Paules Evan M, Trujillo-Gonzalez Isis, VerHague Melissa, Albright Jody, Stewart Delisha, Sumner Susan J, McRitchie Susan L, Kirchner David, Coleman Michael F, Bennett Brian J, Howard Annie Green, Gordon-Larsen Penny, French John E, Hursting Stephen D
Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA.
bioRxiv. 2025 Jul 22:2025.07.18.665483. doi: 10.1101/2025.07.18.665483.
Predictive analytics encompassing metabolomic profiles are increasingly being used to forecast responders to dietary interventions. Advances using this approach are particularly needed to personalize and enhance the effectiveness of dietary weight loss interventions. Using obese Diversity Outbred (DO) mice that model genetic and phenotypic heterogeneity of human populations, we aimed to identify urinary metabolite signatures predictive of responsiveness to calorie restriction (CR)-mediated weight loss. DO mice (150 males, 150 females) were fed a high-fat diet for 12 weeks to induce obesity, then urine was collected and an 8-week CR regimen (30% decrease in energy intake) initiated. At study completion, mice were rank-ordered according to their percent body weight change, with mice in the extreme quartiles deemed CR responders (n=67) versus nonresponders (n=67). Targeted semi-quantitative metabolomics identified elevated glutamic acid and hydroxyproline as key urinary metabolites that distinguish CR responders from CR nonresponders, independent of sex. Three urinary metabolites (glutamic acid, hydroxyproline, and putrescine) distinguished male CR responders from nonresponders. Six metabolites (glutamic acid, hydroxyproline, dopamine, histamine, lysine, and spermine) distinguished female CR responders from nonresponders. Multivariate receiver operating characteristic analyses integrated the common metabolites and sex-specific metabolites to reveal moderate (males) to robust (females, males plus females) prediction models of CR-mediated weight loss. Further, pathway analysis identified several metabolic pathways, including arginine and proline metabolism, and alanine, aspartate, and glutamate biosynthesis, that distinguished CR responders from nonresponders and could be indicative of metabolic reprogramming to enhance insulin sensitivity and energy metabolism.
包含代谢组学特征的预测性分析越来越多地用于预测饮食干预的反应者。尤其需要利用这种方法取得的进展来实现饮食减肥干预的个性化并提高其有效性。我们使用肥胖的多样性远交（DO）小鼠来模拟人类群体的遗传和表型异质性，旨在识别可预测对热量限制（CR）介导的体重减轻反应的尿液代谢物特征。给150只雄性和150只雌性DO小鼠喂食高脂饮食12周以诱导肥胖，然后收集尿液并开始为期8周的CR方案（能量摄入减少30%）。在研究结束时，根据小鼠体重变化百分比进行排序，处于极端四分位数的小鼠被视为CR反应者（n = 67）与无反应者（n = 67）。靶向半定量代谢组学确定谷氨酸和羟脯氨酸水平升高是区分CR反应者与CR无反应者的关键尿液代谢物，与性别无关。三种尿液代谢物（谷氨酸、羟脯氨酸和腐胺）区分了雄性CR反应者与无反应者。六种代谢物（谷氨酸、羟脯氨酸、多巴胺、组胺、赖氨酸和精胺）区分了雌性CR反应者与无反应者。多变量受试者工作特征分析整合了常见代谢物和性别特异性代谢物，以揭示CR介导的体重减轻的中度（男性）至稳健（女性、男性加女性）预测模型。此外，通路分析确定了几种代谢途径，包括精氨酸和脯氨酸代谢以及丙氨酸、天冬氨酸和谷氨酸生物合成，这些途径区分了CR反应者与无反应者，可能表明代谢重编程以增强胰岛素敏感性和能量代谢。
