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Nephrologists treat highly complex patients and at the same time conduct the lowest number of randomized controlled clinical trials (RCTs) in internal medicine. The latter is due to insufficient knowledge of pathophysiology, insufficient preclinical models, and most importantly the lack of accepted surrogate endpoints for RCTs. To address this urgent need, our clinical research unit (CRU) will develop and translate emerging methods that are still largely unexplored in nephrology to better understand the pathophysiology of kidney diseases. By that, we aim to develop new diagnostic approaches, new potential endpoints for RCTs, and ultimately new therapies.


In our CRU we synergistically integrate two key features: first, the systematic combination of basic scientists (chemists, biochemists, biologists, electrical engineers, computational biologist, imaging experts) with translational and clinical scientists (nephrologists, nephropathologists) and second, intense interaction between all groups at the methodological level combining complementary expertise, as well as sharing biomaterials and data. We will particularly focus on phase transitions in kidney diseases, i.e. resolution versus progression of renal diseases and the transition from acute to chronic kidney injury. For this, we aim to develop in vitro high throughput humanized 3D models of the tubulointerstitium for modeling and validation of molecular disease mechanisms.


We will generate  comprehensive molecular maps of kidney disease transitions by applying, further developing, and integrating tissue proteomics and functional genomics focusing on single-cell transcriptomes and epigenomes and develop integrative computational methods for multiomics. We will develop machine learning for digital renal pathology to facilitate robust quantitative and multiparametric analyses, i.e. pathomics. We will also develop and refine our unique methods in molecular imaging and super-resolution ultrasound for non-invasive kidney imaging and disease monitoring. Finally, we aim to integrate these diagnostic methods to better understand human IgA nephropathy, which is particularly difficult to study since no adequate pre-clinical models exist.

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