Performance of Nuclear Magnetic Resonance-Based Estimated Glomerular Filtration Rate in a Real-World Setting

An accurate estimate of glomerular filtration rate (eGFR) is essential for proper clinical management, especially in patients with kidney dysfunction. This prospective observational study evaluated the real-world performance of the nuclear magnetic resonance (NMR)-based GFR_NMR equation, which combines creatinine, cystatin C, valine, and myo-inositol with age and sex. We compared GFR_NMR performance to that of the 2021 CKD-EPI creatinine and creatinine-cystatin C equations (CKD-EPI_2021Cr and CKD-EPI_2021CrCys), using 115 fresh routine samples of patients scheduled for urinary iothalamate clearance measurement (mGFR). Median bias to mGFR of the three eGFR equations was comparably low, ranging from 0.4 to 2.0 mL/min/1.73 m². GFR_NMR outperformed the 2021 CKD-EPI equations in terms of precision (interquartile range to mGFR of 10.5 vs. 17.9 mL/min/1.73 m² for GFR_NMR vs. CKD-EPI_2021CrCys; p = 0.01) and accuracy (P15, P20, and P30 of 66.1% vs. 48.7% [p = 0.007], 80.0% vs. 60.0% [p < 0.001] and 95.7% vs. 86.1% [p = 0.006], respectively, for GFR_NMR vs. CKD-EPI_2021CrCys). Clinical parameters such as etiology, comorbidities, or medications did not significantly alter the performance of the three eGFR equations. Altogether, this study confirmed the utility of GFR_NMR for accurate GFR estimation, and its potential value in routine clinical practice for improved medical care.

Impact of race-independent equations on estimating glomerular filtration rate for the assessment of kidney dysfunction in liver disease

BACKGROUND

Altered hemodynamics in liver disease often results in overestimation of glomerular filtration rate (GFR) by creatinine-based GFR estimating (eGFR) equations. Recently, we have validated a novel eGFR equation based on serum myo-inositol, valine, and creatinine quantified by nuclear magnetic resonance spectroscopy in combination with cystatin C, age and sex (GFR_NMR). We hypothesized that GFR_NMR could improve chronic kidney disease (CKD) classification in the setting of liver disease.

RESULTS

We conducted a retrospective multicenter study in 205 patients with chronic liver disease (CLD), comparing the performance of GFR_NMR to that of validated CKD-EPI eGFR equations, including eGFRcr (based on creatinine) and eGFRcr-cys (based on both creatinine and cystatin C), using measured GFR as reference standard. GFR_NMR outperformed all other equations with a low overall median bias (-1 vs. -6 to 4 ml/min/1.73 m² for the other equations; p < 0.05) and the lowest difference in bias between reduced and preserved liver function (-3 vs. -16 to -8 ml/min/1.73 m² for other equations). Concordant classification by CKD stage was highest for GFR_NMR (59% vs. 48% to 53%) and less biased in estimating CKD severity compared to the other equations. GFR_NMR P30 accuracy (83%) was higher than that of eGFRcr (75%; p = 0.019) and comparable to that of eGFRcr-cys (86%; p = 0.578).

CONCLUSIONS

Addition of myo-inositol and valine to creatinine and cystatin C in GFR_NMR further improved GFR estimation in CLD patients and accurately stratified liver disease patients into CKD stages.

Serum myo-inositol and valine improve metabolomic-based estimated glomerular filtration rate among kidney transplant recipients

BACKGROUND

Close monitoring of glomerular filtration rate (GFR) is essential for the management of patients post kidney transplantation. Measured GFR (mGFR), the gold standard, is not readily accessible in most centers. Furthermore, the performance of new estimated GFR (eGFR) equations based upon creatinine and/or cystatin C have not been validated in kidney transplant patients. Here we evaluate a recently published eGFR equation using cystatin C, creatinine, myo-inositol and valine as measured by nuclear magnetic resonance (eGFRNMR).

METHODS

Residual sera was obtained from a cohort of patients with clinically ordered iothalamate renal clearance mGFR (n = 602). Kidney transplant recipients accounted for 220 (37%) of participants.

RESULTS

Compared to mGFR, there was no significant bias for eGFRcr or eGFRNMR, while eGFRcr-cys significantly underestimated mGFR. P30 values were similar for all eGFR. P15 was significantly higher for eGFRNMR compared to eGFRcr, while the P15 for eGFRcr-cys only improved among patients without a kidney transplant. Agreement with mGFR CKD stages of <15, 30, 45, 60, and 90 ml/min/1.73 m2 was identical for eGFRcr and eGFRcr-cys (61.8%, both cases) while eGFRNMR was significantly higher (66.4%) among patients with a kidney transplant.

CONCLUSION

The 2021 CKD-EPI eGFRcr and eGFRcr-cys have similar bias, P15, and agreement while eGFRNMR more closely matched mGFR with the strongest improvement among kidney transplant recipients.

Analytical Validation of GFRNMR: A Blood-Based Multiple Biomarker Assay for Accurate Estimation of Glomerular Filtration Rate

Accurate and precise monitoring of kidney function is critical for a timely and reliable diagnosis of chronic kidney disease (CKD). The determination of kidney function usually involves the estimation of the glomerular filtration rate (eGFR). We recently reported the clinical performance of a new eGFR equation (GFR_NMR) based on the nuclear magnetic resonance (NMR) measurement of serum myo-inositol, valine, and creatinine, in addition to the immunoturbidometric quantification of serum cystatin C, age and sex. We now describe the analytical performance evaluation of GFR_NMR according to the Clinical and Laboratory Standards Institute guidelines. Within-laboratory coefficients of variation (CV%) of the GFR_NMR equation did not exceed 4.3%, with a maximum CV% for repeatability of 3.7%. Between-site reproducibility (three sites) demonstrated a maximum CV% of 5.9%. GFR_NMR stability was demonstrated for sera stored for up to 8 days at 2–10°C and for NMR samples stored for up to 10 days in the NMR device at 6 ± 2°C. Substance interference was limited to 4/40 (10.0%) of the investigated substances, resulting in an underestimated GFR_NMR (for glucose and metformin) or a loss of results (for naproxen and ribavirin) for concentrations twice as high as usual clinical doses. The analytical performances of GFR_NMR, combined with its previously reported clinical performance, support the potential integration of this NMR method into clinical practice.

A Prospective Multicenter Trial to Evaluate Urinary Metabolomics for Non-invasive Detection of Renal Allograft Rejection (PARASOL): Study Protocol and Patient Recruitment

Background: In an earlier monocentric study, we have developed a novel non-invasive test system for the prediction of renal allograft rejection, based on the detection of a specific urine metabolite constellation. To further validate our results in a large real-world patient cohort, we designed a multicentric observational prospective study (PARASOL) including six independent European transplant centers. This article describes the study protocol and characteristics of recruited better patients as subjects.

