GC × GC-TOFMS metabolomics analysis identifies elevated levels of plasma sugars and sugar alcohols in diabetic mellitus patients with kidney failure
1
Issued Date
2022-10-01
Resource Type
ISSN
00219258
eISSN
1083351X
Scopus ID
2-s2.0-85139348982
Pubmed ID
36055403
Journal Title
Journal of Biological Chemistry
Volume
298
Issue
10
Rights Holder(s)
SCOPUS
Bibliographic Citation
Journal of Biological Chemistry Vol.298 No.10 (2022)
Suggested Citation
Duangkumpha K., Jariyasopit N., Wanichthanarak K., Dhakal E., Wisanpitayakorn P., Thotsiri S., Sirivatanauksorn Y., Kitiyakara C., Sathirapongsasuti N., Khoomrung S. GC × GC-TOFMS metabolomics analysis identifies elevated levels of plasma sugars and sugar alcohols in diabetic mellitus patients with kidney failure. Journal of Biological Chemistry Vol.298 No.10 (2022). doi:10.1016/j.jbc.2022.102445 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/87116
Title
GC × GC-TOFMS metabolomics analysis identifies elevated levels of plasma sugars and sugar alcohols in diabetic mellitus patients with kidney failure
Other Contributor(s)
Abstract
Two dimensional GC (GC × GC)–time-of-flight mass spectrometry (TOFMS) has been used to improve accurate metabolite identification in the chemical industry, but this method has not been applied as readily in biomedical research. Here, we evaluated and validated the performance of high resolution GC × GC-TOFMS against that of GC-TOFMS for metabolomics analysis of two different plasma matrices, from healthy controls (CON) and diabetes mellitus (DM) patients with kidney failure (DM with KF). We found GC × GC-TOFMS outperformed traditional GC-TOFMS in terms of separation performance and metabolite coverage. Several metabolites from both the CON and DM with KF matrices, such as carbohydrates and carbohydrate-conjugate metabolites, were exclusively detected using GC × GC-TOFMS. Additionally, we applied this method to characterize significant metabolites in the DM with KF group, with focused analysis of four metabolite groups: sugars, sugar alcohols, amino acids, and free fatty acids. Our plasma metabolomics results revealed 35 significant metabolites (12 unique and 23 concentration-dependent metabolites) in the DM with KF group, as compared with those in the CON and DM groups (N = 20 for each group). Interestingly, we determined 17 of the 35 (14/17 verified with reference standards) significant metabolites identified from both the analyses were metabolites from the sugar and sugar alcohol groups, with significantly higher concentrations in the DM with KF group than in the CON and DM groups. Enrichment analysis of these 14 metabolites also revealed that alterations in galactose metabolism and the polyol pathway are related to DM with KF. Overall, our application of GC × GC-TOFMS identified key metabolites in complex plasma matrices.