[en] For many inborn errors of metabolism (IEM) the understanding of disease mechanisms remains limited, in part explaining their unmet medical needs. The expressivity of IEM disease phenotypes is affected by disease-modifying factors, including rare and common polygenic variation. We hypothesize that we can identify these modulating pathways using molecular signatures of IEM in combination with multiomic data and gene regulatory networks generated from non-IEM animal and human populations. We tested this approach by identifying and subsequently validating glucocorticoid signaling as a candidate modifier of mitochondrial fatty acid oxidation disorders, and recapitulating complement signaling as a modifier of inflammation in Gaucher disease. Our work describes a novel approach that can overcome the rare disease-rare data dilemma and reveal new IEM pathophysiology and potential drug targets using multiomics data in seemingly healthy populations.
Disciplines :
Genetics & genetic processes
Author, co-author :
Bender, Aaron; Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA ; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
Ranea-Robles, Pablo ; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA ; Departamento de Fisiología, Facultad de Medicina, Universidad de Granada, Centro de Investigación Biomédica, Universidad de Granada, Instituto de Investigación Biosanitaria ibs.Granada, Granada, Spain
WILLIAMS, Evan ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Gene Expression and Metabolism
Mirzaian, Mina; Department of Clinical Chemistry, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
Heimel, J Alexander; Circuits Structure and Function Group, Netherlands Institute for Neuroscience, Amsterdam, the Netherlands
Levelt, Christiaan N; Molecular Visual Plasticity Group, Netherlands Institute for Neuroscience, Amsterdam, the Netherlands
Wanders, Ronald J; Department of Clinical Chemistry and Pediatrics, Laboratory Genetic Metabolic Diseases, Emma Children's Hospital, Amsterdam UMC Location University of Amsterdam, Amsterdam, the Netherlands ; Inborn Errors of Metabolism, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam, the Netherlands
Aerts, Johannes M; Department of Medical Biochemistry, Leiden Institute of Chemistry, Leiden University, Leiden, the Netherlands
Zhu, Jun; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
Auwerx, Johan; Laboratory of Integrative and Systems Physiology, Interfaculty Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
Houten, Sander M ✱; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
Argmann, Carmen A ✱; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
✱ These authors have contributed equally to this work.
External co-authors :
yes
Language :
English
Title :
A Multiomic Network Approach to Uncover Disease Modifying Mechanisms of Inborn Errors of Metabolism.
National Institute of Diabetes and Digestive and Kidney Diseases European Research Council Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung Leona M. and Harry B. Helmsley Charitable Trust
Funding text :
Funding: This work was supported by the National Institute of Diabetes and Digestive and Kidney Diseases (R01 DK113172 and R01 DK116873), the European Research Council (ERC-AdG-787702), the Schweizerischer Nationalfonds zur Frderung der Wissenschaftlichen Forschung (31003A-179435), and the Leona M. and Harry B. Helmsley Charitable Trust. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. We acknowledge the help of the shared resource facilities at the Icahn School of Medicine at Mount Sinai (Colony Management, Real Time Polymerase Chain Reaction [qPCR], Mouse Genetics and Gene Targeting, Scientific Computing and the Genomics Core). DNA from SM/J mice was a kind gift from Dr. Weibin Shi (University of Virginia). The authors thank Simone Denis (Laboratory Genetic Metabolic Diseases) for tissue acylcarnitine analysis.This work was supported by the National Institute of Diabetes and Digestive and Kidney Diseases (R01 DK113172 and R01 DK116873), the European Research Council (ERC\u2010AdG\u2010787702), the Schweizerischer Nationalfonds zur Frderung der Wissenschaftlichen Forschung (31003A\u2010179435), and the Leona M. and Harry B. Helmsley Charitable Trust. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Funding:
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