Skip to main content
Log in

Intensive determination of storage condition effects on human plasma metabolomics

  • Original Article
  • Published:
Metabolomics Aims and scope Submit manuscript

Abstract

Introduction

Human plasma metabolomics offer powerful tools for understanding disease mechanisms and identifying clinical biomarkers for diagnosis, efficacy prediction and patient stratification. Although storage conditions can affect the reliability of data from metabolites, strict control of these conditions remains challenging, particularly when clinical samples are included from multiple centers. Therefore, it is necessary to consider stability profiles of each analyte.

Objectives

The purpose of this study was to extract unstable metabolites from vast metabolome data and identify factors that cause instability.

Method

Plasma samples were obtained from five healthy volunteers, were stored under ten different conditions of time and temperature and were quantified using leading-edge metabolomics. Instability was evaluated by comparing quantitation values under each storage condition with those obtained after −80 °C storage.

Result

Stability profiling of the 992 metabolites showed time- and temperature-dependent increases in numbers of significantly changed metabolites. This large volume of data enabled comparisons of unstable metabolites with their related molecules and allowed identification of causative factors, including compound-specific enzymatic activity in plasma and chemical reactivity. Furthermore, these analyses indicated extreme instability of 1-docosahexaenoylglycerol, 1-arachidonoylglycerophosphate, cystine, cysteine and N6-methyladenosine.

Conclusion

A large volume of data regarding storage stability was obtained. These data are a contribution to the discovery of biomarker candidates without misselection based on unreliable values and to the establishment of suitable handling procedures for targeted biomarker quantification.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Abbreviations

BMI:

Body mass index

C3f:

Complement

EPA:

Eicosapentaenoic acid

FDR:

False discovery rate

GC/MS:

Gas chromatography/mass spectrometry

GluTrp:

Glutamyltryptophan

GPC:

Glycerophosphorylcholine

GPE:

Glycerophosphoethanolamine

LPC:

Lysophosphatidylcholine

LPE:

Lysophophatidylethanolamine

LPI:

Lysophosphatidylinositol

MAG:

Monoacylglycerol

RNase:

Ribonucleotidase

ROS:

Reactive oxygen species

PC:

Phosphorylcholine

PCA:

Principal component analysis

RT:

Room temperature

SOP:

Standard operation procedure

TAG:

Triacylglycerol

UHPLC/MS/MS:

Ultrahigh performance liquid chromatography/tandem mass spectrometry

References

  • Agarwal, S., Vargas, G., Nordstrom, C., Tam, E., Buffone, G. J., & Devaraj, S. (2015). Effect of interference from hemolysis, icterus and lipemia on routine pediatric clinical chemistry assays. Clinica Chimica Acta, 438, 241–245.

    Article  CAS  Google Scholar 

  • Ames, B. N., Cathcart, R., Schwiers, E., & Hochstein, P. (1981). Uric acid provides an antioxidant defense in humans against oxidant- and radical-caused aging and cancer: A hypothesis. Proceedings of the National Academy of Sciences, 78, 6858–6862.

    Article  CAS  Google Scholar 

  • Davies, S. K., Ang, J. E., Revell, V. L., Holmes, B., Mann, A., Robertson, F. P., et al. (2014). Effect of sleep deprivation on the human metabolome. Proceedings of the National Academy of Sciences, 111, 10761–10766.

    Article  CAS  Google Scholar 

  • Elin, C., Michael, B. S., Thomas, M., & Henrik, A. (2012). Physical fitness level is reflected by alterations in the human plasma metabolome. Molecular BioSystems, 8, 1187–1196.

    Article  Google Scholar 

  • Evans, A. M., Bridgewater, B. R., Miller, L. A. D., Mitchell, M. W., Robinson, R. J., Dai, H., et al. (2014). High resolution mass spectrometry improves data quantity and quality as compared to unit mass resolution mass spectrometry in high-throughput profiling metabolomics. Metabolomics, 4(2), 1.

    Google Scholar 

  • Evans, A. M., DeHaven, C. D., Barrett, T., Mitchell, M., & Milgram, E. (2009). Integrated, nontargeted ultrahigh performance liquid chromatography/electrospray ionization tandem mass spectrometry platform for the identification and relative quantification of the small-molecule complement of biological systems. Analytical Chemistry, 81, 6656–6667.

    Article  CAS  PubMed  Google Scholar 

  • Fiskerstrand, T., Refsum, H., Kvalheim, G., & Ueland, P. M. (1993). Homocysteine and other thiols in plasma and urine: Automated determination and sample stability. Clinical Chemistry, 39, 263–271.

    CAS  PubMed  Google Scholar 

  • Fliniaux, O., Gaillard, G., Lion, A., Cailleu, D., Mesnard, F., Betsou, F., et al. (2011). Influence of common preanalytical variations on the metabolic profile of serum samples in biobanks. Journal of Biomolecular NMR, 51, 457–465.

    Article  CAS  PubMed  Google Scholar 

  • International Expert Committee. (2009). International Expert Committee report on the role of the A1C assay in the diagnosis of diabetes. Diabetes Care, 32, 1327–1334.

    Article  Google Scholar 

  • Kamlage, B., Maldonado, S. G., Bethan, B., Peter, E., Schmitz, O., Liebenberg, V., et al. (2014). Quality markers addressing preanalytical variations of blood and plasma processing identified by broad and targeted metabolite profiling. Clinical Chemistry, 60, 399–412.

