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<p>The identification of accurate and simple biomarkers for insulin resistance (IR) and type 2 diabetes mellitus (T2DM) is crucial for early risk stratification. This study investigated the association between the Cardiometabolic Index (CMI), A novel lipid-anthropometric composite, as a marker for IR/T2DM and its relationship with circulating miR-29a. This case-control study, derived from the Kerman Coronary Artery Disease Risk Factors Study (KERCADRS) cohort, included 118 adults with T2DM and 102 non-diabetic controls. Fasting blood samples were analyzed for biochemical parameters, serum miR-29a levels, and a panel of novel metabolic indices, including the CMI, Atherogenic Index of Plasma (AIP), Triglyceride-Glucose (TyG) index, TyG-body mass index (TyG-BMI), and TyG-waist circumference (TyG-WC). IR was assessed using the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR). Associations between CMI (analyzed as a continuous variable and in quartiles) and IR were evaluated using logistic regression models with multiple adjustments. Diabetic subjects had significantly higher Fasting Blood Sugar (FBS (, HOMA-IR, and miR-29a levels (all <i>p</i> &lt; 0.001). A graded increase in adverse metabolic profiles was observed across ascending CMI quartiles. In multivariate models adjusted for age, sex, and lifestyle factors, higher CMI was significantly associated with increased odds of IR (OR = 1.32; 95% CI: 0.99, 1.76; P-trend = 0.03). ROC analysis revealed that miR-29a had diagnostic accuracy for T2DM and IR (AUC = 0.972; 0.933, respectively, <i>p</i> &lt; 0.001), while the TyG index showed predictive value for T2DM and IR (AUC = 0.836 and 0.852, respectively, <i>p</i> &lt; 0.001). TyG-WC also showed good predictive values for T2DM (AUC = 0.692, <i>p</i> &lt; 0.001) and IR (AUC = 0.721, <i>p</i> &lt; 0.001). The CMI is an independent predictor of IR, even after adjusting for key confounders. Its association with dysglycemia and the strong discriminatory power of miR-29a suggest their potential roles as synergistic biomarkers for identifying individuals at high metabolic risk in the Iranian population.</p>

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The cardiometabolic index and miR-29a as related biomarkers for insulin resistance and dysglycemia in adults: insights from the KERCADRS study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月12日

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  • Zahra Bagheri-Hosseinabadi,
  • Mahdis Rahimi Naiini,
  • Neda Malek Mohammadi,
  • Mitra Abbasifard,
  • Farzaneh Arami,
  • Beydolah Shahouzehi,
  • Saeed Mohammadi-Hosseinabad,
  • Mohammad Reza Mirzaei

摘要

The identification of accurate and simple biomarkers for insulin resistance (IR) and type 2 diabetes mellitus (T2DM) is crucial for early risk stratification. This study investigated the association between the Cardiometabolic Index (CMI), A novel lipid-anthropometric composite, as a marker for IR/T2DM and its relationship with circulating miR-29a. This case-control study, derived from the Kerman Coronary Artery Disease Risk Factors Study (KERCADRS) cohort, included 118 adults with T2DM and 102 non-diabetic controls. Fasting blood samples were analyzed for biochemical parameters, serum miR-29a levels, and a panel of novel metabolic indices, including the CMI, Atherogenic Index of Plasma (AIP), Triglyceride-Glucose (TyG) index, TyG-body mass index (TyG-BMI), and TyG-waist circumference (TyG-WC). IR was assessed using the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR). Associations between CMI (analyzed as a continuous variable and in quartiles) and IR were evaluated using logistic regression models with multiple adjustments. Diabetic subjects had significantly higher Fasting Blood Sugar (FBS (, HOMA-IR, and miR-29a levels (all p < 0.001). A graded increase in adverse metabolic profiles was observed across ascending CMI quartiles. In multivariate models adjusted for age, sex, and lifestyle factors, higher CMI was significantly associated with increased odds of IR (OR = 1.32; 95% CI: 0.99, 1.76; P-trend = 0.03). ROC analysis revealed that miR-29a had diagnostic accuracy for T2DM and IR (AUC = 0.972; 0.933, respectively, p < 0.001), while the TyG index showed predictive value for T2DM and IR (AUC = 0.836 and 0.852, respectively, p < 0.001). TyG-WC also showed good predictive values for T2DM (AUC = 0.692, p < 0.001) and IR (AUC = 0.721, p < 0.001). The CMI is an independent predictor of IR, even after adjusting for key confounders. Its association with dysglycemia and the strong discriminatory power of miR-29a suggest their potential roles as synergistic biomarkers for identifying individuals at high metabolic risk in the Iranian population.