This study aimed to examine the diagnostic predictive value of long non-coding RNA (lncRNA) metastasis-associated lung adenocarcinoma transcript 1(MALAT1) and NOD-like receptor protein 3(NLRP3) expression in patients with type 2 diabetes mellitus(T2DM) and lower extremity atherosclerosis disease (LEAD). A total of 162 T2DM patients were divided into T2DM with LEAD group (T2DM + LEAD group) and T2DM alone group (T2DM group). The lncRNA MALAT1 and NLRP3 expression levels were measured in peripheral blood, and their correlation was examined. Least absolute shrinkage and selection operator (LASSO) regression model was used to screen for the best predictors of LEAD, and multivariate logistic regression was used to establish a predictive model and construct the nomogram. The effectiveness of the nomogram was assessed using the receiver operating characteristic (ROC) curve, area under the curve (AUC), calibration curve, and decision curve analysis (DCA). The levels of the lncRNA MALAT1 and NLRP3 in the T2DM + LEAD group were significantly greater than those in the T2DM group (P <0.001), and the level of the lncRNA MALAT1 was positively correlated with that of NLRP3 (r = 0.453, P<0.001). The results of the LASSO combined with the logistic regression analysis showed that age, smoking, systolic blood pressure (SBP), NLRP3, and MALAT1 were the influencing factors of T2DM with LEAD(P<0.05). ROC curve analysis comparison: The discriminatory ability of the model (AUC = 0.898), MALAT1 (AUC = 0.804), and NLRP3 (AUC = 0.794) was greater than that of the other indicators, and the predictive value of the model was the greatest. Calibration curve: The nomogram model was consistent in predicting the occurrence of LEAD in patients with T2DM (Cindex = 0.898). Decision curve: The net benefit rates obtained from using the predictive models for clinical intervention decision-making were greater than those obtained from using the individual factors within the model. MALAT1 and NLRP3 expression increased significantly in T2DM patients with LEAD, while revealing the correlation between MALAT1 and NLRP3. The lncRNA MALAT1 was found as a potential biomarker for T2DM with LEAD.

中文翻译：

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lncRNA MALAT1、NLRP3在糖尿病下肢动脉粥样硬化中的表达及诊断价值

本研究旨在探讨长链非编码RNA（lncRNA）转移相关肺腺癌转录物1（MALAT1）和NOD样受体蛋白3（NLRP3）表达在2型糖尿病（T2DM）和2型糖尿病患者中的诊断预测价值。下肢动脉粥样硬化性疾病（LEAD）。共有162例T2DM患者分为T2DM联合LEAD组（T2DM+LEAD组）和单纯T2DM组（T2DM组）。检测外周血中lncRNA MALAT1和NLRP3的表达水平，并检查其相关性。使用最小绝对收缩和选择算子（LASSO）回归模型筛选LEAD的最佳预测因子，并使用多元逻辑回归建立预测模型并构建列线图。使用受试者工作特征 (ROC) 曲线、曲线下面积 (AUC)、校准曲线和决策曲线分析 (DCA) 评估列线图的有效性。T2DM+LEAD组lncRNA MALAT1、NLRP3水平显着高于T2DM组（P < 0.001），且lncRNA MALAT1水平与NLRP3水平呈正相关（r = 0.453，P < 0.001）。LASSO结合logistic回归分析结果显示，年龄、吸烟、收缩压（SBP）、NLRP3、MALAT1是T2DM合并LEAD的影响因素（P<0.05）。ROC曲线分析对比：模型（AUC=0.898）、MALAT1（AUC=0.804）、NLRP3（AUC=0.794）的判别能力大于其他指标，模型的预测值最大。校准曲线：列线图模型在预测 T2DM 患者 LEAD 发生方面是一致的（Cindex = 0.898）。决策曲线：使用预测模型进行临床干预决策所获得的净效益率大于使用模型内的单个因素所获得的净效益率。合并 LEAD 的 T2DM 患者中 MALAT1 和 NLRP3 表达显着升高，同时揭示了 MALAT1 和 NLRP3 之间的相关性。lncRNA MALAT1 被发现是 LEAD 型 T2DM 的潜在生物标志物。