Sex-specific plasma lipid profiles of ME/CFS patients and their association with pain, fatigue, and cognitive symptoms

Aurore Nkiliza, Megan Parks, Adam Cseresznye, Sarah Oberlin, James E Evans, Teresa Darcey, Kristina Aenlle, Daniel Niedospial, Michael Mullan, Fiona Crawford, Nancy Klimas, Laila Abdullah, Aurore Nkiliza, Megan Parks, Adam Cseresznye, Sarah Oberlin, James E Evans, Teresa Darcey, Kristina Aenlle, Daniel Niedospial, Michael Mullan, Fiona Crawford, Nancy Klimas, Laila Abdullah

Abstract

Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex illness which disproportionally affects females. This illness is associated with immune and metabolic perturbations that may be influenced by lipid metabolism. We therefore hypothesized that plasma lipids from ME/CFS patients will provide a unique biomarker signature of disturbances in immune, inflammation and metabolic processes associated with ME/CFS.

Methods: Lipidomic analyses were performed on plasma from a cohort of 50 ME/CFS patients and 50 controls (50% males and similar age and ethnicity per group). Analyses were conducted with nano-flow liquid chromatography (nLC) and high-performance liquid chromatography (HPLC) systems coupled with a high mass accuracy ORBITRAP mass spectrometer, allowing detection of plasma lipid concentration ranges over three orders of magnitude. We examined plasma phospholipids (PL), neutral lipids (NL) and bioactive lipids in ME/CFS patients and controls and examined the influence of sex on the relationship between lipids and ME/CFS diagnosis.

Results: Among females, levels of total phosphatidylethanolamine (PE), omega-6 arachidonic acid-containing PE, and total hexosylceramides (HexCer) were significantly decreased in ME/CFS compared to controls. In males, levels of total HexCer, monounsaturated PE, phosphatidylinositol (PI), and saturated triglycerides (TG) were increased in ME/CFS patients compared to controls. Additionally, omega-6 linoleic acid-derived oxylipins were significantly increased in male ME/CFS patients versus male controls. Principal component analysis (PCA) identified three major components containing mostly PC and a few PE, PI and SM species-all of which were negatively associated with headache and fatigue severity, irrespective of sex. Correlations of oxylipins, ethanolamides and ME/CFS symptom severity showed that lower concentrations of these lipids corresponded with an increase in the severity of headaches, fatigue and cognitive difficulties and that this association was influenced by sex.

Conclusion: The observed sex-specific pattern of dysregulated PL, NL, HexCer and oxylipins in ME/CFS patients suggests a possible role of these lipids in promoting immune dysfunction and inflammation which may be among the underlying factors driving the clinical presentation of fatigue, chronic pain, and cognitive difficulties in ill patients. Further evaluation of lipid metabolism pathways is warranted to better understand ME/CFS pathogenesis.

Keywords: Immunity; Inflammation; Lipidomic; Myalgic encephalomyelitis/chronic fatigue syndrome.

Conflict of interest statement

Not applicable.

© 2021. The Author(s).

Figures

Fig. 1
Fig. 1
Heatmap visualization of phospholipids and neutral lipids in plasma of ME/CFS patients and controls. The heatmaps represent the average of relative concentrations to male controls of the total level of each lipid classes (left), lipids stratified by their level of unsaturation (middle) and lipids containing arachidonic acid (AA) or docosahexaenoic acid (DHA) (right) in each group. Black asterisks show significant differences between male and female ME/CFS patients and controls (p 

Fig. 2

Heatmap visualization of bioactive lipids…

Fig. 2

Heatmap visualization of bioactive lipids in plasma of ME/CFS patients and controls. The…

Fig. 2
Heatmap visualization of bioactive lipids in plasma of ME/CFS patients and controls. The heatmaps represent the average of relative concentrations to male controls of oxylipins (left) and ethanolamides (right) in each group. Oxylipins are classified based on which fatty acid they are derived, arachidonic acid (AA) or linoleic acid (LA) and which pathway they derived from, lipoxygenase pathway (LOX pathway) or cytochrome P450 pathway (CYP pathway). Black asterisks show significant differences between male and female ME/CFS patients and controls (p 

