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Project Topic
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Autosomal dominant tubulointerstitial disease (ADTKD) is a recently defined genetic entity of rare kidney disorders that is characterized by tubular damage, interstitial fibrosis and ineluctable progression to kidney failure between the 5th and the 7th decade of life. As an extra-renal hallmark, ADTKD-patients variably develop hyperuricemia and precocious episodes of gout. The four major ADTKD-genes (UMOD, MUC1, REN, and HNF1B) together account for the third most frequent genetic kidney disorder, after polycystic kidney disease and Alport Syndrome. As ADTKD is understudied and diagnosis requires access to (specific) genetic testing modalities individuals with ADTKD face many challenges related to delayed diagnosis, inappropriate workup, family burden, uncertain prognosis, and absence of specific therapies. However, this situation is about to change as personalized treatment options with small molecules have emerged on the horizon, highlighting the importance of clinical trial-readiness in ADTKD. In this proposal, we join forces in a world expert consortium to combine existing national cohorts for deep-phenotyping by multi-layered analytic approaches including genetics, biomarker studies, histopathology, and functional magnetic resonance imaging. Basis for all future analyses will be the first dedicated ADTKD-registry in Europe (ADTKD-EUROPE). ADTKD-EUROPE will be configured as a subregistry of the well-established registry structure of the European Reference Network for Rare Kidney Diseases (ERKNet).
Our specific aims are to: (i) capture the natural course in terms of kidney- and non-kidney-related clinical outcomes (ii) define genetic and environmental variables accounting for disease variability (iii) identify patterns of prognostic biomarkers reflecting such variability and (iv) pave the way for immediate recruitment into future therapeutic trials. We anticipate secondary benefits due to the paradigmatic nature of ADTKD, with relevance for the diagnosis and risk-stratification of other rare diseases, the efficiency and harmonization of reference networks, the analysis of multi-level datasets, the integration of patient needs and priorities, and the interconnected mechanisms of rare and complex diseases.
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