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. 2023 Jul 3;146(7):2928-2943.
doi: 10.1093/brain/awac498.

Brain network decoupling with increased serum neurofilament and reduced cognitive function in Alzheimer's disease

Muriah D Wheelock  1 , Jeremy F Strain  2 , Patricia Mansfield  3 , Jiaxin Cindy Tu  1 , Aaron Tanenbaum  2 , Oliver Preische  4 , Jasmeer P Chhatwal  5 , David M Cash  6   7 , Carlos Cruchaga  8 , Anne M Fagan  2 , Nick C Fox  6   7 , Neill R Graff-Radford  9 , Jason Hassenstab  2 , Clifford R Jack  10 , Celeste M Karch  8 , Johannes Levin  11   12   13 , Eric M McDade  2 , Richard J Perrin  2   14 , Peter R Schofield  15   16 , Chengjie Xiong  17 , John C Morris  2 , Randal J Bateman  2 , Mathias Jucker  4   18 , Tammie L S Benzinger  2 , Beau M Ances  2 , Adam T Eggebrecht  1 , Brian A Gordon  1 ; Dominantly Inherited Alzheimer Network
Collaborators, Affiliations

Brain network decoupling with increased serum neurofilament and reduced cognitive function in Alzheimer's disease

Muriah D Wheelock et al. Brain. .

Abstract

Neurofilament light chain, a putative measure of neuronal damage, is measurable in blood and CSF and is predictive of cognitive function in individuals with Alzheimer's disease. There has been limited prior work linking neurofilament light and functional connectivity, and no prior work has investigated neurofilament light associations with functional connectivity in autosomal dominant Alzheimer's disease. Here, we assessed relationships between blood neurofilament light, cognition, and functional connectivity in a cross-sectional sample of 106 autosomal dominant Alzheimer's disease mutation carriers and 76 non-carriers. We employed an innovative network-level enrichment analysis approach to assess connectome-wide associations with neurofilament light. Neurofilament light was positively correlated with deterioration of functional connectivity within the default mode network and negatively correlated with connectivity between default mode network and executive control networks, including the cingulo-opercular, salience, and dorsal attention networks. Further, reduced connectivity within the default mode network and between the default mode network and executive control networks was associated with reduced cognitive function. Hierarchical regression analysis revealed that neurofilament levels and functional connectivity within the default mode network and between the default mode network and the dorsal attention network explained significant variance in cognitive composite scores when controlling for age, sex, and education. A mediation analysis demonstrated that functional connectivity within the default mode network and between the default mode network and dorsal attention network partially mediated the relationship between blood neurofilament light levels and cognitive function. Our novel results indicate that blood estimates of neurofilament levels correspond to direct measurements of brain dysfunction, shedding new light on the underlying biological processes of Alzheimer's disease. Further, we demonstrate how variation within key brain systems can partially mediate the negative effects of heightened total serum neurofilament levels, suggesting potential regions for targeted interventions. Finally, our results lend further evidence that low-cost and minimally invasive blood measurements of neurofilament may be a useful marker of brain functional connectivity and cognitive decline in Alzheimer's disease.

Keywords: NfL; default mode network; enrichment; functional connectivity; neurodegeneration; resting state.

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Conflict of interest statement

R.J.B. is Director of DIAN–TU and Principal Investigator of DIAN–TU-001. He receives research support from the NIA of the NIH, DIAN–TU trial pharmaceutical partners (Eli Lilly and Company, F. Hoffman-La Roche Ltd. and Avid Radiopharmaceuticals), Alzheimer’s Association, GHR Foundation, Anonymous Organization, DIAN–TU Pharma Consortium (active: Biogen, Eisai, Eli Lilly and Company, Janssen, F. Hoffmann-La Roche Ltd/Genentech; previous: AbbVie, Amgen, AstraZeneca, Forum, Mithridion, Novartis, Pfizer, Sanofi, United Neuroscience). He has been an invited speaker and consultant for AC Immune, F. Hoffman-La Roche Ltd. and Janssen and a consultant for Amgen and Eisai. A.M.F. has received research funding from the National Institute on Aging of the National Institutes of Health, Biogen, Centene, Fujirebio and Roche Diagnostics. She is currently a member of the scientific advisory boards for Roche Diagnostics and Genentech and consults for DiademRes, DiamiR and Siemens Healthcare Diagnostics. There are no conflicts. N.R.G.R. takes part in multicenter treatment studies sponsored by Biogen, Lilly, and AbbVie. J.L. reports personal fees from MODAG GmbH, personal fees from Bayer Vital, personal fees from Axon Neuroscience, non-financial support from AbbVie, personal fees from Thieme medical publishers, personal fees from W. Kohlhammer GmbH medical publishers, personal fees from Roche, personal fees from Biogen, outside the submitted work. P.R.S. reports grants from NIH (administered through Wash U), grants from Anonymous Foundation (administered through Wash U), and grants from Roth Charitable Foundation, during the conduct of the study. C.J. serves on an independent data monitoring board for Roche, has served as a speaker for Eisai, and consulted for Biogen, but he receives no personal compensation from any commercial entity. He receives research support from NIH, the GHR Foundation and the Alexander Family Alzheimer’s Disease Research Professorship of the Mayo Clinic. D.M.C. is supported by the UK Dementia Research Institute which receives its funding from DRI Ltd., funded by the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK, as well as Alzheimer’s Research UK (ARUK-PG2017-1946) and the UCL/UCLH NIHR Biomedical Research Centre. T.L.S.B. has investigator-initiated research funding from the NIH, the Alzheimer’s Association, the Barnes-Jewish Hospital Foundation and Avid Radiopharmaceuticals (a wholly owned subsidiary of Eli Lilly). T.L.S.B. participates as a site investigator in clinical trials sponsored by Avid Radiopharmaceuticals, Eli Lilly, Biogen, Eisai, Jaansen, and Roche. She serves as an unpaid consultant to Eisai and Siemens. She is on the Speaker’s Bureau for Biogen.