Fig. 3

Hierarchical clustering and relative levels…

Fig. 3

Hierarchical clustering and relative levels the of TOP 50 lipids. The scaled concentration…

Fig. 3
Hierarchical clustering and relative levels the of TOP 50 lipids. The scaled concentration value of each lipid from the TOP 50 identified by MetaboAnalyst are projected on level heatmap for each group. The color legend identifies in red the lipids in high level and blue the lipids at lower concentration (A). Relative changes in females (top) and males (bottom) between ME/CFS patients and their respective controls are represented on the Volcano plot (B). Each dot represents one individual lipid from the TOP 50 identified by the clustering and the red dots indicate the significant changes relative to controls with p-value threshold set at 0.05 (horizontal dotted line). The vertical dotted lines represent the arbitrary fold-change (FC) cut-off of ± 1.2
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References
    1. Unger ER, Lin JS, Tian H, Natelson BH, Lange G, Vu D, et al. Multi-site clinical assessment of myalgic encephalomyelitis/chronic fatigue syndrome (MCAM): design and implementation of a prospective/retrospective rolling cohort study. Am J Epidemiol. 2017;185(8):617–626. doi: 10.1093/aje/kwx029. - DOI - PMC - PubMed
    1. Reynolds KJ, Vernon SD, Bouchery E, Reeves WC. The economic impact of chronic fatigue syndrome. Cost Eff Resour Alloc. 2004;2(1):4. doi: 10.1186/1478-7547-2-4. - DOI - PMC - PubMed
    1. Jason LA, Mirin AA. Updating the National Academy of Medicine ME/CFS prevalence and economic impact figures to account for population growth and inflation. Fatigue Biomed Health Behav. 2021;9:1–5. doi: 10.1080/21641846.2021.1890347. - DOI
    1. Valdez AR, Hancock EE, Adebayo S, Kiernicki DJ, Proskauer D, Attewell JR, et al. Estimating prevalence, demographics, and costs of ME/CFS using large scale medical claims data and machine learning. Front Pediatr. 2019;6:412. doi: 10.3389/fped.2018.00412. - DOI - PMC - PubMed
    1. Nacul L, O’Boyle S, Palla L, Nacul FE, Mudie K, Kingdon CC, et al. How myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) progresses: the natural history of ME/CFS. Front Neurol. 2020;11:826. doi: 10.3389/fneur.2020.00826. - DOI - PMC - PubMed
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Fig. 2
Fig. 2
Heatmap visualization of bioactive lipids in plasma of ME/CFS patients and controls. The heatmaps represent the average of relative concentrations to male controls of oxylipins (left) and ethanolamides (right) in each group. Oxylipins are classified based on which fatty acid they are derived, arachidonic acid (AA) or linoleic acid (LA) and which pathway they derived from, lipoxygenase pathway (LOX pathway) or cytochrome P450 pathway (CYP pathway). Black asterisks show significant differences between male and female ME/CFS patients and controls (p 

Fig. 3

Hierarchical clustering and relative levels…

Fig. 3

Hierarchical clustering and relative levels the of TOP 50 lipids. The scaled concentration…

Fig. 3
Hierarchical clustering and relative levels the of TOP 50 lipids. The scaled concentration value of each lipid from the TOP 50 identified by MetaboAnalyst are projected on level heatmap for each group. The color legend identifies in red the lipids in high level and blue the lipids at lower concentration (A). Relative changes in females (top) and males (bottom) between ME/CFS patients and their respective controls are represented on the Volcano plot (B). Each dot represents one individual lipid from the TOP 50 identified by the clustering and the red dots indicate the significant changes relative to controls with p-value threshold set at 0.05 (horizontal dotted line). The vertical dotted lines represent the arbitrary fold-change (FC) cut-off of ± 1.2
Fig. 3
Fig. 3
Hierarchical clustering and relative levels the of TOP 50 lipids. The scaled concentration value of each lipid from the TOP 50 identified by MetaboAnalyst are projected on level heatmap for each group. The color legend identifies in red the lipids in high level and blue the lipids at lower concentration (A). Relative changes in females (top) and males (bottom) between ME/CFS patients and their respective controls are represented on the Volcano plot (B). Each dot represents one individual lipid from the TOP 50 identified by the clustering and the red dots indicate the significant changes relative to controls with p-value threshold set at 0.05 (horizontal dotted line). The vertical dotted lines represent the arbitrary fold-change (FC) cut-off of ± 1.2

