Metabolomics-based Studies Research Articles

Rat Fecal Metabolomics-Based Analysis.

The gut's symbiome, a hidden metabolic organ, has gained scientific interest for its crucial role in human health. Acting as a biochemical factory, the gut microbiome produces numerous small molecules that significantly impact host metabolism. Metabolic profiling facilitates the exploration of its influence on human health and disease through the symbiotic relationship. Fecal metabolomics-based analysis is an indisputably valuable tool for elucidating the biochemistry of digestion and absorption in the gastrointestinal system, serving as the most suitable specimen to study the symbiotic relationship between the host and the intestinal microbiota. It is well-established that the balance of the intestinal microbiota changes in response to various stimuli, both physiological, such as gender, age, diet, and exercise, and pathological, such as gastrointestinal and hepatic diseases. Fecal samples have been analyzed using widely adopted analytical techniques, including NMR spectroscopy, GC-MS, and LC-MS/MS. Rat fecal samples are frequently used and particularly useful substrates for metabolomics-based studies in related fields.The complexity and diversity of fecal samples necessitate careful and skillful handling to extract metabolites, while avoiding their deterioration, effectively and quantitatively. Several determinative factors, such as the fecal sample weight to extraction solvent solution volume, the nature and pH value of the extraction solvent, and the homogenization process, play crucial roles in achieving optimal extraction for obtaining high-quality metabolic fingerprints, whether for untargeted or targeted metabolomics.

Hunting Metabolic Biomarkers for Exposure to Per- and Polyfluoroalkyl Substances: A Review.

Per- and polyfluoroalkyl substances (PFAS) represent a class of persistent synthetic chemicals extensively utilized across industrial and consumer sectors, raising substantial environmental and human health concerns. Epidemiological investigations have robustly linked PFAS exposure to a spectrum of adverse health outcomes. Altered metabolites stand as promising biomarkers, offering insights into the identification of specific environmental pollutants and their deleterious impacts on human health. However, elucidating metabolic alterations attributable to PFAS exposure and their ensuing health effects has remained challenging. In light of this, this review aims to elucidate potential biomarkers of PFAS exposure by presenting a comprehensive overview of recent metabolomics-based studies exploring PFAS toxicity. Details of PFAS types, sources, and human exposure patterns are provided. Furthermore, insights into PFAS-induced liver toxicity, reproductive and developmental toxicity, cardiovascular toxicity, glucose homeostasis disruption, kidney toxicity, and carcinogenesis are synthesized. Additionally, a thorough examination of studies utilizing metabolomics to delineate PFAS exposure and toxicity biomarkers across blood, liver, and urine specimens is presented. This review endeavors to advance our understanding of PFAS biomarkers regarding exposure and associated toxicological effects.

Advances in Mass Spectrometry-Based Blood Metabolomics Profiling for Non-Cancer Diseases: A Comprehensive Review.

Blood metabolomics profiling using mass spectrometry has emerged as a powerful approach for investigating non-cancer diseases and understanding their underlying metabolic alterations. Blood, as a readily accessible physiological fluid, contains a diverse repertoire of metabolites derived from various physiological systems. Mass spectrometry offers a universal and precise analytical platform for the comprehensive analysis of blood metabolites, encompassing proteins, lipids, peptides, glycans, and immunoglobulins. In this comprehensive review, we present an overview of the research landscape in mass spectrometry-based blood metabolomics profiling. While the field of metabolomics research is primarily focused on cancer, this review specifically highlights studies related to non-cancer diseases, aiming to bring attention to valuable research that often remains overshadowed. Employing natural language processing methods, we processed 507 articles to provide insights into the application of metabolomic studies for specific diseases and physiological systems. The review encompasses a wide range of non-cancer diseases, with emphasis on cardiovascular disease, reproductive disease, diabetes, inflammation, and immunodeficiency states. By analyzing blood samples, researchers gain valuable insights into the metabolic perturbations associated with these diseases, potentially leading to the identification of novel biomarkers and the development of personalized therapeutic approaches. Furthermore, we provide a comprehensive overview of various mass spectrometry approaches utilized in blood metabolomics research, including GC-MS, LC-MS, and others discussing their advantages and limitations. To enhance the scope, we propose including recent review articles supporting the applicability of GC×GC-MS for metabolomics-based studies. This addition will contribute to a more exhaustive understanding of the available analytical techniques. The Integration of mass spectrometry-based blood profiling into clinical practice holds promise for improving disease diagnosis, treatment monitoring, and patient outcomes. By unraveling the complex metabolic alterations associated with non-cancer diseases, researchers and healthcare professionals can pave the way for precision medicine and personalized therapeutic interventions. Continuous advancements in mass spectrometry technology and data analysis methods will further enhance the potential of blood metabolomics profiling in non-cancer diseases, facilitating its translation from the laboratory to routine clinical application.

