. Tau burden and the functional connectome in Alzheimer's disease and progressive supranuclear palsy. Brain. 2018 Feb 1;141(2):550-567. PubMed.

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  1. In this interesting and creative study from the labs of John O’Brien and James Rowe, Thomas Cope and colleagues graph theoretic measures that are employed to parse apart a very relevant set of competing hypotheses about why more densely interconnected regions tend to demonstrate a higher burden of tau pathology. Is tau more likely to accumulate in these regions precisely because they receive input from a greater number of brain regions and therefore receive more input of a prion-like protein that is spreading trans-neuronally? Or is there something inherently vulnerable about “hub”-like regions because they tend to be under greater metabolic stress?

    The authors hinge their exploration of this question on the assumption that three graph theoretic measures (weighted degree, participation coefficient, and clustering coefficient) most accurately and most completely dissociate three biological properties of a network: susceptibility to prion-like spread, increased metabolic demand, and vulnerable trophic supply, respectively. Beyond the theoretical suppositions the authors describe, it would be of interest to provide more evidence for how and why these three graph theoretic metrics were selected a priori to disentangle the aforementioned hypotheses.

    Throughout the study, the authors employed principled selection of regions of interest, conducted thorough sets of analyses to demonstrate the robustness of their results, and generated promising data on the underexplored relationship between AV-1451 PET patterns and the functional connectome. While this study may offer compelling in vivo human evidence to support the working hypothesis that tau pathology spreads in a prion-like fashion through functionally interconnected regions in AD (while regional patterns of neurodegeneration in PSP may be more related to intrinsic vulnerability of hubs), interpreting quantification of tau pathology using AV-1451 PET is made complicated by some idiosyncrasies of the tracer. First, the binding affinity of the AV-1451 ligand to tau lesions in AD and PSP are not comparable, and the low specificity of the ligand may leave the signal-to-noise ratio in non-AD tauopathies woefully low. This is especially problematic in regions of interest the authors included to quantify average AV-1451 uptake in PSP: Even in controls, the basal ganglia show intense age-related tracer retention that is unrelated to tau pathology (Choi et al., 2018). The authors did not describe controlling for the voxelwise effect of age in these regions; an approach comparing patient data to age-adjusted normative data might be useful here. Finally, many of our patients and controls show “off-target” AV-1451 retention in the meningeal cerebellar tentorium (Baker et al., 2017),  a signal which “bleeds in” to the superior cerebellum—the reference region used for AV-1451 scans in this study. The authors presumably used this superior portion to avoid PSP-related uptake in the dentate nuclei, but it is unclear whether the patients and controls in their study displayed this contaminating “off-target” uptake.

    References:

    . Off-Target 18F-AV-1451 Binding in the Basal Ganglia Correlates with Age-Related Iron Accumulation. J Nucl Med. 2018 Jan;59(1):117-120. Epub 2017 Aug 3 PubMed.

    . Considerations and code for partial volume correcting [18 F]-AV-1451 tau PET data. Data Brief. 2017 Dec;15:648-657. Epub 2017 Oct 16 PubMed.

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