Personalisierte Adipositas-Prävention PAP-MV2022   
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  Externe Publikationen
  • Calle EE, Rodriguez C, Walker-Thurmond K, Thun MJ. Overweight, obesity, and mortality from cancer in a prospectively studied cohort of U.S.adults. N Engl J Med. 2003; 348(17):1625-38.
  • Mokdad AH, Ford ES, Bowman BA, Dietz WH, Vinicor F, Bales VS, Marks JS. Prevalence of obesity, diabetes, and obesity-related health riskfactors, 2001.JAMA. 2003; 289(1):76-9.
  • Speakman JR. If body fatness is under physiological regulation, then how come we have an obesity epidemic? Physiology (Bethesda).2014;29(2):88-98.
  • Do DN, Strathe AB, Jensen J, Mark T, Kadarmideen HN. Genetic parameters for different measures of feed efficiency and related traits in boars of three pig breeds. J Anim Sci 2013; 91: 4069-4079.
  • Ogden CL., Kit BK, Fakhouri THI, Carroll MD, Flegal KM. in GI Epidemiology 2014; 394-404; John Wiley & Sons, Ltd, 2014.
  • van der Klaauw AA, Farooqi IS. The Hunger Genes: Pathways to Obesity. Cell 2015; 161: 119-132.
  • Walley A J, Asher J E, Froguel P. The genetic contribution to non-syndromic human obesity. Nat Rev Genet 2009; 10: 431-442.
  • World Health Organization. Fact sheet: Obesity and Overweight. Available at: mediacentre / factsheets /fs311/en/.Accessed Oct 2017.
  • Yazdi FT, Clee SM, Meyre D. Obesity genetics in mouse and human: back and forth, and back again. PeerJ 2015; 3: e856.
  • Yang J, Bakshi A, Zhu Z, Hemani G, Vinkhuyzen AA, Lee SH, Robinson MR, Perry JR, Nolte IM, van Vliet-Ostaptchouk JV, Snieder H; LifeLinesCohort Study, Esko T, Milani L, Mägi R, Metspalu A, Hamsten A, Magnusson PK, Pedersen NL, Ingelsson E, Soranzo N, Keller MC, Wray NR, Goddard ME, Visscher PM. Genetic variance estimation with imputed variants finds negligible missing heritability for human height and bodymass index. Nat Genet 2015; 47: 1114-1120
  • Moro T et. al, Effects of eight weeks of time-restricted feeding (16/8) on basal metabolism, maximal strength, body composition, inflammation, and cardiovascular risk factors in resistance-trained males. J Transl Med. 2016;14(1):290.
  • Payne AN, Chassard C, Lacroix C. Gut microbial adaptation to dietary consumption of fructose, artificial sweeteners and sugar alcohols: implications for host-microbe interactions contributing to obesity. Obes Rev. 2012;13(9):799-809.
  • Grundberg E, Meduri E, Sandling JK, Hedman AK, Keildson S, Buil A, Busche S, Yuan W, Nisbet J, Sekowska M, Wilk A, Barrett A, Small KS, GeB, Caron M, Shin SY, Multiple Tissue Human Expression Resource Consortium, Lathrop M, Dermitzakis ET, McCarthy MI, Spector TD, Bell JT,Deloukas P. Global analysis of DNA methylation variation in adipose tissue from twins reveals links to disease-associated variants in distal regulatory elements. Am J Hum Genet 2013; 93(5):876-90
  • Hales CN, Barker DJ. Type 2 (non-insulin-dependent) diabetes mellitus: the thrifty phenotype hypothesis. Diabetologia 1992; 35: 595-601.
  • Heyn H, Moran S, Hernando-Herraez I, Sayols S, Gomez A, Sandoval J, Monk D, Hata K, Marques-Bonet T, Wang L, Esteller M. DNA methylation contributes to natural human variation. Genome Res 2013; 23(9):1363-72
  • Junien C. Impact of diets and nutrients/drugs on early epigenetic programming. JIMD 2006; 29: 359-65.
  • Lillycrop KA, Phillips ES, Jackson AA, Hanson MA, Burdge GC. Dietary protein restriction of pregnant rats induces and folic acid supplementation prevents epigenetic modification of hepatic gene expression in the offspring. J Nutrition 2005; 135:1382-86.
  • Richards EJ. Inheritedepigeneticvariation-revisiting soft inheritance. Nat Rev Genet 2006; 7(5):395-401.
  • Slatkin M. Epigenetic Inheritance and the Missing Heritability Problem. Genetics 2009; 182: 845-50
  • Wu G, Bazer F, Wallace J, Spencer T. Board-invited review: intrauterine growth retardation: implications for the animal sciences. J Anim Sci2006; 84: 2316-37.
