Advanced Metabolomics and Lipidomics Approaches in Studying Human Diseases

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

Deadline for manuscript submissions: 31 December 2024 | Viewed by 8914

Special Issue Editor


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Guest Editor
Faculté de Pharmacie, University Paris Cité, Paris, France
Interests: biomarkers discovery; human diseases; mass-spectrometry-based metabolomics; database; molecular networking; falsified medicines

Special Issue Information

Dear Colleagues,

Metabolomics and lipidomics have proven to be powerful strategies that enable the identification of metabolic signatures of pathological conditions, thus offering means for unraveling biomarkers and drug discovery.

This Special Issue on “Advanced Metabolomics and Lipidomics Approaches in Studying Human Diseases” will serve as a platform dedicated to this pursuit.

During the last decade, metabolomics and lipidomics in studying biological processes and metabolic responses of the population to pathophysiological stimuli, genetic modifications, and environmental challenges have revealed new therapeutic avenues.

This Special Issue will cover research targets of outstanding medical and biological interests, in human diseases and experimental models, using a range of cutting-edge technologies and data analysis tools. Several topics including sample preparation and detection techniques, bioinformatics and data analysis, and metabolic and molecular networks will be addressed, with the aim of improving diagnosis, prognosis, and therapeutic monitoring in inherited and common human diseases.

Dr. Judith Nzoughet Kouassi
Guest Editor

Manuscript Submission Information

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Keywords

  • biomarkers discovery
  • metabolomics
  • lipidomics
  • human diseases
  • bioinformatics and data analysis
  • metabolic and molecular networks

Published Papers (6 papers)

