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Neuroinflammation and Functional Connectivity in Alzheimer's Disease: Interactive Influences on Cognitive Performance Research Articles: Neurobiology of Disease Neuroinflammation and functional connectivity in Alzheimer's disease: interactive influences on cognitive performance https://doi.org/10.1523/JNEUROSCI.2574-18.2019 Cite as: J. Neurosci 2019; 10.1523/JNEUROSCI.2574-18.2019 Received: 5 October 2018 Revised: 25 March 2019 Accepted: 11 April 2019 This Early Release article has been peer-reviewed and accepted, but has not been through the composition and copyediting processes. The final version may differ slightly in style or formatting and will contain links to any extended data. Alerts: Sign up at www.jneurosci.org/alerts to receive customized email alerts when the fully formatted version of this article is published. Copyright © 2019 Passamonti et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed. 1 Neuroinflammation and functional connectivity in Alzheimer’s disease: 2 interactive influences on cognitive performance 3 4 L. Passamonti1*, K.A. Tsvetanov1*, P.S. Jones1, W.R. Bevan-Jones2, R. Arnold2, R.J. Borchert1, 5 E. Mak2, L. Su2, J.T. O’Brien2#, J.B. Rowe1,3# 6 7 Joint *first and #last authorship 8 9 10 Authors’ addresses 11 1Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK 12 2Department of Psychiatry, University of Cambridge, Cambridge, UK 13 3Cognition and Brain Sciences Unit, Medical Research Council, Cambridge, UK 14 15 Corresponding Author 16 Luca Passamonti, 17 Department of Clinical Neurosciences 18 University of Cambridge 19 CB2 0SZ, UK 20 Telephone: +44.01223.330293 21 Email: [email protected] 22 23 Short title (≤50 char.): Neuroinflammation-driven connectivity changes in AD (47 char.) 24 Title (≤ 50 words): 12 25 Number of words for abstract (≤ 250): 237 26 Number of words in the significance statement (≤120): 96 27 Number of words for introduction (≤650): 519 28 Number of words for discussion (≤1,500): 999 29 Number of figures and tables: 5 figures, 1 table 30 Total references: 50 31 Number of pages: 25 32 Acknowledgments & Conflict of Interest 33 We thank our volunteers and the radiographers/technologists at WBIC and PET/CT, 34 Addenbrooke’s Hospital, for their invaluable support in data acquisition. We thank the NIHR 35 Eastern Dementias and Neurodegenerative Diseases Research Network for help with subject 36 recruitment. We thank Dr Istvan Boros and others at WBIC RPU for the manufacture of 37 [11C]PK11195 and [11C]PiB. This study was funded by the National Institute for Health 38 Research Cambridge Biomedical Research Centre and Biomedical Research Unit in 39 Dementia (NIHR, RG64473), the Wellcome Trust (JBR 103838), and the Medical Research 40 Council (RG91365/SUAG/004 and MR/P01271X/1). Dr. Li Su is supported by Alzheimer’s 41 Research UK. L. Passamonti, K. Tsvetanov, W.R. Bevan-Jones, P.S. Jones, R. Arnold, R. 42 Borchert, E. Mak, and L. Su report no financial disclosures or conflict of interest relevant to 43 the manuscript. J.T. O’Brien has served as deputy editor of International Psychogeriatrics, 44 received grant support from Avid (Lilly), and served as a consultant for Avid and GE 45 Healthcare, all for matters not related to the current study. J.B. Rowe serves as editor to 46 Brain, has been a consultant for Asceneuron and Syncona, and has received academic grant 47 funding from AZ-MedImmune, Janssen, and Lilly, unrelated to this study. 1 48 Abstract 49 Neuroinflammation is a key part of the etio-pathogenesis of Alzheimer’s disease. We test 50 the relationship between neuroinflammation and the disruption of functional connectivity 51 in large-scale networks, and their joint influence on cognitive impairment. 52 We combined [11C]PK11195 positron emission tomography (PET) and resting-state 53 functional magnetic resonance imaging (rs-fMRI) in 28 humans (12 females/16 males) with 54 clinical diagnosis of probable Alzheimer’s disease or mild cognitive impairment with positive 55 PET biomarker for amyloid, and 14 age-, sex-, and education-matched healthy humans (8 56 females/6 males). Source-based ‘inflammetry’ was used to extract principal components of 57 [11C]PK11195 PET signal variance across all participants. rs-fMRI data were pre-processed via 58 independent component analyses to classify neuronal and non-neuronal signals. Multiple 59 linear regression models identified sources of signal co-variance between 60 neuroinflammation and brain connectivity profiles, in relation to group and cognitive status. 61 Patients showed significantly higher [11C]PK11195 binding relative to controls, in a 62 distributed spatial pattern including the hippocampus, medial, and inferior temporal cortex. 