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Systems Nutrigenomics Reveals Brain Gene Networks Linking Metabolic and Brain Disorders

Authors :
Qingying Meng
Zhe Ying
Emily Noble
Yuqi Zhao
Rahul Agrawal
Andrew Mikhail
Yumei Zhuang
Ethika Tyagi
Qing Zhang
Jae-Hyung Lee
Marco Morselli
Luz Orozco
Weilong Guo
Tina M. Kilts
Jun Zhu
Bin Zhang
Matteo Pellegrini
Xinshu Xiao
Marian F. Young
Fernando Gomez-Pinilla
Xia Yang
Source :
EBioMedicine, Vol 7, Iss C, Pp 157-166 (2016)
Publication Year :
2016
Publisher :
Elsevier, 2016.

Abstract

Nutrition plays a significant role in the increasing prevalence of metabolic and brain disorders. Here we employ systems nutrigenomics to scrutinize the genomic bases of nutrient–host interaction underlying disease predisposition or therapeutic potential. We conducted transcriptome and epigenome sequencing of hypothalamus (metabolic control) and hippocampus (cognitive processing) from a rodent model of fructose consumption, and identified significant reprogramming of DNA methylation, transcript abundance, alternative splicing, and gene networks governing cell metabolism, cell communication, inflammation, and neuronal signaling. These signals converged with genetic causal risks of metabolic, neurological, and psychiatric disorders revealed in humans. Gene network modeling uncovered the extracellular matrix genes Bgn and Fmod as main orchestrators of the effects of fructose, as validated using two knockout mouse models. We further demonstrate that an omega-3 fatty acid, DHA, reverses the genomic and network perturbations elicited by fructose, providing molecular support for nutritional interventions to counteract diet-induced metabolic and brain disorders. Our integrative approach complementing rodent and human studies supports the applicability of nutrigenomics principles to predict disease susceptibility and to guide personalized medicine.

Details

Language :
English
ISSN :
23523964
Volume :
7
Issue :
C
Database :
Directory of Open Access Journals
Journal :
EBioMedicine
Publication Type :
Academic Journal
Accession number :
edsdoj.5395af97d3d64e5e92d3203aec01f273
Document Type :
article
Full Text :
https://doi.org/10.1016/j.ebiom.2016.04.008