Neuronal and oligodendroglial, but not astroglial, tau translates to in vivo tau PET signals in individuals with primary tauopathies

Abstract

Tau PET has attracted increasing interest as an imaging biomarker for 4-repeat (4R)-tauopathy progressive supranuclear palsy (PSP). However, the translation of in vitro 4R-tau binding to in vivo tau PET signals is still unclear. Therefore, we performed a translational study using a broad spectrum of advanced methodologies to investigate the sources of [¹⁸F]PI-2620 tau PET signals in individuals with 4R-tauopathies, including a pilot PET autopsy study in patients. First, we conducted a longitudinal [¹⁸F]PI-2620 PET/MRI study in a 4-repeat-tau mouse model (PS19) and detected elevated [¹⁸F]PI-2620 PET signals in the presence of high levels of neuronal tau. An innovative approach involving cell sorting after radiotracer injection in vivo revealed higher tracer uptake in single neurons than in the astrocytes of PS19 mice. Regional [¹⁸F]PI-2620 tau PET signals during the lifetime correlated with the abundance of fibrillary tau and with autoradiography signal intensity in PSP patients and disease controls who underwent autopsy 2–63 months after tau PET. In autoradiography, tau-positive neurons and oligodendrocytes with a high AT8 density, but not tau-positive astrocytes, were the drivers of [¹⁸F]PI-2620 autoradiography signals in individuals with PSP. The high tau abundance in oligodendrocytes at the boundary of gray and white matter facilitated the identification of an optimized frontal lobe target region to detect the tau burden in patients with PSP. In summary, neuronal and oligodendroglial tau constitutes the dominant source of tau PET radiotracer binding in 4-repeat-tauopathies, translating to an in vivo signal.

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Acta Neuropathologica (2024) 148:70
https://doi.org/10.1007/s00401-024-02834-7
ORIGINAL PAPER
Neuronal andoligodendroglial, butnotastroglial, tau translates
toinvivo tau PET signals inindividuals withprimary tauopathies
LunaSlemann1· JohannesGnörich1,2· SelinaHummel1· LauraM.Bartos1· CarolinKlaus2· AgnesKling1·
JuliaKusche‑Palenga1· SebastianT.Kunte1· LeaH.Kunze1· AmelieL.Englert1· YunleiLi1· LetiziaVogler1·
SabrinaKatzdobler2,3,4· CarlaPalleis2,3,4· AlexanderBernhardt2,3· AlexanderJäck2,3· AndreasZwergal3,5·
FranziskaHopfner3· SebastianN.Roemer‑Cassiano3,15· GloriaBiechele6· SophiaStöcklein6· GerardBischof7,8·
ThilovanEimeren7,8,9,10· AlexanderDrzezga8,10· OsamaSabri11· HenrykBarthel11· GesineRespondek12·
TimoGrimmer13· JohannesLevin2,3,4· JochenHerms2,4,14· LarsPaeger2· MarieWillroider1· LeonieBeyer1·
GünterU.Höglinger2,3,4· SigrunRoeber14· NicolaiFranzmeier4,15,16· MatthiasBrendel1,2,4
Received: 14 June 2024 / Revised: 14 November 2024 / Accepted: 14 November 2024
© The Author(s) 2024
Abstract
Tau PET has attracted increasing interest as an imaging biomarker for 4-repeat (4R)-tauopathy progressive supranuclear
palsy (PSP). However, the translation of invitro 4R-tau binding to invivo tau PET signals is still unclear. Therefore, we
performed a translational study using a broad spectrum of advanced methodologies to investigate the sources of [18F]PI-2620
tau PET signals in individuals with 4R-tauopathies, including a pilot PET autopsy study in patients. First, we conducted a
longitudinal [18F]PI-2620 PET/MRI study in a 4-repeat-tau mouse model (PS19) and detected elevated [18F]PI-2620 PET
signals in the presence of high levels of neuronal tau. An innovative approach involving cell sorting after radiotracer injec-
tion invivo revealed higher tracer uptake in single neurons than in the astrocytes of PS19 mice. Regional [18F]PI-2620 tau
PET signals during the lifetime correlated with the abundance of fibrillary tau and with autoradiography signal intensity
in PSP patients and disease controls who underwent autopsy 2–63months after tau PET. In autoradiography, tau-positive
neurons and oligodendrocytes with a high AT8 density, but not tau-positive astrocytes, were the drivers of [18F]PI-2620
autoradiography signals in individuals with PSP. The high tau abundance in oligodendrocytes at the boundary of gray and
white matter facilitated the identification of an optimized frontal lobe target region to detect the tau burden in patients with
PSP. In summary, neuronal and oligodendroglial tau constitutes the dominant source of tau PET radiotracer binding in
4-repeat-tauopathies, translating to an invivo signal.
Keywords Tau· PET· PI-2620· Autopsy· Autoradiography· Neuron
Introduction
Progressive supranuclear palsy (PSP) is a rare neurode-
generative disease caused by the aggregation of tau protein
with 4 microtubule-binding repeats [48], leading to death
within 7–8years after onset, on average [44]. In the past, the
diagnosis was usually made 3–4years after the first clinical
symptoms, when patients already had severe functional
disabilities. Controlled autopsy data revealed that the clini-
cal diagnosis of PSP by the most recent MDS-PSP criteria
has only limited sensitivity in the early stages with moder-
ate specificity [42]. Currently, no approved causal therapy
exists, and preventive and symptomatic treatment options are
very limited. Since tau-targeting therapies are entering clini-
cal development, diagnosing patients with PSP at an early
stage is important to attenuate tau accumulation and there-
fore symptom progression. Furthermore, ensuring a high
level of specificity for 4-repeat tau for inclusion in tau-tar-
geting treatment trials is important to ensure adequate statis-
tical power and to avoid unnecessary side effects on patients
with clinically overlapping syndromes without 4-repeat tau
Luna Slemann, Johannes Gnörich, Selina Hummel, and Laura M.
Bartos share cofirst authors.
Günter U. Höglinger, Sigrun Roeber, Nicolai Franzmeier, and
Matthias Brendel share cosenior authors.
Extended author information available on the last page of the article
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Acta Neuropathologica (2024) 148:70 70 Page 2 of 23
aggregation. In this context, cohort studies in which the sec-
ond-generation tau PET radiotracers [18F]PI-2620 and [18F]
PM-PBB3 were used differentiated patients with PSP and
CBS from healthy controls and disease controls [12, 39, 49].
However, head-to-head autoradiographic studies with differ-
ent radiotracers by independent groups have produced incon-
sistent results, indicating the presence [32, 52] or absence
of [1] binding of radiolabeled PI-2620 to 4R-tauopathy tis-
sue sections. Furthermore, potential off-target sources still
need to be considered for second-generation radiotracers,
including neuromelanin and hemorrhagic lesions for [18F]
PI-2620 [1] and β-amyloid for [18F]PM-PBB3 [26]. Never-
theless, competitive assays [52] and molecular docking stud-
ies [28] confirmed the initially reported affinity of PI-2620
for 4R-tau [27].
Hence, we aimed to investigate the translation of invitro
[18F]PI-2620 4R-tau binding to invivo PET signals. We
performed longitudinal 4R-tau monitoring in tau transgenic
mice primarily expressing neuronal tau and pinpointed the
cellular source of tracer signals by cell sorting after radi-
otracer injection in living organisms. Invivo PET signals in
patients with definite PSP and disease controls were corre-
lated with the tau abundance and autoradiography signals in
autopsy samples. Cellular and substructure impacts on [18F]
PI-2620 signal contributions were examined in depth using
a PSP autoradiography sample with limited copathology.
Finally, we exploited the combined acquired knowledge to
create an optimized target region for the detection of cortical
tau pathology in patients with 4R-tauopathies.
Materials andmethods
Study design
In this translational study, we combined assessments of tau
PET, invitro autoradiography, quantitative tau immunohis-
tochemistry, and cellular tracer uptake using a 4R-tauopathy
mouse model and human samples consisting of patients with
4R-tauopathies and disease controls.
Small animal experiments
All small animal experiments were approved by the local
animal care committee of the Government of Upper Bavaria
(Regierung Oberbayern, approval number: ROB-55.2-2532.
Vet_02-15-210, ROB-55.2-2532.Vet_02-19-26). The exper-
iments were overseen by a veterinarian and conducted in
compliance with the ARRIVE guidelines and in accordance
with the U.K. Animals (Scientific Procedures) Act, 1986 and
associated guidelines, EU Directive 2010/63/EU for animal
experiments. The animals were housed in a temperature-
and humidity-controlled environment with a 12h light‒dark
cycle and free access to food (Ssniff Spezialdiäten GmbH,
Soest, Germany) and water. Anesthesia was induced before
[18F]PI-2620 application and maintained during the PET and
MR scans, with 1.5% isoflurane delivered via a mask at 3.5
L/min. All procedures were performed at the Department of
Nuclear Medicine, Ludwig Maximilian University (LMU)
Hospital, Munich. First, we conducted a longitudinal [18F]
PI-2620 PET/MRI study in a 4R-tau mouse model (PS19)
and age-matched wild-type mice (n = 10 each, all female)
using regional tau PET signals and volumetric measures as
endpoints. PS19 transgenic mice express mutated human
microtubule-associated protein tau (MAPT) under the
control of the mouse prion protein (Prnp) promoter. This
transgene encompasses the P301S mutation linked to the
disease and contains four microtubule-binding domains
alongside an N-terminal insert (4R/1N) [57]. Next, we per-
formed immunohistochemistry in a subset of these PS19 and
wild-type mice (n = 4 each) to characterize the regional tau
abundance and cellular contributions to tau pathology. Cell
sorting after tau radiotracer injection was applied in another
subset of PS19 and wild-type mice (n = 5 each) to determine
the cellular origin of the tau PET signals.
Human analyses
A key experiment of the study consisted of a correlation
analysis between regional [18F]PI-2620 tau PET signals and
the abundance of fibrillary tau pathology in autopsy samples
from patients with definite PSP (n = 6) and disease controls
(n = 2, amyotrophic lateral sclerosis, TDP-43-positive fron-
totemporal lobe degeneration). In this sample, we performed
a quantitative correlation analysis between tau PET signals,
autoradiography, and the abundance of AT8-positive tau
pathology. An additional autopsy sample from deceased
patients with PSP presenting with limited copathology
(n = 16) was used to determine the contributions of tau-pos-
itive neurons and tau-positive astrocytes to the [18F]PI-2620
autoradiography signals. To this end, the abundance of AT8-
positive tau pathology in subfields (≥ 8) of the frontal cor-
tex and basal ganglia sections was differentiated between
neurons and astrocytes using a data-driven tissue classifier.
