Detection of potential new biomarkers of atherosclerosis by probe electrospray ionization mass spectrometry

Introduction

Atherosclerotic diseases are the leading cause of death worldwide. Biomarkers of atherosclerosis are required to monitor and prevent disease progression. While mass spectrometry is a promising technique to search for such biomarkers, its clinical application is hampered by the laborious processes for sample preparation and analysis.

Methods

We developed a rapid method to detect plasma metabolites by probe electrospray ionization mass spectrometry (PESI-MS), which employs an ambient ionization technique enabling atmospheric pressure rapid mass spectrometry. To create an automatic diagnosis system of atherosclerotic disorders, we applied machine learning techniques to the obtained spectra.

Results

Using our system, we successfully discriminated between rabbits with and without dyslipidemia. The causes of dyslipidemia (genetic lipoprotein receptor deficiency or dietary cholesterol overload) were also distinguishable by this method. Furthermore, after induction of atherosclerosis in rabbits with a cholesterol-rich diet, we were able to detect dynamic changes in plasma metabolites. The major metabolites detected by PESI-MS included cholesterol sulfate and a phospholipid (PE18:0/20:4), which are promising new biomarkers of atherosclerosis.

Conclusion

We developed a remarkably fast and easy method to detect potential new biomarkers of atherosclerosis in plasma using PESI-MS.

     

Metabolomic profiling of maternal hair suggests rapid development of intrahepatic cholestasis of pregnancy

Introduction

Intrahepatic cholestasis of pregnancy (ICP) is a common maternal liver disease; development can result in devastating consequences, including sudden fetal death and stillbirth. Currently, recognition of ICP only occurs following onset of clinical symptoms.

Objective

Investigate the maternal hair metabolome for predictive biomarkers of ICP.

Methods

The maternal hair metabolome (gestational age of sampling between 17 and 41 weeks) of 38 Chinese women with ICP and 46 pregnant controls was analysed using gas chromatography–mass spectrometry.

Results

Of 105 metabolites detected in hair, none were significantly associated with ICP.

Conclusion

Hair samples represent accumulative environmental exposure over time. Samples collected at the onset of ICP did not reveal any metabolic shifts, suggesting rapid development of the disease.

     

Increased circulating RANTES in type 2 diabetes

Aim

The pro-atherogenic role of RANTES, a chemokine expressing pleiotropic activities, in the course of type 2 diabetes-related atherosclerosis has been well documented. However, it is not known which of the diabetes-related factors primarily influence serum RANTES levels in patients with type 2 diabetes. Our aim was to investigate relationships between several factors known to be related to an increased risk of atherosclerosis and serum RANTES levels in type 2 diabetic patients.

Methods

A total of 168 subjects were examined, which included 138 patients with type 2 diabetes and 30 non-diabetic controls. Measurements of venous, fasting, plasma glucose, HbA₁c, lipid profile, 1,5-anhydro-D-glucitol (1,5-AG) plasma levels, homocysteine and the fasting, serum C-peptide levels were performed. Serum concentrations of RANTES were assayed using BD? Cytometric Bead Array tests. Peripheral insulin resistance was expressed according to a new index defined by Ohkura et al.

Results

RANTES levels in type 2 diabetic patients correlated with 1,5-AG, fasting glycaemia, HbA₁c and the Ohkura index. Multivariate regression analysis was performed taking into consideration several factors related to the inflammatory process and atherosclerosis, namely the patient’s age, diabetes duration, waist circumference, 1,5-AG, HbA₁c, lipid profile parameters, serum homocysteine levels and Ohkura index, as independent variables potentially influencing serum RANTES levels in type 2 diabetic patients. It is shown that RANTES concentrations in the serum is primarily dependent upon 1,5-AG plasma levels.

Conclusion

Our results suggest that increased serum levels of RANTES in type 2 diabetic patients are closely related to postprandial (acute) hyperglycaemia.

     

Optimization of fecal sample preparation for untargeted LC-HRMS based metabolomics

Introduction

Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.

Objectives

In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.

Methods

The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.

Results

A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.

Conclusion

The workflow generated repeatable and informative fingerprints for robust metabolome characterization.

     

Forecasting infectious disease emergence subject to seasonal forcing

Background

Despite high vaccination coverage, many childhood infections pose a growing threat to human populations. Accurate disease forecasting would be of tremendous value to public health. Forecasting disease emergence using early warning signals (EWS) is possible in non-seasonal models of infectious diseases. Here, we assessed whether EWS also anticipate disease emergence in seasonal models.

