메뉴 건너뛰기




Volumn 10, Issue 7, 2014, Pages 566-571

New biomarkers and genes for prediction of type 2 diabetes;Neue Biomarker und Gene in der Prädiktion des Typ-2-Diabetes

Author keywords

Amino acids; Genetics; Genome wide association study; Lipids; Metabolomics

Indexed keywords

ACID; BIOLOGICAL MARKER; LIPID;

EID: 85027940171     PISSN: 18609716     EISSN: 18609724     Source Type: Journal    
DOI: 10.1007/s11428-014-1211-y     Document Type: Article
Times cited : (1)

References (31)
  • 1
    • 85028171121 scopus 로고    scopus 로고
    • IDF Diabetes Atlas, 6
    • International Diabetes Federation, Brussels:
    • International Diabetes Federation (2013) IDF Diabetes Atlas, 6. Aufl. International Diabetes Federation, Brussels
    • (2013) Aufl
  • 2
    • 84906329015 scopus 로고    scopus 로고
    • PID: 23762204
    • Rathmann W, Scheidt-Nave C, Roden M et al (2013) Type 2 diabetes: prevalence and relevance of genetic and acquired factors for its prediction. Dtsch Arztebl Int 110:331–337
    • (2013) Dtsch Arztebl Int , vol.110 , pp. 331
    • Rathmann1
  • 3
    • 33847667588 scopus 로고    scopus 로고
    • PID: 17327313
    • Schulze MB, Hoffmann K, Boeing H et al (2007) An accurate risk score based on anthropometric, dietary, and lifestyle factors to predict the development of type 2 diabetes. Diabetes Care 30:510–515
    • (2007) Diabetes Care , vol.30 , pp. 510
    • Schulze1
  • 4
    • 79960505344 scopus 로고    scopus 로고
    • PID: 21622851
    • Buijsse B, Simmons RK, Griffin SJ et al (2011) Risk assessment tools for identifying individuals at risk of developing type 2 diabetes. Epidemiol Rev 33:46–62
    • (2011) Epidemiol Rev , vol.33 , pp. 46
    • Buijsse1
  • 5
    • 84890907150 scopus 로고    scopus 로고
    • PID: 24078135, COI: 1:CAS:528:DC%2BC3sXhsFKqsb3K
    • Herder C, Kowall B, Tabak AG et al (2014) The potential of novel biomarkers to improve risk prediction of type 2 diabetes. Diabetologia 57:16–29
    • (2014) Diabetologia , vol.57 , pp. 16
    • Herder1
  • 6
    • 84904745172 scopus 로고    scopus 로고
    • PID: 24859358, COI: 1:CAS:528:DC%2BC2cXptVaks74%3D
    • Grarup N, Sandholt CH, Hansen T et al (2014) Genetic susceptibility to type 2 diabetes and obesity: from genome-wide association studies to rare variants and beyond. Diabetologia 57:1528–1541
    • (2014) Diabetologia , vol.57 , pp. 1528
    • Grarup1
  • 7
    • 84897098159 scopus 로고    scopus 로고
    • PID: 24535206, COI: 1:CAS:528:DC%2BC2cXivFygtbk%3D
    • Hivert MF, Vassy JL, Meigs JB (2014) Susceptibility to type 2 diabetes mellitus – from genes to prevention. Nat Rev Endocrinol 10:198–205
    • (2014) Nat Rev Endocrinol , vol.10 , pp. 198
    • Hivert1
  • 8
    • 84906708242 scopus 로고    scopus 로고
    • Metabolite traits and genetic risk provide complementary information for the prediction of future type 2 diabetes. Diabetes Care
    • Walford GA, Porneala BC, Dauriz M et al (2014) Metabolite traits and genetic risk provide complementary information for the prediction of future type 2 diabetes. Diabetes Care. DOI 10.2337/dc14-0560 1935-5548
    • (2014) DOI 10.2337/dc14-0560 , pp. 1935-5548
    • Walford, G.A.1    Porneala, B.C.2    Dauriz, M.3
  • 9
    • 84901298851 scopus 로고    scopus 로고
    • PID: 24296717, COI: 1:CAS:528:DC%2BC2cXhsV2ls7rM
