Identification of clinical predictors of diabetic nephropathy and non-diabetic renal disease in Chinese patients with type 2 diabetes, with reference to disease course and outcome

Kidney Biopsy Findings Among Patients With Diabetes in the Cleveland Clinic Kidney Biopsy Epidemiology Project

Rationale & Objectives

Diabetic kidney disease (DKD) is a significant complication of diabetes mellitus, often leading to kidney failure. The absence of well-defined factors prevents distinguishing DKD from non-diabetic kidney disease (non-DKD; alternative primary diagnosis identified on kidney biopsy).

Study Design

Retrospective cohort study.

Setting & Participants

This study assessed 1,242 patients with a history of diabetes from the Cleveland Clinic Kidney Biopsy Epidemiology Project between January 2015 and September 2021.

Exposure

Proteinuria, retinopathy, A1c levels, and estimated glomerular filtration rate.

Outcomes

Non-DKD, defined as an alternative primary diagnosis identified on kidney biopsy other than DKD.

Analytical Approach

Multivariate logistic regression model with backward elimination method.

Results

At the time of biopsy, the median (IQR) age was 63 (53-71 years) years, and 58.8% were men. The median hemoglobin A1c value was 6.7% (6.0%-8.1%), and the median serum creatinine level was 2.5 (1.6-3.9 mg/dL) mg/dL. Among 1,242 patients, 462 (37.2%) had DKD alone, and 780 (62.8%) had non-DKD. Among those with non-DKD, the most common diagnoses were focal segmental glomerulosclerosis (24%), global glomerulosclerosis otherwise not specified (13%), acute tubular necrosis (9%), IgA nephropathy (8%), antineutrophil cytoplasmic antibody vasculitis (7%), and membranous nephropathy (5%). Factors associated with having non-DKD on biopsy were having no retinopathy (vs retinopathy) (adjusted odds ratio [aOR], 3.98; 95% CI, 2.69-5.90), lower A1c levels (<7% vs ≥7%) (aOR, 3.08; 95% CI, 2.16-4.39), higher estimated glomerular filtration rate (≥60 vs <60 mL/min/1.73 m2) (aOR, 2.39; 95% CI 1.28-4.45), microalbuminuria (<300 vs macroalbuminuria ≥300 [mg/g]) (aOR; 2.94; 95% CI, 1.84-4.72), and lower protein-creatinine ratio on random urine sample (<3 vs ≥3 mg/mg) (aOR; 1.80; 95% CI, 1.24-2.61).

Limitations

Selection bias of clinically indicated biopsies, not protocol biopsies, which likely represent a ceiling (maximum) for non-DKD.

Conclusions

Among patients with diabetes undergoing kidney biopsy, 63% have findings in addition to DKD on biopsy. We identified clinical parameters associated with non-DKD in the setting of diabetes. This provides valuable information for clinicians when kidney biopsy should be considered among patients with diabetes to capture all etiologies of proteinuria and kidney dysfunction.

The role of kidney biopsy in deciphering diabetic versus non-diabetic origin of kidney disease among patients with type 2 diabetes mellitus and nephrotic range proteinuria: A retrospective study

Background

Diabetes mellitus (DM) is tightly associated with the increased prevalence of diabetic kidney disease (DKD). Nonetheless, severe renal function impairment and/or nephrotic range-proteinuria could also result from non-diabetic renal disease (non-DRD) among patients with DM. The 'Gold standard' for the differential diagnosis between DKD and non-DRD is kidney biopsy, although no real consensus exists. Thus, this study intends to associate the clinical and biochemical profile of patients with DM and renal disease with the histopathological data of kidney biopsy.In addition, we aimed to evaluate the role of kidney biopsy, especially when other causes, other than DM, are highly suspected among patients with DM and kidney disease.

Methods

Thirty two patients with T2DM and nephrotic range levels of proteinuria or with co-existing factors pointing towards a non-diabetic origin of kidney disease were studied, retrospectively. All 32 patients underwent kidney biopsy and were classified according to histopathological findings into 3 groups: a) isolated diabetic kidney disease (DKD), b) non-diabetic kidney disease (NDKD) and c) mixed kidney disease (MKD).

Results

Fifteen out of the 32 patients had findings of an isolated DKD, while 17 out of 32 patients suffered from NDKD (13 patients) or MKD (4 patients). DKD patients were younger (p = 0.016) and had a higher HbA1c value (p = 0.069, borderline statistical significance), while the NDKD patients had significantly shorter disease duration (p = 0.04). Furthermore, the incidence of diabetic retinopathy (DR) was lower among the NDKD patients (p < 0.001), who had also significantly less interstitial fibrosis (p = 0.02). Finally, the presence of DR, higher levels of interstitial fibrosis and longer T2DM duration were recognized as factors, which were positively associated with DKD.

Conclusion

This study advocates the usefulness of kidney biopsy in patients with T2DM and nephrotic range levels of proteinuria, especially when DR is absent and shorter disease duration is observed.

Spectrum of Nondiabetic Kidney Diseases in Patients with Type 2 Diabetes Mellitus Who Underwent Kidney Biopsy in Egypt

INTRODUCTION

Diabetic kidney disease (DKD) affects 30-40% of patients with diabetes. The prevalence of nondiabetic kidney disease (NDKD) in patients with type 2 diabetes mellitus (T2D) in Egypt is unknown. This study aimed to assess the prevalence of NDKD in patients with T2D in Egypt.

METHODS

In this cross-sectional study, we searched the data of patients with T2D who underwent a native kidney biopsy between January 2010 and December 2020 in a kidney pathology laboratory in Egypt.

RESULTS

Of 12,006 patients who underwent kidney biopsy, 677 patients had T2D. NDKD was found in 285 patients (42.7%), DKD in 220 patients (33%), and mixed DKD and NDKD in 162 patients (24.3%). The total prevalence of NDKD was 67% in patients with T2D in our study group. Membranous nephropathy was the most common histopathological disease in patients with NDKD (20.6%) followed by acute tubular injury (ATI) (19.2%) and focal segmental glomerulosclerosis (15.2%). The presence of ATI in a kidney biopsy was associated with a significantly higher mean serum creatine level (p < 0.001). Minimal change disease was associated with a significantly higher proteinuria level (p < 0.001). In binary logistic regression analysis, combining NDKD and mixed groups, the duration of diabetes was a negative predictor of NDKD, with a longer duration decreasing the likelihood of NDKD.

