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Glycoproteomic Profiling Provides Candidate Myocardial Infarction Predictors of Later Progression to Heart Failure.

ABSTRACT: We hypothesized that identifying plasma glycoproteins that predict the development of heart failure following myocardial infarction (MI) could help to stratify subjects at risk. Plasma collected at visit 2 (2005-2008) from an MI subset of Jackson Heart Study participants underwent glycoproteomics and was grouped by the outcome: (1) heart failure hospitalization after visit 2 (n = 15) and (2) without hospitalization by 2012 (n = 45). Proteins were mapped for biological processes and functional pathways using Ingenuity Pathway Analysis and linked to clinical characteristics. A total of 198 glycopeptides corresponding to 88 proteins were identified (data available via ProteomeXchange with identifier PXD009870). Of these, 14 glycopeptides were significantly different between MI and MI + HF groups and corresponded to apolipoprotein (Apo) F, transthyretin, Apo C-IV, prostaglandin-D2 synthase, complement C9, and CD59 (p < 0.05 for all). All proteins were elevated in the MI + HF group, except CD59, which was lower. Four canonical pathways were upregulated in the MI + HF group (p < 0.05 for all): acute phase response, liver X receptor/retinoid X receptor, and macrophage reactive oxygen species generation. The coagulation pathway was significantly downregulated in the MI + HF group (p < 0.05). Even after adjustment for age and sex, Apo F was associated with the increased risk for heart failure (OR = 21.84; 95% CI 3.20-149.14). In conclusion, glycoproteomic profiling provided candidate early MI predictors of later progression to heart failure.

SUBMITTER: Deleon-Pennell KY

PROVIDER: S-EPMC6356850 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Glycoproteomic Profiling Provides Candidate Myocardial Infarction Predictors of Later Progression to Heart Failure.

Deleon-Pennell Kristine Y KY Ero Osasere K OK Ma Yonggang Y Padmanabhan Iyer Rugmani R Flynn Elizabeth R ER Espinoza Ingrid I Musani Solomon K SK Vasan Ramachandran S RS Hall Michael E ME Fox Ervin R ER Lindsey Merry L ML

ACS omega 20190115 1

We hypothesized that identifying plasma glycoproteins that predict the development of heart failure following myocardial infarction (MI) could help to stratify subjects at risk. Plasma collected at visit 2 (2005-2008) from an MI subset of Jackson Heart Study participants underwent glycoproteomics and was grouped by the outcome: (1) heart failure hospitalization after visit 2 (<i>n</i> = 15) and (2) without hospitalization by 2012 (<i>n</i> = 45). Proteins were mapped for biological processes and ...[more]

PMID: 30729226

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Project description:Background and objectivesEarly diagnosis of patients with acute myocardial infarction (AMI) who are at a high risk of heart failure (HF) progression remains controversial. This study aimed at identifying new predictive biomarkers of post-AMI HF and at revealing the pathogenesis of HF involving these marker genes.Methods and resultsA transcriptomic dataset of whole blood cells from AMI patients with HF progression (post-AMI HF, n = 16) and without progression (post-AMI non-HF, n = 16) was analyzed using the weighted gene co-expression network analysis (WGCNA). The results indicated that one module consisting of 720 hub genes was significantly correlated with post-AMI HF. The hub genes were validated in another transcriptomic dataset of peripheral blood mononuclear cells (post-AMI HF, n = 9; post-AMI non-HF, n = 8). PRKAR1A, SDCBP, SPRED2, and VAMP3 were upregulated in the two datasets. Based on a single-cell RNA sequencing dataset of leukocytes from heart tissues of normal and infarcted mice, PRKAR1A was further verified to be upregulated in monocytes/macrophages on day 2, while SDCBP was highly expressed in neutrophils on day 2 and in monocytes/macrophages on day 3 after AMI. Cell-cell communication analysis via the "CellChat" package showed that, based on the interaction of ligand-receptor (L-R) pairs, there were increased autocrine/paracrine cross-talk networks of monocytes/macrophages and neutrophils in the acute stage of MI. Functional enrichment analysis of the abovementioned L-R genes together with PRKAR1A and SDCBP performed through the Metascape platform suggested that PRKAR1A and SDCBP were mainly involved in inflammation, apoptosis, and angiogenesis. The receiver operating characteristic (ROC) curve analysis demonstrated that PRKAR1A and SDCBP, as well as their combination, had a promising prognostic value in the identification of AMI patients who were at a high risk of HF progression.ConclusionThis study identified that PRKAR1A and SDCBP may serve as novel biomarkers for the early diagnosis of post-AMI HF and also revealed their potentially regulatory mechanism during HF progression.

Dataset Information

Glycoproteomic Profiling Provides Candidate Myocardial Infarction Predictors of Later Progression to Heart Failure.

Publications

Glycoproteomic Profiling Provides Candidate Myocardial Infarction Predictors of Later Progression to Heart Failure.

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