Standardization of diagnostic biomarker concentrations in urine; the hematuria caveat

Sensitive and specific urinary biomarkers can improve patient outcomes in many diseases through informing early diagnosis. Unfortunately, to date, the accuracy and translation of diagnostic urinary biomarkers into clinical practice has been disappointing. We believe this may be due to inappropriate standardization of diagnostic urinary biomarkers. Our objective was therefore to characterize the effects of standardizing urinary levels of IL-6, IL-8, and VEGF using the commonly applied standards namely urinary creatinine, osmolarity and protein. First, we report results based on the biomarker levels measured in 120 hematuric patients, 80 with pathologically confirmed bladder cancer, 27 with confounding pathologies and 13 in whom no underlying cause for their hematuria was identified, designated “no diagnosis”. Protein levels were related to final diagnostic categories (p = 0.022, ANOVA). Osmolarity (mean = 529 mOsm; median = 528 mOsm) was normally distributed, while creatinine (mean = 10163 µmol/l, median = 9350 µmol/l) and protein (0.3297, 0.1155 mg/ml) distributions were not. When we compared AUROCs for IL-6, IL-8 and VEGF levels, we found that protein standardized levels consistently resulted in the lowest AUROCs. The latter suggests that protein standardization attenuates the “true” differences in biomarker levels across controls and bladder cancer samples. Second, in 72 hematuric patients; 48 bladder cancer and 24 controls, in whom urine samples had been collected on recruitment and at follow-up (median = 11 (1 to 20 months)), we demonstrate that protein levels were approximately 24% lower at follow-up (Bland Altman plots). There was an association between differences in individual biomarkers and differences in protein levels over time, particularly in control patients.

The BTA stat test:A tumor marker for the detection of upper tract transitional cell carcinoma

Objectives. To conduct a prospective evaluation to determine the utility of the BTA stat test in the detection of upper tract transitional cell carcinoma (UTTCC). Monitoring for UTTCC currently relies on invasive procedures such as upper tract imaging, ureteral washing cytology (UWC) and/or ureteroscopy, or voided urine cytology (VUC). The BTA stat test is a sensitive qualitative immunoassay that detects human complement factor H-related protein in voided urine.

Methods. A total of 81 patients participated, 27 with histopathologically confirmed UTTCC, 26 with upper tract calculi, and 28 with microscopic hematuria but no evidence of urologic disease. Voided specimens collected before surgery or treatment were tested with the BTA stat test and VUC. UWC was performed in specimens collected by a ureteral catheter.

Results. The BTA stat test was significantly more sensitive and specific than VUC or UWC. The overall sensitivity for each was 82%, 11%, and 48%; the specificity was 89%, 54%, and 33%. The positive predictive value for the BTA stat test was 79% and the negative predictive value was 91%, both the highest of the three tests.

Conclusions. The BTA stat test was superior to VUC and UWC in the detection of UTTCC. These results may support the adoption of a less aggressive follow-up policy when monitoring for UTTCC when the BTA stat result is negative. If cystoscopy is negative and the BTA stat test is positive, upper tract investigations should be expedited and, if the bladder is in place, bladder biopsies performed. (C) 2001, Elsevier Science Inc.

Evaluation of biomarkers for the prediction of pre-eclampsia in women with type 1 diabetes mellitus: A systematic review.

BACKGROUND: Pre-eclampsia is a leading cause of maternal and perinatal morbidity and mortality. Women with type 1 diabetes are considered a high-risk group for developing pre-eclampsia. Much research has focused on biomarkers as a means of screening for pre-eclampsia in the general maternal population; however, there is a lack of evidence for women with type 1 diabetes.
OBJECTIVES: To undertake a systematic review to identify potential biomarkers for the prediction of pre-eclampsia in women with type 1 diabetes.
SEARCH STRATEGY: We searched Medline, EMBASE, Maternity and Infant Care, Scopus, Web of Science and CINAHL SELECTION CRITERIA: Studies were included if they measured biomarkers in blood or urine of women who developed pre-eclampsia and had pre-gestational type 1 diabetes mellitus Data collection and analysis A narrative synthesis was adopted as a meta-analysis could not be performed, due to high study heterogeneity.
MAIN RESULTS: A total of 72 records were screened, with 21 eligible studies being included in the review. A wide range of biomarkers was investigated and study size varied from 34 to 1258 participants. No single biomarker appeared to be effective in predicting pre-eclampsia; however, glycaemic control was associated with an increased risk while a combination of angiogenic and anti-angiogenic factors seemed to be potentially useful.
CONCLUSIONS: Limited evidence suggests that combinations of biomarkers may be more effective in predicting pre-eclampsia than single biomarkers. Further research is needed to verify the predictive potential of biomarkers that have been measured in the general maternal population, as many studies exclude women with diabetes preceding pregnancy.

