NMR-Based Metabolomics for the Assessment of Inhaled Pharmacotherapy in Chronic Obstructive Pulmonary Disease Patients

Predicting reperfusion injury and functional status after stroke using blood biomarkers: the STROKELABED study

BACKGROUND

Ischemic stroke is a leading cause of disability and mortality, particularly among the elderly. Recanalization therapies, including thrombolysis and thrombectomy, are essential for restoring blood flow and saving ischemic tissue. However, these interventions may trigger reperfusion injury, worsening inflammation and tissue damage, leading to blood-brain-barrier (BBB) disruption, cerebral edema (CE) and adverse functional outcomes. Here we propose a model integrating circulating inflammatory biomarkers with metabolomic and lipoproteomic data able to help clinicians in predicting BBB disruption, CE at 24 h post stroke onset and poor post-stroke functional outcome (Modified Rankin Scale (mRS > 2).

METHODS

Peripheral blood from 87 patients was collected at admission and 24 h after stroke onset. The logistic LASSO regression algorithm was employed to identify the optimal combination of metabolites, lipoprotein-related parameters and circulating biomarkers to discriminate the groups of interest at the two time-points.

RESULTS

Multivariable logistic regression models included as covariates: age, sex, onset-to-treatment time, treatment with lipid-lowering medications before stroke, history of heart failure, history of atrial fibrillation and history of diabetes. The regression models showed that methionine, acetate, GlyA and MMP-2 were significant predictors of BBB disruption, methionine, acetate, TIMP-1 and CXCL-10 predicted 24-hours CE, whereas a poor functional outcome at three months was predicted by CXCL-10, IL-12 and LDL-5.

CONCLUSIONS

As stroke has a heterogeneous pathophysiology, a personalized approach based on biomarkers, as presented in this study, shown to be effective in tackling patient individual risk and could help in developing novel diagnostic, prognostic, and therapeutic neuroprotective strategies for the management of stroke patients.

Studying Alzheimer's disease through an integrative serum metabolomic and lipoproteomic approach

BACKGROUND

Alzheimer's disease (AD) is the most frequent neurodegenerative disorder worldwide. The great variability in disease evolution and the incomplete understanding of the molecular mechanisms underlying AD make it difficult to predict when a patient will convert from prodromal stage to dementia. We hypothesize that metabolic alterations present at the level of the brain could be reflected at a systemic level in blood serum of patients, and that these alterations could be used as prognostic biomarkers.

METHODS

This pilot study proposes a serum investigation via nuclear magnetic resonance (NMR) spectroscopy in a consecutive series of AD patients including 57 patients affected by Alzheimer's disease at dementia stage (AD-dem) and 45 patients with mild cognitive impairment (MCI) due to AD (MCI-AD). As control group, we considered 31 subjects with mild cognitive impairment in whom AD and other neurodegenerative disorders were excluded (MCI). A panel of 26 metabolites and 112 lipoprotein-related parameters was quantified and the logistic LASSO regression algorithm was employed to identify the optimal combination of metabolites-lipoproteins and their ratios to discriminate the groups of interest.

RESULTS

In the training set, our model classified AD-dem and MCI with an accuracy of 81.7%. These results were reproduced in the validation set (accuracy 75.0%). Evolution of MCI-AD patients was evaluated over time. Patients who displayed a decrease in MMSE < 1.5 point per year were considered at lower progression rate: we obtained a division in 18 MCI-AD at lower progression rate (MCI-AD LR) and 27 at higher progression rate (MCI-AD HR). The model calculated using 4 metabolic features identified MCI-AD LR and MCI-AD HR with an accuracy of 73.3%.

CONCLUSIONS

The identification of potential novel peripheral biomarkers of Alzheimer's disease, as proposed in this study, opens a new prospect for an innovative and minimally invasive method to identify AD in its very early stages. We proposed a novel approach able to sub-stratify MCI-AD patients identifying those associated with a faster rate of clinical progression.

The serum metabolomic profiles of atrial fibrillation patients treated with direct oral anticoagulants or vitamin K antagonists

AIMS

Long-term oral anticoagulation is the primary therapy for preventing ischemic stroke in patients with atrial fibrillation (AF). Different types of oral anticoagulant drugs can have specific effects on the metabolism of patients. Here we characterize, for the first time, the serum metabolomic and lipoproteomic profiles of AF patients treated with anticoagulants: vitamin K antagonists (VKAs) or direct oral anticoagulants (DOACs).

