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Suchon, P.

Publications and source records attributed to Suchon, P..

2 recordsLinked to original sources

ABO blood group, glycosyltransferase activity and risk of Venous Thrombosis

IntroductionABO blood group influence the risk of venous thrombosis (VT) by modifying A and B glycosyltransferases (AGT and BGT) activities that further modulates Factor VIII (FVIII) and von Willebrand Factor (VWF) plasma levels. The aim of this work was to evaluate the association of plasma GTs activities with VWF/FVIII plasma levels and VT risk in a case-control study. Materials and Methods420 cases were matched with 420 controls for age and ABO blood group. GT activities in plasma were measured using the quantitative transfer of tritiated N-acetylgalactosamine or galactose to the 2-fucosyl-lactose and expressed in disintegration per minute/30{micro}L of plasma and 2 hours of reaction (dpm/30{micro}L/2H). FVIII and VWF plasma levels were respectively measured using human FVIII-deficient plasma in a 1-stage factor assay and STA LIATEST VWF (Diagnostica Stago). ResultsA and B GT activities were significantly lower in cases than in controls (8119{+/-}4027 vs 9682{+/-}4177 dpm/30{micro}L/2H, p=2.03 x 10-5, and 4931{+/-}2305 vs 5524{+/-}2096 dpm/30{micro}L/2H, p=0.043 respectively). This association was observed whatever the ABO blood groups. The ABO A1 blood group was found to explain[~]80% of AGT activity. After adjusting for ABO blood groups, AGT activity was not correlated to VWF/FVIII plasma levels. Conversely, there was a moderate correlation ({rho}[~]0.30) between BGT activity and VWF/ FVIII plasma levels in B blood group carriers. ConclusionThis work showed, for the first time, that GT activities were decreased in VT patients in comparison to controls with the same ABO blood group. The biological mechanisms responsible for this association remained to be determined.

pathology

OPTIMIR, a novel algorithm for integrating available genome-wide genotype data into miRNA sequence alignment analysis.

Next-generation sequencing is an increasingly popular and efficient approach to characterize the full set of microRNAs (miRNAs) present in human biosamples. MiRNAs detection and quantification still remain a challenge as they can undergo different post transcriptional modifications and might harbor genetic variations (polymiRs) that may impact on the alignment step. We present a novel algorithm, OPTIMIR, that incorporates biological knowledge on miRNA editing and genome-wide genotype data available in the processed samples to improve alignment accuracy. OPTIMIR was applied to 391 human plasma samples that had been typed with genome-wide genotyping arrays. OPTIMIR was able to detect genotyping errors, suggested the existence of novel miRNAs and highlighted the allelic imbalance expression of polymiRs in heterozygous carriers. OPTIMIR is written in python, and freely available on the GENMED website (http://www.genmed.fr/index.php/fr/) and on Github (github.com/FlorianThibord/OptimiR).

bioinformatics