Gene expression profiling of patients affected by first acute myocardial infarction (FAMI)

Background: Myocardial infarction (MI) is the single most critical event in coronary disease. Platelets partecipate in processes that precipitate acute MI, lack nuclear DNA but retain megakaryocyte mRNAs, thus their transcriptome could provide information preceding the coronary event. Our aim was to obtain a gene expression atlas of platelets from patients with their very first acute MI (FAMI) in order to identify potential markers of precipitating factors. Methods and results: Platelets from seventeen FAMI patients and matched controls were collected and RNA and protein were purified. Expression profiles were obtained with genome-wide microarrays. Platelet-specific proteomic analysis was also performed with fluorescent DIGE separation in the same samples. Strong transcriptional down-regulation was observed in patient platelets, whereas more balanced numbers of up and down-represented proteins were found by proteomic analysis. Conclusions: Platelet transcriptome revealed quantitative differences between FAMI patients and controls. The functional analysis deregulated mRNAs and the integration with proteomic data in platelets may suggest pre-activation of platelets and/or megakaryocytes in FAMI patients before the acute event. We have selected a group of seventeen patients affected by their very first acute myocardial infarction (FAMI), without any sign of previous cardiovascular sufferance. Whole blood was collected within 6 hours from the acute event and freshly purified platelets were used to profile their mRNA population by DNA microarrays. We performed microarray experiments using the CodeLink Expression Bioarray System (GE Healthcare). Total RNA (1.5 µg) was amplified and biotin-labeled using the CodeLink Expression Assay Reagent Kit following the manufacturer’s protocol. Microarray data analysis identified 712 specifically modulated transcripts, out of 17,594, in FAMI patients, compared with normal controls; the majority (666) was down-regulated, and only 46 genes resulted up-regulated. The main result was that all the patients share some common mechanism that leads to a massive and statistical relevant transcript down-regulation.