Analytical and Bioanalytical Chemistry

, Volume 410, Issue 25, pp 6517–6528 | Cite as

Clustering-based preprocessing method for lipidomic data analysis: application for the evolution of newborn skin surface lipids from birth until 6 months

  • Rime Michael-JubeliEmail author
  • Ali Tfayli
  • Caroline Baudouin
  • Jean Bleton
  • Dominique Bertrand
  • Arlette Baillet-Guffroy
Research Paper


After life in utero and birth, the skin is submitted to an important process of adaptation to a relatively dry gaseous environment. Skin surface lipids (SSLs) contribute actively to the protection of the skin barrier. Within this context, our objective was to study the evolution of each lipid compound during the postnatal period. SSLs were collected from six newborns a few days after birth until the age of 6 months. Seventy samples were analyzed using high-temperature gas chromatography coupled to mass spectrometry (HT-GC/MS). The use of separative techniques coupled to mass spectrometry for the analysis of samples containing complex mixtures of lipids generates a large volume of data which renders the results interpretation very difficult. In this study, we propose a new approach to handle the raw data, a clustering-based preprocessing method (CB-PPM), in order to achieve (1) volume reduction of data provided by each chromatogram without loss of information, (2) alignment of time retention shift between different runs, (3) clustering of mass spectra of the same molecule in one qualitative group, (4) and integration of all data into a single matrix to be explored by chemometric tools. This approach allowed us to gather data variations in 256 qualitative groups and therefore enabled us to highlight the variation of compounds including those of low intensity. Moreover, the representation of all data gathered in one matrix rendered reading of the results rapid and efficient. Thus, using this approach, we have demonstrated an increase of cholesterol esterification with epidermal fatty acids (C20 to C25) with age. This epidermis participation in SSL production at a molecular level in the first period of life has not been previously shown. These data can be very interesting for the development and improvement of products destined for the protection of infant skin.

Graphical abstract


Lipidomic Preprocessing data Clustering-based preprocessing method (CB-PPM) HT-GC/MS Skin surface lipids (SSLs) Epidermis lipids 



Clustering-based preprocessing method




Cholesteryl ester


Chemical ionization




Free fatty acid


High-temperature gas chromatography-mass spectrometry


Individual alignment of peaks


Independent component analysis




Principal component analysis




Skin surface lipid




Total ion current





We would like to thank Dr. Stéphanie Brédif from Expanscience Laboratoires-Epernon for her valuable input and assistance.

Compliance with ethical standards

All the parents of the infants who participated in this study gave their informed consent before the start of the experiment.

Conflict of interest

The authors declare that they have no conflict of interest.


