SLIDE-Novel Approach to Apocrine Sweat Sampling for Lipid Profiling in Healthy Individuals

. 2021 Jul 28 ; 22 (15) : . [epub] 20210728

Jazyk angličtina Země Švýcarsko Médium electronic

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid34360820

Grantová podpora
NU20-08-00367 Agentura Pro Zdravotnický Výzkum České Republiky
FNOL, 00098892 Ministerstvo Zdravotnictví Ceské Republiky
FNHK, 00179906 Ministerstvo Zdravotnictví Ceské Republiky

We designed a concept of 3D-printed attachment with porous glass filter disks-SLIDE (Sweat sampLIng DevicE) for easy sampling of apocrine sweat. By applying advanced mass spectrometry coupled with the liquid chromatography technique, the complex lipid profiles were measured to evaluate the reproducibility and robustness of this novel approach. Moreover, our in-depth statistical evaluation of the data provided an insight into the potential use of apocrine sweat as a novel and diagnostically relevant biofluid for clinical analyses. Data transformation using probabilistic quotient normalization (PQN) significantly improved the analytical characteristics and overcame the 'sample dilution issue' of the sampling. The lipidomic content of apocrine sweat from healthy subjects was described in terms of identification and quantitation. A total of 240 lipids across 15 classes were identified. The lipid concentrations varied from 10-10 to 10-4 mol/L. The most numerous class of lipids were ceramides (n = 61), while the free fatty acids were the most abundant ones (average concentrations of 10-5 mol/L). The main advantages of apocrine sweat microsampling include: (a) the non-invasiveness of the procedure and (b) the unique feature of apocrine sweat, reflecting metabolome and lipidome of the intracellular space and plasmatic membranes. The SLIDE application as a sampling technique of apocrine sweat brings a promising alternative, including various possibilities in modern clinical practice.

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Wilke K., Martin A., Terstegen L., Biel S.S. A short history of sweat gland biology. Int. J. Cosmet. Sci. 2007;29:169–179. doi: 10.1111/j.1467-2494.2007.00387.x. PubMed DOI

Montagna W. The Structure and Function of Skin. Elsevier; Amsterdam, The Netherlands: 2012.

Sato K. The physiology, pharmacology, and biochemistry of the eccrine sweat gland. Rev. Physiol. Biochem. Pharmacol. 1977;79:51–131. PubMed

Sato K., Sato F. Sweat secretion by human axillary apoeccrine sweat gland in vitro. Am. J. Physiol. 1987;252:R181–R187. doi: 10.1152/ajpregu.1987.252.1.R181. PubMed DOI

Bovell D.L., Corbett A.D., Holmes S., Macdonald A., Harker M. The absence of apoeccrine glands in the human axilla has disease pathogenetic implications, including axillary hyperhidrosis. Br. J. Dermatol. 2007;156:1278–1286. doi: 10.1111/j.1365-2133.2007.07917.x. PubMed DOI

Farkaš R. Apocrine secretion: New insights into an old phenomenon. Biochim. Biophys. Acta. 2015;1850:1740–1750. doi: 10.1016/j.bbagen.2015.05.003. PubMed DOI

Aumüller G., Wilhelm B., Seitz J. Apocrine secretion—fact or artifact? Ann. Anat. Anat. Anz. 1999;181:437–446. doi: 10.1016/S0940-9602(99)80020-X. PubMed DOI

Stefaniak A.B., Harvey C.J. Dissolution of materials in artificial skin surface film liquids. Toxicol. In Vitro. 2006;20:1265–1283. doi: 10.1016/j.tiv.2006.05.011. PubMed DOI

Baker L.B. Physiology of sweat gland function: The roles of sweating and sweat composition in human health. Temperature (Austin) 2019;6:211–259. doi: 10.1080/23328940.2019.1632145. PubMed DOI PMC

Lin S., Yu W., Wang B., Zhao Y., En K., Zhu J., Cheng X., Zhou C., Lin H., Wang Z., et al. Noninvasive wearable electroactive pharmaceutical monitoring for personalized therapeutics. Proc. Natl. Acad. Sci. USA. 2020;117:19017–19025. doi: 10.1073/pnas.2009979117. PubMed DOI PMC

Hudson M., Stuchinskaya T., Ramma S., Patel J., Sievers C., Goetz S., Hines S., Menzies E., Russell D.A. Drug screening using the sweat of a fingerprint: Lateral flow detection of Δ9-tetrahydrocannabinol, cocaine, opiates and amphetamine. J. Anal. Toxicol. 2019;43:88–95. doi: 10.1093/jat/bky068. PubMed DOI PMC

Sears M.E., Kerr K.J., Bray R.I. Arsenic, cadmium, lead, and mercury in sweat: A systematic review. J. Environ. Public Health. 2012;2012 doi: 10.1155/2012/184745. PubMed DOI PMC

