Longitudinal serum metabolomics evaluation of trastuzumab and everolimus combination as pre-operative treatment for HER-2 positive breast cancer patients

Serum metabolite and metal ions profiles for breast cancer screening

Enhancing early-stage breast cancer detection requires integrating additional screening methods with current diagnostic imaging. Omics screening, using easily collectible serum samples, could serve as an initial step. Alongside biomarker identification capabilities, omics analysis allows for a comprehensive analysis of prevalent histological types-DCIS and IDC. Employing metabolomics, metallomics, and machine learning, could yield accurate screening models with valuable insights into organism responses. Serum samples of confirmed breast cancer patients were utilized to analyze metabolite and metal ion profiles, using two distinct analysis methods, proton NMR for metabolomics and ICP-OES for metallomics. The resulting responses were then subjected to discriminant analysis, progression biomarker exploration, examination of correlations between patients' metabolites and metal ions, and the impact of age and menopause status. Measured NMR spectra and metabolite relative integrals were used to achieve statistically significant discrimination through MVA between breast cancer and control groups. The analysis identified 24 metabolites and 4 metal ions crucial for discrimination. Furthermore, four metabolites were associated with disease progression. Additionally, there were important correlations and relationships between metabolite relative integrals, metal ion concentrations, and age/menopausal status subgroups. Quantified relative integrals allowed for discrimination between studied subgroups, validated with a holdout set. Feature importance and statistical analysis for metabolomics and metallomics extracted a set of common entities which in combination provides valuable insights into ongoing molecular disturbances and disease progression.

Metabolomics assisted by transcriptomics analysis to reveal metabolic characteristics and potential biomarkers associated with treatment response of neoadjuvant therapy with TCbHP regimen in HER2 + breast cancer

BACKGROUND

This study aimed to explore potential indicators associated with the neoadjuvant efficacy of TCbHP regimen (taxane, carboplatin, trastuzumab, and pertuzumab) in HER2 + breast cancer (BrCa) patients.

METHODS

A total of 120 plasma samples from 40 patients with HER2 + BrCa were prospectively collected at three treatment times of neoadjuvant therapy (NAT) with TCbHP regimen. Serum metabolites were analyzed based on LC-MS and GC-MS data. Random forest was used to establish predictive models based on pre-therapeutic differentially expressed metabolites. Time series analysis was used to obtain potential monitors for treatment response. Transcriptome analysis was performed in nine available pre‑therapeutic specimens of core needle biopsies. Integrated analyses of metabolomics and transcriptomics were also performed in these nine patients. qRT-PCR was used to detect altered genes in trastuzumab-sensitive and trastuzumab-resistant cell lines.

RESULTS

Twenty-one patients achieved pCR, and 19 patients achieved non-pCR. There were significant differences in plasma metabolic profiles before and during treatment. A total of 100 differential metabolites were identified between pCR patients and non-pCR patients at baseline; these metabolites were markedly enriched in 40 metabolic pathways. The area under the curve (AUC) values for discriminating the pCR and non-PCR groups from the NAT of the single potential metabolite [sophorose, N-(2-acetamido) iminodiacetic acid, taurine and 6-hydroxy-2-aminohexanoic acid] or combined panel of these metabolites were greater than 0.910. Eighteen metabolites exhibited potential for monitoring efficacy. Several validated genes might be associated with trastuzumab resistance. Thirty-nine altered pathways were found to be abnormally expressed at both the transcriptional and metabolic levels.

CONCLUSION

Serum-metabolomics could be used as a powerful tool for exploring informative biomarkers for predicting or monitoring treatment efficacy. Metabolomics integrated with transcriptomics analysis could assist in obtaining new insights into biochemical pathophysiology and might facilitate the development of new treatment targets for insensitive patients.

