| Background and Objective:Studies showed that the metabolic disorder of lipid and inflammatory factor in blood might lead to the injury of endangium, and then generate artherosclerosis gradually. The narrow degree of coronary artery and atheromatous plaque texture are evaluated by imageology characteristics. However, it is difficult to distinguish plaque characteristics and composition. Our team plans to carry out related studies and raise the blood imprinting theory that reflects the plaque characteristics. We want to evaluate the risk degree of cardiovascular disease by analyzing blood related gene expressing profile, cytokines profile and lipid metabolism profile.Material and Methods:Up to 205 imageology characteristics from health control group, having no clinical symptom group and having clinical symptom group are analyzed by Dual source CT. Subjects were divided into group A (control group without plaque), group B (calcification group) and group C (none calcification group, and combination group). Using GeXP technology to analyze cardiovascular disease related gene expression profile in peripheral blood including IL-β, IL-6, IL-8, IFN-γ, MCP-1, VWF, MTHFR, L-Selectin, TNFa, Ubiquitin, MCSF, ICAM-1, ID2, HMOX-1 and LDL-R.10 items of cytokines expression profile were detected by liquid chip method including IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IFN-γ, MCP-1, TNFa and GM-CSF. The variations of blood lipid and hsCRP level were evaluated on Hitachi automatic analyzer. The n-3 index from peripheral blood was detected by Gas Chromatography method.Results:Compared with control group, the level of systolic blood pressure, GLU, TC, TG, APOB, APOC2 and hsCRP increased in group C and it has significant statistic difference. Discriminant analysis showed that 85.7% of group C cases were correctly classifiled. These 7 items yield an AUC (area under curve) of 0.720 in discriminating group C patients from control group with sensitivity of 60.5% and specificity of 76.8%. There was no significant different item between calcification group and control group.Multi-PCR systems for analyzing 17 genes were set up and optimized using GeXP technic. The within-run and between-run CV values were 3.695%-12.537% and 4.405%-13.405% respectively. We detected 15-gene expression profile in plaque group and control group with the method described as above, and found expression of IL-1β,IL-6, IL-8, MCP1 were significantly different between group C (without diabetes) and control group.Peripheral blood cytokine levels showed that IL-6 of group C increased significantly compared with control group. IL-6 yields an AUC of 0.592 in discriminating group C patients from control group with sensitivity of 78.0% and specificity of 39.7%.n-3 index and n-6/n-3 from peripheral blood of different plaque group were analyzed and results showed an increasing trend in plaque group.A diagnostic model was set up by IL-6 combined with biochemical items, which yield an AUC of 0.746 in discriminating group C from control group with sensitivity of 78.0% and specificity of 65.1%.Conclusion:In conclusion, Multi-PCR systems for analyzing 17 genes and Gas Chromatography for detecting n-3 index from peripheral blood were set up. Diagnostic model was established to distinguish group C from control group with detecting the level of blood lipid, peripheral blood gene expression profile and cytokines, which could provide useful laboratory information for risk assessment of cardiovascular disease patients.
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