  • Camarinha-Silva A, Maushammer M, Wellmann R, Vital M, Preuss S, Bennewitz J. Host Genome Influence on Gut Microbial Composition and Microbial Prediction of Complex Traits in Pigs. Genetics. 2017;206(3):1637-44.
  • Graf D, Di Cagno R, Fak F, et al. Contribution of diet to the composition of the human gut microbiota. Microb Ecol Health Dis. 2015;26:10.3402/mehd.v26.26164.
  • Mohan M, Chow CT, Ryan CN, Chan LS, Dufour J, Aye PP, Blanchard J, Moehs CP Sestak K. 2016. Dietary Gluten-Induced Gut Dysbiosis Is Accompanied by Selective Upregulation of microRNAs with Intestinal Tight Junction and Bacteria-Binding Motifs in Rhesus Macaque Model of Celiac Disease. Nutrients 8, E684.
  • Shen TD. Diet and Gut Microbiota in Health and Disease. NestlĂ© Nutr Inst Workshop Ser. 2017;88: 117-126.
  • Aten JE, Fuller TF, Lusis AJ, Horvath S Using genetic markers to orient the edges in quantitative trait networks: the NEO software. BMC Systems Biology 2008; 2, 34.
  • Dalgaard K. et al, (2016): Trim28 Haploinsufficiency Triggers Bi-stable Epigenetic Obesity. Cell, 164(3), 353-64.
  • Doerge RW. Mapping and analysis of quantitative trait loci in experimental populations. Nat Rev Genet 2002; 3:43-52.
  • ENCODE Project Consortium. The ENCODE (ENCyclopedia Of DNA Elements) Project. Science. 2004; 306(5696):636-40.
  • FAANG Consortium. Coordinated international action to accelerate genome-to-phenome with FAANG, the Functional Annotation of Animal Genomes project. Genome Biology 2015 16: 57.
  • Hayes BJ, Visscher PM, Goddard ME. Increased accuracy of artificial selection by using the realized relationship matrix. Genet Res 2009; 91: 47-60
  • Jansen RC, Nap JP. Genetical genomics: the added value from segregation. Trends Genet 2001;17:388-91.
  • Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinforma2008; 9, 559.
  • Luo W, Brouwer C. Pathview: an R/Bioconductor package for pathway-based data integration and visualization. Bioinformatics 2013;, btt285.
  • Ponsuksili S, Du Y, Hadlich F, Siengdee P, Murani E, Schwerin M, Wimmers K. Correlated mRNAs and miRNAs from co-expression and regulatory networks affect porcine muscle and finally meat properties. BMC Genomics 2013; 14, 533.
  • Ponsuksili S, Du Y, Murani E, Schwerin M, Wimmers K. Elucidating molecular networks that either affect or respond to plasma cortisol concentration in target tissues of liver and muscle. Genetics 2012; 192, 1109-22.
  • Ponsuksili S, Murani E, Brand B, Schwerin M, Wimmers K. Integrating expression profiling and whole-genome association for dissection of fat traits in a porcine model. J Lipid Res 2011; 52, 668-78.
  • Ponsuksili S, Murani E, Trakooljul N, Schwerin M, Wimmers K. Discovery of candidate genes for muscle traits based on GWAS supported by eQTL-analysis. Int J Biol Sci 2014; 10, 327-37.
  • Ponsuksili S, Zebunke M, Murani E, Trakooljul N, Krieter J, Puppe B, Schwerin M, Wimmers K. Integrated Genome-wide association and hypothalamus eQTL studies indicate a link between the circadian rhythm-related gene PER1 and coping behavior. Sci Rep 2015; 5, 16264.
  • Teslaa T, Teitell MA. Pluripotent stem cell energy metabolism: an update. EMBO J. 2015; 34(2):138-53.
  • Costa, P. T. McCrae, R. R.(1992). Revised NEO Personality inventory and NEO five-factor inventory (Professional Manual). Odessa: Psychological Assessment Resources.
  • Konturek PC, Konturek JW, Czenikiewicz-Guzik M, Brzozowski T, Sito E, Konturek SJ. Neuro-hormonal control of food intake: basic mechanisms and clinical implications. J Physiol Pharmacol. 2005; 56 Suppl 6:5-25.
  • Walter Mischel: The Marshmallow Test: Mastering Self-Control, Little Brown, New York 2014, ISBN 0316230855
  • Kanfer, F.H. & Saslow, G. Behavioral Analysis: An alternative to diagnostic classification. ArchGen Psychiatry 1974; 12, 529-38.
  • de Lucia C, Murphy T, Thuret S. Emerging Molecular Pathways Governing Dietary Regulation of Neural Stem Cells during Aging. Front Physiol. 2017
  • Aksu S, Koczan D, Renne U, Thiesen HJ, Brockmann GA. Differentially expressed genes in adipose tissues of high body weight-selected (obese) and unselected (lean) mouse lines. J Appl Genet. 2007;48(2):133-43. PMID: 17495347