Genuis S.J., Beesoon S., Lobo R.A., Birkholz D. Human elimination of phthalate compounds: Blood, urine, and sweat (BUS) study. Sci. World J. 2012;2012 doi: 10.1100/2012/615068. PubMed DOI PMC

Austin C., Ellis J. Microbial pathways leading to steroidal malodour in the axilla. J. Steroid Biochem. Mol. Biol. 2003;87:105–110. doi: 10.1016/S0960-0760(03)00387-X. PubMed DOI

Mebazaa R., Rega B., Camel V. Analysis of human male armpit sweat after fenugreek ingestion: Characterisation of odour active compounds by gas chromatography coupled to mass spectrometry and olfactometry. Food Chem. 2011;128:227–235. doi: 10.1016/j.foodchem.2011.02.063. PubMed DOI

Farkaš R., Ďatková Z., Mentelová L., Löw P., Beňová-Liszeková D., Beňo M., Sass M., Řehulka P., Řehulková H., Raška O., et al. Apocrine secretion in drosophila salivary glands: Subcellular origin, dynamics, and identification of secretory proteins. PLoS ONE. 2014;9:e94383. doi: 10.1371/journal.pone.0094383. PubMed DOI PMC

Nanjappa V., Thomas J.K., Marimuthu A., Muthusamy B., Radhakrishnan A., Sharma R., Ahmad Khan A., Balakrishnan L., Sahasrabuddhe N.A., Kumar S., et al. Plasma proteome database as a resource for proteomics research: 2014 update. Nucleic Acids Res. 2014;42:D959–D965. doi: 10.1093/nar/gkt1251. PubMed DOI PMC

Shelley W.B., Hurley H.J., Jr. The physiology of the human axillary apocrine sweat gland. J. Investig. Dermatol. 1953;20:285–297. doi: 10.1038/jid.1953.35. PubMed DOI

McGrath K.G. Apocrine sweat gland obstruction by antiperspirants allowing transdermal absorption of cutaneous generated hormones and pheromones as a link to the observed incidence rates of breast and prostate cancer in the 20th century. Med. Hypotheses. 2009;72:665–674. doi: 10.1016/j.mehy.2009.01.025. PubMed DOI

Jadoon S., Karim S., Akram M.R., Kalsoom Khan A., Zia M.A., Siddiqi A.R., Murtaza G. Recent developments in sweat analysis and its applications. Int. J. Anal. Chem. 2015;2015 doi: 10.1155/2015/164974. PubMed DOI PMC

Hussain J.N., Mantri N., Cohen M.M. Working up a good sweat-the challenges of standardising sweat collection for metabolomics analysis. Clin. Biochem. Rev. 2017;38:13–34. PubMed PMC

World Health Organization . WHO Best Practices for Injections and Related Procedures Toolkit. World Health Organization; Geneva, Switzerland: 2013. PubMed

Dieterle F., Ross A., Schlotterbeck G., Senn H. Probabilistic quotient normalization as robust method to account for dilution of complex biological mixtures. Application in 1H NMR metabonomics. Anal. Chem. 2006;78:4281–4290. doi: 10.1021/ac051632c. PubMed DOI

Li B., Tang J., Yang Q., Cui X., Li S., Chen S., Cao Q., Xue W., Chen N., Zhu F. Performance evaluation and online realization of data-driven normalization methods used in LC/MS based untargeted metabolomics analysis. Sci. Rep. 2016;6:1–13. doi: 10.1038/srep38881. PubMed DOI PMC

Shannon P., Markiel A., Ozier O., Baliga N.S., Wang J.T., Ramage D., Amin N., Schwikowski B., Ideker T. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13:2498–2504. doi: 10.1101/gr.1239303. PubMed DOI PMC

Liebisch G., Vizcaíno J.A., Köfeler H., Trötzmüller M., Griffiths W.J., Schmitz G., Spener F., Wakelam M.J.O. Shorthand notation for lipid structures derived from mass spectrometry. J. Lipid Res. 2013;54:1523–1530. doi: 10.1194/jlr.M033506. PubMed DOI PMC

Avela H.F., Sirén H. Advances in lipidomics. Clin. Chim. Acta. 2020;510:123–141. doi: 10.1016/j.cca.2020.06.049. PubMed DOI

Wang M., Wang C., Han X. Selection of Internal standards for accurate quantification of complex lipid species in biological extracts by electrospray ionization mass spectrometry-what, how and why? Mass Spectrom. Rev. 2017;36:693–714. doi: 10.1002/mas.21492. PubMed DOI PMC

Lange M., Fedorova M. Evaluation of Lipid quantification accuracy using HILIC and RPLC MS on the example of NIST® SRM® 1950 metabolites in human plasma. Anal. Bioanal. Chem. 2020;412:3573–3584. doi: 10.1007/s00216-020-02576-x. PubMed DOI PMC

Kirk J.M., Keston M., McIntosh I., Al Essa S. Variation of sweat sodium and chloride with age in cystic fibrosis and normal populations: Further investigations in equivocal cases. Pt 2Ann. Clin. Biochem. 1992;29:145–152. doi: 10.1177/000456329202900204. PubMed DOI

