Perspectives on personalized nutrition for obesity.

Obesity can result from the disequilibrium between energy intake and expenditure associated with alterations of many metabolic pathways [1] . As many cellular functions related to energy homeostasis are regulated by gene expression and gene-environment interactions, individual variation in body weight/composition and adipose metabolism could be influenced by genetic makeup and nutrient intake. Nutritional outcomes can also be determined by gene-mediated biochemical pathways that regulate nutrient absorption, distribution, metabolism, and excretion as well as other cellular energy processes [2] . Indeed, the interplay between nutrients and genetic variation could be a key factor influencing obesity risk and development as well as associated conditions. About 25–70% of body weight variability is thought to be controlled by genes that affect energy homeostasis through the modulation of nuclear transcription factors, signalling molecules and receptors, adipogenesis and fat deposition, thermogenesis, hypothalamic networks, and other cellular functions related to energy efficiency [3, 4] . More than 50 genes have been implicated in obesity phenotypes, and adiposity traits have been identified in both animal and human studies [5] . For example, monogenic obesity is attributed to the mutation of specific alleles with profound effects, namely in the leptin, leptin receptor, pro-opiomelanocortin, proprotein convertase/kexin type 1, melanocortin-4 receptor, and single-minded homolog 1 genes. However, monogenic obesity is relatively uncommon, and studies on polygenic obesity support the notion that the modern prevalence of obesity has resulted from the interactions of unfavourable lifestyles with specific gene variants or single-nucleotide polymorphisms (SNPs) with less profound but converging effects [6] . Individuals susceptible to excessive fat gain may therefore carry gene variants that influence appetite control (CNR1, NPY, POMC, MC4R, etc.), nuclear and cytoplasm regulatory machinery (FTO, TFAPB2, TCF7L2, SCAP, DRD2, etc.), adipogenesis and lipid metabolism (ADRB3, PPAR, APOs, PLIN, etc.), energy expenditure (UCPs), insulin signalling (ISR-2, INSIG2, GIPR), and inflammation (ADIPOQ, IL-6, RESISTIN, etc.) [6] . Over 500 SNPs or chromosomal regions have been directly or indirectly associated with obesity [7] . Published online: July 24, 2014