scholarly journals Urine proteomics identifies biomarkers for diabetic kidney disease at different stages

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Guanjie Fan ◽  
Tongqing Gong ◽  
Yuping Lin ◽  
Jianping Wang ◽  
Lu Sun ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Kidney Disease ◽  
Regression Models ◽  
Diabetic Kidney Disease ◽  
Kidney Biopsy ◽  
Invasive Procedure ◽  
Urinary Proteins ◽  
Diabetic Kidney ◽  
Logistic Regression Models

Abstract Background Type 2 diabetic kidney disease is the most common cause of chronic kidney diseases (CKD) and end-stage renal diseases (ESRD). Although kidney biopsy is considered as the ‘gold standard’ for diabetic kidney disease (DKD) diagnosis, it is an invasive procedure, and the diagnosis can be influenced by sampling bias and personal judgement. It is desirable to establish a non-invasive procedure that can complement kidney biopsy in diagnosis and tracking the DKD progress. Methods In this cross-sectional study, we collected 252 urine samples, including 134 uncomplicated diabetes, 65 DKD, 40 CKD without diabetes and 13 follow-up diabetic samples, and analyzed the urine proteomes with liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS). We built logistic regression models to distinguish uncomplicated diabetes, DKD and other CKDs. Results We quantified 559 ± 202 gene products (GPs) (Mean ± SD) on a single sample and 2946 GPs in total. Based on logistic regression models, DKD patients could be differentiated from the uncomplicated diabetic patients with 2 urinary proteins (AUC = 0.928), and the stage 3 (DKD3) and stage 4 (DKD4) DKD patients with 3 urinary proteins (AUC = 0.949). These results were validated in an independent dataset. Finally, a 4-protein classifier identified putative pre-DKD3 patients, who showed DKD3 proteomic features but were not diagnosed by clinical standards. Follow-up studies on 11 patients indicated that 2 putative pre-DKD patients have progressed to DKD3. Conclusions Our study demonstrated the potential for urinary proteomics as a noninvasive method for DKD diagnosis and identifying high-risk patients for progression monitoring.

scholarly journals Genetics of diabetic kidney disease: A follow‐up study in the Arab population of the United Arab Emirates

2019 ◽  
Vol 7 (12) ◽  
Author(s):  
Wael M. Osman ◽  
Herbert F. Jelinek ◽  
Guan K. Tay ◽  
Mohamed H. Hassan ◽  
Wael Almahmeed ◽  
...  
Keyword(s):  
Kidney Disease ◽  
United Arab Emirates ◽  
Diabetic Kidney Disease ◽  
Arab Population ◽  
Diabetic Kidney ◽  
Follow Up Study

scholarly journals HEROIC: a 5-year observational cohort study aimed at identifying novel factors that drive diabetic kidney disease: rationale and study protocol

BMJ Open ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. e033923
Author(s):  
Kieran Mccafferty ◽  
Ben Caplin ◽  
Sinead Knight ◽  
Paul Hockings ◽  
David Wheeler ◽  
...  
Keyword(s):  
Kidney Disease ◽  
Observational Study ◽  
Diabetic Kidney Disease ◽  
Laboratory Data ◽  
Premature Mortality ◽  
Primary Objective ◽  
Imaging Data ◽  
Diabetic Kidney ◽  
Number Of Patients