CONCLUSION

NDKD is prevalent among patients with T2D who underwent a kidney biopsy. Kidney biopsy remains the gold standard for diagnosing NDKD in patients with T2D.

A retrospective cohort study of clinical characteristics and outcomes of type 2 diabetic patients with kidney disease

Background

Type 2 diabetes mellitus (T2DM) with chronic kidney disease (CKD) poses a serious health threat and becomes a new challenge. T2DM patients with CKD fall into three categories, diabetic nephropathy (DN), non-diabetic kidney disease (NDKD), and diabetic nephropathy plus non-diabetic kidney disease (DN + NDKD), according to kidney biopsy. The purpose of our study was to compare the clinical characteristics and kidney outcomes of DN, NDKD, and DN + NDKD patients.

Methods

Data on clinical characteristics, pathological findings, and prognosis were collected from June 2016 to July 2022 in patients with previously diagnosed T2DM and confirmed DN and or NDKD by kidney biopsy at Tongji Hospital in Wuhan, China. The endpoint was defined as kidney transplantation, dialysis, or a twofold increase in serum creatinine.

Results

In our 6-year retrospective cohort research, a total of 268 diabetic patients were admitted and categorized into three groups by kidney biopsy. The 268 patients were assigned to DN (n = 74), NDKD (n = 109), and DN + NDKD (n = 85) groups. The most frequent NDKD was membranous nephropathy (MN) (n = 45,41.28%). Hypertensive nephropathy was the most common subtype in the DN+NDKD group (n = 34,40%). A total of 34 patients (12.7%) reached the endpoint. The difference between the Kaplan-Meier survival curves of the DN, NDKD, and DN + NDKD groups was significant (p < 0.05). Multifactorial analysis showed that increased SBP [HR (95% CI): 1.018(1.002-1.035), p = 0.025], lower Hb [HR(95% CI): 0.979(0.961-0.997), p = 0.023], higher glycosylated hemoglobin [HR(95% CI): 1.338(1.080-1.658), p = 0.008] and reduced serum ALB [HR(95% CI): 0.952(0.910-0.996), p = 0.032] were risk factors for outcomes in the T2DM patients with CKD.

Conclusions

This research based on a Chinese cohort demonstrated that the risk of endpoint events differed among DN, NDKD, and DN+NDKD patients. In T2DM patients with CKD, DN patients displayed worse kidney prognosis than those with NDKD or DN + NDKD. Increased SBP, higher glycosylated hemoglobin, lower Hb, and decreased serum ALB may be correlated with adverse kidney outcomes in T2DM patients.

Developing screening tools to estimate the risk of diabetic kidney disease in patients with type 2 diabetes mellitus

BACKGROUND

Diabetic kidney disease (DKD) is an important microvascular complication of diabetes mellitus (DM).

OBJECTIVE

This study aimed to develop predictive nomograms to estimate the risk of DKD in patients with type 2 diabetes mellitus (T2DM).

METHODS

The medical records of patients with T2DM in our hospital from March 2022 to March 2023 were retrospectively reviewed. The enrolled patients were randomly selected for training and validation sets in a 7:3 ratio. The models for predicting risk of DKD were virtualized by the nomograms using logistic regression analysis.

RESULTS

Among the enrolled 597 patients, 418 were assigned to the training set, while 179 were assigned to the validation set. Using the predictors included glycated hemoglobin A1c (HbA1c), high density lipoprotein cholesterol (HDL-C), presence of diabetic retinopathy (DR) and duration of diabetes (DD), we constructed a full model (model 1) for predicting DKD. And using the laboratory indexes of HbA1c, HDL-C, and cystatin C (Cys-C), we developed a laboratory-based model (model 2). The C-indexes were 0.897 for model 1 and 0.867 for model 2, respectively. The calibration curves demonstrated a good agreement between prediction and observation in the two models. The decision curve analysis (DCA) curves showed that the two models achieved a net benefit across all threshold probabilities.

CONCLUSION

We successfully constructed two prediction models to evaluate the risk of DKD in patients with T2DM. The two models exhibited good predictive performance and could be recommended for DKD screening and early detection.

Identification of urinary extracellular vesicles differentially expressed RNAs in diabetic nephropathy via whole-transcriptome integrated analysis

BACKGROUND

Diabetic nephropathy (DN) is a common systemic microvascular complication of diabetes and a leading cause of chronic kidney disease worldwide. Urinary extracellular vesicles (uEVs), which are natural nanoscale vesicles that protect RNA from degradation, have the potential to serve as an invasive diagnostic biomarker for DN.

METHODS

We enrolled 24 participants, including twelve with renal biopsy-proven T2DN and twelve with T2DM, and isolated uEVs using ultracentrifugation. We performed microarrays for mRNAs, lncRNAs, and circRNAs in parallel, and Next-Generation Sequencing for miRNAs. Differentially expressed RNAs (DE-RNAs) were subjected to CIBERSORTx, ssGSEA analysis, GO enrichment, PPI network analysis, and construction of the lncRNA/circRNA-miRNA-mRNA regulatory network. Candidate genes and potential biomarker RNAs were validated using databases and machine learning models.

RESULTS

A total of 1684 mRNAs, 126 lncRNAs, 123 circRNAs and 66 miRNAs were found in uEVs in T2DN samples compared with T2DM. CIBERSORTx revealed the involvement of uEVs in immune activity and ssGSEA explored possible cell or tissue sources of uEVs. A ceRNA co-expression and regulation relationship network was constructed. Candidate genes MYO1C and SP100 mRNA were confirmed to be expressed in the kidney using Nephroseq database, scRNA-seq dataset, and Human Protein Atlas database. We further selected 2 circRNAs, 2 miRNAs, and 2 lncRNAs from WGCNAs and ceRNAs and demonstrated their efficacy as potential diagnostic biomarkers for T2DN using machine learning algorithms.

