Submit to Metabolites Review for Metabolites Propose a Special Issue

Journal Menu

Journal Browser

Metabolomics and Its Application in Human Diseases Volume 2

Special Issue Editors
Special Issue Information
Keywords
Published Papers

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Integrative Metabolomics".

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 61699

Share This Special Issue

Special Issue Editor

Dr. Vladimir V. Tolstikov

E-Mail Website
Guest Editor

Department of Precision Medicine, Berg Pharma, Framingham, MA 01701, USA
Interests: discovery and clinical metabolomics; biomarkers; systems biology; AI; multi-omics; separation science; mass spectrometry
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Metabolomics is a continually growing discipline facilitating innovations and discoveries in the life sciences and in biomedical and clinical research. Metabolomics has emerged as an essential tool for studying metabolic processes on cellular levels and has progressed to the protocols for the stratification of patients, as well as to illuminating the fundamental metabolic alterations in disease onset, progression, and/or response to therapeutic intervention. Whether as a standalone, or as an essential part of multi-omics protocols, metabolomics contributes significantly in biomarker discovery, supported by artificial intelligence (AI) and sustained practically by the principles of precision medicine. Therefore, this Special Issue of Metabolites is tailored to the biomedical and clinical community. It combines timely reviews discussing the challenges associated with metabolomics and its integration with other omics methods and protocols, applied towards human disease studies with research articles presenting new findings and results related to metabolomics application in research related to human diseases, their diagnostics, and applied therapeutic intervention.

Dr. Vladimir Tolstikov
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metabolites is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

precision medicine
metabolomics
biomarker
clinical
diagnostic
therapeutic
AI

Published Papers (14 papers)

Download All Papers

Research

Jump to: Review

16 pages, 1245 KiB

Open AccessArticle

Long-Chain Acylcarnitines and Monounsaturated Fatty Acids Discriminate Heart Failure Patients According to Pulmonary Hypertension Status

by Maxime Tremblay-Gravel, Annik Fortier, Cantin Baron, Chloé David, Pamela Mehanna, Anique Ducharme, Julie Hussin, Qinghua Hu, Jean-Claude Tardif, Christine Des Rosiers, Jocelyn Dupuis and Matthieu Ruiz

Metabolites 2021, 11(4), 196; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo11040196 - 26 Mar 2021

Cited by 5 | Viewed by 2067

Abstract

Defects in fatty acid (FA) utilization have been well described in group 1 pulmonary hypertension (PH) and in heart failure (HF), yet poorly studied in group 2 PH. This study was to assess whether the metabolomic profile of patients with pulmonary hypertension (PH) due HF, classified as group 2 PH, differs from those without PH. We conducted a proof-of-principle cross-sectional analysis of 60 patients with chronic HF with reduced ejection fraction and 72 healthy controls in which the circulating level of 71 energy-related metabolites was measured using various methods. Echocardiography was used to classify HF patients as noPH-HF (n = 27; mean pulmonary artery pressure [mPAP] 21 mmHg) and PH-HF (n = 33; mPAP 35 mmHg). The profile of circulating metabolites among groups was compared using principal component analysis (PCA), analysis of covariance (ANCOVA), and Pearson’s correlation tests. Patients with noPH-HF and PH-HF were aged 64 ± 11 and 68 ± 10 years, respectively, with baseline left ventricular ejection fractions of 27 ± 7% and 26 ± 7%. Principal component analysis segregated groups, more markedly for PH-HF, with long-chain acylcarnitines, acetylcarnitine, and monounsaturated FA carrying the highest loading scores. After adjustment for age, sex, kidney function, insulin resistance, and N-terminal pro-brain natriuretic peptide (NT-proBNP), 5/15 and 8/15 lipid-related metabolite levels were significantly different from controls in noPH-HF and PH-HF subjects, respectively. All metabolites for which circulating levels interacted between group and NT-proBNP significantly correlated with NT-proBNP in HF-PH, but none with HF-noPH. FA-related metabolites were differently affected in HF with or without PH, and may convey adverse outcomes given their distinct correlation with NT-proBNP in the setting of PH. Full article

