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Genetic variation in insulin‐induced kinase signaling

dc.contributor.authorWang, Isabel Xiaorongen_US
dc.contributor.authorRamrattan, Girishen_US
dc.contributor.authorCheung, Vivian Gen_US
dc.date.accessioned2015-08-05T16:47:07Z
dc.date.available2016-08-08T16:18:38Zen
dc.date.issued2015-07en_US
dc.identifier.citationWang, Isabel Xiaorong; Ramrattan, Girish; Cheung, Vivian G (2015). "Genetic variation in insulin‐induced kinase signaling." Molecular Systems Biology (7): n/a-n/a.en_US
dc.identifier.issn1744-4292en_US
dc.identifier.issn1744-4292en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/112224
dc.description.abstractIndividual differences in sensitivity to insulin contribute to disease susceptibility including diabetes and metabolic syndrome. Cellular responses to insulin are well studied. However, which steps in these response pathways differ across individuals remains largely unknown. Such knowledge is needed to guide more precise therapeutic interventions. Here, we studied insulin response and found extensive individual variation in the activation of key signaling factors, including ERK whose induction differs by more than 20‐fold among our subjects. This variation in kinase activity is propagated to differences in downstream gene expression response to insulin. By genetic analysis, we identified cis‐acting DNA variants that influence signaling response, which in turn affects downstream changes in gene expression and cellular phenotypes, such as protein translation and cell proliferation. These findings show that polymorphic differences in signal transduction contribute to individual variation in insulin response, and suggest kinase modulators as promising therapeutics for diseases characterized by insulin resistance.SynopsisGenetic variants contribute to individual variation in insulin response, including kinase activation, changes in gene expression and cell growth, suggesting kinase modulators as promising therapeutics for diseases characterized by insulin resistance.Extensive individual variation is observed in insulin‐induced activation of signal transduction.The variation in signaling response is propagated downstream to influence gene expression and cell growth.There is a genetic component to the individual differences in signaling and gene expression response to insulin.Genetic variants contribute to individual variation in insulin response, including kinase activation, changes in gene expression and cell growth, suggesting kinase modulators as promising therapeutics for diseases characterized by insulin resistance.en_US
dc.publisherInternational Diabetes Federationen_US
dc.publisherWiley Periodicals, Inc.en_US
dc.subject.othersignal transductionen_US
dc.subject.othertype 2 diabetesen_US
dc.subject.otherinsulin responseen_US
dc.subject.otherindividual variationen_US
dc.subject.otherDNA variantsen_US
dc.titleGenetic variation in insulin‐induced kinase signalingen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelMolecular, Cellular and Developmental Biologyen_US
dc.subject.hlbtoplevelHealth Sciencesen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/112224/1/msb156250-sup-0001-EVFigs.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/112224/2/msb156250.reviewer_comments.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/112224/3/msb156250.pdf
