Omics databases on kidney disease: where they can be found and how to benefit from them.
In the recent decades, the evolution of omics technologies has led to advances in all biological fields, creating a demand for effective storage, management and exchange of rapidly generated data and research discoveries. To address this need, the development of databases of experimental outputs has become a common part of scientific practice in order to serve as knowledge sources and data-sharing platforms, providing information about genes, transcripts, proteins or metabolites. In this review, we present omics databases available currently, with a special focus on their application in kidney research and possibly in clinical practice. Databases are divided into two categories: general databases with a broad information scope and kidney-specific databases distinctively concentrated on kidney pathologies. In research, databases can be used as a rich source of information about pathophysiological mechanisms and molecular targets. In the future, databases will support clinicians with their decisions, providing better and faster diagnoses and setting the direction towards more preventive, personalized medicine. We also provide a test case demonstrating the potential of biological databases in comparing multi-omics datasets and generating new hypotheses to answer a critical and common diagnostic problem in nephrology practice. In the future, employment of databases combined with data integration and data mining should provide powerful insights into unlocking the mysteries of kidney disease, leading to a potential impact on pharmacological intervention and therapeutic disease management.
Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Toulouse, France; Université Toulouse III Paul-Sabatier, Toulouse, France.
Theofilos
T
Papadopoulos
Biotechnology Division, Biomedical Research Foundation Academy of Athens, Athens, Greece; Institute for Molecular Cardiovascular Research, Universitätsklinikum RWTH Aachen, Aachen, Germany.
Magdalena
M
Krochmal
Mosaiques Diagnostics GmbH , Hannover , Germany.
Katryna
K
Cisek
BHF Glasgow Cardiovascular Research Centre , University of Glasgow , Glasgow , UK.
Marco
M
Fernandes
BHF Glasgow Cardiovascular Research Centre , University of Glasgow , Glasgow , UK.
Holger
H
Husi
School of Computer Science , University of Manchester , Manchester , UK.
Robert
R
Stevens
Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Toulouse, France; Université Toulouse III Paul-Sabatier, Toulouse, France.
Jean-Loup
JL
Bascands
Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Toulouse, France; Université Toulouse III Paul-Sabatier, Toulouse, France.
Joost P
JP
Schanstra
Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Toulouse, France; Université Toulouse III Paul-Sabatier, Toulouse, France.
Julie
J
Klein
bioinformatics; data integration; kidney disease; omics databases; system biology