(This article belongs to the Special Issue Metabolomics and Its Application in Human Diseases Volume 2)

► Show Figures

Graphical abstract

16 pages, 1780 KiB

Open AccessArticle

Targeted Plasma Metabolic Profiles and Risk of Recurrence in Stage II and III Colorectal Cancer Patients: Results from an International Cohort Consortium

by Jennifer Ose, Biljana Gigic, Stefanie Brezina, Tengda Lin, Andreas Baierl, Anne J. M. R. Geijsen, Eline van Roekel, Nivonirina Robinot, Audrey Gicquiau, David Achaintre, Pekka Keski-Rahkonen, Fränzel J. B. van Duijnhoven, Tanja Gumpenberger, Andreana N. Holowatyj, Dieuwertje E. Kok, Annaleen Koole, Petra Schrotz-King, Alexis B. Ulrich, Martin Schneider, Arve Ulvik, Per-Magne Ueland, Matty P. Weijenberg, Nina Habermann, Augustin Scalbert, Andrea Gsur and Cornelia M. Ulrich Show full author list Hide full author list

Metabolites 2021, 11(3), 129; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo11030129 - 24 Feb 2021

Cited by 5 | Viewed by 2299

Abstract

The identification of patients at high-risk for colorectal cancer (CRC) recurrence remains an unmet clinical need. The aim of this study was to investigate associations of metabolites with risk of recurrence in stage II/III CRC patients. A targeted metabolomics assay (128 metabolites measured) was performed on pre-surgery collected EDTA plasma samples from n = 440 newly diagnosed stage II/III CRC patients. Patients have been recruited from four prospective cohort studies as part of an international consortium: Metabolomic profiles throughout the continuum of CRC (MetaboCCC). Cox proportional hazard models were computed to investigate associations of metabolites with recurrence, adjusted for age, sex, tumor stage, tumor site, body mass index, and cohort; false discovery rate (FDR) was used to account for multiple testing. Sixty-nine patients (15%) had a recurrence after a median follow-up time of 20 months. We identified 13 metabolites that were nominally associated with a reduced risk of recurrence. None of the associations were statistically significant after controlling for multiple testing. Pathway topology analyses did not reveal statistically significant associations between recurrence and alterations in metabolic pathways (e.g., sphingolipid metabolism p = 0.04; pFDR = 1.00). To conclude, we did not observe statistically significant associations between metabolites and CRC recurrence using a well-established metabolomics assay. The observed results require follow-up in larger studies. Full article

(This article belongs to the Special Issue Metabolomics and Its Application in Human Diseases Volume 2)

► Show Figures

Figure 1

12 pages, 1654 KiB

Open AccessArticle

Behavioral and Metabolome Differences between C57BL/6 and DBA/2 Mouse Strains: Implications for Their Use as Models for Depression- and Anxiety-Like Phenotypes

by Michaela D. Filiou, Markus Nussbaumer, Larysa Teplytska and Christoph W. Turck

Metabolites 2021, 11(2), 128; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo11020128 - 23 Feb 2021

Cited by 7 | Viewed by 2723

Abstract

Mouse models are widely used to study behavioral phenotypes related to neuropsychiatric disorders. However, different mouse strains vary in their inherent behavioral and molecular characteristics, which needs to be taken into account depending on the nature of the study. Here, we performed a detailed behavioral and molecular comparison of C57BL/6 (B6) and DBA/2 (DBA) mice, two inbred strains commonly used in neuropsychiatric research. We analyzed anxiety-related and depression-like traits, quantified hippocampal and plasma metabolite profiles, and assessed total antioxidant capacity (ΤAC). B6 mice exhibit increased depression-like and decreased anxiety-related behavior compared to DBA mice. Metabolite level differences indicate alterations in amino acid, nucleotide and mitochondrial metabolism that are accompanied by a decreased TAC in B6 compared to DBA mice. Our data reveal multiple behavioral and molecular differences between B6 and DBA mouse strains, which should be considered in the experimental design for phenotype, pharmacological and mechanistic studies relevant for neuropsychiatric disorders. Full article

