Abstract
Objective
With the widespread use of sex-steroid hormones in contraceptives and hormone replacement
therapy, there is an increasing need for reliable analytical methods. We report the
development of a sensitive and robust UPLC–MS/MS method for quantitation of both endogenous
and synthetic sex-steroid hormones in human serum.
Study design
We developed and validated a UPLC–MS/MS method to quantify progestogens (etonogestrel,
levonorgestrel, medroxyprogesterone acetate, norethindrone, progesterone) and estrogens
(estradiol and ethinyl estradiol) with good accuracy, high sensitivity, and excellent
robustness. We then applied the method to the analysis of sex-steroid hormones in
serum from 451 clinical research participants.
Results
Each UPLC–MS/MS analysis was 6.5 min. The lower limits of quantitation (LLOQs) were
25 pg/ml for the progestogens, and 2.5 and 5.0 pg/ml for estradiol and ethinyl estradiol,
respectively. When estradiol was analyzed without assessment of progestogens, the
LLOQ was reduced to 1 pg/ml. The calibration curves were linear from 25–50,000, 2.5–2000
(1–2000 for estrogens-only analysis) and 5–2000 pg/ml, respectively. Both the accuracy
and precision were below±15% not only for routine validation (intraday and interday),
but for long-term (>2 years) assay robustness with external controls, thereby, demonstrating
the utility of this method for multi-year clinical trial assessments of progestogens
and estrogens. We applied the method to quantify sex-steroid levels in 1804 clinical
samples.
Conclusions
We successfully developed a UPLC-MS/MS method, and overcame the matrix suppression
to allow sensitive quantitation of both synthetic and endogenous sex-steroid hormones
in human serum.
Implications
We developed a sensitive and robust UPLC-MS/MS method to accurately measure the levels
of sex-steroid hormones in serum. The method overcame matrix interference barriers
and achieved excellent long-term stability and reproducibility (≥96.9% accuracy; ≤13.0%
relative variability measured with external controls over 2 years), demonstrating
its utility in clinical sample analysis.
Keywords
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Article info
Publication history
Published online: January 24, 2019
Accepted:
December 28,
2018
Received in revised form:
December 13,
2018
Received:
September 6,
2018
Footnotes
☆Declaration of interest: The authors declare that there is no conflict of interest that could affect the impartiality of the research reported.
☆☆Funding: This work was supported by the NIH grant S10RR023461 (to S.M.P.) and the Bill & Melinda Gates Foundation OPP1055833 (to S.L.A.).
Identification
Copyright
© 2019 Elsevier Inc. All rights reserved.