  1. 1.
    Giusti F, Martella A, Bertoni L, Seidenari S. Skin barrier, hydration, and pH of the skin of infants under 2 years of age. Pediatr Dermatol. 2001;18:93–6.CrossRefPubMedGoogle Scholar
  2. 2.
    Hoeger PH, Enzmann CC. Skin physiology of the neonate and young infant: a prospective study of functional skin parameters during early infancy. Pediatr Dermatol. 2002;19:256–62.CrossRefPubMedGoogle Scholar
  3. 3.
    Youn SW, Kim SJ, Hwang IA, Park KC. Evaluation of facial skin type by sebum secretion: discrepancies between subjective descriptions and sebum secretion. Skin Res Technol. 2002;8:168–72.CrossRefPubMedGoogle Scholar
  4. 4.
    Fluhr JW, Darlenski R, Taieb A, Hachem J-P, Baudouin C, Msika P, et al. Functional skin adaptation in infancy—almost complete but not fully competent. Exp Dermatol. 2010;19:483–92.CrossRefPubMedGoogle Scholar
  5. 5.
    Tansirikongkol A, Wickett RR, Visscher MO, Hoath SB. Effect of vernix caseosa on the penetration of chymotryptic enzyme: potential role in epidermal barrier development. Pediatr Res. 2007;62:49–53.CrossRefPubMedGoogle Scholar
  6. 6.
    Rissmann R, Groenink HWW, Gooris GS, Oudshoorn MHM, Hennink WE, Ponec M, et al. Temperature-induced changes in structural and physicochemical properties of vernix caseosa. J Investig Dermatol. 2007;128:292–9.CrossRefPubMedGoogle Scholar
  7. 7.
    Rissmann R, Groenink HWW, Weerheim AM, Hoath SB, Ponec M, Bouwstra JA. New insights into ultrastructure, lipid composition and organization of vernix caseosa. J Investig Dermatol. 2006;126:1823–33.CrossRefPubMedGoogle Scholar
  8. 8.
    Agache P, Blanc D, Barrand C, Laurent R. Sebum levels during the first year of life. Br J Dermatol. 1980;103:643–50.CrossRefPubMedGoogle Scholar
  9. 9.
    Henderson CA, Taylor J, Cunliffe WJ. Sebum excretion rates in mothers and neonates. Br J Dermatol. 2000;142:110–1.CrossRefPubMedGoogle Scholar
  10. 10.
    Ramasastry P, Downing DT, Pochi PE, Strauss JS. Chemical composition of human skin surface lipids from birth to puberty. J Investig Dermatol. 1970;54:139–44.CrossRefPubMedGoogle Scholar
  11. 11.
    Downing DT, Strauss JS. Synthesis and composition of surface lipids of human skin. J Investig Dermatol. 1974;62:228–44.CrossRefGoogle Scholar
  12. 12.
    Stewart ME, Quinn MA, Downing DT. Variability in the fatty acid composition of wax esters from vernix caseosa and its possible relation to sebaceous gland activity. J Investig Dermatol. 1982;78:291–5.CrossRefPubMedGoogle Scholar
  13. 13.
    Nicolaides N, Fu H, Ansari M, Rice G. The fatty acids of wax esters and sterol esters from vernix caseosa and from human skin surface lipid. Lipids. 1972;7:506–17.CrossRefPubMedGoogle Scholar
  14. 14.
    Karkkainen J, Nikkari T, Ruponen S, Haahti E. Lipids of vernix caseosa. J Investig Dermatol. 1965;44:333–8.CrossRefGoogle Scholar
  15. 15.
    Downing DT, Greene RS. Double bond positions in the unsaturated fatty acids of vernix caseosa1. J Investig Dermatol. 1968;50:380–6.CrossRefPubMedGoogle Scholar
  16. 16.
    Ansari NMA, Fu HC, Nicolaides N. Fatty acides of alkans diols esters of vernix caseosa. Lipids. 1970;5:279–82.CrossRefPubMedGoogle Scholar
  17. 17.
    Myher JJ, Kuksis A. General strategies in chromatographic analysis of lipids. J Chromatogr B Biomed Sci Appl. 1995;671:3–33.CrossRefGoogle Scholar
  18. 18.
    Moldovan Z, Jover E, Bayona JM. Systematic characterisation of long-chain aliphatic esters of wool wax by gas chromatography-electron impact ionisation mass spectrometry. J Chromatogr A. 2002;952:193–204.CrossRefPubMedGoogle Scholar
  19. 19.
    Jover E, Moldovan Z, Bayona JM. Complete characterisation of lanolin steryl esters by sub-ambient pressure gas chromatography-mass spectrometry in the electron impact and chemical ionisation modes. J Chromatogr A. 2002;970:249–58.CrossRefPubMedGoogle Scholar
  20. 20.
    Aichholz R, Lorbeer E. Investigation of combwax of honeybees with high-temperature gas chromatography and high-temperature gas chromatography-chemical ionization mass spectrometry: II: high-temperature gas chromatography-chemical ionization mass spectrometry. J Chromatogr A. 2000;883:75–88.CrossRefPubMedGoogle Scholar