(This article belongs to the Special Issue Metabolomics and Its Application in Human Diseases Volume 2)

► Show Figures

Figure 1

13 pages, 451 KiB

Open AccessArticle

Untargeted Metabolomics Reveals Major Differences in the Plasma Metabolome between Colorectal Cancer and Colorectal Adenomas

by Tanja Gumpenberger, Stefanie Brezina, Pekka Keski-Rahkonen, Andreas Baierl, Nivonirina Robinot, Gernot Leeb, Nina Habermann, Dieuwertje E G Kok, Augustin Scalbert, Per-Magne Ueland, Cornelia M Ulrich and Andrea Gsur

Metabolites 2021, 11(2), 119; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo11020119 - 19 Feb 2021

Cited by 19 | Viewed by 3236

Abstract

Sporadic colorectal cancer is characterized by a multistep progression from normal epithelium to precancerous low-risk and high-risk adenomas to invasive cancer. Yet, the underlying molecular mechanisms of colorectal carcinogenesis are not completely understood. Within the “Metabolomic profiles throughout the continuum of colorectal cancer” (MetaboCCC) consortium we analyzed data generated by untargeted, mass spectrometry-based metabolomics using plasma from 88 colorectal cancer patients, 200 patients with high-risk adenomas and 200 patients with low-risk adenomas recruited within the “Colorectal Cancer Study of Austria” (CORSA). Univariate logistic regression models comparing colorectal cancer to adenomas resulted in 442 statistically significant molecular features. Metabolites discriminating colorectal cancer patients from those with adenomas in our dataset included acylcarnitines, caffeine, amino acids, glycerophospholipids, fatty acids, bilirubin, bile acids and bacterial metabolites of tryptophan. The data obtained discovers metabolite profiles reflecting metabolic differences between colorectal cancer and colorectal adenomas and delineates a potentially underlying biological interpretation. Full article

(This article belongs to the Special Issue Metabolomics and Its Application in Human Diseases Volume 2)

► Show Figures

Figure 1

16 pages, 2464 KiB

Open AccessArticle

Validation of Candidate Phospholipid Biomarkers of Chronic Kidney Disease in Hyperglycemic Individuals and Their Organ-Specific Exploration in Leptin Receptor-Deficient db/db Mouse

by Jialing Huang, Marcela Covic, Cornelia Huth, Martina Rommel, Jonathan Adam, Sven Zukunft, Cornelia Prehn, Li Wang, Jana Nano, Markus F. Scheerer, Susanne Neschen, Gabi Kastenmüller, Christian Gieger, Michael Laxy, Freimut Schliess, Jerzy Adamski, Karsten Suhre, Martin Hrabe de Angelis, Annette Peters and Rui Wang-Sattler

Metabolites 2021, 11(2), 89; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo11020089 - 03 Feb 2021

Cited by 9 | Viewed by 3332

Abstract

Biological exploration of early biomarkers for chronic kidney disease (CKD) in (pre)diabetic individuals is crucial for personalized management of diabetes. Here, we evaluated two candidate biomarkers of incident CKD (sphingomyelin (SM) C18:1 and phosphatidylcholine diacyl (PC aa) C38:0) concerning kidney function in hyperglycemic participants of the Cooperative Health Research in the Region of Augsburg (KORA) cohort, and in two biofluids and six organs of leptin receptor-deficient (db/db) mice and wild type controls. Higher serum concentrations of SM C18:1 and PC aa C38:0 in hyperglycemic individuals were found to be associated with lower estimated glomerular filtration rate (eGFR) and higher odds of CKD. In db/db mice, both metabolites had a significantly lower concentration in urine and adipose tissue, but higher in the lungs. Additionally, db/db mice had significantly higher SM C18:1 levels in plasma and liver, and PC aa C38:0 in adrenal glands. This cross-sectional human study confirms that SM C18:1 and PC aa C38:0 associate with kidney dysfunction in pre(diabetic) individuals, and the animal study suggests a potential implication of liver, lungs, adrenal glands, and visceral fat in their systemic regulation. Our results support further validation of the two phospholipids as early biomarkers of renal disease in patients with (pre)diabetes. Full article

