Dataset Information

RA-map: building a state-of-the-art interactive knowledge base for rheumatoid arthritis.

ABSTRACT: Rheumatoid arthritis (RA) is a progressive, inflammatory autoimmune disease of unknown aetiology. The complex mechanism of aetiopathogenesis, progress and chronicity of the disease involves genetic, epigenetic and environmental factors. To understand the molecular mechanisms underlying disease phenotypes, one has to place implicated factors in their functional context. However, integration and organization of such data in a systematic manner remains a challenging task. Molecular maps are widely used in biology to provide a useful and intuitive way of depicting a variety of biological processes and disease mechanisms. Recent large-scale collaborative efforts such as the Disease Maps Project demonstrate the utility of such maps as versatile tools to organize and formalize disease-specific knowledge in a comprehensive way, both human and machine-readable. We present a systematic effort to construct a fully annotated, expert validated, state-of-the-art knowledge base for RA in the form of a molecular map. The RA map illustrates molecular and signalling pathways implicated in the disease. Signal transduction is depicted from receptors to the nucleus using the Systems Biology Graphical Notation (SBGN) standard representation. High-quality manual curation, use of only human-specific studies and focus on small-scale experiments aim to limit false positives in the map. The state-of-the-art molecular map for RA, using information from 353 peer-reviewed scientific publications, comprises 506 species, 446 reactions and 8 phenotypes. The species in the map are classified to 303 proteins, 61 complexes, 106 genes, 106 RNA entities, 2 ions and 7 simple molecules. The RA map is available online at ramap.elixir-luxembourg.org as an open-access knowledge base allowing for easy navigation and search of molecular pathways implicated in the disease. Furthermore, the RA map can serve as a template for omics data visualization.

SUBMITTER: Singh V

PROVIDER: S-EPMC7170216 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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RA-map: building a state-of-the-art interactive knowledge base for rheumatoid arthritis.

Singh Vidisha V Kalliolias George D GD Ostaszewski Marek M Veyssiere Maëva M Pilalis Eleftherios E Gawron Piotr P Mazein Alexander A Bonnet Eric E Petit-Teixeira Elisabeth E Niarakis Anna A

Database : the journal of biological databases and curation 20200101

Rheumatoid arthritis (RA) is a progressive, inflammatory autoimmune disease of unknown aetiology. The complex mechanism of aetiopathogenesis, progress and chronicity of the disease involves genetic, epigenetic and environmental factors. To understand the molecular mechanisms underlying disease phenotypes, one has to place implicated factors in their functional context. However, integration and organization of such data in a systematic manner remains a challenging task. Molecular maps are widely ...[more]

PMID: 32311035

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Project description:BackgroundComputational biology contributes to a variety of areas related to life sciences and, due to the growing impact of translational medicine--the scientific approach to medicine in tight relation with basic science--, it is becoming an important player in clinical-related areas. In this study, we use computation methods in order to improve our understanding of the complex interactions that occur between molecules related to Rheumatoid Arthritis (RA).MethodologyDue to the complexity of the disease and the numerous molecular players involved, we devised a method to construct a systemic network of interactions of the processes ongoing in patients affected by RA. The network is based on high-throughput data, refined semi-automatically with carefully curated literature-based information. This global network has then been topologically analysed, as a whole and tissue-specifically, in order to translate the experimental molecular connections into topological motifs meaningful in the identification of tissue-specific markers and targets in the diagnosis, and possibly in the therapy, of RA.SignificanceWe find that some nodes in the network that prove to be topologically important, in particular AKT2, IL6, MAPK1 and TP53, are also known to be associated with drugs used for the treatment of RA. Importantly, based on topological consideration, we are also able to suggest CRKL as a novel potentially relevant molecule for the diagnosis or treatment of RA. This type of finding proves the potential of in silico analyses able to produce highly refined hypotheses, based on vast experimental data, to be tested further and more efficiently. As research on RA is ongoing, the present map is in fieri, despite being--at the moment--a reflection of the state of the art. For this reason we make the network freely available in the standardised and easily exportable .xml CellDesigner format at 'www.picb.ac.cn/ClinicalGenomicNTW/temp.html' and 'www.celldesigner.org'.

Dataset Information

RA-map: building a state-of-the-art interactive knowledge base for rheumatoid arthritis.

Publications

RA-map: building a state-of-the-art interactive knowledge base for rheumatoid arthritis.

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