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Quantitative Magnetization Transfer Imaging as a Biomarker for Effects of Systemic Inflammation on the Brain
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BACKGROUND: Systemic inflammation impairs brain function and is increasingly implicated in the etiology of common mental illnesses, particularly depression and Alzheimer's disease. Immunotherapies selectively targeting proinflammatory cytokines demonstrate efficacy in a subset of patients with depression. However, efforts to identify patients most vulnerable to the central effects of inflammation are hindered by insensitivity of conventional structural magnetic resonance imaging. METHODS: We used quantitative magnetization transfer (qMT) imaging, a magnetic resonance imaging technique that enables quantification of changes in brain macromolecular density, together with experimentally induced inflammation to investigate effects of systemic inflammatory challenge on human brain microstructure. Imaging with qMT was performed in 20 healthy participants after typhoid vaccination and saline control injection. An additional 20 participants underwent fluorodeoxyglucose positron emission tomography following the same inflammatory challenge. RESULTS: The qMT data demonstrated that inflammation induced a rapid change in brain microstructure, reflected in increased magnetization exchange from free (water) to macromolecular-bound protons, within a discrete region of insular cortex implicated in representing internal physiologic states including inflammation. The functional significance of this change in insular microstructure was demonstrated by correlation with inflammation-induced fatigue and fluorodeoxyglucose positron emission tomography imaging, which revealed increased resting glucose metabolism within this region following the same inflammatory challenge. CONCLUSIONS: Together these observations highlight a novel structural biomarker of the central physiologic and behavioral effects of mild systemic inflammation. The widespread clinical availability of magnetic resonance imaging supports the viability of qMT imaging as a clinical biomarker in trials of immunotherapeutics, both to identify patients vulnerable to the effects of systemic inflammation and to monitor neurobiological responses.
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![Figure 1 Effects of inflammation on interleukin-6 and fatigue. (A) Change in circulating interleukin-6 before and after vaccine (V base and V 4 Hrs) and placebo injection (P base and P 4 Hrs). Typhoid vaccination evoked a robust inflammatory response with an approximately threefold increase in plasma interleukin-6 from mean (± SE) 1.29 ± .38 pmol/L at baseline to 3.74 ± .27 pmol/L at 4 hours [t19 = 5.93, p < .001]. The placebo condition was not associated with any change in interleukin-6 from .97 ± .23 pmol/L at baseline to .90 ± .18 pmol/L at 4 hours [t19 = −.54, p = .59]. (B) Change in fatigue before and after typhoid vaccination and placebo saline injection. Typhoid vaccination, but not placebo injection, was associated with a significant increase in fatigue as shown by mean (± SE) fatigue visual analog scale 16.18 ± 12.57 at baseline to 42.40 ± 22.52 at 4 hours [t19 = 6.05, p < .001] for typhoid vaccination and 22.08 ± 17.72 at baseline to 29.60 ± 17.94 at 4 hours [t19 = 1.93, p = .07] for placebo injection. IL-6, interleukin-6; n.s., p = non significant; VAS, visual analog scale.](/paper-figures/879501841a7a4caab9830bbc0d561809/quantitative-magnetization-transfer-imaging-as-a-biomarker-for-effects-of-figure-1.jpg)
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“Importantly, they showed that inflammation-induced activity changes in posterior insula and ACC were associated with subjectively perceived fatigue,”
From Allostatic Self-efficacy: A Metacognitive Theory of Dyshomeostasis-Induced Fatigue and Depression (2016) · cites this paper as Harrison et al., 2015
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“while activity changes in SGC predicted mood changes.”
From Allostatic Self-efficacy: A Metacognitive Theory of Dyshomeostasis-Induced Fatigue and Depression (2016) · cites this paper as Harrison et al., 2015
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“in several elegant studies using MRI and PET in conjunction with typhoid vaccination to induce a peripheral immunological response and inflammation, Harrison and colleagues provided compelling evidence for structural and functional changes in posterior insula, anterior insula, and ACC (Harrison et al., 2009a,b, 2015).”
From Allostatic Self-efficacy: A Metacognitive Theory of Dyshomeostasis-Induced Fatigue and Depression (2016) · cites this paper as Harrison et al., 2015
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Cites
Molecular Mechanisms of Depression: Perspectives on New Treatment Strategies
Lang, U. E., & Borgwardt, S. (2013) · Cellular Physiology and Biochemistry · doi:10.1159/000350094 · Cited by 8,526
How do you feel — now? The anterior insula and human awareness
(Bud) Craig, A. D. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2555 · Cited by 6,657 · cited 1×
“org/journa macromolecular bound protons within the insula, a region implicated in representing bodily physiologic state across physiologic domains including inflammation (27,28) and their translation into subjective experiences such as warmth, hunger, or fatigue (29,30).”