(This article belongs to the Special Issue Metabolomics and Its Application in Human Diseases Volume 2)

► Show Figures

Graphical abstract

13 pages, 761 KiB

Open AccessArticle

Physical Activity-Related Metabolites Are Associated with Mortality: Findings from the Atherosclerosis Risk in Communities (ARIC) Study

by Jun Xu, Guning Liu, Sheila M. Hegde, Priya Palta, Eric Boerwinkle, Kelley P. Gabriel and Bing Yu

Metabolites 2021, 11(1), 59; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo11010059 - 19 Jan 2021

Cited by 4 | Viewed by 2883

Abstract

Habitual physical activity can diminish the risk of premature death. Identifying a pattern of metabolites related to physical activity may advance our understanding of disease etiology. We quantified 245 serum metabolites in 3802 participants from the Atherosclerosis Risk in Communities (ARIC) study using chromatography–mass spectrometry. We regressed self-reported moderate-to-vigorous intensity leisure-time physical activity (LTPA) against each metabolite, adjusting for traditional risk factors. A standardized metabolite risk score (MRS) was constructed to examine its association with all-cause mortality using the Cox proportional hazard model. We identified 10 metabolites associated with LTPA (p < 2.04 × 10⁻⁴) and established that an increase of one unit of the metabolic equivalent of task-hours per week (MET·hr·wk⁻¹) in LTPA was associated with a 0.012 SD increase in MRS. During a median of 27.5 years of follow-up, we observed 1928 deaths. One SD increase of MRS was associated with a 10% lower risk of death (HR = 0.90, 95% CI: 0.85–0.95). The highest vs. the lowest MRS quintile rank was associated with a 22% reduced risk of death (HR = 0.78, 95% CI: 0.62–0.94). The effects were consistent across race and sex groups. In summary, we identified a set of metabolites associated with LTPA and an MRS associated with a lower risk of death. Our study provides novel insights into the potential mechanisms underlying the health impacts of physical activity. Full article

(This article belongs to the Special Issue Metabolomics and Its Application in Human Diseases Volume 2)

► Show Figures

Figure 1

13 pages, 1330 KiB

Open AccessArticle

Effect of a Single Bout of Aerobic Exercise on Kynurenine Pathway Metabolites and Inflammatory Markers in Prostate Cancer Patients—A Pilot Randomized Controlled Trial

by Alexander Schenk, Tobias Esser, André Knoop, Mario Thevis, Jan Herden, Axel Heidenreich, Wilhelm Bloch, Niklas Joisten and Philipp Zimmer

Metabolites 2021, 11(1), 4; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo11010004 - 23 Dec 2020

Cited by 7 | Viewed by 4259

Abstract

The kynurenine (KYN) pathway gains growing research interest concerning the genesis, progression and therapy of solid tumors. Previous studies showed exercise-induced effects on metabolite levels along the KYN pathway. Modulations of the KYN pathway might be involved in the positive impact of exercise on prostate cancer progression and mortality. The objective of this trial was to investigate whether a single-physical exercise alters tryptophan (TRP) metabolism and related inflammatory markers in this population. We conducted a randomized controlled trial with 24 patients suffering from prostate cancer. While the control group remained inactive, the intervention group performed a 30-min aerobic exercise on a bicycle ergometer at 75% of individual VO_2peak. Before (t0) and directly after the exercise intervention (t1) KYN, TRP, kynurenic acid, quinolinic acid as well as various inflammation markers (IL6, TNF-α, TGF-β) were measured in blood serum. At baseline, the present sample showed robust correlations between TRP, KYN, quinolinic acid and inflammatory markers. Regarding the exercise intervention, interaction effects for TRP, the KYN/TRP ratio and TGF-β were observed. The results show for the first time that acute physical exercise impacts TRP metabolism in prostate cancer patients. Moreover, baseline associations underline the relationship between inflammation and the KYN pathway in prostate cancer. Full article

