BACKGROUND: We applied untargeted mass spectrometry-based metabolomics to the diseases methylmalonic acidemia (MMA) and propionic acidemia (PA). METHODS: We used a screening platform that used untargeted, mass-based metabolomics of methanol-extracted plasma to find significantly different molecular features in human plasma samples from MMA and PA patients and from healthy individuals. Capillary reverse phase liquid chromatography (4 microL/min) was interfaced to a TOF mass spectrometer, and data were processed using nonlinear alignment software (XCMS) and an online database (METLIN) to find and identify metabolites differentially regulated in disease. RESULTS: Of the approximately 3500 features measured, propionyl carnitine was easily identified as the best biomarker of disease (P value 1.3 x 10(-18)), demonstrating the proof-of-concept use of untargeted metabolomics in clinical chemistry discovery. Five additional acylcarnitine metabolites showed significant differentiation between plasma from patients and healthy individuals, and gamma-butyrobetaine was highly increased in a subset of patients. Two acylcarnitine metabolites and numerous unidentified species differentiate MMA and PA. Many metabolites that do not appear in any public database, and that remain unidentified, varied significantly between normal, MMA, and PA, underscoring the complex downstream metabolic effects resulting from the defect in a single enzyme. CONCLUSIONS: This proof-of-concept study demonstrates that metabolomics can expand the range of metabolites associated with human disease and shows that this method may be useful for disease diagnosis and patient clinical evaluation.
BACKGROUND: We applied untargeted mass spectrometry-based metabolomics to the diseases methylmalonic acidemia (MMA) and propionic acidemia (PA). METHODS: We used a screening platform that used untargeted, mass-based metabolomics of methanol-extracted plasma to find significantly different molecular features in human plasma samples from MMA and PA patients and from healthy individuals. Capillary reverse phase liquid chromatography (4 microL/min) was interfaced to a TOF mass spectrometer, and data were processed using nonlinear alignment software (XCMS) and an online database (METLIN) to find and identify metabolites differentially regulated in disease. RESULTS: Of the approximately 3500 features measured, propionyl carnitine was easily identified as the best biomarker of disease (P value 1.3 x 10(-18)), demonstrating the proof-of-concept use of untargeted metabolomics in clinical chemistry discovery. Five additional acylcarnitine metabolites showed significant differentiation between plasma from patients and healthy individuals, and gamma-butyrobetaine was highly increased in a subset of patients. Two acylcarnitine metabolites and numerous unidentified species differentiate MMA and PA. Many metabolites that do not appear in any public database, and that remain unidentified, varied significantly between normal, MMA, and PA, underscoring the complex downstream metabolic effects resulting from the defect in a single enzyme. CONCLUSIONS: This proof-of-concept study demonstrates that metabolomics can expand the range of metabolites associated with human disease and shows that this method may be useful for disease diagnosis and patient clinical evaluation.
Authors: Kirkland A Wilson; Yong Han; Miaoqi Zhang; Jeremy P Hess; Kimberly A Chapman; Gary W Cline; Gregory P Tochtrop; Henri Brunengraber; Guo-Fang Zhang Journal: Am J Physiol Endocrinol Metab Date: 2017-06-20 Impact factor: 4.310
Authors: Erica L-W Majumder; Elizabeth M Billings; H Paul Benton; Richard L Martin; Amelia Palermo; Carlos Guijas; Markus M Rinschen; Xavier Domingo-Almenara; J Rafael Montenegro-Burke; Bradley A Tagtow; Robert S Plumb; Gary Siuzdak Journal: Nat Protoc Date: 2021-01-22 Impact factor: 13.491
Authors: William R Wikoff; Samir Hanash; Brian DeFelice; Suzanne Miyamoto; Matt Barnett; Yang Zhao; Gary Goodman; Ziding Feng; David Gandara; Oliver Fiehn; Ayumu Taguchi Journal: J Clin Oncol Date: 2015-08-17 Impact factor: 44.544
Authors: Bridgit Crews; William R Wikoff; Gary J Patti; Hin-Koon Woo; Ewa Kalisiak; Johanna Heideker; Gary Siuzdak Journal: Anal Chem Date: 2009-10-15 Impact factor: 6.986