An orienting a priori sample size calculation suggested a
minimum of n = 6 subjects or subfields to achieve a statis-
tical power of 0.8 at α = 0.05 for the detection of a mean-
ingful explanation of variance (β ≥ 0.3; residual variance
of 0.15) by two predictors (i.e., neuronal and astrocytic tau
abundances). The tissue samples from all the autopsy cases
investigated were provided by Neurobiobank Munich, LMU
Munich. They were collected according to the guidelines of
the local ethics committee, and the usage of the material for
this project was additionally approved (application number
19-244). Finally, the combined findings were used to evalu-
ate the emerging gray matter/white matter boundary target
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Acta Neuropathologica (2024) 148:70 Page 3 of 23 70
region for a tau PET assessment of 4R-tau pathology in the
cortex of patients with PSP (n = 17) compared with controls
(n = 9). All patients and controls who underwent invivo PET
imaging provided informed written consent. The study was
conducted in accordance with the principles of the Declara-
tion of Helsinki, and approval was obtained from the local
ethics committee (application numbers 17-569 and 19-022).
Small animal PET/MRI imaging
PET/MRI acquisition
All rodent PET procedures followed an established stand-
ardized protocol for radiochemistry, acquisition times, and
postprocessing using a PET/MRI system. All the mice
were scanned with a 3T Mediso nanoScan PET/MR scan-
ner (Mediso Ltd., Hungary) with a triple-mouse imaging
chamber. Two 2-min anatomical T1 MR scans were per-
formed prior to tracer injection (head receiver coil, matrix
size 96 × 96 × 22, voxel size 0.24 × 0.24 × 0.80 mm3, repeti-
tion time 677ms, echo time 28.56ms, and flip angle 90°).
The injected dose of [18F]PI-2620 delivered in 200µl saline
via intravenous injection was 12.7 ± 2.1MBq. PET emis-
sion was recorded in a dynamic 0–60min window. The
frames used were 6 × 10, 2 × 30, 3 × 60, 5 × 120, 5 × 300, and
5 × 600. The list-mode data within the 400–600keV energy
window were reconstructed using a 3D iterative algorithm
(Tera-Tomo 3D, Mediso Ltd., Hungary) with the following
parameters: matrix size of 55 × 62 × 187 mm3, voxel size
of 0.3 × 0.3 × 0.3 mm3, 8 iterations, and 6 subsets. Decay,
random, and attenuation corrections were applied. The T1
image was used to create a body–air material map for attenu-
ation correction. We longitudinally studied PS19 (n = 10)
and age-matched wild-type mice (n = 10, WT; C57BL6) at
5.9, 7.7, 10.2, and 12.4months of age. The sample size was
selected based on the assumption of detecting a 10% dif-
ference between genotypes at the latest time point with a
power of 0.8, applying an α of 0.05. No randomization was
used to allocate the experimental units due to the absence
of any intervention. No dropouts were registered; hence, all
the mice were included in the subsequent analysis. Blind-
ing was not applied during the scanning process, but it was
implemented during image analysis, where an automatic
coregistration step guaranteed reader independence [38].
PET/MRI analyses
The normalization of the PET data was performed by cal-
culating the volume of distribution (VT) images obtained
from the full dynamic scan, as described previously for
different tracers [6, 56]. Briefly, we generated VT images
with an image-derived input function using the methodol-
ogy described by Logan etal. implemented in PMOD. The
plasma curve was obtained from a standardized bilateral
VOI placed in the left ventricle. A maximum error of 10%
and a VT threshold of 0 were selected for modeling the
full dynamic imaging data. Furthermore, 20–40min static
[18F]PI-2620 images were analyzed as a readout matching
the scRadiotracing normalization. We applied the striatum
as a reference tissue to decrease the variability at the indi-
vidual subject level and calculated the VT ratio and stand-
ardized uptake value ratio (SUVR) for images. The refer-
ence tissue was validated by analyzing VT images from
PS19 and WT mice, which confirmed that no differences
in VT in the striatum (8.4 mm3) were observed between
genotypes. Predefined volumes of interest were delineated
by spheres in the brainstem (4.2 mm3) and the entorhinal
cortex (2.8 mm3), guided by regions of the Mirrione atlas
but eroded to avoid the spill-in of adjacent brain structures
(Supplemental Fig.1). These target regions served for the
extraction of PET values for all the mice.
The MRI volumetric analysis was performed in a
blinded manner on coronal sections by manual delineation
of the cerebellum, the brainstem, and the striatum (each in
three adjacent planes) using PMOD (Supplemental Fig.1).
We conducted a test–retest procedure to ensure the reli-
ability of MRI segmentation, which displayed a high con-
gruency (r) of > 0.9 across 10 test cases. The cerebellum
and brainstem were considered as a combined hindbrain
region.
scRadiotracing
Mouse brain dissociation
Five PS19 and five WT mice underwent scRadiotracing
[7, 8, 56] immediately after the tau PET scan. An Adult
Brain Dissociation Kit (mouse and rat) (Miltenyi Biotec,
130-107-677) was used for brain dissociation according to
the manufacturer's instructions. Adult mouse brains were
dissected, briefly washed with phosphate-buffered saline
(PBS), cut into eight pieces, and dissociated with enzyme
mixtures 1 and 2 using a gentleMACS™ Octo Dissociator
(Miltenyi Biotec, 130-096-427). The dissociated cell suspen-
sion was applied to a prewet 100µm cell strainer (Falcon,
352,360). The cell pellet was resuspended in cold PBS and
cold debris removal solution. Cold PBS was gently overlaid
on the cell suspension. The mixture was centrifuged at 4°C
and 3000×g for 10min with acceleration and deceleration
set at 5. The two top phases were removed entirely. The cell
pellets were collected and resuspended in 1ml of cold red
blood cell removal solution, followed by 10min of incuba-
tion. The cell pellets were collected for astrocyte and subse-
quent neuronal isolation via magnetic activated cell sorting
(MACS) [7, 8, 56].
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Acta Neuropathologica (2024) 148:70 70 Page 4 of 23
Isolation ofastrocytes
An Adult Brain Dissociation Kit for mouse and rat (Milte-
nyi Biotec, 130-107-677) was used according to the manu-
facturer's instructions. The prepared cell pellets were resus-
pended in 80µl of AstroMACS separation buffer (Miltenyi
Biotec, 130-117-336) per 107 total cells. Then, 10 μL of FcR
blocking reagent was added, and the mixture was incubated
for 10min in the dark at 4°C. Next, 10 μL of Anti-ACSA-2
MicroBeads was added, and the mixture was incubated for
15min in the dark at 4°C. The cells were washed by add-
ing 1mL of AstroMACS separation buffer and centrifuged
at 300×g for 5min. The cell pellets were resuspended in 500
μL of AstroMACS separation buffer. The prewet MS columns
(Miltenyi Biotec, 130-042-201) were placed in an OctoMACS
Separator (Miltenyi Biotec, 130-042-109). The cell suspen-
sions were applied onto the column, followed by washes with
3 × 500 µL of AstroMACS separation buffer. The flow-through
was collected and contained nonastrocytic cells as an astro-
cyte-depleted fraction. The columns were removed from the
magnetic field, and the astrocytes were flushed out using 3ml
of AstroMACS separation buffer.
Isolation ofneurons
A Neuron Isolation Kit, mouse (Miltenyi Biotec, 130-115-
390) was used as previously reported [20], according to the
manufacturer's instructions. The astrocyte-depleted cell pellets
were resuspended in 80µl of PBS–0.5% bovine serum albumin
(BSA) buffer per 107 total cells. Twenty microliters of nonneu-
ronal cell biotin–antibody cocktail was added, and the mixture
was incubated for 5min in the dark at 4°C. The cells were
washed and centrifuged at 300×g for 5min. The cell pellets
were again resuspended in 80 μL of PBS–0.5% BSA buffer
per 107 total cells. Next, 20 μL of anti-biotin microbeads was
added, and the mixture was incubated for 10min in the dark
at 4°C. The volume was adjusted to 500µl per 107 total cells
with PBS–0.5% BSA buffer, and then, magnetic separation
was performed. The prewet LS columns (Miltenyi Biotec, 130-
042-401) were placed in a QuadroMACS™ Separator (Milte-
nyi Biotec, 130-090-976). The cell suspensions were applied
onto the columns. The columns were washed with 2 × 1ml
of PBS–0.5% BSA buffer. The flow-throughs containing the
unlabeled cells were collected as the neuron-enriched frac-
tions. The columns were removed from the magnetic field, and
the nonneuronal cells were flushed out with 3ml of PBS–0.5%
BSA buffer [56].
Gamma emission, flow cytometry, andcalculation
ofsingle‑cell tracer uptake
The radioactivity concentrations of the cell pellets were
measured with a highly sensitive gamma counter (Hidex
AMG Automatic Gamma Counter, Mainz, Germany) are
reported relative to the activity in the whole brain, with
decay correction to the time of tracer injection for the final
activity calculations.
Flow cytometry staining was performed at 4°C. After
the gamma emission measurement, the cell suspension was
centrifuged at 400×g for 5min, and the supernatant was
aspirated completely. The cell pellet was then resuspended in
100µl of cold D-PBS containing fluorochrome-conjugated
antibodies recognizing mouse CD11b and ACSA-2 (Milte-
nyi Biotec, 130-113-810 and 130-116-247) at a 1:100 dilu-
tion and incubated for 10min at 4°C in the dark. The sam-
ples were washed with 2ml of D-PBS and centrifuged for
5min at 400×g. Finally, the cell pellets were resuspended in
500μl of D-PBS, and the samples were immediately used for
flow cytometry with an MACSQuant® Analyzer as a quality
control for MACS. Absolute cell numbers were acquired for
all the samples. The purity of the astrocyte-enriched cell pel-
let was determined via ACSA-2 staining. For the assessment
of purity within the neuron-enriched fraction, the proportion
of remaining CD11b- and ACSA-2-positive cells was deter-
mined and subtracted from the total number of cells within
the pellet. The CD11b-/ACSA-2-negative fraction was con-
sidered neurons and validated using CD90.1 as a neuronal
marker for C57BL6 mice (consistently > 85%).
The measured radioactivity (Bq) of the cell pellets was
divided by the specific cell number in the pellet, resulting in
the calculated radioactivity per cell. The sufficient sensitiv-
ity of a single readout was determined as a ≥ twofold ratio
between the cell pellet radioactivity and the background
measurement, with a total procedure duration of 6–7h from
tracer injection to radioactivity measurement in the enriched
cell pellets. The radioactivity per cell was normalized to the
injected radioactivity and body weight (%ID*BW).
