Disease profiling by MALDI MS analysis of biofluids

There is an urgent need for accurate biomarkers of disease. The low-molecular weight proteome of blood serum or other biological fluids may be an ideal source of such biomarkers, although its analysis requires high-throughput strategies to enrich and quantify peptides and small proteins with biomarker potential. Herein, serum samples from cancer cases and controls are compared using a workflow of robotic reversed-phase extraction and clean-up, followed by automated MALDI MS spectral acquisition and analysis of the low-molecular weight peptidome. The aim of the presented methodology is to facilitate the discovery of candidate serum biomarkers of cancer using MALDI MS profiling, although the method is applicable to any comparative proteomic analysis of any biofluid

Identification of potential serum peptide biomarkers of biliary tract cancer using MALDI MS profiling.

The aim of this discovery study was the identification of peptide serum biomarkers for detecting biliary tract cancer (BTC) using samples from healthy volunteers and benign cases of biliary disease as control groups. This work was based on the hypothesis that cancer-specific exopeptidase activities in serum can generate cancer-predictive peptide fragments from circulating proteins during coagulation

Evidence of altered fatty acid metabolism in dogs with naturally occurring valvular heart disease and congestive heart failure

Introduction Myxomatous mitral valve disease (MMVD) is the most common cardiac condition in adult dogs. The disease progresses over several years and affected dogs may develop congestive heart failure (HF). Research has shown that myocardial metabolism is altered in cardiac disease, leading to a reduction in β-oxidation of fatty acids and an increased dependence upon glycolysis. Objectives This study aimed to evaluate whether a shift in substrate use occurs in canine patients with MMVD; a naturally occurring model of human disease. Methods Client-owned dogs were longitudinally evaluated at a research clinic in London, UK and paired serum samples were selected from visits when patients were in ACVIM stage B1: asymptomatic disease without cardiomegaly, and stage C: HF. Samples were processed using ultra-performance liquid chromatography mass spectrometry and lipid profiles were compared using mixed effects models with false discovery rate adjustment. The effect of disease stage was evaluated with patient breed entered as a confounder. Features that significantly differed were screened for selection for annotation efforts using reference databases. Results Dogs in HF had altered concentrations of lipid species belonging to several classes previously associated with cardiovascular disease. Concentrations of certain acylcarnitines, phospholipids and sphingomyelins were increased after individuals had developed HF, whilst some ceramides and lysophosphatidylcholines decreased. Conclusions The canine metabolome appears to change as MMVD progresses. Findings from this study suggest that in HF myocardial metabolism may be characterised by reduced β-oxidation. This proposed explanation warrants further research

Identification of novel bile acids as biomarkers for the early diagnosis of Niemann-Pick C disease

This article describes a rapid UPLC-MS/MS method to quantitate novel bile acids in biological fluids and the evaluation of their diagnostic potential in Niemann-Pick C (NPC). Two new compounds, NPCBA1 (3β-hydroxy,7β-N-acetylglucosaminyl-5-cholenoic acid) and NPCBA2 (probably 3β,5α,6β-trihydroxycholanoyl-glycine), were observed to accumulate preferentially in NPC patients: median plasma concentrations of NPCBA1 and NPCBA2 were 40- and 10-fold higher in patients than in controls. However, NPCBA1 concentrations were normal in some patients because they carried a common mutation inactivating the GlcNAc transferase required for the synthesis of this bile acid. NPCBA2, not containing a GlcNAc moiety, is thus a better NPC biomarker

Early Detection of Ovarian Cancer in Samples Pre-Diagnosis Using CA125 and MALDI-MS Peaks

Aim: A nested case-control discovery study was undertaken 10 test whether information within the serum peptidome can improve on the utility of CA125 for early ovarian cancer detection. Materials and Methods: High-throughput matrix-assisted laser desorption ionisation mass spectrometry (MALDI-MS) was used to profile 295 serum samples from women pre-dating their ovarian cancer diagnosis and from 585 matched control samples. Classification rules incorporating CA125 and MS peak intensities were tested for discriminating ability. Results: Two peaks were found which in combination with CA125 discriminated cases from controls up to 15 and 11 months before diagnosis, respectively, and earlier than using CA125 alone. One peak was identified as connective tissue-activating peptide III (CTAPIII), whilst the other was putatively identified as platelet factor 4 (PF4). ELISA data supported the down-regulation of PF4 in early cancer cases. Conclusion: Serum peptide information with CA125 improves lead time for early detection of ovarian cancer. The candidate markers are platelet-derived chemokines, suggesting a link between platelet function and tumour development

Metabolome-wide association study on ABCA7 indicates a role of ceramide metabolism in Alzheimer's disease.

