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一种使用糖基化指标和循环生物标志物预防心血管疾病的模型。

A proposed model using glycation metrics and circulating biomarkers for the prevention of cardiovascular disease.

作者信息

Valk Timothy, McMorrow Carol

机构信息

CardiacData Analytics, Winter Park, FL, United States.

出版信息

Front Med (Lausanne). 2025 Aug 12;12:1624682. doi: 10.3389/fmed.2025.1624682. eCollection 2025.

Abstract

INTRODUCTION

Cardiovascular aging starts early in life due to the glycation of critical proteins, though its progression remains undetected in the formative years. The glycation reaction affects all tissues by the same non enzymatic irreversible reaction. The variables are the pH, temperature, glucose concentration, and the specific protein. This relationship implies that glycated blood biomarkers could potentially be used as a proxy for assessing myocardial changes.

METHODS

Laboratory tests for troponin I (cTnI), hemoglobin A1c (A1c), fructosamine, and low-density lipoprotein (LDL), were chosen to calculate the proxy for glycation. An algorithm was developed incorporating these variables as individual measurements and as calculated metrics of glycation. This data was obtained from previous large group studies of variables and outcomes.

RESULTS

Modeling of glycation was determined for each variable. Using metrics from multiple studies, theoretical rates of glycation of LDL and troponin I were calculated. The glycated changes in LDL and troponin I were used to determine the increases above optimal physiological rates.

CONCLUSION

Laboratory results of LDL, cTnI, A1c and fructosamine could be used sequentially to derive a cost-effective proxy for assessing aging and deterioration of cardiovascular tissue. This model could theoretically predict the rate of cardiovascular aging by integrating four blood biomarkers into a dedicated algorithm guiding proactive diagnostics and treatment.

摘要

引言

由于关键蛋白质的糖基化,心血管衰老在生命早期就开始了,尽管在成长阶段其进展仍未被察觉。糖基化反应通过相同的非酶促不可逆反应影响所有组织。变量包括pH值、温度、葡萄糖浓度和特定蛋白质。这种关系意味着糖化血液生物标志物有可能被用作评估心肌变化的替代指标。

方法

选择肌钙蛋白I(cTnI)、糖化血红蛋白(A1c)、果糖胺和低密度脂蛋白(LDL)的实验室检测来计算糖基化的替代指标。开发了一种算法,将这些变量作为单独测量值和计算出的糖基化指标纳入其中。这些数据来自先前关于变量和结果的大型群体研究。

结果

确定了每个变量的糖基化模型。使用多项研究的指标,计算了LDL和肌钙蛋白I的理论糖基化速率。LDL和肌钙蛋白I的糖化变化用于确定高于最佳生理速率的增加量。

结论

LDL、cTnI、A1c和果糖胺的实验室结果可依次用于得出一种经济有效的替代指标,以评估心血管组织的衰老和退化情况。该模型理论上可以通过将四种血液生物标志物整合到一个专门的算法中,指导主动诊断和治疗,从而预测心血管衰老的速率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ead5/12378529/bf10299ed9ad/fmed-12-1624682-g001.jpg

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