Article | Published:

Pediatrics

Visceral fat-related systemic inflammation and the adolescent brain: a mediating role of circulating glycerophosphocholines

International Journal of Obesity (2018) | Download Citation

Abstract

Objective

Life-long maintenance of brain health is important for the prevention of cognitive impairment in older age. Low-grade peripheral inflammation associated with excess visceral fat (VF) may influence brain structure and function. Here we examined (i) if this type of inflammation is associated with altered white-matter (WM) microstructure and lower cognitive functioning in adolescents, and (ii) if recently identified circulating glycerophosphocholines (GPCs) can index this type of inflammation and associated variations in WM microstructure and cognitive functioning.

Subjects

We studied a community-based sample of 872 adolescents (12–18 years, 48% males) in whom we assessed VF and WM microstructure with magnetic resonance imaging, processing speed with cognitive testing, serum C-reactive protein (CRP, a common marker of peripheral inflammation) with a high-sensitivity assay, and serum levels of a panel of 64 GPCs with advanced mass spectrometry.

Results

VF was associated with CRP, and CRP in turn was associated with “altered” WM microstructure and lower processing speed (all p < 0.003). Further, “altered” WM microstructure was associated with lower processing speed (p < 0.0001). Of all 64 tested GPCs, 4 were associated with both VF and CRP (at Bonferroni corrected p < 0.0004). One of them, PC16:0/2:0, was also associated with WM microstructure (p < 0.0001) and processing speed (p = 0.0003), and mediated the directed associations between VF and both WM microstructure (p < 0.0001) and processing speed (p = 0.02). As a mediator, PC16:0/2:0 explained 21% of shared variance between VF and WM microstructure, and 22% of shared variance between VF and processing speed. Similar associations were observed in an auxiliary study of 80 middle-aged adults.

Conclusions

Our results show that VF-related peripheral inflammation is associated with "altered" WM microstructure and lower cognitive functioning already in adolescents, and a specific circulating GPC may be a new molecule indexing this VF-related peripheral inflammation and its influences on brain structure and function.

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References

  1. 1.

    Norton S, Matthews FE, Barnes DE, Yaffe K, Brayne C. Potential for primary prevention of Alzheimer’s disease: an analysis of population-based data. Lancet Neurol. 2014;13:788–94.

  2. 2.

    Buckman LB, Hasty AH, Flaherty DK, Buckman CT, Thompson MM, Matlock BK, et al. Obesity induced by a high-fat diet is associated with increased immune cell entry into the central nervous system. Brain Behav Immun. 2014;35:33–42.

  3. 3.

    Hoogland IC, Houbolt C, van Westerloo DJ, van Gool WA, van de Beek D. Systemic inflammation and microglial activation: systematic review of animal experiments. J Neuroinflamm. 2015;12:114.

  4. 4.

    Guillemot-Legris O, Muccioli GG. Obesity-induced neuroinflammation: beyond the hypothalamus. Trends Neurosci. 2017;40:237–53.

  5. 5.

    Bocarsly ME, Fasolino M, Kane GA, LaMarca EA, Kirschen GW, Karatsoreos IN, et al. Obesity diminishes synaptic markers, alters microglial morphology, and impairs cognitive function. Proc Natl Acad Sci USA. 2015;112:15731–6.

  6. 6.

    Hao S, Dey A, Yu X, Stranahan AM. Dietary obesity reversibly induces synaptic stripping by microglia and impairs hippocampal plasticity. Brain Behav Immun. 2016;51:230-9.

  7. 7.

    Shin JA, Jeong SI, Kim M, Yoon JC, Kim HS, Park EM. Visceral adipose tissue inflammation is associated with age-related brain changes and ischemic brain damage in aged mice. Brain Behav Immun. 2015;50:221–31.

  8. 8.

    Schmidt R, Schmidt H, Curb JD, Masaki K, White LR, Launer LJ. Early inflammation and dementia: a 25-year follow-up of the Honolulu-Asia Aging Study. Ann Neurol. 2002;52:168–74.

  9. 9.

    Engelhart MJ, Geerlings MI, Meijer J, Kiliaan A, Ruitenberg A, van Swieten JC, et al. Inflammatory proteins in plasma and the risk of dementia: the Rotterdam Study. Arch Neurol. 2004;61:668–72.

  10. 10.

    Desikan RS, Schork AJ, Wang Y, Thompson WK, Dehghan A, Ridker PM, et al. Polygenic overlap between C-reactive protein, plasma lipids, and Alzheimer disease. Circulation. 2015;131:2061–9.

  11. 11.