Methods: Within the PARASOL study, urine samples were taken from renal transplant recipients when kidney biopsies were performed. According to the Banff classification, urine samples were assigned to a case group (renal allograft rejection), a control group (normal renal histology), or an additional group (kidney damage other than rejection).

Results: Between June 2017 and March 2020, 972 transplant recipients were included in the trial (1,230 urine samples and matched biopsies, respectively). Overall, 237 samples (19.3%) were assigned to the case group, 541 (44.0%) to the control group, and 452 (36.7%) samples to the additional group. About 65.9% were obtained from male patients, the mean age of transplant recipients participating in the study was 53.7 ± 13.8 years. The most frequently used immunosuppressive drugs were tacrolimus (92.8%), mycophenolate mofetil (88.0%), and steroids (79.3%). Antihypertensives and antidiabetics were used in 88.0 and 27.4% of the patients, respectively. Approximately 20.9% of patients showed the presence of circulating donor-specific anti-HLA IgG antibodies at time of biopsy. Most of the samples (51.1%) were collected within the first 6 months after transplantation, 48.0% were protocol biopsies, followed by event-driven (43.6%), and follow-up biopsies (8.5%). Over time the proportion of biopsies classified into the categories Banff 4 (T-cell-mediated rejection [TCMR]) and Banff 1 (normal tissue) decreased whereas Banff 2 (antibody-mediated rejection [ABMR]) and Banff 5I (mild interstitial fibrosis and tubular atrophy) increased to 84.2 and 74.5%, respectively, after 4 years post transplantation. Patients with rejection showed worse kidney function than patients without rejection.

Conclusion: The clinical characteristics of subjects recruited indicate a patient cohort typical for routine renal transplantation all over Europe. A typical shift from T-cellular early rejections episodes to later antibody mediated allograft damage over time after renal transplantation further strengthens the usefulness of our cohort for the evaluation of novel biomarkers for allograft damage.

Estimating Glomerular Filtration Rate from Serum Myo-Inositol, Valine, Creatinine and Cystatin C

Assessment of renal function relies on the estimation of the glomerular filtration rate (eGFR). Existing eGFR equations, usually based on serum levels of creatinine and/or cystatin C, are not uniformly accurate across patient populations. In the present study, we expanded a recent proof-of-concept approach to optimize an eGFR equation targeting the adult population with and without chronic kidney disease (CKD), based on a nuclear magnetic resonance spectroscopy (NMR) derived 'metabolite constellation' (GFRNMR). A total of 1855 serum samples were partitioned into development, internal validation and external validation datasets. The new GFRNMR equation used serum myo-inositol, valine, creatinine and cystatin C plus age and sex. GFRNMR had a lower bias to tracer measured GFR (mGFR) than existing eGFR equations, with a median bias (95% confidence interval [CI]) of 0.0 (-1.0; 1.0) mL/min/1.73 m2 for GFRNMR vs. -6.0 (-7.0; -5.0) mL/min/1.73 m2 for the Chronic Kidney Disease Epidemiology Collaboration equation that combines creatinine and cystatin C (CKD-EPI2012) (p < 0.0001). Accuracy (95% CI) within 15% of mGFR (1-P15) was 38.8% (34.3; 42.5) for GFRNMR vs. 47.3% (43.2; 51.5) for CKD-EPI2012 (p < 0.010). Thus, GFRNMR holds promise as an alternative way to assess eGFR with superior accuracy in adult patients with and without CKD.

Objective biomarkers for clinical relapse in multiple sclerosis: a metabolomics approach

Accurate determination of relapses in multiple sclerosis is important for diagnosis, classification of clinical course and therapeutic decision making. The identification of biofluid markers for multiple sclerosis relapses would add to our current diagnostic armamentarium and increase our understanding of the biology underlying the clinical expression of inflammation in multiple sclerosis. However, there is presently no biofluid marker capable of objectively determining multiple sclerosis relapses although some, in particular neurofilament-light chain, have shown promise. In this study, we sought to determine if metabolic perturbations are present during multiple sclerosis relapses, and, if so, identify candidate metabolite biomarkers and evaluate their discriminatory abilities at both group and individual levels, in comparison with neurofilament-light chain. High-resolution global and targeted ¹H nuclear magnetic resonance metabolomics as well as neurofilament-light chain measurements were performed on the serum in four groups of relapsing-remitting multiple sclerosis patients, stratified by time since relapse onset: (i) in relapse (R); (ii) last relapse (LR) ≥ 1 month (M) to < 6 M ago; (iii) LR ≥ 6 M to < 24 M ago; and (iv) LR ≥ 24 M ago. Two hundred and one relapsing-remitting multiple sclerosis patients were recruited: R (n = 38), LR 1–6 M (n = 28), LR 6–24 M (n = 34), LR ≥ 24 M (n = 101). Using supervised multivariate analysis, we found that the global metabolomics profile of R patients was significantly perturbed compared to LR ≥ 24 M patients. Identified discriminatory metabolites were then quantified using targeted metabolomics. Lysine and asparagine (higher in R), as well as, isoleucine and leucine (lower in R), were shortlisted as potential metabolite biomarkers. ANOVA of these metabolites revealed significant differences across the four patient groups, with a clear trend with time since relapse onset. Multivariable receiver operating characteristics analysis of these four metabolites in discriminating R versus LR ≥ 24 M showed an area under the curve of 0.758, while the area under the curve for serum neurofilament-light chain was 0.575. Within individual patients with paired relapse–remission samples, all four metabolites were significantly different in relapse versus remission, with the direction of change consistent with that observed at group level, while neurofilament-light chain was not discriminatory. The perturbations in the identified metabolites point towards energy deficiency and immune activation in multiple sclerosis relapses, and the measurement of these metabolites, either singly or in combination, are useful as biomarkers to differentiate relapse from remission at both group and individual levels.

NMR-Based Lipid Metabolite Profiles to Predict Outcomes in Patients Undergoing Interventional Therapy for a Hepatocellular Carcinoma (HCC): A Substudy of the SORAMIC Trial

Simple Summary

A hepatocellular carcinoma (HCC) is the most common cause of death in patients suffering from chronic liver diseases. In order to improve the prediction of outcomes in HCC patients, there is a need for new biomarkers. This pilot study aimed at identifying serum metabolites for the prediction of outcomes of HCC patients using nuclear magnetic resonance (NMR) spectroscopy. This analysis revealed that high serum concentrations of myo-inositol or dimethylamine were associated with an improved overall survival. In contrast, high concentrations of total cholesterol, LDL-cholesterol and LDL particles (LDL-P) were associated with a decreased overall survival. The identification of novel biomarkers using this NMR-based technology holds promise for opening new directions in the conduction of interventional trials in HCCs.