Metabolomics Unraveling the Biochemical Insight of High Altitude Diseases and Sepsis A Narrative Review

High altitude diseases and sepsis may seem distinct at first glance, but there are underlying physiological similarities that lie in their responses to hypoxia, tissue dysfunction, inflammation, and multi-organ failure conditions. Understanding these commonalities can help medical professionals draw parallels between them and apply relevant knowledge to improve patient care and treatment.In this direction,a literature review of metabolomics-based studies has been done for high-altitude diseases and sepsis, and the panel of common disease-related metabolic markers and associated pathways areunraveled. Themetabolic pathways found dysregulated in both conditions are amino acid metabolism, lipid metabolism, energy metabolism, inflammatory response-related metabolism, bile acid metabolism, and purine and pyrimidine metabolism.

SERUM METABOLOMICS SIGNATURES OF EXTREME OLD AGE AND LONGEVITY

Abstract A total of 1,495 chemicals including 1,213 compounds of known identity and 282 compounds of unknown structural identity were profiled in serum samples collected at enrollment at Metabolon, Inc. from the blood serum of 213 subjects, including centenarians (n=80), offspring (n=70), and controls (n=63), mean ages of 105, 70, and 70, respectively, enrolled in the New England Centenarian Study (NECS). We performed metabolite- and metabolite module-based regression analyses on age, differential analyses comparing centenarian to offspring and control, and Cox proportional hazard-based survival analyses. We annotated the derived signatures by enrichment analysis using metabolite sets curated by Metabolon, RefMet, and Pathbank, among others. We identified 323 (436) metabolites that change with age at an FDR-corrected q-value of 0.01 (0.05), and 298 (407) metabolites differentially abundant between centenarians, their younger offspring, and controls. Our results confirm and expand upon previous metabolomics-based studies of aging, including decreased abundance with age of Tryptophan, DHEA-S, Pregnenolone, Glutathione, and Androgen, among others, and increased abundance of Amino acids (Tyrosines), Phenylacetylglutamine, Ornithine, Urea, Kynurenine, and Creatine, among others. To distinguish metabolites associated with longevity from those associated with extreme old age, we performed age-adjusted survival analysis, and rank-based enrichment analysis identified several metabolites significantly associated with survival independent of age, including secondary and primary (C 24) bile acids, and multiple classes of steroids (androgens, pregnenolone, progestin), among others. Additional analyses are ongoing to further annotate and characterize these findings. If validated, these results could contribute to the identification of novel healthy aging therapeutics.

Genetically predicted plasma levels of amino acids and metabolic dysfunction-associated fatty liver disease risk: a Mendelian randomization study

