1002-84-2

Hazard Information

Questions And Answer

• Overview

  There is recently a considerable development in the understanding of lipids and their associations with disease, through disease etiology, biomarkers, treatment and prevention. To the present date, there have been over 150 different diseases connected with lipids, ranging from high blood pressure and artery plaques, obesity, type II diabetes, cancer and neurological disorders^[1].
  Fatty acids are the basic building blocks of more complex lipids^[2] and their composition in different lipid species are often used as a means for comparison within a lipid class when examining disease and physiological perturbations in lipid metabolism. It has been shown that saturated fatty acids^[3] are associated with increased relative risks for diseases such as coronary heart disease, atherosclerosis, fatty liver disease, inflammatory diseases and Alzheimer’s disease. In contrast many unsaturated fatty acids including both mono-unsaturated and poly-unsaturated, have been associated with a reduced risk for each of the previously described disorders in certain studies^[4]. Fatty acid chain length is also used for the diagnosis and prognosis of disease with respect to adrenoleukodystrophy, Refsum disease and Zellweger Syndrome where the propagation of very long chain fatty acids (>22 Carbon length chain^[5]) is indicative of these disorders^[6].
  Pentadecanoic acid (15:0), which originate from rumen microbial fermentation, is a kind of minor saturated fatty acid (FAs) in ruminant fat^[7]. Its concentration in conventionally produced cow milk are on average 1.2% of total FAs, respectively. Concentrations in organically produced milk are somewhat higher^[8]. 15:0 is accepted biomarkers for dairy fat intake^[9], because its concentration in human plasma and RBCs increase with higher intake of dairy fat^{[10–13]}.
  For instance, in the EPIC (European Prospective Investigation into Cancer and Nutrition)-InterAct case-cohort study, concentration of 15:0 in plasma phospholipids were on average 0.21% of total FAs, respectively^[5]. Interestingly, 17:0 is present in plasma at approximately twice the concentration of 15:0 [reviewed in^[14]] or even more in RBCs^[4], the association with dairy fat intake is stronger for 15:0 than for 17:0^{[10, 12, 13]}.
  
  Figure 1 the chemical structure of Pentadecanoic acid;

• Source and synthesis

  The first possibility is synthesis from propionic acid (3:0) or other OCFAs shorter than 15:0. Fermentation of dietary fiber by the colonic microbiota is the primary source of SCFAs in humans, that is, acetic acid (2:0), propionic acid, and butyric acid (4:0). Most gut microbial propionic acid is absorbed and mostly metabolized by the liver^[15]. Data from rodents show that feeding dietary fiber results in a measurable increase of both SCFAs, including propionic acid, and also of 15:0 in plasma phospholipids^[16]. In the EPIC study, the OCFA concentrations in plasma phospholipids were also significantly associated with the intake of fruits and vegetables naturally rich in fibers^[11]. The first evidence for an endogenous synthesis of 15:0 from (labeled) propionic acid was provided in subjects with the rare genetic disorders propionic acidemia (PA) and methylmalonic acidemia^[17]. Normally, propionic acid is converted to propionyl-CoA and enters the citric acid cycle (CAC) at the level of succinyl-CoA. However, deficiencies of propionyl-CoA carboxylase or methylmalonyl-CoA mutase, respectively, block this pathway, leading to unusually high concentrations of 15:0 in a number of tissues^{[18, 19]}.
  Another source of 15:0 may be phytosphingosine, also called dihydrosphingosine, a sphingoid base of glycosphingolipids. Phytosphingosine is degraded to 2-hydroxy hexadecanoic acid, which is finally a-oxidized to produce 15:0^[20]. In fact, glycosphingolipids of the rat small intestine mucosa contain far more phytosphingosine than sphingosine[21]. However, the concentration in human tissues is not known. 15:0 may also be formed from hexadecanoic acid (16:0) after intermediate hydroxylation. This was observed in cultured differentiating adipocytes^[22], as outlined before^[14]. The relevance of this pathway in vivo is unknown. ;