CONCLUSIONS

This study reported, for the first time, the whole-transcriptome genetic resources found in urine extracellular vesicles of T2DN patients. The results provide additional support for the possible interactions, and regulators between RNAs from uEVs themselves and as potential biomarkers in DN.

Diabetes-Related Microvascular Complications in Primary Health Care Settings in the West Bank, Palestine

BACKGROUND

Worldwide, retinopathy, nephropathy, and neuropathy are the major diabetes-related microvascular complications. In Palestine, a low-middle-income country, diabetes is the fourth reason for death. However, a few studies examined diabetes microvascular consequences and its management. Therefore, we carried out a national study that aims to investigate the factors associated with diabetes-related microvascular complications among individuals seeking care in primary healthcare settings of the West Bank of Palestine.

METHOD

Using a cluster systematic sampling technique, 882 participants with diabetes patients were chosen for a cross-sectional study from primary healthcare facilities operated by the Ministry of Health (PMoH), the United Nations Relief and Works Agency (UNRWA), and the Palestinian Medical Relief Society (PMRS). Data about patients related to diabetes-related complications, medication use, and other diseases were extracted from patients' medical records. In addition, an interview face-to-face questionnaire was used to collect information about patients' sociodemographic variables, medical history, smoking habits, duration of the disease, presence of concurrent conditions previous referrals, and hospital admissions, as well as their level of knowledge regarding diabetes, complications, and treatments.

RESULTS

Approximately 34.4% of persons with diabetes patients in Palestine encounter at least one microvascular complication associated with diabetes. The most prevalent diabetes-related microvascular complication was retinopathy (17.3%), 23.4% of participants had more than one microvascular complication, and 29% of male patients had erectile dysfunction. A higher probability of having any microvascular complications was associated with older age (over 60 years). Participants with diabetes patients with fundoscopy or ophthalmology reports, according to diabetes follow-up guidelines, were less likely to develop retinopathy. Also, those who performed regular kidney function testing were less likely to have nephropathy, and those who performed a regular foot exam were less likely to develop diabetic foot.

CONCLUSIONS

Diabetes-related microvascular complications were associated with patient age, low education level, residency location, and adherence to diabetes follow-up guidelines of diabetes management; i.e., having been tested for HbA1c, consulting with specialists, regular kidney function, and foot examination. These factors can be utilized in setting up proper management protocols to prevent or delay microvascular complications in many patients.

Clinico-pathological features of diabetic and non-diabetic renal diseases in type 2 diabetic patients: a retrospective study from a 10-year experience in a single center

AIM

To compare clinical and pathological characteristics as well as prognosis between diabetic nephropathy (DN) and non-diabetic renal disease (NDRD) so as to explore potential diagnostic criteria of DN and provide some guidance for the treatment of type 2 diabetes mellitus (T2DM) patients with kidney involvement.

METHODS

T2DM patients with renal impairment who underwent kidney biopsy were included in this study, who were classified into 3 groups (DN, NDRD, DN with NDRD) based on their renal pathological diagnosis. Baseline clinical characteristics as well as follow-up data were collected and analyzed among 3 groups. Logistic regression was performed to determine the best predictors for DN diagnosis. Additional 34 MN patients without diabetes were enrolled by propensity score matching method to compare serum PLA2R antibody titer and kidney outcomes between diabetic MN patients and MN alone.

RESULTS

Among 365 patients with type 2 diabetes who underwent kidney biopsy, 179 (49.0%) patients were diagnosed with NDRD alone and 37 (10.1%) patients with NDRD combined DN. Risk factors for DN development in T2DM patients were longer time since diabetes diagnosis, higher level of serum creatinine, absence of hematuria and presence of diabetic retinopathy by multivariate analysis. Lower rate of proteinuria remission and higher risk of renal progression were observed in DN group compared with NDRD group. Membranous nephropathy was the most common NDRD in diabetic patients. There was no difference in serum PLA2R antibody positiveness or titer between MN patients with or without T2DM. There was lower remission rate but similar renal progression in diabetic MN when age, gender, baseline eGFR, albuminuria and IFTA score were adjusted.

CONCLUSIONS

Non-diabetic renal disease is not uncommon in T2DM patients with renal impairment, which has better prognosis with proper treatment. Coexisting diabetic status does not exert negative impact on renal progression in MN patients, and immunosuppressive agents should be administered when necessary.

Analysis of clinical predictors of kidney diseases in type 2 diabetes patients based on machine learning

BACKGROUND

The heterogeneity of Type 2 Diabetes Mellitus (T2DM) complicated with renal diseases has not been fully understood in clinical practice. The purpose of the study was to propose potential predictive factors to identify diabetic kidney disease (DKD), nondiabetic kidney disease (NDKD), and DKD superimposed on NDKD (DKD + NDKD) in T2DM patients noninvasively and accurately.

METHODS

Two hundred forty-one eligible patients confirmed by renal biopsy were enrolled in this retrospective, analytical study. The features composed of clinical and biochemical data prior to renal biopsy were extracted from patients' electronic medical records. Machine learning algorithms were used to distinguish among different kidney diseases pairwise. Feature variables selected in the developed model were evaluated.

RESULTS

Logistic regression model achieved an accuracy of 0.8306 ± 0.0057 for DKD and NDKD classification. Hematocrit, diabetic retinopathy (DR), hematuria, platelet distribution width and history of hypertension were identified as important risk factors. Then SVM model allowed us to differentiate NDKD from DKD + NDKD with accuracy 0.8686 ± 0.052 where hematuria, diabetes duration, international normalized ratio (INR), D-Dimer, high-density lipoprotein cholesterol were the top risk factors. Finally, the logistic regression model indicated that DD-dimer, hematuria, INR, systolic pressure, DR were likely to be predictive factors to identify DKD with DKD + NDKD.