Abstract

Background: This exploratory study aimed to evaluate lipidomic and metabolomic profiles in patients with early and advanced HCCs and to investigate whether certain metabolic parameters may predict the overall survival in these patients. Methods: A total of 60 patients from the prospective, randomized-controlled, multicenter phase II SORAMIC trial were included in this substudy; among them were 30 patients with an early HCC who underwent radiofrequency ablation combined with sorafenib or a placebo and 30 patients with an advanced HCC who were treated with a selective internal radiation therapy (SIRT) plus sorafenib vs. sorafenib alone. The blood serum of these patients was analyzed using a standardized nuclear magnetic resonance (NMR) platform. All tested metabolites were correlated with the overall survival. Results: The overall survival (OS) was significantly higher in patients with an early HCC (median OS: 34.0 months) compared with patients with an advanced HCC (median OS: 12.0 months) (p < 0.0001). Patients with high serum concentrations of myo-inositol (MI) had a higher overall survival compared with patients with low concentrations (21.6 vs. 13.8 months) with a Pearson correlation coefficient of 0.331 (p = 0.011). Patients with high serum concentrations of dimethylamine had a higher overall survival compared with patients with low concentrations (25.1 vs. 19.7 months) with a Pearson correlation coefficient of 0.279 (p = 0.034). High concentrations of total cholesterol, LDL-cholesterol and LDL particles (LDL-P) were associated with a decreased overall survival. Conclusions: NMR-based lipidomic and metabolomic profiling has the potential to identify individual metabolite biomarkers that predict the outcome of patients with an HCC exposed to non-invasive therapeutic management.

Serum Myo-Inositol, Dimethyl Sulfone, and Valine in Combination with Creatinine Allow Accurate Assessment of Renal Insufficiency-A Proof of Concept

Evaluation of renal dysfunction includes estimation of glomerular filtration rate (eGFR) as the initial step and subsequent laboratory testing. We hypothesized that combined analysis of serum creatinine, myo-inositol, dimethyl sulfone, and valine would allow both assessment of renal dysfunction and precise GFR estimation. Bio-banked sera were analyzed using nuclear magnetic resonance spectroscopy (NMR). The metabolites were combined into a metabolite constellation (GFRNMR) using n = 95 training samples and tested in n = 189 independent samples. Tracer-measured GFR (mGFR) served as a reference. GFRNMR was compared to eGFR based on serum creatinine (eGFRCrea and eGFREKFC), cystatin C (eGFRCys-C), and their combination (eGFRCrea-Cys-C) when available. The renal biomarkers provided insights into individual renal and metabolic dysfunction profiles in selected mGFR-matched patients with otherwise homogenous clinical etiology. GFRNMR correlated better with mGFR (Pearson correlation coefficient r = 0.84 vs. 0.79 and 0.80). Overall percentages of eGFR values within 30% of mGFR for GFRNMR matched or exceeded those for eGFRCrea and eGFREKFC (81% vs. 64% and 74%), eGFRCys-C (81% vs. 72%), and eGFRCrea-Cys-C (81% vs. 81%). GFRNMR was independent of patients' age and sex. The metabolite-based NMR approach combined metabolic characterization of renal dysfunction with precise GFR estimation in pediatric and adult patients in a single analytical step.

Metabolomics Biomarkers of Prostate Cancer: A Systematic Review

Prostate cancer (PCa) diagnosis with current biomarkers is difficult and often results in unnecessary invasive procedures as well as over-diagnosis and over-treatment, highlighting the need for novel biomarkers. The aim of this review is to provide a summary of available metabolomics PCa biomarkers, particularly for clinically significant disease. A systematic search was conducted on PubMed for publications from July 2008 to July 2018 in accordance with PRISMA guidelines to report biomarkers with respect to their application in PCa diagnosis, progression, aggressiveness, recurrence, and treatment response. The vast majority of studies report biomarkers with the ability to distinguish malignant from benign prostate tissue with a few studies investigating biomarkers associated with disease progression, treatment response or tumour recurrence. In general, these studies report high dimensional datasets and the number of analysed metabolites often significantly exceeded the number of available samples. Hence, observed multivariate differences between case and control samples in the datasets might potentially also be associated with pre-analytical, technical, statistical and confounding factors. Giving the technical and methodological hurdles, there are nevertheless a number of metabolites and pathways repeatedly reported across various technical approaches, cohorts and sample types that appear to play a predominant role in PCa tumour biology, progression and recurrence.

Identification of a urine metabolite constellation characteristic for kidney allograft rejection

INTRODUCTION

Allograft rejection is still an important complication after kidney transplantation. Currently, monitoring of these patients mostly relies on the measurement of serum creatinine and clinical evaluation. The gold standard for diagnosing allograft rejection, i.e. performing a renal biopsy is invasive and expensive. So far no adequate biomarkers are available for routine use.

OBJECTIVES

We aimed to develop a urine metabolite constellation that is characteristic for acute renal allograft rejection.

METHODS

NMR-Spectroscopy was applied to a training cohort of transplant recipients with and without acute rejection.

RESULTS

We obtained a metabolite constellation of four metabolites that shows promising performance to detect renal allograft rejection in the cohorts used (AUC of 0.72 and 0.74, respectively).

CONCLUSION

A metabolite constellation was defined with the potential for further development of an in-vitro diagnostic test that can support physicians in their clinical assessment of a kidney transplant patient.

Metabolomics reveals distinct, antibody-independent, molecular signatures of MS, AQP4-antibody and MOG-antibody disease

The overlapping clinical features of relapsing remitting multiple sclerosis (RRMS), aquaporin-4 (AQP4)-antibody (Ab) neuromyelitis optica spectrum disorder (NMOSD), and myelin oligodendrocyte glycoprotein (MOG)-Ab disease mean that detection of disease specific serum antibodies is the gold standard in diagnostics. However, antibody levels are not prognostic and may become undetectable after treatment or during remission. Therefore, there is still a need to discover antibody-independent biomarkers. We sought to discover whether plasma metabolic profiling could provide biomarkers of these three diseases and explore if the metabolic differences are independent of antibody titre. Plasma samples from 108 patients (34 RRMS, 54 AQP4-Ab NMOSD, and 20 MOG-Ab disease) were analysed by nuclear magnetic resonance spectroscopy followed by lipoprotein profiling. Orthogonal partial-least squares discriminatory analysis (OPLS-DA) was used to identify significant differences in the plasma metabolite concentrations and produce models (mathematical algorithms) capable of identifying these diseases. In all instances, the models were highly discriminatory, with a distinct metabolite pattern identified for each disease. In addition, OPLS-DA identified AQP4-Ab NMOSD patient samples with low/undetectable antibody levels with an accuracy of 92%. The AQP4-Ab NMOSD metabolic profile was characterised by decreased levels of scyllo-inositol and small high density lipoprotein particles along with an increase in large low density lipoprotein particles relative to both RRMS and MOG-Ab disease. RRMS plasma exhibited increased histidine and glucose, along with decreased lactate, alanine, and large high density lipoproteins while MOG-Ab disease plasma was defined by increases in formate and leucine coupled with decreased myo-inositol. Despite overlap in clinical measures in these three diseases, the distinct plasma metabolic patterns support their distinct serological profiles and confirm that these conditions are indeed different at a molecular level. The metabolites identified provide a molecular signature of each condition which is independent of antibody titre and EDSS, with potential use for disease monitoring and diagnosis.

