Year: 2018
Type: article
Study design: Clinical Trial
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.
Source: Cell Systems
Authors: Brian D. Piening, Wenyu Zhou, Kévin Contrepois, Hannes Röst, Gucci Jijuan Gu Urban, Tejaswini Mishra, Blake M. Hanson, Eddy J. Bautista, Shana Leopold, Christine Y. Yeh, Daniel Spakowicz, Imon Banerjee, Cynthia Chen, Kimberly Kukurba, Dalia Perelman, Colleen Craig, Elizabeth Colbert, Denis Salins, Shannon Rego, Sunjae Lee, Cheng Zhang, Jessica Wheeler, M. Reza Sailani, Liang Liang, Charles Abbott, Mark Gerstein, Adil Mardinoglu, Ulf Smith, Daniel L. Rubin, Sharon Pitteri, Erica Sodergren, Tracey L. McLaughlin, George M. Weinstock, Michael P. Snyder
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $9,350
Funders: American Diabetes Association, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, EMBO, Vetenskapsrådet, National Institutes of Health, National Heart, Lung, and Blood Institute, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Dental and Craniofacial Research, U.S. National Library of Medicine
Awards: G1076144930, G1643758419, G183918217, High-throughput sequencer for multi-scale genomic studies, Longitudinal Multiomics Microbial Profiling in Healthy and Disease Individuals, G415725723, G5151998174, Longitudinal Multiomics Microbial Profiling in Healthy and Disease Individuals, G6616344337, Personalized longitudinal metabolomic and microbiomic profiling of diabetes progression, Personal omics profiling of the progression to diabetes mellitus type 2, G844559411, G8570322709, Biomedical Informatics and Data Science Training at Yale
OpenAlex ID: W2784691731