Precision medicine for obesity: current evidence and insights for personalization of obesity pharmacotherapy.

IF 4.2 2区 医学 Q1 ENDOCRINOLOGY & METABOLISM
Diego Anazco, Andres Acosta
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Abstract

Obesity is a chronic and complex disease associated with increased morbidity, mortality, and financial burden. It is expected that by 2030 one of two people in the United States will have obesity. The backbone for obesity management continues to be lifestyle interventions, consisting of calorie deficit diets and increased physical activity levels, however, these interventions are often insufficient to achieve sufficient and maintained weight loss. As a result, multiple patients require additional interventions such as antiobesity medications or bariatric interventions in order to achieve clinically significant weight loss and improvement or resolution of obesity-associated comorbidities. Despite the recent advances in the field of obesity pharmacotherapy that have resulted in never-before-seen weight loss outcomes, comorbidity improvement, and even reduction in cardiovascular mortality, there is still a significant interindividual variability in terms of response to antiobesity medications, with a subset of patients not achieving a clinically significant weight loss. Currently, the trial-and-error paradigm for the selection of antiobesity medications results in increased costs and risks for developing side effects, while also reduces engagement in weight management programs for patients with obesity. The implementation of a precision medicine framework to the selection of antiobesity medications might help reduce heterogeneity and optimize weight loss outcomes by identifying unique subsets of patients, or phenotypes, that have a better response to a specific intervention. The detailed study of energy balance regulation holds promise, as actionable behavioral and physiologic traits could help guide antiobesity medication selection based on previous mechanistic studies. Moreover, the rapid advances in genotyping, multi-omics, and big data analysis might hold the key to discover additional signatures or phenotypes that might respond better to a certain intervention and might permit the widespread adoption of a precision medicine approach for obesity management.

Abstract Image

肥胖症精准医疗:肥胖症个性化药物疗法的现有证据和见解。
肥胖症是一种慢性复杂疾病,会增加发病率、死亡率和经济负担。预计到 2030 年,美国每两个人中就有一人患有肥胖症。肥胖症治疗的支柱仍然是生活方式干预,包括热量不足饮食和增加体育锻炼,但这些干预措施往往不足以实现充分和持续的体重减轻。因此,许多患者需要额外的干预措施,如抗肥胖药物或减肥干预措施,以实现临床上显著的体重减轻,改善或解决肥胖相关的并发症。尽管最近肥胖症药物治疗领域取得了前所未有的进展,体重减轻、合并症改善甚至心血管死亡率降低,但个体间对抗肥胖药物的反应仍存在很大差异,一部分患者无法实现临床上显著的体重减轻。目前,选择抗肥胖药物的 "试错 "模式增加了成本和产生副作用的风险,同时也降低了肥胖症患者参与体重管理计划的积极性。在选择抗肥胖药物时实施精准医学框架,可能有助于减少异质性,并通过识别对特定干预措施反应更好的独特患者子集或表型来优化减肥效果。对能量平衡调节的详细研究前景广阔,因为可操作的行为和生理特征有助于在以往机理研究的基础上指导抗肥胖药物的选择。此外,基因分型、多组学和大数据分析的快速发展可能是发现更多可能对某种干预措施反应更好的特征或表型的关键所在,并可能允许在肥胖管理中广泛采用精准医学方法。
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来源期刊
International Journal of Obesity
International Journal of Obesity 医学-内分泌学与代谢
CiteScore
10.00
自引率
2.00%
发文量
221
审稿时长
3 months
期刊介绍: The International Journal of Obesity is a multi-disciplinary forum for research describing basic, clinical and applied studies in biochemistry, physiology, genetics and nutrition, molecular, metabolic, psychological and epidemiological aspects of obesity and related disorders. We publish a range of content types including original research articles, technical reports, reviews, correspondence and brief communications that elaborate on significant advances in the field and cover topical issues.
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