Protease Expression Levels in Prostate Cancer Tissue Can Explain Prostate Cancer-Associated Seminal Biomarkers-An Explorative Concept Study

Previously, we described prostate cancer (PCa) detection (83% sensitivity; 67% specificity) in seminal plasma by CE-MS/MS. Moreover, advanced disease was distinguished from organ-confined tumors with 80% sensitivity and 82% specificity. The discovered biomarkers were naturally occurring fragments of larger seminal proteins, predominantly semenogelin 1 and 2, representing endpoints of the ejaculate liquefaction. Here we identified proteases putatively involved in PCa specific protein cleavage, and examined gene expression and tissue protein levels, jointly with cell localization in normal prostate (nP), benign prostate hyperplasia (BPH), seminal vesicles and PCa using qPCR, Western blotting and confocal laser scanning microscopy. We found differential gene expression of chymase (CMA1), matrix metalloproteinases (MMP3, MMP7), and upregulation of MMP14 and tissue inhibitors (TIMP1 and TIMP2) in BPH. In contrast tissue protein levels of MMP14 were downregulated in PCa. MMP3/TIMP1 and MMP7/TIMP1 ratios were decreased in BPH. In seminal vesicles, we found low-level expression of most proteases and, interestingly, we also detected TIMP1 and low levels of TIMP2. We conclude that MMP3 and MMP7 activity is different in PCa compared to BPH due to fine regulation by their inhibitor TIMP1. Our findings support the concept of seminal plasma biomarkers as non-invasive tool for PCa detection and risk stratification.

Beneficial Metabolic Effects of Duodenal Jejunal Bypass Liner for the Treatment of Adipose Patients with Type 2 Diabetes Mellitus: Analysis of Responders and Non-Responders

Implantation of a duodenal-jejunal endoluminal bypass liner (DJBL) has shown to induce weight loss and to improve metabolic parameters. DJBL is a reversible endoduodenal sleeve mimicking duodenal bypass while lacking risks and limitations of bariatric surgery.Effects on metabolic control, body mass parameters, appetite regulation, glucose tolerance, organ health, and lipid profile were determined in 16 morbidly overweight patients with type 2 diabetes mellitus. In addition, relevant hormones (leptin, ghrelin, gastric inhibitory peptide, glucagon-like peptide, and insulin) were measured by enzyme-linked immunosorbent assay (ELISA) and chemiluminescent microparticle immunoassay (CMIA) at 0, 1, 32, and 52 weeks post-implant following a mixed meal tolerance test. Lipoprotein subclasses were analysed by proton nuclear magnetic resonance (¹H NMR) spectrometry. DJBL provoked weight loss, a decrease in fat mass, and an improvement in insulin resistance and hepatic function in most but not all of the patients, but in the long term did not increase gut hormone fasting levels pointing to a combined effect of more than gut parameters alone. Lipidome analysis was done in 10 patients, allowing classification to responders and non-responders by reduction of sLDL-p subfraction; and to further analyse the atherogenic profile. Responders showed an overall more pronounced effect regarding improvement of HbA1c, BMI, and HOMA index.Implantation of a DJBL in obese type 2 diabetes patients does not per se lead to an improvement of the metabolic situation. Further analyses including larger cohorts have to be performed to identify responding patients, to better treat non-responders and to analyse the key effectors.

Beneficial Metabolic Effects of Duodenal Jejunal Bypass Liner for the Treatment of Adipose Patients with Type 2 Diabetes Mellitus: Analysis of Responders and Non-Responders

Implantation of a duodenal-jejunal endoluminal bypass liner (DJBL) has shown to induce weight loss and to improve metabolic parameters. DJBL is a reversible endoduodenal sleeve mimicking duodenal bypass while lacking risks and limitations of bariatric surgery.Effects on metabolic control, body mass parameters, appetite regulation, glucose tolerance, organ health, and lipid profile were determined in 16 morbidly overweight patients with type 2 diabetes mellitus. In addition, relevant hormones (leptin, ghrelin, gastric inhibitory peptide, glucagon-like peptide, and insulin) were measured by enzyme-linked immunosorbent assay (ELISA) and chemiluminescent microparticle immunoassay (CMIA) at 0, 1, 32, and 52 weeks post-implant following a mixed meal tolerance test. Lipoprotein subclasses were analysed by proton nuclear magnetic resonance (¹H NMR) spectrometry. DJBL provoked weight loss, a decrease in fat mass, and an improvement in insulin resistance and hepatic function in most but not all of the patients, but in the long term did not increase gut hormone fasting levels pointing to a combined effect of more than gut parameters alone. Lipidome analysis was done in 10 patients, allowing classification to responders and non-responders by reduction of sLDL-p subfraction; and to further analyse the atherogenic profile. Responders showed an overall more pronounced effect regarding improvement of HbA1c, BMI, and HOMA index.Implantation of a DJBL in obese type 2 diabetes patients does not per se lead to an improvement of the metabolic situation. Further analyses including larger cohorts have to be performed to identify responding patients, to better treat non-responders and to analyse the key effectors.

Urine proteome analysis as a discovery tool in patients with deep vein thrombosis and pulmonary embolism

PURPOSE

Early and accurate detection of deep vein thrombosis (DVT) is an important clinical need. Based on the hypothesis that urinary peptides may hold information on DVT in conjunction with pulmonary embolism (PE), the study was aimed at identifying such peptide biomarkers using capillary electrophoresis coupled mass spectrometry.

EXPERIMENTAL DESIGN

Patients with symptoms of unprovoked/idiopathic DVT and/or PE were examined by doppler-sonography or angio-computed tomography. Urinary proteome analysis allowed for identification of respective peptide biomarkers. To confirm their biological relevance, we induced PE in mice and assessed human ex vivo thrombi.

RESULTS

We identified 62 urinary peptides as DVT-specific biomarkers, i.e. fragments of collagen type I and a fragment of fibrinogen β-chain. The presence of fibrinogen α/β in the acute thrombus, and collagen type I and osteopontin in the older, organized thrombus was demonstrated. The classifier DVT62 established through support vector machine (SVM) modeling based on the 62 identified peptides was validated in an independent cohort of 47 subjects (six cases and 41 controls) with a sensitivity of 100% and specificity of 83%.

CONCLUSIONS AND CLINICAL RELEVANCE

Urine proteome analysis enabled the detection of DVT-specific peptides, which were validated in human and mouse tissue. Furthermore, it allowed for the establishment of an urinary-proteome based classifier that is relatively specific for DVT. The data provide the basis for assessment of these biomarkers in a prospective clinical study.

