= Emerging. More than 5 years before clinical availability. (16.60%, 2024)
= Expected to be clinically available in 1 to 4 years. (37.02%, 2024)
= Clinically available now. (46.38%, 2024)
MSACL 2024 : Liu

MSACL 2024 Abstract

Self-Classified Topic Area(s): Small Molecule > Tox / TDM / Endocrine > Metabolomics

Poster Presentation
Poster #28a
Attended on Thursday at 09:15

Development of Simple LC-FAIMS-MS/MS Method for the Quantification of Nicotine and Its Metabolites in Urine

Danting Liu, Yubo Chai, Anthony Maus, Loralie Langman, Paul J. Jannetto
Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN

Danting Liu, Ph.D. (Presenter)
Mayo Clinic

>> POSTER (PDF)

Presenter Bio: Danting Liu is currently a first-year clinical chemistry fellow at Mayo Clinic. She did her Ph.D. in the Clinical Chemistry Program of the Chemistry Department, at Cleveland State University. After graduating, she did her postdoctoral training at St. Jude Children’s Research Hospital. In 2022, she joined MD Anderson Cancer Center, leading the proteomics core lab. Her research interests include TMT-based proteomics, toxicology, therapeutic drug monitoring, Biomarkers, and more.

Abstract

Introduction:
The use of tobacco products, particularly smoking, is the main preventable cause of lung cancer in the U.S. Nicotine is the active component in tobacco, responsible for addiction. The clinical test for nicotine and its metabolites in urine is a widely accepted method to evaluate nicotine exposure. In addition, anabasine, an analog of nicotine present in trace amounts in tobacco products, is also used as an indicator for monitoring compliance in tobacco cessation and effectiveness in nicotine replacement therapy. Currently, the conventional methods used to detect these molecules in the clinical laboratory are direct dilution or solid phase extraction (SPE), followed by LC-MS/MS analysis. However, direct dilution and injection methods may introduce bias in quantification and are prone to interferences, especially with low concentration samples. SPE purification is effective at overcoming these limitations, but this technique adds cost and labor to the analysis. Here, we present a novel LC-FAIMS-MS/MS method capable of detecting nicotine and its metabolites in urine with better sensitivity and specificity, without adding labor and cost.

Method:
Residual urine samples from the nicotine positive and negative patients were used in this study. In the test, 50 μL of calibrator, QC, blank, or patient urine samples were mixed with 50 μL of internal standard working solution (200 ng/mL Nicotine-D4, Nonicotine-D4, Anabasine-D4 and Cotinine-D3) and 800 μL of Mobile phase A (5 mM Ammonium Bicarbonate in 0.1% Formic Acid) in a 96 well-plate at room temperature. The sample was then separated by the LC column (C18, 3.0 x 50 mm, 2.6 um PS C-18 Kinetex) using a 10 min gradient (mobile phase B, 0.1% Formic Acid in ACN) and analyzed by TSQ Altis Plus Triple Quadrupole MS with or without FAIMS installed. The solid phase extraction (SPE) method was performed to compare with the dilution method. Nicotine and its metabolites in 50 μL of the urine sample were extracted with a strong cation Bond Elut PlexaPCX 30 mg plate (Agilent), followed by the same LC-MS/MS method. The four analytes were quantitated using internal standards and calibration curves.

Result and Conclusion:
The results obtained from the LC-FAIMS-MS/MS method showed that, compared with the regular dilute-and-shoot method, using the FAIMS cleaned up the background noise up to 80% and largely increased the signal-to-noise ratio (S/N). The chemical noise signals that interfere with the quantification of anabasine and cotinine, especially at low concentrations, were completely eliminated. The Compensation Voltage (CV) values used in FAIMS for each analyte were optimized to produce the highest quantitative accuracy and precision. The agreement between the quantifier and qualifier ions was excellent, with linear regression analysis yielding R2 greater than 0.99 for all four analytes. The total imprecision of the assay was less than 10% across the analytical measuring range. Overall, our new method is simple and utilizes low cost sample preparation, requires minimal instrument maintenance, while providing accurate, precise, and specific measurements, which makes this method an ideal, high throughput analysis technique for the clinical laboratory.


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