Systems Nutrigenomics Reveals Brain Gene Networks Linking Metabolic and Brain Disorders

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-PinillaXia Yang

Research output: Contribution to journalArticlepeer-review

49 Scopus citations


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.

Original languageEnglish
Pages (from-to)157-166
Number of pages10
StatePublished - 1 May 2016
Externally publishedYes


  • Brain disorders
  • Brain networks
  • DHA
  • Epigenome
  • Extracellular matrix
  • Fructose
  • Metabolic diseases
  • Omega-3 fatty acid
  • Systems nutrigenomics
  • Transcriptome


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