Seminal plasma as a source of prostate cancer peptide biomarker candidates for detection of indolent and advanced disease

BACKGROUND

Extensive prostate specific antigen screening for prostate cancer generates a high number of unnecessary biopsies and over-treatment due to insufficient differentiation between indolent and aggressive tumours. We hypothesized that seminal plasma is a robust source of novel prostate cancer (PCa) biomarkers with the potential to improve primary diagnosis of and to distinguish advanced from indolent disease.

METHODOLOGY/PRINCIPAL FINDINGS

In an open-label case/control study 125 patients (70 PCa, 21 benign prostate hyperplasia, 25 chronic prostatitis, 9 healthy controls) were enrolled in 3 centres. Biomarker panels a) for PCa diagnosis (comparison of PCa patients versus benign controls) and b) for advanced disease (comparison of patients with post surgery Gleason score <7 versus Gleason score >7) were sought. Independent cohorts were used for proteomic biomarker discovery and testing the performance of the identified biomarker profiles. Seminal plasma was profiled using capillary electrophoresis mass spectrometry. Pre-analytical stability and analytical precision of the proteome analysis were determined. Support vector machine learning was used for classification. Stepwise application of two biomarker signatures with 21 and 5 biomarkers provided 83% sensitivity and 67% specificity for PCa detection in a test set of samples. A panel of 11 biomarkers for advanced disease discriminated between patients with Gleason score 7 and organ-confined (<pT3a) or advanced (≥pT3a) disease with 80% sensitivity and 82% specificity in a preliminary validation setting. Seminal profiles showed excellent pre-analytical stability. Eight biomarkers were identified as fragments of N-acetyllactosaminide beta-1,3-N-acetylglucosaminyltransferase, prostatic acid phosphatase, stabilin-2, GTPase IMAP family member 6, semenogelin-1 and -2. Restricted sample size was the major limitation of the study.

CONCLUSIONS/SIGNIFICANCE

Seminal plasma represents a robust source of potential peptide makers for primary PCa diagnosis. Our findings warrant further prospective validation to confirm the diagnostic potential of identified seminal biomarker candidates.

Urine proteome analysis reflects atherosclerotic disease in an ApoE-/- mouse model and allows the discovery of new candidate biomarkers in mouse and human atherosclerosis

Noninvasive diagnosis of atherosclerosis via single biomarkers has been attempted but remains elusive. However, a previous polymarker or pattern approach of urine polypeptides in humans reflected coronary artery disease with high accuracy. The aim of the current study is to use urine proteomics in ApoE(-/-) mice to discover proteins with pathophysiological roles in atherogenesis and to identify urinary polypeptide patterns reflecting early stages of atherosclerosis. Urine of ApoE(-/-) mice either on high fat diet (HFD) or chow diet was collected over 12 weeks; urine of wild type mice on HFD was used to exclude diet-related proteome changes. Capillary electrophoresis coupled to mass spectrometry (CE-MS) of samples identified 16 polypeptides specific for ApoE(-/-) mice on HFD. In a blinded test set, these polypeptides allowed identification of atherosclerosis at a sensitivity of 90% and specificity of 100%, as well as monitoring of disease progression. Sequencing of the discovered polypeptides identified fragments of α(1)-antitrypsin, epidermal growth factor (EGF), kidney androgen-regulated protein, and collagen. Using immunohistochemistry, α(1)-antitrypsin, EGF, and collagen type I were shown to be highly expressed in atherosclerotic plaques of ApoE(-/-) mice on HFD. Urinary excretion levels of collagen and α(1)-antitrypsin fragments also significantly correlated with intraplaque collagen and α(1)-antitrypsin content, mirroring plaque protein expression in the urine proteome. To provide further confirmation that the newly identified proteins are relevant in humans, the presence of collagen type I, α(1)-antitrypsin, and EGF was also confirmed in human atherosclerotic disease. Urine proteome analysis in mice exemplifies the potential of a novel multimarker approach for the noninvasive detection of atherosclerosis and monitoring of disease progression. Furthermore, this approach represents a novel discovery tool for the identification of proteins relevant in murine and human atherosclerosis and thus also defines potential novel therapeutic targets.

Urinary proteome analysis to exclude severe vesicoureteral reflux

OBJECTIVES

High-grade vesicoureteral reflux (VUR, grade IV or V) is a risk factor for renal scarring, impaired renal function, and arterial hypertension. Voiding cystourethrography is the gold standard for detecting the severity of VUR. High-grade VUR is present in the minority of children with urinary tract infection (UTI), thus exposing the majority to invasive diagnostics that have no surgical consequence. We therefore aimed at establishing a noninvasive test to identify children with high-grade VUR.

METHODS

In a case-control study, a specific urinary proteome pattern was established by capillary electrophoresis coupled to mass spectrometry in 18 patients with primary VUR grade IV or V, distinguishing these from 19 patients without VUR after UTI. This proteome pattern was independently validated in a blinded cohort of 17 patients with VUR grade IV or V and 19 patients without VUR.

RESULTS

Sensitivity in detecting VUR grade IV or V in the blinded study was 88%, specificity was 79%. The test's accuracy was independent of age, gender, and grade of VUR in the contralateral kidney. The odds ratio of suffering from VUR grade IV or V when tested positive was 28 (95% confidence interval: 4.5 to 176.0).

CONCLUSIONS

This noninvasive test is ready for prospective validation in large cohorts with the aim of identifying those children with UTI and hydronephrosis in need of further invasive diagnostics, such as voiding cystourethrography, thus sparing most children without pathologic urinary proteome patterns from additional diagnostics.

Diagnosis of subclinical and clinical acute T-cell-mediated rejection in renal transplant patients by urinary proteome analysis

PURPOSE

Noninvasive diagnosis of acute renal allograft rejection may be advantageous compared with the allograft biopsy.

EXPERIMENTAL DESIGN

In this study, a multi-marker classification model for rejection was defined on a training set of 39 allograft patients by statistical comparison of capillary electrophoresis mass spectrometry (CE-MS) peptide spectra in urine samples from 16 cases with subclinical acute T-cell-mediated tubulointerstitial rejection and 23 nonrejection controls.

RESULTS

Application of the rejection model to a blinded validation set (n=64) resulted in an AUC value of 0.91 (95% CI: 0.82-0.97, p=0.0001). In total, 16 out of 18 subclinical and 10 out of 10 clinical rejections (BANFF grades Ia/Ib), and 28 out of 36 controls without rejection were correctly classified. Acute tubular injury in the biopsies or concomitant urinary tract infection did not interfere with CE-MS-based diagnosis. Sequence information of identified altered collagen α(I) and α (III) chain fragments in rejection samples suggested an involvement of matrix metalloproteinase-8 (MMP-8). Biopsy stainings revealed matrix metalloproteinase-8 exclusively in neutrophils located within peritubular capillaries and sparsely, in the tubulointerstitium during rejection.

