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Pathway databases and tools for their exploitation: benefits, current limitations and challenges.

ABSTRACT: In past years, comprehensive representations of cell signalling pathways have been developed by manual curation from literature, which requires huge effort and would benefit from information stored in databases and from automatic retrieval and integration methods. Once a reconstruction of the network of interactions is achieved, analysis of its structural features and its dynamic behaviour can take place. Mathematical modelling techniques are used to simulate the complex behaviour of cell signalling networks, which ultimately sheds light on the mechanisms leading to complex diseases or helps in the identification of drug targets. A variety of databases containing information on cell signalling pathways have been developed in conjunction with methodologies to access and analyse the data. In principle, the scenario is prepared to make the most of this information for the analysis of the dynamics of signalling pathways. However, are the knowledge repositories of signalling pathways ready to realize the systems biology promise? In this article we aim to initiate this discussion and to provide some insights on this issue.

SUBMITTER: Bauer-Mehren A

PROVIDER: S-EPMC2724977 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature

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Pathway databases and tools for their exploitation: benefits, current limitations and challenges.

Bauer-Mehren Anna A Furlong Laura I LI Sanz Ferran F

Molecular systems biology 20090728

In past years, comprehensive representations of cell signalling pathways have been developed by manual curation from literature, which requires huge effort and would benefit from information stored in databases and from automatic retrieval and integration methods. Once a reconstruction of the network of interactions is achieved, analysis of its structural features and its dynamic behaviour can take place. Mathematical modelling techniques are used to simulate the complex behaviour of cell signal ...[more]

PMID: 19638971

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Project description:Genome-wide association studies (GWAS) have identified many common single nucleotide polymorphisms (SNPs) that associate with clinical phenotypes, but these SNPs usually explain just a small part of the heritability and have relatively modest effect sizes. In contrast, SNPs that associate with metabolite levels generally explain a higher percentage of the genetic variation and demonstrate larger effect sizes. Still, the discovery of SNPs associated with metabolite levels is challenging since testing all metabolites measured in typical metabolomics studies with all SNPs comes with a severe multiple testing penalty. We have developed an automated workflow approach that utilizes prior knowledge of biochemical pathways present in databases like KEGG and BioCyc to generate a smaller SNP set relevant to the metabolite. This paper explores the opportunities and challenges in the analysis of GWAS of metabolomic phenotypes and provides novel insights into the genetic basis of metabolic variation through the re-analysis of published GWAS datasets.Re-analysis of the published GWAS dataset from Illig et al. (Nature Genetics, 2010) using a pathway-based workflow (http://www.myexperiment.org/packs/319.html), confirmed previously identified hits and identified a new locus of human metabolic individuality, associating Aldehyde dehydrogenase family1 L1 (ALDH1L1) with serine/glycine ratios in blood. Replication in an independent GWAS dataset of phospholipids (Demirkan et al., PLoS Genetics, 2012) identified two novel loci supported by additional literature evidence: GPAM (Glycerol-3 phosphate acyltransferase) and CBS (Cystathionine beta-synthase). In addition, the workflow approach provided novel insight into the affected pathways and relevance of some of these gene-metabolite pairs in disease development and progression.We demonstrate the utility of automated exploitation of background knowledge present in pathway databases for the analysis of GWAS datasets of metabolomic phenotypes. We report novel loci and potential biochemical mechanisms that contribute to our understanding of the genetic basis of metabolic variation and its relationship to disease development and progression.

Project description:BackgroundBiomarker research is gaining increasing attention focusing on the preclinical stages of the disease. Such interest requires special attention for communication and disclosure in clinical contexts. Many countries give dementia a high health policy priority by developing national strategies and by improving guidelines addressing disclosure of a diagnosis; however, risk communication is often neglected.Main textThis paper aims to identify the challenges of disclosure in the context of dementia prediction and to find out whether existing clinical guidelines sufficiently address the issues of disclosing a dementia diagnosis and of disclosing the risk of developing dementia in asymptomatic and MCI stage. We will examine clinical guidelines and recommendations of three countries (USA, Canada and Germany) regarding predictive testing and diagnostic disclosure in dementia and Mild Cognitive Impairment (MCI) to show their potentials and limits. This will provide a background to address ethical implications of predictive information and to identify ways how to proceed further. We will start by examining the guidelines and recommendations by focusing on what there is already and what is missing regarding the challenges of disclosing dementia prediction and MCI. Then, we will highlight the novel ethical issues generated by the shift to identify preclinical stages of the disease by biomarkers. We will argue for the need to develop guidelines for disclosing a risk status, which requires different considerations then disclosing a diagnosis of dementia. Finally, we will make some suggestions on how to address the gap and challenges raised by referring to German Stakeholder Conference, which presents us a good starting point to the applicability of involving stakeholders.ConclusionsThis paper underlines the need to develop empirically based guidelines that address the ethical and social strategies for risk communication of dementia prediction by genetic as well as non-genetic biomarkers. According to our analysis, the guidelines do not address the new developments sufficiently. International efforts should aim for specific guidelines on counseling, communicating risk and disclosing results. We argue that guidelines on (risk) disclosure should be developed by involving various stakeholders and should be informed by socio-empirical studies involving laypersons' needs and wishes regarding risk communication.

Dataset Information

Pathway databases and tools for their exploitation: benefits, current limitations and challenges.

Publications

Pathway databases and tools for their exploitation: benefits, current limitations and challenges.

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