63 Patients with enhanced loading on this [11C]PK11195 binding distribution displayed diffuse 64 abnormal functional connectivity. The expression of a stronger association between such 65 abnormal connectivity and higher levels of neuroinflammation correlated with worse 66 cognitive deficits. 67 Our study suggests that neuroinflammation relates to the pathophysiological 68 changes in network function that underlie cognitive deficits in Alzheimer’s disease. 69 Neuroinflammation, and its association with functionally-relevant reorganisation of brain 70 networks, is proposed as a target for emerging immuno-therapeutic strategies aimed at 71 preventing or slowing the emergence of dementia. 72 73 74 75 76 77 78 79 Significance Statement 80 Neuroinflammation is an important aspect of Alzheimer’s disease (AD), but it was not 81 known whether the influence of neuroinflammation on brain network function in humans 82 was important for cognitive deficit. 83 Our study provides clear evidence that in vivo neuroinflammation in AD impairs 84 large-scale network connectivity; and that the link between inflammation and functional 85 network connectivity is relevant to cognitive impairment. 86 We suggest that future studies should address how neuroinflammation relates to 87 network function as AD progresses; and whether the neuroinflammation in AD is reversible, 88 as the basis of immunotherapeutic strategies to slow the progression of AD. 2 89 Introduction 90 Neuroinflammation plays a key role in the etio-pathogenesis of Alzheimer’s disease and 91 other neurodegenerative disorders (Edison et al., 2008; Fernandez-Botran et al., 2011; Fan 92 et al., 2015; Stefanetti et al., 2016). Pre-clinical models (Heppner et al., 2015; Hoeijmakers 93 et al., 2016; Villegas-Llerena et al., 2016; Li et al., 2018; Wang et al., 2018), and research in 94 humans 95 (Fernandez-Botran et al., 2011; Edison et al., 2013; Fan et al., 2015; Stefaniak and O’Brien, 96 2016; Passamonti et al., 2018), demonstrate that microglia, the brain’s innate immune 97 system, are activated in Alzheimer’s and other neurodegenerative diseases. Furthermore, 98 genetic association studies have demonstrated a link between Alzheimer’s disease and 99 polymorphisms or mutations in genes linked to immune responses (Villegas-Llerena et al., 100 2016). Although the mechanisms and mediators of inflammatory risk in Alzheimer’s disease 101 are not fully understood, synaptic and neuronal injury may arise from the release of 102 cytokines and pro-inflammatory molecules such as interleukin-1ß and TGF-ß (Fernandez- 103 Botran et al., 2011), or direct microglial injury to synapses (Hong and Stevens, 2016; Hong et 104 al., 2016). These, in turn, impair synaptic function, network communication, and may 105 accelerate neurodegeneration and synaptic loss (Heppner et al., 2015; Hoeijmakers et al., 106 2016; Villegas-Llerena et al., 2016; Li et al., 2018; Wang et al., 2018). 107 Clinical studies of neuroinflammation in dementia have exploited positron emission 108 tomography (PET) ligands that bind to the mitochondrial translocator protein (TSPO) in 109 activated microglia (Cagnin et al., 2001; Gerhard et al., 2006a, 2006b; Edison et al., 2008, 110 2013; Fan et al., 2015; Passamonti et al., 2018). For example, relative to controls, patients 111 with Alzheimer’s disease have higher [11C]PK11195 binding in the hippocampus, other 3 112 medial-temporal lobe regions, and posterior cortices such as the pre-cuneus, which in turn 113 correlates with cognitive severity (Passamonti et al., 2018). 114 These findings raise the possibility of immunotherapeutic strategies to prevent or slow the 115 progression of Alzheimer’s disease. However, key issues remain to be resolved before such 116 therapeutic strategies can be realised. For example, it is necessary to show how 117 neuroinflammation is linked to cognitive deficits. A critical and unanswered question is 118 whether regional neuroinflammation changes the functional connectivity of large-scale 119 networks. Such large-scale neural networks represent an intermediate phenotypic 120 expression of pathology in many diseases, that can be non-invasively quantified with 121 resting-state functional magnetic resonance imaging. A challenge is that neither the 122 anatomical substrates of cognition nor the targets of neurodegenerative disease are 123 mediated by single brain regions: they are in contrast distributed across multi-variate and 124 interactive networks. 125 We thus undertook a multi-modal and multi-variate neuroimaging study to combine 126 [11C]PK11195 quantification of distributed neuroinflammation with resting-state functional 127 imaging in patients at different stages of Alzheimer’s disease. We used “source-based 128
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