    Article  CAS  PubMed  Google Scholar 

  • Kand’ar, R., Zakova, P., & Muzakova, V. (2006). Monitoring of antioxidant properties of uric acid in humans for a consideration measuring of levels of allantoin in plasma by liquid chromatography. Clinica Chimica Acta, 365, 249–256.

    Article  Google Scholar 

  • Kasukawa, T., Sugimoto, M., Hida, A., Minami, Y., Mori, M., Honma, S., et al. (2012). Human blood metabolite timetable indicates internal body time. Proceedings of the National Academy of Sciences United States of America, 109, 15036–15041.

    Article  CAS  Google Scholar 

  • Kate, D. M., & Samie, R. J. (2014). The dynamic epitranscriptome: N6-methyladenosine and gene expression control. Nature Reviews Molecular Cell Biology, 15, 313–326.

    Google Scholar 

  • Kleinman, W. A., & Richie, J. P., Jr. (2000). Status of glutathione and other thiols and disulfides in human plasma. Biochemical Pharmacology, 60, 19–29.

    Article  CAS  PubMed  Google Scholar 

  • Krug, S., Kastenmüller, G., Stückler, F., Rist, M. J., Skurk, T., Sailer, M., et al. (2012). The dynamic range of the human metabolome revealed by challenges. FASEB Journal, 26, 2607–2619.

    Article  CAS  PubMed  Google Scholar 

  • Mollnes, T., Garred, P., & Bergseth, G. (1988). Effect of time, temperature and anticoagulants on in vitro complement activation: Consequences for collection and preservation of samples to be examined for complement activation. Clinical and Experimental Immunology, 73, 484–486.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Ohta, T., Masutomi, N., Tsutsui, N., Sakairi, T., Mitchell, M., Milburn, M. V., et al. (2009). Untargeted metabolomic profiling as an evaluative tool of fenofibrate-induced toxicology in Fischer 344 male rats. Toxicologic Pathology, 37, 521–535.

    Article  CAS  PubMed  Google Scholar 

  • Pastor, A., Farre, M., Fito, M., Fernandez-Aranda, F., & de la Torre, R. (2014). Analysis of ECs and related compounds in plasma: Artifactual isomerization and ex vivo enzymatic generation of 2-MGs. Journal of Lipid Research, 55, 966–977.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Pellis, L., van Erk, M. J., van Ommen, B., Bakker, G. C., Hendriks, H. F., Cnubben, N. H., et al. (2012). Plasma metabolomics and proteomics profiling after a postprandial challenge reveal subtle diet effects on human metabolic status. Metabolomics, 8, 347–359.

    Article  CAS  PubMed  Google Scholar 

  • Pinto, J., Domingues, M. R., Galhano, E., Pita, C., Almeida, M. C., Carreira, I. M., et al. (2014). Human plasma stability during handling and storage: Impact on NMR metabolomics. Analyst, 139, 1168–1177.

    Article  CAS  PubMed  Google Scholar 

  • Storey, J. D., & Tibshirani, R. (2003). Statistical significance for genome wide studies. Proceedings of the National Academy of Sciences United States of America, 100, 9440–9445.

    Article  CAS  Google Scholar 

  • Teahan, O., Gamble, S., Holmes, E., Waxman, J., Nicholson, J. K., Bevan, C., et al. (2006). Impact of analytical bias in metabonomic studies of human blood serum and plasma. Analytical Chemistry, 78, 4307–4318.

    Article  CAS  PubMed  Google Scholar 

  • Wu, X. W., Lee, C. C., Muzny, D. M., & Caskey, C. T. (1989). Urate oxidase: Primary structure and evolutionary implications. Proceedings of the National Academy of Sciences United States of America, 86, 9412–9416.

    Article  CAS  Google Scholar 

  • Yin, P., Lehmann, R., & Xu, G. (2015). Effects of pre-analytical processes on blood samples used in metabolomics studies. Analytical and Bioanalytical Chemistry, 407, 4879–4892.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Yin, P., Peter, A., Franken, H., Zhao, X., Neukamm, S. S., Rosenbaum, L., et al. (2013). Preanalytical aspects and sample quality assessment in metabolomics studies of human blood. Clinical Chemistry, 59, 833–845.

    Article  CAS  PubMed  Google Scholar 

  • Yu, Z., Zhai, G., Singmann, P., He, Y., Xu, T., Prehn, C., et al. (2012). Human serum metabolic profiles are age dependent. Aging Cell, 11, 960–967.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zighetti, M. L., Chantarangkul, V., Lombardi, R., Lecchi, A., & Cattaneo, M. (2004). Effects of some pre-analytical conditions on the measurement of homocysteine and cysteine in plasma. Clinical Chemistry and Laboratory Medicine, 42, 204–207.

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yoshinori Satomi.

Ethics declarations

Conflict of interest

All authors ‘Takeo Moriya, Yoshinori Satomi and Hiroyuki Kobayashi’ declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the Institutional and/or National Research Committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 422 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Moriya, T., Satomi, Y. & Kobayashi, H. Intensive determination of storage condition effects on human plasma metabolomics. Metabolomics 12, 179 (2016). https://doi.org/10.1007/s11306-016-1126-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11306-016-1126-2

Keywords

Navigation