Determinants of excess genetic risk of acute myocardial infarction – a matched case-control study

Peripheral blood samples of patients with acute myocardial infarction were matched with those of control patients to identify possible differences in corresponding gene expression profiles. The controls were matched to cases based on gender, age, status of diabetes mellitus and smoking status. Six months cardiovascular survival status of the cases was used to identify two distinct subgroups among the cases. Linear models for microarray data (‘limma’) were employed to identify differential gene expression. Shrunken centroids technique helped in identifying the subsets of differentially expressed genes with predictive properties in independent samples. Predictive properties were evaluated using bootstrap sampling. Using the limma modeling with the log-fold change threshold of one (clinical significance) and Storey’s q-value approach (statistical significance), sixty transcripts were found to be both clinically and statistically differentially expressed among the cases not surviving the follow-up period relative to controls, while no such transcripts were observed among other surviving cases. The two subgroups of cases exhibited fourteen differentially expressed transcripts. Predictive modeling indicated sixteen out of sixty transcripts to best discriminate between the controls and cases who died during the follow-up period from cardiovascular causes, while for the surviving cases the already non-significant set of transcripts could not be further reduced. Eleven out of fourteen transcripts were found to best discriminate between the two groups of cases using shrunken centroids. The study identified genes, which were differentially expressed during the acute myocardial infarction, including those associated with short-term fatality of the cases.

keywords: NCBI GEO expression profiling by array

Project website
https://www.ncbi.nlm.nih.gov/bioproject/PRJNA149837
Start date
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End date
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Types
NCBI GEO
Main contact
Michal Kolář
Email
kolarmi@img.cas.cz
Affiliation
Institute of Computer Science, Academy of Sciences of the Czech Republic
Business Address
Pod Vodárenskou věží 2,Prague,CZ-18207,Czech Republic
Business Phone Number
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