Dataset Information

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 |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:OBJECTIVE:We hypothesized that Displacement Encoding with Stimulated Echoes (DENSE) and feature-tracking derived circumferential strain would provide incremental prognostic value over the extent of infarction for recovery of segmental myocardial function. METHODS:Two hundred and sixty-one patients (mean age 59 years, 73% male) underwent MRI 2 days post-ST elevation myocardial infarction (STEMI) and 241 (92%) underwent repeat imaging 6 months later. The MRI protocol included cine, 2D-cine DENSE, T2 mapping and late enhancement. Wall motion scoring was assessed by 2-blinded observers and adjudicated by a third. (WMS: 1=normal, 2=hypokinetic, 3=akinetic, 4=dyskinetic). WMS improvement was defined as a decrease in WMS???1, and normalization where WMS?=?1 on follow-up. Segmental circumferential strain was derived utilizing DENSE and feature-tracking. A generalized linear mixed model with random effect of subject was constructed and used to account for repeated sampling when investigating predictors of segmental myocardial improvement or normalization RESULTS: At baseline and follow-up, 1416 segments had evaluable data for all parameters. Circumferential strain by DENSE (p?<?0.001) and feature-tracking (p?<?0.001), extent of oedema (p?<?0.001), infarct size (p?<?0.001), and microvascular obstruction (p?<?0.001) were associates of both improvement and normalization of WMS. Circumferential strain provided incremental predictive value even after accounting for infarct size, extent of oedema and microvascular obstruction, for segmental improvement (DENSE: odds ratio, 95% confidence intervals: 1.08 per -1% peak strain, 1.05-1.12, p?<?0.001, feature-tracking: odds ratio, 95% confidence intervals: 1.05 per -1% peak strain, 1.03-1.07, p?<?0.001) and segmental normalization (DENSE: 1.08 per -1% peak strain, 1.04-1.12, p?<?0.001, feature-tracking: 1.06 per -1% peak strain, 1.04-1.08, p?<?0.001). CONCLUSIONS:Circumferential strain provides incremental prognostic value over segmental infarct size in patients post STEMI for predicting segmental improvement or normalization by wall-motion scoring.

Dataset Information

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure