Abstract
In recent decades, mass spectrometry-based lipidomics has provided a fertile environment for scientific investigations of biochemical and mechanistic processes in biological systems. Notably, this approach has been used to characterize physiological and pathological processes relevant to the central nervous system by identifying changes in the sphingolipid content in the brain, cerebral spinal fluid, and blood plasma. However, despite a preponderance of studies identifying correlations between specific lipids and disease progression, this powerful resource has not yet substantively translated into clinically useful diagnostic assays. Part of this gap may be explained by insufficient depth of the lipidomic profiles in many studies, by lab-to-lab inconsistencies in methodology, and a lack of absolute quantification. These issues limit the identification of specific molecular species and the harmonization of results across independent studies. In this chapter, we contextualize these issues with recent reports identifying correlations between brain lipids and neurological diseases, and we describe the workflow our group has optimized for analysis of the blood plasma sphingolipidome, adapted to the characterization of the human brain tissue.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Mielke MM, Haughey NJ, Bandaru VVR et al (2010) Plasma ceramides are altered in MCI and predict cognitive decline and hippocampal volume loss. Alzheimers Dement 6:378–385. https://doi.org/10.1016/j.jalz.2010.03.014
Mielke MM, Bandaru VVR, Haughey NJ et al (2012) Serum ceramides increase the risk of Alzheimer disease: the Women’s Health and Aging Study II. Neurology 79:633–641. https://doi.org/10.1212/WNL.0b013e318264e380
Han X, Rozen S, Boyle SH et al (2011) Metabolomics in early Alzheimer’s disease: identification of altered plasma sphingolipidome using shotgun lipidomics. PLoS One 6:e21643. https://doi.org/10.1371/journal.pone.0021643
Huynh K, Lim WLF, Giles C et al (2020) Concordant peripheral lipidome signatures in two large clinical studies of Alzheimer’s disease. Nat Commun 11:5698. https://doi.org/10.1038/s41467-020-19473-7
Chua XY, Chai YL, Chew WS et al (2020) Immunomodulatory sphingosine-1-phosphates as plasma biomarkers of Alzheimer’s disease and vascular cognitive impairment. Alzheimers Res Ther 12:122. https://doi.org/10.1186/s13195-020-00694-3
Narayanaswamy P, Shinde S, Sulc R et al (2014) Lipidomic “deep profiling”: an enhanced workflow to reveal new molecular species of signaling lipids. Anal Chem 86:3043–3047. https://doi.org/10.1021/ac4039652
Lam BWS, Yam TYA, Chen CP et al (2021) The noncanonical chronicles: emerging roles of sphingolipid structural variants. Cell Signal 79:109890. https://doi.org/10.1016/j.cellsig.2020.109890
Han X, Fagan AM, Cheng H et al (2003) Cerebrospinal fluid sulfatide is decreased in subjects with incipient dementia. Ann Neurol 54:115–119. https://doi.org/10.1002/ana.10618
Kosicek M, Zetterberg H, Andreasen N et al (2012) Elevated cerebrospinal fluid sphingomyelin levels in prodromal Alzheimer’s disease. Neurosci Lett 516:302–305. https://doi.org/10.1016/j.neulet.2012.04.019
Vidaurre OG, Haines JD, Katz Sand I et al (2014) Cerebrospinal fluid ceramides from patients with multiple sclerosis impair neuronal bioenergetics. Brain 137:2271–2286. https://doi.org/10.1093/brain/awu139
Sol J, Jové M, Povedano M et al (2021) Lipidomic traits of plasma and cerebrospinal fluid in amyotrophic lateral sclerosis correlate with disease progression. Brain Commun 3:fcab143. https://doi.org/10.1093/braincomms/fcab143
Hejazi L, Wong JWH, Cheng D et al (2011) Mass and relative elution time profiling: two-dimensional analysis of sphingolipids in Alzheimer’s disease brains. Biochem J 438:165–175. https://doi.org/10.1042/BJ20110566
Han X, Holtzman DM, McKeel DW et al (2002) Substantial sulfatide deficiency and ceramide elevation in very early Alzheimer’s disease: potential role in disease pathogenesis. J Neurochem 82:809–818. https://doi.org/10.1046/j.1471-4159.2002.00997.x
Akyol S, Ugur Z, Yilmaz A et al (2021) Lipid profiling of Alzheimer’s disease brain highlights enrichment in glycerol(phospho)lipid, and sphingolipid metabolism. Cell 10:2591. https://doi.org/10.3390/cells10102591
Couttas TA, Rustam YH, Song H et al (2020) A novel function of sphingosine kinase 2 in the metabolism of Sphinga-4,14-diene lipids. Meta 10:236. https://doi.org/10.3390/metabo10060236
Podbielska M, Szulc ZM, Ariga T et al (2020) Distinctive sphingolipid patterns in chronic multiple sclerosis lesions. J Lipid Res 61:1464–1479. https://doi.org/10.1194/jlr.RA120001022
Don AS, Hsiao J-HT, Bleasel JM et al (2014) Altered lipid levels provide evidence for myelin dysfunction in multiple system atrophy. Acta Neuropathol Commun 2:150. https://doi.org/10.1186/s40478-014-0150-6
Di Pardo A, Basit A, Armirotti A et al (2017) De novo synthesis of sphingolipids is defective in experimental models of Huntington’s disease. Front Neurosci 11:698. https://doi.org/10.3389/fnins.2017.00698
Fitzner D, Bader JM, Penkert H et al (2020) Cell-type- and brain-region-resolved mouse brain Lipidome. Cell Rep 32:108132. https://doi.org/10.1016/j.celrep.2020.108132
Ju J, Yang X, Jiang J et al (2021) Structural and lipidomic alterations of striatal myelin in 16p11.2 deletion mouse model of autism spectrum disorder. Front Cell Neurosci 15:718720. https://doi.org/10.3389/fncel.2021.718720
Wang C, Palavicini JP, Han X (2021) A lipidomics atlas of selected sphingolipids in multiple mouse nervous system regions. Int J Mol Sci 22:11358. https://doi.org/10.3390/ijms222111358
Burla B, Muralidharan S, Wenk MR, Torta F (2018) Sphingolipid analysis in clinical research. Methods Mol Biol 1730:135–162. https://doi.org/10.1007/978-1-4939-7592-1_11
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature
About this protocol
Cite this protocol
Chua, X.Y., Huang, R., Herr, D., Lai, M.K.P., Wenk, M.R., Torta, F. (2023). Mass Spectrometry Analysis of the Human Brain Sphingolipidome. In: Chun, J. (eds) Alzheimer’s Disease. Methods in Molecular Biology, vol 2561. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2655-9_12
Download citation
DOI: https://doi.org/10.1007/978-1-0716-2655-9_12
Published:
Publisher Name: Humana, New York, NY
Print ISBN: 978-1-0716-2654-2
Online ISBN: 978-1-0716-2655-9
eBook Packages: Springer Protocols