Publications by authors named "Leonardo Tenori"

87 Publications

Analysis of Metabolite and Lipid Association Networks Reveals Molecular Mechanisms Associated with 3-Month Mortality and Poor Functional Outcomes in Patients with Acute Ischemic Stroke after Thrombolytic Treatment with Recombinant Tissue Plasminogen Activator.

J Proteome Res 2021 Sep 2. Epub 2021 Sep 2.

Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Stippeneng 4, Wageningen 6708 WE, the Netherlands.

Here, we present an integrated multivariate, univariate, network reconstruction and differential analysis of metabolite-metabolite and metabolite-lipid association networks built from an array of 18 serum metabolites and 110 lipids identified and quantified through nuclear magnetic resonance spectroscopy in a cohort of 248 patients, of which 22 died and 82 developed a poor functional outcome within 3 months from acute ischemic stroke (AIS) treated with intravenous recombinant tissue plasminogen activator. We explored differences in metabolite and lipid connectivity of patients who did not develop a poor outcome and who survived the ischemic stroke from the related opposite conditions. We report statistically significant differences in the connectivity patterns of both low- and high-molecular-weight metabolites, implying underlying variations in the metabolic pathway involving leucine, glycine, glutamine, tyrosine, phenylalanine, citric, lactic, and acetic acids, ketone bodies, and different lipids, thus characterizing patients' outcomes. Our results evidence the promising and powerful role of the metabolite-metabolite and metabolite-lipid association networks in investigating molecular mechanisms underlying AIS patient's outcome.
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http://dx.doi.org/10.1021/acs.jproteome.1c00406DOI Listing
September 2021

Lipid and metabolite correlation networks specific to clinical and biochemical covariate show differences associated with sexual dimorphism in a cohort of nonagenarians.

Geroscience 2021 Jul 29. Epub 2021 Jul 29.

Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen, the Netherlands.

This study defines and estimates the metabolite-lipidic component association networks constructed from an array of 20 metabolites and 114 lipids identified and quantified via NMR spectroscopy in the serum of a cohort of 355 Italian nonagenarians and ultra-nonagenarian. Metabolite-lipid association networks were built for men and women and related to an array of 101 clinical and biochemical parameters, including the presence of diseases, bio-humoral parameters, familiarity diseases, drugs treatments, and risk factors. Different connectivity patterns were observed in lipids, branched chains amino acids, alanine, and ketone bodies, suggesting their association with the sex-related and sex-clinical condition-related intrinsic metabolic changes. Furthermore, our results demonstrate, using a holistic system biology approach, that the characterization of metabolic structures and their dynamic inter-connections is a promising tool to shed light on the dimorphic pathophysiological mechanisms of aging at the molecular level.
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http://dx.doi.org/10.1007/s11357-021-00404-3DOI Listing
July 2021

A Serum Metabolomics Classifier Derived from Elderly Patients with Metastatic Colorectal Cancer Predicts Relapse in the Adjuvant Setting.

Cancers (Basel) 2021 Jun 2;13(11). Epub 2021 Jun 2.

Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy.

Adjuvant treatment for patients with early stage colorectal cancer (eCRC) is currently based on suboptimal risk stratification, especially for elderly patients. Metabolomics may improve the identification of patients with residual micrometastases after surgery. In this retrospective study, we hypothesized that metabolomic fingerprinting could improve risk stratification in patients with eCRC. Serum samples obtained after surgery from 94 elderly patients with eCRC (65 relapse free and 29 relapsed, after 5-years median follow up), and from 75 elderly patients with metastatic colorectal cancer (mCRC) obtained before a new line of chemotherapy, were retrospectively analyzed via proton nuclear magnetic resonance spectroscopy. The prognostic role of metabolomics in patients with eCRC was assessed using Kaplan-Meier curves. PCA-CA-kNN could discriminate the metabolomic fingerprint of patients with relapse-free eCRC and mCRC (70.0% accuracy using NOESY spectra). This model was used to classify the samples of patients with relapsed eCRC: 69% of eCRC patients with relapse were predicted as metastatic. The metabolomic classification was strongly associated with prognosis (-value 0.0005, HR 3.64), independently of tumor stage. In conclusion, metabolomics could be an innovative tool to refine risk stratification in elderly patients with eCRC. Based on these results, a prospective trial aimed at improving risk stratification by metabolomic fingerprinting (LIBIMET) is ongoing.
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http://dx.doi.org/10.3390/cancers13112762DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8199587PMC
June 2021

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.

Metabolites 2021 May 18;11(5). Epub 2021 May 18.

Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Stippeneng 4, 6708 WE Wageningen, The Netherlands.

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.
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http://dx.doi.org/10.3390/metabo11050326DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8158518PMC
May 2021

Precision Oncology via NMR-Based Metabolomics: A Review on Breast Cancer.

Int J Mol Sci 2021 Apr 28;22(9). Epub 2021 Apr 28.

Magnetic Resonance Center (CERM), University of Florence, 50019 Sesto Fiorentino, Italy.

Precision oncology is an emerging approach in cancer care. It aims at selecting the optimal therapy for the right patient by considering each patient's unique disease and individual health status. In the last years, it has become evident that breast cancer is an extremely heterogeneous disease, and therefore, patients need to be appropriately stratified to maximize survival and quality of life. Gene-expression tools have already positively assisted clinical decision making by estimating the risk of recurrence and the potential benefit from adjuvant chemotherapy. However, these approaches need refinement to further reduce the proportion of patients potentially exposed to unnecessary chemotherapy. Nuclear magnetic resonance (NMR) metabolomics has demonstrated to be an optimal approach for cancer research and has provided significant results in BC, in particular for prognostic and stratification purposes. In this review, we give an update on the status of NMR-based metabolomic studies for the biochemical characterization and stratification of breast cancer patients using different biospecimens (breast tissue, blood serum/plasma, and urine).
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http://dx.doi.org/10.3390/ijms22094687DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8124948PMC
April 2021

Metabolomics of gingival crevicular fluid to identify biomarkers for periodontitis: A systematic review with meta-analysis.

