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[Preliminary exploration of the metabolic profile and metabolic pathways in newly diagnosed multiple myeloma].
Huang, Q L; Zhao, R R; Yang, B Y; Jiang, R Y; Yang, L L; Yan, S; Fu, Z Z; Wu, D P; Wu, X J.
Affiliation
  • Huang QL; Department of Hematology, the First Affiliated Hospital of Hainan Medical College, Haikou 570102, China.
  • Zhao RR; Department of Hematology, the First Affiliated Hospital of Soochow University, Suzhou 215006, China.
  • Yang BY; Department of Hematology, the First Affiliated Hospital of Soochow University, Suzhou 215006, China.
  • Jiang RY; Department of Hematology, the First Affiliated Hospital of Soochow University, Suzhou 215006, China.
  • Yang LL; Department of Hematology, the First Affiliated Hospital of Soochow University, Suzhou 215006, China.
  • Yan S; Department of Hematology, the First Affiliated Hospital of Soochow University, Suzhou 215006, China.
  • Fu ZZ; Department of Hematology, the First Affiliated Hospital of Soochow University, Suzhou 215006, China.
  • Wu DP; Department of Hematology, the First Affiliated Hospital of Soochow University, Suzhou 215006, China.
  • Wu XJ; Department of Hematology, the First Affiliated Hospital of Soochow University, Suzhou 215006, China.
Zhonghua Zhong Liu Za Zhi ; 44(12): 1369-1375, 2022 Dec 23.
Article in Zh | MEDLINE | ID: mdl-36575789
ABSTRACT

Objective:

To explore the metabolite profile and metabolic pathways of newly diagnosed multiple myeloma (MM).

Methods:

Gas chromatography-mass spectrometry (GC-MS) was employed for the high-throughput detection and identification of serum samples from 55 patients with MM and 37 healthy controls matched for age and sex from 2016 to 2017 collected at the First Affiliated Hospital of Soochow University. The relative standard deviation (RSD) of quality control (QC) samples was employed to validate the reproducibility of GC-MS approach. The differential metabolites between patients with MM and healthy controls were detected by partial least squares discrimination analysis (PLS-DA), and t-test with false discovery rate (FDR) correction. Metabolomics pathway analysis (MetPA) was employed to construct metabolic pathways.

Results:

There were 55 MM patients, including 34 males and 21 females. The median age was 60 years old (42-73 years old). There were 30 cases of IgG type, 9 cases of IgA type, 1 case of IgM type, 2 cases of non-secreted type, 1 case of double clone type and 12 cases of light chain type, including 3 cases of kappa light chain type and 9 cases of lambda light chain type. The result of QC sample test showed that the proportion of compounds with the RSD of the relative content of metabolites < 15% was 70.21% obtained by the reproducibility of GC-MS experimental data, which implied that the experimental data were reliable. A total of 17 metabolites were screened differently with the healthy control group, including myristic acid, hydroxyproline, cysteine, palmitic acid, L-leucine, stearic acid, methionine, phenylalanine, glycerin, serine, isoleucine, tyrosine, valine, citric acid, inositol, threonine, and oxalic acid (VIP>1, P<0.05). Metabolic pathway analysis suggested that metabolic disorders in MM patients comprised mainly phenylalanine metabolism, glyoxylic acid and dicarboxylic acid metabolism, phosphoinositide metabolism, cysteine and methionine metabolism, glycerolipid metabolism, glycine, serine, and threonine metabolism.

Conclusion:

Compared with normal people, patients with newly diagnosed MM have obvious differences in metabolic profiles and metabolic pathways.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Cysteine / Multiple Myeloma Type of study: Diagnostic_studies / Prognostic_studies Limits: Adult / Aged / Female / Humans / Male / Middle aged Language: Zh Journal: Zhonghua Zhong Liu Za Zhi Year: 2022 Type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Cysteine / Multiple Myeloma Type of study: Diagnostic_studies / Prognostic_studies Limits: Adult / Aged / Female / Humans / Male / Middle aged Language: Zh Journal: Zhonghua Zhong Liu Za Zhi Year: 2022 Type: Article Affiliation country: China