Abstract

ABSTRACTAmino acid analysis or metabonomics requires large-scale sample collection, which makes sample storage a critical consideration. However, functional amino acids are often neglected in metabolite stability studies because of the difficulty in detecting and accurately quantifying them with most analysis methods. Here, we investigated the stability of amino acids and related amines in human serum following different preprocessing and pre-storage procedures. Serum samples were collected and subjected to three storage conditions; cold storage (4°C), room temperature storage (22°C), and freezing (−80°C). The concentration of amino acids and related amines were quantified using iTRAQ®-LC-MS/MS with isobaric tagging reagents. Approximately 54.84%, 58.06%, and 48.39% of detectable and target analytes were altered at the 4°C condition, 22°C condition, and when subjected to freeze-thaw cycles, respectively. Some amino acids which are unstable and relatively stable were found. Our study provides detailed amino acid profiles in human serum and suggests pre-treatment measures that could be taken to improve stability.

Highlights

  • The detection and quantification of free amino acids is routinely applied in clinical laboratories for the diagnosis of inborn errors of metabolism (Phipps et al, 2019)

  • Our study aims to estimate the stability of amino acids and related amines in serum samples after exposure to adverse storage temperatures and freeze-thawing cycles by using iTRAQ®-LC-MS/MS

  • The Multiple reaction monitoring (MRM) ion chromatograms corresponding to the amino acids and their isotopic internal standards were extracted from the data

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Summary

Introduction

The detection and quantification of free amino acids is routinely applied in clinical laboratories for the diagnosis of inborn errors of metabolism (Phipps et al, 2019). Free amino acids have been implicated in having a role in a number of diseases such as cardiovascular diseases (Poggiogalle et al, 2019; Nie et al, 2018; Larsson et al, 2015), insulin resistance and type 2 diabetes (Yoon, 2016; Gar et al, 2018), renal diseases (Xia et al, 2018), hepatic disorders (Korenaga et al, 2015), and cancer (Li and Zhang, 2016; Yang and Vousden, 2016).

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