Genome-wide association studies (GWASs) have identified genetic loci associated with the risk of Alzheimer's disease (AD), but the molecular mechanisms by which they confer risk are largely unknown. We conducted a metabolome-wide association study (MWAS) of AD-associated loci from GWASs using untargeted metabolic profiling (metabolomics) by ultraperformance liquid chromatography-mass spectrometry (UPLC-MS). We identified an association of lactosylceramides (LacCer) with AD-related single-nucleotide polymorphisms (SNPs) in ABCA7 (P = 5.0 × 10-5 to 1.3 × 10-44). We showed that plasma LacCer concentrations are associated with cognitive performance and genetically modified levels of LacCer are associated with AD risk. We then showed that concentrations of sphingomyelins, ceramides, and hexosylceramides were altered in brain tissue from Abca7 knockout mice, compared with wild type (WT) (P = 0.049-1.4 × 10-5), but not in a mouse model of amyloidosis. Furthermore, activation of microglia increases intracellular concentrations of hexosylceramides in part through induction in the expression of sphingosine kinase, an enzyme with a high control coefficient for sphingolipid and ceramide synthesis. Our work suggests that the risk for AD arising from functional variations in ABCA7 is mediated at least in part through ceramides. Modulation of their metabolism or downstream signaling may offer new therapeutic opportunities for AD

Metabolome-wide association study on ABCA7 indicates a role of ceramide metabolism in Alzheimer’s disease

Genome-wide association studies (GWASs) have identified genetic loci associated with the risk of Alzheimer’s disease (AD), but the molecular mechanisms by which they confer risk are largely unknown. We conducted a metabolome-wide association study (MWAS) of AD-associated loci from GWASs using untargeted metabolic profiling (metabolomics) by ultraperformance liquid chromatography–mass spectrometry (UPLC-MS). We identified an association of lactosylceramides (LacCer) with AD-related single-nucleotide polymorphisms (SNPs) in ABCA7 (P = 5.0 × 10−5 to 1.3 × 10−44). We showed that plasma LacCer concentrations are associated with cognitive performance and genetically modified levels of LacCer are associated with AD risk. We then showed that concentrations of sphingomyelins, ceramides, and hexosylceramides were altered in brain tissue from Abca7 knockout mice, compared with wild type (WT) (P = 0.049–1.4 × 10−5), but not in a mouse model of amyloidosis. Furthermore, activation of microglia increases intracellular concentrations of hexosylceramides in part through induction in the expression of sphingosine kinase, an enzyme with a high control coefficient for sphingolipid and ceramide synthesis. Our work suggests that the risk for AD arising from functional variations in ABCA7 is mediated at least in part through ceramides. Modulation of their metabolism or downstream signaling may offer new therapeutic opportunities for AD

Serum CA19-9 is significantly upregulated up to 2 years before diagnosis with pancreatic cancer: implications for early disease detection

PURPOSE: Biomarkers for the early detection of pancreatic cancer are urgently needed. The primary objective of this study was to evaluate whether increased levels of serum CA19-9, CA125, CEACAM1, and REG3A are present before clinical presentation of pancreatic cancer and to assess the performance of combined markers for early detection and prognosis. EXPERIMENTAL DESIGN: This nested case-control study within the UKCTOCS included 118 single and 143 serial serum samples from 154 postmenopausal women who were subsequently diagnosed with pancreatic cancer and 304 matched noncancer controls. Samples were split randomly into independent training and test sets. CA19-9, CA125, CEACAM1, and REG3A were measured using ELISA and/or CLIA. Performance of markers to detect cancers at different times before diagnosis and for prognosis was evaluated. RESULTS: At 95% specificity, CA19-9 (>37 U/mL) had a sensitivity of 68% up to 1 year, and 53% up to 2 years before diagnosis. Combining CA19-9 and CA125 improved sensitivity as CA125 was elevated (>30 U/mL) in approximately 20% of CA19-9-negative cases. CEACAM1 and REG3A were late markers adding little in combined models. Average lead times of 20 to 23 months were estimated for test-positive cases. Prediagnostic levels of CA19-9 and CA125 were associated with poor overall survival (HR, 2.69 and 3.15, respectively). CONCLUSIONS: CA19-9 and CA125 have encouraging sensitivity for detecting preclinical pancreatic cancer, and both markers can be used as prognostic tools. This work challenges the prevailing view that CA19-9 is upregulated late in the course of pancreatic cancer development

Demonstrating the reliability of in vivo metabolomics based chemical grouping:towards best practice

While grouping/read-across is widely used to fill data gaps, chemical registration dossiers are often rejected due to weak category justifications based on structural similarity only. Metabolomics provides a route to robust chemical categories via evidence of shared molecular effects across source and target substances. To gain international acceptance, this approach must demonstrate high reliability, and best-practice guidance is required. The MetAbolomics ring Trial for CHemical groupING (MATCHING), comprising six industrial, government and academic ring-trial partners, evaluated inter-laboratory reproducibility and worked towards best-practice. An independent team selected eight substances (WY-14643, 4-chloro-3-nitroaniline, 17α-methyl-testosterone, trenbolone, aniline, dichlorprop-p, 2-chloroaniline, fenofibrate); ring-trial partners were blinded to their identities and modes-of-action. Plasma samples were derived from 28-day rat tests (two doses per substance), aliquoted, and distributed to partners. Each partner applied their preferred liquid chromatography–mass spectrometry (LC–MS) metabolomics workflows to acquire, process, quality assess, statistically analyze and report their grouping results to the European Chemicals Agency, to ensure the blinding conditions of the ring trial. Five of six partners, whose metabolomics datasets passed quality control, correctly identified the grouping of eight test substances into three categories, for both male and female rats. Strikingly, this was achieved even though a range of metabolomics approaches were used. Through assessing intrastudy quality-control samples, the sixth partner observed high technical variation and was unable to group the substances. By comparing workflows, we conclude that some heterogeneity in metabolomics methods is not detrimental to consistent grouping, and that assessing data quality prior to grouping is essential. We recommend development of international guidance for quality-control acceptance criteria. This study demonstrates the reliability of metabolomics for chemical grouping and works towards best-practice