Literature DB >> 20376050

Getting biological about the genetics of diabetes.

Christopher B Newgard1, Alan D Attie.   

Abstract

New technology has provided methods for collecting large amounts of data reflecting gene expression, metabolite and protein abundance, and post-translational modification of proteins. Integration of these various data sets enable the genetic mapping of many new phenotypes and facilitates the creation of network models that link genetic variation with intermediate traits leading to human disease. The first round of genome-wide association studies has not accounted for common human diseases to the extent that was expected. New phenotyping approaches and methods of data integration should bring these studies closer to their promised goals.

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Year:  2010        PMID: 20376050     DOI: 10.1038/nm0410-388

Source DB:  PubMed          Journal:  Nat Med        ISSN: 1078-8956            Impact factor:   53.440


  42 in total

1.  Mitochondrial overload and incomplete fatty acid oxidation contribute to skeletal muscle insulin resistance.

Authors:  Timothy R Koves; John R Ussher; Robert C Noland; Dorothy Slentz; Merrie Mosedale; Olga Ilkayeva; James Bain; Robert Stevens; Jason R B Dyck; Christopher B Newgard; Gary D Lopaschuk; Deborah M Muoio
Journal:  Cell Metab       Date:  2008-01       Impact factor: 27.287

Review 2.  Molecular networks as sensors and drivers of common human diseases.

Authors:  Eric E Schadt
Journal:  Nature       Date:  2009-09-10       Impact factor: 49.962

3.  Retinol-binding protein 4 and insulin resistance in lean, obese, and diabetic subjects.

Authors:  Timothy E Graham; Qin Yang; Matthias Blüher; Ann Hammarstedt; Theodore P Ciaraldi; Robert R Henry; Christopher J Wason; Andreas Oberbach; Per-Anders Jansson; Ulf Smith; Barbara B Kahn
Journal:  N Engl J Med       Date:  2006-06-15       Impact factor: 91.245

4.  Population-based resequencing of ANGPTL4 uncovers variations that reduce triglycerides and increase HDL.

Authors:  Stefano Romeo; Len A Pennacchio; Yunxin Fu; Eric Boerwinkle; Anne Tybjaerg-Hansen; Helen H Hobbs; Jonathan C Cohen
Journal:  Nat Genet       Date:  2007-02-25       Impact factor: 38.330

5.  A branched-chain amino acid-related metabolic signature that differentiates obese and lean humans and contributes to insulin resistance.

Authors:  Christopher B Newgard; Jie An; James R Bain; Michael J Muehlbauer; Robert D Stevens; Lillian F Lien; Andrea M Haqq; Svati H Shah; Michelle Arlotto; Cris A Slentz; James Rochon; Dianne Gallup; Olga Ilkayeva; Brett R Wenner; William S Yancy; Howard Eisenson; Gerald Musante; Richard S Surwit; David S Millington; Mark D Butler; Laura P Svetkey
Journal:  Cell Metab       Date:  2009-04       Impact factor: 27.287

6.  Agouti protein is an antagonist of the melanocyte-stimulating-hormone receptor.

Authors:  D Lu; D Willard; I R Patel; S Kadwell; L Overton; T Kost; M Luther; W Chen; R P Woychik; W O Wilkison
Journal:  Nature       Date:  1994-10-27       Impact factor: 49.962

7.  Positional cloning of the mouse obese gene and its human homologue.

Authors:  Y Zhang; R Proenca; M Maffei; M Barone; L Leopold; J M Friedman
Journal:  Nature       Date:  1994-12-01       Impact factor: 49.962

8.  Genetics meets metabolomics: a genome-wide association study of metabolite profiles in human serum.

Authors:  Christian Gieger; Ludwig Geistlinger; Elisabeth Altmaier; Martin Hrabé de Angelis; Florian Kronenberg; Thomas Meitinger; Hans-Werner Mewes; H-Erich Wichmann; Klaus M Weinberger; Jerzy Adamski; Thomas Illig; Karsten Suhre
Journal:  PLoS Genet       Date:  2008-11-28       Impact factor: 5.917

9.  Metabolomics applied to diabetes research: moving from information to knowledge.

Authors:  James R Bain; Robert D Stevens; Brett R Wenner; Olga Ilkayeva; Deborah M Muoio; Christopher B Newgard
Journal:  Diabetes       Date:  2009-11       Impact factor: 9.461