CONCLUSION

Predictive factors were successfully identified among different renal diseases in type 2 diabetes patients via machine learning methods. More attention should be paid on the coagulation factors in the DKD + NDKD patients, which might indicate a hypercoagulable state and an increased risk of thrombosis.

Development and validation of a novel nomogram to predict diabetic kidney disease in patients with type 2 diabetic mellitus and proteinuric kidney disease

PURPOSE

Differentiating between diabetic kidney disease (DKD) and non-diabetic kidney disease (NDKD) in patients with Type 2 diabetes mellitus (T2DM) is important due to implications on treatment and prognosis. Clinical methods to accurately distinguish DKD from NDKD are lacking. We aimed to develop and validate a novel nomogram to predict DKD in patients with T2DM and proteinuric kidney disease to guide decision for kidney biopsy.

METHODS

A hundred and two patients with Type 2 Diabetes Mellitus (T2DM) who underwent kidney biopsy from 1st January 2007 to 31st December 2016 were analysed. Univariate and multivariate analyses were performed to identify predictive variables and construct a nomogram. The discriminative ability of the nomogram was assessed by calculating the area under the receiver operating characteristic curve (AUROC), while calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test and calibration plot. Internal validation of the nomogram was assessed using bootstrap resampling.

RESULTS

Duration of T2DM, HbA1c, absence of hematuria, presence of diabetic retinopathy and absence of positive systemic biomarkers were found to be independent predictors of DKD in multivariate analysis and were represented as a nomogram. The nomogram showed excellent discrimination, with a bootstrap-corrected C statistic of 0.886 (95% CI 0.815-0.956). Both the calibration curve and the Hosmer-Lemeshow goodness-of-fit test (p = 0.242) showed high degree of agreement between the prediction and actual outcome, with the bootstrap bias-corrected curve similarly indicating excellent calibration.

CONCLUSIONS

A novel nomogram incorporating 5 clinical parameters is useful in predicting DKD in type 2 diabetes mellitus patients with proteinuric kidney disease.

Assessment of urinary podocalyxin as an alternative marker for urinary albumin creatinine ratio in early stage of diabetic kidney disease in older patients

This study's objective is to evaluate the correlation relationship between Podocalyxin (PCX), an urinary marker of podocytes, urinary albumin-creatinine ratio (ACR) and the predictive value of PCX in the routine screen of early diabetic kidney disease (DKD) among older people. We also aimed to explore its prediction value despite of other metabolic factor and how PCX alters in the predictive power for early stage of diabetic nephropathy. In retrospective, 320 cases of older patients diagnosed with type 2 diabetes mellitus who met both inclusion and exclusion criteria were collected and divided with levels of urinary albumin, that is, normal albuminuria group, microalbuminuria group and healthy group. The correlation coefficient between PCX and ACR, and the odds ratio of PCX were gauged in the study. Area under the receiver operating characteristic (ROC) curve was also calculated. There were 188 patients in the normal group with urine ACR<30mg/g, and 132 patients in the microproteinuria group with urine ACR 30-300mg/g. 132 cases of DKD diagnosed with ACR, among them, 104 cases of DKD were predicted by PCX. The percentage correction value was 78.8%. The following parameters such as gender, age, course of disease, glycated hemoglobin, triglyceride, total cholesterol, BMI, blood pressure, uric acid, and eGFR were used as variables for adjustment to establish the prediction model of urine PCX and ACR. Multiple logistic regression test was carried out to evaluate against the predictive ability of the model. The area under the ROC curve corresponding to the regression model after adjustment is 0.952. Although factors such as the course of disease, HbA1C, UA, and eGFR could influence on the predictive ability of PCX, PCX still has a good ability to predict early DKD in older patients. Therefore, it could be used as a diagnostic indicator for early-stage DKD in older patients.

Prognostic value of metabolic syndrome in renal structural changes in type 2 diabetes

PURPOSE

To investigate the prognostic value of metabolic syndrome (MetS) and its relationship with renal structure changes in patients with type 2 diabetes and associated diabetic nephropathy (DN).

METHODS

411 Chinese patients with type 2 diabetes and biopsy-confirmed DN were enrolled in this retrospective study. MetS was defined according to the modified criteria of the 2005 International Diabetes Federation. Baseline demographics and clinical information at the time of renal biopsy were extracted from the hospital's electronic medical records system. Renal pathological findings were assessed according to Renal Pathology Society system. Univariate and multivariate logistic regression analyses were performed to define the pathological covariates associated with MetS. A competing risk model, with death as the competing risk, was used to estimate the sub-distribution hazard ratio (SHR) of MetS for end-stage kidney disease (ESKD).

RESULTS

224 (55%) patients had MetS. Patients with MetS had poor renal function and more severe interstitial fibrosis tubular atrophy scores (IFTA) than those without MetS. Multivariate logistic regression analysis revealed that IFTA was significantly associated with MetS (odds ratio per score increase 1.45, 95% confidence interval [CI] 1.02-2.05). Of the patients with DN at risk, 40% of patients progressed to ESKD. After adjusting for renal function and pathological parameters, the presence of MetS was an independent predictor for progression to ESKD (SHR 1.93, 95% CI 1.34-2.79). The SHRs for progression to ESKD also increased as the number of MetS components increased. Additionally, adding the IFTA scores improved the prognostic power of a model that only contained MetS and clinical covariates for predicting future ESKD.

CONCLUSION

MetS is an independent prognostic predictor of ESKD in patients with T2D and DN, while adding the IFTA scores increased the prognostic value of MetS for renal outcome.

Diagnostic value of triglyceride and cystatin C ratio in diabetic kidney disease: a retrospective and prospective cohort study based on renal biopsy

Background

Currently, there is a lack of clinical indicators that can accurately distinguish diabetic kidney disease (DKD) from non-diabetic kidney disease (NDKD) in type 2 diabetes. The purpose of this study was to investigate the diagnostic value of triglyceride and cystatin C (TG/ Cys-C) ratio in DKD. Nowadays, there are few studies on the differential diagnosis of TG/ Cys-C ratio between DKD and NDKD.

