Gottmann, P. and Schumacher, Fabian and Kleuser, Burkhard and Haltenhof, T. and Heyd, F. and Roden, Michael and Chadt, Alexandra and Al-Hasani, Hadi and Jonas, W. and Vogel, Heike and Sch{\"u}rmann, Annette}, title = {Two immune-related GTPases prevent from hepatic fat accumulation by inducing autophagy}, series = {Diabetologia : journal of the European Association for the Study of Diabetes (EASD)}, volume = {61}, journal = {Diabetologia : journal of the European Association for the Study of Diabetes (EASD)}, publisher = {Springer}, address = {New York}, issn = {0012-186X}, pages = {S259 -- S259}, year = {2018}, language = {en} } @phdthesis{Chadt2009, author = {Chadt, Alexandra}, title = {Functional characterization of a novel candidate gene for obesity, Tbc 1d1}, address = {Potsdam}, pages = {133 S.}, year = {2009}, language = {en} }