BackgroundEmerging metabolomics-based studies suggested links between amino acid metabolism and metabolic dysfunction-associated fatty liver disease (MAFLD) risk; however, whether there exists an aetiological role of amino acid metabolism in MAFLD development remains unknown. The aim of the present study was to assess the causal relationship between circulating levels of amino acids and MAFLD risk.MethodsWe conducted a two-sample Mendelian randomization (MR) analysis using summary-level data from genome-wide association studies (GWAS) to evaluate the causal relationship between genetically predicted circulating levels of amino acids and the risk of MAFLD. In the discovery MR analysis, we used data from the largest MAFLD GWAS (8434 cases and 770,180 controls), while in the replication MR analysis, we used data from a GWAS on MAFLD (1483 cases and 17,781 controls) where MAFLD cases were diagnosed using liver biopsy. We used Wald ratios or inverse variance-weighted (IVW) methods in the MR main analysis and weighted median and MR-Egger regression analyses in sensitivity analyses. Furthermore, we performed a conservative MR analysis by restricting genetic instruments to those directly involved in amino acid metabolism pathways.ResultsWe found that genetically predicted higher alanine (OR = 1.43, 95% CI 1.13–1.81) and lower glutamine (OR = 0.83, 95% CI 0.73–0.96) levels were associated with a higher risk of developing MAFLD based on the results from the MR main and conservative analysis. The results from MR sensitivity analyses and complementary analysis using liver proton density fat fraction as a continuous outcome proxying for MAFLD supported the main findings.ConclusionsNovel causal metabolites related to MAFLD development were uncovered through MR analysis, suggesting future potential for evaluating these metabolites as targets for MAFLD prevention or treatment.

An Untargeted Metabolomics Approach on Carfilzomib-Induced Nephrotoxicity.

Carfilzomib (Cfz) is an anti-cancer drug related to cardiorenal adverse events, with cardiovascular and renal complications limiting its clinical use. Despite the important progress concerning the discovery of the underlying causes of Cfz-induced nephrotoxicity, the molecular/biochemical background is still not well clarified. Furthermore, the number of metabolomics-based studies concerning Cfz-induced nephrotoxicity is limited. A metabolomics UPLC-HRMS-DIA methodology was applied to three bio-sample types i.e., plasma, kidney, and urine, obtained from two groups of mice, namely (i) Cfz (8 mg Cfz/ kg) and (ii) Control (0.9% NaCl) (n = 6 per group). Statistical analysis, involving univariate and multivariate tools, was applied for biomarker detection. Furthermore, a sub-study was developed, aiming to estimate metabolites' correlation among bio-samples, and to enlighten potential mechanisms. Cfz mostly affects the kidneys and urine metabolome. Fifty-four statistically important metabolites were discovered, and some of them have already been related to renal diseases. Furthermore, the correlations between bio-samples revealed patterns of metabolome alterations due to Cfz. Cfz causes metabolite retention in kidney and dysregulates (up and down) several metabolites associated with the occurrence of inflammation and oxidative stress.

Effect of acute high-intensity exercise on myocardium metabolic profiles in rat and human study via metabolomics approach

Acute high-intensity exercise can affect cardiac health by altering substance metabolism. However, few metabolomics-based studies provide data on the effect of exercise along with myocardial metabolism. Our study aimed to identify metabolic signatures in rat myocardium during acute high-intensity exercise and evaluate their diagnostic potential for sports injuries. We collected rat myocardium samples and subjects’ serum samples before and after acute high-intensity exercise for metabolite profiling to explore metabolic alterations of exercise response in the myocardium. Multivariate analysis revealed myocardium metabolism differed before and after acute high-intensity exercise. Furthermore, 6 target metabolic pathways and 12 potential metabolic markers for acute high-intensity exercise were identified. Our findings provided an insight that myocardium metabolism during acute high-intensity exercise had distinct disorders in complex lipids and fatty acids. Moreover, an increase of purine degradation products, as well as signs of impaired glucose metabolism, were observed. Besides, amino acids were enhanced with a certain protective effect on the myocardium. In this study, we discovered how acute high-intensity exercise affected myocardial metabolism and exercise-related heart injury risks, which can provide references for pre-competition screening, risk prevention, and disease prognosis in competitive sports and effective formulation of exercise prescriptions for different people.

Metabolomics in Diabetic Neuropathy

Diabetic neuropathy is a common diabetic complication.The application of metabolomics in the research on diabetic neuropathy is beneficial for us to understand the pathophysiological processes and overall metabolic disturbance of the nervous system under the condition of hyperglycemia,decipher the pathogenesis of diabetic neuropathy,and mine the potential biomarkers for clinical diagnosis and treatment.Long-term hyperglycemia may lead to disorders in multiple pathways,such as tricarboxylic acid circle,amino acid metabolism,and lipid metabolism.These metabolic changes are closely associated with the injuries of the peripheral and central nervous system.In the paper,we reviewed the metabolomics-based studies about diabetic neuropathy in the last five years.