Methods

The clinical data of patients with type 2 diabetes complicated with proteinuria who underwent renal biopsy from January 2013 to September 2019 in 2 hospitals in Xuzhou were retrospectively collected. According to the pathological classification of kidney, 25 patients in group DKD and 34 patients in non-diabetic kidney disease (NDKD) group were divided into two groups. The admission information and blood biochemical indexes of all patients with renal biopsy were collected, and the TG / Cys-C ratio was calculated. Logistic regression analysis was used to analyze the related factors of DKD in patients with type 2 diabetes and proteinuria. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic value of TG/Cys-C ratio for DKD in patients with type 2 diabetes and proteinuria. Another 37 patients with type 2 diabetes complicated by proteinuria who were treated in the Department of Nephrology, four hospitals in Xuzhou from October 2019 to October 2021 were selected as the research objects. The TG/Cys-C value cut-off value selected in the retrospective study was selected as the boundary point and divided into two groups according to the values of greater than or equal to the tangent point and less than the tangential point. Serum triglyceride and cystatin C levels were measured and TG / Cys-C ratio was calculated. All patients underwent ultrasound-guided fine-needle renal biopsy. The positive rates of DKD diagnosis in the two groups were compared to verify the predictive value of TG / Cys-C ratio in the diagnosis of DKD.

Results

Retrospective study showed that compared with group NDKD, the DKD group had higher systolic blood pressure, higher cystatin C and creatinine, more diabetic retinopathy, longer duration of diabetes, lower hemoglobin concentration, lower glomerular filtration rate, lower cholesterol, lower triglyceride and lower TG/ Cys-C ratio (P < 0.05).Multivariate Logistic regression analysis showed that TG/Cys-C ratio (OR = 0.429, P = 0.009) was a protective factor for DKD in patients with type 2 diabetes and proteinuria. Diabetic retinopathy (OR = 7.054, P = 0.021) and systolic blood pressure (OR = 1.041, P = 0.047) were independent risk factors for DKD in patients with type 2 diabetes complicated with proteinuria. ROC curve showed that the area under the curve predicted by TG/Cys-C ratio for the diagnosis of DKD was 0.816, the sensitivity was 84%, and the specificity was 67.6%. The tangent value of TG / Cys-C ratio is 2.43. Prospective studies showed that in 37 patients with type 2 diabetes and proteinuria, 29 patients had a TG/Cys-C ratio of less than 2.43. The TG/Cys-C ratio of 8 patients was more than 2.43. Ultrasound guided fine needle aspiration biopsy revealed that 22 of the 29 patients had pathological diagnosis of DKD, sensitivity 91.67%, specificity 46.15%, positive predictive value 75.80%, and negative predictive value 75%.

Conclusion

In type 2 diabetic patients with proteinuria, the ratio of TG/Cys-C has certain predictive value for the diagnosis of DKD.

Clinical predictors for nondiabetic kidney diseases in patients with type 2 diabetes mellitus: a retrospective study from 2017 to 2021

BACKGROUND

Nondiabetic kidney disease (NDKD), which is prevalent among patients with diabetes mellitus (DM), is considerably different from diabetic kidney disease (DKD) in terms of the pathological features, treatment strategy and prognosis. Although renal biopsy is the current gold-standard diagnostic method, it cannot be routinely performed due to a range of risks. The aim of this study was to explore the predictors for differentiating NDKD from DKD to meet the urgent medical needs of patients who cannot afford kidney biopsy.

METHODS

This is a retrospective study conducted by reviewing the medical records of patients with type 2 DM who underwent percutaneous renal biopsy at the Affiliated Hospital of Guizhou Medical University between January 2017 and May 2021. The demographic data, clinical data, blood test results, and pathological examination results of the patients were obtained from their medical records. Multivariate regression analysis was performed to evaluate the predictive factors for NDKD.

RESULTS

A total of 244 patients were analyzed. The median age at biopsy was 55 (46, 62) years. Patients diagnosed with true DKD, those diagnosed with NDKD and those diagnosed with NDKD superimposed DKD represented 48.36% (118/244), 45.9% (112/244) and 5.74% (14/244), respectively, of the patient population. Immunoglobulin A nephropathy was the most common type of lesion in those with NDKD (59, 52.68%) and NDKD superimposed DKD (10, 71.43%). Independent predictive indicators for diagnosing NDKD included a DM duration of less than 5 years (odds ratio [OR] = 4.476; 95% confidence interval [CI]: 2.257-8.877; P < 0.001), an absence of diabetic retinopathy (OR = 4.174; 95% CI: 2.049-8.502; P < 0.001), a high RBC count (OR = 1.901; 95% CI: 1.251-2.889; P = 0.003), and a negative of urinary glucose excretion test result (OR = 2.985; 95% CI: 1.474-6.044; P = 0.002)..

CONCLUSIONS

A DM duration less than 5 years, an absence of retinopathy, a high RBC count and an absence of urinary glucose excretion were independent indicators for the diagnosis of NDKD, suggesting that patients with NDKD may require a different treatment regimen than those with DKD.

The analysis of risk factors for diabetic kidney disease progression: a single-centre and cross-sectional experiment in Shanghai

OBJECTIVE

To identify the risk factors for diabetic kidney disease (DKD) development, especially the difference between patients with different courses.

PATIENTS AND METHODS

791 patients were considered to be eligible and were enrolled in the cross-sectional study from Shanghai Tongren Hospital Inpatient Department. 36 variables were initially screened by univariate analysis. The risk factors affecting progression of DKD were determined by logistics regression analysis. Subgroups were grouped according to the course of diabetes disease, and multivariate logistics regression analysis was performed to find out the different risk factors in two subgroups. Finally, the receiver operating characteristics curve is used to verify the result.