• Applications

  The majority of research into fatty acid metabolism has been conducted primarily on even chain fatty acids (carbon chain length of 2–26) as these represent >99% of the total fatty acid plasma concentration in humans^[13,14]. However, there is also a detectable amount of odd-chain fatty acids in human tissue. As a result of the low concentration there are only four significantly measureable odd chain fatty acids, which are C15:0, C17:0, C17:1[25] and C23:0^[26]. C15:0 and C17:0; these have been gaining research interest within the scientific community as they have been found to be important as: (1) quantitative internal standards; (2) biomarkers for dietary food intake assessment; (3) biomarkers for coronary heart disease (CHD) risk and type II diabetes mellitus (T2D) risk (although the objective is not to provide a meta-analysis of odd chain saturated fatty acids (OCS-FAs) and disease risk); (4) evidence for theories of alternate endogenous metabolic pathways.
  Quantitative internal standards
  Since the early 1960s, it has been concluded that odd chain saturated fatty acids (OCS-FAs) are of little physiological significance^[27–29] and that the only real difference with their more abundant counterparts, even chain fatty acids^[24], is seen in the endpoint of metabolism where OCS-FAs result in propionyl CoA^[29] as opposed to acetyl CoA^[30]. Moreover, the OCS-FAs are present at apparently insignificant plasma concentrations^[31] (<0.5% total plasma fatty acid concentration^[32]) and the natural variation of concentrations within blood plasma ranging from 0%–1%.
  Therefore, OCS-FAs can be used as low cost internal standards in quantitative analysis,
  with C15:0 fatty acids being the most widely employed in this context. Many assumed that the concentration of OCS-FAs did not vary in different diseases and these lipid species were commonly used for standards in analyses[33,34]. The natural plasma variation of C15:0 could account for a 0.2%–3% variation in the Q-Int. Std response and therefore affecting the observed instrument abundance of the analytes. Furthermore, the use of these two OCS-FAs as quantitative internal standards does not allow them to be incorporated into any statistical analysis and therefore no correlations can be deduced. This is the main limiting factor to the amount of understand there is around the physiology of OCS-FAs.
  Biomarkers for dietary food intake assessment
  With the realization that OCS-FAs are in fact a biologically relevant component of blood plasma[35] there came further insights into their origin, either through consumption or through endogenous biosynthetic or metabolic pathways. This new direction of research interest led into the field of dietary analysis and the aim to identify lipidome variations^[36] in relation to dietary intake^[37].
  OCS-FAs have attracted attention with research into the possible application of C15:0 in blood as a marker for intake of milk fat and subsequent relations between intake of milk fat with metabolic risk factors, the results in the first published study that focused on this showed that the proportions of C15:0 in cholesterol esters are associated with the total amount of fat from milk products (r = 0.46, p < 0.0001), based on 62 men^[46].
  Biomarkers for coronary heart disease (CHD) risk and type II diabetes mellitus (T2D) risk
  In recent years, researches has been carried out in two key studies: The European Prospective Investigation into Cancer and Nutrition (EPIC) and The Norfolk Prospective Study^[38]. The plasma samples of 1595 CHD cases and 2246 controls were used to extract plasma phospholipid fatty acids. The lipid extracts were measured by gas chromatography coupled to electron impact mass spectrometry and the concentrations were determined by peak comparison with an internal standard (di-palmitoyl-D31-phosphatidylcholine). The incidence of CHD was ascertained by the participant’s admission into hospital with a CHD diagnosis or death from CHD according to ICD9 410-414/ICD10 I22–I25. The results from this study clearly revealed saturated plasma phospholipid fatty acid, C14:0, C16:0, C18:0, concentrations were significantly associated with an increased risk of CHD. However, OCS-FAs concentrations of C15:0 and C17:0 showed a significant inverse association with CHD incidence, making them potential biomarkers of CHD. ;