dc.identifier.doi10.15252/msb.20156250en_US
dc.identifier.sourceMolecular Systems Biologyen_US
dc.identifier.citedreferencePollin TI, Damcott CM, Shen H, Ott SH, Shelton J, Horenstein RB, Post W, McLenithan JC, Bielak LF, Peyser PA, Mitchell BD, Miller M, O'Connell JR, Shuldiner AR ( 2008 ) A null mutation in human APOC3 confers a favorable plasma lipid profile and apparent cardioprotection. Science 322: 1702 – 1705en_US
dc.identifier.citedreferenceKislinger T, Cox B, Kannan A, Chung C, Hu P, Ignatchenko A, Scott MS, Gramolini AO, Morris Q, Hallett MT, Rossant J, Hughes TR, Frey B, Emili A ( 2006 ) Global survey of organ and organelle protein expression in mouse: combined proteomic and transcriptomic profiling. Cell 125: 173 – 186en_US
dc.identifier.citedreferenceLi WW, Dammerman MM, Smith JD, Metzger S, Breslow JL, Leff T ( 1995 ) Common genetic variation in the promoter of the human apo CIII gene abolishes regulation by insulin and may contribute to hypertriglyceridemia. J Clin Invest 96: 2601 – 2605en_US
dc.identifier.citedreferenceMa XM, Yoon S‐O, Richardson CJ, Jülich K, Blenis J ( 2008 ) SKAR links Pre‐mRNA splicing to mTOR/S6K1‐mediated enhanced translation efficiency of spliced mRNAs. Cell 133: 303 – 313en_US
dc.identifier.citedreferenceMarcheva B, Ramsey KM, Buhr ED, Kobayashi Y, Su H, Ko CH, Ivanova G, Omura C, Mo S, Vitaterna MH, Lopez JP, Philipson LH, Bradfield CA, Crosby SD, JeBailey L, Wang X, Takahashi JS, Bass J ( 2010 ) Disruption of the clock components CLOCK and BMAL1 leads to hypoinsulinaemia and diabetes. Nature 466: 627 – 631en_US
dc.identifier.citedreferenceMelmed S, Polonsky KS, Larsen PR, Kronenberg HM ( 2011 ) Williams Textbook of Endocrinology, 12 th edn. Philadelphia, PA: Saunders Elsevieren_US
dc.identifier.citedreferenceNyholt DR ( 2004 ) A simple correction for multiple testing for single‐nucleotide polymorphisms in linkage disequilibrium with each other. Am J Hum Genet 74: 765 – 769en_US
dc.identifier.citedreferenceOng S‐E, Blagoev B, Kratchmarova I, Kristensen DB, Steen H, Pandey A, Mann M ( 2002 ) Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol Cell Proteomics 1: 376 – 386en_US
dc.identifier.citedreferencePorter KE, Turner NA ( 2009 ) Cardiac fibroblasts: at the heart of myocardial remodeling. Pharmacol Ther 123: 255 – 278en_US
dc.identifier.citedreferencePrudente S, Morini E, Trischitta V ( 2009 ) Insulin signaling regulating genes:effect on T2DM and cardiovascular risk. Nat Rev Endocrinol 5: 682 – 693en_US
dc.identifier.citedreferencePurcell S, Neale B, Todd‐Brown K, Thomas L, Ferreira MAR, Bender D, Maller J, Sklar P, de Bakker PIW, Daly MJ, Sham PC ( 2007 ) PLINK: a tool set for whole‐genome association and population‐based linkage analyses. Am J Hum Genet 81: 559 – 575en_US
dc.identifier.citedreferenceSamii A, Lopez‐Devine J, Wasserman EM, Dalakas MC, Clark K, Grafman J, Hallett M ( 1998 ) Normal postexercise facilitation and depression of motor evoked potentials in postpolio patients. Muscle Nerve 21: 948 – 950en_US