Trastuzumab-Mediated Cardiotoxicity and Its Preventive Intervention by Zingerone through Antioxidant and Inflammatory Pathway in Rats

Trastuzumab (TZB) is a new medicine, used to treat cancers of the breast and stomach. However, the cardiotoxic potential of this drug edges out its clinical advantages. The present study was designed to find out the effect of zingerone against trastuzumab-mediated cardiotoxicity in rats. In this study, five groups of rats with eight animals in each group were used. Group 1 was treated with normal saline, as a normal control (NC); Group 2 was treated with TZB (6 mg/kg/week-for five weeks) intraperitoneally as a toxic control. Groups 3 and 4 were pre-treated with zingerone (50 and 100 mg/kg, as per their body weight orally) along with five doses of TZB for five weeks, and Group 5 was treated with zingerone (100 mg/kg, body weight orally) as a control. TZB treatment showed cardiotoxicity as evidenced by increased levels of aspartate aminotransferase (AST), creatine kinase-myocardial band (CK-MB), lactate dehydrogenase (LDH), and lipid peroxidation (LPO) and decreased level of glutathione (GSH), and antioxidant enzymes such as glutathione peroxidase (GPx), glutathione reductase (GR), glutathione-s- transferase (GST), catalase (CAT), and superoxide dismutase (SOD) activities. Zingerone pre-treatment significantly decreased the levels of AST, CK-MB, LDH, and LPO and increased GSH and antioxidant enzymes content toward their normal level. In the TZB-alone administered group, inflammatory cytokines (IL-2 and TNF-α) levels were also elevated. Pre-treatment with zingerone restored the level of IL-2 and TNF-α toward normal level. The current findings undoubtedly demonstrated zingerone's cardioprotective nature against TZB-mediated cardiotoxicity in rats with the evidence of histopathological recall.

Blood metabolomes as non-invasive biomarkers and targets of metabolic interventions for doxorubicin and trastuzumab-induced cardiotoxicity

This study aimed to identify the alterations of blood metabolome levels and their association with cardiac dysfunction and cardiac injury following treatment with doxorubicin and trastuzumab. Eight-week-old male Wistar rats were divided into four groups (n = 6 per group) to receive intraperitoneal injection with either: (1) 1 mL of normal saline solution (NSS) at days 0, 4, 8, 15, 22, and 29 (control group for doxorubicin); (2) 3 mg/kg/day of doxorubicin at days 0, 4, 8, 15, 22, and 29 (doxorubicin group); (3) 1 mL of NSS at days 0-6 (control group for trastuzumab); or (4) 4 mg/kg/day of trastuzumab at days 0-6 (trastuzumab group). Four days after the last injected dose, cardiac function was determined. The rats were then euthanized to collect venous blood and the heart for the quantification of 107 serum and 100 cardiac metabolomes using mass spectrometry-based targeted metabolomics. We observed strong relationships between 72 cardiac versus 61 serum metabolomes in doxorubicin and trastuzumab groups. Moreover, significant correlations between cardiac function and the cardiac injury biomarker versus 28 and 58 serum metabolomes were revealed in doxorubicin and trastuzumab-treated rats, respectively. Interestingly, the patterns of both serum and cardiac metabolome alterations differed between doxorubicin and trastuzumab groups. Our findings emphasize the potential role of the constituents of the blood metabolome as non-invasive biomarkers to assess severity and prognosis of heart failure induced by doxorubicin and trastuzumab. These findings may contribute to the development of metabolic-targeted therapy specific for cardioprotection during different phases of cancer treatment.

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.

Could allicin alleviate trastuzumab-induced cardiotoxicity in a rat model through antioxidant, anti-inflammatory, and antihyperlipidemic properties?

AIMS

Although trastuzumab (TZB)-induced cardiotoxicity is well documented and allicin (one of the main active garlic ingredients) has ameliorating effects against numerous causes of toxicities; however, the influence of allicin on TZB-induced cardiotoxicity has not been investigated yet. Therefore, the current work explored the potential cardioprotective structural, biochemical, and molecular mechanisms of allicin against TZB-induced cardiotoxicity in a rat's model.