How do you feel? Interoception: The sense of the physiological condition of the body
Craig, A. D. (2002) · Nature Reviews Neuroscience · doi:10.1038/nrn894 · Cited by 6,006
A Meta-Analysis of Cytokines in Major Depression
Dowlati, Y., Herrmann, N., Swardfager, W., Liu, H., Sham, L., Reim, E. K., & Lanctôt, K. L. (2010) · Biological Psychiatry · doi:10.1016/j.biopsych.2009.09.033 · Cited by 4,729
Inflammation and Its Discontents: The Role of Cytokines in the Pathophysiology of Major Depression
Miller, A. H., Maletic, V., & Raison, C. L. (2009) · Biological Psychiatry · doi:10.1016/j.biopsych.2008.11.029 · Cited by 3,848
Pellerin, L., & Magistretti, P. J. (1994) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.91.22.10625 · Cited by 2,927
Brain energy metabolism: focus on Astrocyte-neuron metabolic cooperation
Bélanger, M., Allaman, I., & Magistretti, P. J. (2011) · Cell Metabolism · doi:10.1016/j.cmet.2011.08.016 · Cited by 2,313
Region of interest analysis using an SPM toolbox
Brett, M. (2002) · NeuroImage · Cited by 2,273
Biological basis of the behavior of sick animals
Hart, B. L. (1988) · Neuroscience & Biobehavioral Reviews · doi:10.1016/s0149-7634(88)80004-6 · Cited by 2,223
Raison, C. L., Rutherford, R. E., Woolwine, B. J., Shuo, C., Schettler, P., Drake, D. F., Haroon, E., & Miller, A. H. (2013) · JAMA Psychiatry · doi:10.1001/2013.jamapsychiatry.4 · Cited by 1,617
Research works printed but not linked: 1
- Lin, 2010, Nonlinear coupling between cerebral blood flow oxygen consumption, and ATP production in human visual cortex, Proc Natl Acad Sci U S A, 107, 8446, 10.1073/pnas.0909711107 · DOI · Paper page
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Self-citationJenkins, V. A., Thwaites, R. S., Cercignani, M., Sacre, S. M., Harrison, N. A., Whiteley-Jones, H., Mullen, L., Chamberlain, G., Davies, K. A., Zammit, C., et al. (2016) · SpringerPlus · doi:10.1186/s40064-016-2030-y · Cited by 35
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Yang, W., Lee, J., Leninger, M., Windschuh, J., Traaseth, N. J., & Jerschow, A. (2019) · NMR in Biomedicine · doi:10.1002/nbm.4097 · Cited by 9
Santos, M. V., Lopes, L. D. S., Machado, H. R., & de Oliveira, R. S. (2019) · Developmental Neuroscience · doi:10.1159/000497433 · Cited by 9
Kitzbichler, M. G., Aruldass, A. R., Barker, G. J., Wood, T., Dowell, N. G., Hurley, S. A., McLean, J., Correia, M., Clarke, C., Pointon, L. J., et al. (2020) · medRxiv · doi:10.1101/2020.09.09.20191262 · Cited by 9
Self-citationPlank, J. R., Morgan, C., Dell’Acqua, F., Sundram, F., Hoeh, N. R., Muthukumaraswamy, S. D., & Lin, J. C. (2025) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2025.05.002 · Cited by 10
Meng, Y., Cheung, J., & Sun, P. Z. (2020) · Magnetic Resonance in Medicine · doi:10.1002/mrm.28159 · Cited by 8
Plank, J. R., Glover, S. C., Moloney, B. D., Hoeh, N. R., Sundram, F., Sumner, R. L., Muthukumaraswamy, S. D., & Lin, J. C. (2022) · Trials · doi:10.1186/s13063-022-06738-3 · Cited by 8
Bernardoni, F., Tam, F. I., Poitz, D. M., Hellerhoff, I., Arold, D., Geisler, D., Lemme, F., Keeler, J. L., Weidner, K., Pariante, C. M., et al. (2024) · Neuropsychopharmacology · doi:10.1038/s41386-024-01836-z · Cited by 7
Dekerle, J., Wrightson, J. G., & Greenhouse‐Tucknott, A. (2025) · Sports Medicine · doi:10.1007/s40279-025-02252-z · Cited by 5
Suchting, R., Razouq, D., Jose, L., Nascimento, F., Wardle, M. C., Soares, J. C., Teixeira, A. L., & Selvaraj, S. (2023) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2023.03.019 · Cited by 7
Luu, H. M., & Park, S. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120449 · Cited by 6
Gangadin, S. S., Mandl, R. C. W., de Witte, L. D., van Haren, N. E. M., Schutte, M. J. L., Begemann, M., Kahn, R. S., & Sommer, I. E. (2022) · Schizophrenia Research · doi:10.1016/j.schres.2022.12.009 · Cited by 7
Plank, J. R., Morgan, C., Smith, A. K., Sundram, F., Hoeh, N. R., Muthukumaraswamy, S. D., & Lin, J. C. (2023) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.28938 · Cited by 6
Periche-Tomas, E., Cattaneo, A., Cattane, N., Bone, C., Tibble, J. A., Bullmore, E. T., Pariante, C. M., & Harrison, N. A. (2024) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2024.09.038 · Cited by 5
