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Composition of marker for predicting prognosis of coronary heart disease and kit thereof

A technology of metabolites and coronary heart disease, applied in the field of coronary heart disease detection, can solve the problems of limited prediction efficiency and achieve the effect of improving prognosis and reducing mortality

Inactive Publication Date: 2018-10-23
BMK BIOMEDICAL TECH GUANGZHOU CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Despite increasing attention to metabolic abnormalities involved in cardiovascular disease, traditional risk factors explain only a small fraction of the disease state and have limited predictive power, requiring new research methods and biomarkers

Method used

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  • Composition of marker for predicting prognosis of coronary heart disease and kit thereof
  • Composition of marker for predicting prognosis of coronary heart disease and kit thereof
  • Composition of marker for predicting prognosis of coronary heart disease and kit thereof

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0075] Example 1 Combination analysis of metabolic markers for risk of death

[0076] 1. Experimental operation

[0077] 1. Case source

[0078] This study recruited 1040 patients with coronary heart disease, and all the selected patients signed the informed consent. All patients were sequentially enrolled between January 2010 and December 2013 according to the same inclusion and exclusion criteria. The average age of the research subjects was 63.03±10.04 years old, the average BMI was 24.28±4.79kg / m2, and about 80% were male. The clinical data of the patients included demographic data, past medical history, laboratory tests and past medication history. During the 5-year follow-up, there were 63 deaths and 183 MACEs among 1040 CHD patients.

[0079] The time of blood collection was in the morning on an empty stomach.

[0080] Follow-up information was collected on the basis of inpatient and hospital outpatient visits, and telephone follow-up of all enrolled patients or th...

Embodiment 2

[0108] Metabolic Marker Combination Analysis of Example 2 MACE Analysis

[0109] 1. Experimental operation

[0110] To identify combinations of metabolic markers associated with MACE risk, COX regression was used to analyze the association of metabolites with MACE risk. Concrete operation is with embodiment 1.

[0111] 2. Experimental results

[0112] After adjusting for potential confounding factors including age, gender, BMI, SYNTAX score, complications, liver and kidney function, and drug treatment, multivariate COX regression analysis showed that 20 metabolites were still associated with the risk of MACE (P <0.05, Table 3), including lyso-lecithin 20:2 (LysoPC 20:2), lyso-lecithin 20:2 (2n isomer) (LysoPC 20:2 (2n isomer)), 5-methyl Uridine (5-Methyluridine), 4-Acetamidobutyric acid (4-Acetamidobutyric acid), L-Kynurenine (L-Kynurenine), LysoPC 20:1 (LysoPC 20:1), D-Sorbitol (D-Sorbitol), Dulcitol, LysoPC 20:0 (LysoPC 20:0), LysoPC 20:1 (2n isomer) (LysoPC 20:1 (2n iso...

Embodiment 3

[0116] Example 3 Combination analysis of metabolic markers for cardiac insufficiency (LVEF<50%)

[0117] 1. Experimental operation

[0118] In order to identify plasma metabolites associated with cardiac insufficiency, Logistic regression was used to analyze the correlation of plasma metabolites with cardiac insufficiency (LVEF<50%). According to the value of LVEF, 833 patients with LVEF data were divided into two groups, 152 cases with LVEF<50% (cases), and 681 cases with LVEF≥50% (control).

[0119] Concrete steps are as embodiment 1.

[0120] 2. Experimental results

[0121] After adjusting for several potential confounding factors including demographics, clinical measures, prevalent comorbidities, and concomitant medications, multivariate Logistic regression analysis showed that 32 metabolites were statistically associated with LVEF Significance (P<0.05, Table 5), including dimethylguanosine (2-(dimethylamino)guanosine), creatine (Creatine), N6-acetyl-L-lysine (N6-Acety...

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Abstract

The invention discloses a use of endogenous metabolites as markers for predicting the prognosis risk of coronary heart disease or in preparation of a kit for predicting the prognosis risk of coronaryheart disease. The metabolite marker can effectively predict the risk of death and major adverse cardiovascular events (MACE) in patients with coronary heart disease and the risk of cardiac insufficiency, and has the characteristics of specificity, sensitivity, high efficiency and non-invasiveness. After the metabolite marker is used for predicting the prognosis survival rate of patients with coronary heart disease, the AUC is 65% or more. Through combination, the AUC is close to 100% compared with AUC based on the single marker and the prediction effect is good. The method for detecting through the marker has high sensitivity, is convenient and quick and produces accurate and reliable results. The predictive model constructed by the marker can be used for predicting the prognosis risk ofcoronary heart disease, has good predictive effects and high sensitivity, is convenient, rapid and non-invasive and has an important clinical application value.

Description

technical field [0001] The invention relates to the technical field of coronary heart disease detection, and more specifically, to a combination of metabolic markers for predicting the prognosis of coronary heart disease and a kit thereof. Background technique [0002] Coronary atherosclerotic heart disease refers to the heart disease caused by atherosclerosis in the coronary arteries causing lumen stenosis or occlusion, resulting in myocardial ischemia hypoxia or necrosis, referred to as coronary heart disease (coronary heart disease) disease, CHD), also known as ischemic heart disease (ischemic heart disease). With the development of my country's economy and society, the annual mortality and incidence of coronary heart disease are increasing year by year, and it is one of the most important death risk factors threatening human society. According to the "China Cardiovascular Disease Report 2016", the mortality rate of cardiovascular disease accounts for 42-45% of the total...

Claims

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Application Information

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IPC IPC(8): G01N30/02G01N30/06G01N30/54
CPCG01N30/02G01N30/06G01N30/54G01N2030/027G01N2030/062
Inventor 朱茜钟诗龙刘仪滨汤雅男
Owner BMK BIOMEDICAL TECH GUANGZHOU CO LTD
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