Simultaneous quantification of endogenous and exogenous plasma glucose by isotope dilution LC-MS/MS with indirect MRM of the derivative tag

Quantification of glucose in the plasma of healthy Chinese volunteers and a bioequivalence study using a surrogate matrix approach combined with UHPLC-MS/MS

Acarbose works by competitively inhibiting α-glucosidase, delaying the breakdown of starch into glucose. Thus, it plays an important role in treating type 2 diabetes. Acarbose exhibits unique pharmacokinetic characteristics, and the United States of America (USA) Food and Drug Administration (FDA) has focused on pharmacodynamic parameters rather than pharmacokinetic ones in acarbose bioequivalence studies since issuing its 2009 draft guidance, which was formalized in 2017. A literature review on glucose measurement shows that glucose concentration data are primarily derived from serum matrices. In the 2022 draft guidance, the FDA reaffirmed that plasma glucose concentration is the most suitable pharmacodynamic endpoint for acarbose. This study employed a surrogate matrix method combined with ultra-high performance liquid chromatography-MS/MS (UHPLC-MS/MS) to measure plasma glucose levels. Because glucose is an endogenous substance, directly measuring its concentration in biological matrices does not effectively reflect the impact of acarbose on blood glucose levels. This study used Phosphate Buffered Saline (PBS) as the surrogate matrix to determine glucose concentrations and accurately achieve precise glucose quantification. Moreover, glucose and fructose are structural isomers that are difficult to quickly separate chromatographically, which can affect detection efficiency and introduce interference. Therefore, we aim to develop a rapid, simple, and accurate method for quantifying glucose concentration in human plasma using a surrogate matrix approach combined with UHPLC-MS/MS. Plasma samples were processed using protein precipitation, with glucose-[U-13C6] as the internal standard. Chromatographic separation was performed using a Waters ACQUITY UPLC BEH amide column (100 × 2.1 mm, 1.7 μm), and gradient elution was carried out at a flow rate of 0.4 mL min-1 with a mobile phase of 0.05% aqueous ammonia and 0.05% ammonia in acetonitrile. Electrospray ionization (ESI) in negative ion multiple reaction monitoring (MRM) mode was used for detection, with a total analysis time of 6 min. Glucose exhibited good linearity in the concentration range of 2.00 to 20.00 mmol L-1 (r2 = 0.9980), with a precision and accuracy within and between batches of less than 10%. The method was fully validated to ensure data accuracy. This method was successfully applied to a bioequivalence study of acarbose tablets in healthy Chinese subjects in the fasting state, providing valuable data for evaluating the consistency of acarbose formulations.

Advancements, Challenges, and clinical implications of integration of metabolomics technologies in diabetic nephropathy

BACKGROUND

Diabetic nephropathy (DN), a severe complication of diabetes, involves a range of renal abnormalities driven by metabolic derangements. Metabolomics, revealing dynamic metabolic shifts in diseases like DN and offering insights into personalized treatment strategies, emerges as a promising tool for improved diagnostics and therapies.

METHODS

We conducted an extensive literature review to examine how metabolomics contributes to the study of DN and the challenges associated with its implementation in clinical practice. We identified and assessed relevant studies that utilized metabolomics methods, including nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) to assess their efficacy in diagnosing DN.

RESULTS

Metabolomics unveils key pathways in DN progression, highlighting glucose metabolism, dyslipidemia, and mitochondrial dysfunction. Biomarkers like glycated albumin and free fatty acids offer insights into DN nuances, guiding potential treatments. Metabolomics detects small-molecule metabolites, revealing disease-specific patterns for personalized care.

CONCLUSION

Metabolomics offers valuable insights into the molecular mechanisms underlying DN progression and holds promise for personalized medicine approaches. Further research in this field is warranted to elucidate additional metabolic pathways and identify novel biomarkers for early detection and targeted therapeutic interventions in DN.

A chemometric strategy to automatically screen selected ion monitoring ions for gas chromatography-mass spectrometry-based pseudotargeted metabolomics

The pseudotargeted metabolomics based on gas chromatography-mass spectrometry (GC-MS) has the advantage of filtering out artifacts originating from sample treatment and accurately quantifying underlying compounds in the analyzed samples. However, this technique faces the problem of selecting high-quality selective ions for performing selected ion monitoring (SIM) on instruments. In this work, we proposed AntDAS-SIMOpt, an automatic untargeted strategy for SIM ion optimization that was accomplished on the basis of an experimental design combined with advanced chemometric algorithms. First, a group of diluted quality control samples was used to screen underlying compounds in samples automatically. Ions in each of the resolved mass spectrum were then evaluated by using the developed algorithms to identify the SIM ion. A Matlab graphical user interface (GUI) was designed to facilitate routine analysis, which can be obtained from http://www.pmdb.org.cn/antdassimopt. The performance of the developed strategy was comprehensively investigated by using standard and complex plant datasets. Results indicated that AntDAS-SIMOpt may be useful for GC-MS-based metabolomics.

An adapted isotope dilution 1H-13C heteronuclear single-quantum correlation (ID-HSQC) for rapid and accurate quantification of endogenous and exogenous plasma glucose

A wide variety of methods, such as enzymatic methods, LC-MS, and LC-MS/MS, are currently available for the concentration determination of plasma glucose in studies of diabetes, obesity, exercise, etc. However, these methods rarely discriminate endogenous and exogenous glucose in plasma. A novel NMR strategy for discriminative quantification of the endogenous and exogenous glucose in plasma has been developed using an adapted isotope dilution ¹H-¹³C heteronuclear single-quantum correlation (ID-HSQC) with uniformly ¹³C-labeled glucose as a tracer of exogenous glucose. This method takes advantage of the distinct ¹H-¹³C chemical shifts of the hemiacetal group of the α-D-glucopyranose and makes use of the ¹³C-¹³C one-bond J-coupling (¹J_CC) in uniformly ¹³C-labeled glucose to differentiate the ¹H-¹³C HSQC signal of labeled glucose from that of its natural counterpart when data are acquired in high-resolution mode. The molar ratio between the endogenous and exogenous plasma glucose can then be calculated from the peak intensities of the natural and labeled glucose. The accuracy and precision of the method were evaluated using a series of standard mixtures of natural and uniformly ¹³C-labeled glucose with varied but known concentrations. Application of this method is demonstrated for the quantification of endogenous and exogenous glucose in plasma derived from healthy and diabetic cynomolgus monkeys. The results nicely agree with our previous LC-MS/MS results. Considering the natural abundance of ¹³C isotope at the level of 1.1% in endogenous glucose, comparable peak intensities of quantitatively measurable signals derived from natural and labeled glucose imply that the ID-HSQC can tolerate a significantly high ratio of isotope dilution, with labeled/natural glucose at ~ 1%. We expect that the ID-HSQC method can serve as an alternative approach to the biomedical or clinical studies of glucose metabolism.