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Tau molecular diversity contributes to clinical heterogeneity in Alzheimer’s disease

Nature Medicine volume 26, pages 1256–1263 (2020)Cite this article

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An Author Correction to this article was published on 29 January 2021

Abstract

Alzheimer’s disease (AD) causes unrelenting, progressive cognitive impairments, but its course is heterogeneous, with a broad range of rates of cognitive decline1. The spread of tau aggregates (neurofibrillary tangles) across the cerebral cortex parallels symptom severity2,3. We hypothesized that the kinetics of tau spread may vary if the properties of the propagating tau proteins vary across individuals. We carried out biochemical, biophysical, MS and both cell- and animal-based-bioactivity assays to characterize tau in 32 patients with AD. We found striking patient-to-patient heterogeneity in the hyperphosphorylated species of soluble, oligomeric, seed-competent tau. Tau seeding activity correlates with the aggressiveness of the clinical disease, and some post-translational modification (PTM) sites appear to be associated with both enhanced seeding activity and worse clinical outcomes, whereas others are not. These data suggest that different individuals with ‘typical’ AD may have distinct biochemical features of tau. These data are consistent with the possibility that individuals with AD, much like people with cancer, may have multiple molecular drivers of an otherwise common phenotype, and emphasize the potential for personalized therapeutic approaches for slowing clinical progression of AD.

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Fig. 1: Heterogeneity of clinical progression and age of onset in Alzheimer’s disease.
Fig. 2: Heterogeneity of tau seeding in the human brain.
Fig. 3: Tau seeding relies on an oligomeric form of tau.
Fig. 4: Tau seeding is associated with rate of disease progression and intensity of tau phosphorylation.

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Data availability

All requests for raw and analyzed data and materials are promptly reviewed by the Partners Healthcare innovation department to verify whether the request is subject to any intellectual property or confidentiality obligations. Patient-related data not included in the paper may be subject to patient confidentiality. Any data and materials that can be shared will be released via a Material Transfer Agreement upon reasonable request to the corresponding author.

The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE52 partner repository with the dataset identifier PXD018855. Source data are provided with this paper.

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Acknowledgements

This work was supported in part by a research agreement to Massachusetts General Hospital from Merck and by the NIH/NIA—5P50AG005134-35 (B.T.H.), 1RF1AG059789 (B.T.H.), 1RF1AG058674 (B.T.H.), 1P30AG062421 (B.T.H.), 1K08AG064039 (A.S.-P.). The authors also want to thank additional funding sources: Alzheimer’s Association (2018-AARF-591935 (S.D.), AACSF-19-617308 (A.L.)), the Martin L. and Sylvia Seevak Hoffman Fellowship for Alzheimer’s Research (S.D.), the Tau Consortium (B.T.H.), the Cure Alzheimer’s Fund (R.E.T.), the JPB Foundation (B.T.H. and R.E.T.), and the Swiss National Science Foundation (P2ELP3_184403 (A.L.)). We thank J. A. Gonzalez for helping with brain sampling, M. C. Potter for input in early phases of the work, P. Davies (Albert Einstein College of Medicine, New York City) for generously providing with PHF1 antibody and M. Diamond (UT Southwertern, Dallas, Texas) for the generous gift of the TauRD-P301S-CFP/YFP cells.

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Author notes

  1. Benjamin D. Moore

    Present address: Aquinnah Pharmaceuticals, Cambridge, MA, USA

  2. Fiona Elwood

    Present address: Novartis Institutes for BioMedical Research, Cambridge, MA, USA

Authors and Affiliations

  1. Alzheimer Research Unit, Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA

    Simon Dujardin, Caitlin Commins, Aurelien Lathuiliere, Analiese R. Fernandes, Tarun V. Kamath, Mark B. De Los Santos, Naomi Klickstein, Diana L. Corjuc, Bianca T. Corjuc, Patrick M. Dooley, Derek H. Oakley, Benjamin D. Moore, Lori B. Chibnik, Alberto Serrano-Pozo & Bradley T. Hyman

  2. Harvard Medical School, Boston, MA, USA

    Simon Dujardin, Aurelien Lathuiliere, Pieter Beerepoot, Arthur Viode, Derek H. Oakley, Benjamin D. Moore, Lori B. Chibnik, Rudolph E. Tanzi, Matthew P. Frosch, Alberto Serrano-Pozo, Judith A. Steen & Bradley T. Hyman