J Periodontal Res 2021 Aug 12;56(4):633-645. Epub 2021 Mar 12.

Department of Surgical Sciences, C.I.R. Dental School, University of Turin, Turin, Italy.

The present systematic review aimed to examine periodontitis-specific biomarkers in the gingival crevicular fluid (GCF) that could have a diagnostic relevance, and to provide a qualitative assessment of the current literature. Metabolites are reliable indicators of pathophysiological statuses, and their quantification in the GCF can provide an outlook of the changes associated with periodontitis and have diagnostic value. Relevant studies identified from PubMed, Embase, Cochrane Library, and Scopus databases were examined to answer the following PECO question: "In systemically healthy individuals, can concentration of specific metabolites in the GCF be used to discriminate subjects with healthy periodontium (H) or gingivitis from patients with periodontitis (P) and which is the diagnostic accuracy?" Quality of included studies was rated using a modified version of the QUADOMICS tool. Meta-analysis was conducted whenever possible. After the screening of 1,554 titles, 15 studies were selected, with sample size ranging from 30 to 93 subjects. Eleven studies performed targeted metabolomics analysis and provided data for 10 metabolites. Among the most consistent markers, malondialdehyde levels were found higher in the P group compared with H group (SMD = 2.86; 95% CI: 1.64, 4.08). Also, a significant increase of 8-hydroxy-deoxyguanosine, 4-hydroxynonenal, and neopterin was detected in periodontally diseased sites, while glutathione showed an inverse trend. When considering data from untargeted metabolomic analysis in four studies, more than 40 metabolites were found significantly discriminant, mainly related to amino acids and lipids degradation pathways. Notably, only one study reported measures of diagnostic accuracy. Several metabolites were differentially expressed in GCF of subjects across different periodontal conditions, having a major potential for investigating periodontal pathophysiology and for site-specific diagnosis. Oxidative stress-related molecules, such as malondialdehyde and 8-hydroxy-deoxyguanosine, were the most consistently associated to periodontitis (PROSPERO CRD42020188482).
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http://dx.doi.org/10.1111/jre.12872DOI Listing
August 2021

Evaluation of Serum/Urine Genomic and Metabolomic Profiles to Improve the Adherence to Sildenafil Therapy in Patients with Erectile Dysfunction.

Front Pharmacol 2020 10;11:602369. Epub 2020 Dec 10.

Unit of Andrology and Reproduction Medicine-Department of Medicine, University of Padova, Padova, Italy.

Type V-phosphodiesterase-inhibitors (PDE5i) are the first choice drugs in the treatment of erectile dysfunction (ED), being effective in 60-70% of patients. However, approximately 50% of patients per year discontinue the treatment with PDE5i after reporting poor drug efficacy or major adverse drug reactions (ADR). To identify early markers of efficacy/safety for the treatment of ED with PDE5i, the basal clinical characteristics of patients, integrated with metabolomics analysis of serum and urine and genomic data, were here correlated with the PDE5i efficacy and the occurrence of ADR upon administration. Thirty-six males with new diagnosis of ED were consecutively recruited and characterized at baseline for anthropometrics, blood pressure, blood glucose, lipid profile, serum levels of thyroid/sex hormones and erectile function evaluated by IIEF-15 questionnaire. Targeted Next Generation Sequencing (NGS) was applied to genes involved in PDE5i pharmacodynamics and pharmacokinetics. Fasting metabolic profiles of serum and urine were assessed by nuclear magnetic resonance (NMR)-based metabolomics analysis. Patients were prescribed on-demand therapy with Sildenafil oro-dispersible film and followed-up after 3 months from recruitment. Baseline data were compared with IIEF-15 score at follow-up and with the occurrence of ADR recorded by a dedicated questionnaire. Twenty-eight patients were finally included in the analysis. Serum LDL-cholesterol levels were increased in those reporting ADR (143.3 ± 13.2 mg/dl ADR vs. 133.1 ± 12.4 mg/dl No ADR; = 0.046). NGS data showed that specific variants of and genes were more represented in drug responders (both relative risk = 2.7 [0.9-5.1]; = 0.04). NMR-based metabolomics showed the highest association between serum LDL-cholesterol metabolites and the occurrence of ADR (Hazard ratio = 17.5; = 0.019). The association between lipid profile and the ADR pattern suggests major cues in the tailoring of ED therapy with PDE5i.
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http://dx.doi.org/10.3389/fphar.2020.602369DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7849189PMC
December 2020

Metabolomic/lipidomic profiling of COVID-19 and individual response to tocilizumab.

PLoS Pathog 2021 02 1;17(2):e1009243. Epub 2021 Feb 1.

Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Florence, Italy.

The current pandemic emergence of novel coronavirus disease (COVID-19) poses a relevant threat to global health. SARS-CoV-2 infection is characterized by a wide range of clinical manifestations, ranging from absence of symptoms to severe forms that need intensive care treatment. Here, plasma-EDTA samples of 30 patients compared with age- and sex-matched controls were analyzed via untargeted nuclear magnetic resonance (NMR)-based metabolomics and lipidomics. With the same approach, the effect of tocilizumab administration was evaluated in a subset of patients. Despite the heterogeneity of the clinical symptoms, COVID-19 patients are characterized by common plasma metabolomic and lipidomic signatures (91.7% and 87.5% accuracy, respectively, when compared to controls). Tocilizumab treatment resulted in at least partial reversion of the metabolic alterations due to SARS-CoV-2 infection. In conclusion, NMR-based metabolomic and lipidomic profiling provides novel insights into the pathophysiological mechanism of human response to SARS-CoV-2 infection and to monitor treatment outcomes.
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http://dx.doi.org/10.1371/journal.ppat.1009243DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7877736PMC
February 2021

A geroscience approach for Parkinson's disease: Conceptual framework and design of PROPAG-AGEING project.

