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

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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.