  3. F.M. Kirby Neurobiology Center, Boston Children’s Hospital, Boston, MA, USA

    Pieter Beerepoot, Arthur Viode & Judith A. Steen

  4. C.S. Kubik Laboratory for Neuropathology, Massachusetts General Hospital, Boston, MA, USA

    Patrick M. Dooley, Derek H. Oakley & Matthew P. Frosch

  5. Genetics and Aging Research Unit, Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA

    Kristina Mullin & Rudolph E. Tanzi

  6. Department of Neuroscience, Merck & Co., Boston, MA, USA

    Dinorah Jean-Gilles, Ryan Clark, Kevin Atchison, Renee Moore, Fiona Elwood & Matthew E. Kennedy

  7. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Lori B. Chibnik

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Contributions

S.D., F.E., M.E.K. and B.T.H. conceived the study and designed the experiments. S.D., C.C., A.L., A.R.F., T.V.K., P.B., A.V., M.B.D.L.S., N.K., D.L.C., B.T.C., P.M.D., B.D.M., K.M., D.J.-G., R.C., K.A., R.M. and A.S.-P. performed experiments and analyzed data. J.A.S. designed the MS experiments. L.B.C. helped with the statistical analysis. R.E.T. designed the whole-exome sequencing procedure. A.S.-P., D.H.O. and M.P.F. provided clinical advice and critical input on the manuscript. The manuscript was written by S.D. and B.T.H. with input from all of the authors.

Corresponding author

Correspondence to Bradley T. Hyman.

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Competing interests

This work was supported in part by a research agreement to Massachusetts General Hospital from Merck & Co. D.J.-G, R.C., R.M., K.A., F.E., and M.E.K. are/were full time employees of Merck & Co. Inc. during the course of the work.

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Extended data

Extended Data Fig. 1 Kinetics of tau seeding in FRET biosensor assay relates to Fig. 2d.

a, Tau seeding was quantified by live imaging over 72 h of FRET biosensor cells exposed to PBS extracts of the 32 human AD brains. This process is divided into three phases: a nucleation/lag phase followed by the exponential polymerization/elongation phase and ending by a plateau phase. Samples were normalized to total tau levels before being added to the seeding assay and the number of aggregates obtained was normalized to both positive and negative controls. A sigmoidal, 4PL, X is log(concentration) nonlinear regression was applied before plotting the data b, Tau seeding dose response was investigated in two of these AD brain extracts. Tau seeding was quantified with 8 ng of total tau in the sample (dose used for Fig. 2d and in panel A) but also with 0.08 ng, 0.8 ng, 4 ng, 16 ng and 40 ng to demonstrate the dose dependence of the plateau phase and the ceiling effect of the assay. c, Statistically significant two-tailed Spearman’s rank nonparametric correlation between the plateau value for each of the 32 AD brain extracts measured in this manner and the seeding value obtained on the FRET biosensor assay by flow cytometry (Fig. 2b). d, Statistically significant two-tailed Spearman’s rank nonparametric correlation between the values of the plateau and of the slope for the 32 AD brains.

Source data

Extended Data Fig. 2 hTau seeding assay cell viability and association with FRET biosensor assay.

a, Timecourse of insoluble AT8 aggregates appearance in the hTau primary neuron seeding assay 1 hour, 1 day, 2 days and 7 days post incubation with the AD brain extracts. The right panel only represents the time points from 1 h to 2 days post incubation with the brain extracts. Error bars represents Standard deviations to the mean. n = 10 human subjects. Quantification of immunolabelling with NeuN (b) and MAP2 (c) in hTau mouse primary neurons incubated with 9 different AD brain extracts from our study’s cohort show a general viability of neuronal cells after brain extract incubation beside a possible toxicity with subject #32 brain extract. n = 4 independent experiments, error bars represent standard deviations to the mean d, Quantification of AT8 hyperphosphorylated tau staining on 9 human subjects from Fig. 2g. n = 4 independent experiments. Error bars represents Standard deviations to the mean. The color gradient scale bar relates to seeding quantities obtained in Fig. 2b. e, Statistically significant two-tailed Spearman’s rank nonparametric correlation between the value of seeding activity obtained in Fig. 2b and the AT8 signal intensity obtained with the hTau primary neuron seeding assay for 9 subjects AD brain extracts. f, Tau seeding in a mouse model of tauopathy- Relates to Fig. 2h,i. Two-month-old P301S transgenic mice were stereotactically injected with human AD brain PBS extracts from 10 human AD subject. Mice were euthanized 2 months later, and their brains processed for AT8 immunohistochemistry to assess the in vivo seeding potential of human AD brain extracts. n = 5 animals per human subject. Bar graph depicts the stereological quantification of the number of AT8-positive neurons in the cortex and hippocampus. The color gradient scale bar relates to seeding quantities obtained in Fig. 2b. Error bars represents Standard deviations to the mean.