Clinical implications of recent findings in schistosome proteomics

Schistosomiasis is a neglected tropical disease of clinical significance that, despite years of research, still requires an effective vaccine and improved diagnostics for surveillance, control and potential elimination. Furthermore, the causes of host pathology during schistosomiasis are still not completely understood. The recent sequencing of the genomes of the three key schistosome species has enabled the discovery of many new possible vaccine and drug targets, as well as diagnostic biomarkers, using high-throughput and sensitive proteomics methods. This review focuses on the literature of the last 5 years that has reported on the use of proteomics to both better understand the biology of the schistosome parasites and the disease they cause in definitive mammalian hosts.

Associates of an elevated natriuretic peptide level in stable heart failure patients:implications for targeted management

BACKGROUND: Persistently elevated natriuretic peptide (NP) levels in heart failure (HF) patients are associated with impaired prognosis. Recent work suggests that NP-guided therapy can improve outcome, but the mechanisms behind an elevated BNP remain unclear. Among the potential stimuli for NP in clinically stable patients are persistent occult fluid overload, wall stress, inflammation, fibrosis, and ischemia. The purpose of this study was to identify associates of B-type natriuretic peptide (BNP) in a stable HF population.

METHODS: In a prospective observational study of 179 stable HF patients, the association between BNP and markers of collagen metabolism, inflammation, and Doppler-echocardiographic parameters including left ventricular ejection fraction (LVEF), left atrial volume index (LAVI), and E/e prime (E/e') was measured.

RESULTS: Univariable associates of elevated BNP were age, LVEF, LAVI, E/e', creatinine, and markers of collagen turnover. In a multiple linear regression model, age, creatinine, and LVEF remained significant associates of BNP. E/e' and markers of collagen turnover had a persistent impact on BNP independent of these covariates.

CONCLUSION: Multiple variables are associated with persistently elevated BNP levels in stable HF patients. Clarification of the relative importance of NP stimuli may help refine NP-guided therapy, potentially improving outcome for this at-risk population.

Proteomics Identification of Azaspiracid Toxin Biomarkers in Blue Mussels, Mytilus edulis

Azaspiracids are a class of recently discovered algae-derived shellfish toxins. Their distribution globally is on the increase with mussels being most widely implicated in azaspiracid-related food poisoning events. Evidence that these toxins were bound to proteins in contaminated mussels has been shown recently. In the present study characterization of these proteins in blue mussels, Mytilus edulis, was achieved using a range of advanced proteomics tools. Four proteins present only in the hepatopancreas of toxin-contaminated mussels sharing identity or homology with cathepsin D, superoxide dismutase, glutathione S-transferase Pi, and a bacterial flagellar protein have been characterized. Several of the proteins are known to be involved in self-defense mechanisms against xenobiotics or up-regulated in the presence of carcinogenic agents. These findings would suggest that azaspiracids should now be considered and evaluated as potential tumorigenic compounds. The presence of a bacterial protein only in contaminated mussels was an unexpected finding and requires further investigation. The proteins identified in this study should assist with development of urgently required processes for the rapid depuration of azaspiracid-contaminated shellfish. Moreover they may serve as early warning indicators of shellfish exposed to this family of toxins. Molecular & Cellular Proteomics 8: 1811-1822, 2009.

The impact of biomarkers in multivariate algorithms for bladder cancer diagnosis in patients with hematuria

BACKGROUND: We appraised 23 biomarkers previously associated with urothelial cancer in a case-control study. Our aim was to determine whether single biomarkers and/or multivariate algorithms significantly improved on the predictive power of an algorithm based on demographics for prediction of urothelial cancer in patients presenting with hematuria. METHODS: Twenty-two biomarkers in urine and carcinoembryonic antigen (CEA) in serum were evaluated using enzyme-linked immunosorbent assays (ELISAs) and biochip array technology in 2 patient cohorts: 80 patients with urothelial cancer, and 77 controls with confounding pathologies. We used Forward Wald binary logistic regression analyses to create algorithms based on demographic variables designated prior predicted probability (PPP) and multivariate algorithms, which included PPP as a single variable. Areas under the curve (AUC) were determined after receiver-operator characteristic (ROC) analysis for single biomarkers and algorithms. RESULTS: After univariate analysis, 9 biomarkers were differentially expressed (t test; P

Collectives of diagnostic biomarkers identify high-risk subpopulations of hematuria patients: exploiting heterogeneity in large-scale biomarker data

Background: Ineffective risk stratification can delay diagnosis of serious disease in patients with hematuria. We applied a systems biology approach to analyze clinical, demographic and biomarker measurements (n = 29) collected from 157 hematuric patients: 80 urothelial cancer (UC) and 77 controls with confounding pathologies.