MATERIALS AND METHODS

Serum samples of 167 AF patients (median age 78 years, 62 % males, 70 % on DOACs treatment) were analyzed via high resolution 1H nuclear magnetic resonance (NMR) spectroscopy. Data on 25 metabolites and 112 lipoprotein-related fractions were quantified and analyzed with multivariate and univariate statistical approaches.

KEY FINDINGS

Our data provide evidence that patients treated with VKAs and DOACs present significant differences in their profiles: lower levels of alanine and lactate (odds ratio: 1.72 and 1.84), free cholesterol VLDL-4 subfraction (OR: 1.75), triglycerides LDL-1 subfraction (OR: 1.80) and 4 IDL cholesterol fractions (ORs ∼ 1.80), as well as higher levels of HDL cholesterol (OR: 0.48), apolipoprotein A1 (OR: 0.42) and 7 HDL cholesterol fractions/subfractions (ORs: 0.40-0.51) are characteristic of serum profile of patients on DOACs' therapy.

SIGNIFICANCE

Our results support the usefulness of NMR-based metabolomics for the description of the effects of oral anticoagulants on AF patient circulating metabolites and lipoproteins. The higher serum levels of HDL cholesterol observed in patients on DOACs could contribute to explaining their reduced cardiovascular risk, suggesting the need of further studies in this direction to fully understand possible clinical implications.

Exhaled breath analysis in adult patients with cystic fibrosis by real-time proton mass spectrometry

BACKGROUND

Proton-transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS) is a promising tool for a rapid online determination of exhaled volatile organic compounds (eVOCs) profiles in patients with cystic fibrosis (CF).

OBJECTIVE

To detect VOC breath signatures specific to adult patients with CF compared with controls using PTR-TOF-MS.

METHODS

102 CF patients (54 M/48, mean age 25.6 ± 7.8 yrs) and 97 healthy controls (56 M/41F, mean age 25.8 ± 6.0 yrs) were examined. Samples from normal quiet breathing and forced expiratory maneuvers were analyzed with PTR-TOF-MS (Ionicon, Austria) to obtain VOC profiles listed as ions at various mass-to-charge ratios (m/z).

RESULTS

PTR-TOF-MS analysis was able to detect 167 features in exhaled breath from CF patients and healthy controls. According to cluster analysis and LASSO regression, patients with CF and controls were separated. The most significant VOCs for CF were indole, phenol, dimethyl sulfide, and not indicated: m/z = 297.0720 ([C12H13N2O7 and C17H13O5]H + ), m/z = 281.0534 ([C19H7NO2, C12H11NO7 and C16H9O5]H + ) during five-fold cross-validation both in forced expiratory maneuver and in normal quiet breathing.

CONCLUSION

PTR-TOF-MS is a promising method for determining the molecular composition of exhaled air specific to CF.

NMR-based metabolomics in Alzheimer's disease research: a review

Alzheimer's disease (AD) is a progressive neurodegenerative disorder and represents the most common cause of dementia in the elderly population worldwide. Currently, there is no cure for AD, and the continuous increase in the number of susceptible individuals poses one of the most significant emerging threats to public health. However, the molecular pathways involved in the onset and progression of AD are not fully understood. This information is crucial for developing less invasive diagnostic instruments and discovering novel potential therapeutic targets. Metabolomics studies the complete ensemble of endogenous and exogenous metabolites present in biological specimens and may provide an interesting approach to identify alterations in multiple biochemical processes associated with AD onset and evolution. In this mini review, we summarize the results from metabolomic studies conducted using nuclear magnetic resonance (NMR) spectroscopy on human biological samples (blood derivatives, cerebrospinal fluid, urine, saliva, and tissues) from AD patients. We describe the metabolic alterations identified in AD patients compared to controls and to patients diagnosed with mild cognitive impairment (MCI). Moreover, we discuss the challenges and issues associated with the application of NMR-based metabolomics in the context of AD research.