Source data

Extended Data Fig. 3 Hyperphosphorylation is closely associated with tau seeding.

Brain extracts from the 32 AD subject were quantified for two epitopes of tau using alphaLISA (AT8 (a) and PHF6 (b)). Prior to this assay, samples were normalized for total protein amount as obtained using a BCA assay. Background Corrected Relative Light Unit (RLU) are plotted here. The color gradient scale bar relates to seeding quantities obtained in Fig. 2b. Both phospho-epitopes show a positive statistically significant association with tau seeding using a two-tailed Spearman’s rank non parametric correlation. SEC fractions from 9 AD brain extracts grouped into high seeders (red, n = 3), moderate seeders (green, n = 3) and low seeders (blue, n = 3) were tested for the presence of epitopes of tau hyperphosphorylation by alphaLISA (AT8 (d) and PHF6 (c)). Error bars represent the standard deviation to the mean. Showing the enriched presence of these epitopes in HMW fractions, especially in high and moderate seeders. e, HMW tau species quantified from the SDD-AGE (bin1-6, see Fig. 3b) were correlated with oligomeric tau levels from the alphaLISA showing a significant two-tailed Spearman’s rank nonparametric correlation. The r coefficient and p value are indicated on the plot. n = 14 individual subjects.

Source data

Extended Data Fig. 4 Proteinase K digestion Western blots.

Relates to Fig. 3f–i. 12 AD brain extracts from our study’s cohort were incubated with increasing doses of proteinase K and run on a Western blot in order to investigate differential stabilities of tau species. Antibodies recognizing total tau proteins as well as hyperphosphorylated tau proteins were used as detection antibodies. This experiment was repeated two times with similar results.

Extended Data Fig. 5 Correlation of postmortem interval and longevity versus intensities of phosphorylation.

Intensity of phosphorylation of phospho-sites T181, S198/S199/S202, T217, T231, T231&S235, S262, S400/T403/S404 (ordinate) were correlated with postmortem interval53 (a) or age at death54 (b) (abscissa). n = 31 individual subjects. Two-tailed Spearman’s rank nonparametric correlation tests were used, and r coefficient and p values are indicated on the tables. c, Some phospho-epitopes do not correlate with seeding- Intensity of phosphorylation of phospho-sites T181, T217 and T231 (ordinate) were correlated with tau seeding activity (abscissa). n = 31 individual subjects. Two-tailed Spearman’s rank nonparametric correlation test was used, and r coefficient and p value are indicated on the plots.

Source data

Extended Data Fig. 6 Tau seeding activity correlates with tau and GFAP-immunoreactive burdens.

Immunohistochemical staining of tau (indicative of NFTs, neuropil threads and plaque-associated neuritic dystrophies) a, Amyloid-β (indicative of Aβ plaques) c, GFAP + reactive astrocytes e, and CD68 + phagocytic microglia g, formalin-fixed paraffin-embedded sections from the frontal association cortex (BA8/9) of the 32 AD subjects and their respective burden quantifications (b,d,f,h). The color gradient scale bar relates to seeding activities obtained in Fig. 2b. Both the tau burden and the GFAP burden show a statistically significant positive association with tau seeding using a two-tailed Spearman’s rank nonparametric correlation. i, Cortical thickness measured as a proxy for neurodenegeration45 in the same sections did not significantly correlated with tau seeding activity using a two-tailed Spearman’s rank nonparametric correlation. n = 32 individual human subjects.

