Inflammation blood and tissue factors of plaque growth in an experimental model evidenced by a systems approach.
OBJECTIVE
The multifactorial pathogenesis of coronary atherosclerotic lesion formation has been investigated in a swine model of high cholesterol diet induced atherogenesis and data processed by a systems approach.


METHODS
Farm pigs were fed on standard or high cholesterol diet of 8 and 16 weeks duration. Plasma assessment of total cholesterol, HDL, LDL, and ELISA of some cytokines and ICAM-1 were performed on baseline and end-diet samples. Segments of the right coronary artery were incubated for 24 h in serum-free medium to collect secreted proteins and their expression analyzed by mass spectrometry. Data of plasma and tissue factors were processed by a statistical systems inference approach: both histologic parameters of coronary intimal thickness (IT) and of lesion area (LA) were chosen as dependent variables (coronary atherosclerotic burden).


RESULTS
Relations among plasma adhesion molecules, cytokines, lipoproteins, tissue proteins and histology indexes were integrated in a model regression scheme. Bayesian model averaging (BMA) variable selection was chosen as a method to identify relevant factors associated to atherosclerotic burden: TNFα was identified as an associated plasma marker, oxLDL and HDL as relevant lipoproteins; macrophage function related antioxidant Catalase enzyme, lysosome associated Cathepsin D, S100-A10, and Transforming growth factor-beta-induced protein ig-h3 were identified and selected as associated to atherogenesis outcome.


CONCLUSIONS
The results of this systems approach are consistent with the hypothesis that, in high cholesterol diet-induced experimental atherogenesis, the interaction between plasma cytokines, lipoproteins and artery-specific proteins, influences lesion initiation and growth. In particular, some macrophage function related proteins are found significantly and positively associated to atherosclerotic burden, suggesting a novel molecular framework into the atherogenesis-inflammatory disorder.
Institute of Clinical Physiology, Consiglio Nazionale delle Ricerche Pisa, Italy.
Gualtiero
G
Pelosi
Institute of Clinical Physiology, Consiglio Nazionale delle Ricerche Pisa, Italy.
Silvia
S
Rocchiccioli
Institute of Clinical Physiology, Consiglio Nazionale delle Ricerche Pisa, Italy ; Department of Clinical and Experimental Medicine, University of Pisa Pisa, Italy.
Antonella
A
Cecchettini
Institute of Clinical Physiology, Consiglio Nazionale delle Ricerche Pisa, Italy.
Federica
F
Viglione
Institute of Clinical Physiology, Consiglio Nazionale delle Ricerche Pisa, Italy.
Mariarita
M
Puntoni
Institute of Clinical Physiology, Consiglio Nazionale delle Ricerche Pisa, Italy.
Oberdan
O
Parodi
Laboratory of Integrative Systems Medicine, Institute of Clinical Physiology, Consiglio Nazionale delle Ricerche Pisa, Italy ; Center for Computational Science, University of Miami Miami, FL, USA.
Enrico
E
Capobianco
Institute of Clinical Physiology, Consiglio Nazionale delle Ricerche Pisa, Italy.
Maria G
MG
Trivella
Bayesian model averaging; coronary atherogenesis; swine model; systems biomedicine; vascular inflammation