Background and Aims: Recent genome-wide association studies have shown that low-density lipoprotein receptor (LDLR) rs1433099 polymorphism is associated with cardiovascular disease (CVD) risk in many countries. However, the association of LDLR rs1433099 with CVD in China has not been reported yet. There are no studies on LDLR rs1433099 and non-alcoholic fatty liver disease (NAFLD) as well. The purpose of this study was to investigate whether LDLR rs1433099 is related to CVD or NAFLD in the Chinese population. Methods: LDLR rs1433099 polymorphism was genotyped in 507 individuals, including 140 healthy controls, 79 NAFLD patients, 185 CVD patients, and 103 patients with NAFLD combined with CVD. The expression of LDLR was tested by the sequence detection system, and clinical parameters were assessed by biochemical tests and physical examination. Results: The genotype distribution of LDLR rs1433099 was not statistically different among the NAFLD group, the CVD group, the combined group, and the healthy control group (p>0.05). There was no significant correlation of LDLR rs1433099 genotypic distribution or allele frequency and the risk of NAFLD, CVD or NAFLD combined with CVD (p>0.05). In the CVD group, T allele carriers had higher alkaline phosphatase and gamma-glutamyl transpeptidase than non-carriers (p<0.05). Conclusions: Our study demonstrated that the LDLR rs1433099 polymorphism is not a risk factor of NAFLD. The LDLR rs1433099 polymorphism may increase the risk of CVD through a mechanism involving alkaline phosphatase and gamma-glutamyl transpeptidase.
The Fault tree analysis has large limitations in the application of complex fault diagnosis system, which is difficult to solve complex system fault diagnosis polymorphism exhibited events, uncertainty of information, failure logical relationship and other issues, this paper presents a novel Bayesian network method , which can solve these problems better. This paper is taking an example of faulting diagnosis of the fan system to verify the effectiveness of this new method.
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