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Updated: Aug 1, 2025

Ultrasonic Assessment of Myocardial Microstructure
Published on: January 14, 2014
An integrated signature of extracellular matrix proteins and a diastolic function imaging parameter predicts post-MI
Hiromi W L Koh1,2, Anna P Pilbrow3, Sock Hwee Tan1,4
1Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Insights
Identifying new biomarkers after acute myocardial infarction (AMI) is crucial for predicting secondary outcomes. Post-discharge levels of E/e
Area of Science:
- Cardiovascular Medicine
- Biomarker Discovery
- Proteomics and Lipidomics
Background:
- Patients with acute myocardial infarction (AMI) face risks of major adverse cardiovascular events (MACE) and heart failure (HF).
- Post-discharge molecular phenotyping and cardiac imaging can aid in risk stratification for these secondary outcomes.
Purpose of the Study:
- To identify predictive signatures for long-term secondary outcomes in AMI patients using integrated molecular and imaging data.
- To assess the prognostic potential of these signatures in an independent cohort.
Main Methods:
- A prospective AMI cohort (N=464) underwent plasma protein and lipid measurement 30 days post-discharge.
- A unified partial correlation network was created with echocardiographic and clinical biomarkers.
- A network-based approach (iOmicsPASS+) identified predictive subnetworks, validated in a Singapore cohort (N=190).
Main Results:
- Plasma proteins and lipids showed distinct correlation structures with imaging and clinical biomarkers.
- Network signatures identified 211 (MACE) and 189 (HF) predictive features, primarily imaging parameters and ECM-related proteins.
- The combination of NT-proBNP and EFEMP1 achieved an AUC of 0.80 for HF prediction; E/e', EFEMP1, and FSTL3 showed comparable or superior performance to NT-proBNP and LV measures.
Conclusions:
- E/e', EFEMP1, and FSTL3 show promise as complementary biomarkers for secondary adverse outcomes post-AMI.
- These markers, particularly diastolic function and specific ECM proteins, offer valuable prognostic information.
Background:
Patients suffering from acute myocardial infarction (AMI) are at risk of secondary outcomes including major adverse cardiovascular events (MACE) and heart failure (HF). Comprehensive molecular phenotyping and cardiac imaging during the post-discharge time window may provide cues for risk stratification for the outcomes.
Materials And Methods:
In a prospective AMI cohort in New Zealand (N = 464), we measured plasma proteins and lipids 30 days after hospital discharge and inferred a unified partial correlation network with echocardiographic variables and established clinical biomarkers (creatinine, c-reactive protein, cardiac troponin I and natriuretic peptides). Using a network-based data integration approach (iOmicsPASS+), we identified predictive signatures of long-term secondary outcomes based on plasma protein, lipid, imaging markers and clinical biomarkers and assessed the prognostic potential in an independent cohort from Singapore (N = 190).
Results:
The post-discharge levels of plasma proteins and lipids showed strong correlations within each molecular type, reflecting concerted homeostatic regulation after primary MI events. However, the two molecular types were largely independent with distinct correlation structures with established prognostic imaging parameters and clinical biomarkers. To deal with massively correlated predictive features, we used iOmicsPASS + to identify subnetwork signatures of 211 and 189 data features (nodes) predictive of MACE and HF events, respectively (160 overlapping). The predictive features were primarily imaging parameters, including left ventricular and atrial parameters, tissue Doppler parameters, and proteins involved in extracellular matrix (ECM) organization, cell differentiation, chemotaxis, and inflammation. The network signatures contained plasma protein pairs with area-under-the-curve (AUC) values up to 0.74 for HF prediction in the validation cohort, but the pair of NT-proBNP and fibulin-3 (EFEMP1) was the best predictor (AUC = 0.80). This suggests that there were a handful of plasma proteins with mechanistic and functional roles in predisposing patients to the secondary outcomes, although they may be weaker prognostic markers than natriuretic peptides individually. Among those, the diastolic function parameter (E/e' - an indicator of left ventricular filling pressure) and two ECM proteins, EFEMP1 and follistatin-like 3 (FSTL3) showed comparable performance to NT-proBNP and outperformed left ventricular measures as benchmark prognostic factors for post-MI HF.
Conclusion:
Post-discharge levels of E/e', EFEMP1 and FSTL3 are promising complementary markers of secondary adverse outcomes in AMI patients.
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