Multicentric validation of proteomic biomarkers in urine specific for diabetic nephropathy

Background: Urine proteome analysis is rapidly emerging as a tool for diagnosis and prognosis in disease states. For diagnosis of diabetic nephropathy (DN), urinary proteome analysis was successfully applied in a pilot study. The validity of the previously established proteomic biomarkers with respect to the diagnostic and prognostic potential was assessed on a separate set of patients recruited at three different European centers. In this case-control study of 148 Caucasian patients with diabetes mellitus type 2 and duration >= 5 years, cases of DN were defined as albuminuria >300 mg/d and diabetic retinopathy (n = 66). Controls were matched for gender and diabetes duration (n = 82). Methodology/Principal Findings: Proteome analysis was performed blinded using high-resolution capillary electrophoresis coupled with mass spectrometry (CE-MS). Data were evaluated employing the previously developed model for DN. Upon unblinding, the model for DN showed 93.8% sensitivity and 91.4% specificity, with an AUC of 0.948 (95% CI 0.898-0.978). Of 65 previously identified peptides, 60 were significantly different between cases and controls of this study. In <10% of cases and controls classification by proteome analysis not entirely resulted in the expected clinical outcome. Analysis of patient's subsequent clinical course revealed later progression to DN in some of the false positive classified DN control patients. Conclusions: These data provide the first independent confirmation that profiling of the urinary proteome by CE-MS can adequately identify subjects with DN, supporting the generalizability of this approach. The data further establish urinary collagen fragments as biomarkers for diabetes-induced renal damage that may serve as earlier and more specific biomarkers than the currently used urinary albumin

Urinary Proteomics to Support Diagnosis of Stroke

Accurate diagnosis in suspected ischaemic stroke can be difficult. We explored the urinary proteome in patients with stroke (n = 69), compared to controls (n = 33), and developed a biomarker model for the diagnosis of stroke. We performed capillary electrophoresis online coupled to micro-time-of-flight mass spectrometry. Potentially disease-specific peptides were identified and a classifier based on these was generated using support vector machine-based software. Candidate biomarkers were sequenced by liquid chromatography-tandem mass spectrometry. We developed two biomarker-based classifiers, employing 14 biomarkers (nominal p-value <0.004) or 35 biomarkers (nominal p-value <0.01). When tested on a blinded test set of 47 independent samples, the classification factor was significantly different between groups; for the 35 biomarker model, median value of the classifier was 0.49 (−0.30 to 1.25) in cases compared to −1.04 (IQR −1.86 to −0.09) in controls, p<0.001. The 35 biomarker classifier gave sensitivity of 56%, specificity was 93% and the AUC on ROC analysis was 0.86. This study supports the potential for urinary proteomic biomarker models to assist with the diagnosis of acute stroke in those with mild symptoms. We now plan to refine further and explore the clinical utility of such a test in large prospective clinical trials

RANKL Is a Downstream Mediator for Insulin-Induced Osteoblastic Differentiation of Vascular Smooth Muscle Cells

Several reports have shown that circulating insulin level is positively correlated with arterial calcification; however, the relationship between insulin and arterial calcification remains controversial and the mechanism involved is still unclear. We used calcifying vascular smooth muscle cells (CVSMCs), a specific subpopulation of vascular smooth muscle cells that could spontaneously express osteoblastic phenotype genes and form calcification nodules, to investigate the effect of insulin on osteoblastic differentiation of CVSMCs and the cell signals involved. Our experiments demonstrated that insulin could promote alkaline phosphatase (ALP) activity, osteocalcin expression and the formation of mineralized nodules in CVSMCs. Suppression of receptor activator of nuclear factor κB ligand (RANKL) with small interfering RNA (siRNA) abolished the insulin-induced ALP activity. Insulin induced the activation of extracellular signal-regulated kinase (ERK)1/2, mitogen-activated protein kinase (MAPK) and RAC-alpha serine/threonine-protein kinase (Akt). Furthermore, pretreatment of human osteoblasts with the ERK1/2 inhibitor PD98059, but not the phosphoinositide 3-kinase (PI3K) inhibitor, LY294002, or the Akt inhibitor, 1L-6-hydroxymethyl-chiro-inositol 2-(R)-2-O-methyl-3-O-octadecylcarbonate (HIMO), abolished the insulin-induced RANKL secretion and blocked the promoting effect of insulin on ALP activities of CVSMCs. Recombinant RANKL protein recovered the ALP activities decreased by RANKL siRNA in insulin-stimulated CVSMCs. These data demonstrated that insulin could promote osteoblastic differentiation of CVSMCs by increased RANKL expression through ERK1/2 activation, but not PI3K/Akt activation

Coronary artery calcium screening: current status and recommendations from the European Society of Cardiac Radiology and North American Society for Cardiovascular Imaging

Current guidelines and literature on screening for coronary artery calcium for cardiac risk assessment are reviewed for both general and special populations. It is shown that for both general and special populations a zero score excludes most clinically relevant coronary artery disease. The importance of standardization of coronary artery calcium measurements by multi-detector CT is discussed