Mech Ageing Dev 2021 03 29;194:111426. Epub 2020 Dec 29.

Consorzio Interuniversitario Risonanze Magnetiche di Metalloproteine (CIRMMP), Florence, Italy.

Advanced age is the major risk factor for idiopathic Parkinson's disease (PD), but to date the biological relationship between PD and ageing remains elusive. Here we describe the rationale and the design of the H2020 funded project "PROPAG-AGEING", whose aim is to characterize the contribution of the ageing process to PD development. We summarize current evidences that support the existence of a continuum between ageing and PD and justify the use of a Geroscience approach to study PD. We focus in particular on the role of inflammaging, the chronic, low-grade inflammation characteristic of elderly physiology, which can propagate and transmit both locally and systemically. We then describe PROPAG-AGEING design, which is based on the multi-omic characterization of peripheral samples from clinically characterized drug-naïve and advanced PD, PD discordant twins, healthy controls and "super-controls", i.e. centenarians, who never showed clinical signs of motor disability, and their offspring. Omic results are then validated in a large number of samples, including in vitro models of dopaminergic neurons and healthy siblings of PD patients, who are at higher risk of developing PD, with the final aim of identifying the molecular perturbations that can deviate the trajectories of healthy ageing towards PD development.
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http://dx.doi.org/10.1016/j.mad.2020.111426DOI Listing
March 2021

Changes in the Salivary Metabolic Profile of Generalized Periodontitis Patients after Non-surgical Periodontal Therapy: A Metabolomic Analysis Using Nuclear Magnetic Resonance Spectroscopy.

J Clin Med 2020 Dec 8;9(12). Epub 2020 Dec 8.

Department of Surgical Sciences, C.I.R. Dental School, Section of Periodontology, University of Turin, 10126 Turin, Italy.

Pattern analysis of the salivary metabolic profile has been proven accurate in discriminating between generalized periodontitis (GP) patients and healthy individuals (HI), as this disease modifies the salivary concentrations of specific metabolites. Due to the scarcity of data from previous studies, this study aimed to evaluate if non-surgical periodontal therapy (NST) could affect the metabolomic profile in GP patients' saliva and if it compares to that of HI. Unstimulated salivary samples were collected from 11 HI and 12 GP patients before and 3 months after NST. Nuclear Magnetic Resonance (NMR) spectroscopy, followed by a supervised multivariate statistical approach on entire saliva spectra and partial least square (PLS) discriminant analysis, were performed to obtain metabolic profiles. In the GP group, periodontal treatment improved all clinical parameters, but not all the diseased sites were eradicated. PLS revealed an accuracy of 100% in distinguishing between metabolic profiles of GP patients before and after NST. Orthogonal projection to latent structure was able to discriminate between the three groups of subjects with an accuracy of 85.6%. However, the post-NST metabolic profile of GP patients could not be completely assimilated to that of HI. Although NST may produce significant changes in the metabolic profile, GP patients maintained a distinctive fingerprint compared to HI.
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http://dx.doi.org/10.3390/jcm9123977DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7763572PMC
December 2020

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

J Proteome Res 2021 01 4;20(1):1040-1051. Epub 2020 Dec 4.

Laboratory of Systems and Synthetic Biology, Wageningen University & Research, 6708 WE Wageningen, The Netherlands.

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.
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http://dx.doi.org/10.1021/acs.jproteome.0c00882DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7786375PMC
January 2021

Metabolomics: The Stethoscope for the Twenty-First Century.

Med Princ Pract 2021 3;30(4):301-310. Epub 2020 Dec 3.

Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona and CIBERHD (CIBER de Enfermedades hepáticas y digestivas), Barcelona, Spain.

Metabolomics encompasses the systematic identification and quantification of all metabolic products in the human body. This field could provide clinicians with novel sets of diagnostic biomarkers for disease states in addition to quantifying treatment response to medications at an individualized level. This literature review aims to highlight the technology underpinning metabolic profiling, identify potential applications of metabolomics in clinical practice, and discuss the translational challenges that the field faces. We searched PubMed, MEDLINE, and EMBASE for primary and secondary research articles regarding clinical applications of metabolomics. Metabolic profiling can be performed using mass spectrometry and nuclear magnetic resonance-based techniques using a variety of biological samples. This is carried out in vivo or in vitro following careful sample collection, preparation, and analysis. The potential clinical applications constitute disruptive innovations in their respective specialities, particularly oncology and metabolic medicine. Outstanding issues currently preventing widespread clinical use are scalability of data interpretation, standardization of sample handling practice, and e-infrastructure. Routine utilization of metabolomics at a patient and population level will constitute an integral part of future healthcare provision.
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http://dx.doi.org/10.1159/000513545DOI Listing
December 2020

Metabolomics to Assess Response to Immune Checkpoint Inhibitors in Patients with Non-Small-Cell Lung Cancer.

Cancers (Basel) 2020 Nov 30;12(12). Epub 2020 Nov 30.

Sandro Pitigliani, Department of Medical Oncology, Hospital of Prato, via Suor Niccolina Infermiera, 20/22, 59100 Prato, Italy.

