Research Article

Abnormal metabolites related to bone marrow failure in aplastic anemia patients

Published: October 29, 2015
Genet. Mol. Res. 14 (4) : 13709-13718 DOI: https://doi.org/10.4238/2015.October.28.33
Cite this Article:
(2015). Abnormal metabolites related to bone marrow failure in aplastic anemia patients. Genet. Mol. Res. 14(4): gmr6454. https://doi.org/10.4238/2015.October.28.33
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Abstract

Metabolomics is the identification and quantitation of small molecules that are involved in metabolic reactions. Liquid chromatography-mass spectrometry (LC-MS) has enjoyed growing popularity as the platform for metabolomic studies due to high throughput, soft ionization, and good coverage of metabolites. Serum metabolites of aplastic anemia (AA) patients and healthy controls were investigated using LC-MS. A wavelet-based method was utilized to find and align LC-MS peaks. Principal component analysis, partial least squares discriminant analysis, and optimized potential for liquid simulations were used to identify differences in metabolite levels, and to reveal useful biomarkers. Thirty-two metabolites that were significantly altered were detected. Of these metabolites, 23 were successfully identified. In AA patients, metabolites involved amino acid biosynthesis, aminoacyl-tRNA biosynthesis, and ATP-binding cassette transporters were higher than normal, while the levels of metabolites involved in TCA cycles were lower than normal. These changes may be the primary cause or result of bone marrow failure in patients with AA.

Metabolomics is the identification and quantitation of small molecules that are involved in metabolic reactions. Liquid chromatography-mass spectrometry (LC-MS) has enjoyed growing popularity as the platform for metabolomic studies due to high throughput, soft ionization, and good coverage of metabolites. Serum metabolites of aplastic anemia (AA) patients and healthy controls were investigated using LC-MS. A wavelet-based method was utilized to find and align LC-MS peaks. Principal component analysis, partial least squares discriminant analysis, and optimized potential for liquid simulations were used to identify differences in metabolite levels, and to reveal useful biomarkers. Thirty-two metabolites that were significantly altered were detected. Of these metabolites, 23 were successfully identified. In AA patients, metabolites involved amino acid biosynthesis, aminoacyl-tRNA biosynthesis, and ATP-binding cassette transporters were higher than normal, while the levels of metabolites involved in TCA cycles were lower than normal. These changes may be the primary cause or result of bone marrow failure in patients with AA.

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