Correlation of Serum Acylcarnitines with Clinical Presentation and Severity of Coronary Artery Disease.

Recent studies support that acylcarnitines exert a significant role in cardiovascular disease development and progression. The aim of this metabolomics-based study was to investigate the association of serum acylcarnitine levels with coronary artery disease (CAD) severity, as assessed via SYNTAX Score. Within the context of the prospective CorLipid trial (NCT04580173), the levels of 13 circulating acylcarnitines were accurately determined through a newly developed HILIC-MS/MS method in 958 patients undergoing coronary angiography in the AHEPA University Hospital of Thessaloniki, Greece. Patients presenting with acute coronary syndrome had significantly lower median acylcarnitine C8, C10, C16, C18:1 and C18:2 values, compared to patients with chronic coronary syndrome (p = 0.012, 0.007, 0.018, 0.011 and <0.001, respectively). Among CAD subgroups, median C5 levels were significantly decreased in unstable angina compared to STEMI (p = 0.026), while median C10, C16, C18:1 and C18:2 levels were higher in stable angina compared to STEMI (p = 0.019 p = 0.012, p = 0.013 and p < 0.001, respectively). Moreover, median C2, C3, C4 and C8 levels were significantly elevated in patients with diabetes mellitus (p < 0.001, <0.001, 0.029 and 0.011, respectively). Moreover, short-chain acylcarnitine C2, C4, C5 and C6 levels were elevated in patients with heavier calcification and lower left ventricular ejection fraction (LVEF) % (all p-values less than 0.05). With regard to CAD severity, median C4 and C5 levels were elevated and C16 and C18:2 levels were reduced in the high CAD complexity group with SYNTAX Score > 22 (p = 0.002, 0.024, 0.044 and 0.012, respectively), indicating a potential prognostic capability of those metabolites and of the ratio C4/C18:2 for the prediction of CAD severity. In conclusion, serum acylcarnitines could serve as clinically useful biomarkers leading to a more individualized management of patients with CAD, once further clinically oriented metabolomics-based studies provide similar evidence.

Environmental Metabolomics Promises and Achievements in the Field of Aquatic Ecotoxicology: Viewed through the Pharmaceutical Lens.

Scientists often set ambitious targets using environmental metabolomics to address challenging ecotoxicological issues. This promising approach has a high potential to elucidate the mechanisms of action (MeOAs) of contaminants (in hazard assessments) and to develop biomarkers (in environmental biomonitoring). However, metabolomics fingerprints often involve a complex mixture of molecular effects that are hard to link to a specific MeOA (if detected in the analytical conditions used). Given these promises and limitations, here we propose an updated review on the achievements of this approach. Metabolomics-based studies conducted on the effects of pharmaceutical active compounds in aquatic organisms provide a relevant means to review the achievements of this approach, as prior knowledge about the MeOA of these molecules could help overcome some shortcomings. This review highlighted that current metabolomics advances have enabled more accurate MeOA assessment, especially when combined with other omics approaches. The combination of metabolomics with other measured biological endpoints has also turned out to be an efficient way to link molecular effects to (sub)-individual adverse outcomes, thereby paving the way to the construction of adverse outcome pathways (AOPs). Here, we also discuss the importance of determining MeOA as a key strategy in the identification of MeOA-specific biomarkers for biomonitoring. We have put forward some recommendations to take full advantage of environmental metabolomics and thus help fulfil these promises.

Alterations of the Intestinal Permeability are Reflected by Changes in the Urine Metabolome of Young Autistic Children: Preliminary Results.