(This article belongs to the Special Issue Metabolomics and Its Application in Human Diseases Volume 2)

► Show Figures

Figure 1

20 pages, 2793 KiB

Open AccessArticle

Prediction of Autoimmune Diseases by Targeted Metabolomic Assay of Urinary Organic Acids

by Dimitris Tsoukalas, Vassileios Fragoulakis, Evangelos Papakonstantinou, Maria Antonaki, Athanassios Vozikis, Aristidis Tsatsakis, Ana Maria Buga, Mihaela Mitroi and Daniela Calina

Metabolites 2020, 10(12), 502; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo10120502 - 08 Dec 2020

Cited by 26 | Viewed by 14185

Abstract

Autoimmune diseases (ADs) are chronic disorders characterized by the loss of self-tolerance, and although being heterogeneous, they share common pathogenic mechanisms. Self-antigens and inflammation markers are established diagnostic tools; however, the metabolic imbalances that underlie ADs are poorly described. The study aimed to employ metabolomics for the detection of disease-related changes in autoimmune diseases that could have predictive value. Quantitative analysis of 28 urine organic acids was performed using Gas Chromatography-Mass Spectrometry in a group of 392 participants. Autoimmune thyroiditis, inflammatory bowel disease, psoriasis and rheumatoid arthritis were the most prevalent autoimmune diseases of the study. Statistically significant differences were observed in the tricarboxylate cycle metabolites, succinate, methylcitrate and malate, the pyroglutamate and 2-hydroxybutyrate from the glutathione cycle and the metabolites methylmalonate, 4-hydroxyphenylpyruvate, 2-hydroxyglutarate and 2-hydroxyisobutyrate between the AD group and the control. Artificial neural networks and Binary logistic regression resulted in the highest predictive accuracy scores (66.7% and 74.9%, respectively), while Methylmalonate, 2-Hydroxyglutarate and 2-hydroxybutyrate were proposed as potential biomarkers for autoimmune diseases. Urine organic acid levels related to the mechanisms of energy production and detoxification were associated with the presence of autoimmune diseases and could be an adjunct tool for early diagnosis and prediction. Full article

(This article belongs to the Special Issue Metabolomics and Its Application in Human Diseases Volume 2)

► Show Figures

Graphical abstract

21 pages, 4958 KiB

Open AccessArticle

The Urine Metabolome of Young Autistic Children Correlates with Their Clinical Profile Severity

by Michele Mussap, Martina Siracusano, Antonio Noto, Claudia Fattuoni, Assia Riccioni, Hema Sekhar Reddy Rajula, Vassilios Fanos, Paolo Curatolo, Luigi Barberini and Luigi Mazzone

Metabolites 2020, 10(11), 476; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo10110476 - 23 Nov 2020

Cited by 21 | Viewed by 4246

Abstract

Autism diagnosis is moving from the identification of common inherited genetic variants to a systems biology approach. The aims of the study were to explore metabolic perturbations in autism, to investigate whether the severity of autism core symptoms may be associated with specific metabolic signatures; and to examine whether the urine metabolome discriminates severe from mild-to-moderate restricted, repetitive, and stereotyped behaviors. We enrolled 57 children aged 2–11 years; thirty-one with idiopathic autism and twenty-six neurotypical (NT), matched for age and ethnicity. The urine metabolome was investigated by gas chromatography-mass spectrometry (GC-MS). The urinary metabolome of autistic children was largely distinguishable from that of NT children; food selectivity induced further significant metabolic differences. Severe autism spectrum disorder core deficits were marked by high levels of metabolites resulting from diet, gut dysbiosis, oxidative stress, tryptophan metabolism, mitochondrial dysfunction. The hierarchical clustering algorithm generated two metabolic clusters in autistic children: 85–90% of children with mild-to-moderate abnormal behaviors fell in cluster II. Our results open up new perspectives for the more general understanding of the correlation between the clinical phenotype of autistic children and their urine metabolome. Adipic acid, palmitic acid, and 3-(3-hydroxyphenyl)-3-hydroxypropanoic acid can be proposed as candidate biomarkers of autism severity. Full article