    • Dimas AS, Lagou V, Barker A et al (2014) Impact of type 2 diabetes susceptibility variants on quantitative glycemic traits reveals mechanistic heterogeneity. Diabetes 63:2158–2171
    • (2014) Diabetes , vol.63 , pp. 2158
    • Dimas1
  • 10
    • 84868337361 scopus 로고    scopus 로고
    • PID: 22885922, COI: 1:CAS:528:DC%2BC38XhtFOgsLfP
    • Morris AP, Voight BF, Teslovich TM et al (2012) Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat Genet 44:981–990
    • (2012) Nat Genet , vol.44 , pp. 981
    • Morris1
  • 11
    • 84895858002 scopus 로고    scopus 로고
    • PID: 24464100, COI: 1:CAS:528:DC%2BC2cXht12ju7g%3D
    • Steinthorsdottir V, Thorleifsson G, Sulem P et al (2014) Identification of low-frequency and rare sequence variants associated with elevated or reduced risk of type 2 diabetes. Nat Genet 46:294–298
    • (2014) Nat Genet , vol.46 , pp. 294
    • Steinthorsdottir1
  • 12
    • 84906226932 scopus 로고    scopus 로고
    • PID: 25043022, COI: 1:CAS:528:DC%2BC2cXhtlGntLfJ
    • Moltke I, Grarup N, Jorgensen ME et al (2014) A common Greenlandic TBC1D4 variant confers muscle insulin resistance and type 2 diabetes. Nature 512:190–193
    • (2014) Nature , vol.512 , pp. 190
    • Moltke1
  • 13
    • 84890260477 scopus 로고    scopus 로고
    • PID: 24290377, COI: 1:CAS:528:DC%2BC3sXhvVKisrzK
    • Lohmueller KE, Sparso T, Li Q et al (2013) Whole-exome sequencing of 2,000 Danish individuals and the role of rare coding variants in type 2 diabetes. Am J Hum Genet 93:1072–1086
    • (2013) Am J Hum Genet , vol.93 , pp. 1072
    • Lohmueller1
  • 14
    • 84895868553 scopus 로고    scopus 로고
    • PID: 24509480, COI: 1:CAS:528:DC%2BC2cXitFanuro%3D
    • Mahajan A, Go MJ, Zhang W et al (2014) Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility. Nat Genet 46:234–239
    • (2014) Nat Genet , vol.46 , pp. 234
    • Mahajan1
  • 15
    • 84901380958 scopus 로고    scopus 로고
    • PID: 24520119, COI: 1:CAS:528:DC%2BC2cXhsV2ls7rN
    • Vassy JL, Hivert MF, Porneala B et al (2014) Polygenic type 2 diabetes prediction at the limit of common variant detection. Diabetes 63:2172–2182
    • (2014) Diabetes , vol.63 , pp. 2172
    • Vassy1
  • 17
    • 84901387060 scopus 로고    scopus 로고
    • PID: 24845081
    • Langenberg C, Sharp SJ, Franks PW et al (2014) Gene-lifestyle interaction and type 2 diabetes: the EPIC InterAct case-cohort study. PLoS Med 11:e1001647
    • (2014) PLoS Med , vol.11
    • Langenberg1
  • 18
    • 84862134307 scopus 로고    scopus 로고
    • Aschard H, Chen J, Cornelis MC et al (2012) Inclusion of gene-gene and gene-environment interactions unlikely to dramatically improve risk prediction for complex diseases. Am J Hum Genet 90:1–11
    • (2012) Am J Hum Genet , vol.90 , pp. 1
    • Aschard1
  • 19
    • 70350560562 scopus 로고    scopus 로고
    • PID: 19875619, COI: 1:CAS:528:DC%2BD1MXhsVChtrbF
    • Bain JR, Stevens RD, Wenner BR et al (2009) Metabolomics applied to diabetes research: moving from information to knowledge. Diabetes 58:2429–2443
    • (2009) Diabetes , vol.58 , pp. 2429
    • Bain1
  • 20
    • 0036007687 scopus 로고    scopus 로고
    • PID: 11860207, COI: 1:CAS:528:DC%2BD38Xht1Kqtr0%3D
    • Fiehn O (2002) Metabolomics – the link between genotypes and phenotypes. Plant Mol Biol 48:155–171
    • (2002) Plant Mol Biol , vol.48 , pp. 155