Several metabolomics-based studies have provided evidence that autistic subjects might share metabolic abnormalities with gut microbiota dysbiosis and alterations in gut mucosal permeability. Our aims were to explore the most relevant metabolic perturbations in a group of autistic children, compared with their healthy siblings, and to investigate whether the increased intestinal permeability may be mirrored by specific metabolic perturbations. We enrolled 13 autistic children and 14 unaffected siblings aged 2–12 years; the evaluation of the intestinal permeability was estimated by the lactulose:mannitol test. The urine metabolome was investigated by proton nuclear magnetic resonance (1H-NMR) spectroscopy. The lactulose:mannitol test unveiled two autistic children with altered intestinal permeability. Nine metabolites significantly discriminated the urine metabolome of autistic children from that of their unaffected siblings; however, in the autistic children with increased permeability, four additional metabolites—namely, fucose, phenylacetylglycine, nicotinurate, and 1-methyl-nicotinamide, strongly discriminated their urine metabolome from that of the remaining autistic children. Our preliminary data suggest the presence of a specific urine metabolic profile associated with the increase in intestinal permeability.

Defining Acute Coronary Syndrome through Metabolomics.

As an emerging platform technology, metabolomics offers new insights into the pathomechanisms associated with complex disease conditions, including cardiovascular diseases. It also facilitates assessing the risk of developing the disease before its clinical manifestation. For this reason, metabolomics is of growing interest for understanding the pathogenesis of acute coronary syndromes (ACS), finding new biomarkers of ACS, and its associated risk management. Metabolomics-based studies in ACS have already demonstrated immense potential for biomarker discovery and mechanistic insights by identifying metabolomic signatures (e.g., branched-chain amino acids, acylcarnitines, lysophosphatidylcholines) associated with disease progression. Herein, we discuss the various metabolomics approaches and the challenges involved in metabolic profiling, focusing on ACS. Special attention has been paid to the clinical studies of metabolomics and lipidomics in ACS, with an emphasis on ischemia/reperfusion injury.

Could metabolomics drive the fate of COVID-19 pandemic? A narrative review on lights and shadows.

Human Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) infection activates a complex interaction host/virus, leading to the reprogramming of the host metabolism aimed at the energy supply for viral replication. Alterations of the host metabolic homeostasis strongly influence the immune response to SARS-CoV-2, forming the basis of a wide range of outcomes, from the asymptomatic infection to the onset of COVID-19 and up tolife-threatening acute respiratory distress syndrome, vascular dysfunction, multiple organ failure, and death. Deciphering the molecular mechanisms associated with the individual susceptibility to SARS-CoV-2 infection calls for a system biology approach; this strategy can address multiple goals, including which patients will respond effectively to the therapeutic treatment. The power of metabolomics liesin the ability to recognize endogenous and exogenous metabolites within a biological sample, measuring their concentration, and identifying perturbations of biochemical pathways associated with qualitative and quantitative metabolic changes. Over the last year, a limited number of metabolomics- and lipidomics-based clinical studies in COVID-19 patients have been published and are discussed in this review. Remarkable alterations in the lipid and amino acid metabolism depict the molecular phenotype ofsubjects infected by SARS-CoV-2; notably, structural and functionaldata on the lipids-virus interaction may open new perspectives on targeted therapeutic interventions. Several limitations affect most metabolomics-based studies, slowing the routine application of metabolomics. However, moving metabolomics from bench to bedside cannot imply the mere determination of a given metabolite panel; rather, slotting metabolomics into clinical practice requires the conversion of metabolic patient-specific data into actionable clinical applications.

Identification of metabolic markers predictive of prediabetes in a Korean population

Prediabetes (PD) is a high-risk state of developing type 2 diabetes, and cardiovascular and metabolic diseases. Metabolomics-based biomarker studies can provide advanced opportunities for prediction of PD over the conventional methods. Here, we aimed to identify metabolic markers and verify their abilities to predict PD, as compared to the performance of the traditional clinical risk factor (CRF) and previously reported metabolites in other population-based studies. Targeted metabolites quantification was performed in 1723 participants in the Korea Association REsource (KARE) cohort, from which 500 normal individuals were followed up for 6 years. We selected 12 significant metabolic markers, including five amino acids, four glycerophospholipids, two sphingolipids, and one acylcarnitine, at baseline, resulting in a predicted incidence of PD with an area under the curve (AUC) of 0.71 during follow-up. The performance of these metabolic markers compared to that of fasting glucose was significantly higher in obese patients (body mass index: BMI ≥ 25 kg/m2, 0.79 vs. 0.58, P < 0.001). The combination with metabolic markers, CRF, and fasting glucose yielded the best prediction performance (AUC = 0.86). Our results revealed that metabolic markers were not only associated with the risk of PD, but also improved the prediction performance in combination with conventional approaches.

