Clinical lipidomics - A community-driven roadmap to translate research into clinical applications
Status PubMed-not-MEDLINE Jazyk angličtina Země Nizozemsko Médium electronic-ecollection
Typ dokumentu časopisecké články
PubMed
35199094
PubMed Central
PMC8844780
DOI
10.1016/j.jmsacl.2022.02.002
PII: S2667-145X(22)00003-7
Knihovny.cz E-zdroje
- Klíčová slova
- Harmonization, Lipidomics, Standardization, Translation, Validation,
- Publikační typ
- časopisecké články MeSH
Lipid metabolites, beyond triglycerides and cholesterol, have been shown to have vast potential for applications in clinical applications, with substantial societal and economical value. To successfully evolve from the current research-grade methods to assays suitable for routine clinical applications, a harmonization - if not standardization - of these mass spectrometry-based workflows is necessary. Input on clinical needs and technological capabilities must be obtained from all relevant stakeholders, including wet lab scientists, informaticians and data scientists, manufacturers, and medical professionals. In order to build bridges between this diverse group of professionals, the International Lipidomics Society and its Clinical Lipidomics Interest Group were created. This opinion article is intended to provide an overview of international efforts to tackle the issues of workflow harmonization, and to serve as an open invitation for others to join this growing community.
Baker Heart and Diabetes Institute Melbourne Victoria Australia
Institute for Laboratory Medicine in the Munich University Clinic Munich Germany
Lipidomics Consulting Ltd Esbo Finland
Max Planck Institute of Molecular Cell Biology and Genetics Dresden Germany
Singapore Lipidomics Incubator Life Sciences Institute National University of Singapore Singapore
Zobrazit více v PubMed
Rämö J.T., Ripatti P., Tabassum R., Söderlund S., Matikainen N., Gerl M.J., Klose C., Surma M.A., Stitziel N.O., Havulinna A.S. Coronary artery disease risk and lipidomic profiles are similar in hyperlipidemias with family history and population-ascertained hyperlipidemias. J. Am. Heart Assoc. 2019;8(13):e012415. PubMed PMC
Vvedenskaya O., Rose T.D., Knittelfelder O., Palladini A., Wodke J.A.H., Schumann K., Ackerman J.M., Wang Y., Has C., Brosch M., Thangapandi V.R., Buch S., Züllig T., Hartler J., Köfeler H.C., Röcken C., Coskun Ü., Klipp E., von Schoenfels W., Gross J., Schafmayer C., Hampe J., Pauling J.K., Shevchenko A. Non-alcoholic fatty liver disease stratification by liver lipidomics. J. Lipid Res. 2021:100104. PubMed PMC
Hilvo M., Meikle P.J., Pedersen E.R., Tell G.S., Dhar I., Brenner H., Schöttker B., Lääperi M., Kauhanen D., Koistinen K.M. Development and validation of a ceramide-and phospholipid-based cardiovascular risk estimation score for coronary artery disease patients. Eur. Heart J. 2020;41(3):371–380. PubMed
Tham Y.K., Jayawardana K.S., Alshehry Z.H., Giles C., Huynh K., Smith A.A.T., Ooi J.Y.Y., Zoungas S., Hillis G.S., Chalmers J. Novel lipid species for detecting and predicting atrial fibrillation in patients with type 2 diabetes. Diabetes. 2021;70(1):255–261. PubMed
Huynh K., Lim W.L.F., Giles C., Jayawardana K.S., Salim A., Mellett N.A., Smith A.A.T., Olshansky G., Drew B.G., Chatterjee P., Martins I., Laws S.M., Bush A.I., Rowe C.C., Villemagne V.L., Ames D., Masters C.L., Arnold M., Nho K., Saykin A.J., Baillie R., Han X., Kaddurah-Daouk R., Martins R.N., Meikle P.J. Concordant peripheral lipidome signatures in two large clinical studies of Alzheimer’s disease. Nat Commun. 2020;11(1):5698. PubMed PMC
Wolrab D., Jirásko R., Chocholoušková M., Peterka O., Holčapek M. Oncolipidomics: Mass spectrometric quantitation of lipids in cancer research. TrAC, Trends Anal. Chem. 2019;120
Meikle T.G., Huynh K., Giles C., Meikle P.J. Clinical lipidomics: realizing the potential of lipid profiling. J. Lipid Res. 2021:100127. PubMed PMC
O’Donnell V.B., Dennis E.A., Wakelam M.J.O., Subramaniam S. LIPID MAPS: Serving the next generation of lipid researchers with tools, resources, data, and training. Sci. Signal. 2019;12(563) eaaw2964–eaaw2964. PubMed
O’Donnell V.B., Ekroos K., Liebisch G., Wakelam M. Lipidomics: Current state of the art in a fast moving field. Wiley Interdiscip. Rev. Syst. Biol. Med. 2020;12(1):e1466. PubMed
M. Holcapek, E. Cifkova, M. Lisa, R. Jirasko, D. Wolrab, H. Tereza, A method of diagnosing pancreatic cancer based on lipidomic analysis of a body fluid. EP3514545B1, 2020.
