Metabolic syndrome biomarker and use thereof

Abstract

The application discloses a metabolic syndrome biomarker and application thereof. The application provides a new biomarker for early diagnosis of metabolic syndrome. Detection of the biomarker hs-cTnT level helps clinicians to identify a high-risk population of metabolic syndrome earlier, and then timely start early intervention measures, such as diet adjustment, exercise intervention, or regulate metabolic disorder state through drugs, so as to block the pathophysiological cascade reaction of'metabolic disorder-myocardial injury- cardiovascular disease'.

Description

Technical Field

[0001] This invention belongs to the field of biomedical technology and relates to a biomarker for metabolic syndrome and its application. Background Technology

[0002] In clinical practice, metabolic disorder (MetD) is a group of metabolic syndromes characterized by central obesity, hypertension, dyslipidemia, and hyperglycemia, posing a serious threat to global public health. According to the latest diagnostic criteria, metabolic syndrome (MetS) is defined as the presence of a cluster of three or more metabolic risk factors, which significantly increases the risk of type 2 diabetes, cardiovascular disease (CVD), and all-cause mortality.

[0003] Previous studies have shown that elevated levels of high-sensitivity cardiac troponin T (hs-cTnT) can reflect metabolic disorders even in individuals without definite clinical cardiovascular events, and hs-cTnT itself is a biomarker closely related to myocardial injury. Traditionally, hs-cTnT was considered primarily for the diagnosis of acute coronary syndromes, but increasing evidence suggests that in asymptomatic individuals, hs-cTnT can indicate early myocardial stress and is strongly correlated with metabolic abnormalities. Multiple studies have confirmed that hs-cTnT is correlated with various components of the MetS, including abdominal obesity, hypertension, dyslipidemia, and hyperglycemia. A community-based atherosclerosis risk study (ARIC) showed that individuals with metastatic atherosclerosis (MetS) had significantly higher hs-cTnT concentrations than those without MetS, and hs-cTnT concentrations progressively increased with the number of MetS components, suggesting that metabolic disorders may lead to myocardial micro-injury through oxidative stress and chronic inflammation pathways. Other studies have shown that in MetS patients without cardiovascular disease, elevated hs-cTnT levels were independently associated with increased arterial stiffness and elevated levels of oxidative stress markers (such as reactive oxygen species), indicating a potential role of vascular dysfunction in metabolic-related myocardial injury.

[0004] However, most existing studies focus on individuals diagnosed with cardiovascular disease or those at high risk for cardiovascular disease. The mechanism of the relationship between metabolic disorders and hs-cTnT in the general population without underlying cardiovascular disease remains controversial. Some researchers have proposed that elevated hs-cTnT levels may appear earlier than the clinical manifestations of traditional cardiovascular risk factors, serving as an early biomarker for target organ damage caused by metabolic abnormalities. A cross-sectional study showed that even when hs-cTnT levels were below the clinical diagnostic threshold (<14 ng / L), its concentration fluctuations were independently correlated with metabolic indicators such as waist circumference, fasting blood glucose, and blood pressure, with this correlation being particularly significant in men and the elderly. These results suggest that hs-cTnT may serve as a sensitive marker reflecting imbalances in the "metabolic-cardiac axis," while the specific pathophysiological mechanisms behind metabolic microenvironment changes such as adipokines abnormalities and endothelial dysfunction require further investigation. As mentioned earlier, the expression patterns of hs-cTnT in cardiovascularly healthy individuals, especially the differential effects of specific metabolic components on its levels, are not yet fully elucidated. Furthermore, existing studies mostly analyze MetS as a whole, lacking a systematic comparison of the contribution of each metabolic component to the increase of hs-cTnT, and especially lacking differential analysis for different sexes and age subgroups. Summary of the Invention

[0005] The purpose of this invention is to address the above-mentioned problems by providing a biomarker for metabolic syndrome and its application.

[0006] To achieve its objective, the present invention employs the following technical solution:

[0007] A first aspect of the present invention provides a biomarker for metabolic syndrome, wherein the biomarker is hs-cTnT.

[0008] Preferably, the metabolic syndrome is a metabolic syndrome without cardiovascular disease, and the biomarker is an early biomarker.

