OBJECTIVE: To characterize the serum metabolome of a primate model of in utero high-fat exposure. STUDY DESIGN: Serum from maternal and fetal (e130) macaque monkeys exposed to either a high-fat or control diet were analyzed by gas chromatography-mass spectrometry. Multivariate data analysis was performed to reduce the generated data set. Candidate metabolites were further analyzed for significance by using the analysis of variance and comparative t tests. RESULTS: Approximately 1300 chromatographic features were detected. Through multivariate data analysis this number was reduced to 60 possible metabolites. With the use of comparative t tests, 22 metabolites had statistical significance (P < .05) over the entire study. By virtue of maternal high-fat diet alone, fetal phenotypic differences are accompanied by altered metabolite concentrations of 7 metabolites (P < .05). CONCLUSION: In utero high-fat diet exposure is associated with an altered fetal epigenome and parlays a characteristic modification in the fetal metabolite profile.
OBJECTIVE: To characterize the serum metabolome of a primate model of in utero high-fat exposure. STUDY DESIGN: Serum from maternal and fetal (e130) macaque monkeys exposed to either a high-fat or control diet were analyzed by gas chromatography-mass spectrometry. Multivariate data analysis was performed to reduce the generated data set. Candidate metabolites were further analyzed for significance by using the analysis of variance and comparative t tests. RESULTS: Approximately 1300 chromatographic features were detected. Through multivariate data analysis this number was reduced to 60 possible metabolites. With the use of comparative t tests, 22 metabolites had statistical significance (P < .05) over the entire study. By virtue of maternal high-fat diet alone, fetal phenotypic differences are accompanied by altered metabolite concentrations of 7 metabolites (P < .05). CONCLUSION: In utero high-fat diet exposure is associated with an altered fetal epigenome and parlays a characteristic modification in the fetal metabolite profile.
Authors: Nicole K MacLennan; S Jill James; Stephan Melnyk; Ali Piroozi; Stefanie Jernigan; Jennifer L Hsu; Sara M Janke; Tho D Pham; Robert H Lane Journal: Physiol Genomics Date: 2004-06-17 Impact factor: 3.107
Authors: Santosh K Bhargava; Harshpal Singh Sachdev; Caroline H D Fall; Clive Osmond; Ramakrishnan Lakshmy; David J P Barker; Sushant K Dey Biswas; Siddharth Ramji; Dorairaj Prabhakaran; Kolli Srinath Reddy Journal: N Engl J Med Date: 2004-02-26 Impact factor: 91.245
Authors: Melissa Suter; Philip Bocock; Lori Showalter; Min Hu; Cynthia Shope; Robert McKnight; Kevin Grove; Robert Lane; Kjersti Aagaard-Tillery Journal: FASEB J Date: 2010-11-19 Impact factor: 5.191
Authors: Amanda L Prince; Ryan M Pace; Tyler Dean; Diana Takahashi; Paul Kievit; Jacob E Friedman; Kjersti M Aagaard Journal: Am J Primatol Date: 2019-05-07 Impact factor: 2.371
Authors: M F Hivert; W Perng; S M Watkins; C S Newgard; L C Kenny; B S Kristal; M E Patti; E Isganaitis; D L DeMeo; E Oken; M W Gillman Journal: J Dev Orig Health Dis Date: 2015-01-29 Impact factor: 2.401
Authors: Wei Perng; Matthew W Gillman; Abby F Fleisch; Ryan D Michalek; Steven M Watkins; Elvira Isganaitis; Mary-Elizabeth Patti; Emily Oken Journal: Obesity (Silver Spring) Date: 2014-09-24 Impact factor: 5.002
Authors: Maria Theresa E Montales; Stepan B Melnyk; Shi J Liu; Frank A Simmen; Y Lucy Liu; Rosalia C M Simmen Journal: Endocr Relat Cancer Date: 2016-07-08 Impact factor: 5.678
Authors: Maxim D Seferovic; Danielle M Goodspeed; Derrick M Chu; Laura A Krannich; Pablo J Gonzalez-Rodriguez; James E Cox; Kjersti M Aagaard Journal: FASEB J Date: 2015-03-10 Impact factor: 5.191
Authors: Junjun Wang; Zhenlong Wu; Defa Li; Ning Li; Scott V Dindot; M Carey Satterfield; Fuller W Bazer; Guoyao Wu Journal: Antioxid Redox Signal Date: 2012-01-13 Impact factor: 8.401