| Literature DB >> 29361466 |
Brian D Piening1, Wenyu Zhou1, Kévin Contrepois1, Hannes Röst1, Gucci Jijuan Gu Urban2, Tejaswini Mishra1, Blake M Hanson3, Eddy J Bautista3, Shana Leopold3, Christine Y Yeh4, Daniel Spakowicz3, Imon Banerjee5, Cynthia Chen5, Kimberly Kukurba1, Dalia Perelman6, Colleen Craig6, Elizabeth Colbert6, Denis Salins1, Shannon Rego1, Sunjae Lee7, Cheng Zhang7, Jessica Wheeler1, M Reza Sailani1, Liang Liang1, Charles Abbott1, Mark Gerstein8, Adil Mardinoglu9, Ulf Smith10, Daniel L Rubin5, Sharon Pitteri11, Erica Sodergren3, Tracey L McLaughlin12, George M Weinstock13, Michael P Snyder14.
Abstract
Advances in omics technologies now allow an unprecedented level of phenotyping for human diseases, including obesity, in which individual responses to excess weight are heterogeneous and unpredictable. To aid the development of better understanding of these phenotypes, we performed a controlled longitudinal weight perturbation study combining multiple omics strategies (genomics, transcriptomics, multiple proteomics assays, metabolomics, and microbiomics) during periods of weight gain and loss in humans. Results demonstrated that: (1) weight gain is associated with the activation of strong inflammatory and hypertrophic cardiomyopathy signatures in blood; (2) although weight loss reverses some changes, a number of signatures persist, indicative of long-term physiologic changes; (3) we observed omics signatures associated with insulin resistance that may serve as novel diagnostics; (4) specific biomolecules were highly individualized and stable in response to perturbations, potentially representing stable personalized markers. Most data are available open access and serve as a valuable resource for the community.Entities:
Keywords: genomics; metabolomics; microbiome; obesity; proteomics; systems biology; type 2 diabetes
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Year: 2018 PMID: 29361466 PMCID: PMC6021558 DOI: 10.1016/j.cels.2017.12.013
Source DB: PubMed Journal: Cell Syst ISSN: 2405-4712 Impact factor: 10.304