[0009] A second aspect of the invention provides the use of reagents for detecting the above-mentioned biomarkers in the preparation of reagents or kits for early diagnosis of metabolic disorders or metabolic syndromes.

[0010] Preferably, the biomarker is a biomarker in plasma, serum, or blood.

[0011] Preferably, the kit includes reagents required for the immunoassay of the biomarker hs-cTnT.

[0012] In the above application technical solution, the metabolic disorder or metabolic syndrome is a metabolic disorder or metabolic syndrome without cardiovascular disease.

[0013] Preferably, the subjects of the application are elderly, male, or individuals with elevated metabolic abnormality indicators.

[0014] Among the above-mentioned application technologies, the expression of hs-cTnT is significantly increased in patients with metabolic disorders or metabolic syndrome.

[0015] A third aspect of the present invention provides an early diagnostic kit for metabolic disorders or metabolic syndrome, comprising reagents required for immunoassay of the aforementioned biomarker hs-cTnT.

[0016] The beneficial effects of this invention are as follows: This study used individuals diagnosed with Metabolic D or Metabolic Surgery (MetD) without cardiovascular disease as research subjects. A high-sensitivity detection method was used to measure and analyze the plasma hs-cTnT levels of the subjects. The results showed that hs-cTnT can serve as a preliminary screening biomarker for metabolic disorders in individuals without cardiovascular disease, especially suitable for the elderly, men, and those with elevated metabolic abnormalities. This study confirmed that in patients with metabolic syndrome, hs-cTnT levels were significantly and independently correlated with both the occurrence and severity of the disease, and the quantity of abnormal components in metabolic syndrome was directly correlated with hs-cTnT concentration. These results indicate that hs-cTnT has certain application value in risk stratification of metabolic syndrome, helping to conduct more accurate risk assessments and optimize clinical management plans for individual patients. This invention provides a novel biomarker for the early diagnosis of metabolic syndrome. Detecting the level of the biomarker hs-cTnT helps clinicians identify high-risk individuals for metabolic syndrome earlier, thereby enabling timely initiation of early intervention measures (such as dietary adjustments, exercise interventions, or drug regulation of metabolic disorders) to block the pathophysiological cascade of "metabolic disorder-myocardial damage-cardiovascular disease". Attached Figure Description

[0017] Figure 1 The correlation between hs-cTnT levels and the number of abnormal components in metabolic syndrome is shown. *P<0.05: compared with the abnormal groups of items 0 and 1; #P<0.05: compared with the abnormal groups of items 0, 1, and 2.

[0018] Figure 2 The expression levels of hs-cTnT in different subgroups: (a) hs-cTnT levels in different age groups (<60 years, ≥60 years) and sex groups (female, male); (b) hs-cTnT levels in different fasting blood glucose groups (normal, elevated), blood pressure groups (normal, elevated), and triglyceride groups (normal, elevated); ***P<0.001.

[0019] Figure 3 ROC curve analysis for predicting metabolic syndrome with hs-cTnT. Detailed Implementation

[0020] The present invention will be further described below with reference to embodiments, but these embodiments are not intended to limit the scope of the invention.

[0021] Unless otherwise specified, the experimental methods described in the following examples are conventional methods.

[0022] Methods of this invention: This is a single-center retrospective study that included 162 subjects without cardiovascular disease, who were divided into three groups according to metabolic-related diagnostic criteria. High-sensitivity detection methods were used to measure plasma hs-cTnT levels in the subjects, and the correlation between hs-cTnT and various clinical indicators was analyzed. Receiver operating characteristic (ROC) curve analysis was used to determine the cutoff value of hs-cTnT for predicting metabolic syndrome. Multivariate linear regression analysis was then used to identify independent influencing factors of elevated hs-cTnT.

