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Introduction
Congenital anomalies of the kidney and urinary tract (CAKUT) are the major cause of kidney failure in childhood and adolescence. Although one in three children with end-stage kidney disease have congenital kidney defects, a substantially larger subset of CAKUT individuals have a better prognosis of kidney function. This strong clinical variability highlights the urgent need for accurate decision-making in the management of CAKUT patients. Two major problems currently hamper decision-making:

• The aetiology of CAKUT is largely unknown.
• The long-term clinical outcome of patients with CAKUT is highly unpredictable.

Consequently, the risks of under detection of chronic kidney disease as well as overtreatment of relatively mild kidney disease exist in patients with CAKUT.

Rationale of the project plan for solving the problem
Understanding the molecular aetiology is the key to devising personalised medicine strategies that change this alarming situation for individuals with CAKUT. Since the aetiology of CAKUT remains unknown in ≥80% of children, the outcome remains unconnected to the underpinnings of developmental kidney defects for most patients. Further, the current low diagnostic yield prevents clinicians to perform standardized genetic testing in CAKUT patients, which in return hampers additional gene discovery and better understanding of disease aetiology. Since we integrate state-of-the-art molecular techniques and experiments with clinical data, the ArtDECO consortium is indispensable for moving clinical management of CAKUT patients forward.

Central hypothesis and aims
Better understanding of the molecular aetiology of CAKUT leads to a better clinical outcome for individuals with CAKUT.

The ArtDECO consortium aims to identify the missing links between causes and prognosis of CAKUT by:

1 | Establishment of a nation-wide CAKUT data- and biobank;

2 | Identification and functional characterization of genetic and environmental causes;

3 | Gene-environment risk modelling and prediction of clinical outcome.

To achieve these objectives, we have designed the following work packages:

 

Work package 1 | CAKUT data- and biobank
The ArtDECO consortium establishes a nation-wide data- and biobank for CAKUT based on the existing protocols, infrastructure, and licenses of the AGORA data- and biobank. One important hallmark of AGORA is the combination of DNA sample collection and detailed information on phenotypes, clinical parameters, and environmental exposures. AGORA was founded in 2004 and contains DNA of 14,000 subjects with various developmental defects, among which 2,000 individuals with CAKUT. The ArtDECO consortium will add DNA from newly diagnosed patients and historic subjects with the final aim to establish a cohort of 3,750 cases with complete data on clinical parameters and environmental hazard exposures. Thus, we will create a unique and world-leading CAKUT data- and biobank that combines high quality phenotypic and genetic data to set up innovative aetiological and prognostic studies. We will perform genome-wide genotyping in all study participants and whole exome sequencing in a subset of selected cases. Hereby, work package 1 facilitates the central aims and objectives defined in work packages 2-5.

The integration of genetics, clinical data, and questionnaire data on environmental factors provide the strong basis for the identification of causes of kidney and urinary tract malformations and potential prognostic factors for kidney injury. Furthermore, the high quality and well-established infrastructure of our data- and biobank builds a framework for future innovative and novel research questions.

 

Work package 2 | Monogenic aetiology of CAKUT
In work package 2, we aim to increase the diagnostic yield of genetic testing in CAKUT patients. By performing whole exome sequencing in ≥350 selected cases of the cohort included in work package 1 and by performing genome-wide genotyping in all participants, we will first characterize the CAKUT cohort in detail for known causal single nucleotide variants and copy number variants. This will aid stratification of patients for more complex approaches (work package 3 and 4). Secondly, we will identify new driver genes by analysing the newly genotyped cohort as well as CAKUT samples we have access to in kind, and exome datasets that are available through our network of established collaborations.

In these combined datasets, we will not only look for rare genetic variation. We will also deploy the innovative KidneyNetwork that improves gene function predictions based on cell type-specific (co-) expression data, which will help to prioritise the wealth of genetic variation identified. Prioritised candidate genes and gene variants will be functionally characterised in work package 5 to determine their roles in CAKUT aetiology. Lastly, the data generated in work package 2 will be integrated with KidneyNetwork to bridge the gap towards more complex genetic causal variation in work package 3.

 

Work package 3 | Complex genetic aetiology of CAKUT
Next, we will perform innovative multi-angle analyses using genome-wide microarray data to elucidate the complex genetic background of study participants without a known or novel monogenic background. We will integrate genome-wide association study (GWAS) signals on kidney function with our recently developed gene co-expression matrix to prioritize novel biological ‘core’ genes in CAKUT aetiology. These core genes can subsequently support the KidneyNetwork (work package 2) and functional validation studies (work package 5). Furthermore, we will perform a GWAS in all 3,750 study participants and >40,000 ethnicity-matched healthy controls to define the role of common variants in CAKUT. We will additionally conduct a meta-analysis of GWAS signals in collaboration with an external cohort of CAKUT patients (>7,500 cases). As such, work package 3 generates the largest cohort of genotyped individuals with CAKUT in the world (>10,000 individuals). We will use our extensive international networks (e.g. ERKNet, eUROGEN) to further expand our cohort size for polygenic risk scores (PRS) development. PRS are currently being implemented successfully in the clinical management of common diseases such as coronary artery disease and diabetes, and we ultimately aim to devise such PRS for all individuals with CAKUT.

 

Work package 4 | Complex aetiology and prognosis of CAKUT
Previous studies have demonstrated that the majority of CAKUT patients have a complex aetiology. This means that multiple genetic and environmental factors are involved. We will identify environmental risk factors using information from questionnaires filled in by parents of CAKUT patients and healthy controls. Subsequently, we will delineate genetic variants and environmental risk factors with reciprocal effects by performing gene-environment interaction analyses. We will also integrate health record information for all included study subjects (work package 1) with genetic data from work package 2 and 3 and environmental data from the questionnaires with the aim to detect genetic variants and environmental exposures that are associated with the development of kidney injury, and to generate a prediction model for progression of chronic kidney disease among CAKUT patients. We will use a machine learning technique and multivariable logistic regression analyses for gene-environment risk prediction in our study population. Before implementation into clinical care, validation of our prognostic model will be conducted in collaboration with renowned international research groups, including members of ERKNet, eUROGEN, and partners at Columbia University Medical Center.

 

Work package 5 | Functional modelling of CAKUT
To maximize the impact of ArtDECO by expanding mere associations to true pathogenicity, determining underlying disease mechanisms and identifying new preventive or therapeutic avenues, we will perform functional modelling of prioritized candidate gene variants and environmental factors by combining innovative modelling using patient-specific induced-pluripotent stem cells (iPSCs) and human kidney organoids with tailor-made animal-based modelling.