• References

  1. Reitz, C.; Tang, M.; Luchsinger, J.; Mayeux, R. Arch. Neurol. 2004, 61, 705–714.
  2. LIPID Maps. Available online: http://www.lipidmaps.org/ (accessed on 28 January 2015).
  3. Ulbricht, T.L.V.; Southgate, D.A.T. Lancet 1991, 338, 985–992.
  4. Simopoulos, A.P. Am. J. Clin. Nutr. 1991, 54, 438–463.
  5. Izai, K.; Uchida, Y.; Orii, T.; Yamamoto, S.; Hashimoto, T. J. Biol. Chem. 1992, 267, 1027–1033.
  6. Poulos, A.; Sharp, P.; Fellenberg, A.J.; Danks, D.M. Hum. Genet. 1985, 70, 172–177.
  7. Ratnayake WM. Am J Clin Nutr 2015;101:1102–3.
  8. Kusche D, Kuhnt K, Ruebesam K, Rohrer C, Nierop AF, Jahreis G, Baars T. J Sci Food Agric 2015;95:529–39.
  9. Yakoob MY, Shi P, Hu FB, Campos H, Rexrode KM, Orav EJ, Willett WC, Mozaffarian D. Am J Clin Nutr 2014;100:1437–47.
  10. Sun Q, Ma J, Campos H, Hu FB. Am J Clin Nutr 2007; 86:929–37.
  11. Forouhi NG, Koulman A, Sharp SJ, Imamura F, Kroger J, Schulze MB, Crowe FL, Huerta JM, Guevara M, Beulens JW, et al. Lancet Diabetes Endocrinol 2014;2:810–8.
  12. Golley RK, Hendrie GA. Ann Nutr Metab 2014;65:310–6.
  13. Allen NE, Grace PB, Ginn A, Travis RC, Roddam AW, Appleby PN, Key T. Br J Nutr 2008;99:653–9.
  14. Jenkins B, West JA, Koulman A. Molecules 2015;20:2425–44.
  15. Al-Lahham SH, Peppelenbosch MP, Roelofsen H, Vonk RJ, Venema K. Biochim Biophys Acta= 2010;1801:1175–83.
  16. Weitkunat K, Schumann S, Petzke KJ, Blaut M, Loh G, Klaus S. J Nutr Biochem 2015;26:929–37.
  17. Oizumi J, Giudici TA, Ng WG, Shaw KN, Donnell GN. Biochem Med 1981;26:28–40.
  18. Sperl W, Murr C, Skladal D, Sass JO, Suormala T, Baumgartner R,Wendel U. Eur J Pediatr 2000;159:54–8.
  19. Kishimoto Y, Williams M, Moser HW, Hignite C, Biermann K. J Lipid Res 1973;14:69–77.
  20. Dahiya R, Brasitus TA. Lipids 1986;21:112–6.
  21. Kondo N, Ohno Y, YamagataM, Obara T, Seki N, Kitamura T, Naganuma T, Kihara A. Nat Commun 2014;5: 5338.
  22. Roberts LD, Virtue S, Vidal-Puig A, Nicholls AW, Griffin JL. Physiol Genomics 2009;39:109–19.
  23. Hodson, L.; Skeaff, C.M.; Fielding, B.A. Prog. Lipid Res. 2008, 47, 348–380.
  24. Khaw, K.T.; Friesen, M.D.; Riboli, E.; Luben, R.; Wareham, N.PLoS Med. 2012, 9, e1001255.
  25. Çoker, M.; de Klerk, J.B.C.; Poll-The, B.T.; Huijmans, J.G.M.; Duran, M. J. Inherit. Metab. Dis. 1996, 19, 743–751.
  26. Phillips, G.B.; Dodge, J.T. J. Lipid Res. 1967, 8, 676–681.
  27. Horning, M.G.; Martin, D.B.; Karmen, A.; Vagelos, P.R. J. Biol. Chem. 1961, 236, 669–672.
  28. Mead, J.F.; Gabriel, M. Levis. A 1 J. Biol. Chem. 1963, 238, 1634–1636.
  29. Vanitallie, T.B.; Khachadurian, A.K. Science 1969, 165, 811–813.
  30. Jansen, G.A.; Ronald, J.A. Wanders. Alpha-oxidation. Biochim. Biophys. Acta (BBA) Mol. Cell Res. 2006, 1763, 1403–1412.
  31. Ferrannini, E.; Barrett, E.J.; Bevilacqua, S.; DeFronzo, R.A. J. Clin. Investig. 1983, 72, 1737–1747.
  32. Nestel, P.J.; Straznicky, N.; Mellett, N.A.; Wong, G.; De Souza, D.P.; Tull, D.L.; Barlow, C.K.; Grima, M.T.; Meikle, P.J. Am. J. Clin. Nutr. 2014, 99, 46–53.
  33. Tserng, K.Y.; Kliegman, R.M.; Miettinen, E.L.; Kalhan, S.C. J. Lipid Res. 1981, 22, 852–858.
  34. Persson, X.M.; Blachnio-Zabielska, A.U.; Jensen, M.D. J. Lipid Res. 2010, 51, 2761–2765.
  35. Baylin, A.; Kim, M.K.; Donovan-Palmer, A.; Siles, X.; Dougherty, L.; Tocco, P.; Campos, H. Fasting whole blood as a biomarker of essential fatty acid intake in epidemiologic studies: comparison with adipose tissue and plasma.Am. J. Epidemiol. 2005, 162, 373–381.
  36. Astrup, A. A changing view on saturated fatty acids and dairy: From enemy to friend. Am. J. Clin. Nutr. 2014, 100, 1407–1408.
  37. Seppänen-Laakso, T.; Oresic, M. How to study lipidomes. J. Mol. Endocrinol. 2009, 42, 185–190.
  38. Emmanuel, B. Biochim. Emmanuel, B. The relative contribution of propionate, and long-chain even-numbered fatty acids to the production of long-chain odd-numbered fatty acids in rumen bacteria. Biophys. Acta (BBA) Lipids Lipid Metab. 1978, 528, 239–246.
  ;

Spectrum Detail

Well-known Reagent Company Product Information

Supplier

Related Products