Gabrielli Alexander P, Manzardo Ann M, Butler Merlin G
Departments of Psychiatry and Behavioral Sciences and Pediatrics, University of Kansas Medical Center, Kansas City, Kansas, USA.
Obesity (Silver Spring). 2017 Jun;25(6):1136-1143. doi: 10.1002/oby.21847. Epub 2017 May 5.
Obesity has been reaching epidemic levels in recent decades, with a growing body of research identifying predisposing genetic components. To explore the relationship of genetic factors contributing to obesity, an analytical computer-based gene-profiling approach utilizing an updated list of clinically relevant and known obesity-related genes was undertaken.
An updated list of 494 genes reportedly associated with obesity was compiled, and the GeneAnalytics profiling software was utilized to interrogate genomic databases from GeneCards® to cross-reference obesity gene sets against tissues and cells, diseases, genetic pathways, gene ontology (GO)-biological processes and GO-molecular functions, phenotypes, and compounds.
Obesity-related fields identified by GeneAnalytics algorithms included 8 diseases, 46 pathways, 62 biological processes, 22 molecular functions, 148 phenotypes, and 286 compounds impacting adipogenesis, signal transduction by G-protein coupled receptors, and lipid metabolism involving insulin-related genes (IGF1, INS, IRS1). GO-biological processes identified feeding behavior, cholesterol metabolic process, and glucose and cholesterol homeostasis pathways, while GO-molecular processes pertained to receptor binding, affecting glucose homeostasis, body weight, and circulating insulin and triglyceride levels.
The gene-profiling model suggests that pathogenesis of obesity relates to the coordination of biological responses to glucose and intracellular lipids possibly through a disruption of biochemical cascades and cellular signaling arising from affected receptors.
近几十年来，肥胖已达到流行程度，越来越多的研究确定了相关的遗传因素。为了探究导致肥胖的遗传因素之间的关系，我们采用了一种基于计算机分析的基因谱分析方法，该方法使用了一份更新后的临床相关且已知的肥胖相关基因列表。
汇编了一份据报道与肥胖相关的494个基因的更新列表，并使用GeneAnalytics基因谱分析软件查询来自GeneCards®的基因组数据库，以将肥胖基因集与组织和细胞、疾病、遗传途径、基因本体论（GO）-生物学过程和GO-分子功能、表型及化合物进行交叉对照。
GeneAnalytics算法识别出的与肥胖相关的领域包括8种疾病、46条途径、62个生物学过程、22种分子功能、148种表型以及286种影响脂肪生成、G蛋白偶联受体信号转导和涉及胰岛素相关基因（IGF1、INS、IRS1）的脂质代谢的化合物。GO-生物学过程识别出进食行为、胆固醇代谢过程以及葡萄糖和胆固醇稳态途径，而GO-分子过程与受体结合有关，影响葡萄糖稳态、体重以及循环胰岛素和甘油三酯水平。
基因谱分析模型表明，肥胖的发病机制可能与受影响受体引发的生化级联反应和细胞信号传导中断导致的对葡萄糖和细胞内脂质的生物反应协调有关。