References

    1. Unger ER, Lin JS, Tian H, Natelson BH, Lange G, Vu D, et al. Multi-site clinical assessment of myalgic encephalomyelitis/chronic fatigue syndrome (MCAM): design and implementation of a prospective/retrospective rolling cohort study. Am J Epidemiol. 2017;185(8):617–626. doi: 10.1093/aje/kwx029.
    1. Reynolds KJ, Vernon SD, Bouchery E, Reeves WC. The economic impact of chronic fatigue syndrome. Cost Eff Resour Alloc. 2004;2(1):4. doi: 10.1186/1478-7547-2-4.
    1. Jason LA, Mirin AA. Updating the National Academy of Medicine ME/CFS prevalence and economic impact figures to account for population growth and inflation. Fatigue Biomed Health Behav. 2021;9:1–5. doi: 10.1080/21641846.2021.1890347.
    1. Valdez AR, Hancock EE, Adebayo S, Kiernicki DJ, Proskauer D, Attewell JR, et al. Estimating prevalence, demographics, and costs of ME/CFS using large scale medical claims data and machine learning. Front Pediatr. 2019;6:412. doi: 10.3389/fped.2018.00412.
    1. Nacul L, O’Boyle S, Palla L, Nacul FE, Mudie K, Kingdon CC, et al. How myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) progresses: the natural history of ME/CFS. Front Neurol. 2020;11:826. doi: 10.3389/fneur.2020.00826.
    1. Brenu EW, Huth TK, Hardcastle SL, Fuller K, Kaur M, Johnston S, et al. Role of adaptive and innate immune cells in chronic fatigue syndrome/myalgic encephalomyelitis. Int Immunol. 2014;26(4):233–242. doi: 10.1093/intimm/dxt068.
    1. Brenu EW, Hardcastle SL, Atkinson GM, van Driel ML, Kreijkamp-Kaspers S, Ashton KJ, et al. Natural killer cells in patients with severe chronic fatigue syndrome. Autoimmunity Highlights. 2013;4(3):69–80. doi: 10.1007/s13317-013-0051-x.
    1. Hornig M, Gottschalk G, Peterson DL, Knox KK, Schultz AF, Eddy ML, et al. Cytokine network analysis of cerebrospinal fluid in myalgic encephalomyelitis/chronic fatigue syndrome. Mol Psychiatry. 2016;21(2):261–269. doi: 10.1038/mp.2015.29.
    1. Hornig M, Montoya JG, Klimas NG, Levine S, Felsenstein D, Bateman L, et al. Distinct plasma immune signatures in ME/CFS are present early in the course of illness. Sci Adv. 2015;1(1):e1400121. doi: 10.1126/sciadv.1400121.
    1. de Pablo M. Immune cell functions, lipids and host natural resistance. FEMS Immunol Med. 2000;29(4):323–328. doi: 10.1111/j.1574-695X.2000.tb01540.x.
    1. Duffney PF, Falsetta ML, Rackow AR, Thatcher TH, Phipps RP, Sime PJ. Key roles for lipid mediators in the adaptive immune response. J Clin. 2018;128(7):2724–2731.
    1. Martínez-Colón GJ, Moore BB. Prostaglandin E 2 as a regulator of immunity to pathogens. Pharmacol Ther. 2018;185:135–146. doi: 10.1016/j.pharmthera.2017.12.008.
    1. Serhan CN, Chiang N, van Dyke TE. Resolving inflammation: dual anti-inflammatory and pro-resolution lipid mediators. Nat Rev Immunol. 2008;8(5):349–361. doi: 10.1038/nri2294.
    1. Adibhatla RM, Hatcher JF. Altered lipid metabolism in brain injury and disorders. Subcell Biochem. 2008;49:241–268. doi: 10.1007/978-1-4020-8831-5_9.
    1. Serhan CN, Chiang N, Dalli J, Levy BD. Lipid mediators in the resolution of inflammation. Cold Spring Harb Perspect Biol. 2015;7(2):a016311. doi: 10.1101/cshperspect.a016311.
