Women experienced the same or greater decreases in platelet reactivity after aspirin therapy, retaining modestly more platelet reactivity compared with men. However, most women achieved total suppression of aggregation in the direct COX-1 pathway, the putative mechanism for aspirin's cardioprotection.

Genetic variation is thought to contribute to variability in platelet function; however, the specific variants and mechanisms that contribute to altered platelet function are poorly defined. With the use of a combination of fine mapping and sequencing of the platelet endothelial aggregation receptor 1 (PEAR1) gene we identified a common variant (rs12041331) in intron 1 that accounts for < 15% of total phenotypic variation in platelet function. Association findings were robust in 1241 persons of European ancestry (P ‫؍‬ 2.22 ؋ 10 ؊8 ) and were replicated down to the variant and nucleotide level in 835 persons of African ancestry (P ‫؍‬ 2.31 ؋ 10 ؊27 ) and in an independent sample of 2755 persons of European descent (P ‫؍‬ 1.64 ؋ 10 ؊5 ). Sequencing confirmed that variation at rs12041331 accounted most strongly (P ‫؍‬ 2.07 ؋ 10 ؊6 ) for the relation between the PEAR1 gene and platelet function phenotype. A doseresponse relation between the number of G alleles at rs12041331 and expression of PEAR1 protein in human platelets was confirmed by Western blotting and ELISA. Similarly, the G allele was associated with greater protein expression in a luciferase reporter assay. These experiments identify the precise genetic variant in PEAR1 associated with altered platelet function and provide a plausible biologic mechanism to explain the association between variation in the PEAR1 gene and platelet function phenotype. (Blood. 2011;118(12):3367-3375)

BackgroundThe introduction of benchtop sequencers has made adoption of whole genome sequencing possible for a broader community of researchers than ever before. Concurrently, metagenomic sequencing (MGS) is rapidly emerging as a tool for interrogating complex samples that defy conventional analyses. In addition, next-generation sequencers are increasingly being used in clinical or related settings, for instance to track outbreaks. However, information regarding the analytical sensitivity or limit of detection (LoD) of benchtop sequencers is currently lacking. Furthermore, the specificity of sequence information at or near the LoD is unknown.ResultsIn the present study, we assess the ability of three next-generation sequencing platforms to identify a pathogen (viral or bacterial) present in low titers in a clinically relevant sample (blood). Our results indicate that the Roche-454 Titanium platform is capable of detecting Dengue virus at titers as low as 1X102.5 pfu/mL, corresponding to an estimated 5.4X104 genome copies/ml maximum. The increased throughput of the benchtop sequencers, the Ion Torrent PGM and Illumina MiSeq platforms, enabled detection of viral genomes at concentrations as low as 1X104 genome copies/mL. Platform-specific biases were evident in sequence read distributions as well as viral genome coverage. For bacterial samples, only the MiSeq platform was able to provide sequencing reads that could be unambiguously classified as originating from Bacillus anthracis.ConclusionThe analytical sensitivity of all three platforms approaches that of standard qPCR assays. Although all platforms were able to detect pathogens at the levels tested, there were several noteworthy differences. The Roche-454 Titanium platform produced consistently longer reads, even when compared with the latest chemistry updates for the PGM platform. The MiSeq platform produced consistently greater depth and breadth of coverage, while the Ion Torrent was unequaled for speed of sequencing. None of the platforms were able to verify a single nucleotide polymorphism responsible for antiviral resistance in an Influenza A strain isolated from the 2009 H1N1 pandemic. Overall, the benchtop platforms perform well for identification of pathogens from a representative clinical sample. However, unlike identification, characterization of pathogens is likely to require higher titers, multiple libraries and/or multiple sequencing runs.