METHODS

Forty rats were divided into four equal groups and treated for five weeks. The control group (G1) received PBS, the allicin group (G2) received allicin (9 mg/kg/day), the TZB group (G3) received TZB (6 mg/kg/week), and the allicin+TZB group (G4) received 9 mg of allicin/kg/day +6 mg of TZB/kg/week. Heart specimens and blood samples were processed for histopathological, immunohistochemical, biochemical, and molecular investigations to determine the extent of cardiac injury in all groups.

KEY FINDINGS

The myocardium of G3 revealed significant increases in the numbers of inflammatory and apoptotic cells and the area percentage of collagen fibers and TNF-α immunoexpression compared with G1 and G2. Besides, qRT-PCR analysis exhibited significant reductions of SOD3, GPX1, and CAT expressions with significant increases in TNFα, IL-1β, IL-6, cTnI, cTnT, and LDH expressions. Additionally, flow cytometry analysis demonstrated a significant elevation in the apoptotic and ROS levels. In contrast, allicin+TZB cotherapy in G4 ameliorated all previous changes compared with G3.

SIGNIFICANCE

The current study proves that allicin could be used as a novel supplementary cardioprotective therapy to avoid TZB-induced cardiotoxicity via its anti-inflammatory, antifibrotic, antioxidant, antihyperlipidemic, and antiapoptotic properties.

Predicting dynamic response to neoadjuvant chemotherapy in breast cancer: a novel metabolomics approach

Neoadjuvant chemotherapy (NACT) outcomes vary according to breast cancer (BC) subtype. Since pathologic complete response is one of the most important target endpoints of NACT, further investigation of NACT outcomes in BC is crucial. Thus, identifying sensitive and specific predictors of treatment response for each phenotype would enable early detection of chemoresistance and residual disease, decreasing exposures to ineffective therapies and enhancing overall survival rates. We used liquid chromatography−high‐resolution mass spectrometry (LC‐HRMS)‐based untargeted metabolomics to detect molecular changes in plasma of three different BC subtypes following the same NACT regimen, with the aim of searching for potential predictors of response. The metabolomics data set was analyzed by combining univariate and multivariate statistical strategies. By using ANOVA–simultaneous component analysis (ASCA), we were able to determine the prognostic value of potential biomarker candidates of response to NACT in the triple‐negative (TN) subtype. Higher concentrations of docosahexaenoic acid and secondary bile acids were found at basal and presurgery samples, respectively, in the responders group. In addition, the glycohyocholic and glycodeoxycholic acids were able to classify TN patients according to response to treatment and overall survival with an area under the curve model > 0.77. In relation to luminal B (LB) and HER2+ subjects, it should be noted that significant differences were related to time and individual factors. Specifically, tryptophan was identified to be decreased over time in HER2+ patients, whereas LysoPE (22:6) appeared to be increased, but could not be associated with response to NACT. Therefore, the combination of untargeted‐based metabolomics along with longitudinal statistical approaches may represent a very useful tool for the improvement of treatment and in administering a more personalized BC follow‐up in the clinical practice.

A phase II randomised study of preoperative trastuzumab alone or combined with everolimus in patients with early HER2-positive breast cancer and predictive biomarkers (RADHER trial)

INTRODUCTION

Resistance to trastuzumab in breast cancer is an ongoing challenge. Clinical and biological effects of co-targeting HER2 and mammalian target of rapamycin (mTOR) in patients with HER2-positive early operable breast cancer via the addition of everolimus to preoperative trastuzumab were evaluated in a phase II randomised study.

METHODS

Patients were randomised 1:1 to receive trastuzumab (4 mg/kg initial dose then 2 mg/kg weekly for 5 weeks) alone or combined with everolimus (10 mg/day for 6 weeks) and then underwent surgery. Tumours were assessed by clinical examination and echography at the baseline and on treatment. The primary end-point was the clinical response rate at 6 weeks. Pathological response and safety were also evaluated. Baseline and surgery tumour samples were assessed by immunohistochemistry and multiplex immunoanalysis for predictive downstream effectors of the PI3K/AKT/mTOR and MAP kinase (MAPK) pathways.

