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Novel loci for hyperglycemia identified by QTL mapping of longitudinal phenotypes and congenic analysis. Sci Rep 2023; 13:1315. [PMID: 36693911 PMCID: PMC9873599 DOI: 10.1038/s41598-023-28189-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 01/13/2023] [Indexed: 01/25/2023] Open
Abstract
We previously reported that four hyperglycemia loci are located on three chromosomes in the Nagoya-Shibata-Yasuda (NSY) mouse model, commonly used to study type 2 diabetes. However, we did not search for hyperglycemia loci across all chromosomes. In this study, we performed quantitative trait loci (QTLs) mapping of longitudinal phenotypes from crosses between NSY (hyperglycemic) and C3H (normoglycemic) mice. We identified four new QTLs for hyperglycemia, namely Nidd5nsy, Nidd6nsy, Nidd1c3h, and Nidd2c3h, on Chromosome 1, 4, 10, and 13, respectively. These QTLs were associated with hyperglycemia in young mice and had attenuated effects in older mice. Nidd5nsy and Nidd6nsy were hyperglycemic with NSY alleles, and Nidd1c3h and Nidd2c3h were hyperglycemic with C3H alleles. We further bred Nidd5nsy congenic mice and demonstrated that Nidd5nsy has a strong effect on hyperglycemia when young, accompanied by insulin resistance and visceral fat accumulation. These results showed that the effects of individual QTLs strengthened or weakened with age, and that the sum of the effects of QTLs captured the age-related deterioration of glucose tolerance in individuals. Our results support the importance of longitudinal phenotypes in the genetic analysis of polygenic traits and have implications for the genetic basis and pathogenesis of type 2 diabetes in humans.
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E96V Mutation in the Kdelr3 Gene Is Associated with Type 2 Diabetes Susceptibility in Obese NZO Mice. Int J Mol Sci 2023; 24:ijms24010845. [PMID: 36614300 PMCID: PMC9820861 DOI: 10.3390/ijms24010845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 12/16/2022] [Accepted: 12/28/2022] [Indexed: 01/05/2023] Open
Abstract
Type 2 diabetes (T2D) represents a multifactorial metabolic disease with a strong genetic predisposition. Despite elaborate efforts in identifying the genetic variants determining individual susceptibility towards T2D, the majority of genetic factors driving disease development remain poorly understood. With the aim to identify novel T2D risk genes we previously generated an N2 outcross population using the two inbred mouse strains New Zealand obese (NZO) and C3HeB/FeJ (C3H). A linkage study performed in this population led to the identification of the novel T2D-associated quantitative trait locus (QTL) Nbg15 (NZO blood glucose on chromosome 15, Logarithm of odds (LOD) 6.6). In this study we used a combined approach of positional cloning, gene expression analyses and in silico predictions of DNA polymorphism on gene/protein function to dissect the genetic variants linking Nbg15 to the development of T2D. Moreover, we have generated congenic strains that associated the distal sublocus of Nbg15 to mechanisms altering pancreatic beta cell function. In this sublocus, Cbx6, Fam135b and Kdelr3 were nominated as potential causative genes associated with the Nbg15 driven effects. Moreover, a putative mutation in the Kdelr3 gene from NZO was identified, negatively influencing adaptive responses associated with pancreatic beta cell death and induction of endoplasmic reticulum stress. Importantly, knockdown of Kdelr3 in cultured Min6 beta cells altered insulin granules maturation and pro-insulin levels, pointing towards a crucial role of this gene in islets function and T2D susceptibility.
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Wagner A, Schosserer M. The epitranscriptome in ageing and stress resistance: A systematic review. Ageing Res Rev 2022; 81:101700. [PMID: 35908668 DOI: 10.1016/j.arr.2022.101700] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 07/15/2022] [Accepted: 07/25/2022] [Indexed: 01/31/2023]
Abstract
Modifications of RNA, collectively called the "epitranscriptome", might provide novel biomarkers and innovative targets for interventions in geroscience but are just beginning to be studied in the context of ageing and stress resistance. RNA modifications modulate gene expression by affecting translation initiation and speed, miRNA binding, RNA stability, and RNA degradation. Nonetheless, the precise underlying molecular mechanisms and physiological consequences of most alterations of the epitranscriptome are still only poorly understood. We here systematically review different types of modifications of rRNA, tRNA and mRNA, the methodology to analyze them, current challenges in the field, and human disease associations. Furthermore, we compiled evidence for a connection between individual enzymes, which install RNA modifications, and lifespan in yeast, worm and fly. We also included resistance to different stressors and competitive fitness as search criteria for genes potentially relevant to ageing. Promising candidates identified by this approach include RCM1/NSUN5, RRP8, and F33A8.4/ZCCHC4 that introduce base methylations in rRNA, the methyltransferases DNMT2 and TRM9/ALKBH8, as well as factors involved in the thiolation or A to I editing in tRNA, and finally the m6A machinery for mRNA.
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Affiliation(s)
- Anja Wagner
- Institute of Molecular Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria
| | - Markus Schosserer
- Institute of Molecular Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria; Institute of Medical Genetics, Center for Pathobiochemistry and Genetics, Medical University of Vienna, Vienna, Austria; Austrian Cluster for Tissue Regeneration, Vienna, Austria.
