Mass spectrometry-based metabolomics for an in-depth questioning of human health

Alvès, Sandra; Paris, Alain; Rathahao‐Paris, Estelle

doi:10.1016/bs.acc.2020.02.009

Cited by 10 publications

(9 citation statements)

References 132 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Metabolomics, an innovative analytical profiling technique, aims to detect the whole set of metabolites of low molecular weight present in body fluid. In recent years, it has already shown great potential in exploring the physiological status of healthy populations and in discovering subtle metabolic discrepancies in some specific disorders ( 1 – 4 ).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Urinary Metabolomic Study in a Healthy Children Population and Metabolic Biomarker Discovery of Attention-Deficit/Hyperactivity Disorder (ADHD)

et al. 2022

View full text Add to dashboard Cite

ObjectivesKnowledge of the urinary metabolomic profiles of healthy children and adolescents plays a promising role in the field of pediatrics. Metabolomics has also been used to diagnose disease, discover novel biomarkers, and elucidate pathophysiological pathways. Attention-deficit/hyperactivity disorder (ADHD) is one of the most common psychiatric disorders in childhood. However, large-sample urinary metabolomic studies in children with ADHD are relatively rare. In this study, we aimed to identify specific biomarkers for ADHD diagnosis in children and adolescents by urinary metabolomic profiling.MethodsWe explored the urine metabolome in 363 healthy children aged 1–18 years and 76 patients with ADHD using high-resolution mass spectrometry.ResultsMetabolic pathways, such as arachidonic acid metabolism, steroid hormone biosynthesis, and catecholamine biosynthesis, were found to be related to sex and age in healthy children. The urinary metabolites displaying the largest differences between patients with ADHD and healthy controls belonged to the tyrosine, leucine, and fatty acid metabolic pathways. A metabolite panel consisting of FAPy-adenine, 3-methylazelaic acid, and phenylacetylglutamine was discovered to have good predictive ability for ADHD, with a receiver operating characteristic area under the curve (ROC–AUC) of 0.918. A panel of FAPy-adenine, N-acetylaspartylglutamic acid, dopamine 4-sulfate, aminocaproic acid, and asparaginyl-leucine was used to establish a robust model for ADHD comorbid tic disorders and controls with an AUC of 0.918.

show abstract

Section: Introductionmentioning

confidence: 99%

“…Urine can potentially provide crucial metabolic information. The applications of urine metabolomics are very promising in biomarker discovery for disease etiology, diagnosis, and prognosis ( 4 , 23 ). However, there have been fewer urinary metabolomic studies on childhood ADHD.…”

Section: Introductionmentioning

confidence: 99%

Urinary Metabolomic Study in a Healthy Children Population and Metabolic Biomarker Discovery of Attention-Deficit/Hyperactivity Disorder (ADHD)

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Untargeted and targeted approaches are the two analytical strategies commonly used in metabolomics (29). The untargeted approach detects metabolites without an a priori hypothesis and is more suitable for studies focused on assessing potential biomarkers or metabolic mechanisms for diseases (29)(30)(31)(32). The targeted approach analyzes the specific kind of metabolites and the relative metabolic pathways with a priori information and is used for biomarker validation and studying a specific biological pathway (29)(30)(31)(32).…”

Section: Metabolomics In Gestational Diabetes Mellitus Studiesmentioning

confidence: 99%

Perspectives from metabolomics in the early diagnosis and prognosis of gestational diabetes mellitus

Zhang

Yang²

2022

Front. Endocrinol.

View full text Add to dashboard Cite

Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders in pregnant women. The early detection of GDM provides an opportunity for the effective treatment of hyperglycemia in pregnancy, thus decreasing the risk of adverse perinatal outcomes for mothers and newborns. Metabolomics, an emerging technique, offers a novel point of view in understanding the onset and development of diseases and has been repeatedly used in various gestational periods in recent studies of GDM. Moreover, metabolomics provides varied opportunities in the different diagnoses of GDM from prediabetes or predisposition to diabetes, the diagnosis of GDM at a gestational age several weeks earlier than that used in the traditional method, and the assessment of prognosis considering the physiologic subtypes of GDM and clinical indexes. Longitudinal metabolomics truly facilitates the dynamic monitoring of metabolic alterations over the course of pregnancy. Herein, we review recent advancements in metabolomics and summarize evidence from studies on the application of metabolomics in GDM, highlighting the aspects of the diagnosis and differential diagnoses of GDM in an early stage. We also discuss future study directions concerning the physiologic subtypes, prognosis, and limitations of metabolomics.

show abstract

“…Methodologically, metabolomics strategies can be supported by several techniques, namely nuclear magnetic resonance “spectroscopy” (NMR) [ 21 ], liquid chromatography coupled to mass spectrometry (LC–MS) and gas chromatography coupled to mass spectrometry (GC–MS) [ 20 , 22 ]. LC–MS has possibly been the most used technique because it offers greater sensitivity in the identification of metabolites [ 15 , 23 ].…”

Section: Introductionmentioning

confidence: 99%

Metabolic Phenotypes in Asthmatic Adults: Relationship with Inflammatory and Clinical Phenotypes and Prognostic Implications

et al. 2021

View full text Add to dashboard Cite

Bronchial asthma is a chronic disease that affects individuals of all ages. It has a high prevalence and is associated with high morbidity and considerable levels of mortality. However, asthma is not a single disease, and multiple subtypes or phenotypes (clinical, inflammatory or combinations thereof) can be detected, namely in aggregated clusters. Most studies have characterised asthma phenotypes and clusters of phenotypes using mainly clinical and inflammatory parameters. These studies are important because they may have clinical and prognostic implications and may also help to tailor personalised treatment approaches. In addition, various metabolomics studies have helped to further define the metabolic features of asthma, using electronic noses or targeted and untargeted approaches. Besides discriminating between asthma and a healthy state, metabolomics can detect the metabolic signatures associated with some asthma subtypes, namely eosinophilic and non-eosinophilic phenotypes or the obese asthma phenotype, and this may prove very useful in point-of-care application. Furthermore, metabolomics also discriminates between asthma and other “phenotypes” of chronic obstructive airway diseases, such as chronic obstructive pulmonary disease (COPD) or Asthma–COPD Overlap (ACO). However, there are still various aspects that need to be more thoroughly investigated in the context of asthma phenotypes in adequately designed, homogeneous, multicentre studies, using adequate tools and integrating metabolomics into a multiple-level approach.

show abstract

Mass spectrometry-based metabolomics for an in-depth questioning of human health

Cited by 10 publications

References 132 publications

Urinary Metabolomic Study in a Healthy Children Population and Metabolic Biomarker Discovery of Attention-Deficit/Hyperactivity Disorder (ADHD)

Urinary Metabolomic Study in a Healthy Children Population and Metabolic Biomarker Discovery of Attention-Deficit/Hyperactivity Disorder (ADHD)

Perspectives from metabolomics in the early diagnosis and prognosis of gestational diabetes mellitus

Metabolic Phenotypes in Asthmatic Adults: Relationship with Inflammatory and Clinical Phenotypes and Prognostic Implications

Contact Info

Product

Resources

About