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Integrative Personal Omics Profiles during Periods of Weight Gain and Loss

Journal article
Authors B. D. Piening
W. Y. Zhou
K. Contrepois
H. Rost
G. J. G. Urban
T. Mishra
B. M. Hanson
E. J. Bautista
S. Leopold
C. Y. Yeh
D. Spakowicz
I. Banerjee
C. Chen
K. Kukurba
D. Perelman
C. Craig
E. Colbert
D. Salins
S. Rego
S. Lee
C. Zhang
J. Wheeler
M. R. Sailani
L. Liang
C. Abbott
M. Gerstein
A. Mardinoglu
Ulf Smith
D. L. Rubin
S. Pitteri
E. Sodergren
T. L. McLaughlin
G. M. Weinstock
M. P. Snyder
Published in Cell Systems
Volume 6
Issue 2
Pages 157-170.e8
ISSN 2405-4712
Publication year 2018
Published at Institute of Medicine, Department of Molecular and Clinical Medicine
Pages 157-170.e8
Language en
Links doi.org/10.1016/j.cels.2017.12.013
Keywords high-fat diet, mediated glucose disposal, insulin suppression test, adipose-cell size, large gene lists, gut microbiota, subclinical, inflammation, akkermansia-muciniphila, oxalobacter-formigenes, metabolic, syndrome, Biochemistry & Molecular Biology, Cell Biology
Subject categories Biochemistry and Molecular Biology, Cell Biology

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.

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