Small animal immunohistochemistry
An additional number of four female PS19 mice and four
wild-type mice were used for immunohistochemistry, as
the same brains could not be used for both scRadiotracing
analysis and immunohistochemical staining. Fifty-micron-
thick slices were cut in the sagittal plane using a vibratome
(VT1200S, Leica Biosystems). Slices were treated with
blocking solution (10% normal goat serum and 10% donkey
serum in 0.3% Triton and PBS to a total volume of at least
200μl per well/slice) for 3h at RT. The following primary
antibodies were used: chicken anti-GFAP (1:500; ab5541;
Merck Millipore, Darmstadt, Germany), mouse anti-AT8
(1:1000; ab5541; Merck Millipore, Darmstadt, Germany),
and rabbit anti-MAP2 (1:500) diluted in blocking solution
(5% normal goat serum and 5% donkey serum in 0.3% Triton
and PBS to a total volume of at least 200μl per well/slice).
The antibodies were applied to the slices and subsequently
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Acta Neuropathologica (2024) 148:70 Page 5 of 23 70
incubated for ~ 48h at 4°C on a horizontal shaker. The fol-
lowing secondary antibodies were used: goat anti-rabbit
Alexa Fluor 488 (1:500), goat anti-chicken Alexa Fluor
555 (1:500), and goat anti-mouse Alexa Fluor 647 (1:500)
diluted in PBS. Slices were incubated for 2–3h at RT on a
horizontal shaker in the dark. After 3 × 10min washes with
PBS, the slices were mounted and cover slipped with fluo-
rescence mounting medium containing DAPI (Dako, Santa
Clara, USA).
Three-dimensional images were acquired with an
Apotome microscope (Zeiss Oberkochen, Germany) using
10 × and 40 × objectives. The analysis programs Zeiss blue
and ImageJ were used for quantification. Z-stack images
(10μm) were acquired with a 10 × objective. Each signal
(AT8 and GFAP) was quantified as the % area of the entire
scanning frame.
Single optical sections were acquired using a 40 × objec-
tive, and the AT8 signal was analyzed, because the percep-
tual signals were MAP2- and GFAP-positive. To this end,
we created a mask of the AT8 signal and transferred it into
GFAP-positive astrocytes and MAP2-positive neuronal
structures. After local brightness/contrast adjustments and
background subtraction, we set a fixed threshold and calcu-
lated the AT8 area (%) inside the mask of the GFAP-positive
astrocytes and MAP-positive neurons.
Human postmortem samples
Human samples
For PET of autopsy samples, we included all patients who
underwent [18F]PI-2620 tau PET prior to death, donated
their brain to the Munich Brain Bank, and underwent a
tissue workup by 31 March 2024 (n = 8; Supplemental
Table1). The formalin-fixed and paraffin-embedded tissue
blocks of one hemisphere were used for AT8 and autoradi-
ography analyses. The tissue from the medial frontal gyrus
and basal ganglia, including the globus pallidus, was avail-
able for seven patients with definite PSP, one patient with
FTLD-TDP, and one patient with FTLD/MND-TDP. For
in-depth analyses of the origins of the cellular and struc-
tural radiotracer signals, we selected samples with limited
α-synuclein, TDP-43, and FUS pathology from the Munich
Brain Bank. Limited β-amyloid pathology was tolerated,
resulting in a total sample size of n = 16 (Supplemental
Table2). Intact medial frontal gyrus tissue was available
for fourteen patients, and intact basal ganglia tissue, includ-
ing the globus pallidus, was available for seven patients. We
conducted [18F]PI-2620 autoradiography and AT8 immu-
nohistochemistry on postmortem brain tissues from n = 4
patients with clinically diagnosed Parkinson’s disease (PD)
to examine the specificity of tracer binding (Supplemental
Table3).
Immunohistochemistry
Immunohistochemistry was performed on 4µm-thick sec-
tions of formalin-fixed and paraffin-embedded tissue using
standard techniques. Immunohistochemical tau staining was
performed semiautomatically using a BenchMark device
(Ventana, now Hoffmann-LaRoche, Basel, Switzerland)
with a mouse monoclonal AT8 antibody raised against
hyperphosphorylated tau (Ser202/Thr205, 1:200, Invitro-
gen/Thermo Fisher, Carlsbad, CA, USA), as well as with
the mouse monoclonal isoform-specific tau antibodies RD3
(8E6/C11) and RD4 (1E1/A6), on adjacent sections of those
used for ARG. The immunostained sections were digitized
at 20 × magnification with a Mirax Midi scanner (Zeiss, Carl
Zeiss MicroImaging GmbH, Jena, Germany). For frontal
cortex (medial frontal gyrus) and globus pallidus analyses,
8–12 regions of interest (subfields) were drawn manually per
section, and the AT8-positive tau load (%) was quantified
using ZEN 3.4 blue edition software (Zeiss, Jena, Germany).
Similar to previous approaches, i.e., by Rittman etal.
[40], we aimed to subdivide the AT8-positive tau load into
different underlying cell types. Therefore, we used semiau-
tomated object characterization and recognition to differ-
entiate neurofibrillary tangles (NFTs), coiled bodies (CBs),
and tufted astrocytes (TAs) based on several parameters of
morphological characteristics. Blinding was ensured by
randomizing and renaming the digital images, effectively
eliminating any potential bias associated with the sample
origin. Single NFT, CB, and TA (n = 15–20 objects per slice)
were manually selected to define object thresholds, including
the size (area), diameter, ellipse axis, perimeter, intensity,
grade of circularity, roundness, and compactness. Specific
masks were generated for positive NFTs, CBs, and TAs and
were uniformly applied to all sections (Supplemental Fig.2).
This combination of blinding, randomization, and consistent
mask application ensured reproducibility and allowed for
the precise quantification of AT8 immunoreactivity across
the entire sample set. Due to substantial overlap of object
characteristics, we subsequently defined NFT and CB as a
combined group of AT8-positive cells with high density.
Notably, tau fragments (TFs) were partially included in the
TA channel, resulting in two analysis channels (NFT/CB and
TA/TF). This finding was substantiated by the correlation
analysis between AT8 positivity and autoradiography signals
in single subjects, which revealed similar associations of
neuron- and oligodendrocyte-enriched regions with autora-
diography signals. The final segmentation resulted in NFT/
CB AT8-area-%, TA/TF AT8-area% and intensities within
8–12 subfields per analyzed section.
For the correlation analysis between invivo PET imag-
ing data and the tau load at autopsy, composite regions of
interest in the medial frontal gyrus and in the globus pallidus
(internal and external parts) were used.
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Acta Neuropathologica (2024) 148:70 70 Page 6 of 23
Autoradiography
For direct comparison with the autoradiography signal, tau
immunostaining of formalin-fixed and paraffin-embedded
tissue blocks from 16 PSP patients and 4 PD patients and
three brain regions (frontal cortex, putamen, and pallidum)
was performed. For each patient and brain region, autoradi-
ography with [18F]PI-2620 was performed on ≥ 4 sections,
as described previously [55]. Briefly, the sections were incu-
bated for 45min (21.6μCi/ml after dilution to a volume
of 50ml with phosphate-buffered saline solution, pH 7.4,
specific activity of 480 ± 90GBq/μmol), washed, dried,
placed on imaging plates for 12h, and scanned at 25.0µm
resolution. Regions of interest were drawn on each sample
using the AT8 staining of the adjacent section, thus serving
to anatomically define subfields in the frontal cortex (gray
matter and white matter). An AT8-negative region in the
white matter was used as the reference region, and the ratios
between the subfield target regions and the reference region
were calculated. Each subfield region was labeled with a
cortical or gray matter/white matter boundary. Binding
ratios were correlated with a semiquantitative AT8 assess-
ment using Pearson’s correlation coefficient after testing for
normality and subjected to a regression analysis (neuronal
vs. astrocytic tau).
Human PET imaging andanalysis
Tau PET image acquisition andpreprocessing
[18F]PI-2620 was synthesized as previously described [47].
The injected dose ranged between 156 and 223MBq and
was applied as a slow (10s) intravenous bolus injection.
Positron emission tomography (PET) imaging was per-
formed in a fully dynamic setting (scan duration: 0–60min
postinjection) using a Siemens Biograph True point 64 PET/
CT system or a Siemens mCT system (Siemens, Erlangen,
Germany). The dynamic brain PET data were acquired in
three-dimensional list mode over 60min and reconstructed
into a 336 × 336 × 109 matrix (voxel size: 1.02 × 1.02 × 2.03
mm3) using the built-in ordered subset expectation maximi-
zation (OSEM) algorithm with 4 iterations, 21 subsets, and
a 5mm Gaussian filter on the Siemens Biograph and with
5 iterations, 24 subsets, and a 5mm Gaussian filter on the
Siemens mCT. Low-dose CT served for attenuation correc-
tion. Frame binning was standardized to 12 × 5s, 6 × 10s,
3 × 20s, 7 × 60 s, 4 × 300s, and 3 × 600 s. Image-derived
input functions were generated by manual and automated
extraction of the PET standardized uptake value (SUV) from
the carotid artery over a 60-min dynamic PET scan.
Via manual extraction, the blood activity concentration
in the bilateral carotid artery was detected in early frames
of the dynamic PET images, and spheres with a diameter of
5.0mm were placed as volumes of interest (VOIs) in the pars
cervicalis of the internal carotid artery prior to entering the
pars petrosal using PMOD version 4.2 (PMOD Technolo-
gies, Zürich, Switzerland). The activity concentration over
time was calculated from the average values of the VOI.
Tau PET quantification
Volume distribution (VT) images were calculated with the
IDIFs using Logan plots [30], which assume that the data
become linear after an equilibration time t*. t* was fitted
based on the maximum error criterion, which indicates the
maximum relative error between the linear regression and
the Logan-transformed measurements in the segment start-
ing from t*. The maximum error was set to 10%. The per-
centage of masked pixels was set to 0%. The putamen, which
was defined by manual placement of a VOI (sphere with a
diameter of 10mm), served as the tissue region.
All VT images were transformed to MNI space via
20–40min coregistration using the established [18F]PI-2620
PET template [18]. The automated brain normalization set-
tings in PMOD included nonlinear warping, 8mm input
smoothing, equal modality, 16 iterations, a frequency cutoff
of 3, regularization of 1.0, and no thresholding.
For the PET-to-autopsy correlation analysis, VT ratios
(temporal white matter reference region [10]) were obtained
in the medial frontal gyrus and in the globus pallidus as
PSP target regions (see immunohistochemistry), which were
predefined by the atlas of the basal ganglia [25], the Brain-
netome atlas [17], and the Hammers atlas [21]. The rationale
was to employ a matched quantification strategy between
PET and autoradiography.
