Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine (MDC), Berlin, Germany.
Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine (MDC), Berlin, Germany; Digital Health - Machine Learning Group, Hasso-Plattner-Institute for Digital Engineering, Potsdam, Germany.
Metabolism. 2019 Mar;92:61-70. doi: 10.1016/j.metabol.2018.12.006. Epub 2018 Dec 23.
The global epidemic of obesity is a major public health problem today. Obesity increases the risk of many chronic diseases, such as type 2 diabetes, coronary heart disease, and certain types of cancer, and is associated with lower life expectancy. The body mass index (BMI), which is currently used to classify obesity, is only an imperfect measure of abnormal or excessive body fat accumulation. Studies have shown that waist circumference as a measure of fat distribution may improve disease prediction. More elaborate techniques such as magnetic resonance imaging are increasingly available to assess body fat distribution, but these measures are not readily available in routine clinical practice, and health-relevant cut-offs not yet been established. The measurement of biomarkers that reflect the underlying biological mechanisms for the increased disease risk may be an alternative approach to characterize the relevant obesity phenotype. The insulin/insulin-like growth factor (IGF) axis and chronic low-grade inflammation have been identified as major pathways. In addition, specific adipokines such as leptin, adiponectin and resistin have been related to obesity-associated health outcomes. This biomarker research, which is currently further developed with the application of high throughput methods, gives important insights in obesity-related disease etiology and pathophysiological pathways and may be used to better characterize obese persons at high risk of disease development and target disease-causing biomarkers in personalized prevention strategies.
全球肥胖症的流行是当今一个主要的公共卫生问题。肥胖增加了许多慢性疾病的风险，如 2 型糖尿病、冠心病和某些类型的癌症，并且与预期寿命降低有关。目前用于分类肥胖的身体质量指数（BMI）只是衡量异常或过多体脂堆积的不完美指标。研究表明，腰围作为衡量脂肪分布的指标可能会改善疾病预测。更精细的技术，如磁共振成像，越来越多地用于评估体脂分布，但这些方法在常规临床实践中并不容易获得，也尚未确定与健康相关的截止值。测量反映增加疾病风险的潜在生物学机制的生物标志物可能是一种描述相关肥胖表型的替代方法。胰岛素/胰岛素样生长因子（IGF）轴和慢性低度炎症已被确定为主要途径。此外，特定的脂肪因子，如瘦素、脂联素和抵抗素，与肥胖相关的健康结果有关。这项生物标志物研究目前正在通过高通量方法的应用进一步发展，为肥胖相关疾病的病因学和病理生理学途径提供了重要的见解，并可能用于更好地描述处于疾病发展高风险的肥胖人群，并针对个性化预防策略中的致病生物标志物。
