Zlatuse Clark (Presenter)
ARUP Laboratories
Bio: B.S. in analytical chemistry from Masaryk University, Brno, Czech Republic Ph.D. in bioanalytical chemistry from Brigham Young University, Provo, Utah Currently an R&D scientist at ARUP Laboratories, Salt Lake City, Utah
Authorship: Zlatuse D Clark
ARUP Laboratories, Salt Lake City, UT
| Short Abstract This session segment will discuss: • How do we test for interference in LC-MS/MS? • When do we test for interference? |
Long Abstract
Introduction
The popularity of LC-MS/MS-based methods for clinical testing continues to rise. However, despite their superior analytical specificity, these methods may still suffer from interference affecting method accuracy and precision, and hence negatively impacting patient care. The aim of this Practical Training Track presentation is to introduce the participant to what analytical interference is, where it may come from, how we test for it in LC-MS/MS, ways to mitigate it, and how to monitor for it (1). Practical examples of interference issues and how they were resolved will be shown.
Methods
N/A
Results
How do we test for interference in LC-MSMS?
Interference may appear in an assay as partially or completely co-eluting peaks in the analyte or internal standard mass chromatograms. Interference may also be virtually invisible to the naked eye—a matrix effect, caused by interfering substance altering the efficiency of the analyte and/or internal standard ions reaching the MS detector.
Assessing susceptibility to analytical interference is a very important part of any LC-MS/MS method development and validation as interference affects method accuracy, precision and therefore the quality and validity of reported results. Interference testing can be divided into two categories: 1) Direct testing of the effect of specific substances on analyte concentration; 2) Evaluation of unidentified interferences arising from sample matrix and anything that has been added to it (matrix effects).
1) Testing for Specific Interference
When testing for specific interference, a potential interferent (drug, medication, supplement, sample abnormality, etc.) is added to a sample pool and the target analyte concentration bias is evaluated relative to a control portion of the same sample pool (3). Both test and control pools are analyzed in the same manner as patient specimens, with adequate replication, within one analytical run. Initially, the test substances are spiked at the highest concentration expected in patient specimens submitted for analysis (3). When substances produce a clinically significant interference, they should be evaluated further at different concentrations to determine the magnitude of the interference (3, 4).
The advantages of this approach are the ability to define acceptable/unacceptable sample collection conditions and abnormalities and to provide a health practitioner ordering the test guidelines for patient preparation – such as which medications, supplements, and foods to avoid prior to sample collection in order to obtain a valid test result and reduce a need for repeat specimen collection and analysis. The disadvantages of this approach are the laboriousness of testing a large number of substances and the fact that no practical interference study can identify all potential interferents.
2) Testing for Unidentified Interference
Unlike most other analytical techniques, LC-MS/MS enables labs to test for interference that cannot be anticipated or identified beforehand. Interference arising from sample matrix has the potential to cause either signal enhancement or, more commonly, signal suppression. These matrix effects can be evaluated without identifying the specific substances causing them using either a quantitative matrix effect study, or a qualitative post-column infusion study (6-9).
In the former, analyte is added to both extracted test samples (typically blank matrix when available) and control samples (typically solvent based, containing no matrix elements). The difference in signal between the test and control samples is expressed as a percentage and provides a quantitative expression of the extent of ion suppression or enhancement: Values <100% indicate suppression, while those >100% indicate enhancement. The extent of a matrix effect can be calculated as non-normalized (as a ratio of peak areas) or normalized to internal standard (as a ratio of response factors, which are analyte peak areas divided by internal standard peak areas). Both provide valuable information: non-normalized matrix effect values show the actual magnitude of ion suppression/enhancement, while the normalized values indicate how well the internal standard compensates for the matrix effect. These experiments should be performed at two concentrations expected in the patient population and with several native matrix sources, such as different patient specimens.