CONCLUSIONS AND CLINICAL RELEVANCE

The established marker set contains peptides related to tubulointerstitial infiltration seen in acute rejection. The set of urinary peptide markers will be used for early diagnosis of acute kidney allograft rejection marker in a multicenter phase III prospective study.

Bile proteomic profiles differentiate cholangiocarcinoma from primary sclerosing cholangitis and choledocholithiasis

Early detection of malignant biliary tract diseases, especially cholangiocarcinoma (CC) in patients with primary sclerosing cholangitis (PSC), is very difficult and often comes too late to give the patient a therapeutic benefit. We hypothesize that bile proteomic analysis distinguishes CC from nonmalignant lesions. We used capillary electrophoresis mass spectrometry (CE-MS) to identify disease-specific peptide patterns in patients with choledocholithiasis (n = 16), PSC (n = 18), and CC (n = 16) in a training set. A model for differentiation of choledocholithiasis from PSC and CC (PSC/CC model) and another model distinguishing CC from PSC (CC model) were subsequently validated in independent cohorts (choledocholithiasis [n = 14], PSC [n = 18] and CC [n = 25]). Peptides were characterized by sequencing. Application of the PSC/CC model in the independent test cohort resulted in correct exclusion of 12/14 bile samples from patients with choledocholithiasis and identification of 40/43 patients with PSC or CC (86% specificity, 93% sensitivity). The corresponding receiver operating characteristic (ROC) analysis revealed an area under the curve (AUC) of 0.93 (95% confidence interval [CI]: 0.82-0.98, P = 0.0001). The CC model succeeded in an accurate detection of 14/18 bile samples from patients with PSC and 21/25 samples with CC (78% specificity, 84% sensitivity) in the independent cohort, resulting in an AUC value of 0.87 (95% CI: 0.73-0.95, P = 0.0001) in ROC analysis. Eight out of 10 samples of patients with CC complicating PSC were identified.

CONCLUSION

Bile proteomic analysis discriminates benign conditions from CC accurately. This method may become a diagnostic tool in future as it offers a new possibility to diagnose malignant bile duct disease and thus enables efficient therapy particularly in patients with PSC.

Urinary proteomics: ready for prime time in urological cancer diagnostics?

The impact of clinical proteomics on the diagnosis and treatment of urological malignancies is modest in comparison with the high expectations of the past. However, most available studies suffer from flawed clinical designs rather than from technical limitations. This article will briefly introduce the main technological approaches taken, their advantages and disadvantages and will highlight the different challenges associated with urinary proteome analysis. Furthermore, several examples of the successful application of urinary clinical proteomics in the field of prostate and bladder cancer will be introduced. These examples suggest careful validation of novel biomarkers, appropriate study designs using blinded cohorts enrolled from appropriate target populations and the standardization of techniques as key elements required for successful urinary proteomics studies. These prerequisites are essential for turning the old promise of a personalized medicine approach into a new reality to optimize patients’ preventive and therapeutic care.

Urinary collagen fragments are significantly altered in diabetes: a link to pathophysiology

Background

The pathogenesis of diabetes mellitus (DM) is variable, comprising different inflammatory and immune responses. Proteome analysis holds the promise of delivering insight into the pathophysiological changes associated with diabetes. Recently, we identified and validated urinary proteomics biomarkers for diabetes. Based on these initial findings, we aimed to further validate urinary proteomics biomarkers specific for diabetes in general, and particularity associated with either type 1 (T1D) or type 2 diabetes (T2D).

Methodology/Principal Findings

Therefore, the low-molecular-weight urinary proteome of 902 subjects from 10 different centers, 315 controls and 587 patients with T1D (n = 299) or T2D (n = 288), was analyzed using capillary-electrophoresis mass-spectrometry. The 261 urinary biomarkers (100 were sequenced) previously discovered in 205 subjects were validated in an additional 697 subjects to distinguish DM subjects (n = 382) from control subjects (n = 315) with 94% (95% CI: 92–95) accuracy in this study. To identify biomarkers that differentiate T1D from T2D, a subset of normoalbuminuric patients with T1D (n = 68) and T2D (n = 42) was employed, enabling identification of 131 biomarker candidates (40 were sequenced) differentially regulated between T1D and T2D. These biomarkers distinguished T1D from T2D in an independent validation set of normoalbuminuric patients (n = 108) with 88% (95% CI: 81–94%) accuracy, and in patients with impaired renal function (n = 369) with 85% (95% CI: 81–88%) accuracy. Specific collagen fragments were associated with diabetes and type of diabetes indicating changes in collagen turnover and extracellular matrix as one hallmark of the molecular pathophysiology of diabetes. Additional biomarkers including inflammatory processes and pro-thrombotic alterations were observed.

Conclusions/Significance

These findings, based on the largest proteomic study performed to date on subjects with DM, validate the previously described biomarkers for DM, and pinpoint differences in the urinary proteome of T1D and T2D, indicating significant differences in extracellular matrix remodeling.

Urinary proteome analysis identifies infants but not older children requiring pyeloplasty

One out of every five children suffering from ureteropelvic junction obstruction (UPJO) requires pyeloplasty. This prevalence indicates an urgent necessity to identify high-grade UPJO as early as possible to avoid renal damage. A novel non-invasive proteomic urine test has recently been introduced that is able to detect these patients at an early stage. In the study reported here, we tested this approach to assess its use in our centre and to expand its application to older children. Twenty-seven children (median age 0.4 years, range 0.1-8.8 years) with hydronephrosis who had been scheduled a nuclear diuretic renal scan (DR) to identify urodynamically relevant UPJO were included in our prospective study. Patients with prior surgery of the urinary tract were excluded. The urinary proteome pattern was analysed using capillary electrophoresis coupled to mass spectrometry. Of the 27 children, 11 had a relevant UPJO diagnosed by the DR. In 19 children <1 year of age, urinary proteome analysis predicted obstruction with a sensitivity of 83% (5/6) and a specificity of 92% (12/13). However, in older patients, the sensitivity decreased to 20% (1/5) and specificity to 66% (2/3). Based on our results, the proteome pattern established by Decramer and co-workers predicts the need for surgery in infants but not in older children with UPJO.