GM/WM target region
All patients and controls used for this dedicated analysis
underwent T1-weighted structural MRI on a 3T Siemens
Magnetom PRISMA or SKYRA Scanner and [18F]PI-2620
tau PET in a fully dynamic setting (0–60min postinjection)
using pre-established standard PET scanning parameters
[46]. Our in-house [18F]PI-2620 synthesis and quality con-
trol pipeline has been described in detail previously [12,
19]. Dynamic [18F]PI-2620 tau PET images were acquired
on a Siemens Biograph True point 64 PET/CT (Siemens,
Erlangen, Germany) or a Siemens mCT scanner (Siemens,
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Acta Neuropathologica (2024) 148:70 Page 7 of 23 70
Erlangen, Germany) in 3D list mode over 60min together
with low-dose CT for attenuation correction. For dynamic
PET image acquisition, we reconstructed late-phase tau PET
images at 20–40min p.i., which were summarized into a
single frame after motion correction [9, 24, 46, 53].
All images were screened for artifacts before preprocess-
ing. T1-weighted structural MR scans were bias-corrected
and segmented into tissue types using the CAT12 toolbox
(https:// neuro- jena. github. io/ cat12- help/). PET images were
linearly coregistered to the corresponding T1 MRI data, and
the intensity was normalized using a pre-established inferior
cerebellar reference region [19]. Using T1 MRI data, surface
reconstruction was performed using the CAT12-based corti-
cal thickness pipeline. Surface reconstruction was performed
for the GM/WM boundary and then systematically shifted
to the underlying white matter, as well as to the GM/CSF
boundary. Using these systematically shifted surfaces, we
extracted PI-2620 tau PET SUVRs for 200 regions of the
cortical Schaefer atlas to systematically determine the tau
PET signal from the GM/CSF toward the GM/WM bound-
ary and below.
Statistics
GraphPad Prism (V10, GraphPad Software, US) and SPSS
(V27, IBM, US) were used for the statistical analyses.
Mouse PET/MRI
Mixed linear models (Graph Pad Prism) were used to test for
age × genotype effects on PS19 and WT mice, including tau
PET binding and MRI volumes, between 6 and 12months
of age as indices of interest. Pearson’s correlation coefficient
was calculated between brainstem tau PET binding and the
brainstem volume at all investigated time points (separately
for PS19 and WT mice). As a supporting analysis, we cor-
related tau PET binding and immunohistochemistry in the
frontal cortex (n = 4) and the hippocampus (n = 3), which are
brain regions with well-documented tau protein immunore-
activity [3] and limited spill-over from adjacent tissue, to
ensure reliable values at the single-mouse-level of individual
PS19 mice. One hippocampal section was excluded due to
limited quality of the tissue material. A sample size calcu-
lation was performed (G*Power) to determine the minimal
age of detectability of tau PET binding and MRI volume
with cohorts of n = 12 PS19 mice and n = 12 WT mice
(power = 0.8, α = 0.05; Supplemental Fig.3). No corrections
for multiple comparisons were applied in the small animal
PET experiments, as only a limited number of target regions
were selected. This approach resulted in a low Type I error
rate (α), with moderate sample sizes, thereby adhering to the
3Rs (Reduction) principles of animal welfare.
Mouse immunohistochemistry
Regional coverage of AT8 and GFAP staining was compared
between PS19 and WT mice with an unpaired Student’s t
test. The colocalization of AT8 with neurons (MAP2 +) and
astrocytes (GFAP +) was compared using an unpaired Stu-
dent’s t test.
Mouse scRadiotracing
Radiotracer uptake per neuron and astrocyte was compared
between PS19 and WT mice using an unpaired Student’s t
test. Furthermore, in PS19 and WT mice, radiotracer uptake
was compared between neurons and astrocytes. Pearson’s
correlation coefficients were calculated between the radio-
activity per cell and the tau PET signals for the combined
data from the PS19 and WT mice, as well as for the subset
of PS19 mice. For the whole-brain voxelwise correlation
analysis between cellular tracer uptake (n = 5 PS19, n = 5
WT), statistical parametric mapping (SPM) was performed
using SPM12 routines (Wellcome Department of Cogni-
tive Neurology, London, UK) implemented in MATLAB
(version 2016). Individual SUVR images were subjected
to linear regression analysis with cellular tracer uptake in
neurons or astrocytes (%ID*BW) as a vector in the pooled
cohort of PS19 and WT mice (threshold: p < 0.005 uncor-
rected, k > 20 voxels). Increases in the tau PET signals in
each of the five PS19 mice that underwent scRadiotracing
were compared with the average tau PET signal in the WT
mice. The average tau PET signal in the WT mice was con-
sidered an unspecific background signal, as the WT mice did
not show any tau accumulation in the brain. As PET signals
need to be recognized as a product of cellular tracer uptake
and cell type abundance in the brain, we used extrapolation
to estimate the total contributions of neurons and astrocytes
to increases in tau-related PET signals in PS19 mice. We
multiplied the individual cellular tracer uptake (astrocytes
and neurons) of each mouse with published cell numbers
(i.e., 71*10e6 neurons and 21*10e6 astrocytes) as a surrogate
for the cell type abundance in the brains of PS19 mice [22]
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Acta Neuropathologica (2024) 148:70 70 Page 8 of 23
We used the sum of all 5 mice for comparison instead
of single mice to minimize confounding factors caused by,
e.g., distinct cell type abundances in the brains of individual
mice compared with those reported in the literature or the
methodological variance of scRadiotracing. A paired t test
was used to compare PET radioactivity and the extrapolated
radioactivity of single cells in the cohort of five PS19 mice.
Human PET‑to‑autopsy correlation
Partial correlation coefficients were calculated for the mul-
timodal correlation between tau abundance via immunohis-
tochemistry, autoradiography ratios, and tau PET signals,
accounting the globus pallidus and frontal cortex as cofac-
tors across samples.
Human autoradiography
Neuronal and astroglial tau abundances were compared with
paired t tests. The Kolmogorov‒Smirnov test confirmed the
normality of the residuals. Neuronal and astroglial tau abun-
dances in subfields of the frontal cortex were correlated with
autoradiography binding ratios in corresponding regions
(total n = 129; Supplemental Fig.4). Additionally, a linear
regression analysis was performed with neuronal and astro-
glial tau abundances as predictors and autoradiography bind-
ing ratios as the outcome variable. At the individual level,
the correlation between neuronal and astroglial tau abun-
dances and autoradiography binding ratios was determined
in 8–12 subfields per subject. These individual correlations
were analyzed as a function of overall tau abundance (sepa-
rately for neurons and astroglia). In basal ganglia regions,
the AT8 signal intensity and AT8 occupancy were correlated
with autoradiography binding ratios.
Human PET target region
Differences in the SUVRs of n = 5 different layers (GM/
CSF boundary, GM toward CSF, GM toward WM, GM/WM
boundary, and below the GM/WM boundary) were com-
pared using a repeated-measures ANOVA, accounting for
within-subject variability. Post hoc pairwise comparisons
were performed using Tukey-adjusted estimated marginal
means to identify specific differences between layers.
71
∗10e6∗

Bq
neuron Mouse#1 +Bq
neuron Mouse#2 +Bq
neuron Mouse#3 +Bq
neuron Mouse#4 +Bq
neuron Mouse#5

+
21∗10e6∗Bq
astrocyte Mouse#1 +Bq
astrocyte Mouse#2 +Bq
astrocyte Mouse#3 +Bq
astrocyte Mouse#4 +Bq
astrocyte Mouse#5

=
Bq
tau - PET
Mouse#1 −AVG WT

+Bq
tau - PET
Mouse#2 −AVG WT

…+Bq
tau - PET
Mouse#5 −AVG WT

.
Results
[18F]PI‑2620 tau PET monitoring reveals
age‑dependent increases intracer binding
inAT8‑positive brain regions inthePS19 4‑repeat
tau mouse model
First, we investigated whether [18F]PI-2620 tau PET has suf-
ficient sensitivity to detect an invivo tracer signal in PS19
mice, which accumulate 4R-tau pathology, compared with
that in wild-type (WT) mice (Fig.1a). Longitudinal tau PET
scans from 6 to 12months of age revealed an increasing PET
signal and a significant genotype × age interaction effect on
the entorhinal cortex (F(3,40) = 6.33, p = 0.0013) and brain-
stem (F(3,40) = 9.09, p = 0.0001) of PS19 mice compared
with those of WT mice (Fig.1b–d). The cerebellum did not
qualify as a suitable target region in mice because of the
strong spill-over of the adjacent skull relative to the brain
(Fig.1b). Compared with WT mice, late-stage PS19 mice
presented strongly elevated [18F]PI-2620 tau PET signals in
the entorhinal cortex (+ 19%, Cohen’s d = 3.26, p = 0.0003)
and brainstem (+ 21%, Cohen’s d = 2.47, p = 0.0009). Power
calculations with standardized sample sizes of n = 12 mice
per genotype indicated an age of 9.7months for the earli-
est detection of signal alterations in cohorts of PS19 mice
compared with WT mice at a predefined power of 0.8 (Sup-
plemental Fig.3). Individual PET images of PS19 and
WT mice at 12months of age are shown in Supplemental
Fig.5. Regional AT8 staining correlated with regional tau
PET signal enhancement at the final time point (R = 0.921,
p = 0.0032; Supplemental Fig.6). The volumetric 3T MRI
analysis revealed a decrease in the hindbrain volume of late-
stage PS19 mice compared with WT mice (−7%, Cohen’s
d = 1.98, p = 0.0062) and a weaker genotype × age interac-
tion effect (F(3,59) = 3.93, p = 0.013) than tau PET (Fig.1e,
f). The earliest detection of differences in hindbrain vol-
ume was estimated at 11.7months of age (Supplemental
Fig.3). PS19 mice with high tau PET signals in the brain-
stem were characterized by a substantial volume loss in the
brainstem, whereas this association was not present in WT
mice (Fig.1g).
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Acta Neuropathologica (2024) 148:70 Page 9 of 23 70
Fig. 1 Monitoring of tau
pathology and atrophy in PS19
and wild-type mice using [18F]
PI-2620 PET/MRI. a Experi-
mental workflow of serial PET/
MRI imaging sessions and
terminal immunohistochemistry
(IHC) and single-cell Radiotrac-
ing (scRT) in PS19 and wild-
type (WT) mice. b Coronal
and axial group average [18F]
PI-2620 PET images obtained
using an MRI template show
the monitoring of radiotracer
binding (volume of distribution
ratios, VT; striatal reference),
with pronounced temporal and
brainstem patterns in aged PS19
mice (n = 8–10) compared with
WT mice (n = 8–10). c, d Mixed
linear models of entorhinal and
brainstem [18F]PI-2620 PET
signals indicate a significant
age × genotype effect and ele-
vated tau PET signals in PS19
mice compared with WT mice
at 12months of age. e Examples
of serial MRI atrophy patterns
in an individual PS19 mouse
compared with a WT mouse.