IntroductionDiabetic kidney disease (DKD) is the leading cause of end-stage kidney disease worldwide and a major cause of premature mortality in diabetes mellitus (DM). While improvements in care have reduced the incidence of kidney disease among those with DM, the increasing prevalence of DM means that the number of patients worldwide with DKD is increasing. Improved understanding of the biology of DKD and identification of novel therapeutic targets may lead to new treatments. A major challenge to progress has been the heterogeneity of the DKD phenotype and renal progression. To investigate the heterogeneity of DKD we have set up The East and North London Diabetes Cohort (HEROIC) Study, a secondary care-based, multiethnic observational study of patients with biopsy-proven DKD. Our primary objective is to identify histological features of DKD associated with kidney endpoints in a cohort of patients diagnosed with type 1 and type 2 DM, proteinuria and kidney impairment.Methods and analysisHEROIC is a longitudinal observational study that aims to recruit 500 patients with DKD at high-risk of renal and cardiovascular events. Demographic, clinical and laboratory data will be collected and assessed annually for 5 years. Renal biopsy tissue will be collected and archived at recruitment. Blood and urine samples will be collected at baseline and during annual follow-up visits. Measured glomerular filtration rate (GFR), echocardiography, retinal optical coherence tomography angiography and kidney and cardiac MRI will be performed at baseline and twice more during follow-up. The study is 90% powered to detect an association between key histological and imaging parameters and a composite of death, renal replacement therapy or a 30% decline in estimated GFR.Ethics and disseminationEthical approval has been obtained from the Bloomsbury Research Ethics Committee (REC 18-LO-1921). Any patient identifiable data will be stored on a password-protected National Health Services N3 network with full audit trail. Anonymised imaging data will be stored in a ISO27001-certificated data warehouse.Results will be reported through peer-reviewed manuscripts and conferences and disseminated to participants, patients and the public using web-based and social media engagement tools as well as through public events.

scholarly journals Does Flipping the Tubercle for Improved Cartilage Repair Exposure Increase the Risk for Arthrofibrosis?

Cartilage ◽  
2020 ◽  
pp. 194760352096820
Author(s):  
Gergo Merkely ◽  
Jakob Ackermann ◽  
Emily Sheehy ◽  
Andreas H. Gomoll
Keyword(s):  
Logistic Regression ◽  
Cartilage Repair ◽  
Regression Models ◽  
Case Control Study ◽  
Level Of Evidence ◽  
Logistic Regression Models ◽  
Increased Risk ◽  
Repair Procedure ◽  
Control Study

Objective We sought to determine whether rates of postoperative arthrofibrosis following tibial tuberosity osteotomy (TTO) with complete mobilization of the fragment (TTO-HD) are comparable to TTOs where the hinge remained intact (TTO-HI). Design Patients who underwent TTO with concomitant cartilage repair procedure between January 2007 and May 2017, with at least 2 years of follow-up were included in this study. Postoperative reinterventions following TTO-HD and TTO-HI were assessed and multivariant logistic regression models were used to identify whether postoperative reinterventions can be attributed to either technique when controlled for defect size or defect number. Results A total of 127 patients (TTO-HD, n = 80; TTO-HI, n = 47) were included in this study. Significantly more patients in the TTO-HD group (31.2%) developed postoperative arthrofibrosis compared with TTO-HI (6.4%; P < 0.05). Multivariant logistic regression revealed that TTO-HD is an independent risk factor for predicting postoperative arthrofibrosis (OR 6.5, CI = 1.7-24.2, P < 0.05). Conclusion Patients who underwent TTO with distal hinge detachment and a proximally flipped tubercle for better exposure during concomitant cartilage repair were at a significantly higher risk of postoperative arthrofibrosis than patients with similar size and number of defects treated without mobilization of the tubercle. While certain procedures can benefit from larger exposure, surgeons should be aware of the increased risk of postoperative arthrofibrosis. Level of Evidence Level III, case-control study.

scholarly journals Cohort profile: the Singapore diabetic cohort study

BMJ Open ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. e036443 ◽  
Author(s):  
Miyang Luo ◽  
Linda Wei Lin Tan ◽  
Xueling Sim ◽  
Milly Khiam Hoon Ng ◽  
Rob Van Dam ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Kidney Disease ◽  
Diabetic Kidney Disease ◽  
Sample Collection ◽  
Data Set ◽  
Diabetic Kidney ◽  
New Biomarkers ◽  
Rich Data

