Display options
Share it on

Rapid Commun Mass Spectrom. 2017 Mar 15;31(5):447-456. doi: 10.1002/rcm.7808.

Comparing identified and statistically significant lipids and polar metabolites in 15-year old serum and dried blood spot samples for longitudinal studies.

Rapid communications in mass spectrometry : RCM

Jennifer E Kyle, Cameron P Casey, Kelly G Stratton, Erika M Zink, Young-Mo Kim, Xueyun Zheng, Matthew E Monroe, Karl K Weitz, Kent J Bloodsworth, Daniel J Orton, Yehia M Ibrahim, Ronald J Moore, Christine G Lee, Catherine Pedersen, Eric Orwoll, Richard D Smith, Kristin E Burnum-Johnson, Erin S Baker

Affiliations

  1. Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, USA.
  2. National Security Directorate, Pacific Northwest National Laboratory, Richland, WA, USA.
  3. Department of Medicine, Bone and Mineral Unit, Oregon Health and Science University, Portland, OR, USA.
  4. Research Service, Portland Veterans Affairs Medical Center, Portland, OR, USA.

PMID: 27958645 PMCID: PMC5292309 DOI: 10.1002/rcm.7808

Abstract

RATIONALE: The use of dried blood spots (DBS) has many advantages over traditional plasma and serum samples such as the smaller blood volume required, storage at room temperature, and ability to sample in remote locations. However, understanding the robustness of different analytes in DBS samples is essential, especially in older samples collected for longitudinal studies.

METHODS: Here we analyzed the stability of polar metabolites and lipids in DBS samples collected in 2000-2001 and stored at room temperature. The identified and statistically significant molecules were then compared to matched serum samples stored at -80°C to determine if the DBS samples could be effectively used in a longitudinal study following metabolic disease.

RESULTS: A total of 400 polar metabolites and lipids were identified in the serum and DBS samples using gas chromatograph/mass spectrometry (GC/MS), liquid chromatography (LC)/MS, and LC/ion mobility spectrometry-MS (LC/IMS-MS). The identified polar metabolites overlapped well between the sample types, though only one statistically significant metabolite was conserved in a case-control study of older diabetic males with low amounts of high-density lipoproteins and high body mass indices, triacylglycerides and glucose levels when compared to non-diabetic patients with normal levels, indicating that degradation in the DBS samples affects polar metabolite quantitation. Differences in the lipid identifications indicated that some oxidation occurs in the DBS samples. However, 36 statistically significant lipids correlated in both sample types.

CONCLUSIONS: The difference in the number of statistically significant polar metabolites and lipids indicated that the lipids did not degrade to as great of a degree as the polar metabolites in the DBS samples and lipid quantitation was still possible. Copyright © 2016 John Wiley & Sons, Ltd.

Copyright © 2016 John Wiley & Sons, Ltd.

References

  1. Rapid Commun Mass Spectrom. 2012 Mar 30;26(6):645-52 - PubMed
  2. Bioinformatics. 2011 Oct 15;27(20):2866-72 - PubMed
  3. mSystems. 2016 May 10;1(3):null - PubMed
  4. J Antimicrob Chemother. 2008 Mar;61(3):694-8 - PubMed
  5. Int J STD AIDS. 2002 Jan;13(1):25-8 - PubMed
  6. Nat Med. 2010 Apr;16(4):400-2 - PubMed
  7. Bioanalysis. 2013 Jun;5(12):1507-14 - PubMed
  8. J Lipid Res. 1967 Nov;8(6):667-75 - PubMed
  9. Anal Chim Acta. 2009 Feb 9;633(2):257-62 - PubMed
  10. Arterioscler Thromb Vasc Biol. 2008 Jul;28(7):1225-36 - PubMed
  11. Proc Natl Acad Sci U S A. 2013 Apr 9;110(15):5875-80 - PubMed
  12. Rapid Commun Mass Spectrom. 2004;18(23):2849-58 - PubMed
  13. Biochem Mol Med. 1996 Apr;57(2):116-24 - PubMed
  14. J Int AIDS Soc. 2014 Nov 02;17(4 Suppl 3):19686 - PubMed
  15. AAPS J. 2016 Mar;18(2):519-27 - PubMed
  16. Anal Chem. 2007 Jul 1;79(13):5013-22 - PubMed
  17. J Med Virol. 2004 Aug;73(4):624-30 - PubMed
  18. Lipids. 2016 Feb;51(2):193-8 - PubMed
  19. Bioinformatics. 2013 Nov 1;29(21):2804-5 - PubMed
  20. Am J Trop Med Hyg. 2014 Feb;90(2):195-210 - PubMed
  21. Anal Chem. 2009 Dec 15;81(24):10038-48 - PubMed
  22. Prostaglandins Leukot Essent Fatty Acids. 2014 Dec;91(6):251-60 - PubMed
  23. Mass Spectrom Rev. 2006 May-Jun;25(3):450-82 - PubMed
  24. Trends Pharmacol Sci. 2012 Jul;33(7):374-81 - PubMed
  25. J Lipid Res. 2009 Apr;50 Suppl:S9-14 - PubMed
  26. Anal Chem. 2009 May 1;81(9):3429-39 - PubMed
  27. Anal Chem. 2014 Feb 18;86(4):2107-16 - PubMed
  28. Int J Mass Spectrom. 2015 Feb 1;377:655-662 - PubMed
  29. J Proteome Res. 2010 Nov 5;9(11):5748-56 - PubMed
  30. Biomed Chromatogr. 2010 Jan;24(1):49-65 - PubMed
  31. Biodemography Soc Biol. 2014;60(1):38-48 - PubMed
  32. Demography. 2007 Nov;44(4):899-925 - PubMed
  33. Pediatrics. 1963 Sep;32:338-43 - PubMed
  34. Genes Nutr. 2016 Apr 16;11:12 - PubMed
  35. Diabetes Care. 2016 May;39(5):833-46 - PubMed
  36. Mass Spectrom Rev. 2016 May-Jun;35(3):361-438 - PubMed
  37. J Clin Invest. 2011 Apr;121(4):1402-11 - PubMed
  38. Antiviral Res. 2012 Mar;93(3):309-21 - PubMed
  39. Biotechniques. 2013 Mar;54(3):165-8 - PubMed
  40. PLoS One. 2010 May 28;5(5):e10883 - PubMed
  41. Lipids. 2013 Nov;48(11):1079-91 - PubMed
  42. Biophys J. 2012 Aug 22;103(4):702-10 - PubMed
  43. Front Microbiol. 2015 Apr 17;6:209 - PubMed
  44. Bioanalysis. 2011 Nov;3(22):2501-14 - PubMed
  45. PLoS One. 2013 Sep 27;8(9):e74341 - PubMed
  46. J Biol Chem. 1957 May;226(1):497-509 - PubMed
  47. N Engl J Med. 2010 May 27;362(21):2037-9 - PubMed
  48. Virol J. 2013 Mar 05;10:72 - PubMed
  49. J Lipid Res. 2005 May;46(5):839-61 - PubMed
  50. Clin Chem. 2007 Apr;53(4):717-22 - PubMed
  51. Ann Intern Med. 2010 Dec 21;153(12 ):790-9 - PubMed
  52. Metabolomics. 2014;10(5):1018-1025 - PubMed
  53. Sci Rep. 2011;1:139 - PubMed
  54. PLoS One. 2013 Dec 31;8(12):e84034 - PubMed
  55. BMC Bioinformatics. 2010 Jul 23;11:395 - PubMed

Publication Types

Grant support