PgmNr M5023: IMPC metabolic phenotyping: Systemic search for new gene functions associated with disturbances in energy balance regulation and glucose homeostasis.

Authors:
Jan Rozman ^1,10 ; Robert Brommage ¹ ; Birgit Rathkolb ^1,2,10 ; Manuela Oestereicher ¹ ; Stefanie Leuchtenberger ¹ ; Martin Kistler ¹ ; Valerie Gailus-Durner ¹ ; Helmut Fuchs ¹ ; Eckhard Wolf ^2,10 ; Martin Klingenspor ^3,4 ; Monica Campillos ^5,10 ; Aakash Chavan Ravindranath ^5,10 ; Thomas Werner ^6,7 ; Christine Schuett ¹ ; The IMPC Consortium ⁹ ; Martin Hrabe de Angelis ^1,8,10

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Institutes
1) German Mouse Clinic, Inst. of Experimental Genetics, Helmholtz Zentrum Muenchen, Germany; 2) Inst. of Molecular Animal Breeding and Biotechnology, Gene Center, Ludwig-Maximilians-Universitaet Muenchen, Germany; 3) Technical University Munich, Else-Kroener-Fresenius Center for Nutritional Medicine, TUM School of Life Sciences Weihenstephan, Freising, Germany; 4) Technical University Munich, ZIEL - Institute for Food and Health, Freising, Germany; 5) Systems Biology of Small Molecules, Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum Muenchen, 85764 Neuherberg, Germany; 6) Departments of Internal Medicine and Nephrology, University of Michigan, Ann Arbor, Michigan, USA; 7) Genomatix GmbH Muenchen, Germany; 8) Chair of Experimental Genetics, Center for Nutrition and Food Sciences Weihenstephan, Technische Universitaet Muenchen, Germany; 9) The International Mouse Phenotyping Consortium, MRC Harwell, Oxfordshire, UK; 10) German Center for Diabetes Research, Helmholtz Zentrum Muenchen, 85764 Neuherberg, Germany.

Abstract:

The International Mouse Phenotyping Consortium (IMPC) aims to generate, phenotype, and offer a knock-out mouse model for every protein-coding gene. Disturbances in energy balance regulation or glucose homeostasis result in diseases such as obesity and type 2 diabetes mellitus. We are especially interested in genes linked to these metabolic disorders. Therefore, IMPC phenotyping data were used to identify novel genotype-phenotype associations. From the IMPC adult phenotyping pipeline we selected 7 clinically relevant parameters: (1) blood glucose levels after overnight fasting, (2) area under the curve during the glucose tolerance test, (3) non-fasting triglycerides, (4) body mass, (5) metabolic rate and (6) oxygen consumption both normalized to body mass, and (7) respiratory exchange ratio. Depending on the completeness of uploaded data, phenotyping data were obtained from 329 mutant lines (for metabolic rate) to 1649 mutant lines (for body mass). Phenodeviants were selected based on the ratio of absolute mean mutant divided by absolute mean wildtype (wt) parameter values, resulting in a new index value that ranged between 0.2 (i.e. 20% of wt) and 2.8 (i.e. 280% of wt) depending on the parameter. In brief, we could both confirm published knowledge regarding functional associations to metabolism (Mrap2 and Cpe) as well as identify novel genes that could be linked to human disorders. The combination of more than one parameter ratio (e.g. strong deviations in glucose clearance, fasted blood glucose, and triglyceride levels in 1.4 % of the genes) also helped to detect new disease models. The dataset may be useful for analysis of metabolic pathways and identification of novel regulatory networks.