Fingerprinting and profiling in metabolomics of biosamples

This review focuses on metabolomics from an NMR point of view. It attempts to cover the broad scope of metabolomics and describes the NMR experiments that are most suitable for each sample type. It is addressed not only to NMR specialists, but to all researchers who wish to approach metabolomics with a clear idea of what they wish to achieve but not necessarily with a deep knowledge of NMR. For this reason, some technical parts may seem a bit naïve to the experts. The review starts by describing standard metabolomics procedures, which imply the use of a dedicated 600 MHz instrument and of four properly standardized 1D experiments. Standardization is a must if one wants to directly compare NMR results obtained in different labs. A brief mention is also made of standardized pre-analytical procedures, which are even more essential. Attention is paid to the distinction between fingerprinting and profiling, and the advantages and disadvantages of fingerprinting are clarified. This aspect is often not fully appreciated. Then profiling, and the associated problems of signal assignment and quantitation, are discussed. We also describe less conventional approaches, such as the use of different magnetic fields, the use of signal enhancement techniques to increase sensitivity, and the potential of field-shuttling NMR. A few examples of biomedical applications are also given, again with the focus on NMR techniques that are most suitable to achieve each particular goal, including a description of the most common heteronuclear experiments. Finally, the growing applications of metabolomics to foodstuffs are described.

Update on metabolomic findings in COPD patients

COPD is a heterogeneous disorder that shows diverse clinical presentations (phenotypes and "treatable traits") and biological mechanisms (endotypes). This heterogeneity implies that to carry out a more personalised clinical management, it is necessary to classify each patient accurately. With this objective, and in addition to clinical features, it would be very useful to have well-defined biological markers. The search for these markers may either be done through more conventional laboratory and hypothesis-driven techniques or relatively blind high-throughput methods, with the omics approaches being suitable for the latter. Metabolomics is the science that studies biological processes through their metabolites, using various techniques such as gas and liquid chromatography, mass spectrometry and nuclear magnetic resonance. The most relevant metabolomics studies carried out in COPD highlight the importance of metabolites involved in pathways directly related to proteins (peptides and amino acids), nucleic acids (nitrogenous bases and nucleosides), and lipids and their derivatives (especially fatty acids, phospholipids, ceramides and eicosanoids). These findings indicate the relevance of inflammatory-immune processes, oxidative stress, increased catabolism and alterations in the energy production. However, some specific findings have also been reported for different COPD phenotypes, demographic characteristics of the patients, disease progression profiles, exacerbations, systemic manifestations and even diverse treatments. Unfortunately, the studies carried out to date have some limitations and shortcomings and there is still a need to define clear metabolomic profiles with clinical utility for the management of COPD and its implicit heterogeneity.

NMR-Based Metabolomics to Evaluate Individual Response to Treatments

The aim of this chapter is to highlight the various aspects of metabolomics in relation to health and diseases, starting from the definition of metabolic space and of how individuals tend to maintain their own position in this space. Physio-pathological stimuli may cause individuals to lose their position and then regain it, or move irreversibly to other positions. By way of examples, mostly selected from our own work using ¹H NMR on biological fluids, we describe the effects on the individual metabolomic fingerprint of mild external interventions, such as diet or probiotic administration. Then we move to pathologies (such as celiac disease, various types of cancer, viral infections, and other diseases), each characterized by a well-defined metabolomic fingerprint. We describe the effects of drugs on the disease fingerprint and on its reversal to a healthy metabolomic status. Drug toxicity can be also monitored by metabolomics. We also show how the individual metabolomic fingerprint at the onset of a disease may discriminate responders from non-responders to a given drug, or how it may be prognostic of e.g., cancer recurrence after many years. In parallel with fingerprinting, profiling (i.e., the identification and quantification of many metabolites and, in the case of selected biofluids, of the lipoprotein components that contribute to the ¹H NMR spectral features) can provide hints on the metabolic pathways that are altered by a disease and assess their restoration after treatment.

