Biosciences Laboratory, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, I‑47014 Meldola, Italy.
Department of Otolaryngology, School of Medicine, Johns Hopkins University, Baltimore, MD 21231, USA.
Mol Med Rep. 2018 Jan;17(1):1699-1709. doi: 10.3892/mmr.2017.8039. Epub 2017 Nov 14.
Single nucleotide polymorphisms associated with lipid metabolism and energy balance are implicated in the weight loss response caused by nutritional interventions. Diet‑induced weight loss is also associated with differential global DNA methylation. DNA methylation has been proposed as a predictive biomarker for weight loss response. Personalized biomarkers for successful weight loss may inform clinical decisions when deciding between behavioral and surgical weight loss interventions. The aim of the present study was to investigate the association between global DNA methylation, genetic variants associated with energy balance and lipid metabolism, and weight loss following a non‑surgical weight loss regimen. The present study included 105 obese participants that were enrolled in a personalized weight loss program based on their allelic composition of the following five energy balance and lipid metabolism‑associated loci: Near insulin‑induced gene 2 (INSIG2); melanocortin 4 receptor; adrenoceptor β2; apolipoprotein A5; and G‑protein subunit β3. The present study investigated the association between a global DNA methylation index (GDMI), the allelic composition of the five energy balance and lipid metabolism‑associated loci, and weight loss during a 12 month program, after controlling for age, sex and body mass index (BMI). The results demonstrated a significant association between the GDMI and near INSIG2 locus, after adjusting for BMI and weight loss, and significant trends were observed when stratifying by gender. In conclusion, a combination of genetic and epigenetic biomarkers may be used to design personalized weight loss interventions, enabling adherence and ensuring improved outcomes for obesity treatment programs. Precision weight loss programs designed based on molecular information may enable the creation of personalized interventions for patients, that use genomic biomarkers for treatment design and for treatment adherence monitoring, thus improving response to treatment.
与脂质代谢和能量平衡相关的单核苷酸多态性与营养干预引起的体重减轻反应有关。饮食诱导的体重减轻也与全基因组 DNA 甲基化的差异有关。DNA 甲基化已被提议作为体重减轻反应的预测生物标志物。成功减肥的个性化生物标志物可能会为临床决策提供信息，帮助在行为和手术减肥干预之间做出选择。本研究旨在探讨全基因组 DNA 甲基化、与能量平衡和脂质代谢相关的遗传变异与非手术减肥方案后体重减轻之间的关系。本研究纳入了 105 名肥胖参与者，他们根据以下五个与能量平衡和脂质代谢相关的基因座的等位基因组成参加了个性化减肥计划：胰岛素诱导基因 2（INSIG2）附近；黑皮质素 4 受体；肾上腺素能受体 β2；载脂蛋白 A5；G 蛋白亚基 β3。本研究调查了全基因组 DNA 甲基化指数（GDMI）与 5 个与能量平衡和脂质代谢相关的基因座的等位基因组成，以及在 12 个月的计划中体重减轻之间的关系，同时控制了年龄、性别和体重指数（BMI）。结果表明，在调整 BMI 和体重减轻后，GDMI 与近 INSIG2 基因座之间存在显著相关性，并且在按性别分层时观察到显著趋势。综上所述，遗传和表观遗传生物标志物的组合可用于设计个性化减肥干预措施，从而提高肥胖治疗计划的依从性并确保改善治疗效果。基于分子信息设计的精准减肥方案可以为患者创建个性化干预措施，使用基因组生物标志物进行治疗设计和治疗依从性监测，从而提高治疗反应。