In the treatment of advanced non-small cell lung cancer (NSCLC), immune checkpoint inhibitors have shown remarkable results. However, not all patients with NSCLC respond to this drug treatment or receive durable benefits. Thus, patient stratification and selection, as well as the identification of predictive biomarkers, represent pivotal aspects to address. In this framework, metabolomics can be used to support the discrimination between responders and non-responders. Here, metabolomics was used to analyze the sera samples from 50 patients with NSCL treated with immune checkpoint inhibitors. All the samples were collected before the beginning of the treatment and were analyzed by NMR spectroscopy and multivariate statistical analyses. Significantly, we show that the metabolomic fingerprint of serum acts as a predictive "collective" biomarker to immune checkpoint inhibitors response, being able to predict individual therapy outcome with > 80% accuracy. Metabolomics represents a potential strategy for the real-time selection and monitoring of patients treated with immunotherapy. The prospective identification of responders and non-responders could improve NSCLC treatment and patient stratification, thus avoiding ineffective therapeutic strategies.
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http://dx.doi.org/10.3390/cancers12123574DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7760033PMC
November 2020

Effects of Probiotics Administration on Human Metabolic Phenotype.

Metabolites 2020 Oct 7;10(10). Epub 2020 Oct 7.

Consorzio Interuniversitario Risonanze Magnetiche di Metallo Proteine (CIRMMP), 50019 Sesto Fiorentino, Italy.

The establishment of the beneficial interactions between the host and its microbiota is essential for the correct functioning of the organism, since microflora alterations can lead to many diseases. Probiotics improve balanced microbial communities, exerting substantial health-promoting effects. Here we monitored the molecular outcomes, obtained by gut microflora modulation through probiotic treatment, on human urine and serum metabolic profiles, with a metabolomic approach. Twenty-two subjects were enrolled in the study and administered with two different probiotic types, both singularly and in combination, for 8 weeks. Urine and serum samples were collected before and during the supplementation and were analyzed by nuclear magnetic resonance (NMR) spectroscopy and statistical analyses. After eight weeks of treatment, probiotics deeply influence the urinary metabolic profiles of the volunteers, without significantly altering their single phenotypes. Anyway, bacteria supplementation tends to reduce the differences in metabolic phenotypes among individuals. Overall, the effects are recipient-dependent, and in some individuals, robust effects are already well visible after four weeks. Modifications in metabolite levels, attributable to each type of probiotic administration, were also monitored. Metabolomic analysis of biofluids turns out to be a powerful technique to monitor the dynamic interactions between the microflora and the host, and the individual response to probiotic assumption.
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http://dx.doi.org/10.3390/metabo10100396DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7601401PMC
October 2020

Manipulation of Dietary Amino Acids Prevents and Reverses Obesity in Mice Through Multiple Mechanisms That Modulate Energy Homeostasis.

Diabetes 2020 11 10;69(11):2324-2339. Epub 2020 Aug 10.

Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN.

Reduced activation of energy metabolism increases adiposity in humans and other mammals. Thus, exploring dietary and molecular mechanisms able to improve energy metabolism is of paramount medical importance because such mechanisms can be leveraged as a therapy for obesity and related disorders. Here, we show that a designer protein-deprived diet enriched in free essential amino acids can ) promote the brown fat thermogenic program and fatty acid oxidation, ) stimulate uncoupling protein 1 (UCP1)-independent respiration in subcutaneous white fat, ) change the gut microbiota composition, and ) prevent and reverse obesity and dysregulated glucose homeostasis in multiple mouse models, prolonging the healthy life span. These effects are independent of unbalanced amino acid ratio, energy consumption, and intestinal calorie absorption. A brown fat-specific activation of the mechanistic target of rapamycin complex 1 seems involved in the diet-induced beneficial effects, as also strengthened by in vitro experiments. Hence, our results suggest that brown and white fat may be targets of specific amino acids to control UCP1-dependent and -independent thermogenesis, thereby contributing to the improvement of metabolic health.
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http://dx.doi.org/10.2337/db20-0489DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7576563PMC
November 2020

Metabolomics profile in gastrointestinal cancers: Update and future perspectives.

World J Gastroenterol 2020 May;26(20):2514-2532

Consorzio Interuniversitario Risonanze Magnetiche di Metalloproteine, Florence 50019, Italy.

Despite recent progress in diagnosis and therapy, gastrointestinal (GI) cancers remain one of the most important causes of death with a poor prognosis due to late diagnosis. Serum tumor markers and detection of occult blood in the stool are the current tests used in the clinic of GI cancers; however, these tests are not useful as diagnostic screening since they have low specificity and low sensitivity. Considering that one of the hallmarks of cancer is dysregulated metabolism and metabolomics is an optimal approach to illustrate the metabolic mechanisms that belong to living systems, is now clear that this -omics could open a new way to study cancer. In the last years, nuclear magnetic resonance (NMR) metabolomics has demonstrated to be an optimal approach for diseases' diagnosis nevertheless a few studies focus on the NMR capability to find new biomarkers for early diagnosis of GI cancers. For these reasons in this review, we will give an update on the status of NMR metabolomic studies for the diagnosis and development of GI cancers using biological fluids.
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http://dx.doi.org/10.3748/wjg.v26.i20.2514DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7265149PMC
May 2020

Nuclear Magnetic Resonance-Based Metabolomic Comparison of Breast Milk and Organic and Traditional Formula Milk Brands for Infants and Toddlers.

OMICS 2020 07 9;24(7):424-436. Epub 2020 Jun 9.

Centro Risonanze Magnetiche (CERM) and Department of Chemistry, University of Florence, Florence, Italy.