Coronal slices are shown with
indications of the cerebellum
(CBL) and brainstem (BST)
regions. The orange arrows
highlight atrophy in PS19
mice. f Mixed linear model of
hindbrain volume indicating
a significant age × genotype
effect and a decreased hindbrain
volume in PS19 mice compared
with WT mice at 12months of
age. g Association between tau
PET signals and brain volume
in the brainstem of PS19 and
WT mice across all investigated
time points showing greater
atrophy in the presence of high
tau PET signals, specifically in
PS19 mice
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Acta Neuropathologica (2024) 148:70 70 Page 10 of 23
Immunohistochemistry shows thedominance
ofneuronal tau overastrocytic tau inPS19 mice
Next, we assessed the detailed regional sources of tau pathol-
ogy in the brains of PS19 mice using immunohistochemis-
try. Consistent with previous work, a greater abundance of
AT8-positive tau pathology was observed in the hippocam-
pus (+ 20.1%, p = 0.0004), cortex (+ 7.0%, p = 0.0025) and
brainstem (+ 5.0%, p = 0.0321) of PS19 mice than in those
of age-matched WT mice at 12months (Fig.2a, b) [57]. In
contrast, the cerebellum showed no significant increase in
the AT8-positive area (1.3%, p = 0.552). Similarly, stronger
GFAP reactivity, a surrogate for reactive gliosis, was
observed in the frontal cortex (+ 9.7%, p = 0.025) and the
hippocampus (+ 9.2%, p = 0.050; Fig.2a, c) of PS19 mice
than in those of WT mice [41].
The colabeling of AT8 with GFAP to indicate astro-
glia and MAP2 to mark neuronal soma, including
Fig. 2 Immunohistochemical assessments of tau pathology, reac-
tive astrocytes, and neurons in PS19 mice. a Overview of sections
from PS19 mice showing pTau (AT8, red), astrocytes (GFAP, pur-
ple), and neurons (MAP2, green), as well as merged images of the
cortex (CTX, motor cortex, and somatosensory cortex), hippocampus
(HPC), cerebellum (CBL), and brainstem (BS). Scale bar = 100µm. b
Quantitative comparison of AT8 occupancy in target regions between
wild-type (WT) and PS19 mice, as well as a comparison of PS19
AT8 occupancy across target regions. c Quantitative comparison
of GFAP occupancy in target regions between wild-type (WT) and
PS19 mice, as well as a comparison of PS19 GFAP occupancy across
target regions. d High-magnification images of sections from PS19
mice showing pTau (AT8, red), astrocytes (GFAP, purple), and neu-
rons (MAP2, green), as well as merged images of the cortex (CTX),
hippocampus (HPC), cerebellum (CBL), and brainstem (BS). Scale
bar = 20 µm. e Quantitative comparison of AT8 occupancy between
neurons (MAP2-positive) and astrocytes (GFAP-positive) in target
regions of PS19 mice. CTX cortex, HIP hippocampus, PFC prefrontal
cortex, BS brainstem, CBL cerebellum
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Acta Neuropathologica (2024) 148:70 Page 11 of 23 70
Fig. 3 Cell sorting after radi-
otracer injection identifies neu-
rons as the predominant origin
of [18F]PI-2620 tau PET signals.
a Experimental workflow of
PET/MRI with subsequent cell
sorting of neurons and astro-
cytes prior to the determination
of radioactivity per isolated cell
via gamma emission measure-
ments and flow cytometry. b, c
Comparison of radioactivity per
isolated neuron and astrocyte
between PS19 (n = 5) and wild-
type (WT, n = 5) mice. Each bar
represents an individual animal.
d Sagittal sections obtained
via an MRI template showing
z score images (vs. WT) of all
investigated PS19 mice (n = 5).
Each image represents an indi-
vidual animal. e, f Quantitative
correlation between brainstem
tau PET signals and radio-
activity per single neuron or
astrocyte. Pearson’s correlation
coefficients are provided for
the combined data from PS19
and WT mice (regression line
with 95% confidence interval),
as well as for the subset of
PS19 mice. g, h Data-driven
voxelwise correlation between
radioactivity per single neuron
or astrocyte and [18F]PI-2620
tau PET images using statisti-
cal parametric mapping of
the combined sample of PS19
and WT mice. Radiotracer
uptake per neuron correlated
with the distribution pattern of
tau pathology in PS19 mice,
whereas radiotracer uptake per
astrocyte did not correlate with
tau PET patterns. i, j Cell count
and purity of isolated cells (neu-
rons and astrocytes) as bench-
mark indices of the cell sorting
procedure. k The increase in
PET radioactivity in PS19 mice
(n = 5) compared with that in
WT mice matches the increase
in radioactivity determined by
the number of isolated cells.
The radioactivity per single
cell was extrapolated from the
established cell numbers in the
mouse brain (71 × 10e6 neurons,
21 × 10e6 astrocytes)
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Acta Neuropathologica (2024) 148:70 70 Page 12 of 23
somatodendritic structures, revealed that tau aggregation
predominantly occurred in neurons (somata and putatively
postsynaptic compartments), with a significantly lower level
observed in astrocytes (2–18-fold, all target regions p < 0.05;
Fig.2e). Collectively, these data reflect signals obtained
from PS19 mice subjected to tau PET imaging and depict
the predominant neuronal origin of tau pathology.
Increased neuronal [18F]PI‑2620 uptake inlate‑stage
PS19 mice translates toaninvivo PET signal
We performed scRadiotracing in a subset of five transgenic
and five WT mice immediately after the final tau PET ses-
sion to determine the cellular source of [18F]PI-2620 binding
in PS19 mice (Fig.3a). Neurons and astrocytes were isolated
using MACS, and radioactivity was measured in enriched
cell pellets. Strikingly, we observed a 1.89-fold higher [18F]
PI-2620 uptake per single neuron in PS19 mice than in the
single neurons of WT mice (p = 0.028; Fig. 3b). In con-
trast, [18F]PI-2620 uptake per single astrocyte did not differ
between PS19 and WT mice (p = 0.439; Fig.3c). In PS19
mice, neuronal tracer uptake was 27-fold higher than that in
astrocytes (p = 0.023), whereas in WT mice, [18F]PI-2620
uptake by neurons was higher than that by astrocytes (five-
fold, p = 0.009). Individual tau PET z score maps of PS19
mice matched the magnitude of single-cell [18F]PI-2620
uptake in neurons (Fig.3d). Furthermore, late static tau PET
quantification in a predefined hindbrain region was corre-
lated with individual neuronal tracer uptake in the whole
sample (R = 0.727, p = 0.017) and in PS19 mice (R = 0.919,
p = 0.027; Fig.3e), whereas no significant associations were
observed between tau PET signals and individual astrocytic
tracer uptake (Fig.3f). We correlated individual neuronal
and astrocytic tracer uptake with voxelwise tau PET signals
using SPM to increase regional flexibility. Neuronal [18F]
PI-2620 uptake was correlated with regional PET signals
in the brainstem, midbrain, and entorhinal cortex (Fig.3g),
whereas astrocytic [18F]PI-2620 uptake was not significantly
correlated with regional tau PET signals (Fig.3h). Flow
cytometry confirmed the sufficient yield (Fig.3i) and purity
(Fig.3j) of neurons and astrocytes. Thus, we questioned
whether the magnitude of cell-specific tracer uptake in indi-
vidual PS19 animals corresponds to the alterations observed
in PET signals. Considering 71*10e6 neurons and 21*10e6
astrocytes in the rodent brain, we found that cellular radio-
activity (7.7–36.5kBq per animal) explained the specific
increase in the tau PET signal (16.4–37.2kBq per animal;
p = 0.880), which also closely matched the summations of
cellular and PET-related radioactivity measures across the
five PS19 mice studied (Fig.3k).
[18F]PI‑2620 tau PET signals correlate strongly
withregional tau abundance indeceased patients
withPSP anddisease controls
Next, we examined whether invivo signals of the tau PET
tracer [18F]PI-2620 are determined by tau neuropathology.
To this end, we investigated a small cohort of nine patients
who underwent [18F]PI-2620 PET invivo, with subsequent
donation of their brains for autopsy. Seven patients were
classified as having definite PSP, and two patients were
classified as having TAR DNA-binding protein 43 (TDP-
43)-positive frontotemporal lobar degeneration (FTLD-
TDP): one with FTLD/MND-TDP and one with FTLD-
TDP related to a TANK-binding kinase 1 (TBK1) mutation
(Supplemental Table1). The globus pallidus showed greater
visual and quantitative AT8 occupancy than did the medial
frontal gyrus in patients with definite PSP, which was well
reflected by the corresponding autoradiography signals
(Fig.4a, b). Tau PET, autoradiography, and AT8 immu-
nohistochemistry indicated higher signals or occupancy in
patients with definite PSP than in disease controls (Fig.4a,
b). Notably, the TBK1 mutation carrier presented mild AT8-
positive tau copathology in the globus pallidus and in the
putamen and moderate AT8-Co-pathology in the nucleus
basalis of Meynert at autopsy, which explained the moder-
ate increase in the [18F]PI-2620 PET signal in these regions.
Across modalities, a strong association was observed
between quantitative AT8 occupancy and autoradiography
ratios (R = 0.878, p < 0.001), even when challenged by con-
sideration of both target regions as cofactors across all sam-
ples (Fig.4c). Furthermore, the quantitative AT8 occupancy
(R = 0.584, p = 0.014) and autoradiography ratios (R = 0.556,
p = 0.021) were consistent with the tau PET signals acquired
5–63months before death invivo (Fig.4c).
In vitro autoradiography confirms tau‑positive
neurons andoligodendrocytes asthemajor sources
oftau tracer binding intissues frompatients
withPSP
Next, we translated our murine cell type findings to human
tau PET imaging and examined the detailed sources of
tau PET signals. A correlation analysis between the area
of AT8-positive neurons/oligodendrocytes (NFT/CB) and
the area of AT8-positive astrocytes (TA, including TF) with
[18F]PI-2620 autoradiography signals was performed using
autopsy tissues derived from 16 patients with PSP (Sup-
plemental Table2). This PSP sample was selected based on
absence of α-synuclein, TDP-43 or FUS copathology and
limited β-amyloid copathology to minimize confounding
factors, as assessed in the frontal cortex.
