2型糖尿病患者循环CCN6/WISP3及其与胰岛素抵抗和炎症的相关性:统计学和机器学习分析

IF 3.3 3区 医学 Q2 MEDICAL INFORMATICS
Reza Afrisham, Yasaman Jadidi, Nariman Moradi, Seyed Mohammad Ayyoubzadeh, Reza Fadaei, Omid Kiani Ghalesardi, Vida Farrokhi, Shaban Alizadeh
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引用次数: 0

摘要

细胞通信网络因子6 (CCN6)是一种脂肪因子,其产生在代谢紊乱中发生显著改变。鉴于肥胖诱导的脂肪因子功能障碍与胰岛素抵抗和2型糖尿病(T2DM)的发展之间存在明确的联系,本研究探讨了CCN6作为T2DM生物标志物的潜在作用。本研究旨在首次探讨血清CCN6水平与T2DM及其危险因素之间的关系。方法:在本病例对照研究中,共纳入80例确诊为2型糖尿病的患者和80例转诊至伊朗德黑兰sharati医院的健康对照患者。生化指标包括空腹血糖(FBG)、天冬氨酸转氨酶(AST)、丙氨酸转氨酶(ALT)、甘油三酯(TG)、总胆固醇(TC)、高密度脂蛋白(HDL)、低密度脂蛋白(LDL)。ELISA法测定血清CCN6、脂联素、肿瘤坏死因子-α (TNF)-α、白细胞介素6 (IL-6)、胰岛素水平。对以均数±标准差(SD)表示的数据应用学生t检验。此外,利用基尼指数确定T2DM分类中各因素的权重。此外,各种机器学习模型被用于开发预测T2DM的分类器。结果:T2DM患者CCN6水平(1259.76±395.02 pg/ml)明显低于对照组(1979.17±471.99 pg/ml)。结论:我们的研究发现血清CCN6水平与T2DM的可能性以及炎症生物标志物(IL-6和TNF-α)之间存在显著的负相关。CCN6有望成为T2DM的潜在生物标志物;然而,需要进一步的研究来验证这一发现并评估其临床应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Circulating CCN6/WISP3 in type 2 diabetes mellitus patients and its correlation with insulin resistance and inflammation: statistical and machine learning analyses.

Introduction: Cellular Communication Network Factor 6 (CCN6) is an adipokine whose production undergoes significant alterations in metabolic disorders. Given the well-established link between obesity-induced adipokine dysfunction and the development of insulin resistance and type 2 diabetes mellitus (T2DM), this study investigates the potential role of CCN6 as a biomarker for T2DM. The present study aimed to investigate the association between serum CCN6 levels and T2DM, as well as its risk factors, for the first time.

Methods: In this case-control study, a total of 80 individuals diagnosed with T2DM and 80 healthy control individuals, who referred to Shariati hospital (Tehran, Iran), were included in the study. Biochemical parameters including fasting blood glucose (FBG), aspartate transaminase (AST), alanine transaminase (ALT), triglycerides (TG), total cholesterol (TC), high-density lipoprotein (HDL), and low-density lipoprotein (LDL) were determined using the AutoAnalyzer instrument. The circulating levels of CCN6, adiponectin, Tumor necrosis factor-α (TNF)-α, Interleukin 6 (IL-6), and insulin were quantified using ELISA. The Student t-test was applied to data that presented as mean ± standard deviations (SD). Moreover, the Gini Index was utilized to determine the weight of each factor in T2DM classification. Additionally, various machine learning models were employed to develop classifiers for predicting T2DM.

Results: T2DM patients demonstrated significantly lower levels of CCN6 (1259.76 ± 395.02 pg/ml) compared to controls (1979.17 ± 471.99 pg/ml, P < 0.001), as well as lower levels of adiponectin (P < 0.001) and higher levels of TNF-α and IL-6 (P < 0.001) compared to non-T2DM individuals. In the T2DM group, CCN6 exhibited negative correlations with insulin, Homeostatic Model Assessment for Insulin Resistance (HOMA-IR), body mass index (BMI), IL-6, and TNF-α. Logistic regression analysis indicated an increased risk of T2DM, with a CCN6 cutoff value of 1527.95 pg/mL distinguishing T2DM patients with 86.3% sensitivity and 73.8% specificity. The Gini Index highlighted that HOMA-IR, IL6, and CCN6 had the highest weighting on T2DM.

Conclusion: Our research identified a significant and negative association between serum CCN6 levels and the likelihood of T2DM, as well as inflammation biomarkers (IL-6 and TNF-α). CCN6 shows promise as a potential biomarker for T2DM; however, further investigations are necessary to validate this finding and assess its clinical utility.

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来源期刊
CiteScore
7.20
自引率
5.70%
发文量
297
审稿时长
1 months
期刊介绍: BMC Medical Informatics and Decision Making is an open access journal publishing original peer-reviewed research articles in relation to the design, development, implementation, use, and evaluation of health information technologies and decision-making for human health.
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