In recent years, new formula milk (FM) products based on milk from farms that strictly adhere to the "organic farming" practices became available. However, little is known about the differences in nutritional profile of these organic formulae with respect to traditional ones. We comprehensively evaluated the metabolite profiles of FM with nuclear magnetic resonance (NMR)-based metabolomic analysis. Five commercial brands of organic and nonorganic formula liquid milk for infants (0-12 months) and toddlers (1-3 years) were analyzed, together with human milk (HM) samples. Proton NMR (H NMR) spectroscopy mapped molecular characteristics of FM linked to different production techniques, and identified differences between FM and HM samples. We performed a metabolic fingerprint analysis using multivariate and univariate statistical techniques. A clear distinction is found among different commercial brands of the FM samples. In addition, several differences in metabolomic profiles of FM have been found in comparison with HM for the first time. Notably, it was possible to identify, both in the formulations for toddlers and for infants, metabolites that vary in concentration between the formulae produced with milk obtained according to organic farming techniques, and those produced using nonorganic milk. In particular, organic and nonorganic formulations are differentiated by the levels of glucose, methionine, -phosphocholine, butyrate, hippurate, creatine, and dimethyl sulfone. Importantly, the HM appeared to differ from both organic and nonorganic brands in a context of metabolites. These findings inform efforts to design FM in ways that closely mimic HM, and guide research to differentiate organic and traditional FM.
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http://dx.doi.org/10.1089/omi.2019.0125DOI Listing
July 2020

Fingerprinting Alzheimer's Disease by H Nuclear Magnetic Resonance Spectroscopy of Cerebrospinal Fluid.

J Proteome Res 2020 04 12;19(4):1696-1705. Epub 2020 Mar 12.

Laboratory of Clinical Neurochemistry, Department of Medicine, Section of Neurology, University of Perugia, Perugia 06123, Italy.

In this study, we sought for a cerebrospinal fluid (CSF) metabolomic fingerprint in Alzheimer's disease (AD) patients characterized, according to the clinical picture and CSF AD core biomarkers (Aβ, p-tau, and t-tau), both at pre-dementia (mild cognitive impairment due to AD, MCI-AD) and dementia stages (ADdem) and in a group of patients with a normal CSF biomarker profile (non-AD) using untargeted H nuclear magnetic resonance (NMR) spectroscopy-based metabolomics. This is a retrospective study based on two independent cohorts: a Dutch cohort, which comprises 20 ADdem, 20 MCI-AD, and 20 non-AD patients, and an Italian cohort, constituted by 14 ADdem and 12 non-AD patients. H NMR CSF spectra were analyzed using OPLS-DA. Metabolomic fingerprinting in the Dutch cohort provides a significant discrimination (86.1% accuracy) between ADdem and non-AD. MCI-AD patients show a good discrimination with respect to ADdem (70.0% accuracy) but only slight differences when compared with non-AD (59.6% accuracy). Acetate, valine, and 3-hydroxyisovalerate result to be altered in ADdem patients. Valine correlates with cognitive decline at follow-up ( = 0.53, = 0.0011). The discrimination between ADdem and non-AD was confirmed in the Italian cohort. The CSF metabolomic fingerprinting shows a signature characteristic of ADdem patients with respect to MCI-AD and non-AD patients.
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http://dx.doi.org/10.1021/acs.jproteome.9b00850DOI Listing
April 2020

Multivariate Curve Resolution for 2D Solid-State NMR spectra.

Anal Chem 2020 03 3;92(6):4451-4458. Epub 2020 Mar 3.

Magnetic Resonance Center (CERM), University of Florence, and Consorzio Interuniversitario Risonanze Magnetiche di Metalloproteine (CIRMMP), via L. Sacconi 6, 50019 Sesto Fiorentino, Italy.

We present a processing method, based on the multivariate curve resolution approach (MCR), to denoise 2D solid-state NMR spectra, yielding a substantial S/N ratio increase while preserving the lineshapes and relative signal intensities. These spectral features are particularly important in the quantification of silicon species, where sensitivity is limited by the low natural abundance of the Si nuclei and by the dilution of the intrinsic protons of silica, but can be of interest also when dealing with other intermediate-to-low receptivity nuclei. This method also offers the possibility of coprocessing multiple 2D spectra that have the signals at the same frequencies but with different intensities (e.g.: as a result of a variation in the mixing time). The processing can be carried out on the time-domain data, thus preserving the possibility of applying further processing to the data. As a demonstration, we have applied Cadzow denoising on the MCR-processed FIDs, achieving a further increase in the S/N ratio and more effective denoising also on the transients at longer indirect evolution times. We have applied the combined denoising on a set of experimental data from a lysozyme-silica composite.
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http://dx.doi.org/10.1021/acs.analchem.9b05420DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7997113PMC
March 2020

The inner temperature of the olives (cv. Leccino) before processing affects the volatile profile and the composition of the oil.

Food Res Int 2020 03 2;129:108861. Epub 2019 Dec 2.