RESULTS

Eighty-two patients were enrolled, 41 per arm. The clinical response rates were 34.1% and 43.9% with trastuzumab alone and combined with everolimus, respectively. Pathological response rates were 43.6% and 47.5%, respectively. Addition of everolimus increased toxicity, notably mucositis (82.5% versus 5.0%) and rash (57.5% versus 10.0%), but grade III/IV events were rare. No correlation between response to treatments and baseline candidate biomarkers was identified, except for PIK3CA mutations which were found to predict trastuzumab resistance. Significant changes were seen in several MAPK pathway effectors after combination therapy.

CONCLUSIONS

The addition of everolimus did not improve the efficacy, but induced MAPK signalling. Combination therapy to overcome pathway cross-talk should be considered to maximise the effectiveness of trastuzumab in this setting. ClinicalTrial.gov Identifier NCT00674414.

Nuclear Magnetic Resonance Spectroscopy in Clinical Metabolomics and Personalized Medicine: Current Challenges and Perspectives

Personalized medicine is probably the most promising area being developed in modern medicine. This approach attempts to optimize the therapies and the patient care based on the individual patient characteristics. Its success highly depends on the way the characterization of the disease and its evolution, the patient’s classification, its follow-up and the treatment could be optimized. Thus, personalized medicine must combine innovative tools to measure, integrate and model data. Towards this goal, clinical metabolomics appears as ideally suited to obtain relevant information. Indeed, the metabolomics signature brings crucial insight to stratify patients according to their responses to a pathology and/or a treatment, to provide prognostic and diagnostic biomarkers, and to improve therapeutic outcomes. However, the translation of metabolomics from laboratory studies to clinical practice remains a subsequent challenge. Nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are the two key platforms for the measurement of the metabolome. NMR has several advantages and features that are essential in clinical metabolomics. Indeed, NMR spectroscopy is inherently very robust, reproducible, unbiased, quantitative, informative at the structural molecular level, requires little sample preparation and reduced data processing. NMR is also well adapted to the measurement of large cohorts, to multi-sites and to longitudinal studies. This review focus on the potential of NMR in the context of clinical metabolomics and personalized medicine. Starting with the current status of NMR-based metabolomics at the clinical level and highlighting its strengths, weaknesses and challenges, this article also explores how, far from the initial “opposition” or “competition”, NMR and MS have been integrated and have demonstrated a great complementarity, in terms of sample classification and biomarker identification. Finally, a perspective discussion provides insight into the current methodological developments that could significantly raise NMR as a more resolutive, sensitive and accessible tool for clinical applications and point-of-care diagnosis. Thanks to these advances, NMR has a strong potential to join the other analytical tools currently used in clinical settings.

Pharmacometabolomics by NMR in Oncology: A Systematic Review

Pharmacometabolomics (PMx) studies aim to predict individual differences in treatment response and in the development of adverse effects associated with specific drug treatments. Overall, these studies inform us about how individuals will respond to a drug treatment based on their metabolic profiles obtained before, during, or after the therapeutic intervention. In the era of precision medicine, metabolic profiles hold great potential to guide patient selection and stratification in clinical trials, with a focus on improving drug efficacy and safety. Metabolomics is closely related to the phenotype as alterations in metabolism reflect changes in the preceding cascade of genomics, transcriptomics, and proteomics changes, thus providing a significant advance over other omics approaches. Nuclear Magnetic Resonance (NMR) is one of the most widely used analytical platforms in metabolomics studies. In fact, since the introduction of PMx studies in 2006, the number of NMR-based PMx studies has been continuously growing and has provided novel insights into the specific metabolic changes associated with different mechanisms of action and/or toxic effects. This review presents an up-to-date summary of NMR-based PMx studies performed over the last 10 years. Our main objective is to discuss the experimental approaches used for the characterization of the metabolic changes associated with specific therapeutic interventions, the most relevant results obtained so far, and some of the remaining challenges in this area.

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

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).