dc.identifier.citedreferenceSchilling EE, Rechler MM, Grunfeld C, Rosenberg AM ( 1979 ) Primary defect of insulin receptors in skin fibroblasts cultured from an infant with leprechaunism and insulin resistance. Proc Natl Acad Sci USA 76: 5877 – 5881en_US
dc.identifier.citedreferenceSmigielski EM, Sirotkin K, Ward M, Sherry ST ( 2000 ) dbSNP: a database of single nucleotide polymorphisms. Nucleic Acids Res 28: 352 – 355en_US
dc.identifier.citedreferenceSmirnov DA, Morley M, Shin E, Spielman RS, Cheung VG ( 2009 ) Genetic analysis of radiation‐induced changes in human gene expression. Nature 459: 587 – 591en_US
dc.identifier.citedreferenceTaylor SI, Roth J, Blizzard RM, Elders MJ ( 1981 ) Qualitative abnormalities in insulin binding in a patient with extreme insulin resistance: decreased sensitivity to alterations in temperature and pH. Proc Natl Acad Sci USA 78: 7157 – 7161en_US
dc.identifier.citedreferenceTurek FW, Joshu C, Kohsaka A, Lin E, Ivanova G, McDearmon E, Laposky A, Losee‐Olson S, Easton A, Jensen DR, Eckel RH, Takahashi JS, Bass J ( 2005 ) Obesity and metabolic syndrome in circadian Clock mutant mice. Science 308: 1043 – 1045en_US
dc.identifier.citedreferenceVoight BF, Scott LJ, Steinthorsdottir V, Morris AP, Dina C, Welch RP, Zeggini E, Huth C, Aulchenko YS, Thorleifsson G, McCulloch LJ, Ferreira T, Grallert H, Amin N, Wu G, Willer CJ, Raychaudhuri S, McCarroll SA, Langenberg C, Hofmann OM et al ( 2010 ) Twelve type 2 diabetes susceptibility loci identified through large‐scale association analysis. Nat Genet 42: 579 – 589en_US
dc.identifier.citedreferenceWeber F, Hung H‐C, Maurer C, Kay SA ( 2006 ) Second messenger and Ras/MAPK signalling pathways regulate CLOCK/CYCLE‐dependent transcription. J Neurochem 98: 248 – 257en_US
dc.identifier.citedreferenceWu JJ, Roth RJ, Anderson EJ, Hong E‐G, Lee M‐K, Choi CS, Neufer PD, Shulman GI, Kim JK, Bennett AM ( 2006 ) Mice lacking MAP kinase phosphatase‐1 have enhanced MAP kinase activity and resistance to diet‐induced obesity. Cell Metab 4: 61 – 73en_US
dc.identifier.citedreferenceZeggini E, Scott LJ, Saxena R, Voight BF, Marchini JL, Hu T, de Bakker PIW, Abecasis GR, Almgren P, Andersen G, Ardlie K, Boström KB, Bergman RN, Bonnycastle LL, Borch‐Johnsen K, Burtt NP, Chen H, Chines PS, Daly MJ, Deodhar P et al ( 2008 ) Meta‐analysis of genome‐wide association data and large‐scale replication identifies additional susceptibility loci for type 2 diabetes. Nat Genet 40: 638 – 645en_US
dc.identifier.citedreferenceZhao L, Gregoire F, Sul HS ( 2000 ) Transient induction of ENC‐1, a Kelch‐related actin‐binding protein, is required for adipocyte differentiation. J Biol Chem 275: 16845 – 16850en_US
dc.identifier.citedreferenceZhou G, Myers R, Li Y, Chen Y, Shen X, Fenyk‐Melody J, Wu M, Ventre J, Doebber T, Fujii N, Musi N, Hirshman MF, Goodyear LJ, Moller DE ( 2001 ) Role of AMP‐activated protein kinase in mechanism of metformin action. J Clin Invest 108: 1167 – 1174en_US
dc.identifier.citedreferenceAalto‐Setälä K, Fisher EA, Chen X, Chajek‐Shaul T, Hayek T, Zechner R, Walsh A, Ramakrishnan R, Ginsberg HN, Breslow JL ( 1992 ) Mechanism of hypertriglyceridemia in human apolipoprotein (apo) CIII transgenic mice. Diminished very low density lipoprotein fractional catabolic rate associated with increased apo CIII and reduced apo E on the particles. J Clin Invest 90: 1889 – 1900en_US