[0023] The results of this study show that hs-cTnT levels gradually increase with the increase of the number of metabolically abnormal components (P<0.05). Elevated hs-cTnT levels were significantly positively correlated with age, systolic blood pressure (SBP), fasting blood glucose (FBG), triglycerides (TG), and uric acid (UA) (all P<0.001), and negatively correlated with high-density lipoprotein cholesterol (HDL-C) and estimated glomerular filtration rate (eGFR) (P<0.05). ROC curve analysis showed that the area under the curve (AUC) for hs-cTnT in predicting metabolic syndrome was 0.752 (P<0.001), with an optimal cutoff value of 2.14 ng / L, corresponding to a sensitivity of 59.4% and a specificity of 75.8%. Multivariate analysis showed that age, fasting blood glucose (β=0.349, P<0.01), and systolic blood pressure (β=0.079, P<0.05) were independent predictors of elevated hs-cTnT levels.

[0024] The findings of this study indicate that in this single-center retrospective cohort of cardiovascular disease-free subjects, hs-cTnT levels were significantly and independently positively correlated with metabolic syndrome components and their severity. These results suggest that hs-cTnT may serve as a potential early biomarker and preliminary clinical predictor of metabolic syndrome in this specific population.

[0025] The specific research process is as follows:

[0026] Example 1

[0027] 1. Materials and Methods

[0028] 1.1 Study Design and Study Population

[0029] This was a single-center retrospective study, with participants recruited at Chongqing West District Hospital between May and November 2023. Inclusion criteria were: age > 18 years; presence of metabolic abnormalities such as abnormal body mass index (BMI), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), blood pressure (BP), and fasting blood glucose (FBG); exclusion of potential cardiac lesions by baseline cardiac assessment (electrocardiogram, brain natriuretic peptide / N-terminal pro-brain natriuretic peptide / soluble growth-stimulating gene 2 protein detection), and no evidence of subclinical myocardial injury or cardiac structural disease. Exclusion criteria were: participants diagnosed with coronary artery disease, heart failure, valvular heart disease, tumors, autoimmune diseases, or infections; and participants with abnormal cardiac assessment results. Healthy individuals who underwent physical examinations during the same period were selected as the control group. This group had no abnormalities in metabolic-related indicators, normal electrocardiograms, and no history of cardiovascular disease. Based on preliminary experimental data (mean difference of hs-cTnT 1.29 ng / L, pooled standard deviation 2.0 ng / L), the sample size was calculated using PASS 25.0 software (significance level α=0.05, two-tailed test; power 0.8), determining the required sample size to be 114 cases. Considering a 20% missing data rate, this study required at least 143 cases to be enrolled. Ultimately, 162 subjects were enrolled to complete the study. This study protocol was reviewed and approved by the Ethics Committee of Chongqing West District Hospital.

[0030] 1.2 Definition of Metabolic Syndrome and Metabolic Disorder

[0031] This study adopted the diagnostic criteria for metabolic syndrome (MetS) established by the American Association of Clinical Endocrinologists. The specific diagnostic criteria are: ① presence of insulin resistance, or body mass index ≥ 25 kg / m². 2 The following criteria must be met for a diagnosis of metabolic syndrome: ① Waist circumference ≥102 cm for men and ≥88 cm for women; ② Fasting blood glucose ≥6.1 mmol / L, or 2-hour postprandial blood glucose ≥7.8 mmol / L; ③ High-density lipoprotein cholesterol <1.0 mmol / L for men and <1.3 mmol / L for women; ④ Triglycerides ≥1.7 mmol / L; ⑤ Blood pressure ≥130 / 85 mmHg. Meeting three or more of these five criteria will result in a diagnosis of metabolic syndrome. To differentiate the severity of metabolic diseases, meeting one or two of these criteria will result in a diagnosis of metabolic disorder (MetD).

[0032] 1.3 Data Collection

[0033] All data in this study were derived from retrospective clinical records from Chongqing West District Hospital, specifically including: ① demographic and medical history data, collected by physicians through standardized consultations; ② physical examination data, completed by professionally trained staff according to standard operating procedures; and ③ laboratory test results, all from the hospital's clinical laboratory department, and all tests passed national standard quality control verification. Immediately after blood collection, plasma samples were centrifuged, separated, and aliquoted, and stored at -80℃ to avoid repeated freeze-thaw cycles for subsequent testing. After all plasma samples were collected, plasma hs-cTnT levels were detected using the Pylon hs-cTnT assay kit from Suzhou Xingtong Medical Technology Co., Ltd., based on cyclic enhanced fluorescence immunoassay technology, on the Pylon IRIS fully automated immunoassay analyzer.