    1. Serhan CN. Novel lipid mediators and resolution mechanisms in acute inflammation. Am J Pathol. 2010;177(4):1576–1591. doi: 10.2353/ajpath.2010.100322.
    1. Germain A, Ruppert D, Levine SM, Hanson MR. Prospective biomarkers from plasma metabolomics of myalgic encephalomyelitis/chronic fatigue syndrome implicate redox imbalance in disease symptomatology. Metabolites. 2018;8(4):16–21. doi: 10.3390/metabo8040090.
    1. Germain A, Barupal DK, Levine SM, Hanson MR. Comprehensive Circulatory metabolomics in ME/CFS reveals disrupted metabolism of acyl lipids and steroids. Metabolites. 2020;10(1):34. doi: 10.3390/metabo10010034.
    1. Naviaux RK, Naviaux JC, Li K, Bright AT, Alaynick WA, Wang L, et al. Metabolic features of chronic fatigue syndrome. Proc Natl Acad Sci USA. 2016;113(37):E5472–E5480. doi: 10.1073/pnas.1607571113.
    1. Nagy-Szakal D, Barupal DK, Lee B, Che X, Williams BL, Kahn EJR, et al. Insights into myalgic encephalomyelitis/chronic fatigue syndrome phenotypes through comprehensive metabolomics. Scientific. 2018;8(1):10056.
    1. Mandarano AH, Maya J, Giloteaux L, Peterson DL, Maynard M, Gottschalk CG, et al. Myalgic encephalomyelitis/chronic fatigue syndrome patients exhibit altered T cell metabolism and cytokine associations. J Clin Investig. 2020;130(3):1491–1505. doi: 10.1172/JCI132185.
    1. Jason LA, So S, Brown AA, Sunnquist M, Evans M. Test–retest reliability of the DePaul symptom questionnaire. Fatigue Biomed Health Behav. 2015;3(1):16–32. doi: 10.1080/21641846.2014.978110.
    1. Huguenard CJC, Cseresznye A, Evans JE, Oberlin S, Langlois H, Ferguson S, et al. Plasma lipidomic analyses in cohorts with mTBI and/or PTSD reveal lipids differentially associated with diagnosis and APOE ε4 carrier status. Front Physiol. 2020;11:12. doi: 10.3389/fphys.2020.00012.
    1. Calder PC. Omega-3 fatty acids and inflammatory processes. Nutrients. 2010;2(3):355–374. doi: 10.3390/nu2030355.
    1. Innes JK, Calder PC. Omega-6 fatty acids and inflammation. Prostaglandins Leukot Essent Fatty Acids. 2018;132:41–48. doi: 10.1016/j.plefa.2018.03.004.
    1. Briggs M, Petersen K, Kris-Etherton P. Saturated fatty acids and cardiovascular disease: replacements for saturated fat to reduce cardiovascular risk. Healthcare. 2017;5(2):29. doi: 10.3390/healthcare5020029.
    1. Visioli F, Poli A. Fatty acids and cardiovascular risk. Evidence, lack of evidence, and diligence. Nutrients. 2020;12(12):3782. doi: 10.3390/nu12123782.
    1. Abdullah L, Evans JE, Emmerich T, Crynen G, Shackleton B, Keegan AP, et al. APOE ε4 specific imbalance of arachidonic acid and docosahexaenoic acid in serum phospholipids identifies individuals with preclinical Mild Cognitive Impairment/Alzheimer’s Disease. Aging. 2017;9(3):964–985. doi: 10.18632/aging.101203.
    1. Ernest B, Gooding JR, Campagna SR, Saxton AM, Voy BH. MetabR: an R script for linear model analysis of quantitative metabolomic data. BMC Res Notes. 2012;5(1):1. doi: 10.1186/1756-0500-5-596.