Figures

Figure 1
Figure 1
Disruptions at the molecular level drive network level disruptions in the connectome. (A) Neurofilaments, surrounding an inner layer of microtubules and tau proteins, provide a structural framework to axons. (B) Axonal injury and neuronal death lead to the release of neurofilaments into the extracellular fluid. (C) Amyloid PET and (D) tau PET spatial localization converted to a regional SUVR for an individual with ADAD. (E) Regional neurodegeneration results in reduced communication among brain regions and resulting network dysfunction. (F) Network Level Analysis can be used to assess connectome-wide disruptions in FC and associations with biomarkers and clinical outcomes. BOLD time series were extracted from 246 spherical ROI. The non-parametric correlation between NfL and whole brain connectome was examined separately for each group. Significance was established by randomly permuting the NfL values 10 000 times and measuring the permuted connectome-NfL relationship. AUD = auditory; BG = basal ganglia; CO = cingulo-opercular; DAN, dorsal attention network; DMN, default mode network; FPN = frontoparietal network; LATM = lateral motor; MEM = memory; MOT = motor; SN = salience network; THAL = thalamus; VAN = ventral attention network; VIS = visual.
Figure 2
Figure 2
Demographic characteristics and blood estimates of neurofilament light. (A) Mutation carriers had greater levels of serum NfL than NC (P < 0.05). (B) MC and NC did not differ in age. However, age positively correlated with serum NfL in both NC (C) and MC (D). (E–F) NfL was positively correlated with Aβ Pittsburgh Compound B SUVRs and CCS in MC but not NC.
Figure 3
Figure 3
Connectome changes as a function of EYO and carrier group. (A) Group average connectomes for NC compared to MC categorized into three EYO bins. MC demonstrated decreased FC compared to NC when approaching and upon surpassing their EYO. (B) Spring embedded plots for NC and MC with an EYO < −10 demonstrate a similar FC pattern, while plots for MC with an EYO > −10 exhibit reduced/less extensive network topology. (C) One-way ANOVA revealed five significant network pairs (FWE P < 0.001). (D) Post hoc tests revealed reduced FC in the MC group from pre- to post-EYO. MC had reduced FC compared to NC post-EYO (see Supplementary Tables 1–3). AUD = auditory; BG = basal ganglia; CO = cingulo-opercular; DAN, dorsal attention network; DMN, default mode network; FPN = frontoparietal network; LATM = lateral motor; MEM = memory; MOT = motor; SN = salience network; THAL = thalamus; VAN = ventral attention network; VIS = visual. *P < 0.05 FWE.
Figure 4
Figure 4
Functional networks associated with NfL. (A) Partial correlations between NfL and FC (regressing out effects of age) in MC and NC groups. (B) MC demonstrated stronger associations with NfL than NC in four network pairs (P < 0.025). (C) For MC and (D) NC, pink and green lines indicate negative and positive correlations between NfL and FC, respectively, wherein individuals with the highest NfL have the lowest DMN FC along with reduced anti-correlation between DMN and SN, DAN, and CO networks. Scatter plots demonstrate correlation between NfL with average FC from within DMN and between DMN and SN, DAN, and CO networks.
Figure 5
Figure 5
Network FC associated with NfL is correlated with cognitive function in MC. Orange-red lines indicate a positive correlation between DMN within network FC and CCS, wherein individuals with the lowest CCS have the lowest DMN FC. Blue lines indicate a negative correlation between DMN FC with control networks and CCS, wherein individuals with the worse cognitive function have reduced anti-correlation between DMN and SN, DAN, and CO networks.
See this image and copyright information in PMC

References

    1. Gordon BA, Blazey TM, Christensen J, et al. . Tau PET in autosomal dominant Alzheimer’s disease: Relationship with cognition, dementia and other biomarkers. Brain. 2019;142:1063–1076. - PMC - PubMed
    1. Benzinger TL, Blazey T, JackCR, Jr., et al. . Regional variability of imaging biomarkers in autosomal dominant Alzheimer’s disease. Proc Natl Acad Sci U S A. 2013;110:E4502–9. - PMC - PubMed
    1. Buckner RL, Sepulcre J, Talukdar T, et al. . Cortical hubs revealed by intrinsic functional connectivity: Mapping, assessment of stability, and relation to Alzheimer’s disease. J Neurosci. 2009;29:1860–1873. - PMC - PubMed
    1. La Joie R, Perrotin A, Barre L, et al. . Region-specific hierarchy between atrophy, hypometabolism, and β-amyloid (Aβ) load in Alzheimer’s disease dementia. J Neurosci. 2012;32:16265–16273. - PMC - PubMed
    1. Bridel C, van Wieringen WN, Zetterberg H, et al. . Diagnostic value of cerebrospinal fluid neurofilament light protein in neurology: A systematic review and meta-analysis. JAMA Neurol. 2019;76:1035–1048. - PMC - PubMed

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