PurposeThe diabetic cohort (DC) was set up to study the determinants of complications in individuals with type 2 diabetes and examine the role of genetic, physiological and lifestyle factors in the development of complications in these individuals.ParticipantsA total of 14 033 adult participants with type 2 diabetes were recruited from multiple public sector polyclinics and hospital outpatient clinics in Singapore between November 2004 and November 2010. The first round of follow-up was conducted for 4131 participants between 2012 and 2016; the second round of follow-up started in 2016 and is expected to end in 2021. A questionnaire survey, physical assessments, blood and urine sample collection were conducted at recruitment and each follow-up visit. The data set also includes genetic data and linkage to medical and administrative records for recruited participants.Findings to dateData from the cohort have been used to identify determinants of diabetes and related complications. The longitudinal data of medical records have been used to analyse diabetes control over time and its related outcomes. The cohort has also contributed to the identification of genetic loci associated with type 2 diabetes and diabetic kidney disease in collaboration with other large cohort studies. About 25 scientific papers based on the DC data have been published up to May 2019.Future plansThe rich data in DC can be used for various types of research to study disease-related complications in patients with type 2 diabetes. We plan to further investigate disease progression and new biomarkers for common diabetic complications, including diabetic kidney disease and diabetic neuropathy.

scholarly journals Identification of urinary proteins potentially associated with diabetic kidney disease

2016 ◽  
Vol 26 (6) ◽  
pp. 434 ◽  
Author(s):  
GR Chandak ◽  
RK Marikanty ◽  
MK Gupta ◽  
SVB Cherukuvada ◽  
SSS Kompella ◽  
...  
Keyword(s):  
Kidney Disease ◽  
Diabetic Kidney Disease ◽  
Urinary Proteins ◽  
Diabetic Kidney

scholarly journals Superimposed Nephrotic Syndrome in Diabetic Patients: 15 Cases of Mismatched Clinicopathological Correlation

2020 ◽  
Vol 5 (07) ◽  
pp. 252-256
Author(s):  
Kamel El-Reshaid ◽  
Shaikha Al-Bader
Keyword(s):  
Nephrotic Syndrome ◽  
Kidney Disease ◽  
Diabetic Kidney Disease ◽  
Kidney Biopsy ◽  
Case Series ◽  
Diabetic Patients ◽  
Clinicopathological Correlation ◽  
Diabetic Kidney ◽  
Patients With Diabetes ◽  
Rule Out

The spectrum of renal disease in patients with diabetes encompasses both diabetic kidney disease (including albuminuric and non-albuminuric phenotypes) and non-diabetic kidney disease (NDKD). Acute nephrotic syndrome (NS) with short duration of diabetes indicates NDKD. Moreover, such presentation is atypical in patients with IgA nephropathy and pre-eclampsia and hence warrants kidney biopsy to rule out treatable glomerulopathy. In this case series; we present our experience with 15 patients with atypical NS and outline their management.

scholarly journals Prevalence of and risk factors for chronic kidney disease and diabetic kidney disease in a central Chinese urban population: a cross-sectional survey

2019 ◽  
Author(s):  
Jiayu Duan ◽  
Duan Guang-Cai ◽  
Wang Chong-Jian ◽  
Liu Dong-Wei ◽  
Qiao Ying-Jin ◽  
...  
Keyword(s):  
Risk Factors ◽  
Chronic Kidney Disease ◽  
Logistic Regression ◽  
Renal Function ◽  
Kidney Disease ◽  
Diabetic Kidney Disease ◽  
Density Lipoprotein ◽  
Ordinal Logistic Regression ◽  
Central China ◽  
Diabetic Kidney