Identification of high-dimensional omics-derived predictors for tumor growth dynamics using machine learning and pharmacometric modeling

Pharmacometric modeling can capture tumor growth inhibition (TGI) dynamics and variability. These approaches do not usually consider covariates in high-dimensional settings, whereas high-dimensional molecular profiling technologies ("omics") are being increasingly considered for prediction of anticancer drug treatment response. Machine learning (ML) approaches have been applied to identify high-dimensional omics predictors for treatment outcome. Here, we aimed to combine TGI modeling and ML approaches for two distinct aims: omics-based prediction of tumor growth profiles and identification of pathways associated with treatment response and resistance. We propose a two-step approach combining ML using least absolute shrinkage and selection operator (LASSO) regression with pharmacometric modeling. We demonstrate our workflow using a previously published dataset consisting of 4706 tumor growth profiles of patient-derived xenograft (PDX) models treated with a variety of mono- and combination regimens. Pharmacometric TGI models were fit to the tumor growth profiles. The obtained empirical Bayes estimates-derived TGI parameter values were regressed using the LASSO on high-dimensional genomic copy number variation data, which contained over 20,000 variables. The predictive model was able to decrease median prediction error by 4% as compared with a model without any genomic information. A total of 74 pathways were identified as related to treatment response or resistance development by LASSO, of which part was verified by literature. In conclusion, we demonstrate how the combined use of ML and pharmacometric modeling can be used to gain pharmacological understanding in genomic factors driving variation in treatment response.

Effects of an Exercise and Nutritional Intervention on Circulating Biomarkers and Metabolomic Profiling During Adjuvant Treatment for Localized Breast Cancer: Results From the PASAPAS Feasibility Randomized Controlled Trial

Purpose:

Exercise has been shown to improve physical and psychological conditions during cancer therapy, but mechanisms remain poorly understood. The purpose of the present study was to report the results of cancer-related biomarkers and metabolomics outcomes from the PASAPAS feasibility study.

Methods:

In the PASAPAS randomized controlled trial, 61 women beginning adjuvant chemotherapy for localized breast cancer were randomized in a 6-month program of weekly aerobic exercises associated with nutritional counseling versus usual care with nutritional counseling. In the present analysis of 58 women for whom blood samples were available, first, circulating levels of biomarkers (ie, insulin, insulin-like growth factor 1, estradiol, adiponectin, leptin, interleukin-6, and tumor necrosis factor α) were measured at baseline and 6-month follow-up. Changes in biomarkers were compared between exercisers (n = 40) and controls (n = 18) using mixed-effect models. Second, serum metabolites were studied using an untargeted ¹H nuclear magnetic resonance spectroscopy, and orthogonal partial least squares analyses were performed to discriminate exercisers and controls at baseline and at 6 months.

Results:

Over the 6-month intervention, no statistically significant differences were observed between exercisers and controls regarding changes in biomarkers and metabolomic profiles.

Conclusion:

The present analysis of the PASAPAS feasibility trial did not reveal any improvement in circulating biomarkers nor identified metabolic signatures in exercisers versus controls during adjuvant breast cancer treatment. Larger studies preferably in women with poor physical activity level to avoid ceiling effect, testing different doses and types of exercise on additional biological pathways, could allow to clarify the mechanisms mediating beneficial effects of physical exercise during cancer treatment.

Trial registration:

ClinicalTrials.gov Identifier: NCT01331772. Registered 8 April 2011, https://clinicaltrials.gov/ct2/show/NCT01331772?term=pasapas&rank=1

Dietary Energy Modulation and Autophagy: Exploiting Metabolic Vulnerabilities to Starve Cancer

