Srivastava J, Trivedi R, Saxena P, Yadav S, Gupta R, Nityanand S, Kumar D, Chaturvedi CP. Bone marrow plasma metabonomics of idiopathic acquired aplastic anemia patients using 1H nuclear magnetic resonance spectroscopy.
Metabolomics 2023;
19:94. [PMID:
37975930 DOI:
10.1007/s11306-023-02056-0]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 10/10/2023] [Indexed: 11/19/2023]
Abstract
INTRODUCTION
Idiopathic acquired aplastic anemia (AA) is a bone marrow failure disorder where aberrant T-cell functions lead to depletion of hematopoietic stem and progenitor cells in the bone marrow (BM) microenvironment. T-cells undergo metabolic rewiring, which regulates their proliferation and differentiation. Therefore, studying metabolic variation in AA patients may aid us with a better understanding of the T-cell regulatory pathways governed by metabolites and their pathological engagement in the disease.
OBJECTIVE
To identify the differential metabolites in BM plasma of AA patients, AA follow-up (AAF) in comparison to normal controls (NC) and to identify potential disease biomarker(s).
METHODS
The study used 1D 1H NMR Carr-Purcell-Meiboom-Gill (CPMG) spectra to identify the metabolites present in the BM plasma samples of AA (n = 40), AAF (n = 16), and NC (n = 20). Metabolic differences between the groups and predictive biomarkers were identified by using multivariate analysis and receiver operating characteristic (ROC) module of Metaboanalyst V5.0 tool, respectively.
RESULTS
The AA and AAF samples were well discriminated from NC group as per Principal Component analysis (PCA). Further, we found significant alteration in the levels of 17 metabolites in AA involved in amino-acid (Leucine, serine, threonine, phenylalanine, lysine, histidine, valine, tyrosine, and proline), carbohydrate (Glucose, lactate and mannose), fatty acid (Acetate, glycerol myo-inositol and citrate), and purine metabolism (hypoxanthine) in comparison to NC. Additionally, biomarker analysis predicted Hypoxanthine and Acetate can be used as a potential biomarker.
CONCLUSION
The study highlights the significant metabolic alterations in the BM plasma of AA patients which may have implication in the disease pathobiology.
Collapse