    Koyama A, O’Brien J, Weuve J, Blacker D, Metti AL, Yaffe K. The role of peripheral inflammatory markers in dementia and Alzheimer’s disease: a meta-analysis. J Gerontol A Biol Sci Med Sci. 2013;68:433–40.

  12. 12.

    van Himbergen TM, Beiser AS, Ai M, Seshadri S, Otokozawa S, Au R, et al. Biomarkers for insulin resistance and inflammation and the risk for all-cause dementia and alzheimer disease: results from the Framingham Heart Study. Arch Neurol. 2012;69:594–600.

  13. 13.

    Heppner FL, Ransohoff RM, Becher B. Immune attack: the role of inflammation in Alzheimer disease. Nat Rev Neurosci. 2015;16:358–72.

  14. 14.

    Heneka MT, Carson MJ, El Khoury J, Landreth GE, Brosseron F, Feinstein DL, et al. Neuroinflammation in Alzheimer’s disease. Lancet Neurol. 2015;14:388–405.

  15. 15.

    Osborn O, Olefsky JM. The cellular and signaling networks linking the immune system and metabolism in disease. Nat Med. 2012;18:363–74.

  16. 16.

    Trayhurn P, Wood IS. Adipokines: inflammation and the pleiotropic role of white adipose tissue. Br J Nutr. 2004;92:347–55.

  17. 17.

    Canada S Canadian Health Measures Survey, 2012 to 2013. Health Fact Sheets 2015: (82-625-X).

  18. 18.

    O’Rourke RW, Metcalf MD, White AE, Madala A, Winters BR, Maizlin II. et al. Depot-specific differences in inflammatory mediators and a role for NK cells and IFN-gamma in inflammation in human adipose tissue. Int J Obes. 2009;33:978–90.

  19. 19.

    Gabriely I, Ma XH, Yang XM, Atzmon G, Rajala MW, Berg AH, et al. Removal of visceral fat prevents insulin resistance and glucose intolerance of aging: an adipokine-mediated process? Diabetes. 2002;51:2951–8.

  20. 20.

    Thorne A, Lonnqvist F, Apelman J, Hellers G, Arner P. A pilot study of long-term effects of a novel obesity treatment: omentectomy in connection with adjustable gastric banding. Int J Obes Relat Metab Disord. 2002;26:193–9.

  21. 21.

    Klein S, Fontana L, Young VL, Coggan AR, Kilo C, Patterson BW, et al. Absence of an effect of liposuction on insulin action and risk factors for coronary heart disease. N Engl J Med. 2004;350:2549–57.

  22. 22.

    Tchernof A, Despres JP. Pathophysiology of human visceral obesity: an update. Physiol Rev. 2013;93:359–404.

  23. 23.

    Pou KM, Massaro JM, Hoffmann U, Vasan RS, Maurovich-Horvat P, Larson MG, et al. Visceral and subcutaneous adipose tissue volumes are cross-sectionally related to markers of inflammation and oxidative stress: the Framingham Heart Study. Circulation. 2007;116:1234–41.

  24. 24.

    Hocking SL, Stewart RL, Brandon AE, Suryana E, Stuart E, Baldwin EM, et al. Subcutaneous fat transplantation alleviates diet-induced glucose intolerance and inflammation in mice. Diabetologia. 2015;58:1587–600.

  25. 25.

    Debette S, Beiser A, Hoffmann U, Decarli C, O’Donnell CJ, Massaro JM, et al. Visceral fat is associated with lower brain volume in healthy middle-aged adults. Ann Neurol. 2010;68:136–44.

  26. 26.

    Kim KW, Seo H, Kwak MS, Kim D. Visceral obesity is associated with white matter hyperintensity and lacunar infarct. Int J Obes. 2017;41:683–8.

  27. 27.

    Yamashiro K, Tanaka R, Tanaka Y, Miyamoto N, Shimada Y, Ueno Y, et al. Visceral fat accumulation is associated with cerebral small vessel disease. Eur J Neurol. 2014;21:667–73.

  28. 28.

    Higuchi S, Kabeya Y, Kato K. Visceral-to-subcutaneous fat ratio is independently related to small and large cerebrovascular lesions even in healthy subjects. Atherosclerosis. 2017;259:41–5.

  29. 29.

    Schwartz DH, Dickie E, Pangelinan MM, Leonard G, Perron M, Pike GB, et al. Adiposity is associated with structural properties of the adolescent brain. Neuroimage. 2014;103:192–201.

  30. 30.

    Schwartz DH, Leonard G, Perron M, Richer L, Syme C, Veillette S, et al. Visceral fat is associated with lower executive functioning in adolescents. Int J Obes. 2013;37:1336–43.