  21. 21.
    Aichholz R, Lorbeer E. Investigation of combwax of honeybees with high-temperature gas chromatography and high-temperature gas chromatography-chemical ionization mass spectrometry: I. High-temperature gas chromatography. J Chromatogr A. 1999;855:601–15.CrossRefPubMedGoogle Scholar
  22. 22.
    Christie WW. Determination of lipid profiles by gas chromatography. In: Christie WW, editor. Lipids Analysis. 3rd ed. Bridgwater: The Oily Press; 2003. p. 118–21.Google Scholar
  23. 23.
    Michael-Jubeli R, Bleton J, Baillet-Guffroy A. High-temperature gas chromatography-mass spectrometry for skin surface lipids profiling. J Lipid Res. 2011;52:143–51.CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Johnson KJ, Wright BW, Jarman KH, Synovec RE. High-speed peak matching algorithm for retention time alignment of gas chromatographic data for chemometric analysis. J Chromatogr A. 2003;996:141–55.CrossRefPubMedGoogle Scholar
  25. 25.
    Jouan-Rimbaud Bouveresse D, Benabid H, Rutledge DN. Independent component analysis as a pretreatment method for parallel factor analysis to eliminate artefacts from multiway data. Anal Chim Acta. 2007;589:216–24.CrossRefGoogle Scholar
  26. 26.
    Hyvarinen A, Oja E. Independent component analysis: algorithms and applications. Neural Netw. 2000;13:411–30.CrossRefPubMedGoogle Scholar
  27. 27.
    Jutten C, Herault J. Blind separation of sources, part I: an adaptive algorithm based on neuromimetic architecture. Signal Process. 1991;24:1–10.CrossRefGoogle Scholar
  28. 28.
    Ramsay JO, Silverman BW. Functional data analysis, Springer Series in Statistics. 2nd ed. NY: Springer; 2005. p. 217–22.Google Scholar
  29. 29.
    Katajamaa M, Oresic M. Processing methods for differential analysis of LC/MS profile data. BMC Bioinformatics. 2005;6:179.CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Katajamaa M, Miettinen J, Oresic M. MZmine: toolbox for processing and visualization of mass spectrometry based molecular profile data. Bioinformatics. 2006;22:634–6.CrossRefPubMedGoogle Scholar
  31. 31.
    Issaq HJ, Van QN, Waybright TJ, Muschik GM, Veenstra TD. Analytical and statistical approaches to metabolomics research. J Sep Sci. 2009;32:2183–99.CrossRefPubMedGoogle Scholar
  32. 32.
    Robinson M, De Souza D, Keen W, Saunders E, McConville M, Speed T, et al. A dynamic programming approach for the alignment of signal peaks in multiple gas chromatography-mass spectrometry experiments. BMC Bioinformatics. 2007;8:419.CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Hartigan JA, Wong MA, Algorithm AS. 136: a K-means clustering algorithm. J R Stat Soc: Ser C: Appl Stat. 1979;28:100–8.Google Scholar
  34. 34.
    Ward JH. Hierarchical grouping to optimize an objective function. J Am Stat Assoc. 1963;58:236–44.CrossRefGoogle Scholar
  35. 35.
    Ben-Hur A, Guyon I. Detecting stable clusters using principal component analysis. In: Brownstein M, Khodursky A, editors. Functional genomics; methods and protocoles, vol. 224. NY: Humana Press; 2003. p. 159–82.CrossRefGoogle Scholar
  36. 36.
    Nicolaides N. Skin lipids: their biochemical uniqueness. Science. 1974;186:19–26.CrossRefPubMedGoogle Scholar
  37. 37.
    Saint-Léger D. Normal and pathologic sebaceous function. Pathol Biol. 2003;51:275–8.CrossRefPubMedGoogle Scholar
  38. 38.
    Visscher MO, Chatterje R, Munson KA, Pickens WL, Hoath SB. Changes in diapered and nondiapered infant skin over the first month of life. Pediatr Dermatol. 2000;17:45–51.CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Rime Michael-Jubeli
    • 1
    Email author
  • Ali Tfayli
    • 1
  • Caroline Baudouin
    • 2
  • Jean Bleton
    • 3
  • Dominique Bertrand
    • 4
  • Arlette Baillet-Guffroy
    • 1
  1. 1.Lip(Sys)2- Chimie Analytique Pharmaceutique (FKA EA4041 Groupe de Chimie Analytique de Paris-Sud)University Paris-Sud 11, Université Paris-SaclayChâtenay-MalabryFrance
  2. 2.Laboratoires ExpanscienceEpernonFrance
  3. 3.Lip(Sys)2- LETIAM (FKA EA4041 Groupe de Chimie Analytique de Paris-Sud)University Paris-Sud, Université Paris-SaclayOrsayFrance
  4. 4.data_frameNantesFrance

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