Methods

We simulated the dynamics of an immunizing infectious pathogen approaching the tipping point to disease endemicity. To explore the effect of seasonality on the reliability of early warning statistics, we varied the amplitude of fluctuations around the average transmission. We proposed and analyzed two new early warning signals based on the wavelet spectrum. We measured the reliability of the early warning signals depending on the strength of their trend preceding the tipping point and then calculated the Area Under the Curve (AUC) statistic.

Results

Early warning signals were reliable when disease transmission was subject to seasonal forcing. Wavelet-based early warning signals were as reliable as other conventional early warning signals. We found that removing seasonal trends, prior to analysis, did not improve early warning statistics uniformly.

Conclusions

Early warning signals anticipate the onset of critical transitions for infectious diseases which are subject to seasonal forcing. Wavelet-based early warning statistics can also be used to forecast infectious disease.

     

Metabolic response of porcine colon explants to in vitro infection by <Emphasis Type="Italic">Brachyspira hyodysenteriae</Emphasis>: a leap into disease pathophysiology

Introduction

Swine dysentery caused by Brachyspira hyodysenteriae is a production limiting disease in pig farming. Currently antimicrobial therapy is the only treatment and control method available.

Objective

The aim of this study was to characterize the metabolic response of porcine colon explants to infection by B. hyodysenteriae.

Methods

Porcine colon explants exposed to B. hyodysenteriae were analyzed for histopathological, metabolic and pro-inflammatory gene expression changes.

Results

Significant epithelial necrosis, increased levels of l-citrulline and IL-1α were observed on explants infected with B. hyodysenteriae.

Conclusions

The spirochete induces necrosis in vitro likely through an inflammatory process mediated by IL-1α and NO.

     

Markov modeling in hepatitis B screening and linkage to care

Background

With up to 240 million people chronically infected with hepatitis B worldwide, including an estimated 2 million in the United States, widespread screening is needed to link the infected to care and decrease the possible consequences of untreated infection, including liver cancer, cirrhosis and death. Screening is currently fraught with challenges in both the developed and developing world. New point-of-care tests may have advantages over standard-of-care tests in terms of cost-effectiveness and linkage to care. Stochastic modeling is applied here for relative utility assessment of point-of-care tests and standard-of-care tests for screening.

Methods

We analyzed effects of point-of-care versus standard-of-care testing using Markov models for disease progression in individual patients. Simulations of large cohorts with distinctly quantified models permitted the assessment of particular screening schemes. The validity of the trends observed is supported by sensitivity analyses for the simulation parameters.

Results

Increased utilization of point-of-care screening was shown to decrease hepatitis B-related mortalities and increase life expectancy at low projected expense.

Conclusions

The results suggest that standard-of-care screening should be substituted by point-of-care tests resulting in improved linkage to care and decrease in long-term complications.

     

Plasma lipidomic profiling in patients with rheumatoid arthritis

Introduction

Rheumatoid arthritis (RA) is linked to increased cardiovascular morbidity and mortality, not completely explained by traditional risk factors. Importantly, the increased risk occurs despite lower levels of total and low-density lipoprotein cholesterol. Whilst systemic inflammation may be a factor, it is possible that changes in individual lipid species contribute to the increased cardiovascular risk.

Objectives

In the present study, we characterized plasma lipidomic profiles in patients with RA in comparison with healthy controls.

Methods

Patients with RA (n = 32) and age- and gender-matched healthy volunteers (n = 84) were recruited. Fasting plasma lipid profiles were measured using electrospray-ionisation tandem mass spectrometry. 24 lipid classes and subclasses were measured.

Results

Patients with RA had normal total, low-density lipoprotein and high-density lipoprotein cholesterol, but higher triglycerides than controls. Five lipid classes (dihydroceramides, alkylphosphatidylethanolamine, alkenylphosphatidylethanolamine, lysophosphatidylinositol, phosphatidylserine) differed between patients with RA and controls. Then we measured 36 lipid species within these 5 classes and found that 11 lipid species were different between patients with RA and controls. Three lipid classes (dihydroceramides, lysophosphatidylinositol, phosphatidylserine) and 10 lipid species remained significantly associated with RA after adjusting for age, sex, body mass index, current smoking, systolic blood pressure and anti-hypertensive treatment in a binary logistic regression model.

Conclusion

This study has identified lipid alterations in RA. These alterations of lipids warrant further investigation as they may be associated with accelerated atherosclerosis and joint inflammation in patient with RA.

     

A lost opportunity for science: journals promote data sharing in metabolomics but do not enforce it

Introduction

Data sharing is being increasingly required by journals and has been heralded as a solution to the ‘replication crisis’.

Objectives

(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals’ policies to those that publish the most metabolomics papers.

Methods

A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.

Results

Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.

Conclusion

Further efforts are required to improve data sharing in metabolomics.