Systematic Review of NMR-Based Metabolomics Practices in Human Disease Research

Nuclear magnetic resonance (NMR) spectroscopy is one of the principal analytical techniques for metabolomics. It has the advantages of minimal sample preparation and high reproducibility, making it an ideal technique for generating large amounts of metabolomics data for biobanks and large-scale studies. Metabolomics is a popular “omics” technology and has established itself as a comprehensive exploratory biomarker tool; however, it has yet to reach its collaborative potential in data collation due to the lack of standardisation of the metabolomics workflow seen across small-scale studies. This systematic review compiles the different NMR metabolomics methods used for serum, plasma, and urine studies, from sample collection to data analysis, that were most popularly employed over a two-year period in 2019 and 2020. It also outlines how these methods influence the raw data and the downstream interpretations, and the importance of reporting for reproducibility and result validation. This review can act as a valuable summary of NMR metabolomic workflows that are actively used in human biofluid research and will help guide the workflow choice for future research.

Metabolic profile of exhaled breath condensate from the pneumonia patients

PURPOSE OF THE STUDY

Exhaled breath condensate (EBC) is increasingly being used for disease diagnosis and environmental exposure assessment as a noninvasive method reducing the risk of exposure. The purpose of this study was to investigate the application of a new sample type of EBC in pneumonia by metabolomics and to explore differential metabolites and potential metabolic pathways.

MATERIALS AND METHODS

A case-control study was performed at the Peking University Third Hospital from August to December 2020. C-MS/MS analyses were performed on EBC samples using a UHPLC system.

RESULTS

Totally 22 patients with pneumonia and 24 healthy controls were recruited. Using untargeted metabolomics based on LC-MS/MS analysis, 25 kinds of differential metabolites were found. Through a comprehensive analysis of the pathways in which the differential metabolites were located, the key pathway with the highest correlation with the difference of metabolites was taurine and hypotaurine metabolism.

CONCLUSIONS

The study implicates that the hypotaurine/taurine metabolic pathway may play a role on the development of pneumonia through metabolism analysis on EBC and the 3-Sulfinoalanine may be used as a biomarker in the diagnosis of pneumonia.

Research Progress of NMR in Natural Product Quantification

In the fields of medicine and health, traditional high-performance liquid chromatography or UV-visible spectrophotometry is generally used for substance quantification. However, over time, nuclear magnetic resonance spectroscopy (NMR) has gradually become more mature. Nuclear magnetic resonance spectroscopy has certain advantages in the quantitative analysis of substances, such as being nondestructive, having a high flux and short analysis time. Nuclear magnetic resonance spectroscopy has been included in the pharmacopoeiae of various countries. In this paper, the principle of nuclear magnetic resonance spectroscopy and the recent progress in the quantitative study of natural products by NMR are reviewed, and its application in the quantitative study of natural products is proposed. At the same time, the problems of using NMR alone to quantify natural products are summarized and corresponding suggestions are put forward.

Effects of Workers Exposure to Nanoparticles Studied by NMR Metabolomics

In this study, the effects of occupational exposure to nanoparticles (NPs) were studied by NMR metabolomics. Exhaled breath condensate (EBC) and blood plasma samples were obtained from a research nanoparticles-processing unit at a national research university. The samples were taken from three groups of subjects: samples from workers exposed to nanoparticles collected before and after shift, and from controls not exposed to NPs. Altogether, 60 1H NMR spectra of exhaled breath condensate (EBC) samples and 60 1H NMR spectra of blood plasma samples were analysed, 20 in each group. The metabolites identified together with binning data were subjected to multivariate statistical analysis, which provided clear discrimination of the groups studied. Statistically significant metabolites responsible for group separation served as a foundation for analysis of impaired metabolic pathways. It was found that the acute effect of NPs exposure is mainly reflected in the pathways related to the production of antioxidants and other protective species, while the chronic effect is manifested mainly in the alteration of glutamine and glutamate metabolism, and the purine metabolism pathway.

Exploration of Blood Lipoprotein and Lipid Fraction Profiles in Healthy Subjects through Integrated Univariate, Multivariate, and Network Analysis Reveals Association of Lipase Activity and Cholesterol Esterification with Sex and Age

In this study, we investigated blood lipoprotein and lipid fraction profiles, quantified using nuclear magnetic resonance, in a cohort of 844 healthy blood donors, integrating standard univariate and multivariate analysis with predictive modeling and network analysis. We observed a strong association of lipoprotein and lipid main fraction profiles with sex and age. Our results suggest an age-dependent remodulation of lipase lipoprotein activity in men and a change in the mechanisms controlling the ratio between esterified and non-esterified cholesterol in both men and women.

