The present project aims to determine whether a deficit in migration of stem cells could be implicated in the failure to mount an adequate collateralization after Myocardial Infarction (MI) and thereby facilitate the development of post-ischemic heart failure (HF) and to dissect underlying molecular mechanisms. Furthermore, the investigators wish to determine the predictive value of stem cell migration assay in patients with MI.
MAIN OBJECTIVES OF THE STUDY: Characterization of circulating CD133+ stem cells in a group of 170 patients with MI (mean post-MI follow up, 6 months): * Counting total mononuclear cells and FACS analysis of CD133 stem cells. * Characterization of CD133+ stem cell biology: Migratory assay, imaging of cytoskeleton, angiogenesis tests in vitro. * Evaluation of migratory signalling, with specific focus on the PI3K/Akt/eNOS system. Assessment of the prognostic value of the stem cell migration assay. * Relationship between cell biology tests on CD133+ cells and changes in circulating cytokines and pro-angiogenic factors after MI. * Assessment of area at risk by ECG-synchronized Single Photon Emission Computed Tomography (gated-SPECT) in subgroups with different patterns of stem cell migratory tests. * Assessment of ventricular remodelling (echocardiography, NMR) in relation with patterns of stem cell migratory test. EXPECTED RESULTS: Clarification of the implication of stem cell migratory deficit in post-ischemic HF. * Identification of underlying mechanisms * Identification of a cellular marker for prediction of patients at risk of HF. RELEVANCE TO PUBLIC HEALTH: * Introduction of a biological test for the early diagnosis of post-MI HF * Recognition of therapeutic targets for the rescue of stem cell migratory liabilities
Study Type
OBSERVATIONAL
Enrollment
170
Cardiology Dept. Arcispedale S.Anna
Ferrara, Italy
IRCCS Multimedica
Milan, Italy
Prognostic value of CD133+ stem cells in MI
Correlation of clinical parameters of disease evolution and biological features
Time frame: 12 months
Correlation of disease evolution and other biomarkers
Time frame: 12 months
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