Abstract Background This study was conducted to evaluate and update the current prevalence of and risk factors for chronic kidney disease (CKD) and diabetic kidney disease (DKD) in a China. Methods A total of 5231 participants were randomly recruited for this study. CKD and DKD were defined according to the combination of estimated glomerular filtration rate (eGFR), presence of albuminuria and diabetes. Participants completed a questionnaire assessing lifestyle and relevant medical history, and blood and urinary specimens were taken. Serum creatinine, uric acid, total cholesterol, triglycerides, low-density lipoprotein, high-density lipoprotein and urinary albumin were assessed. The age- and gender-adjusted prevalences of CKD and DKD were calculated, and risk factors associated with the presence of reduced eGFR, albuminuria, DKD, severity of albuminuria and progression of reduce renal function were analyzed by binary and ordinal logistic regression. Results The overall adjusted prevalence of CKD was 16.8% (15.8 – 17.8%) and that of DKD was 3.5% (3.0 – 4.0%). Decreased renal function was detected in 132 participants [2.9%, 95% confidence interval (CI): 2.5 – 3.2%], whereas albuminuria was found in 858 participants (14.9%, 95% CI: 13.9 – 15.9%). In all participants with diabetes, the prevalence of reduced eGFR was 6.3% (95% CI = 3.9 – 8.6%) and that of albuminuria was 45.3% (95% CI = 40.4 – 50.1%). The overall prevalence of CKD in participants with diabetes was 48.0% (95% CI = 43.1 – 52.9%). The results of the binary and ordinal logistic regression indicated that factors independently associated with higher risk of reduced eGFR and albuminuria were older age, gender, smoking, alcohol consumption, overweight, obesity, diabetes, hypertension, dyslipidemia and hyperuricemia. Conclusions Our study shows the current prevalences of CKD and DKD in residents of Central China. The high prevalence suggests an urgent need to implement interventions to relieve the high burden of CKD and DKD in China.

scholarly journals Effect of diabetic kidney disease on therapeutic strategies for coronary artery disease: ten year follow-up

Aging ◽  
2021 ◽  
Author(s):  
Daniel Valente Batista ◽  
Whady Hueb ◽  
Eduardo Gomes Lima ◽  
Paulo Cury Rezende ◽  
Cibele Larrosa Garzillo ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Kidney Disease ◽  
Diabetic Kidney Disease ◽  
Therapeutic Strategies ◽  
Diabetic Kidney ◽  
Artery Disease

Clinical Prediction Score for Diagnosing Non-Diabetic Renal Disease in Patients with Type 2 Diabetes Mellitus

2021 ◽  
Vol 104 (7) ◽  
pp. 1109-1116
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Kidney Disease ◽  
Diabetic Kidney Disease ◽  
Kidney Biopsy ◽  
Prediction Score ◽  
Clinical Prediction ◽  
Diabetic Kidney

Background: When non-diabetic kidney disease (NDKD) is suspected, biopsy proven is used for definite diagnosis. However, there are not always easily available and may lead to cause complications. A clinical prediction score may help selecting appropriate patients for kidney biopsy. Objective: To develop a clinical prediction score for distinguishing any type of NDKD (NDKD alone or coexisting NDKD and diabetic nephropathy [DN]) and DN alone. Materials and Methods: A retrospective cohort study was conducted in type 2 diabetes mellitus (T2DM) patients with atypical features of DN, who had kidney biopsy at Thammasat University Hospital between 2011 and 2019. The present study divided patients into NDKD alone, coexisting NDKD and DN, and DN alone, confirmed by pathological diagnoses. The authors developed a clinical prediction score by weighing coefficients of predictors in a multivariable logistic model. Internal validation was performed with bootstrapping. Results: The present study included 81 patients of which 28 (34%) had NDKD alone, 15 (18%) had coexisting NDKD and DN, and 38 (41%) had DN alone. Primary membranous nephropathy, primary focal segmental glomerulosclerosis (FSGS), and secondary FSGS were prevalent in any NDKD. Absence of diabetic retinopathy (DR) showed a significant association with any NDKD (adjusted OR 3.72; 95% CI 1.28 to 10.8; p=0.02). The prediction score, AUROC of 0.75 (95% CI 0.63 to 0.86), had four predictors, duration of DM of less than 10 years, eGFR of more than 30 mL/minute/1.73 m², HbA1c of less than 8%, and absence of DR. Higher scores were associated with higher probability of NDKD. Conclusion: The present study clinical prediction score appears to be a useful tool to determine NDKD probability. T2DM patients with atypical presentation of DN with lower scores (0 to 2) may defer kidney biopsy. Keywords: Non-diabetic kidney disease; clinical prediction score; kidney biopsy; type 2 diabetes mellitus

Sign in / Sign up

Export Citation Format

Share Document