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19 pages, 20557 KiB  
Article
Metabolomic Profiling of Bipolar Disorder by 1H-NMR in Serbian Patients
by Katarina Simić, Zoran Miladinović, Nina Todorović, Snežana Trifunović, Nataša Avramović, Aleksandra Gavrilović, Silvana Jovanović, Dejan Gođevac, Ljubodrag Vujisić, Vele Tešević, Ljubica Tasic and Boris Mandić
Metabolites 2023, 13(5), 607; https://doi.org/10.3390/metabo13050607 - 28 Apr 2023
Cited by 3 | Viewed by 1648
Abstract
Bipolar disorder (BD) is a brain disorder that causes changes in a person’s mood, energy, and ability to function. It has a prevalence of 60 million people worldwide, and it is among the top 20 diseases with the highest global burden. The complexity [...] Read more.
Bipolar disorder (BD) is a brain disorder that causes changes in a person’s mood, energy, and ability to function. It has a prevalence of 60 million people worldwide, and it is among the top 20 diseases with the highest global burden. The complexity of this disease, including diverse genetic, environmental, and biochemical factors, and diagnoses based on the subjective recognition of symptoms without any clinical test of biomarker identification create significant difficulties in understanding and diagnosing BD. A 1H-NMR-based metabolomic study applying chemometrics of serum samples of Serbian patients with BD (33) and healthy controls (39) was explored, providing the identification of 22 metabolites for this disease. A biomarker set including threonine, aspartate, gamma-aminobutyric acid, 2-hydroxybutyric acid, serine, and mannose was established for the first time in BD serum samples by an NMR-based metabolomics study. Six identified metabolites (3-hydroxybutyric acid, arginine, lysine, tyrosine, phenylalanine, and glycerol) are in agreement with the previously determined NMR-based sets of serum biomarkers in Brazilian and/or Chinese patient samples. The same established metabolites (lactate, alanine, valine, leucine, isoleucine, glutamine, glutamate, glucose, and choline) in three different ethnic and geographic origins (Serbia, Brazil, and China) might have a crucial role in the realization of a universal set of NMR biomarkers for BD. Full article
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15 pages, 2760 KiB  
Article
Metabolomic Profiling in Mouse Model of Menopause-Associated Asthma
by William P. Pederson, Laurie M. Ellerman, Yan Jin, Haiwei Gu and Julie G. Ledford
Metabolites 2023, 13(4), 546; https://doi.org/10.3390/metabo13040546 - 11 Apr 2023
Cited by 2 | Viewed by 1726
Abstract
Menopause-associated asthma impacts a subset of women, tends to be more severe, and is less responsive to current treatments. We recently developed a model of menopause-associated asthma using 4-Vinylcyclohexene Diepoxide (VCD) and house dust mites (HDM). The goal of this study was to [...] Read more.
Menopause-associated asthma impacts a subset of women, tends to be more severe, and is less responsive to current treatments. We recently developed a model of menopause-associated asthma using 4-Vinylcyclohexene Diepoxide (VCD) and house dust mites (HDM). The goal of this study was to uncover potential biomarkers and drivers of menopause-onset asthma by assessing serum and bronchoalveolar lavage fluid (BALF) samples from mice with and without menopause and HDM challenge by large-scale targeted metabolomics. Female mice were treated with VCD/HDM to model menopause-associated asthma, and serum and BALF samples were processed for large-scale targeted metabolomic assessment. Liquid chromatography–tandem mass spectrometry (LC-MS/MS) was used to examine metabolites of potential biological significance. We identified over 50 individual metabolites, impacting 46 metabolic pathways, in the serum and BALF that were significantly different across the four study groups. In particular, glutamate, GABA, phosphocreatine, and pyroglutamic acid, which are involved in glutamate/glutamine, glutathione, and arginine and proline metabolisms, were significantly impacted in the menopausal HDM-challenged mice. Additionally, several metabolites had significant correlations with total airway resistance including glutamic acid, histamine, uridine, cytosine, cytidine, and acetamide. Using metabolic profiling, we identified metabolites and metabolic pathways that may aid in discriminating potential biomarkers for and drivers of menopause-associated asthma. Full article
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12 pages, 1185 KiB  
Article
Association of Metabolomic Biomarkers with Sleeve Gastrectomy Weight Loss Outcomes
by Wendy M. Miller, Kathryn M. Ziegler, Ali Yilmaz, Nazia Saiyed, Ilyas Ustun, Sumeyya Akyol, Jay Idler, Matthew D. Sims, Michael E. Maddens and Stewart F. Graham
Metabolites 2023, 13(4), 506; https://doi.org/10.3390/metabo13040506 - 31 Mar 2023
Cited by 2 | Viewed by 1345
Abstract
This prospective observational study aimed to evaluate the association of metabolomic alterations with weight loss outcomes following sleeve gastrectomy (SG). We evaluated the metabolomic profile of serum and feces prior to SG and three months post-SG, along with weight loss outcomes in 45 [...] Read more.
This prospective observational study aimed to evaluate the association of metabolomic alterations with weight loss outcomes following sleeve gastrectomy (SG). We evaluated the metabolomic profile of serum and feces prior to SG and three months post-SG, along with weight loss outcomes in 45 adults with obesity. The percent total weight loss for the highest versus the lowest weight loss tertiles (T3 vs. T1) was 17.0 ± 1.3% and 11.1 ± 0.8%, p < 0.001. Serum metabolite alterations specific to T3 at three months included a decrease in methionine sulfoxide concentration as well as alterations to tryptophan and methionine metabolism (p < 0.03). Fecal metabolite changes specific to T3 included a decrease in taurine concentration and perturbations to arachidonic acid metabolism, and taurine and hypotaurine metabolism (p < 0.002). Preoperative metabolites were found to be highly predictive of weight loss outcomes in machine learning algorithms, with an average area under the curve of 94.6% for serum and 93.4% for feces. This comprehensive metabolomics analysis of weight loss outcome differences post-SG highlights specific metabolic alterations as well as machine learning algorithms predictive of weight loss. These findings could contribute to the development of novel therapeutic targets to enhance weight loss outcomes after SG. Full article
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11 pages, 718 KiB  
Article
Global and Partial Effect Assessment in Metabolic Syndrome Explored by Metabolomics
by Marion Brandolini-Bunlon, Benoit Jaillais, Véronique Cariou, Blandine Comte, Estelle Pujos-Guillot and Evelyne Vigneau
Metabolites 2023, 13(3), 373; https://doi.org/10.3390/metabo13030373 - 2 Mar 2023
Viewed by 989
Abstract
In nutrition and health research, untargeted metabolomics is actually analyzed simultaneously with clinical data to improve prediction and better understand pathological status. This can be modeled using a multiblock supervised model with several input data blocks (metabolomics, clinical data) being potential predictors of [...] Read more.
