190 Metabonomics in Chronic Venous Disease - Local and Systemic Phenotypes. (28th February 2022)

• Record Type: Journal Article
• Authors: Adenipekun, A.; Bergner, R.; Onida, S.; Davies, A.
• Is Part Of: British journal of surgery. Volume 109(2022)Supplement 1
• Publication Date: 2022-02-28
• Subjects: Surgery -- Periodicals; 617.005
• DOI: 10.1093/bjs/znac039.115
• Languages: English
• ISSNs: 0007-1323

Abstract

Abstract: Aim: Chronic venous disease (CVD) describes a spectrum of clinical presentations associated with a poorly functioning venous system, ranging from asymptomatic venous disease to varicose veins, skin changes and venous leg ulceration. These conditions negatively impact on quality of life. There is evidence that 'local' blood sampled from lower limb veins contains different biomarkers to systemic blood, particularly with respect to inflammatory and prothrombotic mediators; however, the literature pertaining to metabolic phenotyping platforms is limited. The aim of this study was to assess whether the metabolic signatures in systemic serum differed from the signatures in truncal/varicose vein (local blood) in patients with CVD. Method: 64 patients presenting with CVD were recruited to participate in the study following clinical and duplex ultrasound assessment. Blood samples were collected from the antecubital fossa and from the lowermost refluxing vein or varicosity in the leg. Metabolic profiling was performed using Reversed-Phase Ultra Performance Liquid Chromatography (RP-UPLC) lipid profiling analysis. Univariate and multivariate statistical analysis were performed. Results: Principal component analysis (PCA) of overall spectral data showed no separation amongst metabolites. Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) revealed preliminary group differences between leg and arm samples, but this was not significant upon CV-ANOVA testing (P = 1) Conclusions: The analysis via RP-UPLC did not identify significant differences in the metabolic profile of systemic and local serum samples; however, this may be due to the limited sample size, or the platform employed. Future work will include performing the analysis employing complimentary metabolic phenotyping platforms and a larger sample size.