The frontal cortex was used as the primary brain region
of interest due to the low probability of off-target sources
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Acta Neuropathologica (2024) 148:70 Page 13 of 23 70
[29]. Here, we found substantial visual agreement between
AT8 immunohistochemistry and [18F]PI-2620 autoradi-
ography signals in FFPE sections of patients with defi-
nite PSP (Fig.5a). We tested the differential associations
of neuronal/oligodendroglial (NFT/CB) and astrocytic
(TA, including TF) tau abundances, as determined by AT8
immunohistochemistry (Fig.5b), with [18F]PI-2620 autora-
diography quantification in 129 predefined subfields of the
gray matter and white matter (drawn on autoradiography
sections by investigators blinded to the corresponding AT8
sections; Supplemental Fig.4). NFT/CB tau abundance in
PSP samples correlated more strongly with autoradiography
Fig. 4 Correlations of in vivo PET signals with tau abundance and
autoradiography signals in autopsy samples. a Basal ganglia AT8
immunohistochemistry together with [18F]PI-2620 autoradiogra-
phy of adjacent sections and axial [18F]PI-2620 tau PET signals in
basal ganglia sections prior to death. Images are shown for all seven
investigated patients with definite PSP and two patients with TAR
DNA-binding protein 43 (TDP-43)-positive frontotemporal lobar
degeneration (FTLD-TDP): one with FTLD/MND-TDP and one with
FTLD-TDP related to a TANK-binding kinase 1 (TBK1) mutation. b
Frontal medial gyrus AT8 immunohistochemistry together with [18F]
PI-2620 autoradiography of adjacent sections and axial [18F]PI-2620
tau PET signals in cortical sections prior to death. Images are dis-
played for seven patients with definite PSP and two disease controls,
as indicated in (A). c Multimodal quantitative partial correlation
between tau abundance, autoradiography signals and tau PET signals.
Linear regression lines (including 95% confidence intervals) were
calculated, taking into account the globus pallidus and frontal medial
gyrus as cofactors, in samples derived from seven patients with def-
inite PSP, one patient with FTLD/MND-TDP, and one patient with
FTLD related to a TBK1 mutation. R indicates Pearson’s correlation
coefficient. %N/Area-% = AT8 occupancy of neurofibrillary tangles
and coiled bodies
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Acta Neuropathologica (2024) 148:70 70 Page 14 of 23
signals (R = 0.487, p < 0.0001; Fig.5c) than did TA/TF tau
abundance (R = 0.280, p = 0.0013; Fig. 5d). A regression
analysis with NFT/CB and TA/TF tau abundances as predic-
tors revealed that only NFT/CB tau (β = 0.455, p < 0.0001)
but not TA/TF tau (β = 0.068, p = 0.442) explained the [18F]
PI-2620 autoradiography signal. We noticed that subfield-
specific tau abundance in individual samples from patients
with PSP was strongly correlated with autoradiography
signals above only 0.2% of the mean occupied area of tau-
positive NFT/CB (R = 0.623, p = 0.017; Fig.5e), indicat-
ing the sensitivity threshold for translation into measurable
signals. In contrast, individual samples from patients with
PSP presenting high mean occupied areas of tau-positive
TA/TF did not show strong individual subfield correlations
Fig. 5 Cell type-specific
immunohistochemistry-to-auto-
radiography correlation in the
frontal medial gyrus of tissue
samples from patients with PSP.
a AT8 immunohistochemistry
together with [18F]PI-2620 auto-
radiography of adjacent frontal
medial gyrus sections from two
exemplary patients with definite
PSP. ARG = autoradiography.
WM = white matter. b Compari-
son of neuronal/oligodendro-
glial (NFT/CB) and astrocytic
(TA, including TF) AT8
occupancy in frontal medial
gyrus sections from patients
with definite PSP (n = 14). c, d
Quantitative analysis of the cor-
relation between tau abundance
in the NFT/CB and TA/TF with
autoradiography signals in the
frontal medial gyrus subfields
(including gray matter and
white matter regions). Regres-
sion lines (including 95% confi-
dence intervals) were calculated
for 129 subfields derived from
n = 14 patients with definite
PSP after confirming the
normality of the residuals. R
indicates Pearson’s correlation
coefficient. e, f Dependency of
individual subfield correlation
coefficients (AT8 × autoradi-
ography) from the mean AT8
occupancy of all subfields per
patient as determined for NFT/
CB and TA/TF. Regression
lines (including 95% confidence
intervals) were calculated for 14
patients with definite PSP with
normally distributed data. R
indicates Pearson’s correlation
coefficient
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Acta Neuropathologica (2024) 148:70 Page 15 of 23 70
Fig. 6 Cell- and substructure-
specific immunohistochemistry-
to-autoradiography correlations
in the basal ganglia of tissue
samples from patients with PSP.
a AT8 immunohistochemistry
together with [18F]PI-2620
autoradiography of the adjacent
basal ganglia section from one
exemplary patient with definite
PSP. b Comparison of neuronal
and oligodendroglial (NFT/CB)
versus astrocytic (TA, includ-
ing TF) AT8 occupancy in the
globus pallidus of patients with
definite PSP (n = 8). c Quantita-
tive analysis of the correlation
between NFT/CB tau abun-
dance and autoradiography
signals in the basal ganglia sub-
fields. A regression line (includ-
ing 95% confidence intervals)
was calculated for 73 subfields
derived from n = 8 patients with
definite PSP. R indicates Pear-
son’s correlation coefficient.
d Quantitative analysis of the
correlation between TA/TF tau
abundance and autoradiography
signals in the basal ganglia sub-
fields. A regression line (includ-
ing 95% confidence intervals)
was calculated for 73 subfields
derived from n = 8 patients with
definite PSP. R indicates Pear-
son’s correlation coefficient. e–g
Quantitative analysis and visual
correlation between AT8 inten-
sity and AT8 occupancy with
autoradiography signals in an
individual sample from a patient
with PSP. The small images in
(E) show high-magnification
images of faint AT8 intensity in
white matter fibers and strong
AT8 intensity in large neu-
rons (NFTs). Note the strong
autoradiography signal, which
is discernible as single spots
in the same area. Regression
lines (including 95% confidence
intervals) were calculated for
n = 8 subfields of one patient
with definite PSP. R indicates
Pearson’s correlation coefficient
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Acta Neuropathologica (2024) 148:70 70 Page 16 of 23
(Fig.5f), again suggesting the limited translation of TA/TF
tau abundance to autoradiography and PET signals.
Despite substantial visual agreement in most samples
from patients with PSP (Fig.6a) and the presence of pre-
dominant TA/TF tau aggregation compared with sparse
NFT/CB tau aggregation (Fig.6b), only NFT/CB tau occu-
pancy showed a substantial correlation with [18F]PI-2620
autoradiography signals in 73 subfields of the globus palli-
dus (Fig.6c, R = 0.467, p < 0.0001). In contrast, the quantita-
tive agreement between the TA/TF tau occupancy and [18F]
PI-2620 autoradiography signals reached only borderline
significance (Fig.6d, R = 0.231, p = 0.0498). A reg ression
model including NFT/CB AT8 occupancy and TA/TF AT8
occupancy as predictors provided a significant explanation
of autoradiography signals only by NFT/CB tau (β = 0.676,
p < 0.0001) but not by TA/TF tau (β = −0.278, p = 0.081).
Compared with the frontal cortex, AT8-positive areas in the
basal ganglia were characterized by greater heterogeneity
in AT8 staining intensity, including a high abundance of
AT8-positive axons and occupancy of large neurons with
high AT8 intensity in individual patients (see examples in
Fig.6e–g). Notably, large AT8-positive neurons (NFTs)
were visually discernible in the [18F]PI-2620 autoradiog-
raphy images (Fig.6e). We investigated the impact of the
AT8 density on the resulting autoradiography signal and
observed a strong association between the AT8 lesion
density and autoradiography signals in individual patients
(R = 0.800, p = 0.017; Fig.6f), whereas the AT8-occupied
area was not a significant predictor of the autoradiography
signal in these patients (Fig.6g). Notably, some samples
from patients with PSP presented a visually detectable [18F]
PI-2620 autoradiography signal in the putamen, although
AT8 occupancy was low, resulting in higher yet unexplained
background [18F]PI-2620 signals in the putamen of healthy
controls than in cortical areas [12]. We further performed tau
isoform-specific staining using RD3 and RD4 antibodies and
visually compared these results to AT8 staining. RD3 occu-
pancy was barely detectable across all cases for both regions
examined. In some frontal cortex sections, RD4 occupancy
was also limited, leading to a nearly equal proportion of
RD3 occupancy. Nevertheless, all the subjects exhibited
a predominance of RD4-positive tau pathology compared
with RD3-positive pathology in the frontal cortex, and RD4-
positive tau pathology was even more pronounced in the
basal ganglia (Supplemental Figs.7 and 8). Importantly,
significant tau accumulation was not detected in the frontal
cortex or basal ganglia of the four deceased PD patients, as
assessed by AT8 immunostaining and [18F]PI-2620 autora-
diography. Additionally, only minor off-target binding was
observed across PD patients (Supplemental Fig.9).
High oligodendroglial density attheboundary
ofgray andwhite matter indicates animproved
cortical target region fortau PET inpatients
withPSP
Finally, we exploited the cellular and regional findings of
our study to further improve the use of tau PET for the diag-
nosis of 4R-tauopathies. Pronounced regional autoradiogra-
phy signals were observed in white matter areas adjacent to
the GM/WM boundary (Fig.7a). Consistent with previous
reports [15, 16], these areas were characterized by distinctly
higher NFT/CB-to-TA/TF ratios than cortical gray matter
regions (fourfold, p < 0.0001; Fig.7c). We assessed the rel-
evance of this observation invivo by analyzing seventeen
[18F]PI-2620 tau PET scans of patients with PSP-RS and a
high likelihood of underlying 4R-tauopathy and nine healthy
controls with an MRI-based layer segmentation of gray mat-
ter and WM/GM boundary areas of the frontal cortex (Sup-
plemental Fig.10). Here, we found a greater effect size for
the comparison of tau PET signals in the frontal cortex of
patients with 4R-tauopathies and controls using the GM/
WM boundary target region (Cohen’s d = 1.68) in contrast
to the common gray matter target region (Cohen’s d = 1.37).
Thus, focusing on oligodendroglia-rich regions with high
AT8 positivity enhanced the assessment and diagnostic
accuracy of cortical tau burden by [18F]PI-2620 tau PET in
patients with 4R-tauopathies.