    1. Emmerich T, Zakirova Z, Klimas N, Sullivan K, Shetty AK, Evans JE, et al. Phospholipid profiling of plasma from GW veterans and rodent models to identify potential biomarkers of Gulf War Illness. PLoS ONE. 2017;12(4):1–24. doi: 10.1371/journal.pone.0176634.
    1. Emmerich T, Abdullah L, Crynen G, Dretsch M, Evans J, Ait-Ghezala G, et al. Plasma lipidomic profiling in a military population of mild traumatic brain injury and post-traumatic stress disorder with apolipoprotein E ɛ4–dependent effect. J Neurotrauma. 2016;33(14):1331–1348. doi: 10.1089/neu.2015.4061.
    1. Seidell JC, Cigolini M, Charzewska J, Ellsinger B-M, Björntorp P, Hautvast JGAJ, et al. Fat distribution and gender differences in serum lipids in men and women from four European communities. Atherosclerosis. 1991;87(2–3):203–210. doi: 10.1016/0021-9150(91)90022-U.
    1. Patel D, Witt SN. Ethanolamine and phosphatidylethanolamine: partners in health and disease. Oxid Med Cell Longev. 2017;2017:4829180. doi: 10.1155/2017/4829180.
    1. DiNicolantonio JJ, O’Keefe JH. Importance of maintaining a low omega–6/omega–3 ratio for reducing inflammation. Open Heart. 2018;5(2):e000946. doi: 10.1136/openhrt-2018-000946.
    1. Rahman IAS, Tsuboi K, Uyama T, Ueda N. New players in the fatty acyl ethanolamide metabolism. Pharmacol Res. 2014;86:1–10. doi: 10.1016/j.phrs.2014.04.001.
    1. Bradshaw HB, Walker JM. The expanding field of cannabimimetic and related lipid mediators. Br J Pharmacol. 2005;144(4):459–465. doi: 10.1038/sj.bjp.0706093.
    1. Alsalem M, Wong A, Millns P, Arya PH, Chan MSL, Bennett A, et al. The contribution of the endogenous TRPV1 ligands 9-HODE and 13-HODE to nociceptive processing and their role in peripheral inflammatory pain mechanisms. Br J Pharmacol. 2013;168(8):1961–1974. doi: 10.1111/bph.12092.
    1. Ricciotti E, FitzGerald GA. Prostaglandins and Inflammation. Arterioscler Thromb Vasc Biol. 2011;31(5):986–1000. doi: 10.1161/ATVBAHA.110.207449.
    1. Levan SR, Stamnes KA, Lin DL, Panzer AR, Fukui E, McCauley K, et al. Author Correction: elevated faecal 12,13-diHOME concentration in neonates at high risk for asthma is produced by gut bacteria and impedes immune tolerance. Nat Microbiol. 2019;4(11):1851–1861. doi: 10.1038/s41564-019-0498-2.
    1. Kim MH, Ahn HK, Lee E-J, Kim S-J, Kim Y-R, Park J-W, et al. Hepatic inflammatory cytokine production can be regulated by modulating sphingomyelinase and ceramide synthase 6. Int J Mol Med. 2017;39(2):453–462. doi: 10.3892/ijmm.2016.2835.
    1. Albeituni S, Stiban J. The role of bioactive lipids in cancer, inflammation and related diseases. In: Honn KV, Zeldin DC, editors. Genome. Advances in experimental medicine and biology. Cham: Springer International Publishing; 2019. pp. 1–12.
    1. Maceyka M, Spiegel S. Sphingolipid metabolites in inflammatory disease. Nature. 2014;510(7503):58–67. doi: 10.1038/nature13475.
    1. Yeom M, Park J, Lim C, Sur B, Lee B, Han J-J, et al. Glucosylceramide attenuates the inflammatory mediator expression in lipopolysaccharide-stimulated RAW264.7 cells. Nutr Res. 2015;35(3):241–250. doi: 10.1016/j.nutres.2015.01.001.