Cancer cells experience unique and dynamic shifts in their metabolic function in order to survive, proliferate, and evade growth inhibition in the resource-scarce tumor microenvironment. Therefore, identification of pharmacological agents with potential to reprogram cancer cell metabolism may improve clinical outcomes in cancer therapy. Cancer cells also often exhibit an increased dependence on the process known as autophagy, both for baseline survival and as a response to stressors such as chemotherapy or a decline in nutrient availability. There is evidence to suggest that this increased dependence on autophagy in cancer cells may be exploitable clinically by combining autophagy modulators with existing chemotherapies. In light of the increased metabolic rate in cancer cells, interest is growing in approaches aimed at "starving" cancer through dietary and pharmacologic interventions that reduce availability of nutrients and pro-growth hormonal signals known to promote cancer progression. Several dietary approaches, including chronic calorie restriction and multiple forms of fasting, have been investigated for their potential anti-cancer benefits, yielding promising results in animal models. Induction of autophagy in response to dietary energy restriction may underlie some of the observed benefit. However, while interventions based on dietary energy restriction have demonstrated safety in clinical trials, uncertainty remains regarding translation to humans as well as feasibility of achieving compliance due to the potential discomfort and weight loss that accompanies dietary restriction. Further induction of autophagy through dietary or pharmacologic metabolic reprogramming interventions may enhance the efficacy of autophagy inhibition in the context of adjuvant or neo-adjuvant chemotherapy. Nonetheless, it remains unclear whether therapeutic agents aimed at autophagy induction, autophagy inhibition, or both are a viable therapeutic strategy for improving cancer outcomes. This review discusses the literature available for the therapeutic potential of these approaches.

African Vegetables (Clerodendrum volibile Leaf and Irvingia gabonensis Seed Extracts) Effectively Mitigate Trastuzumab-Induced Cardiotoxicity in Wistar Rats

Trastuzumab (TZM) is a humanized monoclonal antibody that has been approved for the clinical management of HER2-positive metastatic breast and gastric cancers but its use is limited by its cumulative dose and off-target cardiotoxicity. Unfortunately, till date, there is no approved antidote to this off-target toxicity. Therefore, an acute study was designed at investigating the protective potential and mechanism(s) of CVE and IGE in TZM-induced cardiotoxicity utilizing cardiac enzyme and oxidative stress markers and histopathological endpoints. 400 mg/kg/day CVE and IGE dissolved in 5% DMSO in sterile water were investigated in Wistar rats injected with 2.25 mg/kg/day/i.p. route of TZM for 7 days, using serum cTnI and LDH, complete lipid profile, cardiac tissue oxidative stress markers assays, and histopathological examination of TZM-intoxicated heart tissue. Results showed that 400 mg/kg/day CVE and IGE profoundly attenuated increases in the serum cTnI and LDH levels but caused no significant alterations in the serum lipids and weight gain pattern in the treated rats. CVE and IGE profoundly attenuated alterations in the cardiac tissue oxidative stress markers' activities while improving TZM-associated cardiac histological lesions. These results suggest that CVE and IGE could be mediating its cardioprotection via antioxidant, free radical scavenging, and antithrombotic mechanisms, thus, highlighting the therapeutic potentials of CVE and IGE in the management of TZM-mediated cardiotoxicity.

High-Throughput Metabolomics by 1D NMR

Metabolomics deals with the whole ensemble of metabolites (the metabolome). As one of the -omic sciences, it relates to biology, physiology, pathology and medicine; but metabolites are chemical entities, small organic molecules or inorganic ions. Therefore, their proper identification and quantitation in complex biological matrices requires a solid chemical ground. With respect to for example, DNA, metabolites are much more prone to oxidation or enzymatic degradation: we can reconstruct large parts of a mammoth's genome from a small specimen, but we are unable to do the same with its metabolome, which was probably largely degraded a few hours after the animal's death. Thus, we need standard operating procedures, good chemical skills in sample preparation for storage and subsequent analysis, accurate analytical procedures, a broad knowledge of chemometrics and advanced statistical tools, and a good knowledge of at least one of the two metabolomic techniques, MS or NMR. All these skills are traditionally cultivated by chemists. Here we focus on metabolomics from the chemical standpoint and restrict ourselves to NMR. From the analytical point of view, NMR has pros and cons but does provide a peculiar holistic perspective that may speak for its future adoption as a population-wide health screening technique.