(This article belongs to the Special Issue Metabolomics and Its Application in Human Diseases Volume 2)

► Show Figures

Figure 1

18 pages, 3329 KiB

Open AccessArticle

Effects of Probiotics Administration on Human Metabolic Phenotype

by Veronica Ghini, Leonardo Tenori, Marco Pane, Angela Amoruso, Giada Marroncini, Diletta Francesca Squarzanti, Barbara Azzimonti, Roberta Rolla, Paola Savoia, Mirko Tarocchi, Andrea Galli and Claudio Luchinat

Metabolites 2020, 10(10), 396; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo10100396 - 07 Oct 2020

Cited by 8 | Viewed by 3592

Abstract

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. Full article

(This article belongs to the Special Issue Metabolomics and Its Application in Human Diseases Volume 2)

► Show Figures

Graphical abstract

Review

Jump to: Research

32 pages, 6158 KiB

Open AccessReview

The Potential of Metabolomics in Biomedical Applications

by Vanessa Gonzalez-Covarrubias, Eduardo Martínez-Martínez and Laura del Bosque-Plata

Metabolites 2022, 12(2), 194; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo12020194 - 19 Feb 2022

Cited by 57 | Viewed by 7448

Abstract

The metabolome offers a dynamic, comprehensive, and precise picture of the phenotype. Current high-throughput technologies have allowed the discovery of relevant metabolites that characterize a wide variety of human phenotypes with respect to health, disease, drug monitoring, and even aging. Metabolomics, parallel to genomics, has led to the discovery of biomarkers and has aided in the understanding of a diversity of molecular mechanisms, highlighting its application in precision medicine. This review focuses on the metabolomics that can be applied to improve human health, as well as its trends and impacts in metabolic and neurodegenerative diseases, cancer, longevity, the exposome, liquid biopsy development, and pharmacometabolomics. The identification of distinct metabolomic profiles will help in the discovery and improvement of clinical strategies to treat human disease. In the years to come, metabolomics will become a tool routinely applied to diagnose and monitor health and disease, aging, or drug development. Biomedical applications of metabolomics can already be foreseen to monitor the progression of metabolic diseases, such as obesity and diabetes, using branched-chain amino acids, acylcarnitines, certain phospholipids, and genomics; these can assess disease severity and predict a potential treatment. Future endeavors should focus on determining the applicability and clinical utility of metabolomic-derived markers and their appropriate implementation in large-scale clinical settings. Full article

(This article belongs to the Special Issue Metabolomics and Its Application in Human Diseases Volume 2)

► Show Figures

Graphical abstract

16 pages, 1312 KiB

Open AccessReview

Microbial Metabolites in Colorectal Cancer: Basic and Clinical Implications

by Yao Peng, Yuqiang Nie, Jun Yu and Chi Chun Wong

Metabolites 2021, 11(3), 159; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo11030159 - 10 Mar 2021