RESULTS

The logistic regression model indicated age (OR=1.020, p=0.017, 95% CI 1.004 to 1.040), systolic blood pressure (OR=1.013, p=0.006, 95% CI 1.004 to 1.022), waist circumference (OR=1.021, p=0.015, 95% CI 1.004 to 1.038), white blood cells (WBC, OR=1.185, p=0.001, 95% CI 1.085 to 1.295) and triglycerides (TG, OR=1.110, p=0.047, 95% CI 1.001 to 1.230) were risk factors for DKD, while free triiodothyronine (fT3, OR=0.711, p=0.011, 95% CI 0.547 to 0.926) was a protective factor for DKD in patients with type 2 diabetes mellitus (T2DM). Subgroup analysis revealed that in patients with a short duration of diabetes (<8 years), WBC (OR=1.306, p<0.001, 95% CI 1.157 to 1.475) and TG (OR=1.188, p=0.033, 95% CI 1.014 to 1.393) were risk factors for DKD,fT3 (OR=0.544, p=0.002, 95% CI 0.367 to 0.804) was a protective factor for DKD; whereas for patients with disease course more than 8 years, age (OR=1.026, Pp=0.012, 95%CI=95% CI[ 1.006- to 1.048]) was identified as the only risk factor for DKD and fT3 (OR=0.036, Pp=0.017, 95%CI=95% CI[ 0.439- to 0.922]) was a protective factor for DKD.

CONCLUSION

The focus of attention should especially be on patients with a prolonged course of T2DM, and those with comorbid hypertension and hypertriglyceridaemia waist phenotype. More potential clinical indexes such as thyroid function and inflammatory indicators might be considered as early warning factors for DKD in T2DM. Women should pay attention to controlling inflammation and TGs, and men should strictly control blood pressure. Avoiding abdominal obesity in both men and women will bring great benefits.

Salivary Glycopatterns as Potential Non-Invasive Biomarkers for Diagnosing and Reflecting Severity and Prognosis of Diabetic Nephropathy

Discriminating between diabetic nephropathy (DN) and non-diabetic renal disease (NDRD) can help provide more specific treatments. However, there are no ideal biomarkers for their differentiation. Thus, the aim of this study was to identify biomarkers for diagnosing and predicting the progression of DN by investigating different salivary glycopatterns. Lectin microarrays were used to screen different glycopatterns in patients with DN or NDRD. The results were validated by lectin blotting. Logistic regression and artificial neural network analyses were used to construct diagnostic models and were validated in in another cohort. Pearson's correlation analysis, Cox regression, and Kaplan-Meier survival curves were used to analyse the correlation between lectins, and disease severity and progression. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) and bioinformatics analyses were used to identify corresponding glycoproteins and predict their function. Both the logistic regression model and the artificial neural network model achieved high diagnostic accuracy. The levels of Aleuria aurantia lectin (AAL), Lycopersicon esculentum lectin (LEL), Lens culinaris lectin (LCA), Vicia villosa lectin (VVA), and Narcissus pseudonarcissus lectin (NPA) were significantly correlated with the clinical and pathological parameters related to DN severity. A high level of LCA and a low level of LEL were associated with a higher risk of progression to end-stage renal disease. Glycopatterns in the saliva could be a non-invasive tool for distinguishing between DN and NDRD. The AAL, LEL, LCA, VVA, and NPA levels could reflect the severity of DN, and the LEL and LCA levels could indicate the prognosis of DN.

Characterizing predictors of non-diabetic kidney disease (NDKD) in diabetic patients

BACKGROUND

Diabetic kidney disease (DKD) is the chief cause of renal involvement in diabetic patients. It is primarily a clinical diagnosis. Non-diabetic kidney disease (NDKD) may be missed if they are not biopsied. In this study, we describe the spectrum of NDKD and evaluate the predictors considered for planning a biopsy in diabetic patients with kidney disease.

METHODS

In a retrospective cohort study, diabetic patients who underwent kidney biopsy at our centre between May 2006 and July 2019 were evaluated for NDKD.

RESULTS

321 diabetic patients who underwent kidney biopsy were analyzed. Mean age was 49.3 ± 12.4 years and 71% were males. 75.8% patients had hypertension and 25.2% had diabetic retinopathy. Based on the kidney biopsy, patients were classified as DKD-127 (39.6%), NDKD-179(55.8%) and combined DKD + NDKD-15(4.7%). Overall, the most commonly diagnosed pathology was membranous nephropathy-MN (17%), followed by IgA nephropathy (16.0%) and focal segmental glomerulosclerosis-FSGS (14.9%). In patients with DKD + NDKD, IgA nephropathy (53.3%) was predominant. 165 (51.4%) patients had a diagnosis potentially amenable to a specific therapy. On multivariate analysis, female gender [OR 2.07 (1.08-3.97), p = 0.02], absence of diabetic retinopathy [OR 7.47 (3.71-15), p < 0.001] absence of hypertension [OR 3.17 (1.56-6.45), p = 0.001] and duration of diabetes ≤ 24 months [OR 3.67(1.97-6.84), p < 0.001], were independent predictors for NDKD while the absence of nephrotic range proteinuria [OR 1.73 (0.98-3.05), p 0.05] showed a trend towards significance.

CONCLUSION

Astute use of kidney biopsy can detect potentially treatable NDKD in a large number of diabetic patients with glomerular diseases being the predominant diagnosis. A combination of risk factors needs to be considered to guide the need for kidney biopsy in diabetic patients.

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

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.

Identification of Lumican and Fibromodulin as Hub Genes Associated with Accumulation of Extracellular Matrix in Diabetic Nephropathy

INTRODUCTION

Diabetic nephropathy (DN) remains a major cause of end-stage renal disease. The development of novel biomarkers and early diagnosis of DN are of great clinical importance. The goal of this study was to identify hub genes with diagnostic potential for DN by weighted gene co-expression network analysis (WGCNA).

METHODS

Gene Expression Omnibus database was searched for microarray data including distinct types of CKD. Gene co-expression network was constructed, and modules specific for DN were identified by WGCNA. Gene ontology (GO) analysis was performed, and the hub genes were screened out within the selected gene modules. In addition, cross-validation was performed in an independent dataset and in samples of renal biopsies with DN and other types of glomerular diseases.

