Metabolomic Analysis of Platelets of Patients With Aspirin Non-Response.

Background: Aspirin is the most commonly used antiplatelet agent for the prevention of cardiovascular diseases. However, a certain proportion of patients do not respond to aspirin therapy. The mechanisms of aspirin non-response remain unknown. The unique metabolomes in platelets of patients with coronary artery disease (CAD) with aspirin non-response may be one of the causes of aspirin resistance. Materials and Methods: We enrolled 29 patients with CAD who were aspirin non-responders, defined as a study subject who were taking aspirin with a platelet aggregation time less than 193 s by PFA-100, and 31 age- and sex-matched patients with CAD who were responders. All subjects had been taking 100 mg of aspirin per day for more than 1 month. Hydrophilic metabolites from the platelet samples were extracted and analyzed by nuclear magnetic resonance (NMR). Both 1D 1H and 2D J-resolved NMR spectra were obtained followed by spectral processing and multivariate statistical analysis, such as partial least squares discriminant analysis (PLS-DA). Results: Eleven metabolites were identified. The PLS-DA model could not distinguish aspirin non-responders from responders. Those with low serum glycine level had significantly shorter platelet aggregation time (mean, 175.0 s) compared with those with high serum glycine level (259.5 s). However, this association became non-significant after correction for multiple tests. Conclusions: The hydrophilic metabolic profile of platelets was not different between aspirin non-responders and responders. An association between lower glycine levels and higher platelet activity in patients younger than 65 years suggests an important role of glycine in the pathophysiology of aspirin non-response.

Use of groESL as a target for identification of Abiotrophia, Granulicatella, and Gemella species.

We determined the groESL sequences of three species of nutritionally variant streptococci (Abiotrophia defectiva, Granulicatella adiacens, and Granulicatella elegans) and three Gemella species (Gemella morbillorum, Gemella haemolysans, and Gemella sanguinis). The nucleotide sequence similarities between the groES and groEL genes of the above genera were 41.7 to 85.9% and 63.7 to 84.3%, respectively. The intraspecies similarities of groESL sequences for the isolates of Abiotrophia and Granulicatella species were 94.4 to 97.8% for groES and 94.0 to 98.2% for groEL. For Ge. morbillorum and Ge. sanguinis, all strains showed the same groESL spacer length (8 bp), and sequence identities within species were >97.8% for groES and >96.1% for groEL. However, higher intraspecies heterogeneity was observed in Ge. haemolysans. Phylogenetic analysis of groEL sequences separated the 6 isolates of Ge. haemolysans into two subgroups. Among these isolates, three isolates with the same groESL spacer region length (45 bp) clustered together but were distant from the ATCC reference strain (with a spacer length of 8 bp). The remaining three isolates, with a spacer length of 50 or 8 bp, clustered together. Although 16S rRNA gene sequence analysis did not provide enough discrimination for the 6 Ge. haemolysans isolates, rpoB gene sequence analysis supported the subgrouping. Based on the obtained groESL sequences, we developed a multiplex PCR that enables simple, rapid, and accurate identification of Abiotrophia, Granulicatella, and Gemella at the genus level. This assay would be helpful for identifying these fastidious and slow-growing organisms in clinical laboratories.