Observational studyBMC nephrology2025
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.
Observational study in BMC nephrology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Objective tongue phenotyping identifies phenotypic heterogeneity in diabetic kidney disease: a dual-center clustering analysis.Frontiers in endocrinology · 2026Article
- The triglyceride-glucose index in chronic kidney disease: a narrative review.Frontiers in nutrition · 2026Review
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and hypothesisDiabetic 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.
methodsData 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.
resultsIndependent 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.
conclusionsACE, 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.
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