dc.identifier.citedreferenceArcidiacono B, Iiritano S, Nocera A, Possidente K, Nevolo MT, Ventura V, Foti D, Chiefari E, Brunetti A ( 2012 ) Insulin resistance and cancer risk: an overview of the pathogenetic mechanisms. J Diabetes Res 2012: e789174en_US
dc.identifier.citedreferenceAshburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel‐Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G ( 2000 ) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25: 25 – 29en_US
dc.identifier.citedreferenceBorisov N, Aksamitiene E, Kiyatkin A, Legewie S, Berkhout J, Maiwald T, Kaimachnikov NP, Timmer J, Hoek JB, Kholodenko BN ( 2009 ) Systems‐level interactions between insulin–EGF networks amplify mitogenic signaling. Mol Syst Biol 5: 256en_US
dc.identifier.citedreferenceBost F, Aouadi M, Caron L, Binétruy B ( 2005 ) The role of MAPKs in adipocyte differentiation and obesity. Biochimie 87: 51 – 56en_US
dc.identifier.citedreferenceBouatia‐Naji N, Rocheleau G, Van Lommel L, Lemaire K, Schuit F, Cavalcanti‐Proença C, Marchand M, Hartikainen A‐L, Sovio U, De Graeve F, Rung J, Vaxillaire M, Tichet J, Marre M, Balkau B, Weill J, Elliott P, Jarvelin M‐R, Meyre D, Polychronakos C et al ( 2008 ) A polymorphism within the G6PC2 gene is associated with fasting plasma glucose levels. Science 320: 1085 – 1088en_US
dc.identifier.citedreferenceBoulton TG, Nye SH, Robbins DJ, Ip NY, Radziejewska E, Morgenbesser SD, DePinho RA, Panayotatos N, Cobb MH, Yancopoulos GD ( 1991 ) ERKs: a family of protein‐serine/threonine kinases that are activated and tyrosine phosphorylated in response to insulin and NGF. Cell 65: 663 – 675en_US
dc.identifier.citedreferenceBurgering BM, Coffer PJ ( 1995 ) Protein kinase B (c‐Akt) in phosphatidylinositol‐3‐OH kinase signal transduction. Nature 376: 599 – 602en_US
dc.identifier.citedreferenceCarlson LA, Ballantyne D ( 1976 ) Changing relative proportions of apolipoproteins CII and CIII of very low density lipoproteins in hypertriglyceridaemia. Atherosclerosis 23: 563 – 568en_US
dc.identifier.citedreferenceChen M, Breslow JL, Li W, Leff T ( 1994 ) Transcriptional regulation of the apoC‐III gene by insulin in diabetic mice: correlation with changes in plasma triglyceride levels. J Lipid Res 35: 1918 – 1924en_US
dc.identifier.citedreferenceCheung VG, Spielman RS ( 2009 ) Genetics of human gene expression: mapping DNA variants that influence gene expression. Nat Rev Genet 10: 595 – 604en_US
dc.identifier.citedreferenceCiardiello F, Caputo R, Bianco R, Damiano V, Pomatico G, De Placido S, Bianco AR, Tortora G ( 2000 ) Antitumor effect and potentiation of cytotoxic drugs activity in human cancer cells by ZD‐1839 (Iressa), an epidermal growth factor receptor‐selective tyrosine kinase inhibitor. Clin Cancer Res 6: 2053 – 2063en_US
dc.identifier.citedreferenceClausen JO, Borch‐Johnsen K, Ibsen H, Bergman RN, Hougaard P, Winther K, Pedersen O ( 1996 ) Insulin sensitivity index, acute insulin response, and glucose effectiveness in a population‐based sample of 380 young healthy Caucasians. Analysis of the impact of gender, body fat, physical fitness, and life‐style factors. J Clin Invest 98: 1195en_US