RESULTS

Dataset GSE99339 was selected, and a total of 179 microdissected glomeruli samples were analyzed, including DN, normal control, and 7 groups of other glomerular diseases. Twenty-three modules of the total 10,947 genes were grouped by WGCNA, and a module was specifically correlated with DN (r = 0.54, p = 9e-15). GO analysis showed that module genes were mainly enriched in the accumulation of extracellular matrix (ECM). LUM, ELN, FBLN1, MMP2, FBLN5, and FMOD were identified as hub genes. Cross verification showed LUM and FMOD were higher in the DN group and were negatively correlated with estimated glomerular filtration rate (eGFR). In renal biopsies, expression levels of LUM and FMOD were higher in DN than IgA nephropathy, membranous nephropathy, and normal controls.

CONCLUSION

By using WGCNA approach, we identified LUM and FMOD related to ECM accumulation and were specific for DN. These 2 genes may represent potential candidate diagnostic biomarkers of DN.

Diagnostic roles of urinary kidney microvesicles in diabetic nephropathy

Background

The pathology of diabetic nephropathy (DN) broadly involves the injury of glomeruli, tubulointerstitium and endothelium. Cells from these compartments can release increased numbers of microvesicles (MVs) into urine when stressed or damaged. Currently whether urinary MVs from these three parts can help diagnose DN and reflect pathological features remain unclear.

Methods

Forty-nine patients with histologically proven DN and 29 proteinuric controls with membranous nephropathy or minimal change disease were enrolled. Urinary podocyte, proximal tubular and endothelial cell-derived MVs were quantified by flow cytometry. Renal glomerular, tubulointerstitial and vascular lesions were semi-quantitatively scored and their relevance to urinary MVs were analyzed.

Results

DN patients had greater numbers of urinary MVs from podocytes, proximal tubular and endothelial cells compared with proteinuric controls. The combination of podocyte nephrin+ MVs and diabetic retinopathy optimally diagnose DN with 89.7% specificity and 88.9% sensitivity. Moreover, positive correlations were observed between urinary levels of proximal tubular MVs and the severity of tubular injury and between urinary levels of endothelial MVs and the degree of vascular injury. Using urinary proximal tubular MVs as the indicators for tubular injury, the differences between DN patients and proteinuric controls diminished after matching the degree of renal vascular injury or when proteinuria >8 g/24 h.

Conclusions

Urinary kidney-specific cell-derived MVs might serve as noninvasive biomarkers for the diagnosis of DN in diabetic proteinuric patients. Their elevated levels could reflect corresponding renal pathological lesions, helping physicians look into the heterogeneity of DN.

A retrospective cohort study on the pathology and outcomes of type 2 diabetic patients with renal involvement

OBJECTIVE

To investigate the association of clinical and histological characteristics and the development of ESRD in T2DM patients with renal involvement.

METHODS

We conducted a retrospective analysis of clinical and pathologic data from T2DM patients who underwent renal biopsy (n = 120).

RESULTS

The mean age, duration of diabetes, and eGFR were 50.9 ± 11.2 years, 92.8 ± 41.3 months, 55.1 ± 42.3 mL/min/1.73 m², respectively. Among these patients, 57 (47.5%) were diagnosed with diabetic nephropathy (DN), and 63 (52.5%) with non-diabetic renal disease (NDRD). The most common subtype of NDRD is membranous nephropathy. Compared with the NDRD group, the DN group had a longer duration of diabetes, worse renal function, and a higher proportion of diabetic retinopathy. Kaplan-Meier analysis showed that the 5-year renal survival rate of the DN group was only 41%, whereas that of the NDRD group was 84%. ESRD was defined as eGFR below 15 mL/min/1.73 m². After multivariate adjustment, the risk of ESRD in DN patients was 3.81 times higher than that in NDRD patients. According to Glomerular Class, the 5-year renal survival rate of type IIA, IIB, III, and IV in the DN group was 88, 56, 28, and 15%, respectively. Kaplan-Meier analysis showed that there was a significant difference in renal survival among different glomerular classes or different interstitial fibrosis and tubular atrophy (IFTA) scores. But Cox proportional hazards analysis indicated that only IFTA score (HR 2.75, 95% CI 1.37-5.51, P = 0.001), but not the glomerular class (HR 1.21, 95% CI 0.73-2.00, P = 0.465), could predict renal outcome when adjusting for multivariate.

CONCLUSION

The prognosis of DN patients is significantly worse than that of NDRD patients. Compared with glomerular lesions, tubulointerstitial lesions were associated with higher risk for renal death in DN patients.

Insights into the Role of Renal Biopsy in Patients with T2DM: A Literature Review of Global Renal Biopsy Results

INTRODUCTION

Renal biopsy performed in patients with type 2 diabetes mellitus (T2DM) for atypical or suspected diabetic kidney disease (DKD) reveals one of three possibilities: diabetic nephropathy (DN, pathological diagnosis of DKD), nondiabetic kidney disease (NDKD) and DN plus NDKD (mixed form). NDKD (including the mixed form) is increasingly being recognized worldwide. With the emerging concept of DKD and the complexity of routine application of renal biopsy, the identification of "clinical indicators" to differentiate DKD from NDKD has been an area of active research.

METHODS

The PubMed database was searched for relevant articles mainly according to the keyword search method. We reviewed prevalence of the three types of DKD and different pathological lesions of NDKD. We also reviewed the clinical indicators used to identify DKD and NDKD.

RESULTS

The literature search identified 40 studies (5304 data) worldwide between 1977 and 2019 that looked at global renal biopsy and pathological NDKD lesions. The overall prevalence rate of DN, NDKD and DN plus NDKD is reported to be 41.3, 40.6 and 18.1%, respectively. In Asia, Africa (specifically Morocco and Tunisia) and Europe, the most common isolated NDKD pathological type is membranous nephropathy, representing 24.1, 15.1 and 22.6% of cases, respectively. In contrast, focal segmental glomerulosclerosis is reported to be the primary pathological type in North America (specifically the USA) and Oceania (specifically New Zealand), representing 22% and 63.9% of cases, respectively. Tubulointerstitial disease accounts for a high rate in the mixed group (21.7%), with acute interstitial nephritis being the most prevalent (9.3%), followed by acute tubular necrosis (9.0%). Regarding clinical indicators to differentiate DKD from NDKD, a total of 14 indicators were identified included in 42 studies. Among these, the most commonly studied indicators included diabetic retinopathy, duration of diabetes, proteinuria and hematuria. Regrettably, indicators with high sensitivity and specificity have not yet been identified.

