Phenotyping/Signature of adipose tissue compartments: A Radiomic, Cluster-based and geographic Analysis in the German National Cohort

通过本申请，我们建议将我们的SPP项目从第一个资助期延长，该资助期的标题为“脂肪组织复合物和与糖尿病前期和2型糖尿病相关的肝组织变化：德国国家队列的放射组学和基于形状的分析”对整个GNC人群的30，000名MRI参与者，以获得GNC内身体组成和相关心脏代谢风险的全面图片。在第一个资助阶段，我们成功地将11，000人的GNC成像数据整合到我们当地的后处理管道中，对内脏（VAT）和皮下脂肪组织（SAT）以及肝脏脂肪和形状进行了所有预期分析，包括高级放射组学分析。我们还设法根据GNC政策将抽象数据传输和共享到GNC中心数据库。最近，我们从GNC数据库中收到了统计分析所需的相关协变量，并完成了第一份手稿，目前正在审查中。目前有几项分析正在等待GNC协变量转移，以充分实现第一个供资阶段的目标。所有这些计划的手稿已经准备就绪，一旦完成GNC的数据传输，将成功完成。此外，我们通过与其他基于人群的成像项目（即骨骼肌生物标志物;肾功能和疾病;器官特异性年龄）的联系为SPP网络做出了贡献，并参与了所有中心活动，包括放射学工作流程的联合出版物。因此，我们现在已经形成了科学和基础设施基础，将我们先前的方法扩展到整个GNC人群，通过创建基于MR的身体组成成像表型，包括肾脏，心脏，骨髓和肌肉的器官脂肪库，更深入地了解脂肪组织分布和身体组成，而不仅仅是VAT，SAT和肝脏脂肪。为此，我们积极与其他SPP项目（肌肉脂肪变性和肾脂肪）建立联系，并将我们的放射组学和深度学习管道从第一个资助阶段扩展到骨髓和心外膜脂肪分析。我们相信，我们将通过在GNC内应用Radiomic，基于生物学和地理分析，提供身体组成的整体签名和表型分析，全面推进SPP第二资助阶段的目标。从流行病学和临床的角度来看，这项提案的结果将是相关的。说明基于人口水平的脂肪组织区室的患病率和相关的心脏代谢疾病负担将指出区域或性别特异性差异，这可能表明需要局部化，具体的公共卫生干预措施。在临床方面，研究结果将说明脂肪组织分布的成像标记物在心脏代谢风险的个体化估计中的价值。

With the present application we propose to extend our SPP-project from the first funding period entitled “Adipose Tissue Compartments and Changes to Liver Tissue in Association with Prediabetes and Type-2 Diabetes: A Radiomic and Shape-based Analysis in the German National Cohort” to the entire GNC population of 30,000 MRI-participants to obtain a comprehensive picture of body composition and the associated cardiometabolic risks within the GNC. During the first funding phase we have successfully integrated the GNC imaging data of 11,000 individuals into our local post processing pipelines, performed all intended analyses of visceral (VAT) and subcutaneous adipose tissue (SAT) as well as liver fat and shape including advanced Radiomic analysis. We also managed to transfer and share the abstracted data to the GNC central databases according to GNC policies. Recently, we received pertaining and necessary covariates for statistical analyses from the GNC-database and completed the first manuscript, which is currently under review. There are several analyses awaiting GNC covariate transfer at the moment in order to fully accomplish the objectives of the first funding phase. All these planned manuscripts are already well prepared and will be successfully completed once data transfer from GNC is fulfilled. In addition, we have contributed to the SPP-network by connecting with other population-based imaging projects (i.e. biomarkers of skeletal muscle; kidney function and diseases; and organ-specific age) and were involved in all central activities, including the joint publication on Radiomics-Workflows. As a result, we have now formed the scientific and infrastructural basis to extend our prior approach to the full GNC population to gain a deeper understanding of adipose tissue distribution and body composition beyond VAT, SAT and liver fat by creating MR-based imaging phenotypes of body composition including organ fat depots of the kidney, heart, bone marrow and muscle. To this end we actively connect with other SPP-projects (myosteatosis and kidney fat) and extend our Radiomics and deep learning pipelines from the first funding phase to bone marrow and epicardial fat analyses. We are convinced that we will fully advance the herewith proposed aims of the second SPP funding phase by providing a holistic signature and phenotyping of body composition by applying Radiomic, Cluster-based and geographic analyses within the GNC. Findings from this proposal will be relevant from an epidemiological and clinical perspective. Illustrating the prevalence and associated cardiometabolic disease burden of adipose tissue compartments on a population-based level will point out regional or sex-specific differences, which might indicate the need for localized, specific public health interventions. On the clinical side, findings will illustrate the value of imaging markers of adipose tissue distribution in the individualized estimation of cardiometabolic risk.