Institute of Life Sciences, Scuola Superiore Sant'Anna, Piazza Martiri della Libertà 33, 56127 Pisa, Italy. Electronic address:

The effects of pre-processing decreasing temperature (19, 15 and 10 °C) of olive fruit (cv. Leccino) harvested at three developmental stages (semi-ripe, ripe, advanced ripening) have been evaluated on oil in terms of basic quality parameters, composition, organoleptic traits, and aroma profiles. A total of 40 metabolites (volatiles and non-volatiles) were identified by H NMR and GC/MS analyses. Multivariate statistical analysis showed that samples obtained from ripe and advanced ripe olives cooled at 10 and 15 °C better correlated with C6 aldehydes, mainly associated with herbal/green olfactory traits. Compounds responsible for sweet/fruity traits were more abundantly present in oil extracted from 19 °C olive samples. Decreasing pulp temperature before crushing also resulted in reduced presence of 1-penten-3-ol, 1-penten-3-one, acetic acid and ethyl alcohol, associated with specific defects of the oil. Results indicate that slightly lowering fruit temperature just before crushing modulates oil composition by reducing oil off flavours while enhancing green and fresh attributes in particular when ripe olives are processed.
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http://dx.doi.org/10.1016/j.foodres.2019.108861DOI Listing
March 2020

Effect of Estrogen Receptor Status on Circulatory Immune and Metabolomics Profiles of HER2-Positive Breast Cancer Patients Enrolled for Neoadjuvant Targeted Chemotherapy.

Cancers (Basel) 2020 Jan 29;12(2). Epub 2020 Jan 29.

Immunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy.

HER2-positive breast cancer (BC) represents a heterogeneous cancer disease. In an attempt to identify new stratification models useful for prognosis and therapeutic strategy, we investigated the influence of estrogen receptor (ER) status on the host immune and metabolomics profile of HER2-positive BC patients enrolled for neoadjuvant targeted chemotherapy (NATC). The study enrolled 43 HER2-positive BC patients eligible for NATC based on the trastuzumab-paclitaxel combination. Baseline circulatory cytokines and H NMR plasma metabolomics profiles were investigated. Differences in the immune cytokines and metabolomics profile as a function of the ER status, and their association with clinical outcomes were studied by multivariate and univariate analysis. Baseline metabolomics profiles were found to discriminate HER2-positive ER(+) from ER(-) BC patients. Within the ER(+) group an immune-metabolomics model, based on TNF-α and valine, predicted pathological complete response to NATC with 90.9% accuracy (AUROC = 0.92, = 0.004). Moreover, metabolomics information integrated with IL-2 and IL-10 cytokine levels were prognostic of relapse with an accuracy of 95.5%. The results indicate that in HER2-positive BC patients the ER status influences the host circulatory immune-metabolomics profile. The baseline immune-metabolomics assessment in combination with ER status could represent an independent stratification tool able to predict NATC response and disease relapse of HER2-positive patients.
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http://dx.doi.org/10.3390/cancers12020314DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7072610PMC
January 2020

Differential Network Analysis Reveals Metabolic Determinants Associated with Mortality in Acute Myocardial Infarction Patients and Suggests Potential Mechanisms Underlying Different Clinical Scores Used To Predict Death.

J Proteome Res 2020 02 17;19(2):949-961. Epub 2020 Jan 17.

Laboratory of Systems and Synthetic Biology , Wageningen University & Research , Wageningen 6708 WE , the Netherlands.

We present here the differential analysis of metabolite-metabolite association networks constructed from an array of 24 serum metabolites identified and quantified via nuclear magnetic resonance spectroscopy in a cohort of 825 patients of which 123 died within 2 years from acute myocardial infarction (AMI). We investigated differences in metabolite connectivity of patients who survived, at 2 years, the AMI event, and we characterized metabolite-metabolite association networks specific to high and low risks of death according to four different risk parameters, namely, acute coronary syndrome classification, Killip, Global Registry of Acute Coronary Events risk score, and metabolomics NOESY RF risk score. We show significant differences in the connectivity patterns of several low-molecular-weight molecules, implying variations in the regulation of several metabolic pathways regarding branched-chain amino acids, alanine, creatinine, mannose, ketone bodies, and energetic metabolism. Our results demonstrate that the characterization of metabolite-metabolite association networks is a promising and powerful tool to investigate AMI patients according to their outcomes at a molecular level.
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http://dx.doi.org/10.1021/acs.jproteome.9b00779DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7011173PMC
February 2020

DHA-Induced Perturbation of Human Serum Metabolome. Role of the Food Matrix and Co-Administration of Oat β-glucan and Anthocyanins.

Nutrients 2019 Dec 27;12(1). Epub 2019 Dec 27.

Department of Agricultural and Food Sciences, Alma Mater Studiorum University of Bologna, Piazza G. Goidanich, 60, 47521 Cesena (FC), Italy.

Docosahexaenoic acid (DHA) has been reported to have a positive impact on many diet-related disease risks, including metabolic syndrome. Although many DHA-enriched foods have been marketed, the impact of different food matrices on the effect of DHA is unknown. As well, the possibility to enhance DHA effectiveness through the co-administration of other bioactives has seldom been considered. We evaluated DHA effects on the serum metabolome administered to volunteers at risk of metabolic syndrome as an ingredient of three different foods. Foods were enriched with DHA alone or in combination with oat beta-glucan or anthocyanins and were administered to volunteers for 4 weeks. Serum samples collected at the beginning and end of the trial were analysed by NMR-based metabolomics. Multivariate and univariate statistical analyses were used to characterize modifications in the serum metabolome and to evaluate bioactive-bioactive and bioactive-food matrix interactions. DHA administration induces metabolome perturbation that is influenced by the food matrix and the co-presence of other bioactives. In particular, when co-administered with oat beta-glucan, DHA induces a strong rearrangement in the lipoprotein profile of the subjects. The observed modifications are consistent with clinical results and indicate that metabolomics represents a possible strategy to choose the most appropriate food matrices for bioactive enrichment.
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http://dx.doi.org/10.3390/nu12010086DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7019822PMC
December 2019

Nuclear magnetic resonance (NMR)-based metabolome profile evaluation in dairy cows with and without displaced abomasum.

Vet Q 2020 Dec;40(1):1-15

Department of Internal Medicine, Faculty of Veterinary Medicine, Selcuk University, Selcuklu, Konya, Turkey.