Commentary: Metabolomics-Based Studies Assessing Exercise-Induced Alterations of the Human Metabolome: A Systematic Review.

Commentary: Metabolomics-Based Studies Assessing Exercise-Induced Alterations of the Human Metabolome: A Systematic Review.

Overview of Brain-to-Gut Axis Exposed to Chronic CNS Bacterial Infection(s) and a Predictive Urinary Metabolic Profile of a Brain Infected by Mycobacterium tuberculosis.

A new paradigm in neuroscience has recently emerged – the brain–gut axis (BGA). The contemporary focus in this paradigm has been gut → brain (“bottom-up”), in which the gut-microbiome, and its perturbations, affects one’s psychological state-of-mind and behavior, and is pivotal in neurodegenerative disorders. The emerging brain → gut (“top-down”) concept, the subject of this review, proposes that dysfunctional brain health can alter the gut-microbiome. Feedback of this alternative bidirectional highway subsequently aggravates the neurological pathology. This paradigm shift, however, focuses upon non-communicable neurological diseases (progressive neuroinflammation). What of infectious diseases, in which pathogenic bacteria penetrate the blood–brain barrier and interact with the brain, and what is this effect on the BGA in bacterial infection(s) that cause chronic neuroinflammation? Persistent immune activity in the CNS due to chronic neuroinflammation can lead to irreversible neurodegeneration and neuronal death. The properties of cerebrospinal fluid (CSF), such as immunological markers, are used to diagnose brain disorders. But what of metabolic markers for such purposes? If a BGA exists, then chronic CNS bacterial infection(s) should theoretically be reflected in the urine. The premise here is that chronic CNS bacterial infection(s) will affect the gut-microbiome and that perturbed metabolism in both the CNS and gut will release metabolites into the blood that are filtered (kidneys) and excreted in the urine. Here we assess the literature on the effects of chronic neuroinflammatory diseases on the gut-microbiome caused by bacterial infection(s) of the CNS, in the context of information attained via metabolomics-based studies of urine. Furthermore, we take a severe chronic neuroinflammatory infectious disease – tuberculous meningitis (TBM), caused by Mycobacterium tuberculosis, and examine three previously validated CSF immunological biomarkers – vascular endothelial growth factor, interferon-gamma and myeloperoxidase – in terms of the expected changes in normal brain metabolism. We then model the downstream metabolic effects expected, predicting pivotal altered metabolic pathways that would be reflected in the urinary profiles of TBM subjects. Our cascading metabolic model should be adjustable to account for other types of CNS bacterial infection(s) associated with chronic neuroinflammation, typically prevalent, and difficult to distinguish from TBM, in the resource-constrained settings of poor communities.

Metabolomics-Based Prospective Studies and Prediction of Type 2 Diabetes Mellitus Risks.

The preceding decade has witnessed an intense upsurge in the diabetic population across the world making type 2 diabetes mellitus (T2DM) more of an epidemic than a lifestyle disease. Metabolic disorders are often latent for a while before becoming clinically evident, thus reinforcing the pursuit of early biomarkers of metabolic alterations. A prospective study along with metabolic profiling is the most appropriate way to detect the early pathophysiological changes in metabolic diseases such as T2DM. The aim of this review was to summarize the different potential biomarkers of T2DM identified in prospective studies, which used tools of metabolomics. The review also demonstrates on how metabolomic profiling-based prospective studies can be used to address a concern like population-specific disease mechanism. We performed a literature search on metabolomics-based prospective studies on T2DM using the key words "metabolomics," "Type 2 diabetes," "diabetes mellitus", "metabolite profiling," "prospective study," "metabolism," and "biomarker." Additional articles that were obtained from the reference lists of the articles obtained using the above key words were also examined. Articles on dietary intake, type 1 diabetes mellitus, and gestational diabetes were excluded. The review revealed that many studies showed a direct association of branched-chain amino acids and an inverse association of glycine with T2DM. Majority of the prospective studies conducted were targeted metabolomics-based, with Caucasians as their study cohort. The whole disease risk in populations, including Asians, could therefore not be identified. This review proposes the utility of prospective studies in conjunction with metabolomics platform to unravel the altered metabolic pathways that contribute to the risk of T2DM.