CONCLUSION

To date, renal biopsy is still the gold standard to diagnose diabetes complicated with renal disease, especially when T2DM patients present atypical DKD symptoms (e.g. absence of diabetic retinopathy, shorter duration of diabetes, microscopic hematuria, sub-nephrotic range proteinuria, lower glycated hemoglobin, lower fasting blood glucose). We conclude that renal biopsy as early as possible is of great significance to enable personalized treatment to T2DM patients.

Identification of Key Genes of Human Advanced Diabetic Nephropathy Independent of Proteinuria by Transcriptome Analysis

Background

Diabetic nephropathy (DN) is the leading cause of ESRD. Emerging evidence indicated that proteinuria may not be the determinant of renal survival in DN. The aim of the current study was to provide molecular signatures apart from proteinuria in DN by an integrative bioinformatics approach.

Method

Affymetrix microarray datasets from microdissected glomerular and tubulointerstitial compartments of DN, healthy controls, and proteinuric disease controls including minimal change disease and membranous nephropathy were extracted from open-access database. Differentially expressed genes (DEGs) in DN versus both healthy and proteinuric controls were identified by limma package, and further defined by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Hub genes were checked by protein-protein interaction networks.

Results

A total of 566 glomerular and 581 tubulointerstitial DEGs were identified in DN, which were commonly differentially expressed compared to normal controls and proteinuric disease controls. The upregulated DEGs in both compartments were significantly enriched in GO biological process associated with fibrosis, inflammation, and platelet dysfunction, and largely located in extracellular space, including matrix and extracellular vesicles. Pathway analysis highlighted immune system regulation. Hub genes of the upregulated DEGs negatively correlated with estimated glomerular filtration rate (eGFR). While the downregulated DEGs and their hub genes in tubulointerstitium were enriched in pathways associated with lipid metabolism and oxidation, which positively correlated with eGFR.

Conclusions

Our study identified pathways including fibrosis, inflammation, lipid metabolism, and oxidative stress contributing to the progression of DN independent of proteinuria. These genes may serve as biomarkers and therapeutic targets.

DIABETIC RETINOPATHY, CLASSIFIED USING THE LESION-AWARE DEEP LEARNING SYSTEM, PREDICTS DIABETIC END-STAGE RENAL DISEASE IN CHINESE PATIENTS

Objective: To characterize the relationship between diabetic retinopathy (DR) and diabetic nephropathy (DN) in Chinese patients and to determine whether the severity of DR predicts end-stage renal disease (ESRD). Methods: Bilateral fundic photographs of 91 Chinese type 2 diabetic patients with biopsy-confirmed DN, not in ESRD stage, were obtained at the time of renal biopsy in this longitudinal study. The baseline severity of DR was determined using the Lesion-aware Deep Learning System (RetinalNET) in an open framework for deep learning and was graded using the Early Treatment Diabetic Retinopathy Study severity scale. Cox proportional hazard models were used to estimate the hazard ratio (HR) for the effect of the severity of diabetic retinopathy on ESRD. Results: During a median follow-up of 15 months, 25 patients progressed to ESRD. The severity of retinopathy at the time of biopsy was a prognostic factor for progression to ESRD (HR 2.18, 95% confidence interval 1.05 to 4.53, P = .04). At baseline, more severe retinopathy was associated with poor renal function, and more severe glomerular lesions. However, 30% of patients with mild retinopathy and severe glomerular lesions had higher low-density lipo-protein-cholesterol and more severe proteinuria than those with mild glomerular lesions. Additionally, 3% of patients with severe retinopathy and mild glomerular changes were more likely to have had diabetes a long time than those with severe glomerular lesions. Conclusion: Although the severity of DR predicted diabetic ESRD in patients with type 2 diabetes mellitus and DN, the severities of DR and DN were not always consistent, especially in patients with mild retinopathy or microalbuminuria. Abbreviations: CI = confidence interval; DM = diabetic mellitus; DN = diabetic nephropathy; DR = diabetic retinopathy; eGFR = estimated glomerular filtration rate; ESRD = end-stage renal disease; HbA1c = hemoglobin A1c; HR = hazard ratio; NPDR = nonproliferative diabetic retinopathy; PDR = proliferative diabetic retinopathy; SBP = systolic blood pressure; T2DM = type 2 diabetes mellitus; VEGF = vascular endothelial growth factor.

Clinical characteristics of diabetic nephropathy in patients with type 2 diabetic mellitus manifesting heavy proteinuria: A retrospective analysis of 220 cases

AIMS

To determine the predictability of diagnosing diabetic nephropathy (DN) versus non-diabetic renal disease (NDRD) from clinical and laboratory data in Chinese patients with type 2 diabetes mellitus (T2DM) manifesting heavy proteinuria.

METHODS

We retrospectively analyzed the clinical and laboratory data of patients with T2DM manifesting heavy proteinuria who underwent renal biopsy from January 2014 to December 2017.

RESULTS

According to renal biopsy, 220 patients were finally enrolled, including 109 cases diagnosed with DN alone (49.55%), 94 with NDRD alone (42.73%) and 17 with DN plus superimposed NDRD (7.73%). Multivariate analysis showed the significant risk factors for DN alone were age, duration of diabetes, presence of retinopathy, 24-h proteinuria, serum albumin and SBP. Presence of retinopathy achieved the highest overall diagnostic efficiency with the area under the curve of 0.852, sensitivity of 78.9% and specificity of 91.5%. The combined diagnosis with four indicators (duration of diabetes, retinopathy, SBP, and serum albumin) showed the area under the curve of 0.938, sensitivity of 88.1% and specificity of 87.2%.

CONCLUSIONS

The prevalence of DN is high in patients with T2DM manifesting heavy proteinuria. Renal biopsy should be performed in diabetics in the atypical clinical scenario.