Integrative analysis of multi-omics data reveals importance of collagen and the PI3K AKT signalling pathway in CAKUT

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.

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Publication Details

Journal
Scientific Reports
Published
2024-09-05
DOI
https://doi.org/10.1038/s41598-024-71721-8
Citations
2
Primary Topic
Sarcoma Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.84

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article

Integrative analysis of multi-omics data reveals importance of collagen and the PI3K AKT signalling pathway in CAKUT

Rajaram Kaliyaperumal, Joost P. Schanstra, Peter A.C. ’t Hoen, Woosub Shin et al.
2 citations
Scientific Reports
Sarcoma Diagnosis and Treatment
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article

Integrative analysis of multi-omics data reveals importance of collagen and the PI3K AKT signalling pathway in CAKUT

Rajaram Kaliyaperumal, Joost P. Schanstra, Peter A.C. ’t Hoen, Woosub Shin, Cenna Doornbos, Jumamurat R. Bayjanov, Jean Sébastien Saulnier‐Blache, Ozan Özışık, Bénédicte Buffin‐Meyer, Friederike Ehrhart, José M. Fernández, Núria Queralt-Rosiñach, Anaı̈s Baudot, Daphne Wijnbergen, Julie Klein
article en
2 citations

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.

Scientific ReportsVol. 14(1)
Centre National de la Recherche Scientifique (FR), Université Toulouse III - Paul Sabatier (FR), Radboud University Nijmegen (NL), Inserm (FR), Aix-Marseille Université (FR), Barcelona Supercomputing Center (ES), Leiden University Medical Center (NL), Radboud University Medical Center (NL), Maastricht University (NL), Institut des Maladies Métaboliques et Cardiovasculaires (FR), Génétique Médicale & Génomique Fonctionelle (FR), Centre de Génétique Médicale de Marseille (FR), Universitat Politècnica de Catalunya (ES)
Aix-Marseille Université, European Commission, Fondation pour la Recherche Médicale, Agence de la Biomédecine, Seventh Framework Programme
Industry, innovation and infrastructure
Openalex Percentile: Top 24%
Sarcoma Diagnosis and Treatment
0.84
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