Review
Cardiac & Cardiovascular Systems
Alessandro Di Minno, Monica Gelzo, Mariano Stornaiuolo, Margherita Ruoppolo, Giuseppe Castaldo
Summary: Untargeted Metabolomics and targeted Metabolomics have made significant progress in the field of life sciences, particularly in the discovery of biomarkers. Expertise in laboratory medicine and bioinformatics helps address challenges and biases in metabolite profiling. Clinical validation and profitability testing are essential steps in identifying potential biomarkers.
NUTRITION METABOLISM AND CARDIOVASCULAR DISEASES
(2021)
Article
Health Care Sciences & Services
Oxana P. Trifonova, Dmitry L. Maslov, Elena E. Balashova, Steven Lichtenberg, Petr G. Lokhov
Summary: Diabetic nephropathy is a common complication of diabetes that requires early diagnosis. Using metabolomics analysis, researchers identified a combination of 15 compounds that showed high accuracy in diagnosing DN, particularly in the late stage, with a diagnostic performance of up to 99%.
JOURNAL OF PERSONALIZED MEDICINE
(2022)
Article
Biochemical Research Methods
Hanne Bendiksen Skogvold, Elise Mork Sandas, Anja Osteby, Camilla Lokken, Helge Rootwelt, Per Ola Ronning, Steven Ray Wilson, Katja Benedikte Presto Elgstoen
Summary: A single LC-MS method was developed for DBS metabolite analysis in clinical applications such as newborn screening, allowing for simultaneous analysis of a wide range of metabolites. The method utilized a diphenyl column, a multi-linear solvent gradient, and tailored MS settings to enhance sensitivity and reproducibility for diverse metabolites. The performance of the method was suitable for both untargeted and targeted approaches in clinically relevant experiments.
JOURNAL OF PROTEOME RESEARCH
(2021)
Article
Biochemistry & Molecular Biology
Michiel Bongaerts, Ramon Bonte, Serwet Demirdas, Edwin H. Jacobs, Esmee Oussoren, Ans T. van der Ploeg, Margreet A. E. M. Wagenmakers, Robert M. W. Hofstra, Henk J. Blom, Marcel J. T. Reinders, George J. G. Ruijter
Summary: Untargeted metabolomics is crucial in the laboratory diagnosis of inborn errors of metabolism, but faces challenges with batch effects. Researchers have proposed a new normalization method, Metchalizer, which shows promising performance in batch effect removal and biomarker detection, performing at least similarly to other approaches.
Article
Chemistry, Analytical
Eliska Ivanovova, Barbora Pisklakova, Dana Dobesova, Ales Kvasnicka, David Friedecky
Summary: Diagnosing a large group of inborn errors of metabolism poses a challenge for physicians due to non-specific clinical symptoms, leading to the importance of laboratory methods for differential diagnosis. Liquid chromatography and mass spectrometry (LC-MS) technology has significantly expanded diagnostic possibilities in the last two decades. It has been used for multicomponent analysis of metabolites, as well as successfully applied in metabolomics and lipidomics to discover new potential biomarkers.
MICROCHEMICAL JOURNAL
(2021)
Article
Multidisciplinary Sciences
Bennett W. Fox, Olga Ponomarova, Yong-Uk Lee, Gaotian Zhang, Gabrielle E. Giese, Melissa Walker, Nicole M. Roberto, Huimin Na, Pedro R. Rodrigues, Brian J. Curtis, Aiden R. Kolodziej, Timothy A. Crombie, Stefan Zdraljevic, L. Safak Yilmaz, Erik C. Andersen, Frank C. Schroeder, Albertha J. M. Walhout
Summary: Individuals can exhibit differences in metabolism caused by genetic background, nutritional input, microbiota and other environmental factors. This study used the nematode Caenorhabditis elegans to explore inter-individual variation in metabolism and discovered differences in the abundances of known and unknown metabolites, including conjugates between 3-hydroxypropionate (3HP) and amino acids. The accumulation of these conjugates was found to be caused by genetic variation in the HPHD-1 gene.
Article
Biochemistry & Molecular Biology
Michiel Bongaerts, Purva Kulkarni, Alan Zammit, Ramon Bonte, Leo A. J. Kluijtmans, Henk J. J. Blom, Udo F. H. Engelke, David M. J. Tax, George J. G. Ruijter, Marcel J. T. Reinders
Summary: In this study, we assessed different outlier detection methods for identifying patients with inborn errors of metabolism (IEM) using untargeted metabolomics data. We found significant variations in IEM detection performance among the methods tested, with DeepSVDD and R-graph performing the most consistently across three metabolomics datasets. We also demonstrated the importance of performing a PCA transform prior to outlier detection to improve the performance of several methods. While some methods showed clinically satisfying performances in detecting IEM patients in one dataset, further improvements are still needed for more consistent results.
