{"title":"Precision medicine for obesity: current evidence and insights for personalization of obesity pharmacotherapy.","authors":"Diego Anazco, Andres Acosta","doi":"10.1038/s41366-024-01599-z","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":14183,"journal":{"name":"International Journal of Obesity","volume":" ","pages":""},"PeriodicalIF":4.2000,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Obesity","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1038/s41366-024-01599-z","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0
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.
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.