학술논문

Systems Nutrigenomics Reveals Brain Gene Networks Linking Metabolic and Brain Disorders.
Document Type
article
Source
Subject
Hippocampus
Hypothalamus
Animals
Humans
Rats
Metabolic Diseases
Fructose
Gene Expression Profiling
Models
Animal
Cognition Disorders
Systems Biology
Male
Gene Regulatory Networks
Metabolic Networks and Pathways
Nutrigenomics
Epigenomics
Biglycan
Precision Medicine
Fibromodulin
Brain disorders
Brain networks
DHA
Epigenome
Extracellular matrix
Metabolic diseases
Omega-3 fatty acid
Systems nutrigenomics
Transcriptome
Biotechnology
Prevention
Human Genome
Nutrition
Brain Disorders
Neurosciences
Genetics
Complementary and Integrative Health
2.1 Biological and endogenous factors
Neurological
Mental health
Clinical Sciences
Public Health and Health Services
Language
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.