Self-citationStefanov, K., McLean, J., Allan, B., Cavanagh, J., & Krishnadas, R. (2020) · Brain and Neuroscience Advances · doi:10.1177/2398212820949353 · Cited by 5
Yuan, J. P., Jaeger, E. L., Coury, S. M., Uy, J. P., Buthmann, J. L., Ho, T. C., & Gotlib, I. H. (2024) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2024.05.002 · Cited by 5
Kim, J., Lee, S., Choi, S. H., & Park, S. (2019) · Magnetic Resonance in Medicine · doi:10.1002/mrm.27850 · Cited by 5
Cancela, J. G., Vázquez, O. C., Ledesma, S. N., & Pruimboom, L. (2026) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2026.106791 · Cited by 5
Inflammation, Sickness Behaviour and Depression
Khandaker, G. M., Colasanti, A., & Harrison, N. A. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108539623.008 · Cited by 5
Self-citationMagioncalda, P., Yadav, A., & Martino, M. (2025) · Nature Mental Health · doi:10.1038/s44220-025-00493-5 · Cited by 5
The role of the immune system in depersonalisation disorder
Zheng, S., Feng, S., Song, N., Chen, G., Jia, Y., Zhang, G., Liu, M., Li, X., Ning, Y., Wang, D., et al. (2024) · The World Journal of Biological Psychiatry · doi:10.1080/15622975.2024.2346096 · Cited by 3
Sisco, N. J., Wang, P., Stokes, A. M., & Dortch, R. D. (2022) · PeerJ · doi:10.7717/peerj.13043 · Cited by 3
Madison, A. A., Andridge, R., Renna, M. E., Sheridan, J. F., Lustberg, M. B., Ramaswamy, B., Wesolowski, R., Williams, N. O., Sardesai, S. D., Noonan, A. M., et al. (2023) · Journal of Affective Disorders · doi:10.1016/j.jad.2023.09.008 · Cited by 4
Wood, T., & Malik, S. (2020) · Advances in magnetic resonance technology and applications · doi:10.1016/b978-0-12-817057-1.00035-4 · Cited by 3
Mavar, S., Lee, Y.-S., Baranova, E., Duncan, N. W., Magioncalda, P., & Martino, M. (2025) · Molecular Psychiatry · doi:10.1038/s41380-025-03194-8 · Cited by 7
Berthold, M.-L., Hartmann, H., Farrher, E., Zimmermann, M., Jaeger, J. W., Shah, N. J., Schneider, K. M., Neuner, I., & Rajkumar, R. (2025) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2025.1620488 · Cited by 2
Coad, B. M., Ghomroudi, P. A., Sims, R., Aggleton, J. P., Vann, S. D., & Metzler‐Baddeley, C. (2022) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2022.02.004 · Cited by 2
Joint analysis of area and thickness as a replacement for the analysis of cortical volumePreprint
Winkler, A. M., Greve, D. N., Bjuland, K. J., Nichols, T. E., Sabuncu, M. R., Håberg, A. K., Skranes, J., & Rimol, L. M. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/074666 · Cited by 2
Metadata
- Authors
- Harrison, N. A., Cooper, E., Dowell, N. G., Keramida, G., Voon, V., Critchley, H. D., & Cercignani, M.
- Affiliations
- Brighton and Sussex Medical School (GB)
- Fondazione Santa Lucia (IT)
- University of Cambridge (GB)
- Corresponding author
- Harrison, Neil A.
- ORCID
- Venue
- Biological Psychiatry
- Publisher
- Elsevier BV
- Published
- 2015-07
- Volume
- 78
- Issue
- 1
- Pages
- 49-57
- ISSN
- 0006-3223 (ISSN-L)
- PMC
- PMC4503794
- OpenAlex
- W1968629304
- Cited by
- 129
- References
- 55
- Citations by year
- 2026: 6 · 2025: 8 · 2024: 9 · 2023: 9 · 2022: 19 · 2021: 9 · 2020: 14 · 2019: 11 · 2018: 12 · 2017: 14 · 2016: 10 · 2015: 8
- FWCI
- 3.28
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Biological Psychiatry (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- ORCA Online Research @Cardiff (Cardiff University) (acceptedVersion)
- Sussex Research Online (University of Sussex) (submittedVersion, cc-by)
- Figshare (submittedVersion, cc-by)
- Funders
- Wellcome Trust
- Topics
- Life Sciences › Neuroscience › Biological Psychiatry › Tryptophan and brain disorders
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Keywords
- systemic inflammation, brain microstructure, insula, typhoid vaccination, fatigue, neuroinflammation, biomarkers, immunotherapy response, depression, Alzheimer's disease
- MeSH terms
- Adult, Brain, Encephalitis, Fatigue, Female, Humans, Magnetic Resonance Imaging, Male, Typhoid-Paratyphoid Vaccines, Biomarkers, Fluorodeoxyglucose F18, Receptors, Interleukin-6, Positron-Emission Tomography
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