Discussion
In this translational study, we used a large spectrum of meth-
odological approaches, including innovative scRadiotrac-
ing and a cell-type-specific correlation of autoradiography
signals, to disentangle the discrepant findings of previous
reports that investigated second-generation tau PET in
4R-tauopathies. As a major achievement, we detected ele-
vated radiotracer binding in isolated neurons after invivo
injection in mice. Furthermore, our data indicate that tau
PET signals in individuals with 4R-tauopathies are driven
by dense neuronal and oligodendroglial tau aggregation,
whereas faint tau-positive structures of astrocytes and tau
fragments are not capable of translating radiotracer bind-
ing into invivo signals. Finally, we provide the first [18F]
PI-2620 PET-to-autopsy correlation and show that corti-
cal tau PET signals deserve optimized target regions at the
boundary between gray and white matter.
The overarching research question of this work addressed
the validity of second-generation tau PET signals in indi-
viduals with 4R-tauopathies. A recent blocking study
revealed that [3H]PI-2620, but not [3H]MK-6240 or [3H]
RO-948, exhibited high specific binding in the frontal cortex
of deceased patients with PSP and CBD [32]. In contrast,
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Acta Neuropathologica (2024) 148:70 Page 17 of 23 70
Fig. 7 High oligodendroglial
tau abundance at the GM/WM
boundary facilitates the defini-
tion of an optimized frontal
lobe target region in patients
with PSP. a, b AT8 immuno-
histochemistry together with
[18F]PI-2620 autoradiography
of the adjacent frontal medial
gyrus section from an exem-
plary patient with definite PSP.
High-magnification images
show high oligodendroglial
tau levels in the boundary of
gray matter and white mat-
ter, whereas cortical layers are
characterized by low neuronal/
oligodendroglial (NFT/CB) tau
levels but abundant astrocytic
(TA) tau inclusions. c Quantita-
tive comparison of the NFT/
CB-to-TA/TF ratios of tau occu-
pancy in gray matter and the
boundaries of gray matter and
white matter. Data were derived
from NFT/CB and TA/TF AT8
occupancy in the frontal medial
gyrus subfields of patients
with definite PSP (n = 14). d
Schematic illustration of the
PET SUVR assessment from
the GM/WM boundary to the
GM/CSF boundary. Surface
renderings illustrate standard-
ized group differences (Cohen’s
d) between 17 PSP-RS patients
and 9 healthy controls for the
200 regions of the Schaefer
cortical atlas. Group differences
are shown across 5 MRI-based
cortical surface reconstruc-
tions applied to the PET data,
systematically shifted from
the GM/CSF boundary toward
the GM/WM boundary and
below. e Boxplots showing the
corresponding PET SUVRs in
the 17 PSP-RS patients; using
repeated-measures ANOVA,
followed by post hoc pairwise
comparisons with Tukey's test
for multiple comparisons
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Acta Neuropathologica (2024) 148:70 70 Page 18 of 23
another recent autoradiography head-to-head comparison
did not detect a significant extent of [18F]AV-1451, [18F]
MK-6240, or [18F]PI-2620 binding to non-AD tauopathies
[1]. Such discrepancies were previously reported for [18F]
AV-1451, which presented positive [31] and negative [33]
autoradiography signals in brain sections from individuals
with 4R-tauopathy. However, in addition, invitro satura-
tion assays and competitive binding assays [52], as well as
molecular docking [28], have provided additional evidence
that PI-2620 binds to 4R-tau. Therefore, we performed a bat-
tery of experiments to test the translation of PI-2620 binding
to invivo PET signals.
First, we showed that second-generation tau PET with
[18F]PI-2620, a radiotracer that has affinity for 3- and
4-repeat tau, has sufficient sensitivity to detect the accumu-
lation of tau pathology in transgenic PS19 mice. Tau PET
indicated earlier sensitivity for pathological alterations than
3T structural MRI-based atrophy measures did, but we
note that both modalities could still be improved in terms
of resolution, i.e., the availability of ultrahigh-field MRI.
We acknowledge that PET signal spill-over from adjacent
intra- and extracerebral structures may have influenced our
findings [34, 35]. Both WT and PS19 mice were analyzed
using the same standardized approach to mitigate this spill-
over [38]. Additionally, we selected a tau-negative refer-
ence region in the central striatum and target regions in the
entorhinal cortex and brainstem, positioned at a sufficient
distance from the edges of the PET images. In terms of pre-
clinical tau PET imaging, [18F]PM-PBB3 also showed ele-
vated tau PET signals in the rTg4510 mouse model, which
suggests that invivo monitoring of 4-repeat tau pathology
in tau models is feasible with next-generation tau radiotrac-
ers [49]. From a biomechanical perspective, high individual
tau PET levels were associated with greater atrophy in our
cohort of PS19 mice, which highlights the link between tau
and neurodegeneration. Furthermore, this finding shows
that [18F]PI-2620 tau PET signals in PS19 mice may still
be underestimated, since an individual MRI-based partial
volume effect correction has yet to be established in mice.
Nevertheless, while the PS19 model is based on a muta-
tion linked to FTD, it remains relevant for studying certain
aspects of 4R-tauopathies, as both patients with PSP and
PS19 mice exhibit hyperphosphorylated 4R-tau leading to
neurodegeneration [3]. However, the PS19 model primar-
ily reflects neuronal tau pathology, lacking the strong glial
involvement observed in patients with PSP. Alternative mod-
els, such as seed-based approaches [4], the use of tau fibrils
from PSP patients [14, 43], or AAV-mediated tau aggrega-
tion [50], can be used to address this discrepancy, because
they provide a more accurate representation by inducing tau
pathology in both neurons and glial cells, thereby better rep-
licating the complexity of PSP [36].
One major goal of our investigation was to determine
whether tau PET signals are derived from tau-positive
cells. In this context, earlier tau PET radiotracers such as
[18F]THK5117 and [18F]AV1451 also presented increased
signals in P301S or BiGT mice [13], but due to the iden-
tified off-target binding to monoamine oxidases [37], the
observed increased signals could also be derived from acti-
vated immune cells, i.e., reactive astrocytes. As a major
novel approach, we applied cell sorting after invivo tracer
injection [7, 8, 56] to a tau radiotracer. Here, we found that
(i) tau tracer binding was much higher in neurons than in
astrocytes, (ii) neurons from PS19 mice had nearly twofold
higher tracer uptake than neurons from wild-type mice,
and (iii) single-cell tracer uptake was used to determine
the invivo tau PET signal. Thus, scRadiotracing directly
links cellular binding to translation toward an invivo tau
PET signal. Notably, our data cannot prove the occurrence
of intraneuronal binding to 4R-tau, but we deem neuronal
off-target sources less likely than immune cells [37], ves-
sels, iron-associated regions, calcifications in the choroid
plexus, or leptomeningeal melanin [31]. Interestingly, we
also observed greater tracer uptake by neurons than astro-
cytes in wild-type mice, which could indicate larger cell
body volumes of neurons that subsequently contain higher
levels of tau under physiological conditions than astrocytes
do [54]. scRadiotracing data from PS19 mice were consist-
ent with the results of immunohistochemistry, which also
revealed neurons as the major tau-positive cell type. Due
to the decay of radioactivity over time and the lengthy pro-
cedure (6–7h), we established that valid results required
signal-to-noise ratios above 2.0. Using the tau tracer [18F]
PI-2620 and the protocol outlined, we estimate the lower
detection limit for the tracer to be approximately 1–2 × 104
astrocytes, whereas the samples analyzed in this study were
consistently > 105. Additionally, astrocyte tracer uptake was
measured prior to neuronal uptake, thereby ruling out any
sensitivity issues for astrocyte detection. As a result, despite
higher tracer uptake in neurons, the radioactivity measure-
ment remained sufficient, even for lower numbers of isolated
neurons compared to astrocytes. As a limitation, our meth-
odology did not have sufficient sensitivity to analyze tau
tracer uptake in cells other than neurons and astrocytes (i.e.,
vascular cells and oligodendrocytes). Future work could
optimize the sensitivity of scRadiotracing and directly cor-
relate cellular radiotracer binding with the cellular amount
of the tau protein [7].
Our study included the first sample of deceased patients
with 4R-tauopathies and disease controls, which allowed us
to establish a PET-to-autopsy correlation between invivo
[18F]PI-2620 signals and the quantitative tau load exvivo.
The variable time intervals between PET imaging and death
need to be considered a limitation, since the tau load could
still change after PET imaging. Longitudinal tau PET scans
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Acta Neuropathologica (2024) 148:70 Page 19 of 23 70
in PSP patients could overcome this challenge and provide
critical insights into the progression of invivo tau pathol-
ogy and may help predict the disease trajectory in individ-
ual patients. Nevertheless, we obtained a strong correlation
between invivo PET signals and AT8 occupancy in the fron-
tal cortex and the basal ganglia in our cohort consisting of
seven patients with PSP and two disease controls. Invivo
tau PET signals in patients without evidence of significant
tau pathology exvivo matched the signal levels reported for
healthy individuals and disease controls [12]. Notably, one
patient with definite PSP at autopsy was diagnosed with non-
fluent primary progressive aphasia 3.2years before death,
and one patient with definite PSP at autopsy was diagnosed
with behavioral variant frontotemporal dementia 2.5years
before death. However, both also showed a PSP-like [18F]
PI-2620 PET signal in the basal ganglia at the time of their
diagnostic workup, which highlights the diagnostic value of
PET imaging when 4R-tauopathies are a possible differen-
tial diagnosis. Furthermore, [18F]PI-2620 PET also reliably
captured AT8-positive tau (co)pathology of the globus pal-
lidus in the included TBK1 carrier. Synucleinopathies, such
as PD and Lewy body dementia (DLB) [5], are among the
most common differential diagnoses for PSP [23]. Consist-
ent with the recent literature reporting an absence of post-
mortem tau tracer binding in Lewy body-containing tissues,
our postmortem analysis similarly revealed no significant
AT8 occupancy or [18F]PI-2620 autoradiography signal in
the frontal cortex and basal ganglia of the four PD patients
examined [1, 2]. In addition to previously identified sources
of off-target binding, these findings highlight the poten-
tial of [18F]PI-2620 in differentiating 4R-tauopathies from
α-synucleinopathies. Specifically, the results confirmed the
absence of relevant off-target binding to α-synuclein-related
pathology. Nevertheless, we note that a limited degree of off-
target/unspecific binding in the basal ganglia, as indicated
by [18F]PI-2620 autoradiography, should still be considered
for image interpretation. In particular, regions exhibiting
elevated invivo binding of [18F]PI-2620 in PSP correspond
to off-target areas previously identified with other tau ligands
in healthy and disease controls [29].
We determined the contributions of neuronal, oligoden-
droglial and astrocytic tau to human autoradiography signals
using a dataset of patients with PSP presenting with very
limited copathology to overcome the limitations of mixed
pathology and variable intervals between PET and autopsy.
