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Anemia in Diabetic Patients Reflects Severe Tubulointerstitial Injury and Aids in Clinically Predicting a Diagnosis of Diabetic Nephropathy.

ABSTRACT: Objective A kidney biopsy is generally performed in diabetic patients to discriminate between diabetic nephropathy (DN) and non-diabetic kidney disease (NDKD) and to provide more specific treatments. This study investigated the impact of anemia on the renal pathology and the clinical course in patients who underwent a kidney biopsy. Methods We reviewed 81 patients with type 2 diabetes who underwent a percutaneous kidney biopsy. Patients were classified into two groups: isolated DN (DN group, n=30) and NDKD alone or concurrent DN (NDKD group, n=51) groups. The laboratory and pathological findings and clinical courses were investigated. Results In the NDKD group, membranous nephropathy was the most common finding (23.5%), followed by IgA nephropathy (17.6%) and crescentic glomerulonephritis (13.7%). In the logistic regression analysis, the absence of severe hematuria and presence of anemia were significantly associated with a diagnosis of DN. Akaike's information criterion (AIC) and net reclassification improvement (NRI) analyses revealed improved predictive performance by adding anemia to the conventional factors (AIC 100.152 to 91.844; NRI 27.0%). The tissues of patients in the DN group demonstrated more severe interstitial fibrosis and tubular atrophy (IF/TA) than those in the NDKD group (p<0.05) regardless of the rate of global glomerulosclerosis, and IF/TA was related to the prevalence of anemia (odds ratio: 7.31, 95% confidence interval: 2.33-23.00, p<0.01) according to a multivariable regression analysis. Furthermore, the isolated DN group demonstrated a poorer prognosis than the NDKD group. Conclusion DN is associated with anemia because of severe IF/TA regardless of the renal function, and anemia helps clinician discriminate clinically between isolated DN and NDKD.

SUBMITTER: Ito K

PROVIDER: S-EPMC8170246 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:AIMS: The tendency to develop diabetic nephropathy is, in part, genetically determined, however this genetic risk is largely undefined. In this proof-of-concept study, we tested the hypothesis that combined analysis of multiple genetic variants can improve prediction. METHODS: Based on previous reports, we selected 27 SNPs in 15 genes from metabolic pathways involved in the pathogenesis of diabetic nephropathy and genotyped them in 1274 Ashkenazi or Sephardic Jewish patients with Type 1 or Type 2 diabetes of >10 years duration. A logistic regression model was built using a backward selection algorithm and SNPs nominally associated with nephropathy in our population. The model was validated by using random "training" (75%) and "test" (25%) subgroups of the original population and by applying the model to an independent dataset of 848 Ashkenazi patients. RESULTS: The logistic model based on 5 SNPs in 5 genes (HSPG2, NOS3, ADIPOR2, AGER, and CCL5) and 5 conventional variables (age, sex, ethnicity, diabetes type and duration), and allowing for all possible two-way interactions, predicted nephropathy in our initial population (C-statistic?=?0.672) better than a model based on conventional variables only (C?=?0.569). In the independent replication dataset, although the C-statistic of the genetic model decreased (0.576), it remained highly associated with diabetic nephropathy (?(2)?=?17.79, p<0.0001). In the replication dataset, the model based on conventional variables only was not associated with nephropathy (?(2)?=?3.2673, p?=?0.07). CONCLUSION: In this proof-of-concept study, we developed and validated a genetic model in the Ashkenazi/Sephardic population predicting nephropathy more effectively than a similarly constructed non-genetic model. Further testing is required to determine if this modeling approach, using an optimally selected panel of genetic markers, can provide clinically useful prediction and if generic models can be developed for use across multiple ethnic groups or if population-specific models are required.

Project description:Diabetic nephropathy (DN) is the most important cause of end-stage renal disease with a poorer prognosis and high economic burdens of medical treatments. It is of great research value and clinical significance to explore potential gene targets of renal tubulointerstitial lesions in DN. To properly identify key genes associated with tubulointerstitial injury of DN, we initially performed a weighted gene coexpression network analysis of the dataset to screen out two nonconserved gene modules (dark orange and dark red). The regulation of oxidative stress-induced intrinsic apoptotic signaling pathway, PI3K-Akt signaling pathway, p38MAPK cascade, and Th1 and Th2 cell differentiation were primarily included in Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of these two modules. Next, 199 differentially expressed genes (DEGs) were identified via the limma package. Then, the GO annotation and KEGG pathways of the DEGs were primarily enriched in extracellular matrix (ECM) organization, epithelial cell migration, cell adhesion molecules (CAMs), NF-kappa B signaling pathway, and ECM-receptor interaction. Gene set enrichment analysis showed that in the DN group, the interaction of ECM-receptor, CAMs, the interaction of cytokine-cytokine receptor, and complement and coagulation cascade pathways were significantly activated. Eleven key genes, including ALB, ANXA1, ANXA2, C3, CCL2, CLU, EGF, FOS, PLG, TIMP1, and VCAM1, were selected by constructing a protein-protein interaction network, and expression validation, ECM-related pathways, and glomerular filtration rate correlation analysis were performed in the validated dataset. The upregulated expression of hub genes ANXA2 and FOS was verified by real-time quantitative PCR in HK-2 cells treated with high glucose. This study revealed potential regulatory mechanisms of renal tubulointerstitial damage and highlighted the crucial role of extracellular matrix in DN, which may promote the identification of new biomarkers and therapeutic targets.

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Anemia in Diabetic Patients Reflects Severe Tubulointerstitial Injury and Aids in Clinically Predicting a Diagnosis of Diabetic Nephropathy.

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