Tau follows principal axes of functional and structural brain organization in Alzheimer’s disease

Alzheimer’s disease (AD) is a brain network disorder where pathological proteins accumulate through networks and drive cognitive decline. Yet, the role of network connectivity in facilitating this accumulation remains unclear. Using in-vivo multimodal imaging, we show that the distribution of tau and reactive microglia in humans follows spatial patterns of connectivity variation, the so-called gradients of brain organization. Notably, less distinct connectivity patterns (“gradient contraction”) are associated with cognitive decline in regions with greater tau, suggesting an interaction between reduced network differentiation and tau on cognition. Furthermore, by modeling tau in subject-specific gradient space, we demonstrate that tau accumulation in the frontoparietal and temporo-occipital cortices is associated with greater baseline tau within their functionally and structurally connected hubs, respectively. Our work unveils a role for both functional and structural brain organization in pathology accumulation in AD, and supports subject-specific gradient space as a promising tool to map disease progression.

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All analyses are adjusted for sex based on self-report (F=60.6%).Our dataset did not record gender at the time of data collection.Gradient effects disaggregated for sex (Supplementary Fig. 11c) All patients are White.
Methods section 'Participants' and All participants gave their written informed consent prior to inclusion in the study.They received a compensation to cover travel expenses and time.
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Overall gradient directions were consistent across subjects representing different stages of the disease; and were in line with literature as published previously for fMRI in healthy controls (Margulies et al 2016 PNAS).We performed additional leave-one-out-cross validation (LOOCV in sklearn, Python).No cohorts other than TRIAD were included in this study.
No randomized trials were performed, as allocations into groups were performed by clinical diagnosis (cognitively unimpaired vs impaired [MCI or AD dementia]) and/or amyloid/tau positivity.Amyloid status was determined based on visual rating of the amyloid-PET images, with the final rating based on consensus of two physicians specialized in dementia imaging.Describe the methods by which all novel plant genotypes were produced.This includes those generated by transgenic approaches, gene editing, chemical/radiation-based mutagenesis and hybridization.For transgenic lines, describe the transformation method, the number of independent lines analyzed and the generation upon which experiments were performed.For gene-edited lines, describe the editor used, the endogenous sequence targeted for editing, the targeting guide RNA sequence (if applicable) and how the editor was applied.
Report on the source of all seed stocks or other plant material used.
PET images: The 18F-MK6240, 18F-NAV4694, and 11C-PBR28 PET scans were acquired at 90-110, 40-70, and 60-90 min following radiotracer injection, respectively, and reconstructed using an ordered-subsets expectation maximization (OSEM) algorithm on a 4D volume with 4 (x300 seconds), 6 (x300 seconds), and 3 (x600 seconds) frames, respectively.They were corrected for dead time, decay, random and scattered coincidences, and attenuation based on a 6-min transmission scan with a rotating 137Cs point source.- diffusion-weighted MRI: preprocessed using FSL and MRtrix3, including correction for susceptibility distortions, motion (both between frames and within frames), gibbs ringing, and eddy currents (and removal of the full frame if >20% of the slices within the frame are detected as outlier based on the FSL Eddy report).see above.
correlations between gradients; group-wise differences in gradient scores; associations between gradients and PET/ cognition.
nodes were parcellated based on three different brain atlases: (i) an in-house developed highresolution parcellation based on the multi-modal Glasser atlas re-parcellated into equally-sized subregions-of-interest (ROIs) of ~512mm3 totaling 1318 nodes, (ii) the structural-based Desikan-Killiany-Tourville (DKT) atlas implemented in FreeSurfer consisting of 66 nodes, and (iii) the functional-based Schaefer atlas consisting of 100 nodes with addition of the hippocampus based on the Harvard-Oxford atlas.or predictive analysis Functional and/or effective connectivity Multivariate modeling and predictive analysis null models using spatial autocorrelation-preserving surrogates whole-brain: FWE cluster-wise; gradients: Variogram matching with 1000 permutations; cognitions: FDR.undirected weighted connectivity matrix -fMRI: correlation with Pearson's R -diffusion MRI: intra-axonal cross-sectional area of of the FBC Unsupervised dimensionality reduction (https://brainspace.readthedocs.io/en/latest/index.html)

Table 1
; https://triad.tnl-mcgill.com/cohort-description/Allsubjects in this study were part of the Translational Biomarkers in Aging and Dementia (TRIAD) cohort, a longitudinal imaging and biofluid cohort study of aging and AD.Participants were recruited through advertisements in the community, newspaper advertisements, word of mouth, and referrals from the McGill Centre for Studies in Aging.Evaluations of participants included a review of their medical history and an interview with the participant and their study partner followed by a neurologic examination by a dementia specialist and a neuropsychological examination.The main potential bias is participants' willingness to participate in the study, which may result in cognitive and other aspects of the investigated cohort being different from individuals who are unwilling to participate, or are unaware of this possibility.The McGill University, the Montreal Neurological Institute (MNI) PET working committee, and the Douglas Mental Health University Institute Research Ethics Board (Mental Health and Neuroscience subcommittee of the CIUSSS ODIM REB) provided ethical approval (IUSMD-16-60).
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Tau status tau status was based on visual rating of the tau-PET images with high retention in early Braak areas(Seibyl et al. 2023 J. Nucl.Med.Off.Publ.Soc.Nucl.Med)nature portfolio | reporting summary If applicable, state the seed stock centre and catalogue number.If plant specimens were collected from the field, describe the collection location, date and sampling procedures.Structural T1-weighted MRI, diffusion-weighted MRI, functional (resting-state) MRI, and PET.Dicoms were converted to niftii.
Describe any authentication procedures for each seed stock used or novel genotype generated.Describe any experiments used to assess the effect of a mutation and, where applicable, how potential secondary effects (e.g.second site T-DNA insertions, mosiacism, off-target gene editing) were examined.
Post-processing nuisance regressors were based on the CompCor predefined strategy as outlined in Behzadi et al. and included bandpass filtering (0.01-0.08 Hz), non-steady-state volume, head motion with linear/quadratic terms and derivatives, and six components for the anatomical + temporal CompCors.This was implemented in Python through Nilearn's fmriprep.load_confoundsfunction using the CompCor strategy developed by Wang et al 2023 biorxiv.The rs-fMRI data were smoothed with 4mm full-width-at-half-maximum.