Metabolomic Profiling Reveals Sex Specific Associations with Chronic Obstructive Pulmonary Disease and Emphysema

Susceptibility and progression of lung disease, as well as response to treatment, often differ by sex, yet the metabolic mechanisms driving these sex-specific differences are still poorly understood. Women with chronic obstructive pulmonary disease (COPD) have less emphysema and more small airway disease on average than men, though these differences become less pronounced with more severe airflow limitation. While small studies of targeted metabolites have identified compounds differing by sex and COPD status, the sex-specific effect of COPD on systemic metabolism has yet to be interrogated. Significant sex differences were observed in 9 of the 11 modules identified in COPDGene. Sex-specific associations by COPD status and emphysema were observed in 3 modules for each phenotype. Sex stratified individual metabolite associations with COPD demonstrated male-specific associations in sphingomyelins and female-specific associations in acyl carnitines and phosphatidylethanolamines. There was high preservation of module assignments in SPIROMICS (SubPopulations and InteRmediate Outcome Measures In COPD Study) and similar female-specific shift in acyl carnitines. Several COPD associated metabolites differed by sex. Acyl carnitines and sphingomyelins demonstrate sex-specific abundances and may represent important metabolic signatures of sex differences in COPD. Accurately characterizing the sex-specific molecular differences in COPD is vital for personalized diagnostics and therapeutics.

Differential Network Analysis Reveals Molecular Determinants Associated with Blood Pressure and Heart Rate in Healthy Subjects

There is mounting evidence that subclinical nonpathological high blood pressure and heart rate during youth and adulthood steadily increase the risk of developing a cardiovascular disease at a later stage. For this reason, it is important to understand the mechanisms underlying the subclinical elevation of blood pressure and heart rate in healthy, relatively young individuals. In the present study, we present a network-based metabolomic study of blood plasma metabolites and lipids measured using nuclear magnetic resonance spectroscopy on 841 adult healthy blood donor volunteers, which were stratified for subclinical low and high blood pressure (systolic and diastolic) and heart rate. Our results indicate a rewiring of metabolic pathways active in high and low groups, indicating that the subjects with subclinical high blood pressure and heart rate could present latent cardiometabolic dysregulations.

NMR Profiling of Exhaled Breath Condensate Defines Different Metabolic Phenotypes of Non-Cystic Fibrosis Bronchiectasis

Nuclear-magnetic-resonance (NMR) profiling of exhaled breath condensate (EBC) provides insights into the pathophysiology of bronchiectasis by identifying specific biomarkers. We evaluated whether NMR-based metabolomics discriminates the EBC-derived metabolic phenotypes (“metabotypes”) of 41 patients with non-cystic fibrosis (nCF) bronchiectasis of various etiology [24 subjects with Primary Ciliary Dyskinesia (PCD); 17 patients with bronchiectasis not associated with PCD (nCF/nPCD)], who were compared to 17 healthy subjects (HS). NMR was used for EBC profiling, and Orthogonal Projections to Latent Structures with partial least-squares discriminant analysis (OPLS-DA) was used as a classifier. The results were validated by using the EBC from 17 PCD patients not included in the primary analysis. Different statistical models were built, which compared nCF/nPCD and HS, PCD and HS, all classes (nCF/nPCD-PCD-HS), and, finally, PCD and nCF/nPCD. In the PCD-nCF/nPCD model, four statistically significant metabolites were able to discriminate between the two groups, with only a minor reduction of the quality parameters. In particular, for nCF/nPCD, acetone/acetoin and methanol increased by 21% and 18%, respectively. In PCD patients, ethanol and lactate increased by 25% and 28%, respectively. They are all related to lung inflammation as methanol is found in the exhaled breath of lung cancer patients, acetone/acetoin produce toxic ROS that damage lung tissue in CF, and lactate is observed in acute inflammation. Interestingly, a high concentration of ethanol hampers cilia beating and can be associated with the genetic defect of PCD. Model validation with 17 PCD samples not included in the primary analysis correctly predicted all samples. Our results indicate that NMR of EBC discriminates nCF/nPCD and PCD bronchiectasis patients from HS, and patients with nCF/nPCD from those with PCD. The metabolites responsible for between-group separation identified specific metabotypes, which characterize bronchiectasis of a different etiology.