  31. 31.

    Syme C, Czajkowski S, Shin J, Abrahamowicz M, Leonard G, Perron M, et al. Glycerophosphocholine metabolites and cardiovascular disease risk factors in adolescents: a cohort study. Circulation. 2016;134:1629–36.

  32. 32.

    Pickens CA, Vazquez AI, Jones AD, Fenton JI. Obesity, adipokines, and C-peptide are associated with distinct plasma phospholipid profiles in adult males, an untargeted lipidomic approach. Sci Rep. 2017;7:6335.

  33. 33.

    Heimerl S, Fischer M, Baessler A, Liebisch G, Sigruener A, Wallner S, et al. Alterations of plasma lysophosphatidylcholine species in obesity and weight loss. PLoS ONE. 2014;9:e111348.

  34. 34.

    Ganna A, Salihovic S, Sundstrom J, Broeckling CD, Hedman AK, Magnusson PK, et al. Large-scale metabolomic profiling identifies novel biomarkers for incident coronary heart disease. PLoS Genet. 2014;10:e1004801.

  35. 35.

    Sevastou I, Kaffe E, Mouratis MA, Aidinis V. Lysoglycerophospholipids in chronic inflammatory disorders: the PLA(2)/LPC and ATX/LPA axes. Biochim Biophys Acta. 2013;1831:42–60.

  36. 36.

    Marathe GK, Pandit C, Lakshmikanth CL, Chaithra VH, Jacob SP, D’Souza CJ. To hydrolyze or not to hydrolyze: the dilemma of platelet-activating factor acetylhydrolase. J Lipid Res. 2014;55:1847–54.

  37. 37.

    Yan JJ, Jung JS, Lee JE, Lee J, Huh SO, Kim HS, et al. Therapeutic effects of lysophosphatidylcholine in experimental sepsis. Nat Med. 2004;10:161–7.

  38. 38.

    Ojala PJ, Hirvonen TE, Hermansson M, Somerharju P, Parkkinen J. Acyl chain-dependent effect of lysophosphatidylcholine on human neutrophils. J Leukoc Biol. 2007;82:1501–9.

  39. 39.

    Mapstone M, Cheema AK, Fiandaca MS, Zhong X, Mhyre TR, MacArthur LH, et al. Plasma phospholipids identify antecedent memory impairment in older adults. Nat Med. 2014;20:415–8.

  40. 40.

    Klavins K, Koal T, Dallmann G, Marksteiner J, Kemmler G, Humpel C. The ratio of phosphatidylcholines to lysophosphatidylcholines in plasma differentiates healthy controls from patients with Alzheimer’s disease and mild cognitive impairment. Alzheimer’s Dement. 2015;1:295–302.

  41. 41.

    Jove M, Mauri-Capdevila G, Suarez I, Cambray S, Sanahuja J, Quilez A, et al. Metabolomics predicts stroke recurrence after transient ischemic attack. Neurology. 2015;84:36–45.

  42. 42.

    Sigruener A, Kleber ME, Heimerl S, Liebisch G, Schmitz G, Maerz W. Glycerophospholipid and sphingolipid species and mortality: the Ludwigshafen Risk and Cardiovascular Health (LURIC) study. PLoS ONE. 2014;9:e85724.

  43. 43.

    Pausova Z, Paus T, Abrahamowicz M, Bernard M, Gaudet D, Leonard G, et al. Cohort profile: the Saguenay Youth Study (SYS). Int J Epidemiol. 2017; 46(2)e19.

  44. 44.

    Ridker PM. Cardiology patient page. C-reactive protein: a simple test to help predict risk of heart attack and stroke. Circulation. 2003;108:e81–5.

  45. 45.

    Ruff R, Allen C. Ruff 2 and 7 selective attention test: Professional manual. Odessa, Florida: Psychological Assessment Resources. 1996.

  46. 46.

    Xu H, Valenzuela N, Fai S, Figeys D, Bennett SA. Targeted lipidomics - advances in profiling lysophosphocholine and platelet-activating factor second messengers. FEBS J. 2013;280:5652–67.

  47. 47.

    Peterson A, Crockett L, Richards M, Boxer A. A self-report measure of pubertal status: reliability, validity, and initial norms. J Youth Adolesc. 1988;17:117–33.

  48. 48.

    Shirtcliff EA, Dahl RE, Pollak SD. Pubertal development: correspondence between hormonal and physical development. Child Dev. 2009;80:327–37.

  49. 49.

    Bates DMM, Bolker B and Walker S. _lme4: linear mixed-effects models using Eigen and S4_. R package version 1.1–7; 2014.

  50. 50.