[0034] 1.4 Statistical Analysis

[0035] Data analysis was performed using SPSS 25.0 statistical software. Categorical data were expressed as frequencies (percentages), and chi-square tests were used for comparisons between groups. Normally distributed continuous data were expressed as mean ± standard deviation, and independent samples t-tests were used for comparisons between two groups, while one-way ANOVA was used for comparisons among multiple groups. Non-normally distributed continuous data were expressed as medians (interquartile ranges), and Mann-Whitney U tests were used for comparisons between two groups, while Kruskal-Wallis tests were used for comparisons among multiple groups. Pearson or Spearman correlation analysis was used to explore the correlation between hs-cTnT and other clinical indicators; multivariate linear regression analysis was used to screen for clinical factors influencing hs-cTnT levels. All statistical tests were two-tailed, and p < 0.05 was considered statistically significant.

[0036] 2 Results

[0037] This study initially included 261 subjects without cardiovascular disease. After screening according to exclusion criteria, 162 subjects were ultimately included for statistical analysis. The demographic and baseline clinical characteristics of the subjects are detailed in Table 1. Fasting blood glucose, low-density lipoprotein cholesterol, body mass index, total cholesterol, triglycerides, and hs-cTnT levels showed an increasing trend among the healthy group, metabolic disorder group, and metabolic syndrome group, while estimated glomerular filtration rate and high-density lipoprotein cholesterol levels showed a decreasing trend. All inter-group differences were statistically significant (all P < 0.05), indicating significant differences in metabolic characteristics among the three groups. Analysis of the association between hs-cTnT and various components of metabolic syndrome revealed that its level progressively increased with the accumulation of abnormal components in metabolic syndrome; and statistically significant differences in hs-cTnT were found between the groups with ≤1 and ≥2 abnormal components, and between the groups with ≤2 and ≥3 abnormal components (all P < 0.05). Figure 1).

[0038] Table 1. Demographic and baseline clinical characteristics of the study subjects

[0039]

[0040] like Figure 2 As shown, hs-cTnT levels differed significantly among subgroups. Stratified analysis by age and sex revealed ( Figure 2 a) hs-cTnT levels in subjects aged ≥60 years were significantly higher than those in subjects <60 years (P<0.001), and hs-cTnT levels in male subjects were significantly higher than those in female subjects (P<0.001). Furthermore, hs-cTnT levels in the elevated fasting blood glucose group, elevated blood pressure group, and elevated triglyceride group were significantly higher than those in the corresponding normal groups, with statistically significant differences (all P<0.001). Figure 2 b).

[0041] Table 2 shows the correlation coefficients between hs-cTnT and various clinical indicators. The results showed that hs-cTnT levels were significantly positively correlated with age, systolic blood pressure, fasting blood glucose, triglycerides, and uric acid, and significantly negatively correlated with estimated glomerular filtration rate and high-density lipoprotein cholesterol. All these correlations were statistically significant (P < 0.05). ROC curve analysis showed that hs-cTnT had good differential diagnostic efficacy between subjects with and without metabolic syndrome, with an area under the curve of 0.752 (95% confidence interval: 0.654–0.850, P < 0.001). Based on the Youden index, the optimal cutoff value for predicting metabolic syndrome was determined to be 2.38 ng / L, corresponding to a sensitivity of 59.4% and a specificity of 75.8%. Figure 3 Multivariate linear regression analysis confirmed (Table 3) that, after adjusting for various confounding factors, elevated fasting blood glucose and elevated systolic blood pressure were independent predictors of elevated hs-cTnT levels (β values ​​were 0.35 and 0.08, respectively, and P values ​​were < 0.01 and < 0.05, respectively).

[0042] Table 2 Correlation analysis of hs-cTnT with other clinical indicators

[0043]

[0044] Table 3 Multivariate linear regression analysis of factors influencing hs-cTnT

[0045]

[0046] The above findings indicate that even in individuals without overt cardiovascular disease, there remains a close association between hs-cTnT and metabolic disorders.

