Search

Background: Obesity is increasingly prevalent in many countries. Obesity is a major risk factor for the development of type 2 diabetes but its relationship with diabetic kidney disease (DKD) remains unclear. Some studies have suggested that the metabolic syndrome (including obesity) may be associated with DKD in type 1 diabetes.Aim: To investigate the association between obesity and DKD.Design: Retrospective cross-sectional study.Methods: National Diabetes Audit data were available for the 2007–08 cycle. Type 1 and 2 diabetes patients with both a valid serum creatinine and urinary albumin:creatinine ratio were included. DKD was defined as an estimated glomerular filtration rate (eGFR) <60 ml/min/1.73 m2, albuminuria or both. Logistic regression was used to analyse associations of obesity (body mass index &geq;30 kg/m2) and other variables including year of birth, year of diagnosis, ethnicity and stage of kidney disease.Results: A total of 58 791 type 1 and 733 769 type 2 diabetes patients were included in the analysis. After adjustment, when compared with type 1 diabetes patients with normal renal function those with DKD were up to twice as likely to be obese. Type 2 DKD patients were also more likely to be obese. For example, type 2 diabetes patients with an eGFR <15 ml/min/1.73 m2 and normoalbuminuria, microalbuminuria or macroalbuminuria were all more likely to be obese; odds ratios (95% CI) 1.65 (1.3–2.1), 1.56 (1.28–1.92) and 1.27 (1.05–1.54), respectively.Conclusions: This study has highlighted a strong association between obesity and kidney disease in type 1 diabetes and confirmed their association in type 2 diabetes. [ABSTRACT FROM PUBLISHER]

Abstract Chronic kidney disease (CKD) is an aging-related disorder that represents a major global public health burden. Current biochemical biomarkers, such as serum creatinine and urinary albumin, have important limitations when used to identify the earliest indication of CKD or in tracking the progression to more advanced CKD. These issues underline the importance of finding and testing new molecular biomarkers that are capable of successfully meeting this clinical need. The measurement of changes in nature and/or levels of proteins and metabolites in biological samples from patients provide insights into pathophysiological processes. Proteomic and metabolomic techniques provide opportunities to record dynamic chemical signatures in patients over time. This review article presents an overview of the recent developments in the fields of metabolomics and proteomics in relation to CKD. Among the many different proteomic biomarkers proposed, there is particular interest in the CKD273 classifier, a urinary proteome biomarker reported to predict CKD progression and with implementation potential. Other individual non-invasive peptidomic biomarkers that are potentially relevant for CKD detection include type 1 collagen, uromodulin and mucin-1. Despite the limited sample sizes and variability of the metabolomics studies, some metabolites such as trimethylamine N-oxide, kynurenine and citrulline stand out as potential biomarkers in CKD. Graphical abstract Unlabelled Image Highlights • Electrophoretic or chromatographic techniques coupled to spectrometry can be used to identify proteins in different samples. • The CKD273 classifier, the most promising proteomic biomarker in CKD, is the one with the most advanced validation process. • Changes in the nature and levels of metabolites provide a dynamic signature of the processes taking place in the organism. • The urea cycle or amino acid metabolism are key pathways in the human metabolome. [ABSTRACT FROM AUTHOR]