Displaced abomasum (DA) is a condition of dairy cows that severely impacts animal welfare and causes huge economic losses. To assess the metabolic status of the disease using metabolomics in serum, urine and liver samples aimed at both water soluble and lipid soluble fractions. Fifty Holstein multiparous cows with DA (42 left, 8 right) and 20 clinically healthy Holstein multiparous cows were used. Left DA was associated with concomitant ketosis in 19 animals and right in two. NMR-based metabolomics approach and hematological and biochemical analyses were performed. Statistical analysis was carried out on H-NMR data after they have been normalized using PQN method. Contrary to generated PCA score plots the OPLS-supervised method revealed differences between healthy animals and diseased ones based on serum water-soluble samples. While water and lipid soluble metabolites decreased in serum samples, fatty acid fractions and cholesterol were increased in liver samples in DA affected cows. The metabolomic and chemical profiles clearly revealed that cows with DA (especially with LDA) were at risk of ketosis and fatty liver. Serum hippuric acid concentration was significantly higher in healthy cows in comparison with LDA, whereas serum glycine concentration was reported higher for healthy when compared to RDA affected animals. A biochemical network and pathway mapping revealed 'valine, leucine and isoleucine biosynthesis' and 'phenylalanine, tyrosine and tryptophan biosynthesis' as the most probable altered metabolic pathway in DA condition. Serum was advocated as the optimal biological matrix for the H-NMR analysis.
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http://dx.doi.org/10.1080/01652176.2019.1707907DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6968509PMC
December 2020

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

J Proteome Res 2020 01 7;19(1):64-74. Epub 2019 Nov 7.

Department of Pharmacology, Faculty of Medicine, Catholic University of the Sacred Heart, Largo F. Vito, 1, Rome, Italy 00168

The aim of this proof-of-concept, pilot study was the evaluation of the effects of steroid administration and suspension of an inhaled corticosteroid (ICS)-long-acting β-agonist (LABA) extrafine fixed dose combination (FDC) on metabolomic fingerprints in subjects with chronic obstructive pulmonary disease (COPD). We hypothesized that a comprehensive metabolomics approach discriminates across inhaled pharmacotherapies and that their effects on metabolomic signatures depend on the biological fluids analyzed. We performed metabolomics via nuclear magnetic resonance (NMR) spectroscopy in exhaled breath condensate (EBC), sputum supernatants, serum, and urine. Fourteen patients suffering from COPD who were on regular inhaled fluticasone propionate/salmeterol therapy (visit 1) were consecutively treated with 2-week beclomethasone dipropionate/formoterol (visit 2), 4-week formoterol alone (visit 3), and 4-week beclomethasone/formoterol (visit 4). The comprehensive NMR-based metabolomics approach showed differences across all pharmacotherapies and that different biofluids provided orthogonal information. Serum formate was lower at visits 1 versus 3 ( = 0.03), EBC formate was higher at visit 1 versus 4 ( = 0.03), and urinary 1-methyl-nicotinamide was lower at 3 versus 4 visit ( = 0.002). NMR-based metabolomics of different biofluids distinguishes across inhaled pharmacotherapies, provides complementary information on the effects of an extrafine ICS/LABA FDC on metabolic fingerprints in COPD patients, and might be useful for elucidating the ICS mechanism of action.
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http://dx.doi.org/10.1021/acs.jproteome.9b00345DOI Listing
January 2020

Metabolomic analysis of serum may refine 21-gene expression assay risk recurrence stratification.

NPJ Breast Cancer 2019 29;5:26. Epub 2019 Aug 29.

"Sandro Pitigliani" Department of Medical Oncology, Prato Hospital, Via Suor Niccolina 20, Prato, Italy.

Despite recent refinements to the 21-gene g score, allowing a better identification of patients who may derive no benefit from the addition of adjuvant chemotherapy to that of endocrine therapy, patients with early breast cancer still stand to be over-treated in the setting of clinical and/or genomic uncertainty or discordance. Here we describe and demonstrate a potential approach of further refining the OncotypeDX risk score by metabolomic analysis of serum. In a clinical dataset ( = 87), the risk of recurrence was further sub-stratified by metabolomic signature, with an effective splitting of each Oncotype risk classification. A total of seven recurrences were recorded, with metabolomic analysis accurately predicting six of these. Contrastingly, the genomic risk score of the seven recurrences ranged across all three Oncotype classifications (one recurrence occurred in the "low"-risk group, three in the "intermediate" group and three in the "high"-risk group).
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http://dx.doi.org/10.1038/s41523-019-0123-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6715716PMC
August 2019

Fast and Quantitative NMR Metabolite Analysis Afforded by a Paramagnetic Co-Solute.

Angew Chem Int Ed Engl 2019 10 11;58(43):15283-15286. Epub 2019 Sep 11.

Magnetic Resonance Center (CERM), University of Florence, Via L. Sacconi 6, 50019, Sesto Fiorentino (FI), Italy.

NMR spectroscopy is an indispensable technique for the determination of the chemical identity and structure of small molecules. The method is especially recognized for its robustness and intrinsically quantitative nature, and has manifested itself as a key analytical platform for diverse fields of application, ranging from chemical synthesis to metabolomics. Unfortunately, the slow recovery of nuclear spin polarization by spin-lattice (T ) relaxation causes most experimental time to be lost on idle waiting. Furthermore, truly quantitative NMR (qNMR) spectroscopy requires waiting times of 5-times the longest T in the sample, making qNMR spectroscopy slow and inefficient. We demonstrate here that co-solute paramagnetic relaxation can mitigate these two problems simultaneously. The addition of a small amount of paramagnetic gadolinium chelate, available in the form of commercial contrast-agent solutions, enables cheap, quantitative, and efficient high-throughput mixture analysis.
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http://dx.doi.org/10.1002/anie.201908006DOI Listing
October 2019

NMR Spectroscopy for Metabolomics Research.