[0047] 3. Summary

[0048] Metabolic disorders are closely associated with an increased risk of cardiovascular disease, and hs-cTnT, as a biomarker related to cardiovascular disease risk, may be associated with metabolic disorders. This study found that in individuals without cardiovascular disease, hs-cTnT levels increased with the number of metabolically abnormal components; as metabolic disorders progressed to metabolic syndrome, the level of this indicator showed a significant upward trend. Among the components of metabolic syndrome, elevated fasting blood glucose, elevated blood pressure, and elevated triglycerides were all positively correlated with elevated hs-cTnT levels. Furthermore, male sex, age, and fasting blood glucose were independent influencing factors for elevated hs-cTnT levels. These results indicate that elevated hs-cTnT levels are closely related to metabolic abnormalities in individuals without cardiovascular disease, and this indicator may serve as a potential biomarker for early identification of metabolic syndrome.

[0049] Current research on the correlation between hs-cTnT and metabolic abnormalities remains limited. A community atherosclerosis risk study indicated that hs-cTnT levels were significantly higher in individuals with metabolic syndrome than in those without, and this indicator was positively correlated with the number of abnormal components in metabolic syndrome. Similar results were obtained in children; a study by Pervanidou et al. found that obese children with metabolic syndrome had significantly higher hs-cTnT levels than obese and non-obese children without metabolic syndrome, while there was no significant difference in hs-cTnT levels between obese and non-obese children without metabolic syndrome. These results suggest that metabolic syndrome may lead to elevated hs-cTnT levels in the early stages of the disease. Furthermore, this study found that even when hs-cTnT levels were below the clinical diagnostic threshold (<14 ng / L), they were still independently correlated with metabolic indicators such as fasting blood glucose, blood pressure, and blood lipids, and this correlation was particularly significant in the elderly and men. These findings further confirm existing research conclusions that elevated hs-cTnT levels precede the clinical manifestations of cardiovascular disease and may serve as an early warning indicator of cardiovascular disease risk in early metabolic syndrome.

[0050] The association between metabolic abnormalities and elevated hs-cTnT levels may involve multiple pathophysiological mechanisms, with elevated blood pressure and abnormal glucose metabolism being typical features of metabolic disorders. Firstly, elevated blood pressure can lead to excessive myocardial stress, activating matrix metalloproteinase-2 and calpain-1, causing troponin molecules to break down into smaller fragments and release into the bloodstream through the cell membrane. Simultaneously, oxidative stress induced by hypertension, upregulation of Fas protein expression, and enhanced sympathetic nerve activity can activate apoptosis pathways through the cyclic adenosine monophosphate (cAMP) and nuclear factor-κB signaling pathways, further leading to cardiomyocyte apoptosis and hs-cTnT release. Secondly, hyperglycemia accelerates the synthesis of myocardial collagen fibers. The accumulation of collagen fibers in the myocardial interstitium leads to myocardial congestion, increasing myocardial stiffness, inducing myocardial microvascular disease, and ultimately causing cardiomyocyte necrosis and elevated hs-cTnT levels. Studies have confirmed this association: type 2 diabetic patients without cardiovascular disease have significantly higher hs-cTnT levels than healthy controls, and these levels are positively correlated with fasting blood glucose and glycated hemoglobin levels. The results of this study are consistent with the above conclusions, confirming that elevated hs-cTnT levels are associated with diabetes and abnormal glucose metabolism.

[0051] Furthermore, this study found a negative correlation between hs-cTnT and estimated glomerular filtration rate, suggesting that impaired renal function may be involved in the development of myocardial injury. The pathophysiological mechanisms of hs-cTnT release in renal insufficiency require further investigation. Some studies suggest that patients with renal insufficiency may experience recurrent asymptomatic myocardial necrosis, which may be one reason for elevated hs-cTnT levels. Cardiac troponin T can be broken down into immunologically active small molecule fragments and cleared by the kidneys; this characteristic may explain, to some extent, the high incidence of elevated hs-cTnT levels in patients with impaired renal excretion. Notably, hs-cTnT levels show a sex difference (higher levels in men), which may be related to the regulation of cardiomyocyte sensitivity by androgens or the higher prevalence of abdominal obesity in men, but the specific regulatory mechanisms require further investigation.

