FGF-21 biomarker detection at the sub-nanogram per mL level in human serum using normal-flow liquid chromatography/tandem mass spectrometry.

ABSTRACT

RATIONALE Quantitative detection of the FGF-21 biomarker at the sub-nanogram per mL level in human serum has generally been achieved using nanoflow liquid chromatography/tandem mass spectrometry (LC/MS/MS) due to its high sensitivity. However, a nano-LC/MS/MS-based assay can suffer from limited reproducibility and MS signal instability making it challenging to employ it as a robust analytical method for routine clinical applications. METHODS: To tackle these limitations, parallel reaction monitoring (PRM)-based targeted protein quantification using normal-flow liquid chromatography coupled with high-resolution, accurate mass instrumentation was evaluated as a possible alternative. Different from the conventional selected reaction monitoring (SRM) using triple quadrupole MS, the proposed strategy used high-resolution orbitrap MS coupled with conventional normal-flow liquid chromatography. The primary goal of this assay development effort is to significantly improve the robustness of the LC/MS/MS-based assay while maintaining high sensitivity by the use of high-resolution MS and a large sample loading volume. RESULTS: The performance of the normal-flow LC/MS/MS assay was evaluated by using it to quantify the FGF-21 protein, a potential biomarker for non-alcoholic fatty liver disease, in serum samples. Multiple replicated PRM sample quantification results demonstrated the excellent reproducibility and operational robustness of the assay. A limit of quantification of less than 0.4 ng/mL for FGF-21 in a complex serum matrix could be achieved by using the heavy-isotope-labeled peptide technique, a result which is comparable with the sensitivity obtained using the nano-LC/SRM MS-based assay. CONCLUSIONS: The strategy offered an effective alternative to nano-LC/SRM MS for the quantification of protein biomarkers in a complex biomatrix with much improved reproducibility and operational robustness.