Method for detecting novel cardiovascular disease risk marker by liquid chromatography-tandem mass spectrometry

Abstract

The invention belongs to the technical field of clinical biological sample detection, and particularly relates to a method for detecting trimethylamine oxide, choline, betaine, creatinine and L-carnitine in a biological sample through high-throughput liquid chromatography-tandem mass spectrometry. The method can simultaneously detect five substances in a biological sample, and has the advantages of high accuracy, high sensitivity, high specificity, small required sample volume, simple sample pretreatment, good tolerance and the like.

Description

technical field [0001] The invention relates to a method for detecting trimethylamine oxide, choline, betaine, L-carnitine and creatinine in biological samples by high-throughput liquid chromatography tandem mass spectrometry. Background technique [0002] The prevalence and mortality of cardiovascular disease (CVD) in China continue to rise, and the number of patients is about 290 million. CVD mortality ranks first among all causes, accounting for more than 40% of residents' disease deaths. At the same time, the burden of cardiovascular disease in China is increasing day by day and has become a major public health problem. With the development of social economy, the national lifestyle has undergone profound changes. Under the background of social aging and accelerated urbanization, and the prevalence of unhealthy lifestyles among residents, national CVD risk factors are generally exposed, and the prevalence of hypertension, dyslipidemia, and diabetes continues to increase...

AI Technical Summary

Problems solved by technology

[0009] 1. Most methods can only detect TMAO, which cannot meet clinical needs;

[0010] 2. The pretreatment method of biological samples is too complicated to be automated, and it is difficult to promote it to clinical application;

[0011] 3. The clinical significance of the detection markers is not clear, and there is not enough literature and data support

[0012] 4. There are too many irrelevant markers and the cost is too high

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