Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.
Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.
Mol Nutr Food Res. 2018 Aug;62(16):e1800117. doi: 10.1002/mnfr.201800117. Epub 2018 Jul 31.
"Metabotyping" describes the grouping of metabolically similar individuals. We aimed to identify valid metabotypes in a large cohort for targeted dietary intervention, for example, for disease prevention.
We grouped 1729 adults aged 32-77 years of the German population-based KORA F4 study (2006-2008) using k-means cluster analysis based on 34 biochemical and anthropometric parameters. We identified three metabolically distinct clusters showing significantly different biochemical parameter concentrations. Cardiometabolic disease status was determined at baseline in the F4 study and at the 7 year follow-up termed FF4 (2013/2014) to compare disease prevalence and incidence between clusters. Cluster 3 showed the most unfavorable marker profile with the highest prevalence of cardiometabolic diseases. Also, disease incidence was higher in cluster 3 compared to clusters 2 and 1, respectively, for hypertension (41.2%/25.3%/18.2%), type 2 diabetes (28.3%/5.1%/2.0%), hyperuricemia/gout (10.8%/2.3%/0.7%), dyslipidemia (19.2%/18.3%/5.6%), all metabolic (54.5%/36.8%/19.7%), and all cardiovascular (6.3%/5.5%/2.3%) diseases together.
Cluster analysis based on an extensive set of biochemical and anthropometric parameters allows the identification of comprehensive metabotypes that were distinctly different in cardiometabolic disease occurrence. As a next step, targeted dietary strategies should be developed with the goal of preventing diseases, especially in cluster 3.
“代谢分型”描述了代谢相似个体的分组。我们旨在为有针对性的饮食干预确定大型队列中的有效代谢类型，例如用于预防疾病。
我们使用基于 34 种生化和人体测量参数的 k-均值聚类分析，对年龄在 32-77 岁的德国人群为基础的 KORA F4 研究（2006-2008 年）中的 1729 名成年人进行分组。我们确定了三个代谢上明显不同的聚类，它们的生化参数浓度有显著差异。在 F4 研究中确定了基线时的心血管代谢疾病状况，并在 7 年随访时称为 FF4（2013/2014 年），以比较聚类之间的疾病患病率和发病率。聚类 3 显示出最不利的标志物谱，心血管代谢疾病的患病率最高。此外，与聚类 2 和聚类 1 相比，聚类 3 的疾病发病率也更高，分别为高血压（41.2%/25.3%/18.2%）、2 型糖尿病（28.3%/5.1%/2.0%）、高尿酸血症/痛风（10.8%/2.3%/0.7%）、血脂异常（19.2%/18.3%/5.6%）、所有代谢疾病（54.5%/36.8%/19.7%）和所有心血管疾病（6.3%/5.5%/2.3%）。
基于广泛的生化和人体测量参数的聚类分析允许识别在心血管代谢疾病发生方面明显不同的综合代谢类型。作为下一步，应制定有针对性的饮食策略，以预防疾病，特别是在聚类 3 中。