Cited by 24 | Viewed by 3411

Abstract

Colorectal cancer (CRC) is one of the leading cancers that cause cancer-related deaths worldwide. The gut microbiota has been proved to show relevance with colorectal tumorigenesis through microbial metabolites. By decomposing various dietary residues in the intestinal tract, gut microbiota harvest energy and produce a variety of metabolites to affect the host physiology. However, some of these metabolites are oncogenic factors for CRC. With the advent of metabolomics technology, studies profiling microbiota-derived metabolites have greatly accelerated the progress in our understanding of the host-microbiota metabolism interactions in CRC. In this review, we briefly summarize the present metabolomics techniques in microbial metabolites researches and the mechanisms of microbial metabolites in CRC pathogenesis, furthermore, we discuss the potential clinical applications of microbial metabolites in cancer diagnosis and treatment. Full article

(This article belongs to the Special Issue Metabolomics and Its Application in Human Diseases Volume 2)

► Show Figures

Figure 1

30 pages, 1766 KiB

Open AccessReview

The Metabolomics of Childhood Atopic Diseases: A Comprehensive Pathway-Specific Review

by Mette S. Schjødt, Gözde Gürdeniz and Bo Chawes

Metabolites 2020, 10(12), 511; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo10120511 - 16 Dec 2020

Cited by 20 | Viewed by 3269

Abstract

Asthma, allergic rhinitis, food allergy, and atopic dermatitis are common childhood diseases with several different underlying mechanisms, i.e., endotypes of disease. Metabolomics has the potential to identify disease endotypes, which could beneficially promote personalized prevention and treatment. Here, we summarize the findings from metabolomics studies of children with atopic diseases focusing on tyrosine and tryptophan metabolism, lipids (particularly, sphingolipids), polyunsaturated fatty acids, microbially derived metabolites (particularly, short-chain fatty acids), and bile acids. We included 25 studies: 23 examined asthma or wheezing, five examined allergy endpoints, and two focused on atopic dermatitis. Of the 25 studies, 20 reported findings in the pathways of interest with findings for asthma in all pathways and for allergy and atopic dermatitis in most pathways except tyrosine metabolism and short-chain fatty acids, respectively. Particularly, tyrosine, 3-hydroxyphenylacetic acid, N-acetyltyrosine, tryptophan, indolelactic acid, 5-hydroxyindoleacetic acid, p-Cresol sulfate, taurocholic acid, taurochenodeoxycholic acid, glycohyocholic acid, glycocholic acid, and docosapentaenoate n-6 were identified in at least two studies. This pathway-specific review provides a comprehensive overview of the existing evidence from metabolomics studies of childhood atopic diseases. The altered metabolic pathways uncover some of the underlying biochemical mechanisms leading to these common childhood disorders, which may become of potential value in clinical practice. Full article

(This article belongs to the Special Issue Metabolomics and Its Application in Human Diseases Volume 2)

► Show Figures

Figure 1

12 pages, 1133 KiB

Open AccessReview

Current Status of Metabolomic Biomarker Discovery: Impact of Study Design and Demographic Characteristics

by Vladimir Tolstikov, A. James Moser, Rangaprasad Sarangarajan, Niven R. Narain and Michael A. Kiebish

Metabolites 2020, 10(6), 224; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo10060224 - 29 May 2020

Cited by 53 | Viewed by 3655

Abstract

Widespread application of omic technologies is evolving our understanding of population health and holds promise in providing precise guidance for selection of therapeutic interventions based on patient biology. The opportunity to use hundreds of analytes for diagnostic assessment of human health compared to the current use of 10–20 analytes will provide greater accuracy in deconstructing the complexity of human biology in disease states. Conventional biochemical measurements like cholesterol, creatinine, and urea nitrogen are currently used to assess health status; however, metabolomics captures a comprehensive set of analytes characterizing the human phenotype and its complex metabolic processes in real-time. Unlike conventional clinical analytes, metabolomic profiles are dramatically influenced by demographic and environmental factors that affect the range of normal values and increase the risk of false biomarker discovery. This review addresses the challenges and opportunities created by the evolving field of clinical metabolomics and highlights features of study design and bioinformatics necessary to maximize the utility of metabolomics data across demographic groups. Full article

(This article belongs to the Special Issue Metabolomics and Its Application in Human Diseases Volume 2)

► Show Figures