A novel GC-MS method in urinary estrogen analysis from postmenopausal women with osteoporosis

Ju Yeon Moon, Kwang Joon Kim, Myeong Hee Moon, Bong Chul Chung, Man Ho Choi

Research output: Contribution to journalArticlepeer-review

32 Citations (Scopus)

Abstract

Estrogen metabolites play important roles in the development of female-related disorders and homeostasis of the bone. To improve detectability, a validated gas chromatography-mass spectrometry (GC-MS) method was conducted with two-phase extractive ethoxycarbonlyation (EOC) and subsequent pentafluoropropionyl (PFP) derivatization was introduced. The resulting samples were separated through a high-temperature MXT-1 column within an 8 min run and were detected in the selected ion monitoring (SIM) mode. The optimized analytical conditions led to good separation with a symmetric peak shape for 19 estrogens as their EOC-PFP derivatives. The limit of quantification (LOQ) was from 0.02 to ∼ 0.1 ng/ml for most estrogens analyzed, except for 2-hydroxyestriol (0.5 ng/ml). The devised method was found to be linear (r 2 > 0.995) in the range from the LOQ to 40 ng/ml, whereas the precision (% CV) and accuracy (% bias) ranged from 1.4 to 10.5% and from 91.4 to 108.5%, respectively. The good sensitivity and selectivity of this method even allowed quantification of the estrogen metabolites in urine samples obtained from the postmenopausal female patients with osteoporosis. The present technique can be useful for clinical diagnosis as well as to better understand the pathogenesis of estrogen-related disorders in low-level quantification.

Original languageEnglish
Pages (from-to)1595-1603
Number of pages9
JournalJournal of Lipid Research
Volume52
Issue number8
DOIs
Publication statusPublished - 2011 Aug

All Science Journal Classification (ASJC) codes

  • Biochemistry
  • Endocrinology
  • Cell Biology

Fingerprint

Dive into the research topics of 'A novel GC-MS method in urinary estrogen analysis from postmenopausal women with osteoporosis'. Together they form a unique fingerprint.

Cite this