Methods: On the basis of biomarkers, we conducted agglomerative hierarchical clustering to identify patient and biomarker clusters. We then explored the relationship between the patient clusters and clinical characteristics using Chi-square analyses. We determined classification errors and areas under the receiver operating curve of Random Forest Classifiers (RFC) for patient subpopulations using the biomarker clusters to reduce the dimensionality of the data.

Results: Agglomerative clustering identified five patient clusters and seven biomarker clusters. Final diagnoses categories were non-randomly distributed across the five patient clusters. In addition, two of the patient clusters were enriched with patients with ‘low cancer-risk’ characteristics. The biomarkers which contributed to the diagnostic classifiers for these two patient clusters were similar. In contrast, three of the patient clusters were significantly enriched with patients harboring ‘high cancer-risk” characteristics including proteinuria, aggressive pathological stage and grade, and malignant cytology. Patients in these three clusters included controls, that is, patients with other serious disease and patients with cancers other than UC. Biomarkers which contributed to the diagnostic classifiers for the largest ‘high cancer- risk’ cluster were different than those contributing to the classifiers for the ‘low cancer-risk’ clusters. Biomarkers which contributed to subpopulations that were split according to smoking status, gender and medication were different.

Conclusions: The systems biology approach applied in this study allowed the hematuric patients to cluster naturally on the basis of the heterogeneity within their biomarker data, into five distinct risk subpopulations. Our findings highlight an approach with the promise to unlock the potential of biomarkers. This will be especially valuable in the field of diagnostic bladder cancer where biomarkers are urgently required. Clinicians could interpret risk classification scores in the context of clinical parameters at the time of triage. This could reduce cystoscopies and enable priority diagnosis of aggressive diseases, leading to improved patient outcomes at reduced costs. © 2013 Emmert-Streib et al; licensee BioMed Central Ltd.

Protein expression profiling during chick retinal maturation: a proteomics-based approach

Background: The underlying pathways that drive retinal neurogenesis and synaptogenesis are still relatively poorly understood. Protein expression analysis can provide direct insight into these complex developmental processes. The aim of this study was therefore to employ proteomic analysis to study the developing chick retina throughout embryonic (E) development commencing at day 12 through 13, 17, 19 and post-hatch (P) 1 and 33 days.

Results: 2D proteomic and mass spectrometric analysis detected an average of 1514 spots per gel with 15 spots demonstrating either modulation or constitutive expression identified via MS. Proteins identified included alpha and beta-tubulin, alpha enolase, B-creatine kinase, gamma-actin, platelet-activating factor (PAF), PREDICTED: similar to TGF-beta interacting protein 1, capping protein (actin filament muscle Z line), nucleophosmin 1 (NPM1), dimethylarginine dimethylaminohydrolase, triosphoaphate isomerase, DJ1, stathmin, fatty acid binding protein 7 (FABP7/B-FABP), beta-synuclein and enhancer of rudimentary homologue.

Conclusion: This study builds upon previous proteomic investigations of retinal development and represents the addition of a unique data set to those previously reported. Based on reported bioactivity some of the identified proteins are most likely to be important to normal retinal development in the chick. Continued analysis of the dynamic protein populations present at the early stages and throughout retinal development will increase our understanding of the molecular events underpinning retinogenesis.

A pilot survey for Fusarium mycotoxin biomarkers in women from Golestan, northern Iran

Fusarium mycotoxins are frequent contaminants of cereals in many world regions, and are suggested risk factors for various acute and chronic human diseases. To date a lack of exposure tools has restricted epidemiological studies of the potential health effects. Recently established exposure biomarkers for deoxynivalenol (DON) and fumonisins are now available and here a pilot biomarker survey of 110 women (aged 39 to 72 years) from Golestan, northern Iran was conducted on samples collected at one time point during August-September 2007. Urinary DON and DON-glucuronide combined were detected frequently (79/110, 72%), mean 1.3 ng DON/ml urine, range not detected (nd)-6.5 ng/ml; mean creatinine adjusted levels were 1.5 ng DON/mg creatinine, range nd-7.1 ng/mg). Neither urinary de-epoxy DON (DOM-1) and DOM-1 glucuronide combined, nor urinary fumonisin B-1 were detected. This study is the first reported biomarker based exposure assessment of DON and fumonisins in this region. Overall DON exposure at this time point appears modest compared to other world regions where data are available.