    Sobel ME. Asymptotic confidence intervals for indirect effects in structural equation models. Sociol Methodol. 1982;13:290–312.

  51. 51.

    Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol. 1986;51:1173–82.

  52. 52.

    Walker KA, Hoogeveen RC, Folsom AR, Ballantyne CM, Knopman DS, Windham BG, et al. Midlife systemic inflammatory markers are associated with late-life brain volume: the ARIC study. Neurology. 2017;89:2262–70.

  53. 53.

    Walker KA, Power MC, Hoogeveen RC, Folsom AR, Ballantyne CM, Knopman DS, et al. Midlife systemic inflammation, late-life white matter integrity, and cerebral small vessel disease: the atherosclerosis risk in communities study. Stroke. 2017;48:3196–202.

  54. 54.

    Bettcher BM, Yaffe K, Boudreau RM, Neuhaus J, Aizenstein H, Ding J, et al. Declines in inflammation predict greater white matter microstructure in older adults. Neurobiol Aging. 2015;36:948–54.

  55. 55.

    Swardfager W, Yu D, Ramirez J, Cogo-Moreira H, Szilagyi G, Holmes MF, et al. Peripheral inflammatory markers indicate microstructural damage within periventricular white matter hyperintensities in Alzheimer’s disease: a preliminary report. Alzheimer’s Dement. 2017;7:56–60.

  56. 56.

    Lerch JP, van der Kouwe AJ, Raznahan A, Paus T, Johansen-Berg H, Miller KL, et al. Studying neuroanatomy using MRI. Nat Neurosci. 2017;20:314–26.

  57. 57.

    Vavasour IM, Laule C, Li DK, Traboulsee AL, MacKay AL. Is the magnetization transfer ratio a marker for myelin in multiple sclerosis? J Magn Reson Imaging. 2011;33:713–8.

  58. 58.

    Pike GB. Pulsed magnetization transfer contrast in gradient echo imaging: a two-pool analytic description of signal response. Magn Reson Med. 1996;36:95–103.

  59. 59.

    Wishart DS. Emerging applications of metabolomics in drug discovery and precision medicine. Nat Rev Drug Discov. 2016;15:473–84.

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Acknowledgements

We thank the following individuals for their contributions in acquiring data in the SYS: Manon Bernard (database architect, The Hospital for Sick Children), Hélène Simard and her team of research assistants (Cégep de Jonquière), and Jacynthe Tremblay and her team of research nurses (Chicoutimi Hospital). We thank all participants who took part in the Saguenay Youth Study.

Funding

The Saguenay Youth Study has been funded by the Canadian Institutes of Health Research (TP and ZP), Heart and Stroke Foundation of Canada (ZP), and the Canadian Foundation for Innovation (ZP). Dr. Syme is a post-doctoral research fellow funded by the SickKids Research Institute. Dr. Abrahamowicz is a James McGill Professor at McGill University.

Author information

Affiliations

  1. The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada

    • Catriona Syme
    • , Stephanie Pelletier
    • , Jean Shin
    • , Lisa J. Strug
    •  & Zdenka Pausova
  2. Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, ON, Canada

    • Catriona Syme
    • , Stephanie Pelletier
    • , Jean Shin
    •  & Zdenka Pausova
  3. Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada

    • Michal Abrahamowicz
  4. Montreal Neurological Institute, McGill University, Montreal, QC, Canada

    • Gabriel Leonard
  5. Department of Human Sciences, Université du Québec à Chicoutimi, Chicoutimi, QC, Canada

    • Michel Perron
    •  & Suzanne Veillette
  6. Department of Health Sciences, Université du Québec à Chicoutimi, Chicoutimi, QC, Canada

    • Louis Richer
  7. Community Genomic Centre, Université de Montréal, Chicoutimi, QC, Canada

    • Daniel Gaudet
  8. Department of Radiology and Clinical Neurosciences, University of Calgary, Calgary, AB, Canada

    • Bruce Pike
  9. Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada

    • Lisa J. Strug
  10. Neural Regeneration Laboratory, Ottawa Institute of Systems Biology, University of Ottawa, Ottawa, ON, Canada

    • Yun Wang
    • , Hongbin Xu
    • , Graeme Taylor
    •  & Steffany Bennett
  11. Bloorview Research Institute, Toronto, ON, Canada

    • Tomas Paus
  12. Departments of Psychology and Psychiatry, University of Toronto, Toronto, ON, Canada

    • Tomas Paus

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Conflict of interest

The authors declare that they have no conflict of interest.

Corresponding author

Correspondence to Zdenka Pausova.

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DOI

https://doi.org/10.1038/s41366-018-0202-2