     

Minimal variation of the plasma lipidome after delayed processing of neonatal cord blood

Background

Cord blood lipids are potential disease biomarkers. We aimed to determine if their concentrations were affected by delayed blood processing.

Method

Refrigerated cord blood from six healthy newborns was centrifuged every 12 h for 4 days. Plasma lipids were analysed by liquid chromatography/mass spectroscopy.

Results

Of 262 lipids identified, only eight varied significantly over time. These comprised three dihexosylceramides, two phosphatidylserines and two phosphatidylethanolamines whose relative concentrations increased and one sphingomyelin that decreased.

Conclusion

Delay in separation of plasma from refrigerated cord blood has minimal effect overall on the plasma lipidome.

     

Pseudo current density maps of electrophysiological heart,nerve or brain function and their physical basis

Background

In recent years the visualization of biomagnetic measurement data by so-called pseudo current density maps or Hosaka-Cohen (HC) transformations became popular.

Methods

The physical basis of these intuitive maps is clarified by means of analytically solvable problems.

Results

Examples in magnetocardiography, magnetoencephalography and magnetoneurography demonstrate the usefulness of this method.

Conclusion

Hardware realizations of the HC-transformation and some similar transformations are discussed which could advantageously support cross-platform comparability of biomagnetic measurements.

     

Metabolites predict cardiovascular disease events in persons living with HIV: a pilot case–control study

Introduction

Persons living with HIV (PLWH) are at higher risk for cardiovascular disease (CVD) events than uninfected persons. Current risk-stratification methods to define PLWH at highest risk for CVD events are lacking.

Methods

Using tandem flow injection mass spectrometry, we quantified plasma levels of 60 metabolites in 24 matched pairs of PLWH [1:1 with and without known coronary artery disease (CAD)]. Metabolite levels were reduced to interpretable factors using principal components analysis.

Results

Factors derived from short-chain dicarboxylacylcarnitines (SCDA) (p?=?0.08) and glutamine/valine (p?=?0.003) were elevated in CAD cases compared to controls.

Conclusion

SCDAs and glutamine/valine may be valuable markers of cardiovascular risk among persons living with HIV in the future, pending validation in larger cohorts.

     

Nucleotide binding domain 1 pharmacophore modeling for visualization and analysis of P-glycoprotein–flavonoid molecular interactions

Background

P-glycoprotein (P-gp) is a 170-kDa membrane protein. It provides a barrier function and help to excrete toxins from the body as a transporter. Some bioflavonoids have been shown to block P-gp activity.

Objective

To evaluate the important amino acid residues within nucleotide binding domain 1 (NBD1) of P-gp that play a key role in molecular interactions with flavonoids using structure-based pharmacophore model.

Methods

In the molecular docking with NBD1 models, a putative binding site of flavonoids was proposed and compared with the site for ATP. The binding modes for ligands were achieved using LigandScout to generate the P-gp–flavonoid pharmacophore models.

Results

The binding pocket for flavonoids was investigated and found these inhibitors compete with the ATP for binding site in NBD1 including the NBD1 amino acid residues identified by the in silico techniques to be involved in the hydrogen bonding and van der Waals (hydrophobic) interactions with flavonoids.

Conclusion

These flavonoids occupy with the same binding site of ATP in NBD1 proffering that they may act as an ATP competitive inhibitor.

     

Longitudinal data methods for evaluating genome-by-epigenome interactions in families

Background

Longitudinal measurement is commonly employed in health research and provides numerous benefits for understanding disease and trait progression over time. More broadly, it allows for proper treatment of correlated responses within clusters. We evaluated 3 methods for analyzing genome-by-epigenome interactions with longitudinal outcomes from family data.

Results

Linear mixed-effect models, generalized estimating equations, and quadratic inference functions were used to test a pharmacoepigenetic effect in 200 simulated posttreatment replicates. Adjustment for baseline outcome provided greater power and more accurate control of Type I error rates than computation of a pre-to-post change score.

Conclusions

Comparison of all modeling approaches indicated a need for bias correction in marginal models and similar power for each method, with quadratic inference functions providing a minor decrement in power compared to generalized estimating equations and linear mixed-effects models.

     

Untargeted metabolomics suffers from incomplete raw data processing

Introduction

Untargeted metabolomics is a powerful tool for biological discoveries. To analyze the complex raw data, significant advances in computational approaches have been made, yet it is not clear how exhaustive and reliable the data analysis results are.

Objectives

Assessment of the quality of raw data processing in untargeted metabolomics.

Methods

Five published untargeted metabolomics studies, were reanalyzed.

Results

Omissions of at least 50 relevant compounds from the original results as well as examples of representative mistakes were reported for each study.

Conclusion

Incomplete raw data processing shows unexplored potential of current and legacy data.

