Interdisciplinary approach towards a systems medicine toolbox using the example of inflammatory diseases

Abstract

Electronic access to multiple data types, from generic information on biological systems at different functional and cellular levels to high-throughput molecular data from human patients, is a prerequisite of successful systems medicine research. However, scientists often encounter technical and conceptual difficulties that forestall the efficient and effective use of these resources. We summarize and discuss some of these obstacles, and suggest ways to avoid or evade them.The methodological gap between data capturing and data analysis is huge in human medical research. Primary data producers often do not fully apprehend the scientific value of their data, whereas data analysts maybe ignorant of the circumstances under which the data were collected. Therefore, the provision of easy-to-use data access tools not only helps to improve data quality on the part of the data producers but also is likely to foster an informed dialogue with the data analysts.We propose a means to integrate phenotypic data, questionnaire data and microbiome data with a user-friendly Systems Medicine toolbox embedded into i2b2/tranSMART. Our approach is exemplified by the integration of a basic outlier detection tool and a more advanced microbiome analysis (alpha diversity) script. Continuous discussion with clinicians, data managers, biostatisticians and systems medicine experts should serve to enrich even further the functionality of toolboxes like ours, being geared to be used by ‘informed non-experts’ but at the same time attuned to existing, more sophisticated analysis tools.

Usability and Suitability of the Omics-Integrating Analysis Platform tranSMART for Translational Research and Education

“…We additionally recommend the provision of context-sensitive information about the application and the background of statistical methods for the user if requested. This has also been stressed by Bauer et al 14 The majority of the researchers considered tranSMART to be useful for their daily work and stated that the missing availability of a research platform such as tranSMART remains a potential restriction for their research. Our results show that the need for such a platform is very high (at least in case of scenarios/tasks of this kind and with a patient cohort of at least 10-20 patients)-independent of the participants' experience or focus.…”

“…Some publications compare or explain such platforms only from the technical point of view. 7,11,12 Others describe their usage in studies 2,3,[13][14][15] or in connection with other platforms or technologies. [16][17][18] This indicates a substantial need for further research.…”

Implementation of a National Framework to Promote Health Data Sharing

“…The goal of the MI-I is to achieve and maintain interoperability and the roadmap is based on four pillars: (1) standards, (2) coordination and iterative approaches, (3) intensive cooperation, and (4) risk management and monitoring. The stepwise approach starts with milestones around the standardization of patient consent and data use agreement in different refinement steps.…”

“…Sharing health data has been a major topic in medical informatics research in Germany in the last two decades. The latest developments show that the interdisciplinary collaboration between the fields of medical bioinformatics and systems medicine has remarkably progressed, and innovative solutions to foster health data sharing have been presented by various German research groups, e.g., requirements for data integration platforms [1,2], the role of medical informatics for systems medicine [3,4], the interconnection of system architectures for rare disease registries [5], or information technology (IT) supported patient recruitment [6].…”

The Physics behind Systems Biology

“…Accordingly, methods from Bioinformatics and Systems Biology need to be adapted (or even newly developed) for the context of clinical data [66]. The resulting new field, Systems Medicine [67], sets out to offer a multi-'omics' view on patient cohorts.…”