dc.identifier.citedreferenceConejo R, Lorenzo M ( 2001 ) Insulin signaling leading to proliferation, survival, and membrane ruffling in C2C12 myoblasts. J Cell Physiol 187: 96 – 108en_US
dc.identifier.citedreferenceCox J, Mann M ( 2008 ) MaxQuant enables high peptide identification rates, individualized p.p.b.‐range mass accuracies and proteome‐wide protein quantification. Nat Biotechnol 26: 1367 – 1372en_US
dc.identifier.citedreferenceCox J, Matic I, Hilger M, Nagaraj N, Selbach M, Olsen JV, Mann M ( 2009 ) A practical guide to the MaxQuant computational platform for SILAC‐based quantitative proteomics. Nat Protoc 4: 698 – 705en_US
dc.identifier.citedreferenceDe Godoy LMF, Olsen JV, Cox J, Nielsen ML, Hubner NC, Fröhlich F, Walther TC, Mann M ( 2008 ) Comprehensive mass‐spectrometry‐based proteome quantification of haploid versus diploid yeast. Nature 455: 1251 – 1254en_US
dc.identifier.citedreferenceDIAbetes Genetics Replication And Meta‐analysis (DIAGRAM) Consortium, Asian Genetic Epidemiology Network Type 2 Diabetes (AGEN‐T2D) Consortium, South Asian Type 2 Diabetes (SAT2D) Consortium, Mexican American Type 2 Diabetes (MAT2D) Consortium, Type 2 Diabetes Genetic Exploration by Next‐generation sequencing in multi‐Ethnic Samples (T2D‐GENES) Consortium, Mahajan A, Go MJ, Zhang W, Below JE, Gaulton KJ, Ferreira T, Horikoshi M, Johnson AD, Ng MCY, Prokopenko I, Saleheen D, Wang X, Zeggini E, Abecasis GR, Adair LS et al ( 2014 ) Genome‐wide trans‐ancestry meta‐analysis provides insight into the genetic architecture of type 2 diabetes susceptibility. Nat Genet 46: 234 – 244en_US
dc.identifier.citedreferenceDrong AW, Lindgren CM, McCarthy MI ( 2012 ) The genetic and epigenetic basis of type 2 diabetes and obesity. Clin Pharmacol Ther 92: 707 – 715en_US
dc.identifier.citedreferenceDruker BJ, Tamura S, Buchdunger E, Ohno S, Segal GM, Fanning S, Zimmermann J, Lydon NB ( 1996 ) Effects of a selective inhibitor of the Abl tyrosine kinase on the growth of Bcr‐Abl positive cells. Nat Med 2: 561 – 566en_US
dc.identifier.citedreferenceDunaif A, Xia J, Book CB, Schenker E, Tang Z ( 1995 ) Excessive insulin receptor serine phosphorylation in cultured fibroblasts and in skeletal muscle. A potential mechanism for insulin resistance in the polycystic ovary syndrome. J Clin Invest 96: 801 – 810en_US
dc.identifier.citedreferenceDurand J, Lampron A, Mazzuco TL, Chapman A, Bourdeau I ( 2011 ) Characterization of differential gene expression in adrenocortical tumors harboring β‐catenin (CTNNB1) mutations. J Clin Endocrinol Metab 96: E1206 – E1211en_US
dc.identifier.citedreferenceEckardt K, May C, Koenen M, Eckel J ( 2007 ) IGF‐1 receptor signalling determines the mitogenic potency of insulin analogues in human smooth muscle cells and fibroblasts. Diabetologia 50: 2534 – 2543en_US
dc.identifier.citedreferenceEngelman JA, Luo J, Cantley LC ( 2006 ) The evolution of phosphatidylinositol 3‐kinases as regulators of growth and metabolism. Nat Rev Genet 7: 606 – 619en_US
dc.identifier.citedreferenceFavata MF, Horiuchi KY, Manos EJ, Daulerio AJ, Stradley DA, Feeser WS, Van Dyk DE, Pitts WJ, Earl RA, Hobbs F, Copeland RA, Magolda RL, Scherle PA, Trzaskos JM ( 1998 ) Identification of a novel inhibitor of mitogen‐activated protein kinase kinase. J Biol Chem 273: 18623 – 18632en_US