     

Choroidal eye metastases from (recurrent) primary peritoneal carcinoma: case report and review of the literature

Background

Choroidal metastases from gynaecological primary are extremely rare. There is no documented case in the literature of choroid metastasis in a patient with primary peritoneal carcinoma (PPC).

Methods & Results

We describe the first case of a 54-year-old woman with a history of borderline mucinous tumour who presented 17 months later with PPC and 21 months after with recurrent disease metastatic to the eye, and review pertinent literature.

Conclusion

High index of suspicion is warranted when patients with history of primary peritoneal carcinoma present with visual complaints in order to treat and/or relieve symptomatology from metastatic eye disease.

     

Smooth muscle cell differentiation: Mechanisms and models for vascular diseases

Background

Vascular smooth muscle cells (VSMCs) are mature cells that play critical roles in both normal and aberrant cardiovascular conditions. In response to various environmental cues, VSMCs can dedifferentiate from a contractile state to a highly proliferative synthetic state through the so-called ‘phenotypic switching’ process. Changes in VSMC phenotype contribute to numerous vascular-related diseases, including atherosclerosis, calcification, and restenosis following angioplasty. Adventitial VSMC progenitor cells also contribute to formation of the neointima.

Methods/Results

Herein, we review both, the roles of VSMC differentiation in vascular diseases, and the in vitro models used to investigate the molecular mechanisms involved in the regulation of VSMC differentiation and phenotype modulation.

Conclusion

A comprehensive understanding of VSMC behavior in vascular diseases is essential to identify new therapeutic targets for the prevention and treatment of cardiovascular diseases.

     

Quantitative analysis of tetrahydrofolate metabolites from <Emphasis Type="Italic">clostridium autoethanogenum</Emphasis>

Introduction

Quantification of tetrahydrofolates (THFs), important metabolites in the Wood–Ljungdahl pathway (WLP) of acetogens, is challenging given their sensitivity to oxygen.

Objective

To develop a simple anaerobic protocol to enable reliable THFs quantification from bioreactors.

Methods

Anaerobic cultures were mixed with anaerobic acetonitrile for extraction. Targeted LC–MS/MS was used for quantification.

Results

Tetrahydrofolates can only be quantified if sampled anaerobically. THF levels showed a strong correlation to acetyl-CoA, the end product of the WLP.

Conclusion

Our method is useful for relative quantification of THFs across different growth conditions. Absolute quantification of THFs requires the use of labelled standards.

     

KniMet: a pipeline for the processing of chromatography–mass spectrometry metabolomics data

Introduction

Data processing is one of the biggest problems in metabolomics, given the high number of samples analyzed and the need of multiple software packages for each step of the processing workflow.

Objectives

Merge in the same platform the steps required for metabolomics data processing.

Methods

KniMet is a workflow for the processing of mass spectrometry-metabolomics data based on the KNIME Analytics platform.

Results

The approach includes key steps to follow in metabolomics data processing: feature filtering, missing value imputation, normalization, batch correction and annotation.

Conclusion

KniMet provides the user with a local, modular and customizable workflow for the processing of both GC–MS and LC–MS open profiling data.

     

Italian cohort of patients affected by inflammatory bowel disease is characterised by variation in glycerophospholipid,free fatty acids and amino acid levels

Background

Inflammatory bowel disease is a group of pathologies characterised by chronic inflammation of the intestine and an unclear aetiology. Its main manifestations are Crohn’s disease and ulcerative colitis. Currently, biopsies are the most used diagnostic tests for these diseases and metabolomics could represent a less invasive approach to identify biomarkers of disease presence and progression.

Objectives

The lipid and the polar metabolite profile of plasma samples of patients affected by inflammatory bowel disease have been compared with healthy individuals with the aim to find their metabolomic differences. Also, a selected sub-set of samples was analysed following solid phase extraction to further characterise differences between pathological samples.

Methods

A total of 200 plasma samples were analysed using drift tube ion mobility coupled with time of flight mass spectrometry and liquid chromatography for the lipid metabolite profile analysis, while liquid chromatography coupled with triple quadrupole mass spectrometry was used for the polar metabolite profile analysis.

Results

Variations in the lipid profile between inflammatory bowel disease and healthy individuals were highlighted. Phosphatidylcholines, lyso-phosphatidylcholines and fatty acids were significantly changed among pathological samples suggesting changes in phospholipase A₂ and arachidonic acid metabolic pathways. Variations in the levels of cholesteryl esters and glycerophospholipids were also found. Furthermore, a decrease in amino acids levels suggests mucosal damage in inflammatory bowel disease.

Conclusions

Given good statistical results and predictive power of the model produced in our study, metabolomics can be considered as a valid tool to investigate inflammatory bowel disease.