In a post-column infusion study, an analyte solution is infused into the LC column effluent while a matrix blank sample is being analyzed (7-10). When blank sample matrix is not available or is not representative of patient specimens, a solution of the isotopically labeled internal standard may be infused in place of (or in addition to) the analyte. Ion suppression (enhancement) is evaluated as the presence of negative (positive) peaks in a steady signal trace of the infused analyte or internal standard (4, 10). This advantage of this qualitative approach is that it allows for visualization of the position and width of matrix effects regions.
When do we test for interference?
Interference testing is often performed as part of method validation. However, to ensure that any newly developed LC-MS/MS method is robust and provides high quality data, investigating interference by performing the experiments outlined above should be an integral part the method development process. The post-column infusion study specifically is very useful for designing an LC gradient that will maneuver analytes out of suppression zones (especially in the case of dilute-and-shoot methods prone to matrix effects), as well as for assessing extract cleanliness when determining which sample preparation method or conditions may best mitigate matrix effects (4, 10). Please note that interference testing and the adjustment of method parameters may need to be an iterative process. Also, labs should use as many patient specimens as practical to ensure that they capture the biological variability of interference. Waiting until method validation to perform these experiments could result in unwanted surprises.
Conclusions & Discussion
After this segment attendees should be able to:
1. Describe the different types of experiments used for interference testing in LC-MS/MS
2. Explain why waiting until validation to test for interference is not be desirable
References & Acknowledgements:
References:
1. Clark ZD, Balloch S, Calton L, Mason D. Interference Testing and Mitigation in LC-MS/MS Assays. Clinical Laboratory News 2017;43(8):22-5.
2. CLSI. Evaluation of matrix effects; Approved guideline – second edition. CLSI document EP14-A2.Wayne (PA): CLSI; 2005.
3. CLSI. Interference testing in clinical chemistry; Approved guideline – second edition. CLSI document EP7-A2.Wayne (PA): CLSI; 2005.
4. Clark ZD, Cutler JM, Pavlov IY, et al. Simple dilute-and-shoot method for urinary vanillylmandelic acid and homovanillic acid by liquid chromatography tandem mass spectrometry. Clin Chim Acta 2017;468:201–8.
5. Clark ZD, Cutler JM, Frank EL. Practical LC-MS/MS method for 5-hydroxyindoleacetic acid in urine. J Appl Lab Med 2017;1:387–99.
6. Matuszewski BK, Constanzer ML, Chavez-Eng CM. Strategies for the assessment of matrix effect in quantitative bioanalytical methods based on HPLC-MS/MS. Anal Chem 2003;75:3019–30.
7. Annesley TM. Ion suppression in mass spectrometry. Clin Chem 2003;49:1041–4.
8. Bonfiglio R, King RC, Olah TV, et al. The effects of sample preparation methods on the variability of the electrospray ionization response for model drug compounds. Rapid Commun Mass Spectrom 1999;13:1175–85.
9. King R, Bonfiglio R, Fernandez-Metzler C, et al. Mechanistic investigation of ionization suppression in electrospray ionization. J Am Soc Mass Spectrom 2000;11:942–50.
10. Clark ZD, Strathmann FG, McMillin GA. Diluting and shooting yourself in the foot: Complications with sample-to-sample variations in signal suppression. MSACL 2013 podium presentation.
11. CLSI. Liquid chromatography-mass spectrometry methods; Approved guideline. CLSI document C62-A. Wayne (PA): CLSI; 2014.
12. Lynch KL. LC-MS/MS quality assurance in production: The real work begins after validation. Clinical Laboratory News 2017;43(5):28–9.
13. Zabell APR, Stone J, Julian RK. Using big data for LC-MS/MS quality analysis. Clinical Laboratory News 2017;43(5):30–1.
Acknowledgements:
Much gratitude to Dr. Frederick Strathmann for collaboration on several projects addressing the various aspects of interference testing and for facilitating exciting opportunities to present and publish on these topics. Many thanks as well to Donald Mason, Lisa Calton, and Stephen Balloch for their contributions as coauthors of our recent Clinical Laboratory News article “Interference Testing and Mitigation in LC-MS/MS Assays,” which was used in preparing this presentation.
The work presented here was supported in part by ARUP Institute for Clinical and Experimental Pathology®.
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