Identification of diagnostic and prognostic biomarkers to improve the management of diabetes-related ulcers
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Publication: Asian Pacific Journal of Tropical Disease
Start Page: 228
Introduction: Diabetes-related ulcers are a common and severe complication of diabetes which is expected to increase in prevalence in line with projected global growth in rates of diabetes. Caring for these chronic wounds imposes a multi-billion dollar burden on the health care systems. These ulcers can prove lethal if untreated or not recognised and can lead to critical health complications.
Methods: To investigate underlying causes of wound chronicity, proteomic analyses of swab samples collected weekly from healing and non-healing diabetic foot ulcers was performed. Protein profiling was conducted based on Surface Enhanced Laser Desorption Ionisation Time of Flight (SELDI-TOF) mass spectrometry and statistical softwares were used to short list potential biomarkers. In addition, bottom-up proteomics was performed on healing and non-healing samples by SDS-PAGE and LC-MS/MS analysis using an AB SCIEX Triple TOF ® 5600 System. Trans-proteomic pipeline was used for data analyses and X! Tandem was used to search the database. Label-free quantitative proteomic analyses were performed using a computational tool called Abacus.
Results: (1) Statistical analyses of healing and non healing samples analysed on SELDI-TOF revealed 5 and 7 potential biomarkers (m/z) for samples with Texas score A1 and C1 respectively. (2) Bottom-up proteomics approach from both healing and non-healing samples identified 15 unique (healing) and 16 unique (non-healing) potential biomarkers. (3) Quantitative proteomic analyses resulted in 24 and 45 up-regulated healing candidates and 67 and 43 up-regulated nonhealing candidates for Texas score A1 and C1 wounds. (4) Relative quantification of 23 proteins related to oxidative stress has been identified through Abacus and 5/23 proteins have been validated using ELISA.
Conclusions: We are investigating these potential biomarkers using various biochemical, bioinformatics and statistical tools. A thorough investigation and study of the patterns may generate new protein candidates that can be used as potential prognostic and diagnostic biomarkers to improve the management of diabetic ulcers. Â© 2014 Asian Pacific Tropical Medicine Press.