Previously, we reported greater agreement between postmor-
tem neuronal tau covariance and tau PET covariance than
between astrocytic and oligodendroglial tau covariance in
the same samples from patients with PSP [19]. Building
upon these results, we observed greater agreement between
the neuronal/oligodendroglial tau abundance and autora-
diography signals than the astrocytic tau abundance in the
frontal cortex. The most likely explanation for this finding
was provided by a similar analysis of the basal ganglia. Here,
regions with neighboring large dense neurons even resulted
in focal autoradiography signals, whereas astrocyte- or axon-
dominated regions with a lower density of AT8 revealed
only lower increases in the signal.
Similar effects were observed for oligodendroglia with a
higher AT8 density at the GM/WM boundary than for cor-
tical astrocytes with a lower AT8 density. Thus, the faint
processes of astrocytes and axon bundles likely suffer from
partial volume effects within the tissue compartment, which
hampers translation into a measurable tau radiotracer signal
invivo.
This finding aligns with our tau isoform-specific stain-
ing using RD3 and RD4 antibodies in the frontal cortex and
basal ganglia. Consistently higher proportions of RD4 stain-
ing were observed in the frontal cortex and were even more
pronounced in the basal ganglia of PSP patients, where RD4
occupancy accounted for the vast majority of the tau load.
In particular, in cortical sections, we noticed pronounced
autoradiography signals at the GM/WM boundary, and we
were able to correlate these findings with high proportions
of AT8-positive oligodendroglia in this particular region.
A high oligodendroglial tau load in the white matter at the
GM/WM boundary in patients with 4R-tauopathies has
also been reported in larger autopsy studies [16]. Invivo
transfer of this observation to [18F]PI-2620 tau PET signals
in patients with PSP revealed the clinical relevance of this
regional predominance, with higher effect sizes of PET
signals extracted from the GM/WM boundary than from
the whole cortex region (including gray matter and white
matter). This result should guide optimized frontal cortex
target region selection for tau PET analysis in patients with
4R-tauopathies to increase PET sensitivity for cortical tau.
In addition, compared with static imaging, dynamic imaging
has a greater probability of detecting clinically diagnosed
4R-tauopathies invivo [12] [11]. This finding is also sup-
ported by a lack of invivo signals in patients with PSP at
later static imaging windows [51] and a decrease in target
signals with imaging time [45], supporting the preference for
early [46] or dynamic scanning [12] over late imaging win-
dows. Thus, optimized target and reference tissues should
be considered together with dynamic imaging to exploit the
full diagnostic value of [18F]PI-2620 tau PET in patients
with 4R-tauopathies.
In summary, we show that aggregated neuronal and oligo-
dendroglial 4R-tau translates to measurable tau PET signals
in patients with PSP and CBS, whereas astrocytic and axonal
tau inclusions are a minor source of invivo PET signals.
Our novel approach of cell sorting after radiotracer injection
can be readily used to test the cell type specificity of novel
radiotracers with 4R-tau affinity.
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Acta Neuropathologica (2024) 148:70 70 Page 20 of 23
Supplementary Information The online version contains supplemen-
tary material available at https:// doi. org/ 10. 1007/ s00401- 024- 02834-7.
Acknowledgements The authors thank Rosel Oos and Giovanna
Palumbo for providing excellent technical support during small animal
PET imaging. The authors thank the staff of the Department of Nuclear
Medicine and Neurology at the University Hospital LMU Munich. The
authors thank the patients and their families.
Author contributions LS: performed the autoradiography analyses
and interpretation and designed the autoradiography figure panels.
JG: analyzed and interpreted the human PET data and designed the
PET figure panels. SH participated in preclinical PET scan acquisition,
image analysis and interpretation. LMB: performed scRadiotracing,
analyzed the scRadiotracing data, and designed the scRadiotracing
figure panels. CK and LP: performed and interpreted the small animal
immunohistochemistry results and designed the small animal figure
panels. AK, JK-P, and LB processed and analyzed the PET data. STK,
LHK, and AE participated in preclinical PET scan acquisition. SK,
CP, AB, AJ, AZ, FH, TG, and JL performed the clinical evaluation of
all included patients and recruited patients for imaging and autopsy
samples. GlBic and SS performed MRI acquisition and analyzed MRI
data. GBis, TvE, AD, OS, and HB interpreted the PET data and pro-
vided a radiotracer supply. GR, LB, MW, JH, and SNR-C performed
the autopsies and definite diagnoses; provided and analyzed the brain
sections of the patients; and analyzed the autoradiography data. GUH,
SNR-C, NF, and MB were responsible for the study conception and
design; contributed to the interpretation of the data; and enhanced the
intellectual content of the manuscript. All the authors contributed intel-
lectual content and revised the manuscript. MB wrote the first draft of
the manuscript with the input of all the coauthors.
Funding Open Access funding enabled and organized by Projekt
DEAL. SK, CP, JL, JH, GUH, NF, and MB were funded by the
Deutsche Forschungsgemeinschaft (DFG) under Germany’s Excel-
lence Strategy within the framework of the Munich Cluster for Systems
Neurology (EXC 2145 SyNergy, ID 390857198). GUH was funded
by the German Federal Ministry of Education and Research (BMBF,
01EK1605A HitTau). J.L., S.K., and C.P. received research funding
from Lüneburg Heritage. C.P. received funding from Thiemann Stif-
tung and Friedrich–Baur–Stiftung.
Data availability All the data needed to evaluate the conclusions in
Figs.1–7 are presented in the paper and/or the Supplementary Materi-
als. Imaging data will be shared in DICOM format upon reasonable
request to the corresponding author.
Declarations
Conflict of interest MB is a member of the Neuroimaging Committee
of the EANM. MB has received speaker honoraria from Roche, GE
Healthcare, and Life Molecular Imaging; has advised Life Molecular
Imaging; and is currently on the advisory board of MIAC. NF received
speaker honoraria from Eisai and Life Molecular Imaging and consult-
ing honoraria from MSD. CP and JL are inventors in the patent “Oral
Phenylbutyrate for Treatment of Human 4-Repeat Tauopathies” (EP
23 156 122.6) filed by LMU Munich. JL reports speaker fees from
Bayer Vital, Biogen and Roche; consulting fees from Axon Neurosci-
ence and Biogen; author fees from Thieme Medical Publishers and W.
Kohlhammer GmbH Medical Publishers; nonfinancial support from
AbbVie; and compensation for duty as part-time CMO from MODAG,
all outside the submitted work. TvE reports speaker/consultant fees
from Eli Lilly, Shire, H. Lundbeck A/S, and Orion Corporation, and
author fees from Thieme Medical Publishers, all without conflicts of
interest with regard to the submitted work. Gesine Respondek has been
a full-time employee at Roche Pharmaceuticals since July 2021 and
has consulted for UCB, all outside of the submitted work. AZ reports
speaker fees and research support from Dr. Willmar Schwabe GmbH
and author fees from Thieme Medical Publishers, Springer Medical
Publishers and W. Kohlhammer GmbH Medical Publishers. In addi-
tion to the submitted work, TG received consulting fees from AbbVie,
Alector, Anavex, Biogen, BMS, Cogthera, Eli Lilly, Functional Neuro-
modulation, Grifols, Iqvia, Janssen, Noselab, Novo Nordisk, NuiCare,
Orphanzyme, Roche Diagnostics, Roche Pharma, UCB, and Vivoryon;
lecture fees from Biogen, Eisai, Grifols, Medical Tribune, Novo Nord-
isk, Roche Pharma, Schwabe, and Synlab; and grants to his institution
from Biogen, Eisai, and Roche Diagnostics. LB is a Novartis Pharma
GmbH employee, unrelated to this work. All the other authors declare
that no conflicts of interest exist.
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Authors and Aliations
LunaSlemann1· JohannesGnörich1,2· SelinaHummel1· LauraM.Bartos1· CarolinKlaus2· AgnesKling1·
JuliaKusche‑Palenga1· SebastianT.Kunte1· LeaH.Kunze1· AmelieL.Englert1· YunleiLi1· LetiziaVogler1·
SabrinaKatzdobler2,3,4· CarlaPalleis2,3,4· AlexanderBernhardt2,3· AlexanderJäck2,3· AndreasZwergal3,5·
FranziskaHopfner3· SebastianN.Roemer‑Cassiano3,15· GloriaBiechele6· SophiaStöcklein6· GerardBischof7,8·
ThilovanEimeren7,8,9,10· AlexanderDrzezga8,10· OsamaSabri11· HenrykBarthel11· GesineRespondek12·
TimoGrimmer13· JohannesLevin2,3,4· JochenHerms2,4,14· LarsPaeger2· MarieWillroider1· LeonieBeyer1·
GünterU.Höglinger2,3,4· SigrunRoeber14· NicolaiFranzmeier4,15,16· MatthiasBrendel1,2,4
* Matthias Brendel
matthias.brendel@med.uni-muenchen.de
1 Department ofNuclear Medicine, LMU Hospital, Ludwig
Maximilian University ofMunich, Marchioninstraße 15,
81377Munich, Germany
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Acta Neuropathologica (2024) 148:70 Page 23 of 23 70
2 German Center forNeurodegenerative Diseases (DZNE)
Munich, Munich, Germany
3 Department ofNeurology, LMU Hospital, Ludwig
Maximilian University ofMunich, Munich, Germany
4 Munich Cluster forSystems Neurology (SyNergy), Munich,
Germany
5 German Center forVertigo andBalance Disorders, DSGZ,
LMU Hospital, Ludwig Maximilian University ofMunich,
Munich, Germany
6 Department ofRadiology, LMU Hospital, Ludwig
Maximilian University ofMunich, Munich, Germany
7 Cognitive Neuroscience, Institute forNeuroscience
andMedicine (INM-3), Research Centre Juelich, Juelich,
Germany
8 Department ofNuclear Medicine, University Hospital
Cologne, Cologne, Germany
9 Department ofNeurology, University Hospital Cologne,
Cologne, Germany
10 German Center forNeurodegenerative Diseases (DZNE),
Bonn, Germany
11 Department ofNuclear Medicine, University Hospital
Leipzig, Leipzig, Germany
12 Department ofNeurology, Medizinische Hochschule
Hannover, Hannover, Germany
13 Center forCognitive Disorders, Department ofPsychiatry
andPsychotherapy, School ofMedicine andHealth,
Technical University ofMunich, Klinikum rechts der Isar,
Munich, Germany
14 Center ofNeuropathology andPrion Research, Faculty
ofMedicine, LMU Munich, Munich, Germany
15 Institute forStroke andDementia Research, LMU Hospital,
LMU Munich, Munich, Germany
16 Institute ofNeuroscience andPhysiology, Department
ofPsychiatry andNeurochemistry, , University
ofGothenburg, The Sahlgrenska Academy, Mölndal,
Gothenburg, Sweden
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