BMC nephrology · 2025
The "Picasso faces" of diabetic kidney disease - how the art of phenotyping and molecular biomarkers is transforming clinical nephrology: an observational study in patients with type 2 diabetes.
СтатьяНаблюдательное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Rodzoń-Norwicz Małgorzata, Potocka Natalia, Skrzypa Marzena, Zawlik Izabela, Milian-Ciesielska Katarzyna, Kogut Patryk, Gargasz Krzysztof, Maes Michael, Sowa-Kućma Magdalena, Gala-Błądzińska Agnieszka
Аннотация
BACKGROUND AND HYPOTHESIS: Diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus (T2DM) presents heterogeneously, complicating risk assessment. This study evaluated microRNAs and other biomarkers for DKD phenotyping and predicting kidney function in clinical practice.
METHODS: Data from 79 patients with T2DM were analyzed. DKD phenotypes were defined based on eGFR and UACR: • F1 (albuminuric): eGFR < 60 mL/min/1.73 m², UACR ≥ 300 mg/g. • F2 (non-albuminuric, preserved filtration): eGFR ≥ 60 mL/min/1.73 m², UACR ≤ 30 mg/g. • F3 (non-albuminuric, reduced filtration): eGFR < 60 mL/min/1.73 m², UACR ≤ 30 mg/g. • F4 (moderately increased albuminuria): UACR > 30 and < 300 mg/g was shown for completeness but excluded from primary analyses. Multiple regression and partial least squares structural equation modeling (PLS-SEM) were applied to identify predictors of eGFR. Discriminant analysis (including age, ACE, uric acid, and AIP) was used for phenotype classification. Serum levels of hsa-miR-126-3p and hsa-miR-423-5p were compared between phenotypes.
RESULTS: Independent predictors of eGFR included ACE (β = - 0.478; p < 0.001), age (β = - 0.336), AIP (β = - 0.245), and hsa-miR-423-5p (β = 0.138; p = 0.033) (R² = 0.619). In the PLS-SEM model, ACE, AIP, and hsa-miR-423-5p had significant direct effects on eGFR, while ACE was modulated by hsa-miR-126-3p, age, and BMI. Discriminant analysis correctly classified 87.5% of patients (Wilks' Lambda, p < 0.05). F1 exhibited the highest ACE and hsa-miR-126-3p levels, lowest HDL-C, and most microvascular complications. F2 had the best renal function, lowest ACE and miR-126-3p expression, and the highest proportion of women. F3 patients were the oldest, with elevated uric acid and hsa-miR-423-5p levels. Coronary heart disease was most common in F1 and F3, while stroke occurred only in F1 and F2.
CONCLUSIONS: ACE, AIP, and the miRNAs hsa-miR-126-3p and hsa-miR-423-5p may support DKD phenotyping and kidney function prediction. Incorporating these markers into clinical models could enable the implementation of individualized nephroprotective strategies in patients with T2DM.
METHODS: Data from 79 patients with T2DM were analyzed. DKD phenotypes were defined based on eGFR and UACR: • F1 (albuminuric): eGFR < 60 mL/min/1.73 m², UACR ≥ 300 mg/g. • F2 (non-albuminuric, preserved filtration): eGFR ≥ 60 mL/min/1.73 m², UACR ≤ 30 mg/g. • F3 (non-albuminuric, reduced filtration): eGFR < 60 mL/min/1.73 m², UACR ≤ 30 mg/g. • F4 (moderately increased albuminuria): UACR > 30 and < 300 mg/g was shown for completeness but excluded from primary analyses. Multiple regression and partial least squares structural equation modeling (PLS-SEM) were applied to identify predictors of eGFR. Discriminant analysis (including age, ACE, uric acid, and AIP) was used for phenotype classification. Serum levels of hsa-miR-126-3p and hsa-miR-423-5p were compared between phenotypes.
RESULTS: Independent predictors of eGFR included ACE (β = - 0.478; p < 0.001), age (β = - 0.336), AIP (β = - 0.245), and hsa-miR-423-5p (β = 0.138; p = 0.033) (R² = 0.619). In the PLS-SEM model, ACE, AIP, and hsa-miR-423-5p had significant direct effects on eGFR, while ACE was modulated by hsa-miR-126-3p, age, and BMI. Discriminant analysis correctly classified 87.5% of patients (Wilks' Lambda, p < 0.05). F1 exhibited the highest ACE and hsa-miR-126-3p levels, lowest HDL-C, and most microvascular complications. F2 had the best renal function, lowest ACE and miR-126-3p expression, and the highest proportion of women. F3 patients were the oldest, with elevated uric acid and hsa-miR-423-5p levels. Coronary heart disease was most common in F1 and F3, while stroke occurred only in F1 and F2.
CONCLUSIONS: ACE, AIP, and the miRNAs hsa-miR-126-3p and hsa-miR-423-5p may support DKD phenotyping and kidney function prediction. Incorporating these markers into clinical models could enable the implementation of individualized nephroprotective strategies in patients with T2DM.