Naturally occurring human urinary peptides for use in diagnosis of chronic kidney disease

Because of its availability, ease of collection, and correlation with physiology and pathology, urine is an attractive source for clinical proteomics/peptidomics. However, the lack of comparable data sets from large cohorts has greatly hindered the development of clinical proteomics. Here, we report the establishment of a reproducible, high resolution method for peptidome analysis of naturally occurring human urinary peptides and proteins, ranging from 800 to 17,000 Da, using samples from 3,600 individuals analyzed by capillary electrophoresis coupled to MS. All processed data were deposited in an Structured Query Language (SQL) database. This database currently contains 5,010 relevant unique urinary peptides that serve as a pool of potential classifiers for diagnosis and monitoring of various diseases. As an example, by using this source of information, we were able to define urinary peptide biomarkers for chronic kidney diseases, allowing diagnosis of these diseases with high accuracy. Application of the chronic kidney disease-specific biomarker set to an independent test cohort in the subsequent replication phase resulted in 85.5% sensitivity and 100% specificity. These results indicate the potential usefulness of capillary electrophoresis coupled to MS for clinical applications in the analysis of naturally occurring urinary peptides.

[Outpatient surgery: an unstoppable evolution]

The trend is to definitely shorten hospital stays. It follows in the footsteps of a broader range of surgeries that can be managed in an ambulatory care setting. The expected benefits are: a reduction in costs, a shorter preoperative delay, a shorter absence for the work place and a lessened risk of hospital-borne infections. A multidisciplinary approach is essential for the success of such a program. Surgeons, anaesthetists and nursing staff must be prepared to modify and adapt their skills. The criterion of success for such an endeavour is a low level of readmissions and hospitalisations. If day surgery tends to keep the patient away for the hospital settings, it certainly places him in the centre of his medical management.

Prediction of muscle-invasive bladder cancer using urinary proteomics

PURPOSE

Minimally invasive methods of predicting the risk of muscle-invasive urothelial bladder carcinoma may expedite appropriate therapy and reduce morbidity and cost.

EXPERIMENTAL DESIGN

Here, capillary electrophoresis coupled mass spectrometry was used to identify urinary polypeptide bladder cancer biomarkers in 127 patients. These markers were used to construct a panel discriminating muscle-invasive from noninvasive disease, which was refined in 297 additional samples from healthy volunteers, patients with malignant and nonmalignant genitourinary conditions. Sequencing of panel polypeptides was then done. Finally, the ability of the panel to predict muscle-invasive disease was evaluated prospectively in 130 bladder carcinoma patients. Four sequenced polypeptides formed a panel predictive of muscle-invasive disease.

RESULTS

Prospective evaluation of this panel revealed a sensitivity of 81% [95% confidence interval (CI), 69-90] and specificity of 57% (95% CI, 45-69) for muscle-invasive disease. Multivariate analysis revealed the panel (P < 0.0001) and tumor grade (P = 0.0001), but not urine cytology, predict muscle invasion. A model including grade and panel polypeptide levels improved sensitivity [92% (95% CI, 82-97)] and specificity [68% (95% CI, 55-79)] for muscle-invasive disease. A model score of >0.88 provided a negative predictive value of 77% and positive predictive value of 90% for muscle invasion.

CONCLUSIONS

Use of urinary peptides seems promising in estimating the probability a patient harbors muscle-invasive urothelial bladder cancer. These peptides may also shed novel insights into the biology of bladder tumor progression not obtainable by other methods. Clinical trials seem warranted to evaluate the effect of this approach on practice.

The 2nd Annual Oncology Biomarkers Conference

This conference was organized by GTCbio, and the central theme was the lifecycle of a cancer biomarker from discovery, over preclinical and clinical validation, to clinical application phase. The meeting allowed the approximately 100 attendants to gain the knowledge and technologies necessary to use powerful biomarker tools for oncology research activities, provided updates on recent biomarker discoveries by classical or omics strategies and demonstrated a perspective of the downstream processes of biomarker development after the discovery phase. The conference gathered together some of today’s leading laboratory researchers, pharmacy and biotech decision-makers, technology companies and clinicians to focus on the uses of biomarkers in the field of oncology research. They spoke on how biomarkers can be used to fast track the development of novel cancer drugs and how prognostic markers can lead towards early detection and treatment in personalized medicine approaches.

Evaluation of urine proteome pattern analysis for its potential to reflect coronary artery atherosclerosis in symptomatic patients

Coronary artery disease (CAD) is a major cause of mortality and morbidity. Noninvasive proteome analysis could guide clinical evaluation and early/preventive treatment. Under routine clinical conditions, urine of 67 patients presenting with symptoms suspicious for CAD were analyzed by capillary electrophoresis directly coupled with mass spectrometry (CE-MS). All patients were subjected to coronary angiography and either assigned to a CAD or non-CAD group. A training set of 29 patients was used to establish CAD and non-CAD-associated proteome patterns of plasma as well as urine. Significant discriminatory power was achieved in urine but not in plasma. Therefore, urine proteomic analysis of further 38 patients was performed in a blinded study. A combination of 17 urinary polypeptides allowed separation of both groups in the test set with a sensitivity of 81%, a specificity of 92%, and an accuracy of 84%. Sequencing of urinary marker peptides identified fragments of collagen alpha1 (I and III), which we furthermore demonstrated to be expressed in atherosclerotic plaques of human aorta. In conclusion, specific CE-MS polypeptide patterns in urine were associated with significant CAD in patients with angina-typical symptoms. These promising findings need to be further evaluated in regard to reliability of a urine-based screening method with the potential of improving the diagnostic approaches for CAD.

Urinary proteome pattern in children with renal Fanconi syndrome

BACKGROUND

The renal Fanconi syndrome (FS) is characterized by renal glucosuria, loss of electrolytes, bicarbonate and lactate, generalized hyperaminoaciduria and low-molecular-weight proteinuria. We studied the urinary low-molecular-weight proteome to identify excreted peptides indicative of a pathogenetic mechanism leading to tubular dysfunction.

METHODS

We established a urinary proteome pattern using capillary electrophoresis mass spectrometry (CE-MS) of 7 paediatric patients with cystinosis and 6 patients with ifosfamide-induced FS as the study group, and 54 healthy volunteers and 45 patients suffering from other renal diseases such as lupus nephritis (n = 8), focal segmental glomerulosclerosis (n = 27), minimal change disease (n = 7) and membranous glomerulonephritis (n = 3) as controls. Consequently, we conducted a blinded study consisting of 11 FS patients and 9 patients with renal disease other than FS. Additionally, we applied this pattern to 294 previously measured samples of patients with different renal diseases. Amino acid sequences of some marker proteins were obtained.

RESULTS

Specificity for detecting FS was 89% and sensitivity was 82%. The marker peptides constituting the proteome pattern are fragments derived from osteopontin, uromodulin and collagen alpha-1.

CONCLUSIONS

CE-MS can be used to diagnose FS in paediatric patients and might be a future tool for the non-invasive diagnosis of FS. The reduced amount of the marker proteins osteopontin and uromodulin indicates loss of function of tubular excretion in all patients suffering from FS regardless of the underlying cause. In addition, the six different fragments of the collagen alpha-1 (I) chain were either elevated or reduced in the urine. This indicates a change of proteases in collagen degradation as observed in interstitial fibrosis. These changes were prominent irrespectively of the stages of FS. This indicates fibrosis as an early starting pathogenetic reason for the development of renal insufficiency in FS patients.