STRATEGIES AND CHALLENGES IN METHOD DEVELOPMENT AND VALIDATION FOR THE ABSOLUTE QUANTIFICATION OF ENDOGENOUS BIOMARKER METABOLITES USING LIQUID CHROMATOGRAPHY-TANDEM MASS SPECTROMETRY.

Metabolomics is a dynamically evolving field, with a major application in identifying biomarkers for drug development and personalized medicine. Numerous metabolomic studies have identified endogenous metabolites that, in principle, are eligible for translation to clinical practice. However, few metabolomic-derived biomarker candidates have been qualified by regulatory bodies for clinical applications. Such interruption in the biomarker qualification process can be largely attributed to various reasons including inappropriate study design and inadequate data to support the clinical utility of the biomarkers. In addition, the lack of robust assays for the routine quantification of candidate biomarkers has been suggested as a potential bottleneck in the biomarker qualification process. In fact, the nature of the endogenous metabolites precludes the application of the current validation guidelines for bioanalytical methods. As a result, there have been individual efforts in modifying existing guidelines and/or developing alternative approaches to facilitate method validation. In this review, three main challenges for method development and validation for endogenous metabolites are discussed, namely matrix effects evaluation, alternative analyte-free matrices, and the choice of internal standards (ISs). Some studies have modified the equations described by the European Medicines Agency for the evaluation of matrix effects. However, alternative strategies were also described; for instance, calibration curves can be generated in solvents and in biological samples and the slopes can be compared through ratios, relative standard deviation, or a modified Stufour suggested approaches while quantifying mainly endogenous metabolitesdent t-test. ISs, on the contrary, are diverse; in which seven different possible types, used in metabolomics-based studies, were identified in the literature. Each type has its advantages and limitations; however, isotope-labeled ISs and ISs created through isotope derivatization show superior performance. Finally, alternative matrices have been described and tested during method development and validation for the quantification of endogenous entities. These alternatives are discussed in detail, highlighting their advantages and shortcomings. The goal of this review is to compare, apprise, and debate current knowledge and practices in order to aid researchers and clinical scientists in developing robust assays needed during the qualification process of candidate metabolite biomarkers. © 2019 John Wiley & Sons Ltd. Mass Spec Rev.

Metabolomics-Based Studies Assessing Exercise-Induced Alterations of the Human Metabolome: A Systematic Review.

This systematic review provides a qualitative appraisal of 24 high-quality metabolomics-based studies published over the past decade exploring exercise-induced alterations of the human metabolome. Of these papers, 63% focused on acute metabolite changes following intense and prolonged exercise. The best studies utilized liquid chromatography mass spectrometry (LC-MS/MS) analytical platforms with large chemical standard libraries and strong, multivariate bioinformatics support. These studies reported large-fold changes in diverse lipid-related metabolites, with more than 100 increasing two-fold or greater within a few hours post-exercise. Metabolite shifts, even after strenuous exercise, typically return to near pre-exercise levels after one day of recovery. Few studies investigated metabolite changes following acute exercise bouts of shorter durations (< 60 min) and workload volumes. Plasma metabolite shifts in these types of studies are modest in comparison. More cross-sectional and exercise training studies are needed to improve scientific understanding of the human system’s response to varying, chronic exercise workloads. The findings derived from this review provide direction for future investigations focused on the body’s metabolome response to exercise.