    • Fiehn1
  • 21
    • 0036463681 scopus 로고    scopus 로고
    • PID: 12120097, COI: 1:CAS:528:DC%2BD38Xhs1aksbw%3D
    • Nicholson JK, Connelly J, Lindon JC et al (2002) Metabonomics: a platform for studying drug toxicity and gene function. Nat Rev Drug Discov 1:153–161
    • (2002) Nat Rev Drug Discov , vol.1 , pp. 153
    • Nicholson1
  • 22
    • 75749134031 scopus 로고    scopus 로고
    • PID: 20037589, COI: 1:CAS:528:DC%2BD1MXhs1Skur7M
    • Illig T, Gieger C, Zhai G et al (2010) A genome-wide perspective of genetic variation in human metabolism. Nat Genet 42:137–141
    • (2010) Nat Genet , vol.42 , pp. 137
    • Illig1
  • 23
    • 80052398214 scopus 로고    scopus 로고
    • PID: 21886157, COI: 1:CAS:528:DC%2BC3MXhtFWku7nN
    • Suhre K, Shin SY, Petersen AK et al (2011) Human metabolic individuality in biomedical and pharmaceutical research. Nature 477:54–60
    • (2011) Nature , vol.477 , pp. 54
    • Suhre1
  • 24
    • 40349083852 scopus 로고    scopus 로고
    • PID: 18230739, COI: 1:CAS:528:DC%2BD1cXhvFCitrw%3D
    • Assfalg M, Bertini I, Colangiuli D et al (2008) Evidence of different metabolic phenotypes in humans. Proc Natl Acad Sci U S A 105:1420–1424
    • (2008) Proc Natl Acad Sci U S A , vol.105 , pp. 1420
    • Assfalg1
  • 25
    • 79951892537 scopus 로고    scopus 로고
    • PID: 21359215, COI: 1:CAS:528:DC%2BC3MXislChurs%3D
    • Psychogios N, Hau DD, Peng J et al (2011) The human serum metabolome. PLoS One 6:e16957
    • (2011) PLoS One , vol.6 , pp. e16957
    • Psychogios1
  • 26
    • 59449097019 scopus 로고    scopus 로고
    • PID: 19147747, COI: 1:CAS:528:DC%2BD1MXlvFeksw%3D%3D
    • Spratlin JL, Serkova NJ, Eckhardt SG (2009) Clinical applications of metabolomics in oncology: a review. Clin Cancer Res 15:431–440
    • (2009) Clin Cancer Res , vol.15 , pp. 431
    • Spratlin1
  • 27
    • 78649735772 scopus 로고    scopus 로고
    • PID: 21085649
    • Suhre K, Meisinger C, Döring et al (2010) Metabolic footprint of diabetes: a multiplatform metabolomics study in an epidemiological setting. PLoS One 5:e13953
    • (2010) PLoS One , vol.5 , pp. e13953
    • Suhre1
  • 28
    • 79953737332 scopus 로고    scopus 로고
    • PID: 21423183
    • Wang TJ, Larson MG, Vasan RS et al (2011) Metabolite profiles and the risk of developing diabetes. Nat Med 17:448–453
    • (2011) Nat Med , vol.17 , pp. 448
    • Wang1
  • 29
    • 84874412069 scopus 로고    scopus 로고
    • PID: 23129134
    • Würtz P, Soininen P, Kangas AJ et al (2013) Branched-chain and aromatic amino acids are predictors of insulin resistance in young adults. Diabetes Care 36:648–655
    • (2013) Diabetes Care , vol.36 , pp. 648
    • Würtz1
  • 30
    • 84867012919 scopus 로고    scopus 로고
    • PID: 23010998
    • Wang-Sattler R, Yu Z, Herder C et al (2012) Novel biomarkers for pre-diabetes identified by metabolomics. Mol Syst Biol 8:615
    • (2012) Mol Syst Biol , vol.8 , pp. 615
    • Wang-Sattler1
  • 31
    • 84873042769 scopus 로고    scopus 로고
    • PID: 23043162, COI: 1:CAS:528:DC%2BC3sXhvFOnsLg%3D
    • Floegel A, Stefan N, Yu Z et al (2013) Identification of serum metabolites associated with risk of type 2 diabetes using a targeted metabolomic approach. Diabetes 62:639–648
    • (2013) Diabetes , vol.62 , pp. 639
    • Floegel1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.