In nutrition and health research, untargeted metabolomics is actually analyzed simultaneously with clinical data to improve prediction and better understand pathological status. This can be modeled using a multiblock supervised model with several input data blocks (metabolomics, clinical data) being potential predictors of the outcome to be explained. Alternatively, this configuration can be represented with a path diagram where the input blocks are each connected by links directed to the outcome—as in multiblock supervised modeling—and are also related to each other, thus allowing one to account for block effects. On the basis of a path model, we show herein how to estimate the effect of an input block, either on its own or conditionally to other(s), on the output response, respectively called “global” and “partial” effects, by percentages of explained variance in dedicated PLS regression models. These effects have been computed in two different path diagrams in a case study relative to metabolic syndrome, involving metabolomics and clinical data from an older men′s cohort (NuAge). From the two effects associated with each path, the results highlighted the complementary information provided by metabolomics to clinical data and, reciprocally, in the metabolic syndrome exploration. Full article
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11 pages, 1602 KiB  
Article
A Metabolomic Profile of Seminal Fluid in Extremely Severe Oligozoopermia Suggesting an Epididymal Involvement
by Orianne Serri, Magalie Boguenet, Juan Manuel Chao de la Barca, Pierre-Emmanuel Bouet, Hady El Hachem, Odile Blanchet, Pascal Reynier and Pascale May-Panloup
Metabolites 2022, 12(12), 1266; https://doi.org/10.3390/metabo12121266 - 15 Dec 2022
Cited by 4 | Viewed by 1148
Abstract
Male infertility has increased in the last decade. Pathophysiologic mechanisms behind extreme oligospermia (EO) are not yet fully understood. In new “omics” approaches, metabolomic can offer new information and help elucidate these mechanisms. We performed a metabolomics study of the seminal fluid (SF) [...] Read more.
Male infertility has increased in the last decade. Pathophysiologic mechanisms behind extreme oligospermia (EO) are not yet fully understood. In new “omics” approaches, metabolomic can offer new information and help elucidate these mechanisms. We performed a metabolomics study of the seminal fluid (SF) in order to understand the mechanisms implicated in EO. We realized a targeted quantitative analysis using high performance liquid chromatography and mass spectrometry to compare the SF metabolomic profile of 19 men with EO with that of 22 men with a history of vasectomy (V) and 20 men with normal semen parameters (C). A total of 114 metabolites were identified. We obtained a multivariate OPLS-DA model discriminating the three groups. Signatures show significantly higher levels of amino acids and polyamines in C group. The sum of polyunsaturated fatty acids and free carnitine progressively decrease between the three groups (C > EO > V) and sphingomyelins are significantly lower in V group. Our signature characterizing EO includes metabolites already linked to infertility in previous studies. The similarities between the signatures of the EO and V groups are clear evidence of epididymal dysfunction in the case of testicular damage. This study shows the complexity of the metabolomic dysfunction occurring in the SF of EO men and underlines the importance of metabolomics in understanding male infertility. Full article
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17 pages, 2119 KiB  
Protocol
Sphingolipids in Childhood Asthma and Obesity (SOAP Study): A Protocol of a Cross-Sectional Study
by Belavendra Antonisamy, Harshita Shailesh, Yahya Hani, Lina Hayati M. Ahmed, Safa Noor, Salma Yahya Ahmed, Mohamed Alfaki, Abidan Muhayimana, Shana Sunny Jacob, Saroja Kotegar Balayya, Oleksandr Soloviov, Li Liu, Lisa Sara Mathew, Kun Wang, Sara Tomei, Alia Al Massih, Rebecca Mathew, Mohammed Yousuf Karim, Manjunath Ramanjaneya, Stefan Worgall and Ibrahim A. Janahiadd Show full author list remove Hide full author list
Metabolites 2023, 13(11), 1146; https://doi.org/10.3390/metabo13111146 - 11 Nov 2023
Viewed by 1416
Abstract
Asthma and obesity are two of the most common chronic conditions in children and adolescents. There is increasing evidence that sphingolipid metabolism is altered in childhood asthma and is linked to airway hyperreactivity. Dysregulated sphingolipid metabolism is also reported in obesity. However, the [...] Read more.
Asthma and obesity are two of the most common chronic conditions in children and adolescents. There is increasing evidence that sphingolipid metabolism is altered in childhood asthma and is linked to airway hyperreactivity. Dysregulated sphingolipid metabolism is also reported in obesity. However, the functional link between sphingolipid metabolism, asthma, and obesity is not completely understood. This paper describes the protocol of an ongoing study on sphingolipids that aims to examine the pathophysiology of sphingolipids in childhood asthma and obesity. In addition, this study aims to explore the novel biomarkers through a comprehensive multi-omics approach including genomics, genome-wide DNA methylation, RNA-Seq, microRNA (miRNA) profiling, lipidomics, metabolomics, and cytokine profiling. This is a cross-sectional study aiming to recruit 440 children from different groups: children with asthma and normal weight (n = 100), asthma with overweight or obesity (n = 100), overweight or obesity (n = 100), normal weight (n = 70), and siblings of asthmatic children with normal weight, overweight, or obesity (n = 70). These participants will be recruited from the pediatric pulmonology, pediatric endocrinology, and general pediatric outpatient clinics at Sidra Medicine, Doha, Qatar. Information will be obtained from self-reported questionnaires on asthma, quality of life, food frequency (FFQ), and a 3-day food diary that are completed by the children and their parents. Clinical measurements will include anthropometry, blood pressure, biochemistry, bioelectrical impedance, and pulmonary function tests. Blood samples will be obtained for sphingolipid analysis, serine palmitoyltransferase (SPT) assay, whole-genome sequencing (WGS), genome-wide DNA methylation study, RNA-Seq, miRNA profiling, metabolomics, lipidomics, and cytokine analysis. Group comparisons of continuous outcome variables will be carried out by a one-way analysis of variance or the Kruskal–Wallis test using an appropriate pairwise multiple comparison test. The chi-squared test or a Fisher’s exact test will be used to test the associations between categorical variables. Finally, multivariate analysis will be carried out to integrate the clinical data with multi-omics data. This study will help us to understand the role of dysregulated sphingolipid metabolism in obesity and asthma. In addition, the multi-omics data from the study will help to identify novel genetic and epigenetic signatures, inflammatory markers, and mechanistic pathways that link asthma and obesity in children. Furthermore, the integration of clinical and multi-omics data will help us to uncover the potential interactions between these diseases and to offer a new paradigm for the treatment of pediatric obesity-associated asthma. Full article
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