M. Bitenc, K. Kruusmaa, P. Hurtado-Castillo, A.M. Jiménez-Girón, R. Argamasilla-Martinez, A. Fabregat-Rossel, A.J. Adsuar-Gomez, J. Martinez-Barea, C. Hense, P. Rodríguez-Gómez, Á. Peralbo-Molina, J. Casado-Agrelo, A. Sánchez-Brotons, C. Pavón-Solís, R.M. Delgado-Sánchez, Methods and systems for metabolite and/or lipid-based detection of colorectal cancer and/or adenomatous polyps. 2018.
12. Reijo L, Ekroos K, Reini H, Katainen R. Lipidomic biomarkers for identification of high-risk coronary artery disease patients. 10955427, 2021.
Lipidomics-Standards-Initiative (LSI). Lipidomics Standards Initiative [Internet]. Available from: https://lipidomics-standards-initiative.org.
Liebisch G., Ahrends R., Arita M., Arita M., Bowden J.A., Ejsing C.S., Griffiths W.J., Holčapek M., Köfeler H., Mitchell T.W., Wenk M.R., Ekroos K., Consortium LSI Lipidomics needs more standardization. Nat. Metab. 2019;1(8):745–747. doi: 10.1038/s42255-019-0094-z. PubMed DOI
Metabolomics Society I. Metabolomics Society, Scientific Task Groups [Internet]. Available from: https://metabolomicssociety.org/board-committees/scientific-task-groups/.
Köhler N., Rose T.D., Falk L., Pauling J.K. Investigating global lipidome alterations with the lipid network explorer. Metabolites. 2021;11(8):488. PubMed PMC
Tsugawa H., Ikeda K., Arita M. The importance of bioinformatics for connecting data-driven lipidomics and biological insights. Biochim. Biophys. Acta, Mol. Cell. Biol. Lipids. 2017;1862(8):762–765. PubMed
Sales S., Graessler J., Ciucci S., Al-Atrib R., Vihervaara T., Schuhmann K., Kauhanen D., Sysi-Aho M., Bornstein S.R., Bickle M., Cannistraci C.V., Ekroos K., Shevchenko A. Gender, contraceptives and individual metabolic predisposition shape a healthy plasma lipidome. Sci. Rep. 2016;6(1):1–14. PubMed PMC
Ambaw Y.A., Pagac M.P., Irudayaswamy A.S., Raida M., Bendt A.K., Torta F.T., Wenk M.R., Dawson T.L. Host/malassezia interaction: A quantitative, non-invasive method profiling oxylipin production associates human skin eicosanoids with malassezia. Metabolites. 2021;11(10):700. PubMed PMC
Nakashima Y., Sakai Y., Mizuno Y., Furuno K., Hirono K., Takatsuki S., Suzuki H., Onouchi Y., Kobayashi T., Tanabe K. Lipidomics links oxidized phosphatidylcholines and coronary arteritis in Kawasaki disease. Cardiovasc. Res. 2021;117(1):96–108. PubMed
Hirata T., Yamamoto K., Ikeda K., Arita M. Functional lipidomics of vascular endothelial cells in response to laminar shear stress. FASEB J. 2021;35(2) PubMed
