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Abstract Congenital Anomalies of the Kidney and Urinary Tract (CAKUT) is the leading cause of childhood chronic kidney failure and a significant cause of chronic kidney disease in adults. Genetic and environmental factors are known to influence CAKUT development, but the currently known disease mechanism remains incomplete. Our goal is to identify affected pathways and networks in CAKUT, and thereby aid in getting a better understanding of its pathophysiology. With this goal, the miRNome, peptidome, and proteome of over 30 amniotic fluid samples of patients with non-severe CAKUT was compared to patients with severe CAKUT. These omics data sets were made findable, accessible, interoperable, and reusable (FAIR) to facilitate their integration with external data resources. Furthermore, we analysed and integrated the omics data sets using three different bioinformatics strategies: integrative analysis with mixOmics, joint dimensionality reduction and pathway analysis. The three bioinformatics analyses provided complementary features, but all pointed towards an important role for collagen in CAKUT development and the PI3K-AKT signalling pathway. Additionally, several key genes (CSF1, IGF2, ITGB1, and RAC1) and microRNAs were identified. We published the three analysis strategies as containerized workflows. These workflows can be applied to other FAIR data sets and help gaining knowledge on other rare diseases.

Diabetic kidney disease (DKD) is characterized by histological changes including fibrosis and inflammation. Evidence supports that DKD is mediated by the innate immune system and more specifically by the complement system. Using Ins2Akita T1D diabetic mice, we studied the connection between the complement cascade, inflammation, and fibrosis in early DKD. Data were extracted from a previously published quantitative-mass-spectrometry-based proteomics analysis of kidney glomeruli of 2 (early DKD) and 4 months (moderately advanced DKD)-old Ins2Akita mice and their controls A Spearman rho correlation analysis of complement- versus inflammation- and fibrosis-related protein expression was performed. A cross-omics validation of the correlation analyses’ results was performed using public-domain transcriptomics datasets (Nephroseq). Tissue sections from 43 patients with DKD were analyzed using immunofluorescence. Among the differentially expressed proteins, the complement cascade proteins C3, C4B, and IGHM were significantly increased in both early and later stages of DKD. Inflammation-related proteins were mainly upregulated in early DKD, and fibrotic proteins were induced in moderately advanced stages of DKD. The abundance of complement proteins with fibrosis- and inflammation-related proteins was mostly positively correlated in early stages of DKD. This was confirmed in seven additional human and mouse transcriptomics DKD datasets. Moreover, C3 and IGHM mRNA levels were found to be negatively correlated with the estimated glomerular filtration rate (range for C3 rs = −0.58 to −0.842 and range for IGHM rs = −0.6 to −0.74) in these datasets. Immunohistology of human kidney biopsies revealed that C3, C1q, and IGM proteins were induced in patients with DKD and were correlated with fibrosis and inflammation. Our study shows for the first time the potential activation of the complement cascade associated with inflammation-mediated kidney fibrosis in the Ins2Akita T1D mouse model. Our findings could provide new perspectives for the treatment of early DKD as well as support the use of Ins2Akita T1D in pre-clinical studies.