Article
Genetics & Heredity
Elise A. Ferreira, Annemarijne R. J. Veenvliet, Udo F. H. Engelke, Leo A. J. Kluijtmans, Marleen C. D. G. Huigen, Brechtje Hoegen, Lonneke de Boer, Maaike C. de Vries, Bregje W. van Bon, Erika Leenders, Elisabeth A. M. Cornelissen, Charlotte A. Haaxma, Jolanda H. Schieving, M. Estela Rubio-Gozalbo, Irene M. L. W. Korver-Keularts, Lara M. Marten, Susann Diegmann, Jeroen Mourmans, Alexander J. M. Rennings, Clara D. M. van Karnebeek, Richard J. Rodenburg, Karlien L. M. Coene
Summary: This article discusses the application of gene function tests in the diagnosis of patients with inherited metabolic disorders (IMDs), highlighting the value of metabolomics-based analysis in enhancing diagnostic success and improving clinical management.
GENETICS IN MEDICINE
(2023)
Article
Chemistry, Analytical
Isabel Meister, Pei Zhang, Anirban Sinha, C. Magnus Skold, Asa M. Wheelock, Takashi Izumi, Romanas Chaleckis, Craig E. Wheelock
Summary: This study developed a method for measuring specific gravity in urine using a refractive index detector (RID) in a 96-well-plate format, providing a new solution for metabolomic research on this noninvasive biofluid. By developing an automated LC-MS workflow and utilizing multiple technical internal standards to monitor data quality, over 540 urinary metabolites were successfully identified.
ANALYTICAL CHEMISTRY
(2021)
Article
Biochemical Research Methods
Reyhan Sonmez Flitman, Bita Khalili, Zoltan Kutalik, Rico Rueedi, Anneke Bruemmer, Sven Bergmann
Summary: This study identified genes influencing human metabolite concentrations through metabolome-wide and transcriptome-wide association study. The findings highlighted potential causal relationships between gene expression and metabolite concentrations, with some genes showing significant associations with specific metabolites. Mendelian randomization analysis supported the causal links between gene expression and metabolite concentrations, while also revealing reverse causal effects in some cases. The integration of metabolomics, gene expression, and genetic data proved to be effective in pinpointing causal genes modulating metabolite concentrations.
JOURNAL OF PROTEOME RESEARCH
(2021)
Article
Pharmacology & Pharmacy
Serena Correnti, Mariaimmacolata Preiano, Annalisa Fregola, Fabia Gamboni, Daniel Stephenson, Rocco Savino, Angelo D'Alessandro, Rosa Terracciano
Summary: Male infertility is a significant global concern, and traditional semen analysis is inadequate for diagnosis. Metabolomics profiling has become a valuable diagnostic tool in various diseases. This study identified a new pattern of biomarkers for male infertility through metabolomics and lipidomics analysis of seminal plasma samples.
FRONTIERS IN PHARMACOLOGY
(2023)
Article
Pediatrics
Esme Dunne, Daniel O'Reilly, Claire A. Murphy, Caoimhe Howard, Grainne Kelleher, Thomas Suttie, Michael A. Boyle, Jennifer J. Brady, Ina Knerr, Afif El Khuffash
Summary: Inborn errors of metabolism are rare but significant causes of mortality and morbidity in neonates. This study examines the contribution of newborn screening programs and clinician-initiated targeted biochemical screening to the identification of these errors. It also explores factors that may affect the reliability of metabolic testing in this population.
EUROPEAN JOURNAL OF PEDIATRICS
(2022)
Article
Endocrinology & Metabolism
Laura K. M. Steinbusch, Ping Wang, Huub W. A. H. Waterval, Fons A. P. M. Stassen, Karlien L. M. Coene, Udo F. H. Engelke, Daphna D. J. Habets, Jorgen Bierau, Irene M. L. W. Korver-Keularts
Summary: The study developed an innovative targeted urine metabolomics screening procedure for accelerating the diagnosis of patients with inborn errors of metabolism (IEM). By analyzing urinary samples, it is possible to quickly and accurately diagnose the disease phenotypes of patients, particularly for complex metabolic disorders, with high diagnostic efficiency.
JOURNAL OF INHERITED METABOLIC DISEASE
(2021)
Article
Biochemistry & Molecular Biology
Anna Maria Timperio, Federica Gevi, Francesca Cucinotta, Arianna Ricciardello, Laura Turriziani, Maria Luisa Scattoni, Antonio M. Persico
Summary: This study compares the urinary metabolomic differences between a child with idiopathic ASD and his/her typically-developing sibling, and highlights the involvement of purine and tryptophan pathways, as well as abnormalities in phenylalanine, tyrosine, and tryptophan pathways in ASD. It also emphasizes the excess of gut microbiota-derived compounds in ASD, which could have diagnostic value in differentiating the metabolome of autistic and unaffected siblings. Furthermore, it suggests the existence of a metabolic autism spectrum with unaffected siblings displaying an intermediate metabolic profile between autistic siblings and typically-developing controls.
Article
Biochemical Research Methods
Belen Callejon-Leblic, Marta Selma-Royo, Maria Carmen Collado, Jose Luis Gomez-Ariza, Nieves Abril, Tamara Garcia-Barrera
Summary: In this study, the interaction between selenium intake, gut microbiota, and metabolites was investigated. Significant differences in gut metabolites were observed in mice after selenium supplementation, indicating the important effect of selenium on microbiota metabolism. The correlation analysis revealed associations between metabolites and gut bacterial profiles, with a higher abundance of Lactobacillus spp. associated with specific metabolite levels.
JOURNAL OF PROTEOME RESEARCH
(2022)