    1. Yeom M, Kim S-H, Lee B, Han J-J, Chung GH, Choi H-D, et al. Oral administration of glucosylceramide ameliorates inflammatory dry-skin condition in chronic oxazolone-induced irritant contact dermatitis in the mouse ear. J Dermatol Sci. 2012;67(2):101–110. doi: 10.1016/j.jdermsci.2012.05.009.
    1. Rodriguez-Cuenca S, Pellegrinelli V, Campbell M, Oresic M, Vidal-Puig A. Sphingolipids and glycerophospholipids—the “ying and yang” of lipotoxicity in metabolic diseases. Prog Lipid Res. 2017;66:14–29. doi: 10.1016/j.plipres.2017.01.002.
    1. Zimmer B, Angioni C, Osthues T, Toewe A, Thomas D, Pierre SC, et al. The oxidized linoleic acid metabolite 12,13-DiHOME mediates thermal hyperalgesia during inflammatory pain. Biochimica et Biophysica Acta BBA Mol Cell Biol Lipids. 2018;1863(7):669–678.
    1. Mobarak E, Håversen L, Manna M, Rutberg M, Levin M, Perkins R, et al. Glucosylceramide modifies the LPS-induced inflammatory response in macrophages and the orientation of the LPS/TLR4 complex in silico. Sci Rep. 2018;8(1):13600. doi: 10.1038/s41598-018-31926-0.
    1. Zhang J-Y, Qu F, Li J-F, Liu M, Ren F, Zhang J-Y, et al. Up-regulation of plasma hexosylceramide (d18:1/18: 1) contributes to genotype 2 virus replication in chronic hepatitis C: a 20-year cohort study. Medicine. 2016;95(23):e3773. doi: 10.1097/MD.0000000000003773.
    1. Filippatou AG, Moniruzzaman M, Sotirchos ES, Fitzgerald KC, Kalaitzidis G, Lambe J, et al. Serum ceramide levels are altered in multiple sclerosis. Multip Scler J. 2020 doi: 10.1177/1352458520971816.
    1. Harris CP, von Berg A, Berdel D, Bauer C-P, Schikowski T, Koletzko S, et al. Dietary saturated fat and low-grade inflammation modified by accelerometer-measured physical activity in adolescence: results from the GINIplus and LISA birth cohorts. BMC Public Health. 2019;19(1):818. doi: 10.1186/s12889-019-7113-6.
    1. Wallace DC. Bioenergetic origins of complexity and disease. Cold Spring Harb Symp Quant. 2011;76(8):1–16.
    1. Longo N, Frigeni M, Pasquali M. Carnitine transport and fatty acid oxidation. Biochimica et Biophysica Acta BBA Mol Cell Res. 2016;1863(10):2422–2435. doi: 10.1016/j.bbamcr.2016.01.023.
    1. Holden S, Maksoud R, Eaton-Fitch N, Cabanas H, Staines D, Marshall-Gradisnik S. A systematic review of mitochondrial abnormalities in myalgic encephalomyelitis/chronic fatigue syndrome/systemic exertion intolerance disease. J Transl Med. 2020;18(1):290. doi: 10.1186/s12967-020-02452-3.
    1. Zibaeenezhad MJ, Ghavipisheh M, Attar A, Aslani A. Comparison of the effect of omega-3 supplements and fresh fish on lipid profile: a randomized, open-labeled trial. Nutr Diabetes. 2017;7(12):1. doi: 10.1038/s41387-017-0007-8.
    1. Bradberry JC, Hilleman DE. Overview of omega-3 fatty acid therapies. P & T Peer-Rev J for Manag. 2013;38(11):681–691.
    1. Allaire J, Vors C, Tremblay AJ, Marin J, Charest A, Tchernof A, et al. High-dose DHA has more profound effects on LDL-related features than high-dose EPA: the ComparED study. J Clin Endocrinol Metab. 2018;103(8):2909–2917. doi: 10.1210/jc.2017-02745.

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