Metabolites 2019 Jun 27;9(7). Epub 2019 Jun 27.

Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E8, Canada.

Over the past two decades, nuclear magnetic resonance (NMR) has emerged as one of the three principal analytical techniques used in metabolomics (the other two being gas chromatography coupled to mass spectrometry (GC-MS) and liquid chromatography coupled with single-stage mass spectrometry (LC-MS)). The relative ease of sample preparation, the ability to quantify metabolite levels, the high level of experimental reproducibility, and the inherently nondestructive nature of NMR spectroscopy have made it the preferred platform for long-term or large-scale clinical metabolomic studies. These advantages, however, are often outweighed by the fact that most other analytical techniques, including both LC-MS and GC-MS, are inherently more sensitive than NMR, with lower limits of detection typically being 10 to 100 times better. This review is intended to introduce readers to the field of NMR-based metabolomics and to highlight both the advantages and disadvantages of NMR spectroscopy for metabolomic studies. It will also explore some of the unique strengths of NMR-based metabolomics, particularly with regard to isotope selection/detection, mixture deconvolution via 2D spectroscopy, automation, and the ability to noninvasively analyze native tissue specimens. Finally, this review will highlight a number of emerging NMR techniques and technologies that are being used to strengthen its utility and overcome its inherent limitations in metabolomic applications.
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http://dx.doi.org/10.3390/metabo9070123DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6680826PMC
June 2019

The metabolic fingerprints of HCV and HBV infections studied by Nuclear Magnetic Resonance Spectroscopy.

Sci Rep 2019 03 11;9(1):4128. Epub 2019 Mar 11.

Careggi University Hospital, Department of Experimental and Clinical Medicine, Interdepartmental Center for Systemic Manifestations of Hepatitis Viruses (MaSVE), Florence, 50134, Italy.

Few studies are available on metabolic changes in liver injuries and this is the first metabolomic study evaluating a group of HCV-positive patients, before and after viral eradication via DAA IFN-free regimens, using H-NMR to characterize and compare their serum fingerprints to naïve HBV-patients and healthy donors. The investigation clearly shows differences in the metabolomic profile of HCV patients before and after effective DAA treatment. Significant changes in metabolites levels in patients undergoing therapy suggest alterations in several metabolic pathways. It has been shown that H-NMR fingerprinting approach is an optimal technique in predicting the specific infection and the healthy status of studied subjects (Monte-Carlo cross validated accuracies: 86% in the HCV vs HBV model, 98.7% in the HCV vs HC model). Metabolite data collected support the hypothesis that the HCV virus induces glycolysis over oxidative phosphorylation in a similar manner to the Warburg effect in cancer, moreover our results have demonstrated a different action of the two viruses on cellular metabolism, corroborating the hypothesis that the metabolic perturbation on patients could be attributed to a direct role in viral infection. This metabolomic study has revealed some alteration in metabolites for the first time (2-oxoglutarate and 3-hydroxybutrate) concerning the HCV-infection model that could explain several extrahepatic manifestations associated with such an infection.
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http://dx.doi.org/10.1038/s41598-019-40028-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6412048PMC
March 2019

NMR-based metabolomics identifies patients at high risk of death within two years after acute myocardial infarction in the AMI-Florence II cohort.

BMC Med 2019 01 7;17(1). Epub 2019 Jan 7.

Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy.

Background: Risk stratification and management of acute myocardial infarction patients continue to be challenging despite considerable efforts made in the last decades by many clinicians and researchers. The aim of this study was to investigate the metabolomic fingerprint of acute myocardial infarction using nuclear magnetic resonance spectroscopy on patient serum samples and to evaluate the possible role of metabolomics in the prognostic stratification of acute myocardial infarction patients.

Methods: In total, 978 acute myocardial infarction patients were enrolled in this study; of these, 146 died and 832 survived during 2 years of follow-up after the acute myocardial infarction. Serum samples were analyzed via high-resolution H-nuclear magnetic resonance spectroscopy and the spectra were used to characterize the metabolic fingerprint of patients. Multivariate statistics were used to create a prognostic model for the prediction of death within 2 years after the cardiovascular event.

Results: In the training set, metabolomics showed significant differential clustering of the two outcomes cohorts. A prognostic risk model predicted death with 76.9% sensitivity, 79.5% specificity, and 78.2% accuracy, and an area under the receiver operating characteristics curve of 0.859. These results were reproduced in the validation set, obtaining 72.6% sensitivity, 72.6% specificity, and 72.6% accuracy. Cox models were used to compare the known prognostic factors (for example, Global Registry of Acute Coronary Events score, age, sex, Killip class) with the metabolomic random forest risk score. In the univariate analysis, many prognostic factors were statistically associated with the outcomes; among them, the random forest score calculated from the nuclear magnetic resonance data showed a statistically relevant hazard ratio of 6.45 (p = 2.16×10). Moreover, in the multivariate regression only age, dyslipidemia, previous cerebrovascular disease, Killip class, and random forest score remained statistically significant, demonstrating their independence from the other variables.

Conclusions: For the first time, metabolomic profiling technologies were used to discriminate between patients with different outcomes after an acute myocardial infarction. These technologies seem to be a valid and accurate addition to standard stratification based on clinical and biohumoral parameters.
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http://dx.doi.org/10.1186/s12916-018-1240-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6323789PMC
January 2019
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