Wolrab D., Jirásko R., Cífková E., Höring M., Mei D., Chocholoušková M., Peterka O., Idkowiak J., Hrnčiarová T., Kuchař L., Ahrends R., Brumarová R., Friedecký D., Vivo-Truyols G., Škrha P., Škrha J., Kučera R., Melichar B., Liebisch G., Burkhardt R., Wenk M.R., Cazenave-Gassiot A., Karásek P., Novotný I., Greplová K., Hrstka R., Holčapek M. Lipidomic profiling of human serum enables detection of pancreatic cancer. Nat. Commun. 2022;13(1):124. PubMed PMC
B.A. Rappold, A. Hoofnagle, Clinical Chemistry Podcast: Clinical Protein Analysis by Mass Spectrometry: A New Higher Order. PubMed
Bowden J.A., Heckert A., Ulmer C.Z., Jones C.M., Koelmel J.P., Abdullah L., Ahonen L., Alnouti Y., Armando A.M., Asara J.M., Bamba T., Barr J.R., Bergquist J., Borchers C.H., Brandsma J., Breitkopf S.B., Cajka T., Cazenave-Gassiot A., Checa A., Cinel M.A., Colas R.A., Cremers S., Dennis E.A., Evans J.E., Fauland A., Fiehn O., Gardner M.S., Garrett T.J., Gotlinger K.H., Han J., Huang Y., Neo A.H., Hyötyläinen T., Izumi Y., Jiang H., Jiang H., Jiang J., Kachman M., Kiyonami R., Klavins K., Klose C., Köfeler H.C., Kolmert J., Koal T., Koster G., Kuklenyik Z., Kurland I.J., Leadley M., Lin K., Maddipati K.R., McDougall D., Meikle P.J., Mellett N.A., Monnin C., Moseley M.A., Nandakumar R., Oresic M., Patterson R., Peake D., Pierce J.S., Post M., Postle A.D., Pugh R., Qiu Y., Quehenberger O., Ramrup P., Rees J., Rembiesa B., Reynaud D., Roth M.R., Sales S., Schuhmann K., Schwartzman M.L., Serhan C.N., Shevchenko A., Somerville S.E., St John-Williams L., Surma M.A., Takeda H., Thakare R., Thompson J.W., Torta F., Triebl A., Trötzmüller M., Ubhayasekera S.J.K., Vuckovic D., Weir J.M., Welti R., Wenk M.R., Wheelock C.E., Yao L., Yuan M., Zhao X.H., Zhou S. Harmonizing lipidomics: NIST interlaboratory comparison exercise for lipidomics using SRM 1950-Metabolites in frozen human plasma. J. Lipid Res. 2017;58(12):2275–2288. PubMed PMC
Burla B., Arita M., Arita M., Bendt A.K., Cazenave-Gassiot A., Dennis E.A., Ekroos K., Han X., Ikeda K., Liebisch G., Lin M.K., Loh T.P., Meikle P.J., Orešič M., Quehenberger O., Shevchenko A., Torta F., Wakelam M.J.O., Wheelock C.E., Wenk M.R. MS-based lipidomics of human blood plasma - a community-initiated position paper to develop accepted guidelines. J. Lipid Res. 2018 http://www.jlr.org/lookup/doi/10.1194/jlr.S087163 Available from. PubMed DOI PMC
Vvedenskaya O., Wang Y., Ackerman J.M., Knittelfelder O., Shevchenko A. Analytical challenges in human plasma lipidomics: a winding path towards the truth. TrAC - Trends Anal Chem. 2019;120
Aristizabal-Henao J.J., Jones C.M., Lippa K.A., Bowden J.A. Nontargeted lipidomics of novel human plasma reference materials: hypertriglyceridemic, diabetic, and African-American. Anal. Bioanal. Chem. 2020;412(27):7373–7380. PubMed