Source data

Extended Data Fig. 7 Age of disease onset correlates with tau seeding activity but not with intensity of tau phosphorylation.

a, Tau seeding (on the abscissa) as quantified in Fig. 2b negatively correlates with age of onset. n = 32 individual subjects. b, Intensities of phosphorylation of different phospho-sites (ordinate) were positively or negatively correlated with age of onset (abscissa). n = 31 individual subjects. Two-sided Spearman’s rank nonparametric correlation test was used and r coefficient and p value are indicated on the plots.

Source data

Extended Data Fig. 8 Some phospho-epitopes do not correlate with rate of disease clinical progression.

Intensities of phosphorylation of phospho-sites T181, T217 and T231 (ordinate) were correlated with rate of clinical disease progression as indicated by the slope of the linearized CDR-SOB score trajectories (abscissa). Two-sided Spearman’s rank nonparametric correlation test was used and r coefficient and p value are indicated on the plots. n = 31 individual human subjects.

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Extended Data Fig. 9 Rate of clinical disease progression and age of symptom onset correlate with tau burden, oligomeric tau and phosphorylated tau levels.

The relationship between age of onset and rate of progression undoubtedly has many contributors, hence it is not surprising that some relationships are not evident statistically in a relatively small sample that was not selected to examine this question. As expected and previously established2,3,55,56, Rate of disease clinical progression as indicated by the slope of the linearized CDR-SOB score trajectories and age of symptom onset as quantified in Fig. 1b, c significantly correlates with tau burden from Extended Data Fig. 6a,b (respectively a, and b) but also oligomeric tau levels from Fig. 3a (respectively c, and d, p = 0.057) and 2 epitopes of tau hyperphosphorylation: PHF6, from Extended Data Fig. 3b (respectively e, and f, p = 0.051) and AT8 from Extended Data Fig. 3a (respectively g, and h) in the 32 subjects of this study’s cohort54. i, As recently described and probably not independent of the age of onset, tau seeding correlates with age at death54. Correlations were carried out using a two-sided Spearman’s rank nonparametric correlation, r coefficient and p values are indicated on the plots. n = 32 individual human subjects. j, Analysis of tau seeding activity by APOE genotype showed a statistically significant difference with higher seeding activity in APOEε4/ε4 subjects (n = 5) compared to APOEε3/ε4 (n = 20, p = 0.0013) and APOEε4 non-carriers (n = 8, p = 0.0072). Groups were compared using a one-way ANOVA with a Tukey’s multiple comparison post-test. Error bars represent standard deviation to the mean.

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Extended Data Fig. 10 Reduction of tau seeding by antibodies is epitope and subject-to-subject dependent.

a, Schematic representation of the paradigm of tau seeding reduction via immunodepletion. Antibodies were coupled with magnetic beads and incubated with AD brain extract. Beads/antibodies/antigens complexes were depleted and the supernatant placed on the FRET biosensor seeding assay. FRET was quantified by flow cytometry. b, Schematic representation of tau protein with alternative exons 2 (yellow), 3 (green) and 10 (red) as well as the repeated regions of the microtubule binding domains (black). Antibodies used in this study are indicated below. Green antibodies (Tau12, HT7 and Tau46) target the total protein when red antibodies (AT270, AT8, pS262 and PHF1) target phospho-epitopes known to be associated with AD tau pathology. c, Antibody-mediated reduction of tau seeding across 15 AD subjects from our study’s cohort (left column). Antibodies are organized in columns. IgG serve as negative control for seeding reduction. Percentage of seeding reduction and standard deviation are indicated for each individual/antibody association. The color code of seeding reduction is indicated in the lower panel.

Supplementary information

Supplementary Information

Supplementary Tables 1–3 and Figs. 1 and 2.

Reporting Summary

Supplementary Video 1

Kinetic of tau seeding in FRET-biosensor assay. Tau seeding was quantified by fluorescent live imaging over 72 h in the FRET-biosensor assay cells exposed to PBS extracts of a human AD brain. Representative video of the appearance of aggregates is shown in the left panel, along with our image-analysis model (center panel) separating background (white), cells (gray) and aggregates (black). Quantification and plotting overtime are shown in the right panel. This experiment was repeated at least 3 times with similar results.

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Dujardin, S., Commins, C., Lathuiliere, A. et al. Tau molecular diversity contributes to clinical heterogeneity in Alzheimer’s disease. Nat Med 26, 1256–1263 (2020). https://doi.org/10.1038/s41591-020-0938-9

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