dc.identifier.citedreferenceFrittitta L, Spampinato D, Solini A, Nosadini R, Goldfine ID, Vigneri R, Trischitta V ( 1998 ) Elevated PC‐1 content in cultured skin fibroblasts correlates with decreased in vivo and in vitro insulin action in nondiabetic subjects: evidence that PC‐1 may be an intrinsic factor in impaired insulin receptor signaling. Diabetes 47: 1095 – 1100en_US
dc.identifier.citedreferenceFujita M, Furukawa Y, Tsunoda T, Tanaka T, Ogawa M, Nakamura Y ( 2001 ) Up‐regulation of the ectodermal‐neural cortex 1 (ENC1) gene, a downstream target of the beta‐catenin/T‐cell factor complex, in colorectal carcinomas. Cancer Res 61: 7722 – 7726en_US
dc.identifier.citedreferenceGinsberg HN, Le NA, Goldberg IJ, Gibson JC, Rubinstein A, Wang‐Iverson P, Norum R, Brown WV ( 1986 ) Apolipoprotein B metabolism in subjects with deficiency of apolipoproteins CIII and AI. Evidence that apolipoprotein CIII inhibits catabolism of triglyceride‐rich lipoproteins by lipoprotein lipase in vivo. J Clin Invest 78: 1287 – 1295en_US
dc.identifier.citedreferenceGunton JE, Sisavanh M, Stokes RA, Satin J, Satin LS, Zhang M, Liu SM, Cai W, Cheng K, Cooney GJ, Laybutt DR, So T, Molero J‐C, Grey ST, Andres DA, Rolph MS, Mackay CR ( 2012 ) Mice deficient in GEM GTPase show abnormal glucose homeostasis due to defects in beta‐cell calcium handling. PLoS ONE 7: e39462en_US
dc.identifier.citedreferenceGygi SP, Rochon Y, Franza BR, Aebersold R ( 1999 ) Correlation between protein and mRNA abundance in yeast. Mol Cell Biol 19: 1720 – 1730en_US
dc.identifier.citedreferenceHammarsund M, Lerner M, Zhu C, Merup M, Jansson M, Gahrton G, Kluin‐Nelemans H, Einhorn S, Grandér D, Sangfelt O, Corcoran M ( 2004 ) Disruption of a novel ectodermal neural cortex 1 antisense gene, ENC‐1AS and identification of ENC‐1 overexpression in hairy cell leukemia. Hum Mol Genet 13: 2925 – 2936en_US
dc.identifier.citedreferenceHansen T, Andersen CB, Echwald SM, Urhammer SA, Clausen JO, Vestergaard H, Owens D, Hansen L, Pedersen O ( 1997 ) Identification of a common amino acid polymorphism in the p85alpha regulatory subunit of phosphatidylinositol 3‐kinase: effects on glucose disappearance constant, glucose effectiveness, and the insulin sensitivity index. Diabetes 46: 494 – 501en_US
dc.identifier.citedreferenceInternational Diabetes Federation ( 2013 ) IDF Diabetes Atlas, 6 th edn. Brussels, Belgium: International Diabetes Federationen_US
dc.identifier.citedreferenceIto Y, Azrolan N, O'Connell A, Walsh A, Breslow JL ( 1990 ) Hypertriglyceridemia as a result of human apo CIII gene expression in transgenic mice. Science 249: 790 – 793en_US
dc.identifier.citedreferenceJiao P, Feng B, Li Y, He Q, Xu H ( 2013 ) Hepatic ERK activity plays a role in energy metabolism. Mol Cell Endocrinol 375: 157 – 166en_US
dc.identifier.citedreferenceKim Y‐B, Ciaraldi TP, Kong A, Kim D, Chu N, Mohideen P, Mudaliar S, Henry   RR, Kahn BB ( 2002 ) Troglitazone but not metformin restores insulin‐stimulated phosphoinositide 3‐kinase activity and increases p110beta protein levels in skeletal muscle of type 2 diabetic subjects. Diabetes 51: 443 – 448en_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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