Whole-Blood Transcriptome Profiling Identifies Women With Myocardial Infarction With Nonobstructive Coronary Artery Disease

Tessa J Barrett, Angela H Lee, Nathaniel R Smilowitz, Anais Hausvater, Glenn I Fishman, Judith S Hochman, Harmony R Reynolds, Jeffrey S Berger, Tessa J Barrett, Angela H Lee, Nathaniel R Smilowitz, Anais Hausvater, Glenn I Fishman, Judith S Hochman, Harmony R Reynolds, Jeffrey S Berger

No abstract available

Keywords: coronary artery disease; estrogens; myocardial infarction; sequence analysis, RNA; women.

Figures

Figure 1. Whole Blood Transcriptome Profiling Identifies…
Figure 1. Whole Blood Transcriptome Profiling Identifies Women with Myocardial infarction with Non-Obstructive Coronary Artery Disease (MINOCA).
Whole blood was collected into PAXgene Blood RNA tubes, RNA isolated and analyzed by RNA-sequencing (Illumina HiSeq4000 Sequencing). Participants were clustered in hierarchical condition trees with each row representing a single gene and each column an individual subject. Color scale indicates normalized expression values and colored bars indicate the individual’s clinical classification. (A) Transcript intensity for the top 1000 differentially expressed transcripts between MINOCA (n = 11) and control participants (n = 9). (B) Transcript intensity for the top 1000 differentially expressed transcripts between MINOCA (n = 11) and MI-CAD participants (n = 12). (C-D) Volcano plots of differential expressed genes in whole blood from MINOCA versus controls, and MINOCA versus MI-CAD patients. The y-axis corresponds to the p value (-log10), and the x-axis displays the log2 fold change. The red dots represent the significantly differential expressed transcripts (p<0.05). (E) Modular analysis approach. Gene expression levels were compared between MINOCA and MI-CAD or control subjects on a module-by-module basis. Modules correspond to previously identified co-regulated gene clusters that were assigned biological functions by unbiased literature profiling (see legend grid below). Over-abundance of transcripts in a module is depicted in red, under-abundance in blue. The intensity of the dot corresponds to the percentage of genes in the respective module that are significantly (p<0.05) differentially expressed between groups. (F) Canonical pathway analysis (IPA) of significantly differentially regulated transcripts (p<0.05) in MINOCA versus controls and MINOCA versus MI-CAD patients, and subsequent comparison of pathways identified. The significance of the association between transcript expression and a canonical pathway was measured by Fisher’s exact test, -log(p-value). Estrogen receptor signaling was identified as the top common canonical pathway differentially expressed in both comparisons (MINOCA versus controls, -log(P-value) 4.5; MINOCA versus MI-CAD, -log(P-value) 3.4), followed by mammalian target of rapamycin (mTOR) (MINOCA versus controls, -log(P-value) 4.9; MINOCA versus MI-CAD, -log(P-value) 2.5) and eukaryotic initiation factor 2 (eIF2) signaling (MINOCA versus controls, -log(P-value) 3.1; MINOCA versus MI-CAD, -log(P-value) 4.4) (G) Relative expression of whole blood transcripts linked to estrogen signaling as determined by RNA-sequencing in MINOCA (n = 11), MI-CAD (n = 12) and control (n = 9) subjects.

Source: PubMed

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