Proteomics in gerontology: current applications and future aspects--a mini-review

BACKGROUND

Aging is closely related to the onset of chronic diseases, such as coronary artery disease, diabetic nephropathy or different types of malignancies, reflecting the demand for novel biomarkers to manage theses diseases.

OBJECTIVE

The analysis of the human proteome for biomarkers has made considerable advances in the last years.

METHODS

We describe the main technological approaches taken, their advantages and disadvantages.

RESULTS

We will review the different clinical sources of material and attempt to highlight the different challenges and approaches associated with these. Age-related changes in the proteome have been described and were found to be highly similar to changes associated with chronic diseases. We will give several examples on the successful application of proteomics in the diagnosis, prognosis and therapy of these chronic diseases.

CONCLUSIONS

A boost in disease-related proteomic information is expected in the very near future, and will also result in its broad clinical application. However, this view appears to be dependent on the strict adherence to proper technological/analytical parameters, correct statistics, and large databases that allow comparison of datasets provided by different scientists. Clearly, the proteome is by far too complex to be tackled by one laboratory on its own.

Evaluation of urinary biomarkers for coronary artery disease, diabetes, and diabetic kidney disease

BACKGROUND

In this study we sought to validate urinary biomarkers for diabetes and two common complications, coronary artery disease (CAD) and diabetic nephropathy (DN).

METHODS

A CAD score calculated by summing the product of a classification coefficient and signal amplitude of 15 urinary polypeptides was previously developed. Five sequences of biomarkers in the panel were identified as fragments of collagen alpha-1(I) and alpha-1(III). Prospectively collected urine samples available for analysis from 19 out of 20 individuals with CAD (15 with type 1 diabetes [T1D] and four without diabetes) and age-, sex-, and diabetes-matched controls enrolled in the Coronary Artery Calcification in Type 1 Diabetes study were analyzed for the CAD score using capillary electrophoresis and electrospray ionization mass spectrometry. Two panels of biomarkers that were previously defined to distinguish diabetes status were analyzed to determine their relationship to T1D. Three biomarker panels developed to distinguish DN (DNS) and two biomarker panels developed to distinguish renal disease (RDS) were examined to determine their relationship with renal function.

RESULTS

The CAD score was associated with CAD (odds ratio with 95% confidence interval, 2.2 [1.3-5.2]; P = 0.0016) and remained significant when adjusted individually for age, albumin excretion rate (AER), blood pressure, waist circumference, intraabdominal fat, glycosylated hemoglobin, and lipids. DNS and RDS were significantly correlated with AER, cystatin C, and serum creatinine. The biomarker panels for diabetes were both significantly associated with T1D status (P < 0.05 for both).

CONCLUSIONS

We validated a urinary proteome pattern associated with CAD and urinary proteome patterns associated with T1D and DN.

Comparison of the Glidescope, the McGrath, the Airtraq and the Macintosh laryngoscopes in simulated difficult airways*

SUMMARY

Several indirect laryngoscopes have recently been developed, but relatively few have been formally compared. In this study we evaluated the efficacy and the usability of the Macintosh, the Glidescope, the McGrath and the Airtraq laryngoscopes. Sixty anaesthesia providers (20 staff, 20 residents, and 20 nurses) were enrolled into this study. The volunteers intubated the trachea of a Laerdal SimMan manikin in three simulated difficult airway scenarios. In all scenarios, indirect laryngoscopes provided better laryngeal exposure than the Macintosh blade and appeared to produce less dental trauma. In the most difficult scenario (tongue oedema), the Macintosh blade was associated with a high rate of failure and prolonged intubation times whereas indirect laryngoscopes improved intubation time and rarely failed. Indirect laryngoscopes were judged easier to use than the Macintosh. Differences existed between indirect devices. The Airtraq consistently provided the most rapid intubation. Laryngeal grade views were superior with the Airtraq and McGrath than with the Glidescope.

CE-MS analysis of the human urinary proteome for biomarker discovery and disease diagnostics

Owing to its availability, ease of collection, and correlation with pathophysiology of diseases, urine is an attractive source for clinical proteomics. However, many proteomic studies have had only limited clinical impact, due to factors such as modest numbers of subjects, absence of disease controls, small numbers of defined biomarkers, and diversity of analytical platforms. Therefore, it is difficult to merge biomarkers from different studies into a broadly applicable human urinary proteome database. Ideally, the methodology for defining the biomarkers should combine a reasonable analysis time with high resolution, thereby enabling the profiling of adequate samples and recognition of sufficient features to yield robust diagnostic panels. Capillary electrophoresis coupled to mass spectrometry (CE-MS), which was used to analyze urine samples from healthy subjects and patients with various diseases, is a suitable approach for this task. The database of these datasets compiled from the urinary peptides enabled the diagnosis, classification, and monitoring of a wide range of diseases. CE-MS exhibits excellent performance for biomarker discovery and allows subsequent biomarker sequencing independent of the separation platform. This approach may elucidate the pathogenesis of many diseases, and better define especially renal and urological disorders at the molecular level.

Laparoscopic colon surgery: unreliability of end-tidal CO2 monitoring

BACKGROUND

The relatively good haemodynamic and respiratory tolerance to abdominal CO(2) insufflation has mostly been observed in healthy patients during short-lasting laparoscopic procedures. End-tidal CO(2) pressure (PetCO(2)) has been shown to be a reliable method to assess arterial CO(2) (PaCO(2)) in the absence of cardio-respiratory disease in this setting. However, no study has investigated whether PetCO(2) is accurately related to PaCO(2) during laparoscopic colon surgery. Indeed, these procedures last longer, prolonging the pneumoperitoneum and requiring a Trendelenburg position. The aim of the present study was to measure the PaCO(2)-PetCO(2) difference over time in patients undergoing laparoscopic colon surgery and to determine whether PaCO(2) is reliably assessed by PetCO(2).

METHODS

Forty consecutive patients (ASA I and II) scheduled for laparoscopic colon surgery were anaesthetized and ventilated to obtain a PetCO(2) between 4.0 and 5.5 kPa. After initiation of CO(2) insufflation, PaCO(2) and PetCO(2) were recorded every 30 min during surgery.

RESULTS

No complication was observed during anaesthesia. The mean arterial pressure increased significantly after CO(2) insufflation and remained steady up to the end of pneumoperitoneum. The heart rate remained stable over time. The relation between PaCO(2) and PetCO(2) was not constant among patients and increased over time within the same patients. The R(2) values fluctuated and did not show a constant correlation between PaCO(2) and PetCO(2).

CONCLUSION

The correlation between PaCO(2) and PetCO(2) during laparoscopic colon surgery is inconsistent mainly due to inter- and intra-individual variability.