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Home › Dataset Library › Characterisation of Myocardial Infarction and Unstable Angina with mRNA Profiles from Whole Blood of individual patients

Dataset: Characterisation of Myocardial Infarction and Unstable Angina with mRNA Profiles from Whole Blood of individual patients

Coronary artery disease (CAD) remains a leading cause of death worldwide. Acute coronary syndromes (ACS) are the spectrum of diseases...

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Coronary artery disease (CAD) remains a leading cause of death worldwide. Acute coronary syndromes (ACS) are the spectrum of diseases arising from coronary atherosclerotic plaque rupture, ranging from unstable angina (UA; clinical symptoms of cardiac ischemia without myocardial necrosis) to myocardial infarction (MI; clinical symptoms of cardiac ischemia with myocardial necrosis). We use microrray to identify changes in pathways following MI.This study examines mRNA expression levels in human whole blood at 7 and 30 days post ACS. Patients with MI are compared to those with UA (not healthy controls), thus focusing on differences in mRNA expression due to the acute clinical events rather than underlying atherosclerosis and its treatment. We recruited 26 patients presenting with acute coronary syndromes (ACS); 8 with unstable angina (UA) and 18 with MI. Supplementary files: The files contain the combined values (for each group) of the single patients' expression levels, the fold changes and the significance levels associated. Gene expression levels were estimated using probabilistic models implemented in puma (Propagating Uncertainty in Microarray Analysis, bioconductor.org), which provide estimates for the variance and credibility interval for probe level errors of each transcript. FCs were calculated after combining gene expression values within groups using Bayesian hierarchical model, incorporating probe level errors into the variance estimate. Significance levels for differentially expressed genes were detected by calculating the probability of positive log ratio (PPLR). The higher is the probability the more confident is the estimate of that positive FC, conversely the lower is the probability the more confident is the estimate of that FC to be negative. This model was implemented in the pumaComb and pumaDE modules within puma. file1 = mRNA_MI_combday30_exprs file2 = mRNA_MI_combDay7_exprs

Species:
human

Samples:
52

Source:
E-GEOD-29111

Updated:
Dec.12, 2014

Registered:
Sep.16, 2014


Factors: (via ArrayExpress)
Sample AGE TIME POINT DISEASE SEX
GSM720972 56 day 7 MI M
GSM720973 67 day 7 MI F
GSM720974 62 day 7 MI M
GSM720975 50 day 7 MI M
GSM720976 66 day 7 MI F
GSM720977 54 day 7 MI M
GSM720978 63 day 7 MI M
GSM720979 66 day 7 MI M
GSM720977 54 day 7 MI M
GSM72098 41 day 7 MI M
GSM720982 62 day 7 MI F
GSM720983 39 day 7 MI M
GSM720984 53 day 7 MI M
GSM720985 64 day 7 MI M
GSM720986 69 day 7 MI M
GSM720987 57 day 7 MI M
GSM720988 51 day 7 MI M
GSM72098 41 day 7 MI M
GSM720990 56 day 30 MI M
GSM72099 67 day 30 MI F
GSM720992 62 day 30 MI M
GSM720993 50 day 30 MI M
GSM720994 66 day 30 MI F
GSM720995 54 day 30 MI M
GSM720996 63 day 30 MI M
GSM720997 66 day 30 MI M
GSM720995 54 day 30 MI M
GSM720999 41 day 30 MI M
GSM721000 62 day 30 MI F
GSM72100 39 day 30 MI M
GSM721002 53 day 30 MI M
GSM721003 64 day 30 MI M
GSM721004 69 day 30 MI M
GSM721005 57 day 30 MI M
GSM721006 51 day 30 MI M
GSM720999 41 day 30 MI M
GSM721008 64 day 7 UA M
GSM721009 74 day 7 UA M
GSM721010 65 day 7 UA M
GSM7210 56 day 7 UA F
GSM721012 62 day 7 UA M
GSM721013 48 day 7 UA M
GSM721014 71 day 7 UA M
GSM721015 65 day 7 UA F
GSM721016 64 day 30 UA M
GSM721017 74 day 30 UA M
GSM721018 65 day 30 UA M
GSM721019 56 day 30 UA F
GSM721020 62 day 30 UA M
GSM72102 48 day 30 UA M
GSM721022 71 day 30 UA M
GSM721023 65 day 30 UA F

Tags

  • artery
  • artery disease
  • atherosclerosis
  • coronary artery
  • coronary artery disease
  • disease
  • ischemia
  • myocardial infarction
  • unstable angina

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