Identification of new pancreatic beta cell targets for in vivo imaging by a systems biology approach
- Author
- Thomas Bouckenooghe, Daisy Flamez (UGent) , Fernanda Ortis, Serge Goldman and Decio L Eizirik
- Organization
- Abstract
- Systems biology is an emergent field that aims to understand biological systems at system-level. The increasing power of genome sequencing techniques and ranges of other molecular biology techniques is enabling the accumulation of in-depth knowledge of biological systems. This growing information, properly quantified, analysed and presented, will eventually allow the establishment of a system-based cartography of different cellular populations within the organism, and of their interactions at the tissue and organ levels. It will also allow the identification of specific markers of individual cell types. Systems biology approaches to discover diagnostic markers may have an important role in diabetes. There are presently no reliable ways to quantify beta cell mass (BCM) in vivo, which hampers the understanding of the pathogenesis and natural history of diabetes, and the development of novel therapies to preserve BCM. To solve this problem, novel and specific beta cell biomarkers must be identified to enable adequate in vivo imaging by methods such as Positron Emission Tomography (PET). The ideal biomarker should allow measurements by a minimally invasive technology enabling repeated examinations over time, should identify the early stages of decreased BCM, and should provide information on progression of beta cell loss and eventual responses to agents aiming to arrest or revert beta cell loss in diabetes. The present review briefly describes the "state-of-the-art" in the field, and then proposes a step-by-step systems biology approach for the identification and initial testing of novel candidates for beta cell imaging.
- Keywords
- HUMAN TRANSCRIPTOME, beta cell mass, PROTEIN MICROARRAYS, CLINICAL-APPLICATIONS, NONINVASIVE ASSESSMENT, DROSOPHILA-MELANOGASTER, GLIBENCLAMIDE DERIVATIVES, GENE-EXPRESSION, NONOBESE DIABETIC MICE, CYTOKINE-INDUCED DYSFUNCTION, POSITRON-EMISSION-TOMOGRAPHY, system biology, diabetes mellitus, beta cell imaging, Pancreatic beta cells
Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-1072865
- MLA
- Bouckenooghe, Thomas, et al. “Identification of New Pancreatic Beta Cell Targets for in Vivo Imaging by a Systems Biology Approach.” CURRENT PHARMACEUTICAL DESIGN, vol. 16, no. 14, 2010, pp. 1609–18.
- APA
- Bouckenooghe, T., Flamez, D., Ortis, F., Goldman, S., & Eizirik, D. L. (2010). Identification of new pancreatic beta cell targets for in vivo imaging by a systems biology approach. CURRENT PHARMACEUTICAL DESIGN, 16(14), 1609–1618.
- Chicago author-date
- Bouckenooghe, Thomas, Daisy Flamez, Fernanda Ortis, Serge Goldman, and Decio L Eizirik. 2010. “Identification of New Pancreatic Beta Cell Targets for in Vivo Imaging by a Systems Biology Approach.” CURRENT PHARMACEUTICAL DESIGN 16 (14): 1609–18.
- Chicago author-date (all authors)
- Bouckenooghe, Thomas, Daisy Flamez, Fernanda Ortis, Serge Goldman, and Decio L Eizirik. 2010. “Identification of New Pancreatic Beta Cell Targets for in Vivo Imaging by a Systems Biology Approach.” CURRENT PHARMACEUTICAL DESIGN 16 (14): 1609–1618.
- Vancouver
- 1.Bouckenooghe T, Flamez D, Ortis F, Goldman S, Eizirik DL. Identification of new pancreatic beta cell targets for in vivo imaging by a systems biology approach. CURRENT PHARMACEUTICAL DESIGN. 2010;16(14):1609–18.
- IEEE
- [1]T. Bouckenooghe, D. Flamez, F. Ortis, S. Goldman, and D. L. Eizirik, “Identification of new pancreatic beta cell targets for in vivo imaging by a systems biology approach,” CURRENT PHARMACEUTICAL DESIGN, vol. 16, no. 14, pp. 1609–1618, 2010.
@article{1072865,
abstract = {{Systems biology is an emergent field that aims to understand biological systems at system-level. The increasing power of genome sequencing techniques and ranges of other molecular biology techniques is enabling the accumulation of in-depth knowledge of biological systems. This growing information, properly quantified, analysed and presented, will eventually allow the establishment of a system-based cartography of different cellular populations within the organism, and of their interactions at the tissue and organ levels. It will also allow the identification of specific markers of individual cell types.
Systems biology approaches to discover diagnostic markers may have an important role in diabetes. There are presently no reliable ways to quantify beta cell mass (BCM) in vivo, which hampers the understanding of the pathogenesis and natural history of diabetes, and the development of novel therapies to preserve BCM. To solve this problem, novel and specific beta cell biomarkers must be identified to enable adequate in vivo imaging by methods such as Positron Emission Tomography (PET). The ideal biomarker should allow measurements by a minimally invasive technology enabling repeated examinations over time, should identify the early stages of decreased BCM, and should provide information on progression of beta cell loss and eventual responses to agents aiming to arrest or revert beta cell loss in diabetes. The present review briefly describes the "state-of-the-art" in the field, and then proposes a step-by-step systems biology approach for the identification and initial testing of novel candidates for beta cell imaging.}},
author = {{Bouckenooghe, Thomas and Flamez, Daisy and Ortis, Fernanda and Goldman, Serge and Eizirik, Decio L}},
issn = {{1381-6128}},
journal = {{CURRENT PHARMACEUTICAL DESIGN}},
keywords = {{HUMAN TRANSCRIPTOME,beta cell mass,PROTEIN MICROARRAYS,CLINICAL-APPLICATIONS,NONINVASIVE ASSESSMENT,DROSOPHILA-MELANOGASTER,GLIBENCLAMIDE DERIVATIVES,GENE-EXPRESSION,NONOBESE DIABETIC MICE,CYTOKINE-INDUCED DYSFUNCTION,POSITRON-EMISSION-TOMOGRAPHY,system biology,diabetes mellitus,beta cell imaging,Pancreatic beta cells}},
language = {{eng}},
number = {{14}},
pages = {{1609--1618}},
title = {{Identification of new pancreatic beta cell targets for in vivo imaging by a systems biology approach}},
volume = {{16}},
year = {{2010}},
}