Chen Y., Shen G., Zhang R., He J., Zhang Y., Xu J., Yang W., Chen X., Song Y., Abliz Z. Combination of injection volume calibration by creatinine and ms signals’ normalization to overcome urine variability in LC-MS-based metabolomics studies. Anal. Chem. 2013;85:7659–7665. doi: 10.1021/ac401400b. PubMed DOI

Wong M.W.K., Braidy N., Pickford R., Vafaee F., Crawford J., Muenchhoff J., Schofield P., Attia J., Brodaty H., Sachdev P., et al. Plasma lipidome variation during the second half of the human lifespan is associated with age and sex but minimally with BMI. PLoS ONE. 2019;14:e0214141. doi: 10.1371/journal.pone.0214141. PubMed DOI PMC

Takemura T., Wertz P.W., Sato K. Free fatty acids and sterols in human eccrine sweat. Br. J. Dermatol. 1989;120:43–47. doi: 10.1111/j.1365-2133.1989.tb07764.x. PubMed DOI

Peter G., Schröpl F., Feisel H.G., Thürauf W. Gaschromatographische untersuchungen von freien und gebundenen fettsäuren im ekkrinen Schweiß. Arch. Dermatol. Res. 1970;238:154–159. doi: 10.1007/BF00519900. PubMed DOI

Coderch L., López O., de la Maza A., Parra J.L. Ceramides and skin function. Am. J. Clin. Dermatol. 2003;4:107–129. doi: 10.2165/00128071-200304020-00004. PubMed DOI

Agrawal K., Hassoun L.A., Foolad N., Pedersen T.L., Sivamani R.K., Newman J.W. Sweat lipid mediator profiling: A noninvasive approach for cutaneous research. J. Lipid Res. 2017;58:188–195. doi: 10.1194/jlr.M071738. PubMed DOI PMC

Lovászi M., Szegedi A., Zouboulis C.C., Törőcsik D. Sebaceous-immunobiology is orchestrated by sebum lipids. Dermatoendocrinology. 2017;9:e1375636. doi: 10.1080/19381980.2017.1375636. PubMed DOI PMC

Begum H., Torta F., Narayanaswamy P., Mundra P.A., Ji S., Bendt A.K., Saw W.-Y., Teo Y.Y., Soong R., Little P.F., et al. Lipidomic profiling of plasma in a healthy singaporean population to identify ethnic specific differences in lipid levels and associations with disease risk factors. Clin. Mass Spectrom. 2017;6:25–31. doi: 10.1016/j.clinms.2017.11.002. DOI

Weir J.M., Wong G., Barlow C.K., Greeve M.A., Kowalczyk A., Almasy L., Comuzzie A.G., Mahaney M.C., Jowett J.B.M., Shaw J., et al. Plasma lipid profiling in a large population-based cohort. J. Lipid Res. 2013;54:2898–2908. doi: 10.1194/jlr.P035808. PubMed DOI PMC

Skandalakis J.E., Skandalakis L.J., Skandalakis P.N. Anatomy of the lymphatics. surg. Oncol. Clin. N. Am. 2007;16:1–16. doi: 10.1016/j.soc.2006.10.006. PubMed DOI

Zane P., Emmons G.T., editors. Microsampling in Pharmaceutical Bioanalysis. Future Science; London, UK: 2013.

Moyer J., Wilson D., Finkelshtein I., Wong B., Potts R. Correlation between sweat glucose and blood glucose in subjects with diabetes. Diabetes Technol. Ther. 2012;14:398–402. doi: 10.1089/dia.2011.0262. PubMed DOI

Xuan Q., Hu C., Yu D., Wang L., Zhou Y., Zhao X., Li Q., Hou X., Xu G. Development of a high coverage pseudotargeted lipidomics method based on ultra-high performance liquid chromatography-mass spectrometry. Anal. Chem. 2018;90:7608–7616. doi: 10.1021/acs.analchem.8b01331. PubMed DOI PMC

Drotleff B., Roth S.R., Henkel K., Calderón C., Schlotterbeck J., Neukamm M.A., Lämmerhofer M. Lipidomic profiling of non-mineralized dental plaque and biofilm by untargeted UHPLC-QTOF-MS/MS and swath acquisition. Anal. Bioanal. Chem. 2020;412:2303–2314. doi: 10.1007/s00216-019-02364-2. PubMed DOI PMC

AlzbetaG AlzbetaG/Metabol: First Version (Version v1.0.0) [(accessed on 1 July 2021)];Zenodo. 2019 May 30; Available online: https://zenodo.org/record/3235775#.YP4UukARWUk.

Wei R., Wang J., Su M., Jia E., Chen S., Chen T., Ni Y. Missing value imputation approach for mass spectrometry-based metabolomics data. Sci. Rep. 2018;8:663. doi: 10.1038/s41598-017-19120-0. PubMed DOI PMC

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