Identification of novel molecular signatures of IgA nephropathy through an integrative -omics analysis

Abstract IgA nephropathy (IgAN) is the most prevalent among primary glomerular diseases worldwide. Although our understanding of IgAN has advanced significantly, its underlying biology and potential drug targets are still unexplored. We investigated a combinatorial approach for the analysis of IgAN-...

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Autores principales:	Magdalena Krochmal, Katryna Cisek, Szymon Filip, Katerina Markoska, Clare Orange, Jerome Zoidakis, Chara Gakiopoulou, Goce Spasovski, Harald Mischak, Christian Delles, Antonia Vlahou, Joachim Jankowski
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/c72f1e532e7b496a8bf240ac7ab005b4
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spelling	oai:doaj.org-article:c72f1e532e7b496a8bf240ac7ab005b42021-12-02T15:04:54ZIdentification of novel molecular signatures of IgA nephropathy through an integrative -omics analysis10.1038/s41598-017-09393-w2045-2322https://doaj.org/article/c72f1e532e7b496a8bf240ac7ab005b42017-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-09393-whttps://doaj.org/toc/2045-2322Abstract IgA nephropathy (IgAN) is the most prevalent among primary glomerular diseases worldwide. Although our understanding of IgAN has advanced significantly, its underlying biology and potential drug targets are still unexplored. We investigated a combinatorial approach for the analysis of IgAN-relevant -omics data, aiming at identification of novel molecular signatures of the disease. Nine published urinary proteomics datasets were collected and the reported differentially expressed proteins in IgAN vs. healthy controls were integrated into known biological pathways. Proteins participating in these pathways were subjected to multi-step assessment, including investigation of IgAN transcriptomics datasets (Nephroseq database), their reported protein-protein interactions (STRING database), kidney tissue expression (Human Protein Atlas) and literature mining. Through this process, from an initial dataset of 232 proteins significantly associated with IgAN, 20 pathways were predicted, yielding 657 proteins for further analysis. Step-wise evaluation highlighted 20 proteins of possibly high relevance to IgAN and/or kidney disease. Experimental validation of 3 predicted relevant proteins, adenylyl cyclase-associated protein 1 (CAP1), SHC-transforming protein 1 (SHC1) and prolylcarboxypeptidase (PRCP) was performed by immunostaining of human kidney sections. Collectively, this study presents an integrative procedure for -omics data exploitation, giving rise to biologically relevant results.Magdalena KrochmalKatryna CisekSzymon FilipKaterina MarkoskaClare OrangeJerome ZoidakisChara GakiopoulouGoce SpasovskiHarald MischakChristian DellesAntonia VlahouJoachim JankowskiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-13 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Magdalena Krochmal Katryna Cisek Szymon Filip Katerina Markoska Clare Orange Jerome Zoidakis Chara Gakiopoulou Goce Spasovski Harald Mischak Christian Delles Antonia Vlahou Joachim Jankowski Identification of novel molecular signatures of IgA nephropathy through an integrative -omics analysis
description	Abstract IgA nephropathy (IgAN) is the most prevalent among primary glomerular diseases worldwide. Although our understanding of IgAN has advanced significantly, its underlying biology and potential drug targets are still unexplored. We investigated a combinatorial approach for the analysis of IgAN-relevant -omics data, aiming at identification of novel molecular signatures of the disease. Nine published urinary proteomics datasets were collected and the reported differentially expressed proteins in IgAN vs. healthy controls were integrated into known biological pathways. Proteins participating in these pathways were subjected to multi-step assessment, including investigation of IgAN transcriptomics datasets (Nephroseq database), their reported protein-protein interactions (STRING database), kidney tissue expression (Human Protein Atlas) and literature mining. Through this process, from an initial dataset of 232 proteins significantly associated with IgAN, 20 pathways were predicted, yielding 657 proteins for further analysis. Step-wise evaluation highlighted 20 proteins of possibly high relevance to IgAN and/or kidney disease. Experimental validation of 3 predicted relevant proteins, adenylyl cyclase-associated protein 1 (CAP1), SHC-transforming protein 1 (SHC1) and prolylcarboxypeptidase (PRCP) was performed by immunostaining of human kidney sections. Collectively, this study presents an integrative procedure for -omics data exploitation, giving rise to biologically relevant results.
format	article
author	Magdalena Krochmal Katryna Cisek Szymon Filip Katerina Markoska Clare Orange Jerome Zoidakis Chara Gakiopoulou Goce Spasovski Harald Mischak Christian Delles Antonia Vlahou Joachim Jankowski
author_facet	Magdalena Krochmal Katryna Cisek Szymon Filip Katerina Markoska Clare Orange Jerome Zoidakis Chara Gakiopoulou Goce Spasovski Harald Mischak Christian Delles Antonia Vlahou Joachim Jankowski
author_sort	Magdalena Krochmal
title	Identification of novel molecular signatures of IgA nephropathy through an integrative -omics analysis
title_short	Identification of novel molecular signatures of IgA nephropathy through an integrative -omics analysis
title_full	Identification of novel molecular signatures of IgA nephropathy through an integrative -omics analysis
title_fullStr	Identification of novel molecular signatures of IgA nephropathy through an integrative -omics analysis
title_full_unstemmed	Identification of novel molecular signatures of IgA nephropathy through an integrative -omics analysis
title_sort	identification of novel molecular signatures of iga nephropathy through an integrative -omics analysis
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/c72f1e532e7b496a8bf240ac7ab005b4
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_version_	1718389041436557312

Identification of novel molecular signatures of IgA nephropathy through an integrative -omics analysis

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