Determining mycotoxins and mycotoxigenic fungi in food and feed:Developing biomarkers of human exposure to mycotoxins

Exposure assessment is a critical part of epidemiological studies into the effect of mycotoxins on human health. Whilst exposure assessment can be made by estimating the quantity of ingested toxins from food analysis and questionnaire data, the use of biological markers (biomarkers) of exposure can provide a more accurate measure of individual level of exposure in reflecting the internal dose. Biomarkers of exposure can include the excreted toxin or its metabolites, as well as the products of interaction between the toxin and macromolecules such as protein and DNA. Samples in which biomarkers may be analysed include urine, blood, other body fluids and tissues, with urine and blood being the most accessible for human studies. Here we describe the development of biomarkers of exposure for the assessment of three important mycotoxins; aflatoxin, fumonisin and deoxynivalenol. A number of different biomarkers and methods have been developed that can be applied to human population studies, and these approaches are reviewed in the context of their application to molecular epidemiology research.

Biomarkers in diabetes:hemoglobin A1c, vascular and tissue markers

Biomarkers are conventionally defined as "biological molecules that represent health and disease states." They typically are measured in readily available body fluids (blood or urine), lie outside the causal pathway, are able to detect subclinical disease, and are used to monitor clinical and subclinical disease burden and response to treatments. Biomarkers can be "direct" endpoints of the disease itself, or "indirect" or surrogate endpoints. New technologies (such as metabolomics, proteomics, genomics) bring a wealth of opportunity to develop new biomarkers. Other new technologies enable the development of nonmolecular, functional, or biophysical tissue-based biomarkers. Diabetes mellitus is a complex disease affecting almost every tissue and organ system, with metabolic ramifications extending far beyond impaired glucose metabolism. Biomarkers may reflect the presence and severity of hyperglycemia (ie, diabetes itself) or the presence and severity of the vascular complications of diabetes. Illustrative examples are considered in this brief review. In blood, hemoglobin A1c (HbA1c) may be considered as a biomarker for the presence and severity of hyperglycemia, implying diabetes or prediabetes, or, over time, as a "biomarker for a risk factor," ie, hyperglycemia as a risk factor for diabetic retinopathy, nephropathy, and other vascular complications of diabetes. In tissues, glycation and oxidative stress resulting from hyperglycemia and dyslipidemia lead to widespread modification of biomolecules by advanced glycation end products (AGEs). Some of these altered species may serve as biomarkers, whereas others may lie in the causal pathway for vascular damage. New noninvasive technologies can detect tissue damage mediated by AGE formation: these include indirect measures such as pulse wave analysis (a marker of vascular dysfunction) and more direct markers such as skin autofluorescence (a marker of long-term accumulation of AGEs). In the future, we can be optimistic that new blood and tissue-based biomarkers will enable the detection, prevention, and treatment of diabetes and its complications long before overt disease develops.

3-Deoxyfructose concentrations are increased in human plasma and urine in diabetes

3-Deoxyglucosone (3-DG) is a reactive dicarbonyl sugar thought to be a key intermediate in the nonenzymatic polymerization and browning of proteins by glucose. 3-DG may be formed in vivo from fructose, fructose 3-phosphate, or Amadori adducts to protein, such as N epsilon-fructoselysine (FL), all of which are known to be elevated in body fluids or tissues in diabetes. Modification of proteins by 3-DG formed in vivo is thought to be limited by enzymatic reduction of 3-DG to less reactive species, such as 3-deoxyfructose (3-DF). In this study, we have measured 3-DF, as a metabolic fingerprint of 3-DG, in plasma and urine from a group of diabetic patients and control subjects. Plasma and urinary 3-DF concentrations were significantly increased in the diabetic compared with the control population (0.853 +/- 0.189 vs. 0.494 +/- 0.072 microM, P <0.001, and 69.9 +/- 44.2 vs. 38.7 +/- 16.1 nmol/mg creatinine, P <0.001, respectively). Plasma and urinary 3-DF concentrations correlated strongly with one another, with HbA1c (P <0.005 in all cases), and with urinary FL (P <0.02 and P = 0.005, respectively). The overall increase in 3-DF concentrations in plasma and urine in diabetes and their correlation with other indexes of glycemic control suggest that increased amounts of 3-DG are formed in the body during hyperglycemia in diabetes and then metabolized to 3-DF. These observations are consistent with a role for increased formation of the dicarbonyl sugar 3-DG in the accelerated browning of tissue proteins in diabetes.