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Kuhn T, Kaiser K, Lebek S, Altenhofen D, Knebel B, Herwig R, Rasche A, Pelligra A, Görigk S, Khuong JMA, Vogel H, Schürmann A, Blüher M, Chadt A, Al-Hasani H. Comparative genomic analyses of multiple backcross mouse populations suggest SGCG as a novel potential obesity-modifier gene. Hum Mol Genet 2022; 31:4019-4033. [PMID: 35796564 DOI: 10.1093/hmg/ddac150] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 05/10/2022] [Accepted: 07/01/2022] [Indexed: 11/14/2022] Open
Abstract
To nominate novel disease genes for obesity and type 2 diabetes (T2D), we recently generated two mouse backcross populations of the T2D-susceptible New Zealand Obese (NZO/HI) mouse strain and two genetically different, lean and T2D-resistant strains, 129P2/OlaHsd and C3HeB/FeJ. Comparative linkage analysis of our two female backcross populations identified seven novel body fat-associated quantitative trait loci (QTL). Only the locus Nbw14 (NZO body weight on chromosome 14) showed linkage to obesity-related traits in both backcross populations, indicating that the causal gene variant is likely specific for the NZO strain as NZO allele carriers in both crosses displayed elevated body weight and fat mass. To identify candidate genes for Nbw14, we used a combined approach of gene expression and haplotype analysis to filter for NZO-specific gene variants in gonadal white adipose tissue (gWAT), defined as the main QTL-target tissue. Only two genes, Arl11 and Sgcg, fulfilled our candidate criteria. In addition, expression QTL analysis revealed cis-signals for both genes within the Nbw14 locus. Moreover, retroviral overexpression of Sgcg in 3 T3-L1 adipocytes resulted in increased insulin-stimulated glucose uptake. In humans, mRNA levels of SGCG correlated with BMI and body fat mass exclusively in diabetic subjects, suggesting that SGCG may present a novel marker for metabolically unhealthy obesity. In conclusion, our comparative-cross analysis could substantially improve the mapping resolution of the obesity locus Nbw14. Future studies will shine light on the mechanism by which Sgcg may protect from the development of obesity.
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Affiliation(s)
- Tanja Kuhn
- Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Medical Faculty, Duesseldorf, D-40225, Germany.,German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany
| | - Katharina Kaiser
- Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Medical Faculty, Duesseldorf, D-40225, Germany.,German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany
| | - Sandra Lebek
- Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Medical Faculty, Duesseldorf, D-40225, Germany.,German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany
| | - Delsi Altenhofen
- Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Medical Faculty, Duesseldorf, D-40225, Germany.,German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany
| | - Birgit Knebel
- Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Medical Faculty, Duesseldorf, D-40225, Germany.,German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany
| | - Ralf Herwig
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, D-14195, Germany
| | - Axel Rasche
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, D-14195, Germany
| | - Angela Pelligra
- Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Medical Faculty, Duesseldorf, D-40225, Germany.,German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany
| | - Sarah Görigk
- Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Medical Faculty, Duesseldorf, D-40225, Germany.,German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany
| | - Jenny Minh-An Khuong
- Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Medical Faculty, Duesseldorf, D-40225, Germany.,German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany
| | - Heike Vogel
- German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany.,Department of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, D-14558, Germany
| | - Annette Schürmann
- German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany.,Department of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, D-14558, Germany
| | - Matthias Blüher
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Zentrum München at the University of Leipzig and University Hospital Leipzig, Leipzig, D-04103, Germany
| | - Alexandra Chadt
- Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Medical Faculty, Duesseldorf, D-40225, Germany.,German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany
| | - Hadi Al-Hasani
- Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center (DDZ), Heinrich Heine University, Medical Faculty, Duesseldorf, D-40225, Germany.,German Center for Diabetes Research (DZD), Munich-Neuherberg, D-85764, Germany
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Gao R, Fu Q, Jiang HM, Shen M, Zhao RL, Qian Y, He YQ, Xu KF, Xu XY, Chen H, Zhang Q, Yang T. Temporal metabolic and transcriptomic characteristics crossing islets and liver reveal dynamic pathophysiology in diet-induced diabetes. iScience 2021; 24:102265. [PMID: 33817571 PMCID: PMC8008187 DOI: 10.1016/j.isci.2021.102265] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 12/30/2020] [Accepted: 03/01/2021] [Indexed: 12/15/2022] Open
Abstract
To investigate the molecular mechanisms underlying islet dysfunction and insulin resistance in diet-induced diabetes, we conducted temporal RNA sequencing of tissues responsible for insulin secretion (islets) and action (liver) every 4 weeks in mice on high-fat (HFD) or chow diet for 24 weeks, linking to longitudinal profile of metabolic characteristics. The diverse responses of α, β, and δ cells to glucose and palmitate indicated HFD-induced dynamic deterioration of islet function from dysregulation to failure. Insulin resistance developed with variable time course in different tissues. Weighted gene co-expression network analysis and Ingenuity Pathway Analysis implicated islets and liver jointly programmed β-cell compensatory adaption via cell proliferation at early phase and irreversible islet dysfunction by inappropriate immune response at later stage, and identified interconnected molecules including growth differentiation factor 15. Frequencies of T cell subpopulation showed an early decrement in Tregs followed by increases in Th1 and Th17 cells during progression to diabetes.
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Affiliation(s)
- Rui Gao
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China.,Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford OX37LE, UK
| | - Qi Fu
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - He-Min Jiang
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Min Shen
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Rui-Ling Zhao
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Yu Qian
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Yun-Qiang He
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Kuan-Feng Xu
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Xin-Yu Xu
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Heng Chen
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Quan Zhang
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford OX37LE, UK
| | - Tao Yang
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
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