The visit of Dr. Sfar is included in the program of the nephrogenetics research of the UMC Utrecht that aims to elucidate the genetic background of kidney diseases by using next generation sequencing approaches. Dr. Sfar will collaborate in the ongoing studies, in which we aim to identify CAKUT-causing genes and variants. CAKUT is characterized by a wide range of structural renal malformations related to defects in the renal system morphogenesis due to the perturbation of the underlying molecular control of kidney and urinary tract development. The CAKUT phenotypic spectrum encompasses multicystic dysplastic kidney, kidney hypoplasia, renal agenesis, vesicoureteral reflux, and duplex collecting system. CAKUT constitutes the major leading cause (70%) of paediatric end-stage renal disease and increase the risk of hypertension and cardiovascular disease throughout life, accounting for approximately 40% of children that receive renal replacement therapy (i.e. kidney transplantation or dialysis). Therefore, it is fundamental to determine CAKUT aetiology and identify the molecular key players involved, to improve the diagnosis and the prognostic counselling of renal malformations. A genetic predisposition to CAKUT is supported by the occurrence of familial cases and the co-occurrence of renal malformations with other congenital abnormalities outside the urinary tract in syndromal forms of CAKUT. Approximately 10% of CAKUT cases have a family history of kidney anomalies. Furthermore, we know from animal studies that normal nephrogenesis is mastered by a large number of genes and signalling pathways that are involved in the embryogenesis of the kidney and urinary tract. In this context, a multitude of different CAKUT single causing genes have been documented, each gene is representing a monogenic recessive or dominant cause of CAKUT suggesting a genetic heterogeneity of the disease. However, the wide phenotypic spectrum of CAKUT and the absence of genotype-phenotype correlations indicate that CAKUT is a multifactorial disorder implying complex interaction of genetic and environmental factors. Complex inheritance is further supported by intra and interfamilial phenotypic heterogeneity for the same underlying mutation suggesting an oligogenic model of inheritance. To determine the complexity of the genetic background of CAKUT, several approaches have been used, including linkage analysis, single candidate gene studies and massive parallel DNA sequencing. The genetic background of 80-90% of CAKUT cases is unknown and the confirmation of the potential pathogenic role of the majority of the identified mutations has proven to be challenging. Therefore, the main focus of the research project proposed here, is to gain insight into the molecular mechanisms of CAKUT using next generation sequencing analysis. Furthermore, we aim to identify the spectrum of rare and novel variations in known CAKUT susceptibility genes. In this context, the next generation sequencing (NGS) provides an expanding diagnostic tool to investigate the genetic basis of CAKUT which will improve personalized diagnostics, genetic and prognostic counselling for the patients and their relatives. The identification and the functional characterization of the causal genetic factors which underlie this heterogeneous disease may lead to a better understanding of the related control mechanisms and drive predisposition testing in clinical practice.

Data-driven life science plays a key role in gaining new insights into health status and disease, in developing methods to promote health, and enabling health research & personalised medicine. The quality and success of data-driven life science critically depends on the availability of increasingly larger and richer series of human samples, health and disease phenotype data, and the methodological framework to derive information from them. Our DARE-4-LIFE application was crucial in this respect, as it was aimed at sharing, linking and analysing high-quality, comprehensive data across different resources and different levels in The Netherlands. The proposed infrastructure proposed would have built on the achievements of BBMRI.nl 1.0 (2008-2014) and 2.0 (2015-2020), resulting in a larger cluster of initiatives sharing data with new connections in the area of social science and nutrition. The unsuccessfulness of the application poses a direct threat to data-driven life sciences in The Netherlands. Specifically, discontinuation of the BBMRI infrastructure will disrupt the biobank community and the data sharing process. If biobanks in the Netherlands, within the BBMRI cluster and beyond, can no longer rely on an infrastructure to support and maintain data sharing, this is a huge loss for science, also in comparison to the international competition. Bridge funding will be essential to sustain a number of essential activities, namely: - Maintaining support to find & access samples and images, and steps towards integrating more data - Supporting researchers with Ethical, Legal and Societal Implications in data-driven life science research.