[0052] This study further confirms that hs-cTnT holds promise as a sensitive biomarker for reflecting metabolic-cardiac axis dysregulation. Although this indicator has traditionally been considered a biomarker of myocardial injury, our results show that even in individuals without overt cardiovascular disease, elevated hs-cTnT levels are closely associated with various metabolic abnormalities, suggesting that it can reflect early myocardial stress induced by metabolic disorders. Of particular note is the finding that hs-cTnT levels progressively increase with the number of abnormal metabolic components, and exhibit stronger independent correlations with metabolic components such as fasting blood glucose, blood pressure, and triglycerides. This result is consistent with the findings of Milwidsky et al., who demonstrated that even when hs-cTnT concentrations are below the clinical diagnostic threshold, they remain independently associated with metabolic indicators, further confirming the high sensitivity and early warning value of this indicator in metabolic-cardiac axis dysregulation. Furthermore, this study revealed differences in the contribution of different metabolic components to elevated hs-cTnT levels: in the multivariate regression model, fasting blood glucose and systolic blood pressure were independent predictors of elevated hs-cTnT levels, while dyslipidemia components such as high-density lipoprotein cholesterol and triglycerides, although statistically significant in univariate analysis, did not show independent contributions in the multivariate regression model. This result suggests that hyperglycemia and hypertension may play a core pathophysiological role in metabolic-related myocardial micro-injury, and the effects of dyslipidemia may be partially mediated by other metabolic factors. Simultaneously, this study confirmed that age and male sex are important regulators of hs-cTnT levels, with higher baseline levels in men and older adults, which may be related to hormonal regulation, differences in body fat distribution, or accumulated metabolic load. These findings provide preliminary clinical evidence for understanding the heterogeneity of the "metabolic-cardiac axis" in different populations and also provide research directions for future individualized risk assessment.

[0053] In summary, this study demonstrates that hs-cTnT can serve as a preliminary screening biomarker for metabolic disorders in individuals without cardiovascular disease, particularly suitable for the elderly, men, and those with elevated metabolic abnormalities. Measuring hs-cTnT levels helps clinicians identify high-risk individuals for metabolic syndrome earlier, enabling timely intervention (such as dietary adjustments, exercise interventions, or medication to regulate metabolic disorders) to break the pathophysiological cascade of "metabolic disorder-myocardial damage-cardiovascular disease." This study confirms that in patients with metabolic syndrome, hs-cTnT levels are significantly and independently correlated with disease occurrence and severity, and the quantity of abnormal components in metabolic syndrome is directly related to hs-cTnT concentration. These results indicate that hs-cTnT has certain application value in risk stratification of metabolic syndrome, contributing to more accurate risk assessment and optimized clinical management for individual patients.

Claims

1. A biomarker for metabolic syndrome, characterized in that: The biomarker is hs-cTnT.

2. The metabolic syndrome biomarker according to claim 1, characterized in that: The metabolic syndrome is a metabolic syndrome without cardiovascular disease, and the biomarker is an early biomarker.

3. The use of reagents for detecting the biomarkers described in claim 1 or 2 in the preparation of reagents or kits for early diagnosis of metabolic disorders or metabolic syndromes.

4. The application according to claim 3, characterized in that: The biomarkers are markers found in plasma, serum, or blood.

5. The application according to claim 3, characterized in that: The kit includes reagents required for the immunoassay technique to detect the biomarker hs-cTnT.

6. The application according to claim 3, characterized in that: The metabolic disorder or metabolic syndrome referred to is a metabolic disorder or metabolic syndrome without cardiovascular disease.

7. The application according to claim 6, characterized in that: The subjects of this application are elderly, male, or individuals with elevated metabolic abnormalities.

8. The application according to claim 7, characterized in that: in, Patients with metabolic disorders or metabolic syndrome show significantly elevated hs-cTnT expression.

9. A diagnostic kit for early diagnosis of metabolic disorders or metabolic syndrome, characterized in that: Reagents required for immunoassay testing containing the biomarker hs-cTnT as described in claim 5.

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