10.  Statistical methods for gene set co-expression analysis.

Authors:  YounJeong Choi; Christina Kendziorski
Journal:  Bioinformatics       Date:  2009-08-18       Impact factor: 6.937

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  13 in total

1.  Human metabolic individuality in biomedical and pharmaceutical research.

Authors:  So-Youn Shin; Ann-Kristin Petersen; Nicole Soranzo; Christian Gieger; Karsten Suhre; Robert P Mohney; David Meredith; Brigitte Wägele; Elisabeth Altmaier; Panos Deloukas; Jeanette Erdmann; Elin Grundberg; Christopher J Hammond; Martin Hrabé de Angelis; Gabi Kastenmüller; Anna Köttgen; Florian Kronenberg; Massimo Mangino; Christa Meisinger; Thomas Meitinger; Hans-Werner Mewes; Michael V Milburn; Cornelia Prehn; Johannes Raffler; Janina S Ried; Werner Römisch-Margl; Nilesh J Samani; Kerrin S Small; H-Erich Wichmann; Guangju Zhai; Thomas Illig; Tim D Spector; Jerzy Adamski
Journal:  Nature       Date:  2011-08-31       Impact factor: 49.962

Review 2.  Metabolomics and Metabolic Diseases: Where Do We Stand?

Authors:  Christopher B Newgard
Journal:  Cell Metab       Date:  2016-10-27       Impact factor: 27.287

3.  Hepatic SRC-1 activity orchestrates transcriptional circuitries of amino acid pathways with potential relevance for human metabolic pathogenesis.

Authors:  Mounia Tannour-Louet; Brian York; Ke Tang; Erin Stashi; Hichem Bouguerra; Suoling Zhou; Hui Yu; Lee-Jun C Wong; Robert D Stevens; Jianming Xu; Christopher B Newgard; Bert W O'Malley; Jean-Francois Louet
Journal:  Mol Endocrinol       Date:  2014-08-22

4.  Mechanism of amylin fibrillization enhancement by heparin.

Authors:  Suman Jha; Sharadrao M Patil; Jason Gibson; Craig E Nelson; Nathan N Alder; Andrei T Alexandrescu
Journal:  J Biol Chem       Date:  2011-05-09       Impact factor: 5.157

5.  Genetic control of obesity, glucose homeostasis, dyslipidemia and fatty liver in a mouse model of diet-induced metabolic syndrome.

Authors:  D S Sinasac; J D Riordan; S H Spiezio; B S Yandell; C M Croniger; J H Nadeau
Journal:  Int J Obes (Lond)       Date:  2015-09-18       Impact factor: 5.095

6.  Metabolic regulation of CaMKII protein and caspases in Xenopus laevis egg extracts.

Authors:  Francis McCoy; Rashid Darbandi; Si-Ing Chen; Laura Eckard; Keela Dodd; Kelly Jones; Anthony J Baucum; Jennifer A Gibbons; Sue-Hwa Lin; Roger J Colbran; Leta K Nutt
Journal:  J Biol Chem       Date:  2013-02-11       Impact factor: 5.157

Review 7.  Metabolomic profiling for the identification of novel biomarkers and mechanisms related to common cardiovascular diseases: form and function.

Authors:  Svati H Shah; William E Kraus; Christopher B Newgard
Journal:  Circulation       Date:  2012-08-28       Impact factor: 29.690

8.  Chronic kidney disease: the "perfect storm" of cardiometabolic risk illuminates genetic diathesis in cardiovascular disease.

Authors:  Dwight A Towler
Journal:  J Am Coll Cardiol       Date:  2013-05-29       Impact factor: 24.094

9.  Systems biology approach reveals genome to phenome correlation in type 2 diabetes.

Authors:  Priyanka Jain; Saurabh Vig; Malabika Datta; Dinesh Jindel; Ashok Kumar Mathur; Sandeep Kumar Mathur; Abhay Sharma
Journal:  PLoS One       Date:  2013-01-07       Impact factor: 3.240

10.  Amide proton solvent protection in amylin fibrils probed by quenched hydrogen exchange NMR.

Authors:  Andrei T Alexandrescu
Journal:  PLoS One       Date:  2013-02-15       Impact factor: 3.240

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